International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Monthly

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Monthly

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

The Global Soil Partnership

Science.gov (United States)

Montanarella, Luca

2015-07-01

The Global Soil Partnership (GSP) has been established, following an intensive preparatory work of the Food and Agriculture Organization of the United Nations (FAO) in collaboration with the European Commission (EC), as a voluntary partnership coordinated by the FAO in September 2011 [1]. The GSP is open to all interested stakeholders: Governments (FAO Member States), Universities, Research Organizations, Civil Society Organizations, Industry and private companies. It is a voluntary partnership aiming towards providing a platform for active engagement in sustainable soil management and soil protection at all scales: local, national, regional and global. As a “coalition of the willing” towards soil protection, it attempts to make progress in reversing soil degradation with those partners that have a genuine will of protecting soils for our future generations. It openly aims towards creating an enabling environment, despite the resistance of a minority of national governments, for effective soil protection in the large majority of the countries that are genuinely concerned about the rapid depletion of their limited soil resources.

Assessment of BSRN radiation records for the computation of monthly means

Science.gov (United States)

Roesch, A.; Wild, M.; Ohmura, A.; Dutton, E. G.; Long, C. N.; Zhang, T.

2011-02-01

The integrity of the Baseline Surface Radiation Network (BSRN) radiation monthly averages are assessed by investigating the impact on monthly means due to the frequency of data gaps caused by missing or discarded high time resolution data. The monthly statistics, especially means, are considered to be important and useful values for climate research, model performance evaluations and for assessing the quality of satellite (time- and space-averaged) data products. The study investigates the spread in different algorithms that have been applied for the computation of monthly means from 1-min values. The paper reveals that the computation of monthly means from 1-min observations distinctly depends on the method utilized to account for the missing data. The intra-method difference generally increases with an increasing fraction of missing data. We found that a substantial fraction of the radiation fluxes observed at BSRN sites is either missing or flagged as questionable. The percentage of missing data is 4.4%, 13.0%, and 6.5% for global radiation, direct shortwave radiation, and downwelling longwave radiation, respectively. Most flagged data in the shortwave are due to nighttime instrumental noise and can reasonably be set to zero after correcting for thermal offsets in the daytime data. The study demonstrates that the handling of flagged data clearly impacts on monthly mean estimates obtained with different methods. We showed that the spread of monthly shortwave fluxes is generally clearly higher than for downwelling longwave radiation. Overall, BSRN observations provide sufficient accuracy and completeness for reliable estimates of monthly mean values. However, the value of future data could be further increased by reducing the frequency of data gaps and the number of outliers. It is shown that two independent methods for accounting for the diurnal and seasonal variations in the missing data permit consistent monthly means to within less than 1 W m-2 in most cases

SoilGrids1km — Global Soil Information Based on Automated Mapping

Science.gov (United States)

Hengl, Tomislav; de Jesus, Jorge Mendes; MacMillan, Robert A.; Batjes, Niels H.; Heuvelink, Gerard B. M.; Ribeiro, Eloi; Samuel-Rosa, Alessandro; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Gonzalez, Maria Ruiperez

2014-01-01

Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the Soil

SoilGrids1km— global soil information based on automated mapping

NARCIS (Netherlands)

Hengl, T.; Mendes de Jesus, J.S.; Macmillan, R.A.; Batjes, N.H.; Heuvelink, G.B.M.; Carvalho Ribeiro, E.D.; Samuel Rosa, A.; Kempen, B.; Leenaars, J.G.B.; Walsh, M.G.; Ruiperez Gonzalez, M.

2014-01-01

Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited

Soil Carbon Chemistry and Greenhouse Gas Production in Global Peatlands

Science.gov (United States)

Normand, A. E.; Turner, B. L.; Lamit, L. J.; Smith, A. N.; Baiser, B.; Clark, M. W.; Hazlett, C.; Lilleskov, E.; Long, J.; Grover, S.; Reddy, K. R.

2017-12-01

Peatlands play a critical role in the global carbon cycle because they contain approximately 30% of the 1500 Pg of carbon stored in soils worldwide. However, the stability of these vast stores of carbon is under threat from climate and land-use change, with important consequences for global climate. Ecosystem models predict the impact of peatland perturbation on carbon fluxes based on total soil carbon pools, but responses could vary markedly depending on the chemical composition of soil organic matter. Here we combine experimental and observational studies to quantify the chemical nature and response to perturbation of soil organic matter in peatlands worldwide. We quantified carbon functional groups in a global sample of 125 freshwater peatlands using solid-state 13C nuclear magnetic resonance (NMR) spectroscopy to determine the drivers of molecular composition of soil organic matter. We then incubated a representative subset of the soils under aerobic and anaerobic conditions to determine how organic matter composition influences carbon dioxide (CO2) and methane (CH4) emissions following drainage or flooding. The functional chemistry of peat varied markedly at large and small spatial scales, due to long-term land use change, mean annual temperature, nutrient status, and vegetation, but not pH. Despite this variation, we found predictable responses of greenhouse gas production following drainage based on soil carbon chemistry, defined by a novel Global Peat Stability Index, with greater CO2 and CH4 fluxes from soils enriched in oxygen-containing organic carbon (O-alkyl C) and depleted in aromatic and hydrophobic compounds. Incorporation of the Global Peat Stability Index of peatland organic matter into earth system models and management strategies, which will improve estimates of GHG fluxes from peatlands and ultimately advance management to reduce carbon loss from these sensitive ecosystems.

The global Minmax k-means algorithm.

Science.gov (United States)

Wang, Xiaoyan; Bai, Yanping

2016-01-01

The global k -means algorithm is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure from suitable initial positions, and employs k -means to minimize the sum of the intra-cluster variances. However the global k -means algorithm sometimes results singleton clusters and the initial positions sometimes are bad, after a bad initialization, poor local optimal can be easily obtained by k -means algorithm. In this paper, we modified the global k -means algorithm to eliminate the singleton clusters at first, and then we apply MinMax k -means clustering error method to global k -means algorithm to overcome the effect of bad initialization, proposed the global Minmax k -means algorithm. The proposed clustering method is tested on some popular data sets and compared to the k -means algorithm, the global k -means algorithm and the MinMax k -means algorithm. The experiment results show our proposed algorithm outperforms other algorithms mentioned in the paper.

Development of Global Soil Information Facilities

Directory of Open Access Journals (Sweden)

N H Batjes

2013-02-01

Full Text Available ISRIC - World Soil Information has a mandate to serve the international community as custodian of global soil information and to increase awareness and understanding of the role of soils in major global issues. To adapt to the current demand for soil information, ISRIC is updating its enterprise data management system, including procedures for registering acquired data, such as lineage, versioning, quality assessment, and control. Data can be submitted, queried, and analysed using a growing range of web-based services - ultimately aiming at full and open exchange of data, metadata, and products - through the ICSU-accredited World Data Centre for Soils.

Prediction of monthly average global solar radiation based on statistical distribution of clearness index

International Nuclear Information System (INIS)

Ayodele, T.R.; Ogunjuyigbe, A.S.O.

2015-01-01

In this paper, probability distribution of clearness index is proposed for the prediction of global solar radiation. First, the clearness index is obtained from the past data of global solar radiation, then, the parameters of the appropriate distribution that best fit the clearness index are determined. The global solar radiation is thereafter predicted from the clearness index using inverse transformation of the cumulative distribution function. To validate the proposed method, eight years global solar radiation data (2000–2007) of Ibadan, Nigeria are used to determine the parameters of appropriate probability distribution for clearness index. The calculated parameters are then used to predict the future monthly average global solar radiation for the following year (2008). The predicted values are compared with the measured values using four statistical tests: the Root Mean Square Error (RMSE), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error) and the coefficient of determination (R"2). The proposed method is also compared to the existing regression models. The results show that logistic distribution provides the best fit for clearness index of Ibadan and the proposed method is effective in predicting the monthly average global solar radiation with overall RMSE of 0.383 MJ/m"2/day, MAE of 0.295 MJ/m"2/day, MAPE of 2% and R"2 of 0.967. - Highlights: • Distribution of clearnes index is proposed for prediction of global solar radiation. • The clearness index is obtained from the past data of global solar radiation. • The parameters of distribution that best fit the clearness index are determined. • Solar radiation is predicted from the clearness index using inverse transformation. • The method is effective in predicting the monthly average global solar radiation.

Soils - Mean Permeability

Data.gov (United States)

Kansas Data Access and Support Center — This digital spatial data set provides information on the magnitude and spatial pattern of depth-weighted, mean soil permeability throughout the State of Kansas. The...

July: "Soils are living: Overview of soil biodiversity, global issues, and new resources"

Science.gov (United States)

The July poster will provide an overview of soil biology and the many ecosystem functions that soil organisms drive including their impact on global biodiversity, climate regulation, soil health/stability, and plant growth. Five main global issues related to soil biodiversity will be presented such ...

Global warming without global mean precipitation increase?

Science.gov (United States)

Salzmann, Marc

2016-06-01

Global climate models simulate a robust increase of global mean precipitation of about 1.5 to 2% per kelvin surface warming in response to greenhouse gas (GHG) forcing. Here, it is shown that the sensitivity to aerosol cooling is robust as well, albeit roughly twice as large. This larger sensitivity is consistent with energy budget arguments. At the same time, it is still considerably lower than the 6.5 to 7% K(-1) decrease of the water vapor concentration with cooling from anthropogenic aerosol because the water vapor radiative feedback lowers the hydrological sensitivity to anthropogenic forcings. When GHG and aerosol forcings are combined, the climate models with a realistic 20th century warming indicate that the global mean precipitation increase due to GHG warming has, until recently, been completely masked by aerosol drying. This explains the apparent lack of sensitivity of the global mean precipitation to the net global warming recently found in observations. As the importance of GHG warming increases in the future, a clear signal will emerge.

Soil fungal community responses to global changes

DEFF Research Database (Denmark)

Haugwitz, Merian Skouw

Global change will affect the functioning and structure of terrestrial ecosystems and since soil fungi are key players in organic matter decomposition and nutrient turnover, shifts in fungal community composition might have a strong impact on soil functioning. The main focus of this thesis...... was therefore to investigate the impact of global environmental changes on soil fungal communities in a temperate and subartic heath ecosystem. The objective was further to determine global change effects on major functional groups of fungi and analyze the influence of fungal community changes on soil carbon...... and nutrient availability and storage. By combining molecular methods such as 454 pyrosequencing and quantitative PCR of fungal ITS amplicons with analyses of soil enzymes, nutrient pools of carbon, nitrogen and phosphorus we were able to characterize soil fungal communities as well as their impact on nutrient...

Soil data clustering by using K-means and fuzzy K-means algorithm

Directory of Open Access Journals (Sweden)

E. Hot

2016-06-01

Full Text Available A problem of soil clustering based on the chemical characteristics of soil, and proper visual representation of the obtained results, is analysed in the paper. To that aim, K-means and fuzzy K-means algorithms are adapted for soil data clustering. A database of soil characteristics sampled in Montenegro is used for a comparative analysis of implemented algorithms. The procedure of setting proper values for control parameters of fuzzy K-means is illustrated on the used database. In addition, validation of clustering is made through visualisation. Classified soil data are presented on the static Google map and dynamic Open Street Map.

A global predictive model of carbon in mangrove soils

Science.gov (United States)

Jardine, Sunny L.; Siikamäki, Juha V.

2014-10-01

Mangroves are among the most threatened and rapidly vanishing natural environments worldwide. They provide a wide range of ecosystem services and have recently become known for their exceptional capacity to store carbon. Research shows that mangrove conservation may be a low-cost means of reducing CO2 emissions. Accordingly, there is growing interest in developing market mechanisms to credit mangrove conservation projects for associated CO2 emissions reductions. These efforts depend on robust and readily applicable, but currently unavailable, localized estimates of soil carbon. Here, we use over 900 soil carbon measurements, collected in 28 countries by 61 independent studies, to develop a global predictive model for mangrove soil carbon. Using climatological and locational data as predictors, we explore several predictive modeling alternatives, including machine-learning methods. With our predictive model, we construct a global dataset of estimated soil carbon concentrations and stocks on a high-resolution grid (5 arc min). We estimate that the global mangrove soil carbon stock is 5.00 ± 0.94 Pg C (assuming a 1 meter soil depth) and find this stock is highly variable over space. The amount of carbon per hectare in the world’s most carbon-rich mangroves (approximately 703 ± 38 Mg C ha-1) is roughly a 2.6 ± 0.14 times the amount of carbon per hectare in the world’s most carbon-poor mangroves (approximately 272 ± 49 Mg C ha-1). Considerable within country variation in mangrove soil carbon also exists. In Indonesia, the country with the largest mangrove soil carbon stock, we estimate that the most carbon-rich mangroves contain 1.5 ± 0.12 times as much carbon per hectare as the most carbon-poor mangroves. Our results can aid in evaluating benefits from mangrove conservation and designing mangrove conservation policy. Additionally, the results can be used to project changes in mangrove soil carbon stocks based on changing climatological predictors, e.g. to

Global Change Effects on Plant-Soil Interactions

DEFF Research Database (Denmark)

Dam, Marie

of this dissertation has been to determine how soil food web structure and function is affected when the quantity and quality of plant input is altered under global change. By studying the abundance and composition of soil organisms, particularly those in the rhizosphere, closely associated with living plants, we...... (Paper III). Furthermore, by way of meta-analysis, the role of organisms in global change effects on ecosystem function is modelled (Paper IV). Among CO2, warming and summer drought, CO2 is the factor most consistently impacting soil organisms. CO2 increases abundance of microorganisms and nematodes...... suggest that not only the global change effects on established ecosystems, but also the global change effects on plant community composition as well as land use management may determine the composition and function of soil food webs in the future....

Causes of global mean surface temperature slowdowns, trends and variations from months to a century, 1891-2015

Science.gov (United States)

Folland, C. K.; Boucher, O.; Colman, A.; Parker, D. E.

2017-12-01

The recent slowdown in the warming of global mean surface temperature (GST) has highlighted the influences of natural variability. This talk discusses reconstructions of the variations of GST down to the monthly time scale since 1891 using monthly forcing data. We show that most of the variations in annual, and to some extent sub-annual, GST since 1891 can be reproduced skillfully from known forcing factors external and internal to the climate system. This includes the slowdown in warming over about 1998-2013 where reconstruction skill is particularly high down to the multi-monthly time scale. The relative contributions of the several key forcing factors to GST continually vary, but most of the net warming since 1891 is reconstructed to be attributable to the net forcing due to increasing greenhouse gases and anthropogenic aerosols. Separate analyses are carried out for three periods of GST slowdown:- 1896-1910, 1941-1976, together with 1998-2013 and some of its sub periods. We also study two periods where strong warming occurred, 1911-1940 and 1977-1997. Comparisons are made with the skill of average GST provided by 40 CMIP5 models. In the recent 1998-2013 slowdown, TSI forcing appears to have caused significant cooling, particularly over 2001-2010. This is additional to well documented cooling effects of an increased frequency of La Nina events, a negative Interdecadal Pacific Oscillation and some increases in volcanic forcing. Although there are short-term features of the GST curve since 1891 that cannot be fully explained, the most serious disagreements between the reconstructions and observations occur in the Second World War, especially in 1944-1945. Here observed near worldwide SSTs may be biased significantly too warm. Despite this, our generally high reconstruction skill is consistent with a good understanding of the multiple causes of observed GST variations and the general veracity of the GST record since 1891.

GlobalSoilMap and Global Carbon Predictions

DEFF Research Database (Denmark)

Hempel, Jonathan; McBratney, Alex B.; Arrouays, Dominique

consistently produced soil property information at 100 m resolution across the world. This information will aid in solving some of the key environment and societal issues of the day, including food security, global climate change land degradation and carbon sequestration. Data would be produced using mostly...... the storehouse of existing legacy soils data along with geographic information and a range of covariates. A range of modeling techniques is used dependant on the complexity of the background soil survey information. The key soil properties that would be most useful to the modeling community and other users are...... of soil property values throughout the depth of each profile. Maps have been produced at the country level in the Australia, Canada, Denmark, Nigeria, South Korea and the US and work is on-going in many other parts of the world....

Global characterization of surface soil moisture drydowns

Science.gov (United States)

McColl, Kaighin A.; Wang, Wei; Peng, Bin; Akbar, Ruzbeh; Short Gianotti, Daniel J.; Lu, Hui; Pan, Ming; Entekhabi, Dara

2017-04-01

Loss terms in the land water budget (including drainage, runoff, and evapotranspiration) are encoded in the shape of soil moisture "drydowns": the soil moisture time series directly following a precipitation event, during which the infiltration input is zero. The rate at which drydowns occur—here characterized by the exponential decay time scale τ—is directly related to the shape of the loss function and is a key characteristic of global weather and climate models. In this study, we use 1 year of surface soil moisture observations from NASA's Soil Moisture Active Passive mission to characterize τ globally. Consistent with physical reasoning, the observations show that τ is lower in regions with sandier soils, and in regions that are more arid. To our knowledge, these are the first global estimates of τ—based on observations alone—at scales relevant to weather and climate models.

SoilInfo App: global soil information on your palm

Science.gov (United States)

Hengl, Tomislav; Mendes de Jesus, Jorge

2015-04-01

ISRIC ' World Soil Information has released in 2014 and app for mobile de- vices called 'SoilInfo' (http://soilinfo-app.org) and which aims at providing free access to the global soil data. SoilInfo App (available for Android v.4.0 Ice Cream Sandwhich or higher, and Apple v.6.x and v.7.x iOS) currently serves the Soil- Grids1km data ' a stack of soil property and class maps at six standard depths at a resolution of 1 km (30 arc second) predicted using automated geostatistical mapping and global soil data models. The list of served soil data includes: soil organic carbon (), soil pH, sand, silt and clay fractions (%), bulk density (kg/m3), cation exchange capacity of the fine earth fraction (cmol+/kg), coarse fragments (%), World Reference Base soil groups, and USDA Soil Taxonomy suborders (DOI: 10.1371/journal.pone.0105992). New soil properties and classes will be continuously added to the system. SoilGrids1km are available for download under a Creative Commons non-commercial license via http://soilgrids.org. They are also accessible via a Representational State Transfer API (http://rest.soilgrids.org) service. SoilInfo App mimics common weather apps, but is also largely inspired by the crowdsourcing systems such as the OpenStreetMap, Geo-wiki and similar. Two development aspects of the SoilInfo App and SoilGrids are constantly being worked on: Data quality in terms of accuracy of spatial predictions and derived information, and Data usability in terms of ease of access and ease of use (i.e. flexibility of the cyberinfrastructure / functionalities such as the REST SoilGrids API, SoilInfo App etc). The development focus in 2015 is on improving the thematic and spatial accuracy of SoilGrids predictions, primarily by using finer resolution covariates (250 m) and machine learning algorithms (such as random forests) to improve spatial predictions.

A global predictive model of carbon in mangrove soils

International Nuclear Information System (INIS)

Jardine, Sunny L; Siikamäki, Juha V

2014-01-01

Mangroves are among the most threatened and rapidly vanishing natural environments worldwide. They provide a wide range of ecosystem services and have recently become known for their exceptional capacity to store carbon. Research shows that mangrove conservation may be a low-cost means of reducing CO 2 emissions. Accordingly, there is growing interest in developing market mechanisms to credit mangrove conservation projects for associated CO 2 emissions reductions. These efforts depend on robust and readily applicable, but currently unavailable, localized estimates of soil carbon. Here, we use over 900 soil carbon measurements, collected in 28 countries by 61 independent studies, to develop a global predictive model for mangrove soil carbon. Using climatological and locational data as predictors, we explore several predictive modeling alternatives, including machine-learning methods. With our predictive model, we construct a global dataset of estimated soil carbon concentrations and stocks on a high-resolution grid (5 arc min). We estimate that the global mangrove soil carbon stock is 5.00 ± 0.94 Pg C (assuming a 1 meter soil depth) and find this stock is highly variable over space. The amount of carbon per hectare in the world’s most carbon-rich mangroves (approximately 703 ± 38 Mg C ha −1 ) is roughly a 2.6 ± 0.14 times the amount of carbon per hectare in the world’s most carbon-poor mangroves (approximately 272 ± 49 Mg C ha −1 ). Considerable within country variation in mangrove soil carbon also exists. In Indonesia, the country with the largest mangrove soil carbon stock, we estimate that the most carbon-rich mangroves contain 1.5 ± 0.12 times as much carbon per hectare as the most carbon-poor mangroves. Our results can aid in evaluating benefits from mangrove conservation and designing mangrove conservation policy. Additionally, the results can be used to project changes in mangrove soil carbon stocks based on changing climatological

Divergent surface and total soil moisture projections under global warming

Science.gov (United States)

Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.

2017-01-01

Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

Historic and future increase in the global land area affected by monthly heat extremes

International Nuclear Information System (INIS)

Coumou, Dim; Robinson, Alexander

2013-01-01

Climatic warming of about 0.5 ° C in the global mean since the 1970s has strongly increased the occurrence-probability of heat extremes on monthly to seasonal time scales. For the 21st century, climate models predict more substantial warming. Here we show that the multi-model mean of the CMIP5 (Coupled Model Intercomparison Project) climate models accurately reproduces the evolution over time and spatial patterns of the historically observed increase in monthly heat extremes. For the near-term (i.e., by 2040), the models predict a robust, several-fold increase in the frequency of such heat extremes, irrespective of the emission scenario. However, mitigation can strongly reduce the number of heat extremes by the second half of the 21st century. Unmitigated climate change causes most (>50%) continental regions to move to a new climatic regime with the coldest summer months by the end of the century substantially hotter than the hottest experienced today. We show that the land fraction experiencing extreme heat as a function of global mean temperature follows a simple cumulative distribution function, which depends only on natural variability and the level of spatial heterogeneity in the warming. (letter)

Historic and future increase in the global land area affected by monthly heat extremes

NARCIS (Netherlands)

Coumou, Dim; Robinson, Alexander

2013-01-01

Climatic warming of about 0.5 ° C in the global mean since the 1970s has strongly increased the occurrence-probability of heat extremes on monthly to seasonal time scales. For the 21st century, climate models predict more substantial warming. Here we show that the multi-model mean of the CMIP5

Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems

Science.gov (United States)

Wang, G.

2017-12-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

Critical carbon input to maintain current soil organic carbon stocks in global wheat systems.

Science.gov (United States)

Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing

2016-01-13

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha(-1) yr(-1), with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

Monthly, global emissions of carbon dioxide from fossil fuel consumption

Energy Technology Data Exchange (ETDEWEB)

Andres, R. J.; Marland, G.; Boden, T. A. (Environmental Sciences Div., Oak Ridge National Laboratory, Oak Ridge, TN (United States)), e-mail: andresrj@ornl.gov; Gregg, J. S. (Risoe DTU National Laboratory for Sustainable Energy, Roskilde (Denmark)); Losey, L. (Dept. of Space Studies, Univ. of North Dakota, Grand Forks, ND (United States))

2011-07-15

This paper examines available data, develops a strategy and presents a monthly, global time series of fossil-fuel carbon dioxide emissions for the years 1950-2006. This monthly time series was constructed from detailed study of monthly data from the 21 countries that account for approximately 80% of global total emissions. These data were then used in a Monte Carlo approach to proxy for all remaining countries. The proportional-proxy methodology estimates by fuel group the fraction of annual emissions emitted in each country and month. Emissions from solid, liquid and gas fuels are explicitly modelled by the proportional-proxy method. The primary conclusion from this study is the global monthly time series is statistically significantly different from a uniform distribution throughout the year. Uncertainty analysis of the data presented show that the proportional-proxy method used faithfully reproduces monthly patterns in the data and the global monthly pattern of emissions is relatively insensitive to the exact proxy assignments used. The data and results presented here should lead to a better understanding of global and regional carbon cycles, especially when the mass data are combined with the stable carbon isotope data in atmospheric transport models

Progress towards GlobalSoilMap.net soil database of Denmark

DEFF Research Database (Denmark)

Adhikari, Kabindra; Bou Kheir, Rania; Greve, Mogens Humlekrog

2012-01-01

Denmark is an agriculture-based country where intensive mechanized cultivation has been practiced continuously for years leading to serious threats to the soils. Proper use and management of Danish soil resources, modeling and soil research activities need very detailed soil information. This study...... presents recent advancements in Digital Soil Mapping (DSM) activities in Denmark with an example of soil clay mapping using regression-based DSM techniques. Several environmental covariates were used to build regression rules and national scale soil prediction was made at 30 m resolution. Spatial...... content mapping, the plans for future soil mapping activities in support to GlobalSoilMap.net project initiatives are also included in this paper. Our study thought to enrich and update Danish soil database and Soil information system with new fine resolution soil property maps....

Soil organic matter dynamics and the global carbon cycle

International Nuclear Information System (INIS)

Post, W.M.; Emanuel, W.R.; King, A.W.

1992-01-01

The large size and potentially long residence time of the soil organic matter pool make it an important component of the global carbon cycle. Net terrestrial primary production of about 60 Pg C·yr -1 is, over a several-year period of time, balanced by an equivalent flux of litter production and subsequent decomposition of detritus and soil organic matter. We will review many of the major factors that influence soil organic matter dynamics that need to be explicitly considered in development of global estimates of carbon turnover in the world's soils. We will also discuss current decomposition models that are general enough to be used to develop a representation of global soil organic matter dynamics

Remediation of grey forest soils heavily polluted with heavy metals by means of their leaching at acidic pH followed by the soil reclamation by means of neutralization and bacterial manure addition

Science.gov (United States)

Georgiev, Plamen; Groudev, Stoyan; Spasova, Irena; Nicolova, Marina

2014-05-01

Some grey forest soils in Western Bulgaria are heavily polluted with heavy metals (copper, lead, and zinc), arsenic, and uranium due to the infiltration of acid mine drainage generated at the abandoned uranium mine Curilo. This paper presents some results from a study about soil remediation based on the contaminants leaching from the topsoil by means of irrigation with solutions containing sulphuric acid or its in situ generation by means of sulphur-oxidizing chemolithotrophic bacteria in or without the presence of finely cut straw. These methods were tested in large scale zero suction lysimeters. The approaches based on S° and finely cut straw addition was the most efficient amongst the tested methods and for seven months of soil remediation the concentration of all soil contaminants were decreased below the relevant Maximum Admissible Concentration (MAC). Neutralization of the soil acidity was applied as a next stage of soil reclamation by adding CaCO3 and cow manure. As a result, soil pH increased from strongly acidic (2.36) to slightly acidic (6.15) which allowed subsequent addition of humic acids and bacterial manure to the topsoil. The soil habitat changed in this way facilitated the growth of microorganisms which restored the biogeochemical cycles of nitrogen and carbon to the levels typical for non-polluted grey forest soil.

Soil salinity decreases global soil organic carbon stocks.

Science.gov (United States)

Setia, Raj; Gottschalk, Pia; Smith, Pete; Marschner, Petra; Baldock, Jeff; Setia, Deepika; Smith, Jo

2013-11-01

Saline soils cover 3.1% (397 million hectare) of the total land area of the world. The stock of soil organic carbon (SOC) reflects the balance between carbon (C) inputs from plants, and losses through decomposition, leaching and erosion. Soil salinity decreases plant productivity and hence C inputs to the soil, but also microbial activity and therefore SOC decomposition rates. Using a modified Rothamsted Carbon model (RothC) with a newly introduced salinity decomposition rate modifier and a plant input modifier we estimate that, historically, world soils that are currently saline have lost an average of 3.47 tSOC ha(-1) since they became saline. With the extent of saline soils predicted to increase in the future, our modelling suggests that world soils may lose 6.8 Pg SOC due to salinity by the year 2100. Our findings suggest that current models overestimate future global SOC stocks and underestimate net CO2 emissions from the soil-plant system by not taking salinity effects into account. From the perspective of enhancing soil C stocks, however, given the lower SOC decomposition rate in saline soils, salt tolerant plants could be used to sequester C in salt-affected areas. Copyright © 2012 Elsevier B.V. All rights reserved.

Global distribution of mean age of stratospheric air from MIPAS SF6 measurements

Directory of Open Access Journals (Sweden)

H. Fischer

2008-02-01

Full Text Available Global distributions of profiles of sulphur hexafluoride (SF6 have been retrieved from limb emission spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS on Envisat covering the period September 2002 to March 2004. Individual SF6 profiles have a precision of 0.5 pptv below 25 km altitude and a vertical resolution of 4–6 km up to 35 km altitude. These data have been validated versus in situ observations obtained during balloon flights of a cryogenic whole-air sampler. For the tropical troposphere a trend of 0.230±0.008 pptv/yr has been derived from the MIPAS data, which is in excellent agreement with the trend from ground-based flask and in situ measurements from the National Oceanic and Atmospheric Administration Earth System Research Laboratory, Global Monitoring Division. For the data set currently available, based on at least three days of data per month, monthly 5° latitude mean values have a 1σ standard error of 1%. From the global SF6 distributions, global daily and monthly distributions of the apparent mean age of air are inferred by application of the tropical tropospheric trend derived from MIPAS data. The inferred mean ages are provided for the full globe up to 90° N/S, and have a 1σ standard error of 0.25 yr. They range between 0 (near the tropical tropopause and 7 years (except for situations of mesospheric intrusions and agree well with earlier observations. The seasonal variation of the mean age of stratospheric air indicates episodes of severe intrusion of mesospheric air during each Northern and Southern polar winter observed, long-lasting remnants of old, subsided polar winter air over the spring and summer poles, and a rather short period of mixing with midlatitude air and/or upward transport during fall in October/November (NH and April/May (SH, respectively, with small latitudinal gradients, immediately before the new polar vortex starts to form. The mean age distributions further

Soil Response to Global Change: Soil Process Domains and Pedogenic Thresholds (Invited)

Science.gov (United States)

Chadwick, O.; Kramer, M. G.; Chorover, J.

2013-12-01

The capacity of soil to withstand perturbations, whether driven by climate, land use change, or spread of invasive species, depends on its chemical composition and physical state. The dynamic interplay between stable, well buffered soil process domains and thresholds in soil state and function is a strong determinant of soil response to forcing from global change. In terrestrial ecosystems, edaphic responses are often mediated by availability of water and its flux into and through soils. Water influences soil processes in several ways: it supports biological production, hence proton-donor, electron-donor and complexing-ligand production; it determines the advective removal of dissolution products, and it can promote anoxia that leads microorganisms to utilize alternative electron acceptors. As a consequence climate patterns strongly influence global distribution of soil, although within region variability is governed by other factors such as landscape age, parent material and human land use. By contrast, soil properties can vary greatly among climate regions, variation which is guided by the functioning of a suite of chemical processes that tend to maintain chemical status quo. This soil 'buffering' involves acid-base reactions as minerals weather and oxidation-reduction reactions that are driven by microbial respiration. At the planetary scale, soil pH provides a reasonable indicator of process domains and varies from about 3.5 to10, globally, although most soils lie between about 4.5 and 8.5. Those that are above 7.5 are strongly buffered by the carbonate system, those that are characterized by neutral pH (7.5-6) are buffered by release of non-hydrolyzing cations from primary minerals and colloid surfaces, and those that are buffered by hydrolytic aluminum on colloidal surfaces. Alkali and alkaline (with the exception of limestone parent material) soils are usually associated with arid and semiarid conditions, neutral pH soils with young soils in both dry and wet

Engineering Global Soils to Sustain Planet Earth

OpenAIRE

Banwart, Steven A.; Menon, Manoj

2014-01-01

Global soils are under intense pressure from the demographic drivers of increasing human population and\\ud wealth. During the next 40 years Earth’s human population is project to approach 10 billion with a quadrupling\\ud in the global economy, a doubling in the demand for food, a doubling in the demand for fuel, and a more than\\ud 50% increase in the demand for clean water. Can Earth’s soils keep up?

An analysis of prediction skill of monthly mean climate variability

Energy Technology Data Exchange (ETDEWEB)

Kumar, Arun; Chen, Mingyue; Wang, Wanqiu [Climate Prediction Center, National Centers for Environmental Prediction (CPC/NCEP), Camp Springs, MD (United States)

2011-09-15

In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30-40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability. (orig.)

Soil bacterial community responses to global changes

DEFF Research Database (Denmark)

Bergmark, Lasse

competing and very contrasting plant types (Calluna and Deschampsia) dominated the vegetation. This led to Manuscript 3 where the impact and responses of the climate change manipulations on the microbial community composition was investigated under the contrasting vegetation types. Our results show a high......Soil bacteria and archaea are essential for ecosystem functioning and plant growth through their degradation of organic matter and turnover of nutrients. But since the majority of soil bacteria and archaea are unclassified and “nonculturable” the functionality of the microbial community and its...... overall importance for ecosystem function in soil is poorly understood. Global change factors may affect the diversity and functioning of soil prokaryotes and thereby ecosystem functioning. To gain a better understanding of the effects of global changes it is of fundamental importance to classify...

Global monthly water stress: II. Water demand and severity of water

NARCIS (Netherlands)

Wada, Y.; Beek, L.P.H. van; Viviroli, D.; Dürr, H.H.; Weingartner, R.; Bierkens, M.F.P.

2011-01-01

This paper assesses global water stress at a finer temporal scale compared to conventional assessments. To calculate time series of global water stress at a monthly time scale, global water availability, as obtained from simulations of monthly river discharge from the companion paper, is confronted

Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

Science.gov (United States)

Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan

2003-12-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 μmol m-2 s-1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to

Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

Science.gov (United States)

Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team

2003-04-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, inter-annual and spatial variability of soil respiration as affected by water availability, temperature and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g. leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical non-linear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and inter-site variability of soil respiration with a mean absolute error of 0.82 µmol m-2 s-1. The parameterised model exhibits the following principal properties: 1) At a relative amount of upper-layer soil water of 16% of field capacity half-maximal soil respiration rates are reached. 2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. 3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly time-scale we employed the approach by Raich et al. (2002, Global Change Biol. 8, 800-812) that used monthly precipitation and air temperature to globally predict soil respiration (T

Global Soil and Sediment transfer during the Anthropocene

Science.gov (United States)

Hoffmann, Thomas; Vanacker, Veerle; Stinchcombe, Gary; Penny, Dan; Xixi, Lu

2016-04-01

The vulnerability of soils to human-induced erosion and its downstream effects on fluvial and deltaic ecosystems is highly variable in space and time; dependent on climate, geology, the nature and duration of land use, and topography. Despite our knowledge of the mechanistic relationships between erosion, sediment storage, land-use and climate change, the global patterns of soil erosion, fluvial sediment flux and storage throughout the Holocene remain poorly understood. The newly launched PAGES working group GloSS aims to determine the sensitivity of soil resources and sediment routing systems to varying land use types during the period of agriculture, under contrasting climate regimes and socio-ecological settings. Successfully addressing these questions in relation to the sustainable use of soils, sediments and river systems requires an understanding of past human-landscape interactions. GloSS, therefore, aims to: Develop proxies for, or indices of, human impact on rates of soil erosion and fluvial sediment transfer that are applicable on a global scale and throughout the Holocene; Create a global database of long-term (102-104 years) human-accelerated soil erosion and sediment flux records; Identify hot spots of soil erosion and sediment deposition during the Anthropocene, and Locate data-poor regions where particular socio-ecological systems are not well understood, as strategic foci for future work. This paper will present the latest progress of the PAGES GloSS working group.

Quantifying global soil carbon losses in response to warming.

Science.gov (United States)

Crowther, T W; Todd-Brown, K E O; Rowe, C W; Wieder, W R; Carey, J C; Machmuller, M B; Snoek, B L; Fang, S; Zhou, G; Allison, S D; Blair, J M; Bridgham, S D; Burton, A J; Carrillo, Y; Reich, P B; Clark, J S; Classen, A T; Dijkstra, F A; Elberling, B; Emmett, B A; Estiarte, M; Frey, S D; Guo, J; Harte, J; Jiang, L; Johnson, B R; Kröel-Dulay, G; Larsen, K S; Laudon, H; Lavallee, J M; Luo, Y; Lupascu, M; Ma, L N; Marhan, S; Michelsen, A; Mohan, J; Niu, S; Pendall, E; Peñuelas, J; Pfeifer-Meister, L; Poll, C; Reinsch, S; Reynolds, L L; Schmidt, I K; Sistla, S; Sokol, N W; Templer, P H; Treseder, K K; Welker, J M; Bradford, M A

2016-11-30

The majority of the Earth's terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12-17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon-climate feedback that could accelerate climate change.

The global distribution and dynamics of surface soil moisture

Science.gov (United States)

McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara

2017-01-01

Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.

Monthly, global emissions of carbon dioxide from fossil fuel consumption

DEFF Research Database (Denmark)

Andres, R.J.; Gregg, Jay Sterling; Losey, L.

2011-01-01

This paper examines available data, develops a strategy and presents a monthly, global time series of fossil-fuel carbon dioxide emissions for the years 1950–2006. This monthly time series was constructed from detailed study of monthly data from the 21 countries that account for approximately 80......% of global total emissions. These data were then used in a Monte Carlo approach to proxy for all remaining countries. The proportional-proxy methodology estimates by fuel group the fraction of annual emissions emitted in each country and month. Emissions from solid, liquid and gas fuels are explicitly...

A global spectral library to characterize the world's soil

DEFF Research Database (Denmark)

A. Viscarra Rossel, Raphael; Behrens, T.; Ben Dor, E.

2016-01-01

to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible–near infrared (vis–NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition...... help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess andmonitor soil at scales ranging fromregional to global.New contributions to the library are encouraged so that this work and our collaboration might progress to develop......Soil provides ecosystemservices, supports human health and habitation, stores carbon and regulatesemissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agroecological balances and food security. It is important that we learn more about soil...

Impact of soil amendment on phytotoxicity of a 5-month old waste ...

African Journals Online (AJOL)

Administrator

seedlings died within 2 weeks; only those seedlings in unpolluted soils survived. Nine months after soil ... poisonous ... soil and were thoroughly mixed, before taken back into each bucket. ... kilograms (3 kg) of soil was removed from each bucket, and replaced ..... could be killed or injured if it comes in contact with crude oil.

GlobalSoilMap France: High-resolution spatial modelling the soils of France up to two meter depth.

Science.gov (United States)

Mulder, V L; Lacoste, M; Richer-de-Forges, A C; Arrouays, D

2016-12-15

This work presents the first GlobalSoilMap (GSM) products for France. We developed an automatic procedure for mapping the primary soil properties (clay, silt, sand, coarse elements, pH, soil organic carbon (SOC), cation exchange capacity (CEC) and soil depth). The procedure employed a data-mining technique and a straightforward method for estimating the 90% confidence intervals (CIs). The most accurate models were obtained for pH, sand and silt. Next, CEC, clay and SOC were found reasonably accurate predicted. Coarse elements and soil depth were the least accurate of all models. Overall, all models were considered robust; important indicators for this were 1) the small difference in model diagnostics between the calibration and cross-validation set, 2) the unbiased mean predictions, 3) the smaller spatial structure of the prediction residuals in comparison to the observations and 4) the similar performance compared to other developed GlobalSoilMap products. Nevertheless, the confidence intervals (CIs) were rather wide for all soil properties. The median predictions became less reliable with increasing depth, as indicated by the increase of CIs with depth. In addition, model accuracy and the corresponding CIs varied depending on the soil variable of interest, soil depth and geographic location. These findings indicated that the CIs are as informative as the model diagnostics. In conclusion, the presented method resulted in reasonably accurate predictions for the majority of the soil properties. End users can employ the products for different purposes, as was demonstrated with some practical examples. The mapping routine is flexible for cloud-computing and provides ample opportunity to be further developed when desired by its users. This allows regional and international GSM partners with fewer resources to develop their own products or, otherwise, to improve the current routine and work together towards a robust high-resolution digital soil map of the world

Mean residence time of kaolinite and smectite-bound organic matter in mozambiquan soils

NARCIS (Netherlands)

Wattel-Koekkoek, E.J.W.; Buurman, P.

2004-01-01

To gain understanding about the process of global warming, it is essential to study the global C cycle. In the global C cycle, soil organic matter (SOM) is a major source and sink of atmospheric C. Turnover times of C in these soil organic compounds vary from hours to thousands of years. Clay

Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

Science.gov (United States)

Koster, R. D.; Walker, G. K.

2015-01-01

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

Substantial proportion of global streamflow less than three months old

Science.gov (United States)

Jasechko, Scott; Kirchner, James W.; Welker, Jeffrey M.; McDonnell, Jeffrey J.

2016-02-01

Biogeochemical cycles, contaminant transport and chemical weathering are regulated by the speed at which precipitation travels through landscapes and reaches streams. Streamflow is a mixture of young and old precipitation, but the global proportions of these young and old components are not known. Here we analyse seasonal cycles of oxygen isotope ratios in rain, snow and streamflow compiled from 254 watersheds around the world, and calculate the fraction of streamflow that is derived from precipitation that fell within the past two or three months. This young streamflow accounts for about a third of global river discharge, and comprises at least 5% of discharge in about 90% of the catchments we investigated. We conclude that, although typical catchments have mean transit times of years or even decades, they nonetheless can rapidly transmit substantial fractions of soluble contaminant inputs to streams. Young streamflow is less prevalent in steeper landscapes, which suggests they are characterized by deeper vertical infiltration. Because young streamflow is derived from less than 0.1% of global groundwater storage, we conclude that this thin veneer of aquifer storage will have a disproportionate influence on stream water quality.

S-World: A high resolution global soil database for simulation modelling (Invited)

Science.gov (United States)

Stoorvogel, J. J.

2013-12-01

There is an increasing call for high resolution soil information at the global level. A good example for such a call is the Global Gridded Crop Model Intercomparison carried out within AgMIP. While local studies can make use of surveying techniques to collect additional techniques this is practically impossible at the global level. It is therefore important to rely on legacy data like the Harmonized World Soil Database. Several efforts do exist that aim at the development of global gridded soil property databases. These estimates of the variation of soil properties can be used to assess e.g., global soil carbon stocks. However, they do not allow for simulation runs with e.g., crop growth simulation models as these models require a description of the entire pedon rather than a few soil properties. This study provides the required quantitative description of pedons at a 1 km resolution for simulation modelling. It uses the Harmonized World Soil Database (HWSD) for the spatial distribution of soil types, the ISRIC-WISE soil profile database to derive information on soil properties per soil type, and a range of co-variables on topography, climate, and land cover to further disaggregate the available data. The methodology aims to take stock of these available data. The soil database is developed in five main steps. Step 1: All 148 soil types are ordered on the basis of their expected topographic position using e.g., drainage, salinization, and pedogenesis. Using the topographic ordering and combining the HWSD with a digital elevation model allows for the spatial disaggregation of the composite soil units. This results in a new soil map with homogeneous soil units. Step 2: The ranges of major soil properties for the topsoil and subsoil of each of the 148 soil types are derived from the ISRIC-WISE soil profile database. Step 3: A model of soil formation is developed that focuses on the basic conceptual question where we are within the range of a particular soil property

Impact of Hydrologic and Micro-topographic Variabilities on Spatial Distribution of Mean Soil-Nitrogen Age

Science.gov (United States)

Woo, D.; Kumar, P.

2015-12-01

Excess reactive nitrogen in soils of intensively managed agricultural fields causes adverse environmental impact, and continues to remain a global concern. Many novel strategies have been developed to provide better management practices and, yet, the problem remains unresolved. The objective of this study is to develop a 3-dimensional model to characterize the spatially distributed ``age" of soil-nitrogen (nitrate and ammonia-ammonium) across a watershed. We use the general theory of age, which provides an assessment of the elapsed time since nitrogen is introduced into the soil system. Micro-topographic variability incorporates heterogeneity of nutrient transformations and transport associated with topographic depressions that form temporary ponds and produce prolonged periods of anoxic conditions, and roadside agricultural ditches that support rapid surface movement. This modeling effort utilizes 1-m Light Detection and Ranging (LiDAR) data. We find a significant correlation between hydrologic variability and mean nitrate age that enables assessment of preferential flow paths of nitrate leaching. The estimation of the mean nitrogen age can thus serve as a tool to disentangle complex nitrogen dynamics by providing the analysis of the time scales of soil-nitrogen transformation and transport processes without introducing additional parameters.

Global Historical Climatology Network - Monthly (GHCN-M), Version 3

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Please note, GHCN-Monthly provides climatological observations for four elements; monthly mean maximum temperature, minimum temperature, mean temperature, and...

Global patterns in mangrove soil carbon stocks and losses

KAUST Repository

Atwood, Trisha B.

2017-06-26

Mangrove soils represent a large sink for otherwise rapidly recycled carbon (C). However, widespread deforestation threatens the preservation of this important C stock. It is therefore imperative that global patterns in mangrove soil C stocks and their susceptibility to remineralization are understood. Here, we present patterns in mangrove soil C stocks across hemispheres, latitudes, countries and mangrove community compositions, and estimate potential annual CO2 emissions for countries where mangroves occur. Global potential CO2 emissions from soils as a result of mangrove loss were estimated to be ~7.0 Tg CO2e yr−1. Countries with the highest potential CO2 emissions from soils are Indonesia (3,410 Gg CO2e yr−1) and Malaysia (1,288 Gg CO2e yr−1). The patterns described serve as a baseline by which countries can assess their mangrove soil C stocks and potential emissions from mangrove deforestation.

Soil structure and microbial activity dynamics in 20-month field-incubated organic-amended soils

DEFF Research Database (Denmark)

Arthur, Emmanuel; Schjønning, Per; Møldrup, Per

2014-01-01

to determine compressive strength. During incubation, the amount of WDC depended on soil carbon content while the trends correlated with moisture content. Organic amendment only yielded modest decreases (mean of 14% across all sampling times and soils) in WDC, but it was sufficient to stimulate the microbial......Soil structure formation is essential to all soil ecosystem functions and services. This study aims to quantify changes in soil structure and microbial activity during and after field incubation and examine the effect of carbon, organic amendment and clay on aggregate characteristics. Five soils...... community (65–100% increase in FDA). Incubation led to significant macroaggregate formation (>2 mm) for all soils. Friability and strength of newly-formed aggregates were negatively correlated with clay content and carbon content, respectively. Soil workability was best for the kaolinite-rich soil...

Soil Science and Global Issues

Science.gov (United States)

Lal, Rattan

2015-04-01

Sustainable management of soil is integral to any rational approach to addressing global issues of the 21st century. A high quality soil is essential to: i) advancing food and nutritional security, ii) mitigating and adapting to climate change, iii) improving quality and renewability of water, iv) enriching biodiversity, v) producing biofuel feedstocks for reducing dependence on fossil fuel, and vi) providing cultural, aesthetical and recreational opportunities. Being the essence of all terrestrial life, soil functions and ecosystem services are essential to wellbeing of all species of plants and animals. Yet, soil resources are finite, unequally distributed geographically, and vulnerable to degradation by natural and anthropogenic perturbations. Nonetheless, soil has inherent resilience, and its ecosystem functions and services can be restored over time. However, soil resilience depends on several key soil properties including soil organic carbon (SOC) concentration and pool, plant-available water capacity (PWAC), nutrient reserves, effective rooting depth, texture and clay mineralogy, pH, cation exchange capacity (CEC) etc. There is a close inter-dependence among these properties. For example, SOC concentration strongly affects, PWAC, nutrient reserve, activity and species diversity of soil flora and fauna, CEC etc. Thus, judicious management of SOC concentration to maintain it above the threshold level (~1.5-2%) in the root zone is critical to sustaining essential functions and ecosystem services. Yet, soils of some agroecosystems (e.g., those managed by resources-poor farmers and small landholders in the tropics and sub-tropics) are severely depleted of their SOC reserves. Consequently. Agronomic productivity and wellbeing of people dependent on degraded soils is jeopardized. The ecosystem C pool of the terrestrial biosphere has been mined by extractive practices, the nature demands recarbonization of its biosphere for maintenance of its functions and

The global historical climatology network: Long-term monthly temperature, precipitation, and pressure data

International Nuclear Information System (INIS)

Vose, R.S.; Schmoyer, R.L.; Peterson, T.C.; Steurer, P.M.; Heim, R.R. Jr.; Karl, T.R.; Eischeid, J.K.

1992-01-01

Interest in global climate change has risen dramatically during the past several decades. In a similar fashion, the number of data sets available to study global change has also increased. Unfortunately, many different organizations and researchers have compiled these data sets, making it confusing and time consuming for individuals to acquire the most comprehensive data. In response to this rapid growth in the number of global data sets, DOE's Carbon Dioxide Information Analysis Center (CDIAC) and NOAA's National Climatic Data Center (NCDC) established the Global Historical Climatology Network (GHCN) project. The purpose of this project is to compile an improved data set of long-term monthly mean temperature, precipitation, sea level pressure, and station pressure for as dense a network of global stations as possible. Specifically, the GHCN project seeks to consolidate the numerous preexisting national-, regional-, and global-scale data sets into a single global data base; to subject the data to rigorous quality control; and to update, enhance, and distribute the data set at regular intervals. The purpose of this paper is to describe the compilation and contents of the GHCN data base (i.e., GHCN Version 1.0)

Phosphorus in agricultural soils: drivers of its distribution at the global scale

Energy Technology Data Exchange (ETDEWEB)

Ringeval, Bruno [ISPA, Villenave d' Ornon (France); Augusto, Laurent [ISPA, Villenave d' Ornon (France); Monod, Herve [Univ. Paris-Saclay, Jouy-en-Josas (France); van Apeldoorn, Dirk [Utrecht Univ., Utrecht (The Netherlands); Bouwman, Lex [Utrecht Univ., Utrecht (The Netherlands); Yang, Xiaojuan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Achat, David L. [ISPA, Villenave d' Ornon (France); Chini, Louise P. [Univ. of Maryland, College Park, MD (United States); Van Oost, Kristof [Univ. Catholique de Louvain, Louvain-la-Neuve (Belgium); Guenet, Bertrand [Univ. Paris-Saclay, Gif-sur-Yvette (France); Wang, Rong [Univ. Paris-Saclay, Gif-sur-Yvette (France); Peking Univ., Beijing (China); Decharme, Bertrand [CNRS/Meteo-France, Toulouse (France); Nesme, Thomas [ISPA, Villenave d' Ornon (France); Pellerin, Sylvain [ISPA, Villenave d' Ornon (France)

2017-01-09

Phosphorus (P) availability in soils limits crop yields in many regions of the world, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global datasets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analyzed both the labile inorganic P (P_ILAB), a proxy of the pool involved in plant nutrition and the total soil P (P_TOT). We found that the soil biogeochemical background (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between P_TOT vs P_ILAB. Indeed, 97% of the P_TOT spatial variability could be explained by BIOG, while BIOG and FARM explained 41% and 58% of P_ILAB spatial variability, respectively. Other drivers such as climate, soil erosion, atmospheric P deposition and soil buffering capacity made only very small contribution. Lastly, our study is a promising approach to investigate the potential effect of P as a limiting factor for agricultural ecosystems and for global food production. Additionally, we quantified the anthropogenic perturbation of P cycle and demonstrated how the different drivers are combined to explain the global distribution of agricultural soil P.

Global Summary of the Month, version 1.0

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global summaries data set contains a monthly (GSOM) resolution of meteorological elements (max temp, snow, etc) from 1763 to present with updates weekly. The...

Dryland photoautotrophic soil surface communities endangered by global change

Science.gov (United States)

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-03-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth's terrestrial surface will decrease by about 25-40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

Dryland photoautotrophic soil surface communities endangered by global change

Science.gov (United States)

Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina

2018-01-01

Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.

Climate change impacts on soil carbon storage in global croplands: 1901-2010

Science.gov (United States)

Ren, W.; Tian, H.

2015-12-01

New global data finds 12% of earth's surface in cropland at present. Croplands will take on the responsibility to support approximate 60% increase in food production by 2050 as FAO estimates. In addition to nutrient supply to plants, cropland soils also play a major source and sink of greenhouse gases regulating global climate system. It is a big challenge to understand how soils function under global changes, but it is also a great opportunity for agricultural sector to manage soils to assure sustainability of agroecosystems and mitigate climate change. Previous studies have attempted to investigate the impacts of different land uses and climates on cropland soil carbon storage. However, large uncertainty still exists in magnitude and spatiotemporal patterns of global cropland soil organic carbon, due to the lack of reliable environmental databases and relatively poorly understanding of multiple controlling factors involved climate change and land use etc. Here, we use a process-based agroecosystem model (DLEM-Ag) in combination with diverse data sources to quantify magnitude and tempo-spatial patterns of soil carbon storage in global croplands during 1901-2010. We also analyze the relative contributions of major environmental variables (climate change, land use and management etc.). Our results indicate that intensive land use management may hidden the vulnerability of cropland soils to climate change in some regions, which may greatly weaken soil carbon sequestration under future climate change.

Global observation-based diagnosis of soil moisture control on land surface flux partition

Science.gov (United States)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Veal, Karen L.; Folwell, Sonja S.

2016-04-01

Soil moisture plays a central role in the partition of available energy at the land surface between sensible and latent heat flux to the atmosphere. As soils dry out, evapotranspiration becomes water-limited ("stressed"), and both land surface temperature (LST) and sensible heat flux rise as a result. This change in surface behaviour during dry spells directly affects critical processes in both the land and the atmosphere. Soil water deficits are often a precursor in heat waves, and they control where feedbacks on precipitation become significant. State-of-the-art global climate model (GCM) simulations for the Coupled Model Intercomparison Project Phase 5 (CMIP5) disagree on where and how strongly the surface energy budget is limited by soil moisture. Evaluation of GCM simulations at global scale is still a major challenge owing to the scarcity and uncertainty of observational datasets of land surface fluxes and soil moisture at the appropriate scale. Earth observation offers the potential to test how well GCM land schemes simulate hydrological controls on surface fluxes. In particular, satellite observations of LST provide indirect information about the surface energy partition at 1km resolution globally. Here, we present a potentially powerful methodology to evaluate soil moisture stress on surface fluxes within GCMs. Our diagnostic, Relative Warming Rate (RWR), is a measure of how rapidly the land warms relative to the overlying atmosphere during dry spells lasting at least 10 days. Under clear skies, this is a proxy for the change in sensible heat flux as soil dries out. We derived RWR from MODIS Terra and Aqua LST observations, meteorological re-analyses and satellite rainfall datasets. Globally we found that on average, the land warmed up during dry spells for 97% of the observed surface between 60S and 60N. For 73% of the area, the land warmed faster than the atmosphere (positive RWR), indicating water stressed conditions and increases in sensible heat flux

Global controls on carbon storage in mangrove soils

Science.gov (United States)

Rovai, André S.; Twilley, Robert R.; Castañeda-Moya, Edward; Riul, Pablo; Cifuentes-Jara, Miguel; Manrow-Villalobos, Marilyn; Horta, Paulo A.; Simonassi, José C.; Fonseca, Alessandra L.; Pagliosa, Paulo R.

2018-06-01

Global-scale variation in mangrove ecosystem properties has been explained using a conceptual framework linking geomorphological processes to distinct coastal environmental settings (CES) for nearly 50 years. However, these assumptions have not been empirically tested at the global scale. Here, we show that CES account for global variability in mangrove soil C:N:P stoichiometry and soil organic carbon (SOC) stocks. Using this ecogeomorphology framework, we developed a global model that captures variation in mangrove SOC stocks compatible with distinct CES. We show that mangrove SOC stocks have been underestimated by up to 50% (a difference of roughly 200 Mg ha-1) in carbonate settings and overestimated by up to 86% (around 400 Mg ha-1) in deltaic coastlines. Moreover, we provide information for 57 nations that currently lack SOC data, enabling these and other countries to develop or evaluate their blue carbon inventories.

Estimation of global solar radiation by means of sunshine duration

Energy Technology Data Exchange (ETDEWEB)

Luis, Mazorra Aguiar; Felipe, Diaz Reyes [Electrical Engineering Dept., Las Palmas de Gran Canaria Univ. (U.L.P.G.C.), Campus Univ. Tafira (Spain); Pilar, Navarro Rivero [Canary Islands Technological Inst. (I.T.C.), Gran Canaria (Spain)

2008-07-01

This paper analyses the relationship between global solar irradiation and sunshine duration with different estimation models for the island of Gran Canaria (Spain). These parameters were taken from six measurement stations around the Island, and selected for their reliability and the long period of time they covered. All data used in this paper were handed over by the Canary Islands Technological Institute (I.T.C.). As a first approach, it was decided to study the Angstrom lineal model. In order to improve the knowledge on solar resources, a Typical Meteorological Year (TMY) was created from all daily data. TMY shows differences between southern and northern locations, where Trade Winds generate clouds during the summer months. TMY resumes a data bank much longer than a year in duration, generating the characteristics for a year series of each location, for both irradiation and sunshine duration. To create the TMY, weighted means have been used to smooth high or low values. At first, Angstrom lineal model has been used to estimate solar global irradiation from sunshine duration values, using TMY. But the lineal model didn't reproduce satisfactory results when used to obtain global solar radiation from all daily sunshine duration data. For this reason, different models based in both parameters were used. The parameters estimation of this model was achieved both from TMY daily and monthly series and from all daily data for every location. Because of the weather stability all over the year in the Island, most of the daily data are concentrated in a close range, occasioning a deviation in the lineal equations. To avoid this deviation it was proposed to consider a limit condition data, taking into account values out of the main cloud of data. Additionally, different models were proposed (quadratic, cubic, logarithmic and exponential) to make a regression from all daily data. The best results were obtained with the exponential model proposed in this paper. The

Contribution of soil respiration to the global carbon equation.

Science.gov (United States)

Xu, Ming; Shang, Hua

2016-09-20

Soil respiration (Rs) is the second largest carbon flux next to GPP between the terrestrial ecosystem (the largest organic carbon pool) and the atmosphere at a global scale. Given their critical role in the global carbon cycle, Rs measurement and modeling issues have been well reviewed in previous studies. In this paper, we briefly review advances in soil organic carbon (SOC) decomposition processes and the factors affecting Rs. We examine the spatial and temporal distribution of Rs measurements available in the literature and found that most of the measurements were conducted in North America, Europe, and East Asia, with major gaps in Africa, East Europe, North Asia, Southeast Asia, and Australia, especially in dry ecosystems. We discuss the potential problems of measuring Rs on slope soils and propose using obliquely-cut soil collars to solve the existing problems. We synthesize previous estimates of global Rs flux and find that the estimates ranged from 50 PgC/yr to 98 PgC/yr and the error associated with each estimation was also high (4 PgC/yr to 33.2 PgC/yr). Using a newly integrated database of Rs measurements and the MODIS vegetation map, we estimate that the global annual Rs flux is 94.3 PgC/yr with an estimation error of 17.9 PgC/yr at a 95% confidence level. The uneven distribution of Rs measurements limits our ability to improve the accuracy of estimation. Based on the global estimation of Rs flux, we found that Rs is highly correlated with GPP and NPP at the biome level, highlighting the role of Rs in global carbon budgets. Copyright © 2016. Published by Elsevier GmbH.

Global Assessment of the SMAP Level-4 Soil Moisture Product Using Assimilation Diagnostics

Science.gov (United States)

Reichle, Rolf; Liu, Qing; De Lannoy, Gabrielle; Crow, Wade; Kimball, John; Koster, Randy; Ardizzone, Joe

2018-01-01

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx. 2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

Estimate of the global-scale joule heating rates in the thermosphere due to time mean currents

International Nuclear Information System (INIS)

Roble, R.G.; Matsushita, S.

1975-01-01

An estimate of the global-scale joule heating rates in the thermosphere is made based on derived global equivalent overhead electric current systems in the dynamo region during geomagnetically quiet and disturbed periods. The equivalent total electric field distribution is calculated from Ohm's law. The global-scale joule heating rates are calculated for various monthly average periods in 1965. The calculated joule heating rates maximize at high latitudes in the early evening and postmidnight sectors. During geomagnetically quiet times the daytime joule heating rates are considerably lower than heating by solar EUV radiation. However, during geomagnetically disturbed periods the estimated joule heating rates increase by an order of magnitude and can locally exceed the solar EUV heating rates. The results show that joule heating is an important and at times the dominant energy source at high latitudes. However, the global mean joule heating rates calculated near solar minimum are generally small compared to the global mean solar EUV heating rates. (auth)

Artificial neural network optimisation for monthly average daily global solar radiation prediction

International Nuclear Information System (INIS)

Alsina, Emanuel Federico; Bortolini, Marco; Gamberi, Mauro; Regattieri, Alberto

2016-01-01

Highlights: • Prediction of the monthly average daily global solar radiation over Italy. • Multi-location Artificial Neural Network (ANN) model: 45 locations considered. • Optimal ANN configuration with 7 input climatologic/geographical parameters. • Statistical indicators: MAPE, NRMSE, MPBE. - Abstract: The availability of reliable climatologic data is essential for multiple purposes in a wide set of anthropic activities and operative sectors. Frequently direct measures present spatial and temporal lacks so that predictive approaches become of interest. This paper focuses on the prediction of the Monthly Average Daily Global Solar Radiation (MADGSR) over Italy using Artificial Neural Networks (ANNs). Data from 45 locations compose the multi-location ANN training and testing sets. For each location, 13 input parameters are considered, including the geographical coordinates and the monthly values for the most frequently adopted climatologic parameters. A subset of 17 locations is used for ANN training, while the testing step is against data from the remaining 28 locations. Furthermore, the Automatic Relevance Determination method (ARD) is used to point out the most relevant input for the accurate MADGSR prediction. The ANN best configuration includes 7 parameters, only, i.e. Top of Atmosphere (TOA) radiation, day length, number of rainy days and average rainfall, latitude and altitude. The correlation performances, expressed through statistical indicators as the Mean Absolute Percentage Error (MAPE), range between 1.67% and 4.25%, depending on the number and type of the chosen input, representing a good solution compared to the current standards.

Soil density and moisture content on two unused forest roads during first 30 months after construction

Science.gov (United States)

J.D. Helvey; J.N. Kochenderfer; J.N. Kochenderfer

1990-01-01

Reports results of soil density and soil moisture measurements on two roads in the central Appalachians over a 30-month period. Density increased slightly during the measurement period at most locations. Almost all of the density changes occurred during the first few months after construction. Moisture content decreased during the first few months after construction,...

Soil respiration at mean annual temperature predicts annual total across vegetation types and biomes

Directory of Open Access Journals (Sweden)

M. Bahn

2010-07-01

Full Text Available Soil respiration (SR constitutes the largest flux of CO₂ from terrestrial ecosystems to the atmosphere. However, there still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 80 site-years for 57 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (SR_MAT, irrespective of the type of ecosystem and biome. This is theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q₁₀. We further show that for seasonally dry sites where annual precipitation (P is lower than potential evapotranspiration (PET, annual SR can be predicted from wet season SR_MAT corrected for a factor related to P/PET. Our finding indicates that it can be sufficient to measure SR_MAT for obtaining a well constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution of soil CO₂ emissions across ecosystems, landscapes and regions, and thereby contribute to improving the spatial resolution of a major component of the global carbon cycle.

The Global Turnover Time Distribution of Soil Carbon Derived from a Meta-analysis of Radiocarbon Profiles

Science.gov (United States)

He, Y.; Randerson, J. T.; Allison, S. D.; Torn, M. S.; Harden, J. W.; Smith, L. J.; van der Voort, T.; Trumbore, S.

2015-12-01

Soil is the largest terrestrial carbon reservoir and may influence the sign and magnitude of carbon cycle feedbacks under climate change. Soil carbon turnover times provide information about the sensitivity of carbon pools to changes in inputs and warming. The spatial and vertical distribution of soil carbon turnover times emerges from the interplay between climate, vegetation, and soil properties. Radiocarbon levels of soil organic matter can be used to estimate soil carbon turnover using models that take into account radioactive decay over centuries to millennia and inputs of 14C from atmospheric weapons testing ("bomb carbon") during the second half of the 20th century. By synthesizing more than 200 soil radiocarbon profiles from all major biomes and soil orders, we 1) explored the major controlling factors for soil carbon turnover times of surface and deeper soil layers; 2) developed predictive models (tree-based regression, support vector regression and linear regression models) of Δ14C that depends on depth, climate, vegetation, and soil types; and 3) extrapolated the predictive model to produce the first global distribution of soil carbon turnover times to the depth of 1m. Preliminary results indicated that climate and depth were primary controls of the vertical distribution of Δ14C, contributing to about 70% of the variability in our model. Vegetation and soil order exerted similar level of controls (about 15% each). The predictive model performed reasonably well with an R2 of 0.81 and RMSE (root-mean-squared error) of about 50‰ for topsoil and 100‰ for subsoil, as estimated using cross-validation. Extrapolation of the predictive model to the globe in combination with existing soil carbon information (e.g., Harmonized World Soil Database) indicated that more than half of the global total soil carbon in the top 1m had a turnover time of less than 500 years. Subsoils (30-100cm) had millennium-scale turnover times, with the majority (70%) turning over

Global Patterns of the Isotopic Composition of Soil and Plant Nitrogen

Science.gov (United States)

Amundson, R.; Yoo, K.

2014-12-01

From a societal perspective, soil N follows only soil C in the importance of soil to 21st century environmental issues. Amundson et al (2003) developed a mass balance model for soil N and the ratio of 15N/14N, and provided the first global projections of the spatial patterns of soil and plant δ15N values. It was hypothesized that state factors, particularly climate, should drive broad patterns of soil and plant δ15N values in a manner analogous to the known patterns of total soil N (e.g. Post et al., 1984). At that time, the N isotope data available to explore the effect of individual factors was modest. In the past decade, numerous papers from a broad spectrum of locations have created a rich database that can be used to further refine the initial projections made more than a decade ago. In this paper, hundreds of published measurements will be used to more deeply examine the climatic impacts on soil and plant δ15N values. Additionally, we will focus on the local controls of topography on ecosystem N cycling, which can create local isotopic variation that is similar in magnitude to the global effects of climate. The adoption of process-based models from the hillslope geomorphology community appears to be a powerful tool for explaining some existing data from toposequences, designing new studies of topographic controls on biogeochemistry, and particularly for parameterization in global models. Amundson, R., A.T. Austin, E.A.G. Schuur, K. Yoo, V. Matzek, C. Kendall, A. Uebersax, D. Brenner, and W.T. Baisden. 2003. Global Biogeochemical Cycles 17(1):1031.

Plutonium mobility studies in soil sediment decontaminated by means of a soil-washing technology

International Nuclear Information System (INIS)

Negri, M.C.; Orlandini, K.A.; Swift, N.; Carfagno, D.

1995-01-01

The ACT*DE*CON SM process extracts plutonium from contaminated soils/sediments by means of a series of washings with a blend of chemicals, that includes a chelating agent, an oxidant, and carbonates. At the end of the process, the Pu level in the soil is lowered to 25-30 pCi/g from an initial contamination level averaging 500 pCi/g. The radionuclide still present in the soil at the end of the treatment must be strongly immobilized in or onto the soil particles to minimize the risk of its percolation to the aquifer and/or uptake by vegetation. This paper reports the investigation of residual Pu mobility as K d (distribution coefficient) in the treated soil/sediment. Six batches of contaminated soil were treated simultaneously by means of the ACT*DE*CON SM process. Some batches of the treated soil were amended with a standard fertilizer treatment of compost and nutrient and brought to pH 8.5. The treated soil, treated and fertilized soil, and the untreated controls were then incubated at 18 degrees C for 90 days. At four different times, a small aliquot of soil was retrieved from each of the batches and contacted with rainwater for six days to determine the Pu solid/liquid distribution and K d . Results indicated that a higher total amount of Pu was leached from the untreated soil, probably as a consequence of the higher content of available/exchangeable Pu in this soil compared with the treated ones. Treated/fertilized soils showed Pu leaching at intermediate levels between those for treated and untreated soils, at least for the first 30 days of incubation. K d values at the beginning of the incubation period were significantly lower in the untreated and treated/fertilized soils compared with those for the treated-only, but at 90 days, these values were substantially equal among the three different soils. Traces of the chelant were detectable only in treated, unfertilized soil

Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation

Science.gov (United States)

Mandrake, Lukas

2013-01-01

Retrieval algorithms like that used by the Orbiting Carbon Observatory (OCO)-2 mission generate massive quantities of data of varying quality and reliability. A computationally efficient, simple method of labeling problematic datapoints or predicting soundings that will fail is required for basic operation, given that only 6% of the retrieved data may be operationally processed. This method automatically obtains a filter designed to reduce scatter based on a small number of input features. Most machine-learning filter construction algorithms attempt to predict error in the CO2 value. By using a surrogate goal of Mean Monthly STDEV, the goal is to reduce the retrieved CO2 scatter rather than solving the harder problem of reducing CO2 error. This lends itself to improved interpretability and performance. This software reduces the scatter of retrieved CO2 values globally based on a minimum number of input features. It can be used as a prefilter to reduce the number of soundings requested, or as a post-filter to label data quality. The use of the MMS (Mean Monthly Standard deviation) provides a much cleaner, clearer filter than the standard ABS(CO2-truth) metrics previously employed by competitor methods. The software's main strength lies in a clearer (i.e., fewer features required) filter that more efficiently reduces scatter in retrieved CO2 rather than focusing on the more complex (and easily removed) bias issues.

Changes in marsh soils for six months after a fire

International Nuclear Information System (INIS)

Schmalzer, P.A.; Hinkle, C.R.; Koller, A.M. Jr.

1991-01-01

In this study, the authors examined changes in the soil nutrient levels in marsh systems after fire. These studies were conducted in conjunction with studies of particulates and gases generated from biomass combustion and flux measures of methane and nitric oxide before and after the fire. Here data are presented through six months postfire, past the time during which flux measurements were made. These data indicate that changes in soil properties occur at different times after the fire and persist for different intervals, indicating the need for long-term postfire observations

FLO1K, global maps of mean, maximum and minimum annual streamflow at 1 km resolution from 1960 through 2015

Science.gov (United States)

Barbarossa, Valerio; Huijbregts, Mark A. J.; Beusen, Arthur H. W.; Beck, Hylke E.; King, Henry; Schipper, Aafke M.

2018-03-01

Streamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K, a consistent streamflow dataset at a resolution of 30 arc seconds (~1 km) and global coverage. FLO1K comprises mean, maximum and minimum annual flow for each year in the period 1960-2015, provided as spatially continuous gridded layers. We mapped streamflow by means of artificial neural networks (ANNs) regression. An ensemble of ANNs were fitted on monthly streamflow observations from 6600 monitoring stations worldwide, i.e., minimum and maximum annual flows represent the lowest and highest mean monthly flows for a given year. As covariates we used the upstream-catchment physiography (area, surface slope, elevation) and year-specific climatic variables (precipitation, temperature, potential evapotranspiration, aridity index and seasonality indices). Confronting the maps with independent data indicated good agreement (R2 values up to 91%). FLO1K delivers essential data for freshwater ecology and water resources analyses at a global scale and yet high spatial resolution.

Modeling global mangrove soil carbon stocks: filling the gaps in coastal environments

Science.gov (United States)

Rovai, A.; Twilley, R.

2017-12-01

We provide an overview of contemporaneous global mangrove soil organic carbon (SOC) estimates, focusing on a framework to explain disproportionate differences among observed data as a way to improve global estimates. This framework is based on a former conceptual model, the coastal environmental setting, in contrast to the more popular latitude-based hypotheses largely believed to explain hemispheric variation in mangrove ecosystem properties. To demonstrate how local and regional estimates of SOC linked to coastal environmental settings can render more realistic global mangrove SOC extrapolations we combined published and unpublished data, yielding a total of 106 studies, reporting on 552 sites from 43 countries. These sites were classified into distinct coastal environmental setting types according to two concurrent worldwide typology of nearshore coastal systems classifications. Mangrove SOC density varied substantially across coastal environmental settings, ranging from 14.9 ± 0.8 in river dominated (deltaic) soils to 53.9 ± 1.6 mg cm-3 (mean ± SE) in karstic coastlines. Our findings reveal striking differences between published values and contemporary global mangrove SOC extrapolation based on country-level mean reference values, particularly for karstic-dominated coastlines where mangrove SOC stocks have been underestimated by up to 50%. Correspondingly, climate-based global estimates predicted lower mangrove SOC density values (32-41 mg C cm-3) for mangroves in karstic environments, differing from published (21-126 mg C cm-3) and unpublished (47-58 mg C cm-3) values. Moreover, climate-based projections yielded higher SOC density values (27-70 mg C cm-3) for river-dominated mangroves compared to lower ranges reported in the literature (11-24 mg C cm-3). We argue that this inconsistent reporting of SOC stock estimates between river-dominated and karstic coastal environmental settings is likely due to the omission of geomorphological and geophysical

Global drought outlook by means of seasonal forecasts

Science.gov (United States)

Ziese, Markus; Fröhlich, Kristina; Rustemeier, Elke; Becker, Andreas

2017-04-01

Droughts are naturally occurring phenomena which are caused by a shortage of available water due to lower than normal precipitation and/or above normal evaporation. Depending on the length of the droughts, several sectors are affected starting with agriculture, then river and ground water levels and finally socio-economic losses at the long end of the spectrum of drought persistence. Droughts are extreme events that affect much larger areas and last much longer than floods, but are less geared towards media than floods being more short-scale in persistence and impacts. Finally the slow onset of droughts make the detection and early warning of their beginning difficult and time is lost for preparatory measures. Drought indices are developed to detect and classify droughts based on (meteorological) observations and possible additional information tailored to specific user needs, e.g. in agriculture, hydrology and other sectors. Not all drought indices can be utilized for global applications as not all input parameters are available at this scale. Therefore the Global Precipitation Climatology Centre (GPCC) developed a drought index as combination of the Standardized Drought Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), the GPCC-DI. The GPCC-DI is applied to drought monitoring and retrospective analyses on a global scale. As the Deutscher Wetterdienst (DWD) operates a seasonal forecast system in cooperation with Max-Planck-Institute for Meteorology Hamburg and University of Hamburg, these data are also used for an outlook of drought conditions by means of the GPCC-DI. The reliability of seasonal precipitation forecasts is limited, so the drought outlook is available only for forecast months two to four. Based on the GPCC-DI, DWD provides a retrospective analysis, near-real-time monitoring and outlook of drought conditions on a global scale and regular basis.

Temperature and vegetation effects on soil organic carbon quality along a forested mean annual temperature gradient in North America

Science.gov (United States)

Cinzia Fissore; Christian P. Giardina; Randall K. Kolka; Carl C. Trettin; Gary M. King; Martin F. Jurgensen; Christopher D. Barton; S. Douglas McDowell

2008-01-01

Both climate and plant species are hypothesized to influence soil organic carbon (SOC) quality, but accurate prediction of how SOC process rates respond to global change will require an improved understanding of how SOC quality varies with mean annual temperature (MAT) and forest type. We investigated SOC quality in paired hardwood and pine stands growing in coarse...

A global analysis of soil microbial biomass carbon, nitrogen and phosphorus in terrestrial ecosystems

Energy Technology Data Exchange (ETDEWEB)

Xu, Xiaofeng [ORNL; Thornton, Peter E [ORNL; Post, Wilfred M [ORNL

2013-01-01

Soil microbes play a pivotal role in regulating land-atmosphere interactions; the soil microbial biomass carbon (C), nitrogen (N), phosphorus (P) and C:N:P stoichiometry are important regulators for soil biogeochemical processes; however, the current knowledge on magnitude, stoichiometry, storage, and spatial distribution of global soil microbial biomass C, N, and P is limited. In this study, 3087 pairs of data points were retrieved from 281 published papers and further used to summarize the magnitudes and stoichiometries of C, N, and P in soils and soil microbial biomass at global- and biome-levels. Finally, global stock and spatial distribution of microbial biomass C and N in 0-30 cm and 0-100 cm soil profiles were estimated. The results show that C, N, and P in soils and soil microbial biomass vary substantially across biomes; the fractions of soil nutrient C, N, and P in soil microbial biomass are 1.6% in a 95% confidence interval of (1.5%-1.6%), 2.9% in a 95% confidence interval of (2.8%-3.0%), and 4.4% in a 95% confidence interval of (3.9%-5.0%), respectively. The best estimates of C:N:P stoichiometries for soil nutrients and soil microbial biomass are 153:11:1, and 47:6:1, respectively, at global scale, and they vary in a wide range among biomes. Vertical distribution of soil microbial biomass follows the distribution of roots up to 1 m depth. The global stock of soil microbial biomass C and N were estimated to be 15.2 Pg C and 2.3 Pg N in the 0-30 cm soil profiles, and 21.2 Pg C and 3.2 Pg N in the 0-100 cm soil profiles. We did not estimate P in soil microbial biomass due to data shortage and insignificant correlation with soil total P and climate variables. The spatial patterns of soil microbial biomass C and N were consistent with those of soil organic C and total N, i.e. high density in northern high latitude, and low density in low latitudes and southern hemisphere.

Monthly Mean Temperature Observation for Climate Prediction Center (CPC) Forecast Divisions

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This ASCII dataset contains monthly mean temperatures for 102 Forecast Divisions within the conterminous U.S. and is derived from the monthly NCDC climate division...

Global charcoal mobilization from soils via dissolution and riverine transport to the oceans.

Science.gov (United States)

Jaffé, Rudolf; Ding, Yan; Niggemann, Jutta; Vähätalo, Anssi V; Stubbins, Aron; Spencer, Robert G M; Campbell, John; Dittmar, Thorsten

2013-04-19

Global biomass burning generates 40 million to 250 million tons of charcoal every year, part of which is preserved for millennia in soils and sediments. We have quantified dissolution products of charcoal in a wide range of rivers worldwide and show that globally, a major portion of the annual charcoal production is lost from soils via dissolution and subsequent transport to the ocean. The global flux of soluble charcoal accounts to 26.5 ± 1.8 million tons per year, which is ~10% of the global riverine flux of dissolved organic carbon (DOC). We suggest that the mobilization of charcoal and DOC out of soils is mechanistically coupled. This study closes a major gap in the global charcoal budget and provides critical information in the context of geoengineering.

Global Historical Climatology Network - Monthly Temperature, Version 4 (BETA)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Only available as BETA release. The GHCN-Monthly Temperature Version 4 dataset consists of monthly mean temperature - both raw and bias corrected data. A full...

Global patterns in mangrove soil carbon stocks and losses

KAUST Repository

Atwood, Trisha B.; Connolly, Rod M.; Almahasheer, Hanan; Carnell, Paul E.; Duarte, Carlos M.; Ewers Lewis, Carolyn J.; Irigoien, Xabier; Kelleway, Jeffrey J.; Lavery, Paul S.; Macreadie, Peter I.; Serrano, Oscar; Sanders, Christian J.; Santos, Isaac; Steven, Andrew D. L.; Lovelock, Catherine E.

2017-01-01

. Global potential CO2 emissions from soils as a result of mangrove loss were estimated to be ~7.0 Tg CO2e yr−1. Countries with the highest potential CO2 emissions from soils are Indonesia (3,410 Gg CO2e yr−1) and Malaysia (1,288 Gg CO2e yr−1). The patterns

Soil Methanotrophy Model (MeMo v1.0): a process-based model to quantify global uptake of atmospheric methane by soil

Science.gov (United States)

Murguia-Flores, Fabiola; Arndt, Sandra; Ganesan, Anita L.; Murray-Tortarolo, Guillermo; Hornibrook, Edward R. C.

2018-06-01

Soil bacteria known as methanotrophs are the sole biological sink for atmospheric methane (CH4), a potent greenhouse gas that is responsible for ˜ 20 % of the human-driven increase in radiative forcing since pre-industrial times. Soil methanotrophy is controlled by a plethora of factors, including temperature, soil texture, moisture and nitrogen content, resulting in spatially and temporally heterogeneous rates of soil methanotrophy. As a consequence, the exact magnitude of the global soil sink, as well as its temporal and spatial variability, remains poorly constrained. We developed a process-based model (Methanotrophy Model; MeMo v1.0) to simulate and quantify the uptake of atmospheric CH4 by soils at the global scale. MeMo builds on previous models by Ridgwell et al. (1999) and Curry (2007) by introducing several advances, including (1) a general analytical solution of the one-dimensional diffusion-reaction equation in porous media, (2) a refined representation of nitrogen inhibition on soil methanotrophy, (3) updated factors governing the influence of soil moisture and temperature on CH4 oxidation rates and (4) the ability to evaluate the impact of autochthonous soil CH4 sources on uptake of atmospheric CH4. We show that the improved structural and parametric representation of key drivers of soil methanotrophy in MeMo results in a better fit to observational data. A global simulation of soil methanotrophy for the period 1990-2009 using MeMo yielded an average annual sink of 33.5 ± 0.6 Tg CH4 yr-1. Warm and semi-arid regions (tropical deciduous forest and open shrubland) had the highest CH4 uptake rates of 602 and 518 mg CH4 m-2 yr-1, respectively. In these regions, favourable annual soil moisture content ( ˜ 20 % saturation) and low seasonal temperature variations (variations < ˜ 6 °C) provided optimal conditions for soil methanotrophy and soil-atmosphere gas exchange. In contrast to previous model analyses, but in agreement with recent observational data

Global diversity and geography of soil fungi

Science.gov (United States)

Leho Tedersoo; Mohammad Bahram; Sergei Põlme; Urmas Kõljalg; Nourou S. Yorou; Ravi Wijesundera; Luis Villarreal Ruiz; Aida M. Vasco-Palacios; Pham Quang Thu; Ave Suija; Matthew E. Smith; Cathy Sharp; Erki Saluveer; Alessandro Saitta; Miguel Rosas; Taavi Riit; David Ratkowsky; Karin Pritsch; Kadri Põldmaa; Meike Piepenbring; Cherdchai Phosri; Marko Peterson; Kaarin Parts; Kadri Pärtel; Eveli Otsing; Eduardo Nouhra; André L. Njouonkou; R. Henrik Nilsson; Luis N. Morgado; Jordan Mayor; Tom W. May; Luiza Majukim; D. Jean Lodge; Su See Lee; Karl-Henrik Larsson; Petr Kohout; Kentaro Hosaka; Indrek Hiiesalu; Terry W. Henkel; Helery Harend; Liang-dong Guo; Alina Greslebin; Gwen Gretlet; Jozsef Geml; Genevieve Gates; William Dunstan; Chris Dunk; Rein Drenkhan; John Dearnaley; André De Kesel; Tan Dang; Xin Chen; Franz Buegger; Francis Q. Brearley; Gregory Bonito; Sten Anslan; Sandra Abell; Kessy Abarenkov

2014-01-01

Fungi play major roles in ecosystem processes, but the determinants of fungal diversity and biogeographic patterns remain poorly understood. Using DNA metabarcoding data from hundreds of globally distributed soil samples,we demonstrate that fungal richness is decoupled from plant diversity.The plant-to-fungus richness ratio declines exponentially toward the poles....

Impacts of 2°C global warming on primary production and soil carbon storage capacity at pan-European level

Directory of Open Access Journals (Sweden)

Abdulla Sakalli

2017-08-01

Full Text Available Atmospheric CO2 has been dramatically increasing since beginning of the industrial time (i.e. 1860, being one of the main driver for climate change at regional and global level. The change in CO2 concentration in the atmosphere, together with that of temperature, precipitation and/or so radiation, can influence the biogeochemical cycles in all ecosystems. In this study, we investigate the combined effect of CO2 concentration and six climate variables on carbon uptake, i.e., gross primary production (GPP and carbon storage, i.e, soil carbon (SoilC in terrestrial biosphere by using the Community Land Model (CLM vers. 4.5 and evaluate the model’s results against available observation data. We also analysed the change in carbon uptake and storage under a 2°C global mean warming. Results show that the model performed reasonably well for GPP and SoilC at pan-European scale. We also found a positive correlation between GPP, precipitation and surface wind, and a negative correlation between GPP and surface downwelling longwave radiation (rlds. Under a 2°C global warming, GPP and SoilC show an increase, an average, of about 20%, and 5% at pan-European scale, respectively. However, our results indicate that CLM4.5 may need improvements particularly in carbon-nitrogen interaction and carbon accumulation in soil.

Monthly Mean Precipitation Sums at Russian Arctic Stations, 1966-1990

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains monthly mean precipitation sums from Russian arctic stations. Precipitation measurements were acquired using a Tretyakov precipitation gauge....

Soil Methanotrophy Model (MeMo v1.0: a process-based model to quantify global uptake of atmospheric methane by soil

Directory of Open Access Journals (Sweden)

F. Murguia-Flores

2018-06-01

Full Text Available Soil bacteria known as methanotrophs are the sole biological sink for atmospheric methane (CH4, a potent greenhouse gas that is responsible for  ∼  20 % of the human-driven increase in radiative forcing since pre-industrial times. Soil methanotrophy is controlled by a plethora of factors, including temperature, soil texture, moisture and nitrogen content, resulting in spatially and temporally heterogeneous rates of soil methanotrophy. As a consequence, the exact magnitude of the global soil sink, as well as its temporal and spatial variability, remains poorly constrained. We developed a process-based model (Methanotrophy Model; MeMo v1.0 to simulate and quantify the uptake of atmospheric CH4 by soils at the global scale. MeMo builds on previous models by Ridgwell et al. (1999 and Curry (2007 by introducing several advances, including (1 a general analytical solution of the one-dimensional diffusion–reaction equation in porous media, (2 a refined representation of nitrogen inhibition on soil methanotrophy, (3 updated factors governing the influence of soil moisture and temperature on CH4 oxidation rates and (4 the ability to evaluate the impact of autochthonous soil CH4 sources on uptake of atmospheric CH4. We show that the improved structural and parametric representation of key drivers of soil methanotrophy in MeMo results in a better fit to observational data. A global simulation of soil methanotrophy for the period 1990–2009 using MeMo yielded an average annual sink of 33.5 ± 0.6 Tg CH4 yr−1. Warm and semi-arid regions (tropical deciduous forest and open shrubland had the highest CH4 uptake rates of 602 and 518 mg CH4 m−2 yr−1, respectively. In these regions, favourable annual soil moisture content ( ∼  20 % saturation and low seasonal temperature variations (variations  <   ∼  6 °C provided optimal conditions for soil methanotrophy and soil–atmosphere gas exchange

Global charcoal mobilization from soils via dissolution and riverine transport to the oceans

Science.gov (United States)

Rudolf Jaffe; Yan Ding; Jutta Niggemann; Anssi V. Vahatalo; Aron Stubbins; Robert G. M. Spencer; John Campbell; Thorsten Dittmar

2013-01-01

Global biomass burning generates 40 million to 250 million tons of charcoal every year, part of which is preserved for millennia in soils and sediments. We have quantified dissolution products of charcoal in a wide range of rivers worldwide and show that globally, a major portion of the annual charcoal production is lost from soils via dissolution and subsequent...

Effects of climate change on soil moisture over China from 1960-2006

Science.gov (United States)

Zhu, Q.; Jiang, H.; Liu, J.

2009-01-01

Soil moisture is an important variable in the climate system and it has sensitive impact on the global climate. Obviously it is one of essential components in the climate change study. The Integrated Biosphere Simulator (IBIS) is used to evaluate the spatial and temporal patterns of soil moisture across China under the climate change conditions for the period 1960-2006. Results show that the model performed better in warm season than in cold season. Mean errors (ME) are within 10% for all the months and root mean squared errors (RMSE) are within 10% except winter season. The model captured the spatial variability higher than 50% in warm seasons. Trend analysis based on the Mann-Kendall method indicated that soil moisture in most area of China is decreased especially in the northern China. The areas with significant increasing trends in soil moisture mainly locate at northwestern China and small areas in southeastern China and eastern Tibet plateau. ?? 2009 IEEE.

Decadal variability in core surface flows deduced from geomagnetic observatory monthly means

DEFF Research Database (Denmark)

Whaler, K. A.; Olsen, Nils; Finlay, Chris

2016-01-01

. On the annual to decadal timescale, the SV is generated primarily by advection in the fluid outer core. We demonstrate the utility of the revised monthly means by calculating models of the core surface advective flow between 1997 and 2013 directly from the SV data. One set of models assumes flow......Monthly means of the magnetic field measurements at ground observatories are a key data source for studying temporal changes of the core magnetic field. However, when they are calculated in the usual way, contributions of external (magnetospheric and ionospheric) origin may remain, which make them...... less favourable for studying the field generated by dynamo action in the core. We remove external field predictions, including a new way of characterising the magnetospheric ring current, from the data and then calculate revised monthly means using robust methods. The geomagnetic secular variation (SV...

Statistical analysis of simulated global soil moisture and its memory in an ensemble of CMIP5 general circulation models

Science.gov (United States)

Wiß, Felix; Stacke, Tobias; Hagemann, Stefan

2014-05-01

Soil moisture and its memory can have a strong impact on near surface temperature and precipitation and have the potential to promote severe heat waves, dry spells and floods. To analyze how soil moisture is simulated in recent general circulation models (GCMs), soil moisture data from a 23 model ensemble of Atmospheric Model Intercomparison Project (AMIP) type simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are examined for the period 1979 to 2008 with regard to parameterization and statistical characteristics. With respect to soil moisture processes, the models vary in their maximum soil and root depth, the number of soil layers, the water-holding capacity, and the ability to simulate freezing which all together leads to very different soil moisture characteristics. Differences in the water-holding capacity are resulting in deviations in the global median soil moisture of more than one order of magnitude between the models. In contrast, the variance shows similar absolute values when comparing the models to each other. Thus, the input and output rates by precipitation and evapotranspiration, which are computed by the atmospheric component of the models, have to be in the same range. Most models simulate great variances in the monsoon areas of the tropics and north western U.S., intermediate variances in Europe and eastern U.S., and low variances in the Sahara, continental Asia, and central and western Australia. In general, the variance decreases with latitude over the high northern latitudes. As soil moisture trends in the models were found to be negligible, the soil moisture anomalies were calculated by subtracting the 30 year monthly climatology from the data. The length of the memory is determined from the soil moisture anomalies by calculating the first insignificant autocorrelation for ascending monthly lags (insignificant autocorrelation folding time). The models show a great spread of autocorrelation length from a few months in

Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach

DEFF Research Database (Denmark)

Le Roux, Xavier; Bouskill, Nicholas J.; Niboyet, Audrey

2016-01-01

Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil...... functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global...

Global Precipitation Analyses at Time Scales of Monthly to 3-Hourly

Science.gov (United States)

Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric; Einaudi, Franco (Technical Monitor)

2002-01-01

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the Goodyear data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the Goodyear period. Monthly anomalies of precipitation are related to ENRON variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 degree latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based Based analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous OR observations and merges the various calibrated observations into a final, Baehr resolution map. This TRMM standard product will be available for the entire TRMM period (January Represent). A real-time version of this merged product is being produced and is available at 0.25 degree latitude-longitude resolution over the latitude range from 50 deg. N -50 deg. S. Examples will be shown, including its use in monitoring flood conditions.

[Effects of global change on soil fauna diversity: A review].

Science.gov (United States)

Wu, Ting-Juan

2013-02-01

Terrestrial ecosystem consists of aboveground and belowground components, whose interaction affects the ecosystem processes and functions. Soil fauna plays an important role in biogeochemical cycles. With the recognizing of the significance of soil fauna in ecosystem processes, increasing evidences demonstrated that global change has profound effects on soil faunima diversity. The alternation of land use type, the increasing temperature, and the changes in precipitation pattern can directly affect soil fauna diversity, while the increase of atmospheric CO2 concentration and nitrogen deposition can indirectly affect the soil fauna diversity by altering plant community composition, diversity, and nutrient contents. The interactions of different environmental factors can co-affect the soil fauna diversity. To understand the effects of different driving factors on soil fauna diversity under the background of climate change would facilitate us better predicting how the soil fauna diversity and related ecological processes changed in the future.

Error characterisation of global active and passive microwave soil moisture datasets

Directory of Open Access Journals (Sweden)

W. A. Dorigo

2010-12-01

Full Text Available Understanding the error structures of remotely sensed soil moisture observations is essential for correctly interpreting observed variations and trends in the data or assimilating them in hydrological or numerical weather prediction models. Nevertheless, a spatially coherent assessment of the quality of the various globally available datasets is often hampered by the limited availability over space and time of reliable in-situ measurements. As an alternative, this study explores the triple collocation error estimation technique for assessing the relative quality of several globally available soil moisture products from active (ASCAT and passive (AMSR-E and SSM/I microwave sensors. The triple collocation is a powerful statistical tool to estimate the root mean square error while simultaneously solving for systematic differences in the climatologies of a set of three linearly related data sources with independent error structures. Prerequisite for this technique is the availability of a sufficiently large number of timely corresponding observations. In addition to the active and passive satellite-based datasets, we used the ERA-Interim and GLDAS-NOAH reanalysis soil moisture datasets as a third, independent reference. The prime objective is to reveal trends in uncertainty related to different observation principles (passive versus active, the use of different frequencies (C-, X-, and Ku-band for passive microwave observations, and the choice of the independent reference dataset (ERA-Interim versus GLDAS-NOAH. The results suggest that the triple collocation method provides realistic error estimates. Observed spatial trends agree well with the existing theory and studies on the performance of different observation principles and frequencies with respect to land cover and vegetation density. In addition, if all theoretical prerequisites are fulfilled (e.g. a sufficiently large number of common observations is available and errors of the different

Are climate-related changes to the character of global-mean precipitation predictable?

International Nuclear Information System (INIS)

Stephens, Graeme L; Hu, Yongxiang

2010-01-01

The physical basis for the change in global-mean precipitation projected to occur with the warming associated with increased greenhouse gases is discussed. The expected increases to column water vapor W control the rate of increase of global precipitation accumulation through its affect on the planet's energy balance. The key role played by changes to downward longwave radiation controlled by this changing water vapor is emphasized. The basic properties of molecular absorption by water vapor dictate that the fractional rate of increase of global-mean precipitation must be significantly less that the fractional rate of increase in water vapor and it is further argued that this reduced rate of precipitation increase implies that the timescale for water re-cycling is increased in the global mean. This further implies less frequent precipitation over a fixed period of time, and the intensity of these less frequent precipitating events must subsequently increase in the mean to realize the increased global accumulation. These changes to the character of global-mean precipitation, predictable consequences of equally predictable changes to W, apply only to the global-mean state and not to the regional or local scale changes in precipitation.

HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling.

Science.gov (United States)

Ross, C Wade; Prihodko, Lara; Anchang, Julius; Kumar, Sanath; Ji, Wenjie; Hanan, Niall P

2018-05-15

Hydrologic soil groups (HSGs) are a fundamental component of the USDA curve-number (CN) method for estimation of rainfall runoff; yet these data are not readily available in a format or spatial-resolution suitable for regional- and global-scale modeling applications. We developed a globally consistent, gridded dataset defining HSGs from soil texture, bedrock depth, and groundwater. The resulting data product-HYSOGs250m-represents runoff potential at 250 m spatial resolution. Our analysis indicates that the global distribution of soil is dominated by moderately high runoff potential, followed by moderately low, high, and low runoff potential. Low runoff potential, sandy soils are found primarily in parts of the Sahara and Arabian Deserts. High runoff potential soils occur predominantly within tropical and sub-tropical regions. No clear pattern could be discerned for moderately low runoff potential soils, as they occur in arid and humid environments and at both high and low elevations. Potential applications of this data include CN-based runoff modeling, flood risk assessment, and as a covariate for biogeographical analysis of vegetation distributions.

Short-term variations in core surface flow resolved from an improved method of calculating observatory monthly means

DEFF Research Database (Denmark)

Olsen, Nils; Whaler, K. A.; Finlay, Chris

2014-01-01

Monthly means of the magnetic field measurements taken by ground observatories are a useful data source for studying temporal changes of the core magnetic field and the underlying core flow. However, the usual way of calculating monthly means as the arithmetic mean of all days (geomagnetic quiet...... as well as disturbed) and all local times (day and night) may result in contributions from external (magnetospheric and ionospheric) origin in the (ordinary, omm) monthly means. Such contamination makes monthly means less favourable for core studies. We calculated revised monthly means (rmm......), and their uncertainties, from observatory hourly means using robust means and after removal of external field predictions, using an improved method for characterising the magnetospheric ring current. The utility of the new method for calculating observatory monthly means is demonstrated by inverting their first...

Feedback of global warming to soil carbon cycling in forest ecosystems

International Nuclear Information System (INIS)

Nakane, Kaneyuki

1993-01-01

Thus in this study the simulation of soil carbon cycling and dynamics of its storage in several types of mature forests developed from the cool-temperate to the tropics was carried out for quantitatively assessing carbon loss from the soil under several scenarios of global warming, based on the model of soil carbon cycling in forest ecosystems (Nakane et al. 1984, 1987 and Nakane 1992). (J.P.N.)

Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data.

Science.gov (United States)

Adachi, Minaco; Ito, Akihiko; Yonemura, Seiichiro; Takeuchi, Wataru

2017-09-15

Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr -1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q 10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q 10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of Benzimidazoles in Children Younger than 24 Months for the Treatment of Soil-Transmitted Helminthiasis

Science.gov (United States)

Montresor, A; Awasthi, S; Crompton, DWT

2017-01-01

Considerable experience and limited quantitative evidence indicate that infections with the soil-transmitted helminths Ascaris lumbricoides and Trichuris trichiura usually start to become established in children aged 12 months and older. Since children living in countries where the infections are endemic are at risk of morbidity, even those as young as 12 months may need to be considered for inclusion in public health programmes designed to reduce morbidity by means of regular anthelminthic chemotherapy. This situation raises the question as to whether such young children should be given anthelminthic drugs. Systems for the absorption, distribution, metabolism and elimination of drugs do not fully develop until children are in their second year of life. Current knowledge, however, reveals that the incidence of side effects linked to benzimidazole drugs in young children is likely to be the same as in older children. Accordingly, we conclude that albendazole and mebendazole may be used to treat children as young as 12 months if local circumstances show that relief from ascariasis and trichuriasis is justified. PMID:12745139

Will global warming affect soil-to-plant transfer of radionuclides?

International Nuclear Information System (INIS)

Dowdall, M.; Standring, W.; Shaw, G.; Strand, P.

2008-01-01

Recent assessments of global climate/environmental change are reaching a consensus that global climate change is occurring but there is significant uncertainty over the likely magnitude of this change and its impacts. There is little doubt that all aspects of the natural environment will be impacted to some degree. Soil-to-plant transfer of radionuclides has long been a significant topic in radioecology, both for the protection of humans and the environment from the effects of ionising radiation. Even after five decades of research considerable uncertainty exists as to the interplay of key environmental processes in controlling soil-plant transfer. As many of these processes are, to a lesser or greater extent, climate-dependent, it can be argued that climate/environmental change will impact soil-to-plant transfer of radionuclides and subsequent transfers in specific environments. This discussion attempts to highlight the possible role of climatic and climate-dependent variables in soil-to-plant transfer processes within the overall predictions of climate/environmental change. The work is speculative, and intended to stimulate debate on a theme that radioecology has either ignored or avoided in recent years

Monthly Summaries of the Global Historical Climatology Network - Daily (GHCN-D)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Monthly Summaries of Global Historical Climatology Network (GHCN)-Daily is a dataset derived from GHCN-Daily. The data are produced by computing simple averages or...

Soil! Get the Scoop - The Soil Science Society of America's International Year of Soils Campaign

Science.gov (United States)

Lindbo, David L.; Hopmans, Jan; Olson, Carolyn; Fisk, Susan; Chapman, Susan; van Es, Harold

2015-04-01

Soils are a finite natural resource and are nonrenewable on a human time scale. Soils are the foundation for food, animal feed, fuel and natural fiber production, the supply of clean water, nutrient cycling and a range of ecosystem functions. The area of fertile soils covering the world's surface is limited and increasingly subject to degradation, poor management and loss to urbanization. Increased awareness of the life-supporting functions of soil is called for if this trend is to be reversed and so enable the levels of food production necessary to meet the demands of population levels predicted for 2050. The Soil Science Society of America is coordinating with the Global Soil Partnership and other organizations around the world to celebrate the 2015 International Year of Soils and raise awareness and promote the sustainability of our limited soil resources. We all have a valuable role in communicating vital information on soils, a life sustaining natural resource. Therefore, we will provide resources to learn about soils and help us tell the story of soils. We will promote IYS on social media by sharing our posts from Facebook and Twitter. Additionally SSSA developed 12 monthly themes that reflect the diverse value of soils to our natural environment and society. Each month has information on the theme, a lesson plan, and other outreach activities. All information is available on a dedicated website www.soil.org/IYS. The site will be updated constantly throughout the year.

The global re-cycling of persistent organic pollutants is strongly retarded by soils

Energy Technology Data Exchange (ETDEWEB)

Ockenden, W.A.; Breivik, Knut; Meijer, S.N.; Steinnes, Eiliv; Sweetman, A.J.; Jones, K.C

2003-01-01

C-rich soils of the northern hemisphere appear to be serving as sinks for POPs and preventing their transfer to the Arctic. - 'Persistent organic pollutants' (POPs) are semi-volatile, mobile in the environment and bioaccumulate. Their toxicity and propensity for long-range atmospheric transport (LRAT) has led to international bans/restrictions on their use/release. LRAT of POPs may occur by a 'single hop' or repeated temperature-driven air-surface exchange. It has been hypothesised that this will result in global fractionation and distillation - with condensation and accumulation in polar regions. Polychlorinated biphenyls (PCBs)--industrial chemicals banned/restricted in the 1970s - provide a classic illustration of POP behaviour. A latitudinally-segmented global PCB inventory has been produced, which shows that {approx}86% of the 1.3x10{sup 6} tonnes produced was used in the temperate industrial zone of the northern hemisphere. A global survey of background surface soils gives evidence for 'fractionation' of PCBs. More significantly, however, very little of the total inventory has 'made the journey' via primary emission and/or air-surface exchange and LRAT out of the heavily populated source regions, in the 70 years since PCBs were first produced. Soils generally occlude PCBs, especially soils with dynamic turnover of C/bioturbation/burial mechanisms. This limits the fraction of PCBs available for repeated air-soil exchange. The forested soils of the northern hemisphere, and other C-rich soils, appear to be playing an important role in 'protecting' the Arctic from the advective supply of POPs. Whilst investigations on POPs in remote environments are important, it is imperative that researchers also seek to better understand their release from sources, persistence in source regions, and the significant loss mechanisms/global sinks of these compounds, if they wish to predict future trends.

The global re-cycling of persistent organic pollutants is strongly retarded by soils

International Nuclear Information System (INIS)

Ockenden, W.A.; Breivik, Knut; Meijer, S.N.; Steinnes, Eiliv; Sweetman, A.J.; Jones, K.C.

2003-01-01

C-rich soils of the northern hemisphere appear to be serving as sinks for POPs and preventing their transfer to the Arctic. - 'Persistent organic pollutants' (POPs) are semi-volatile, mobile in the environment and bioaccumulate. Their toxicity and propensity for long-range atmospheric transport (LRAT) has led to international bans/restrictions on their use/release. LRAT of POPs may occur by a 'single hop' or repeated temperature-driven air-surface exchange. It has been hypothesised that this will result in global fractionation and distillation - with condensation and accumulation in polar regions. Polychlorinated biphenyls (PCBs)--industrial chemicals banned/restricted in the 1970s - provide a classic illustration of POP behaviour. A latitudinally-segmented global PCB inventory has been produced, which shows that ∼86% of the 1.3x10 6 tonnes produced was used in the temperate industrial zone of the northern hemisphere. A global survey of background surface soils gives evidence for 'fractionation' of PCBs. More significantly, however, very little of the total inventory has 'made the journey' via primary emission and/or air-surface exchange and LRAT out of the heavily populated source regions, in the 70 years since PCBs were first produced. Soils generally occlude PCBs, especially soils with dynamic turnover of C/bioturbation/burial mechanisms. This limits the fraction of PCBs available for repeated air-soil exchange. The forested soils of the northern hemisphere, and other C-rich soils, appear to be playing an important role in 'protecting' the Arctic from the advective supply of POPs. Whilst investigations on POPs in remote environments are important, it is imperative that researchers also seek to better understand their release from sources, persistence in source regions, and the significant loss mechanisms/global sinks of these compounds, if they wish to predict future trends

The maximum reservoir capacity of soils for persistent organic pollutants: implications for global cycling

International Nuclear Information System (INIS)

Dalla Valle, M.; Jurado, E.; Dachs, J.; Sweetman, A.J.; Jones, K.C.

2005-01-01

The concept of maximum reservoir capacity (MRC), the ratio of the capacities of the surface soil and of the atmospheric mixed layer (AML) to hold chemical under equilibrium conditions, is applied to selected persistent organic pollutants (POPs) in the surface 'skin' (1 mm) of soils. MRC is calculated as a function of soil organic matter (SOM) content and temperature-dependent K OA and mapped globally for selected PCB congeners (PCB-28; -153; -180) and HCB, to identify regions with a higher tendency to retain POPs. It is shown to vary over many orders of magnitude, between compounds, locations and time (seasonally/diurnally). The MRC approach emphasises the very large capacity of soils as a storage compartment for POPs. The theoretical MRC concept is compared to reality and its implications for the global cycling of POPs are discussed. Sharp gradients in soil MRC can exist in mountainous areas and between the land and ocean. Exchanges between oceans and land masses via the atmosphere is likely to be an important driver to the global cycling of these compounds, and net ocean-land transfers could occur in some areas. - Major global terrestrial sinks/stores for POPs are identified and the significance of gradients between them discussed

Simply obtained global radiation, soil temperature and soil moisture in an alley cropping system in semi-arid Kenya

NARCIS (Netherlands)

Mungai, D.N.; Stigter, C.J.; Coulson, C.L.; Ng'ang'a, J.K.

2000-01-01

Global radiation, soil temperature and soil moisture data were obtained from a 4-6 year old Cassia siamea/maize (CM) alley cropping (or hedgerow intercropping) system, at a semi-arid site at Machakos, Kenya, in the late eighties. With the growing need to explore and manage variations in

Estimation of monthly global solar radiation in the eastern Mediterranean region in Turkey by using artificial neural networks

International Nuclear Information System (INIS)

Sahan, Muhittin; Yakut, Emre

2016-01-01

In this study, an artificial neural network (ANN) model was used to estimate monthly average global solar radiation on a horizontal surface for selected 5 locations in Mediterranean region for period of 18 years (1993-2010). Meteorological and geographical data were taken from Turkish State Meteorological Service. The ANN architecture designed is a feed-forward back-propagation model with one-hidden layer containing 21 neurons with hyperbolic tangent sigmoid as the transfer function and one output layer utilized a linear transfer function (purelin). The training algorithm used in ANN model was the Levenberg Marquand back propagation algorith (trainlm). Results obtained from ANN model were compared with measured meteorological values by using statistical methods. A correlation coefficient of 97.97 (~98%) was obtained with root mean square error (RMSE) of 0.852 MJ/m 2 , mean square error (MSE) of 0.725 MJ/m 2 , mean absolute bias error (MABE) 10.659MJ/m 2 , and mean absolute percentage error (MAPE) of 4.8%. Results show good agreement between the estimated and measured values of global solar radiation. We suggest that the developed ANN model can be used to predict solar radiation another location and conditions

Reductions in soil surface albedo as a function of biochar application rate: implications for global radiative forcing

NARCIS (Netherlands)

Verheijen, F.G.A.; Jeffery, S.L.; Velde, te M.; Penizek, V.; Beland, M.; Bastos, A.C.; Keizer, J.J.

2013-01-01

Biochar can be defined as pyrolysed (charred) biomass produced for application to soils with the aim of mitigating global climate change while improving soil functions. Sustainable biochar application to soils has been estimated to reduce global greenhouse gas emissions by 71-130 Pg CO2-C-e over 100

The global mean energy balance under cloud-free conditions

Science.gov (United States)

Wild, Martin; Hakuba, Maria; Folini, Dois; Ott, Patricia; Long, Charles

2017-04-01

A long standing problem of climate models is their overestimation of surface solar radiation not only under all-sky, but also under clear-sky conditions (Wild et al. 1995, Wild et al. 2006). This overestimation reduced over time in consecutive model generations due to the simulation of stronger atmospheric absorption. Here we analyze the clear sky fluxes of the latest climate model generation from the Coupled Model Intercomparison Project Phase 5 (CMIP5) against an expanded and updated set of direct observations from the Baseline Surface Radiation Network (BSRN). Clear sky climatologies from these sites have been composed based on the Long and Ackermann (2000) clear sky detection algorithm (Hakuba et al. 2017), and sampling issues when comparing with model simulated clear sky fluxes have been analyzed in Ott (2017). Overall, the overestimation of clear sky insolation in the CMIP5 models is now merely 1-2 Wm-2 in the multimodel mean, compared to 4 Wm-2 in CMIP3 and 6 Wm-2 in AMIPII (Wild et al. 2006). Still a considerable spread in the individual model biases is apparent, ranging from -2 Wm-2 to 10 Wm-2 when averaged over 53 globally distributed BSRN sites. This bias structure is used to infer best estimates for present day global mean clear sky insolation, following an approach developped in Wild et al. (2013, 2015, Clim. Dyn.) for all sky fluxes. Thereby the flux biases in the various models are linearly related to their respective global means. A best estimate can then be inferred from the linear regression at the intersect where the bias against the surface observations becomes zero. This way we obtain a best estimate of 247 Wm-2 for the global mean insolation at the Earth surface under cloud free conditions, and a global mean absorbed solar radiation of 214 Wm-2 in the cloud-free atmosphere, assuming a global mean surface albedo of 13.5%. Combined with a best estimate for the net influx of solar radiation at the Top of Atmosphere under cloud free conditions

Radioisotope tracer approach for understanding the impacts of global change-induced pedoturbation on soil C dynamics

Science.gov (United States)

Gonzalez-Meler, M. A.; Sturchio, N. C.; Sanchez-de Leon, Y.; Blanc-Betes, E.; Taneva, L.; Poghosyan, A.; Norby, R. J.; Filley, T. R.; Guilderson, T. P.; Welker, J. M.

2010-12-01

Biogeochemical carbon-cycle feedbacks to climate are apparent but uncertain, primarily because of gaps in mechanistic understanding on the ecosystem processes that drive carbon cycling and storage in terrestrial ecosystems, particularly in soils. Recent findings are increasingly recognizing the interaction between soil biota and the soil physical environment. Soil carbon turnover is partly determined by burial of organic matter and its physical and chemical protection. These factors are potentially affected by changes in climate (freezing-thawing or wet-drying cycles) or ecosystem structure including biological invasions. A major impediment to understanding dynamics of soil C in terrestrial systems is our inability to measure soil physical processes such as soil mixing rates or turnover of soil structures, including aggregates. Here we present a multiple radioisotope tracer approach (naturally occurring and man-made) to measure soil mixing rates in response to global change. We will present evidence of soil mixing rate changes in a temperate forest exposed to increased levels of atmospheric CO2 and in a tundra ecosystem exposed to increased thermal insulation. In both cases, radioisotope tracers proved to be an effective way to measure effects of global change on pedoturbation. Results also provided insights into the specific mechanisms involved in the responses. Elevated CO2 resulted in deeper soil mixing cells (increased by about 5cm on average) when compared to control soils as a consequence of changes in biota (increased root growth, higher earthworm density). In the tundra, soil warming induced higher rates of cryoturbation, resulting in what appears to be a net uplift of organic matter to the surface thereby exposing deeper C to decomposers. In both cases, global change factors affected the vertical distribution of C and changed the amount of bulk soil actively involved in soil processes. As a consequence, comparisons of C budgets to a given soil depth in

Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

Science.gov (United States)

DY, C. Y.; Fung, J. C. H.

2016-08-01

A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

Remediation of a heavy metal-contaminated soil by means of agglomeration.

Science.gov (United States)

Polettini, Alessandra; Pomi, Raffaella; Valente, Mattia

2004-01-01

The feasibility of treating a heavy metal-contaminated soil by means of a solidification/stabilization treatment consisting of a granulation process is discussed in the present article. The aim of the study was to attain contaminant immobilization within the agglomerated solid matrix. The soil under concern was characterized by varying levels of heavy metal contamination, ranging from 50 to 500 mg kg(-1) dry soil for chromium. from 300 to 2000 mg kg(-1) dry soil for lead and from 270 to 5000 mg kg(-1) dry soil for copper. An artificially contaminated soil with contaminant concentrations corresponding to the upper level of the mentioned ranges was prepared from a sample of uncontaminated soil by means of spiking experiments. Pure soluble species of chromium, copper and lead. namely CrCl3.6H2O, CuCl2.2H2O and Pb(NO3)2, were selected for the spiking experiments, which were arranged according to a 2(3) full factorial design. The solidification/stabilization treatment was based on an agglomeration process making use of hydraulic binders including Portland cement, hydrated lime and sodium methasilicate, which were selected on the basis of preliminary test runs. It was found that after 7 days of curing the applied treatment was able to efficiently immobilize the investigated heavy metals within the hydrated matrix. Good acid neutralization behavior was also observed, indicating improved matrix resistance to acid attack and decreased potential for metal leaching.

Chemistry of organic carbon in soil with relationship to the global carbon cycle

International Nuclear Information System (INIS)

Post, W.M. III.

1988-01-01

Various ecosystem disturbances alter the balances between production of organic matter and its decomposition and therefore change the amount of carbon in soil. The most severe perturbation is conversion of natural vegetation to cultivated crops. Conversion of natural vegetation to cultivated crops results in a lowered input of slowly decomposing material which causes a reduction in overall carbon levels. Disruption of soil matrix structure by cultivation leads to lowered physical protection of organic matter resulting in an increased net mineralization rate of soil carbon. Climate change is another perturbation that affects the amount and composition of plant production, litter inputs, and decomposition regimes but does not affect soil structure directly. Nevertheless, large changes in soil carbon storage are probable with anticipated CO 2 induced climate change, particularly in northern latitudes where anticipated climate change will be greatest (MacCracken and Luther 1985) and large amounts of soil organic matter are found. It is impossible, given the current state of knowledge of soil organic matter processes and transformations to develop detailed process models of soil carbon dynamics. Largely phenomenological models appear to be developing into predictive tools for understanding the role of soil organic matter in the global carbon cycle. In particular, these models will be useful in quantifying soil carbon changes due to human land-use and to anticipated global climate and vegetation changes. 47 refs., 7 figs., 2 tabs

TOMS/EP UV Reflectivity Daily and Monthly Zonal Means V008

Data.gov (United States)

National Aeronautics and Space Administration — This data product contains TOMS/EP UV Reflectivity Daily and Monthly Zonal Means Version 8 data in ASCII format. (The shortname for this Level-3 Earth Probe TOMS...

Removal of PAHs from contaminated clayey soil by means of electro-osmosis

KAUST Repository

Lima, Ana T.; Kleingeld, Pieter J.; Heister, Katja; Loch, J.P. Gustav

2011-01-01

process that has been used for the mobilization and cleanup of contaminants in clayey soils with varying successes. The present study focuses on the remediation of a contaminated peaty clay soil, located in Olst - the Netherlands, by means of electro

Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks

Science.gov (United States)

Vogel, M. M.; Orth, R.; Cheruy, F.; Hagemann, S.; Lorenz, R.; Hurk, B. J. J. M.; Seneviratne, S. I.

2017-02-01

Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level. We investigate the role of soil moisture-temperature feedbacks for this response based on multimodel experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate processes leading to these changes. We find that soil moisture-temperature feedbacks significantly contribute to the amplified warming of the hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America. Soil moisture trends are more important for this response than short-term soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections.

Mediterranean Agricultural Soil Conservation under global Change: The MASCC project.

Science.gov (United States)

Raclot, Damien; Ciampalini, Rossano

2017-04-01

The MASCC project (2016-2019, http://mascc-project.org) aims to address mitigation and adaptation strategies to global change by assessing current and future development of Mediterranean agricultural soil vulnerability to erosion in relation to projected land use, agricultural practices and climate change. It targets to i) assess the similarities/dissimilarities in dominant factors affecting the current Mediterranean agricultural soil vulnerability by exploring a wide range of Mediterranean contexts; ii) improve the ability to evaluate the impact of extreme events on both the current and projected agricultural soil vulnerability and the sediment delivery at catchment outlet; iii) evaluate the vulnerability and resilience of agricultural production to a combination of potential changes in a wide range of Mediterranean contexts, iv) and provide guidelines on sustainable agricultural conservation strategies adapted to each specific agro-ecosystem and taking into consideration both on- and off-site erosion effects and socio-economics issues. To achieve these objectives, the MASCC project consortium gather researchers from six Mediterranean countries (France, Morocco, Tunisia, Italy, Spain and Portugal) which monitor mid- to long-term environmental catchments and benefit from mutual knowledge created from previous projects and network. The major assets for MASCC are: i) the availability of an unrivalled database on catchment soil erosion and innovative agricultural practices comprising a wide range of Mediterranean contexts, ii) the capacity to better evaluate the impact of extreme events on soil erosion, iii) the expert knowledge of the LANDSOIL model, a catchment-scale integrated approach of the soil-landscape system that enables to simulate both the sediment fluxes at the catchment outlet and the intra-catchment soil evolving properties and iv) the multi-disciplinarity of the involved researchers with an international reputation in the fields of soil science

Monthly hydroclimatology of the continental United States

Science.gov (United States)

Petersen, Thomas; Devineni, Naresh; Sankarasubramanian, A.

2018-04-01

Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly hydroclimatology of ungauged basins using regional parameters.

Miocene Soil Database: Global paleosol and climate maps of the Middle Miocene Thermal Maximum

Science.gov (United States)

Metzger, C. A.

2013-12-01

Paleosols, which record past climatic, biologic, and atmospheric conditions, can be used as a proxy to understand ancient terrestrial landscapes, paleoclimate, and paleoenvironment. In addition, the middle Miocene thermal maximum (~16 Ma) provides an ancient analog for understanding the effects of current and future climate change on soil and ecosystem regimes, as it contains records of shifts similar in magnitude to expected global climate change. The Miocene Soil Database (MSDB) combines new paleosol data from Australia and Argentina with existing and previously uncollated paleosol data from the literature and the Paleobiology Database. These data (n = 507) were then used to derive a paleogeographic map of climatically significant soil types zones during the Middle Miocene. The location of each diagnostic paleosol type (Aridisol, Alfisol, Mollisol, Histosol, Oxisol, and Ultisol) was plotted and compared with the extent of these soil types in the modern environment. The middle Miocene soil map highlights the extension of tropical soils (Oxisols, Ultisols), accompanied by thermophilic flora and fauna, into northern and southern mid-latitudes. Peats, lignites, and Histosols of wetlands were also more abundant at higher latitudes, especially in the northern hemisphere, during the middle Miocene. The paleosol changes reflect that the Middle Miocene was a peak of global soil productivity and carbon sequestration, with replacement of unproductive Aridisols and Gelisols with more productive Oxisols, Alfisols, Mollisols and Histosols. With expansion to include additional data such as soil texture, moisture, or vegetation type, the MSDB has the potential to provide an important dataset for computer models of Miocene climate shifts as well as future land use considerations of soils in times of global change.

Uncertainty in regional and zonal monthly mean downward surface irradiances from Edition 4.0 CERES Energy Balanced and Filled (EBAF) data product

Science.gov (United States)

Kato, S.; Rutan, D. A.; Rose, F. G.; Loeb, N. G.

2017-12-01

The surface of the Earth receives solar radiation (shortwave) and emission from the atmosphere (longwave). At a global and annual mean approximately 12% of solar radiation incident on the surface is reflected and the rest is absorbed by the surface. The surface emits radiation proportional to the forth power of the temperature. Although the uncertainty in global and annual mean surface irradiances is estimated in earlier studies (Zhang et al. 1995, 2004; L'Ecuyer et al. 2008; Stephens et al. 2012; Kato et al. 2012), only a few studies estimated the uncertainty in computed surface irradiances at smaller spatial and temporal scales (Zhang et al. 1995, 2004; Kato et al. 2012). We use surface observations at 46 buoys and 36 land sites and newly released the Edition 4.0 Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF)-surface data product to estimate the uncertainty in regional and zonal monthly mean downward shortwave and longwave surface irradiances. The root-mean-square difference of monthly mean computed and observed irradiances is used for the regional uncertainty. The uncertainty is separated into bias and spatially random components. The random component decreases when irradiances are averaged over a larger area, nearly inversely proportional to the number of surface observation sites. The presentation provides the uncertainty in the regional and zonal monthly mean downward surface irradiances over ocean and land. ReferencesKato, S. and N.G.Loeb, D. A.Rutan, F. G. Rose, S. Sun-Mack,W.F.Miller, and Y. Chen, 2012. Surv. Geophys., 33, 395-412, doi:10.1007/s10712-012-9179-x. L'Ecuyer, T. S., N. B. Wood, T. Haladay, G. L. Stephens, and P. W. Stackhouse Jr., 2008, J. Geophys. Res., 113, D00A15, doi:10.1029/2008JD009951. Stephens, G. L. and Coauthors, 2012, Nat. Geosci., 5, 691-696, doi:10.1038/ngeo1580. Zhang, Y., W. B. Rossow, A. A. Lacis, V. Oinas, and M. I. Mishchenko, 2004, J. Geophys. Res., 109, D19105, doi:10.1029/2003JD

Reductions in soil surface albedo as a function of biochar application rate: implications for global radiative forcing

International Nuclear Information System (INIS)

Verheijen, Frank G A; Bastos, Ana Catarina; Keizer, Jan Jacob; Jeffery, Simon; Van der Velde, Marijn; Penížek, Vít; Beland, Martin

2013-01-01

Biochar can be defined as pyrolysed (charred) biomass produced for application to soils with the aim of mitigating global climate change while improving soil functions. Sustainable biochar application to soils has been estimated to reduce global greenhouse gas emissions by 71–130 Pg CO 2 -C e over 100 years, indicating an important potential to mitigate climate change. However, these estimates ignored changes in soil surface reflection by the application of dark-coloured biochar. Through a laboratory experiment we show a strong tendency for soil surface albedo to decrease as a power decay function with increasing biochar application rate, depending on soil moisture content, biochar application method and land use. Surface application of biochar resulted in strong reductions in soil surface albedo even at relatively low application rates. As a first assessment of the implications for climate change mitigation of these biochar–albedo relationships, we applied a first order global energy balance model to compare negative radiative forcings (from avoided CO 2 emissions) with positive radiative forcings (from reduced soil surface albedos). For a global-scale biochar application equivalent to 120 t ha −1 , we obtained reductions in negative radiative forcings of 5 and 11% for croplands and 11 and 23% for grasslands, when incorporating biochar into the topsoil or applying it to the soil surface, respectively. For a lower global biochar application rate (equivalent to 10 t ha −1 ), these reductions amounted to 13 and 44% for croplands and 28 and 94% for grasslands. Thus, our findings revealed the importance of including changes in soil surface albedo in studies assessing the net climate change mitigation potential of biochar, and we discuss the urgent need for field studies and more detailed spatiotemporal modelling. (letter)

Fungal biogeography. Global diversity and geography of soil fungi.

Science.gov (United States)

Tedersoo, Leho; Bahram, Mohammad; Põlme, Sergei; Kõljalg, Urmas; Yorou, Nourou S; Wijesundera, Ravi; Villarreal Ruiz, Luis; Vasco-Palacios, Aída M; Thu, Pham Quang; Suija, Ave; Smith, Matthew E; Sharp, Cathy; Saluveer, Erki; Saitta, Alessandro; Rosas, Miguel; Riit, Taavi; Ratkowsky, David; Pritsch, Karin; Põldmaa, Kadri; Piepenbring, Meike; Phosri, Cherdchai; Peterson, Marko; Parts, Kaarin; Pärtel, Kadri; Otsing, Eveli; Nouhra, Eduardo; Njouonkou, André L; Nilsson, R Henrik; Morgado, Luis N; Mayor, Jordan; May, Tom W; Majuakim, Luiza; Lodge, D Jean; Lee, Su See; Larsson, Karl-Henrik; Kohout, Petr; Hosaka, Kentaro; Hiiesalu, Indrek; Henkel, Terry W; Harend, Helery; Guo, Liang-dong; Greslebin, Alina; Grelet, Gwen; Geml, Jozsef; Gates, Genevieve; Dunstan, William; Dunk, Chris; Drenkhan, Rein; Dearnaley, John; De Kesel, André; Dang, Tan; Chen, Xin; Buegger, Franz; Brearley, Francis Q; Bonito, Gregory; Anslan, Sten; Abell, Sandra; Abarenkov, Kessy

2014-11-28

Fungi play major roles in ecosystem processes, but the determinants of fungal diversity and biogeographic patterns remain poorly understood. Using DNA metabarcoding data from hundreds of globally distributed soil samples, we demonstrate that fungal richness is decoupled from plant diversity. The plant-to-fungus richness ratio declines exponentially toward the poles. Climatic factors, followed by edaphic and spatial variables, constitute the best predictors of fungal richness and community composition at the global scale. Fungi show similar latitudinal diversity gradients to other organisms, with several notable exceptions. These findings advance our understanding of global fungal diversity patterns and permit integration of fungi into a general macroecological framework. Copyright © 2014, American Association for the Advancement of Science.

Western US high June 2015 temperatures and their relation to global warming and soil moisture

Science.gov (United States)

Philip, Sjoukje Y.; Kew, Sarah F.; Hauser, Mathias; Guillod, Benoit P.; Teuling, Adriaan J.; Whan, Kirien; Uhe, Peter; Oldenborgh, Geert Jan van

2018-04-01

The Western US states Washington (WA), Oregon (OR) and California (CA) experienced extremely high temperatures in June 2015. The temperature anomalies were so extreme that they cannot be explained with global warming alone. We investigate the hypothesis that soil moisture played an important role as well. We use a land surface model and a large ensemble from the weather@home modelling effort to investigate the coupling between soil moisture and temperature in a warming world. Both models show that May was anomalously dry, satisfying a prerequisite for the extreme heat wave, and they indicate that WA and OR are in a wet-to-dry transitional soil moisture regime. We use two different land surface-atmosphere coupling metrics to show that there was strong coupling between temperature, latent heat flux and the effect of soil moisture deficits on the energy balance in June 2015 in WA and OR. June temperature anomalies conditioned on wet/dry conditions show that both the mean and extreme temperatures become hotter for dry soils, especially in WA and OR. Fitting a Gaussian model to temperatures using soil moisture as a covariate shows that the June 2015 temperature values fit well in the extrapolated empirical temperature/drought lines. The high temperature anomalies in WA and OR are thus to be expected, given the dry soil moisture conditions and that those regions are in the transition from a wet to a dry regime. CA is already in the dry regime and therefore the necessity of taking soil moisture into account is of lower importance.

Enzymology under global change: organic nitrogen turnover in alpine and sub-Arctic soils

NARCIS (Netherlands)

Weedon, J.T.; Aerts, R.; Kowalchuk, G.A.; van Bodegom, P.M.

2011-01-01

Understanding global change impacts on the globally important carbon storage in alpine, Arctic and sub-Arctic soils requires knowledge of the mechanisms underlying the balance between plant primary productivity and decomposition. Given that nitrogen availability limits both processes, understanding

Enzymology under global change: organic nitrogen turnover in alpine and sub-Arctic soils.

NARCIS (Netherlands)

Weedon, J.T.; Aerts, R.; Kowalchuk, G.A.; van Bodegom, P.M.

2011-01-01

Understanding global change impacts on the globally important carbon storage in alpine, Arctic and sub-Arctic soils requires knowledge of the mechanisms underlying the balance between plant primary productivity and decomposition. Given that nitrogen availability limits both processes, understanding

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

Science.gov (United States)

Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry

2017-07-01

Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF

Data-mining analysis of the global distribution of soil carbon in observational databases and Earth system models

Science.gov (United States)

Hashimoto, Shoji; Nanko, Kazuki; Ťupek, Boris; Lehtonen, Aleksi

2017-03-01

Future climate change will dramatically change the carbon balance in the soil, and this change will affect the terrestrial carbon stock and the climate itself. Earth system models (ESMs) are used to understand the current climate and to project future climate conditions, but the soil organic carbon (SOC) stock simulated by ESMs and those of observational databases are not well correlated when the two are compared at fine grid scales. However, the specific key processes and factors, as well as the relationships among these factors that govern the SOC stock, remain unclear; the inclusion of such missing information would improve the agreement between modeled and observational data. In this study, we sought to identify the influential factors that govern global SOC distribution in observational databases, as well as those simulated by ESMs. We used a data-mining (machine-learning) (boosted regression trees - BRT) scheme to identify the factors affecting the SOC stock. We applied BRT scheme to three observational databases and 15 ESM outputs from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and examined the effects of 13 variables/factors categorized into five groups (climate, soil property, topography, vegetation, and land-use history). Globally, the contributions of mean annual temperature, clay content, carbon-to-nitrogen (CN) ratio, wetland ratio, and land cover were high in observational databases, whereas the contributions of the mean annual temperature, land cover, and net primary productivity (NPP) were predominant in the SOC distribution in ESMs. A comparison of the influential factors at a global scale revealed that the most distinct differences between the SOCs from the observational databases and ESMs were the low clay content and CN ratio contributions, and the high NPP contribution in the ESMs. The results of this study will aid in identifying the causes of the current mismatches between observational SOC databases and ESM outputs

Statistical modelling of monthly mean sea level at coastal tide gauge stations along the Indian subcontinent

Digital Repository Service at National Institute of Oceanography (India)

Srinivas, K.; Das, V.K.; DineshKumar, P.K.

This study investigates the suitability of statistical models for their predictive potential for the monthly mean sea level at different stations along the west and east coasts of the Indian subcontinent. Statistical modelling of the monthly mean...

The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present)

Science.gov (United States)

Adler, Robert F.; Huffman, George J.; Chang, Alfred; Ferraro, Ralph; Xie, Ping-Ping; Janowiak, John; Rudolf, Bruno; Schneider, Udo; Curtis, Scott; Bolvin, David

2003-01-01

The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The data set is extended back into the premicrowave era (before 1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Precipitation Climatology Project (GPCP) consists of monthly satellite-gauge and associated precipitation error estimates and covers the period January...

Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks

Science.gov (United States)

Vogel, Martha Marie; Orth, René; Cheruy, Frederique; Hagemann, Stefan; Lorenz, Ruth; van den Hurk, Bart; Seneviratne, Sonia Isabelle

2017-04-01

Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level. We investigate here the role of soil moisture-temperature feedbacks for this response based on multi-model experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate physical processes leading to these changes. We find that soil moisture-temperature feedbacks significantly contribute to the amplified warming of hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America and between 42%-52% in Amazonia, Northern Australia and Southern Africa. Soil moisture trends (multi-decadal soil moisture variability) are more important for this response than short-term (e.g. seasonal, interannual) soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections. Vogel, M.M. et al.,2017. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks. Geophysical Research Letters, accepted.

Global retrieval of soil moisture and vegetation properties using data-driven methods

Science.gov (United States)

Rodriguez-Fernandez, Nemesio; Richaume, Philippe; Kerr, Yann

2017-04-01

Data-driven methods such as neural networks (NNs) are a powerful tool to retrieve soil moisture from multi-wavelength remote sensing observations at global scale. In this presentation we will review a number of recent results regarding the retrieval of soil moisture with the Soil Moisture and Ocean Salinity (SMOS) satellite, either using SMOS brightness temperatures as input data for the retrieval or using SMOS soil moisture retrievals as reference dataset for the training. The presentation will discuss several possibilities for both the input datasets and the datasets to be used as reference for the supervised learning phase. Regarding the input datasets, it will be shown that NNs take advantage of the synergy of SMOS data and data from other sensors such as the Advanced Scatterometer (ASCAT, active microwaves) and MODIS (visible and infra red). NNs have also been successfully used to construct long time series of soil moisture from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and SMOS. A NN with input data from ASMR-E observations and SMOS soil moisture as reference for the training was used to construct a dataset sharing a similar climatology and without a significant bias with respect to SMOS soil moisture. Regarding the reference data to train the data-driven retrievals, we will show different possibilities depending on the application. Using actual in situ measurements is challenging at global scale due to the scarce distribution of sensors. In contrast, in situ measurements have been successfully used to retrieve SM at continental scale in North America, where the density of in situ measurement stations is high. Using global land surface models to train the NN constitute an interesting alternative to implement new remote sensing surface datasets. In addition, these datasets can be used to perform data assimilation into the model used as reference for the training. This approach has recently been tested at the European Centre

Responses of soil respiration to soil management changes in an agropastoral ecotone in Inner Mongolia, China.

Science.gov (United States)

Xue, Haili; Tang, Haiping

2018-01-01

Studying the responses of soil respiration ( R s ) to soil management changes is critical for enhancing our understanding of the global carbon cycle and has practical implications for grassland management. Therefore, the objectives of this study were (1) quantify daily and seasonal patterns of R s , (2) evaluate the influence of abiotic factors on R s , and (3) detect the effects of soil management changes on R s . We hypothesized that (1) most of daily and seasonal variation in R s could be explained by soil temperature ( T s ) and soil water content ( S w ), (2) soil management changes could significantly affect R s , and (3) soil management changes affected R s via the significant change in abiotic and biotic factors. In situ R s values were monitored in an agropastoral ecotone in Inner Mongolia, China, during the growing seasons in 2009 (August to October) and 2010 (May to October). The soil management changes sequences included free grazing grassland (FG), cropland (CL), grazing enclosure grassland (GE), and abandoned cultivated grassland (AC). During the growing season in 2010, cumulative R s for FG, CL, GE, and AC averaged 265.97, 344.74, 236.70, and 226.42 gC m -2  year -1 , respectively. The T s and S w significantly influenced R s and explained 66%-86% of the variability in daily R s . Monthly mean temperature and precipitation explained 78%-96% of the variability in monthly R s . The results clearly showed that R s was increased by 29% with the conversion of FG to CL and decreased by 35% and 11% with the conversion of CL to AC and FG to GE. The factors impacting the change in R s under different soil management changes sequences varied. Our results confirm the tested hypotheses. The increase in Q 1 0 and litter biomass induced by conversion of FG to GE could lead to increased R s if the climate warming. We suggest that after proper natural restoration period, grasslands should be utilized properly to decrease R s .

Time series modelling of global mean temperature for managerial decision-making.

Science.gov (United States)

Romilly, Peter

2005-07-01

Climate change has important implications for business and economic activity. Effective management of climate change impacts will depend on the availability of accurate and cost-effective forecasts. This paper uses univariate time series techniques to model the properties of a global mean temperature dataset in order to develop a parsimonious forecasting model for managerial decision-making over the short-term horizon. Although the model is estimated on global temperature data, the methodology could also be applied to temperature data at more localised levels. The statistical techniques include seasonal and non-seasonal unit root testing with and without structural breaks, as well as ARIMA and GARCH modelling. A forecasting evaluation shows that the chosen model performs well against rival models. The estimation results confirm the findings of a number of previous studies, namely that global mean temperatures increased significantly throughout the 20th century. The use of GARCH modelling also shows the presence of volatility clustering in the temperature data, and a positive association between volatility and global mean temperature.

Effects of Recent Regional Soil Moisture Variability on Global Net Ecosystem CO2 Exchange

Science.gov (United States)

Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.

2017-12-01

Soil moisture exerts a major regional control on the inter-annual variability of the global land sink for atmospheric CO2. In semi-arid regions, annual biomass production is closely coupled to variability in soil moisture availability, while in cold-season-affected regions, summer drought offsets the effects of advancing spring phenology. Availability of satellite solar-induced fluorescence (SIF) observations and improvements in atmospheric inversions has led to unprecedented ability to monitor atmospheric sink strength. However, discrepancies still exist between such top-down estimates as atmospheric inversion and bottom-up process and satellite driven models, indicating that relative strength, mechanisms, and interaction of driving factors remain poorly understood. We use soil moisture fields informed by Soil Moisture Active Passive Mission (SMAP) observations to compare recent (2015-2017) and historic (2000-2014) variability in net ecosystem land-atmosphere CO2 exchange (NEE). The operational SMAP Level 4 Carbon (L4C) product relates ground-based flux tower measurements to other bottom-up and global top-down estimates to underlying soil moisture and other driving conditions using data-assimilation-based SMAP Level 4 Soil Moisture (L4SM). Droughts in coastal Brazil, South Africa, Eastern Africa, and an anomalous wet period in Eastern Australia were observed by L4C. A seasonal seesaw pattern of below-normal sink strength at high latitudes relative to slightly above-normal sink strength for mid-latitudes was also observed. Whereas SMAP-based soil moisture is relatively informative for short-term temporal variability, soil moisture biases that vary in space and with season constrain the ability of the L4C estimates to accurately resolve NEE. Such biases might be caused by irrigation and plant-accessible ground-water. Nevertheless, SMAP L4C daily NEE estimates connect top-down estimates to variability of effective driving factors for accurate estimates of regional-to-global

Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties

Science.gov (United States)

Astitha, M.; Lelieveld, J.; Abdel Kader, M.; Pozzer, A.; de Meij, A.

2012-11-01

Airborne desert dust influences radiative transfer, atmospheric chemistry and dynamics, as well as nutrient transport and deposition. It directly and indirectly affects climate on regional and global scales. Two versions of a parameterization scheme to compute desert dust emissions are incorporated into the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry). One uses a globally uniform soil particle size distribution, whereas the other explicitly accounts for different soil textures worldwide. We have tested these two versions and investigated the sensitivity to input parameters, using remote sensing data from the Aerosol Robotic Network (AERONET) and dust concentrations and deposition measurements from the AeroCom dust benchmark database (and others). The two versions are shown to produce similar atmospheric dust loads in the N-African region, while they deviate in the Asian, Middle Eastern and S-American regions. The dust outflow from Africa over the Atlantic Ocean is accurately simulated by both schemes, in magnitude, location and seasonality. Approximately 70% of the modelled annual deposition data and 70-75% of the modelled monthly aerosol optical depth (AOD) in the Atlantic Ocean stations lay in the range 0.5 to 2 times the observations for all simulations. The two versions have similar performance, even though the total annual source differs by ~50%, which underscores the importance of transport and deposition processes (being the same for both versions). Even though the explicit soil particle size distribution is considered more realistic, the simpler scheme appears to perform better in several locations. This paper discusses the differences between the two versions of the dust emission scheme, focusing on their limitations and strengths in describing the global dust cycle and suggests possible future improvements.

Parameterization of dust emissions in the global atmospheric chemistry-climate model EMAC: impact of nudging and soil properties

Directory of Open Access Journals (Sweden)

M. Astitha

2012-11-01

Full Text Available Airborne desert dust influences radiative transfer, atmospheric chemistry and dynamics, as well as nutrient transport and deposition. It directly and indirectly affects climate on regional and global scales. Two versions of a parameterization scheme to compute desert dust emissions are incorporated into the atmospheric chemistry general circulation model EMAC (ECHAM5/MESSy2.41 Atmospheric Chemistry. One uses a globally uniform soil particle size distribution, whereas the other explicitly accounts for different soil textures worldwide. We have tested these two versions and investigated the sensitivity to input parameters, using remote sensing data from the Aerosol Robotic Network (AERONET and dust concentrations and deposition measurements from the AeroCom dust benchmark database (and others. The two versions are shown to produce similar atmospheric dust loads in the N-African region, while they deviate in the Asian, Middle Eastern and S-American regions. The dust outflow from Africa over the Atlantic Ocean is accurately simulated by both schemes, in magnitude, location and seasonality. Approximately 70% of the modelled annual deposition data and 70–75% of the modelled monthly aerosol optical depth (AOD in the Atlantic Ocean stations lay in the range 0.5 to 2 times the observations for all simulations. The two versions have similar performance, even though the total annual source differs by ~50%, which underscores the importance of transport and deposition processes (being the same for both versions. Even though the explicit soil particle size distribution is considered more realistic, the simpler scheme appears to perform better in several locations. This paper discusses the differences between the two versions of the dust emission scheme, focusing on their limitations and strengths in describing the global dust cycle and suggests possible future improvements.

Is the global mean temperature trend too low?

Science.gov (United States)

Venema, Victor; Lindau, Ralf

2015-04-01

The global mean temperature trend may be biased due to similar technological and economic developments worldwide. In this study we want to present a number of recent results that suggest that the global mean temperature trend might be steeper as generally thought. In the Global Historical Climate Network version 3 (GHCNv3) the global land surface temperature is estimated to have increased by about 0.8°C between 1880 and 2012. In the raw temperature record, the increase is 0.6°C; the 0.2°C difference is due to homogenization adjustments. Given that homogenization can only reduce biases, this 0.2°C stems from a partial correction of bias errors and it seems likely that the real non-climatic trend bias will be larger. Especially in regions with sparser networks, homogenization will not be able to improve the trend much. Thus if the trend bias in these regions is similar to the bias for more dense networks (industrialized countries), one would expect the real bias to be larger. Stations in sparse networks are representative for a larger region and are given more weight in the computation of the global mean temperature. If all stations are given equal weight, the homogenization adjustments of the GHCNv3 dataset are about 0.4°C per century. In the subdaily HadISH dataset one break with mean size 0.12°C is found every 15 years for the period 1973-2013. That would be a trend bias of 0.78°C per century on a station by station basis. Unfortunately, these estimates strongly focus on Western countries having more stations. It is known from the literature that rich countries have a (statistically insignificant) stronger trend in the global datasets. Regional datasets can be better homogenized than global ones, the main reason being that global datasets do not contain all stations known to the weather services. Furthermore, global datasets use automatic homogenization methods and have less or no metadata. Thus while regional data can be biased themselves, comparing them

Prediction of mean monthly river discharges in Colombia through Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

A. M. Carmona

2015-04-01

Full Text Available The hydro-climatology of Colombia exhibits strong natural variability at a broad range of time scales including: inter-decadal, decadal, inter-annual, annual, intra-annual, intra-seasonal, and diurnal. Diverse applied sectors rely on quantitative predictions of river discharges for operational purposes including hydropower generation, agriculture, human health, fluvial navigation, territorial planning and management, risk preparedness and mitigation, among others. Various methodologies have been used to predict monthly mean river discharges that are based on "Predictive Analytics", an area of statistical analysis that studies the extraction of information from historical data to infer future trends and patterns. Our study couples the Empirical Mode Decomposition (EMD with traditional methods, e.g. Autoregressive Model of Order 1 (AR1 and Neural Networks (NN, to predict mean monthly river discharges in Colombia, South America. The EMD allows us to decompose the historical time series of river discharges into a finite number of intrinsic mode functions (IMF that capture the different oscillatory modes of different frequencies associated with the inherent time scales coexisting simultaneously in the signal (Huang et al. 1998, Huang and Wu 2008, Rao and Hsu, 2008. Our predictive method states that it is easier and simpler to predict each IMF at a time and then add them up together to obtain the predicted river discharge for a certain month, than predicting the full signal. This method is applied to 10 series of monthly mean river discharges in Colombia, using calibration periods of more than 25 years, and validation periods of about 12 years. Predictions are performed for time horizons spanning from 1 to 12 months. Our results show that predictions obtained through the traditional methods improve when the EMD is used as a previous step, since errors decrease by up to 13% when the AR1 model is used, and by up to 18% when using Neural Networks is

Are there links between responses of soil microbes and ecosystem functioning to elevated CO2, N deposition and warming? A global perspective.

Science.gov (United States)

García-Palacios, Pablo; Vandegehuchte, Martijn L; Shaw, E Ashley; Dam, Marie; Post, Keith H; Ramirez, Kelly S; Sylvain, Zachary A; de Tomasel, Cecilia Milano; Wall, Diana H

2015-04-01

In recent years, there has been an increase in research to understand how global changes' impacts on soil biota translate into altered ecosystem functioning. However, results vary between global change effects, soil taxa, and ecosystem processes studied, and a synthesis of relationships is lacking. Therefore, here we initiate such a synthesis to assess whether the effect size of global change drivers (elevated CO2, N deposition, and warming) on soil microbial abundance is related with the effect size of these drivers on ecosystem functioning (plant biomass, soil C cycle, and soil N cycle) using meta-analysis and structural equation modeling. For N deposition and warming, the global change effect size on soil microbes was positively associated with the global change effect size on ecosystem functioning, and these relationships were consistent across taxa and ecosystem processes. However, for elevated CO2, such links were more taxon and ecosystem process specific. For example, fungal abundance responses to elevated CO2 were positively correlated with those of plant biomass but negatively with those of the N cycle. Our results go beyond previous assessments of the sensitivity of soil microbes and ecosystem processes to global change, and demonstrate the existence of general links between the responses of soil microbial abundance and ecosystem functioning. Further we identify critical areas for future research, specifically altered precipitation, soil fauna, soil community composition, and litter decomposition, that are need to better quantify the ecosystem consequences of global change impacts on soil biodiversity. © 2014 John Wiley & Sons Ltd.

A global map of mangrove forest soil carbon at 30 m spatial resolution

Science.gov (United States)

Sanderman, Jonathan; Hengl, Tomislav; Fiske, Greg; Solvik, Kylen; Adame, Maria Fernanda; Benson, Lisa; Bukoski, Jacob J.; Carnell, Paul; Cifuentes-Jara, Miguel; Donato, Daniel; Duncan, Clare; Eid, Ebrahem M.; Ermgassen, Philine zu; Ewers Lewis, Carolyn J.; Macreadie, Peter I.; Glass, Leah; Gress, Selena; Jardine, Sunny L.; Jones, Trevor G.; Ndemem Nsombo, Eugéne; Mizanur Rahman, Md; Sanders, Christian J.; Spalding, Mark; Landis, Emily

2018-05-01

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m‑3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha‑1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

Soil erosion, climate change and global food security: challenges and strategies.

Science.gov (United States)

Rhodes, Christopher J

2014-01-01

An overview is presented of the determined degree of global land degradation (principally occurring through soil erosion), with some consideration of its possible impact on global food security. Most determinations of the extent of land degradation (e.g. GLASOD) have been made on the basis of "expert judgement" and perceptions, as opposed to direct measurements of this multifactorial phenomenon. More recently, remote sensing measurements have been made which indicate that while some regions of the Earth are "browning" others are "greening". The latter effect is thought to be due to fertilisation of the growth of biomass by increasing levels of atmospheric CO2, and indeed the total amount of global biomass was observed to increase by 3.8% during the years 1981-2003. Nonetheless, 24% of the Earth's surface had occasioned some degree of degradation in the same time period. It appears that while long-term trends in NDVI (normalised difference vegetation index) derivatives are only broad indicators of land degradation, taken as a proxy, the NDVI/NPP (net primary productivity) trend is able to yield a benchmark that is globally consistent and to illuminate regions in which biologically significant changes are occurring. Thus, attention may be directed to where investigation and action at the ground level is required, i.e. to potential "hot spots" of land degradation and/or erosion. The severity of land degradation through soil erosion, and an according catastrophic threat to the survival of humanity may in part have been overstated, although the rising human population will impose inexorable demands for what the soil can provide. However the present system of industrialised agriculture would not be possible without plentiful provisions of cheap crude oil and natural gas to supply fuels, pesticides, herbicides and fertilisers. It is only on the basis of these inputs that it has been possible for the human population to rise above 7 billion. Hence, if the cheap oil and gas

European Atlas of Soil Biodiversity

DEFF Research Database (Denmark)

Krogh (contributor), Paul Henning

Soil is one of the fundamental components for supporting life on Earth. Most ecosystem processes and global functions that occur within soil are driven by living organisms that, in turn, sustain life above ground. However, despite the fact that soils are home to a quarter of all living species on...... Biodiversity is an essential reference to the many and varied aspects of soil. The overall goal of this work is to convey the fundamental necessity to safeguard soil biodiversity in order to guarantee life on this planet.......Soil is one of the fundamental components for supporting life on Earth. Most ecosystem processes and global functions that occur within soil are driven by living organisms that, in turn, sustain life above ground. However, despite the fact that soils are home to a quarter of all living species...... on Earth, life within the soil is often hidden away and suffers by being 'out of sight and out of mind'. What kind of life is there in soil? What do we mean by soil biodiversity? What is special about soil biology? How do our activities affect soil ecosystems? What are the links between soil biota...

Climate and soil attributes determine plant species turnover in global drylands.

Science.gov (United States)

Ulrich, Werner; Soliveres, Santiago; Maestre, Fernando T; Gotelli, Nicholas J; Quero, José L; Delgado-Baquerizo, Manuel; Bowker, Matthew A; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R; Hernández, Rosa M; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A; Raveh, Eran; Romão, Roberto L; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2014-12-01

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate

Climate and soil attributes determine plant species turnover in global drylands

Science.gov (United States)

Maestre, Fernando T.; Gotelli, Nicholas J.; Quero, José L.; Delgado-Baquerizo, Manuel; Bowker, Matthew A.; Eldridge, David J.; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I.; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R.; Hernández, Rosa M.; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L.; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A.; Raveh, Eran; Romão, Roberto L.; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2015-01-01

Aim Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. Location 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Methods Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake’s beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R2)), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Results Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R2)) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Main conclusions Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These

Global carbon sequestration in tidal, saline wetland soils

Science.gov (United States)

Chmura, G.L.; Anisfeld, S.C.; Cahoon, D.R.; Lynch, J.C.

2003-01-01

Wetlands represent the largest component of the terrestrial biological carbon pool and thus play an important role in global carbon cycles. Most global carbon budgets, however, have focused on dry land ecosystems that extend over large areas and have not accounted for the many small, scattered carbon-storing ecosystems such as tidal saline wetlands. We compiled data for 154 sites in mangroves and salt marshes from the western and eastern Atlantic and Pacific coasts, as well as the Indian Ocean, Mediterranean Ocean, and Gulf of Mexico. The set of sites spans a latitudinal range from 22.4??S in the Indian Ocean to 55.5??N in the northeastern Atlantic. The average soil carbon density of mangrove swamps (0.055 ?? 0.004 g cm-3) is significantly higher than the salt marsh average (0.039 ?? 0.003 g cm-3). Soil carbon density in mangrove swamps and Spartina patens marshes declines with increasing average annual temperature, probably due to increased decay rates at higher temperatures. In contrast, carbon sequestration rates were not significantly different between mangrove swamps and salt marshes. Variability in sediment accumulation rates within marshes is a major control of carbon sequestration rates masking any relationship with climatic parameters. Globally, these combined wetlands store at least 44.6 Tg C yr-1 and probably more, as detailed areal inventories are not available for salt marshes in China and South America. Much attention has been given to the role of freshwater wetlands, particularly northern peatlands, as carbon sinks. In contrast to peatlands, salt marshes and mangroves release negligible amounts of greenhouse gases and store more carbon per unit area. Copyright 2003 by the American Geophysical Union.

Sovereignty, globalization and the constitution of meaning

Directory of Open Access Journals (Sweden)

Farid Samir Benavides Vanegas

2015-06-01

Full Text Available In this essay I wish to show how law’s and the nation’s loss of sovereignty have meant the emergence of new sites of identity construction and how these new identities have become global due to the loss of centrality of the nation state as a place of meaning production. By analyzing the concept of sovereignty and its relation to the power of naming held by the State, and exercised through the law, I want to show how in a society of the spectacle that power is removed from the State and given to other places that can ensure passivity of viewers and thus the absence of resistance in the construction of meaning. This I will do by analyzing a Colombian soap opera and its handling of the concept of corruption to show legal meaning was overtaken by the one built in the media.

Soil Temperature Manipulation to Study Global Warming Effects in Arable Land

DEFF Research Database (Denmark)

Patil, R H; Laegdsmand, M; Olesen, Jørgen E

2013-01-01

in a plough layer. Temperature sensors were placed at 0.05, 0.1 and 0.25 m depths in soil, and 0.1 m above the soil surface in all plots, which were connected to an automated data logger. Soil-warming setup was able to maintain a mean seasonal temperature difference of 5.0 ± 0.005℃ between heated and control......-ground vegetation response as this method heats only the soil. Therefore, using infrared heaters seems to represent natural climate warming (both air and soil) much more closely and may be used for future climate manipulation field studies....

Soil temperature manipulation to study global warming effects in arable land

DEFF Research Database (Denmark)

Patil, Raveendra H.; Laegdsmand, Mette; Olesen, Jørgen Eivind

2013-01-01

in a plough layer. Temperature sensors were placed at 0.05, 0.1 and 0.25 m depths in soil, and 0.1 m above the soil surface in all plots, which were connected to an automated data logger. Soil-warming setup was able to maintain a mean seasonal temperature difference of 5.0 ± 0.005 oC between heated...... that of above-ground vegetation response as this method heats only the soil. Therefore, using infrared heaters seems to represent natural climate warming (both air and soil) much more closely and may be used for future climate manipulation field studies....

Monthly mean wind stress along the coast of the north Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Shetye, S.R.; Shenoi, S.S.C.; Antony, M.K.; Krishnakumar, V.

Monthly-mean wind stress and its longshore and offshore components have been computed using the bulk aerodynamic method for each of a string of 36 two-degree-latitude by two-degree-longitude squares along the coast of the north Indian Ocean...

Regionalization of monthly rainfall erosivity patternsin Switzerland

Science.gov (United States)

Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

2016-10-01

One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of

Scale-dependency of the global mean surface temperature trend and its implication for the recent hiatus of global warming.

Science.gov (United States)

Lin, Yong; Franzke, Christian L E

2015-08-11

Studies of the global mean surface temperature trend are typically conducted at a single (usually annual or decadal) time scale. The used scale does not necessarily correspond to the intrinsic scales of the natural temperature variability. This scale mismatch complicates the separation of externally forced temperature trends from natural temperature fluctuations. The hiatus of global warming since 1999 has been claimed to show that human activities play only a minor role in global warming. Most likely this claim is wrong due to the inadequate consideration of the scale-dependency in the global surface temperature (GST) evolution. Here we show that the variability and trend of the global mean surface temperature anomalies (GSTA) from January 1850 to December 2013, which incorporate both land and sea surface data, is scale-dependent and that the recent hiatus of global warming is mainly related to natural long-term oscillations. These results provide a possible explanation of the recent hiatus of global warming and suggest that the hiatus is only temporary.

Scanning Multichannel Microwave Radiometer (SMMR) Monthly Mean Atmospheric Liquid Water (ALW) By Prabhakara

Data.gov (United States)

National Aeronautics and Space Administration — SMMR_ALW_PRABHAKARA data are Special Multichannel Microwave Radiometer (SMMR) Monthly Mean Atmospheric Liquid Water (ALW) data by Prabhakara.The Prabhakara Scanning...

The importance of 'global meaning' for people rehabilitating from spinal cord injury.

Science.gov (United States)

Littooij, E; Leget, C J W; Stolwijk-Swüste, J M; Doodeman, S; Widdershoven, G A M; Dekker, J

2016-11-01

Qualitative study. To explore whether aspects of global meaning (that is, fundamental beliefs and life goals concerning core values, relationships, worldview, identity and inner posture) are associated with processes and outcomes in rehabilitation, as experienced by people with spinal cord injury (SCI). People living in the community receiving outpatient rehabilitation in a Dutch rehabilitation center. In-depth semi-structured interviews were conducted with 16 people with SCI. Interviews were analyzed using qualitative research methods: structural and provisional coding. Core values, relationships, worldview, identity and inner posture (that is, the way in which people relate to the facts of life) were associated with various processes and outcomes of rehabilitation. Elements of the rehabilitation process included motivation, regulation of emotion, making decisions and handling stress. Elements of the outcome of rehabilitation included physical functioning, emotional functioning, social functioning and subjective sense of meaning. The influence was positive, with the exception of one case in which worldview and inner posture were negatively associated with motivation. Besides that, respondents emphasized the importance of rehabilitation professionals attuning to their global meaning. All aspects of global meaning were positively associated with various processes and outcomes of rehabilitation. It is recommended that rehabilitation professionals are aware of the importance of global meaning to people with SCI and that they take people's fundamental beliefs and life goals into account.

Meteoric 10Be in soil profiles - A global meta-analysis

Science.gov (United States)

Graly, Joseph A.; Bierman, Paul R.; Reusser, Lucas J.; Pavich, Milan J.

2010-01-01

In order to assess current understanding of meteoric 10Be dynamics and distribution in terrestrial soils, we assembled a database of all published meteoric 10Be soil depth profiles, including 104 profiles from 27 studies in globally diverse locations, collectively containing 679 individual measurements. This allows for the systematic comparison of meteoric 10Be concentration to other soil characteristics and the comparison of profile depth distributions between geologic settings. Percent clay, 9Be, and dithionite-citrate extracted Al positively correlate to meteoric 10Be in more than half of the soils where they were measured, but the lack of significant correlation in other soils suggests that no one soil factor controls meteoric 10Be distribution with depth. Dithionite-citrate extracted Fe and cation exchange capacity are only weakly correlated to meteoric 10Be. Percent organic carbon and pH are not significantly related to meteoric 10Be concentration when all data are complied.The compilation shows that meteoric 10Be concentration is seldom uniform with depth in a soil profile. In young or rapidly eroding soils, maximum meteoric 10Be concentrations are typically found in the uppermost 20 cm. In older, more slowly eroding soils, the highest meteoric 10Be concentrations are found at depth, usually between 50 and 200 cm. We find that the highest measured meteoric 10Be concentration in a soil profile is an important metric, as both the value and the depth of the maximum meteoric 10Be concentration correlate with the total measured meteoric 10Be inventory of the soil profile.In order to refine the use of meteoric 10Be as an estimator of soil erosion rate, we compare near-surface meteoric 10Be concentrations to total meteoric 10Be soil inventories. These trends are used to calibrate models of meteoric 10Be loss by soil erosion. Erosion rates calculated using this method vary based on the assumed depth and timing of erosional events and on the reference data selected.

Toxicity of a metal(loid)-polluted agricultural soil to Enchytraeus crypticus changes under a global warming perspective: Variations in air temperature and soil moisture content

NARCIS (Netherlands)

Gonzalez Alcaraz, M.N.; van Gestel, C.A.M.

2016-01-01

This study aimed to assess how the current global warming perspective, with increasing air temperature (20 °C vs. 25 °C) and decreasing soil moisture content (50% vs. 30% of the soil water holding capacity, WHC), affected the toxicity of a metal(loid)-polluted agricultural soil to Enchytraeus

Offsetting global warming-induced elevated greenhouse gas emissions from an arable soil by biochar application.

Science.gov (United States)

Bamminger, Chris; Poll, Christian; Marhan, Sven

2018-01-01

Global warming will likely enhance greenhouse gas (GHG) emissions from soils. Due to its slow decomposability, biochar is widely recognized as effective in long-term soil carbon (C) sequestration and in mitigation of soil GHG emissions. In a long-term soil warming experiment (+2.5 °C, since July 2008) we studied the effect of applying high-temperature Miscanthus biochar (0, 30 t/ha, since August 2013) on GHG emissions and their global warming potential (GWP) during 2 years in a temperate agroecosystem. Crop growth, physical and chemical soil properties, temperature sensitivity of soil respiration (R s ), and metabolic quotient (qCO 2 ) were investigated to yield further information about single effects of soil warming and biochar as well as on their interactions. Soil warming increased total CO 2 emissions by 28% over 2 years. The effect of warming on soil respiration did not level off as has often been observed in less intensively managed ecosystems. However, the temperature sensitivity of soil respiration was not affected by warming. Overall, biochar had no effect on most of the measured parameters, suggesting its high degradation stability and its low influence on microbial C cycling even under elevated soil temperatures. In contrast, biochar × warming interactions led to higher total N 2 O emissions, possibly due to accelerated N-cycling at elevated soil temperature and to biochar-induced changes in soil properties and environmental conditions. Methane uptake was not affected by soil warming or biochar. The incorporation of biochar-C into soil was estimated to offset warming-induced elevated GHG emissions for 25 years. Our results highlight the suitability of biochar for C sequestration in cultivated temperate agricultural soil under a future elevated temperature. However, the increased N 2 O emissions under warming limit the GHG mitigation potential of biochar. © 2017 John Wiley & Sons Ltd.

FUNGAL BIOGEOGRAPHY. Comment on "Global diversity and geography of soil fungi".

Science.gov (United States)

Schadt, Christopher W; Rosling, Anna

2015-06-26

Tedersoo et al. (Research Article, 28 November 2014, p. 1078) present a compelling study regarding patterns of biodiversity of fungi, carried out at a scale unprecedented to date for fungal biogeographical studies. The study demonstrates strong global biogeographic patterns in richness and community composition of soil fungi. What concerns us with the study is what we do not see. Unfortunately, this study underestimates the fungal diversity of one key group of soil fungi due to reliance on a single primer with known flaws. Copyright © 2015, American Association for the Advancement of Science.

The global kernel k-means algorithm for clustering in feature space.

Science.gov (United States)

Tzortzis, Grigorios F; Likas, Aristidis C

2009-07-01

Kernel k-means is an extension of the standard k -means clustering algorithm that identifies nonlinearly separable clusters. In order to overcome the cluster initialization problem associated with this method, we propose the global kernel k-means algorithm, a deterministic and incremental approach to kernel-based clustering. Our method adds one cluster at each stage, through a global search procedure consisting of several executions of kernel k-means from suitable initializations. This algorithm does not depend on cluster initialization, identifies nonlinearly separable clusters, and, due to its incremental nature and search procedure, locates near-optimal solutions avoiding poor local minima. Furthermore, two modifications are developed to reduce the computational cost that do not significantly affect the solution quality. The proposed methods are extended to handle weighted data points, which enables their application to graph partitioning. We experiment with several data sets and the proposed approach compares favorably to kernel k -means with random restarts.

Modeling soil organic carbon dynamics and their driving factors in the main global cereal cropping systems

Science.gov (United States)

Wang, Guocheng; Zhang, Wen; Sun, Wenjuan; Li, Tingting; Han, Pengfei

2017-10-01

Changes in the soil organic carbon (SOC) stock are determined by the balance between the carbon input from organic materials and the output from the decomposition of soil C. The fate of SOC in cropland soils plays a significant role in both sustainable agricultural production and climate change mitigation. The spatiotemporal changes of soil organic carbon in croplands in response to different carbon (C) input management and environmental conditions across the main global cereal systems were studied using a modeling approach. We also identified the key variables that drive SOC changes at a high spatial resolution (0.1° × 0.1°) and over a long timescale (54 years from 1961 to 2014). A widely used soil C turnover model (RothC) and state-of-the-art databases of soil and climate variables were used in the present study. The model simulations suggested that, on a global average, the cropland SOC density increased at annual rates of 0.22, 0.45 and 0.69 Mg C ha-1 yr-1 under crop residue retention rates of 30, 60 and 90 %, respectively. Increasing the quantity of C input could enhance soil C sequestration or reduce the rate of soil C loss, depending largely on the local soil and climate conditions. Spatially, under a specific crop residue retention rate, relatively higher soil C sinks were found across the central parts of the USA, western Europe, and the northern regions of China. Relatively smaller soil C sinks occurred in the high-latitude regions of both the Northern and Southern hemispheres, and SOC decreased across the equatorial zones of Asia, Africa and America. We found that SOC change was significantly influenced by the crop residue retention rate (linearly positive) and the edaphic variable of initial SOC content (linearly negative). Temperature had weak negative effects, and precipitation had significantly negative impacts on SOC changes. The results can help guide carbon input management practices to effectively mitigate climate change through soil C

Spatiotemporal models of global soil organic carbon stock to support land degradation assessments at regional and global scales: limitations, challenges and opportunities

Science.gov (United States)

Hengl, Tomislav; Heuvelink, Gerard; Sanderman, Jonathan; MacMillan, Robert

2017-04-01

There is an increasing interest in fitting and applying spatiotemporal models that can be used to assess and monitor soil organic carbon stocks (SOCS), for example, in support of the '4 pourmille' initiative aiming at soil carbon sequestration towards climate change adaptation and mitigation and UN's Land Degradation Neutrality indicators and similar degradation assessment projects at regional and global scales. The land cover mapping community has already produced several spatiotemporal data sets with global coverage and at relatively fine resolution e.g. USGS MODIS land cover annual maps for period 2000-2014; European Space Agency land cover maps at 300 m resolution for the year 2000, 2005 and 2010; Chinese GlobeLand30 dataset available for years 2000 and 2010; Columbia University's WRI GlobalForestWatch with deforestation maps at 30 m resolution for the period 2000-2016 (Hansen et al. 2013). These data sets can be used for land degradation assessment and scenario testing at global and regional scales (Wei et al 2014). Currently, however, no compatible global spatiotemporal data sets exist on status of soil quality and/or soil health (Powlson et al. 2013). This paper describes an initial effort to devise and evaluate a procedure for mapping spatio-temporal changes in SOC stocks using a complete stack of soil forming factors (climate, relief, land cover, land use, lithology and living organisms) represented mainly through remote sensing based time series of Earth images. For model building we used some 75,000 geo-referenced soil profiles and a stacks space-time covariates (land cover, land use, biomass, climate) at two standard resolutions: (1) 10 km resolution with data available for period 1920-2014 and (2) 1000 m resolution with data available for period 2000-2014. The initial results show that, although it is technically feasible to produce space time estimates of SOCS that demonstrate the procedure, the estimates are relatively uncertain (<45% of variation

Improved Ground Hydrology Calculations for Global Climate Models (GCMs): Soil Water Movement and Evapotranspiration.

Science.gov (United States)

Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

1988-09-01

A physically based ground hydrology model is developed to improve the land-surface sensible and latent heat calculations in global climate models (GCMs). The processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff are explicitly included in the model. The amount of detail in the hydrologic calculations is restricted to a level appropriate for use in a GCM, but each of the aforementioned processes is modeled on the basis of the underlying physical principles. Data from the Goddard Institute for Space Studies (GISS) GCM are used as inputs for off-line tests of the ground hydrology model in four 8° × 10° regions (Brazil, Sahel, Sahara, and India). Soil and vegetation input parameters are calculated as area-weighted means over the 8° × 10° gridhox. This compositing procedure is tested by comparing resulting hydrological quantities to ground hydrology model calculations performed on the 1° × 1° cells which comprise the 8° × 10° gridbox. Results show that the compositing procedure works well except in the Sahel where lower soil water levels and a heterogeneous land surface produce more variability in hydrological quantities, indicating that a resolution better than 8° × 10° is needed for that region. Modeled annual and diurnal hydrological cycles compare well with observations for Brazil, where real world data are available. The sensitivity of the ground hydrology model to several of its input parameters was tested; it was found to be most sensitive to the fraction of land covered by vegetation and least sensitive to the soil hydraulic conductivity and matric potential.

Improved representations of coupled soil-canopy processes in the CABLE land surface model (Subversion revision 3432)

Science.gov (United States)

Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; Harman, Ian N.

2016-09-01

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil-canopy processes by introducing an alternative hydrology model with a physically accurate representation of coupled energy and water fluxes at the soil-air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.

Towards a global understanding of vertical soil carbon dynamics: meta-analysis of soil 14C data

Science.gov (United States)

hatte, C.; Balesdent, J.; Guiot, J.

2012-12-01

Soil represents the largest terrestrial storage mechanism for atmospheric carbon from photosynthesis, with estimates ranging from 1600 Pg C within the top 1 meter to 2350 Pg C for the top 3 meters. These values are at least 2.5 times greater than atmospheric C pools. Small changes in soil organic carbon storage could result in feedback to atmospheric CO2 and the sensitivity of soil organic matter to changes in temperature, and precipitation remains a critical area of research with respect to the global carbon cycle. As an intermediate storage mechanism for organic material through time, the vertical profile of carbon generally shows an age continuum with depth. Radiocarbon provides critical information for understanding carbon exchanges between soils and atmosphere, and within soil layers. Natural and "bomb" radiocarbon has been used to demonstrate the importance and nature of the soil carbon response to climatic and human impacts on decadal to millennial timescales. Radiocarbon signatures of bulk, or chemically or physically fractionated soil, or even of specific organic compounds, offer one of the only ways to infer terrestrial carbon turnover times or test ecosystem carbon models. We compiled data from the literature on radiocarbon distribution on soil profiles and characterized each study according to the following categories: soil type, analyzed organic fraction, location (latitude, longitude, elevation), climate (temperature, precipitation), land use and sampling year. Based on the compiled data, soil carbon 14C profiles were reconstructed for each of the 226 sites. We report here partial results obtained by statistical analyses of portion of this database, i.e. bulk and bulk-like organic matter and sampling year posterior to 1980. We highlight here 14C vertical pattern in relationship with external parameters (climate, location and land use).

Differences in the diurnal pattern of soil respiration under adjacent Miscanthus x giganteus and barley crops reveal potential flaws in accepted sampling strategies

Science.gov (United States)

Keane, James; Ineson, Phil

2017-04-01

Soil respiration (Rs) plays an important role in the global carbon cycle and contributes ca. 30% of global ecosystem respiration.However, for convenience, measurements used to compare Rs from different land uses, crops or management practices are often made between 09:00 and 16:00, with an implicit assumption that Rs is largely controlled by temperature. Three months' continuous data presented here show distinctly different diurnal patterns of Rs between barley (Hordeum vulgare) and Miscanthus x giganteus (Miscanthus) grown on adjacent fields. Maximum Rs in barley occurred during the afternoon and correlated with soil temperature, whereas Rs peaked in Miscanthus during the night and was significantly correlated with earlier levels of solar radiation, probably due to delays in translocation of recent photosynthate. Since daily mean Rs in Miscanthus coincided with levels 40% greater than the mean in barley, it is vital to select appropriate times to measure Rs if only single daily measurements are to be made.

Rates of Litter Decomposition and Soil Respiration in Relation to Soil Temperature and Water in Different-Aged Pinus massoniana Forests in the Three Gorges Reservoir Area, China

Science.gov (United States)

Zeng, Lixiong; Huang, Zhilin; Lei, Jingpin; Zhou, Benzhi; Li, Maihe

2014-01-01

To better understand the soil carbon dynamics and cycling in terrestrial ecosystems in response to environmental changes, we studied soil respiration, litter decomposition, and their relations to soil temperature and soil water content for 18-months (Aug. 2010–Jan. 2012) in three different-aged Pinus massoniana forests in the Three Gorges Reservoir Area, China. Across the experimental period, the mean total soil respiration and litter respiration were 1.94 and 0.81, 2.00 and 0.60, 2.19 and 0.71 µmol CO2 m−2 s−1, and the litter dry mass remaining was 57.6%, 56.2% and 61.3% in the 20-, 30-, and 46-year-old forests, respectively. We found that the temporal variations of soil respiration and litter decomposition rates can be well explained by soil temperature at 5 cm depth. Both the total soil respiration and litter respiration were significantly positively correlated with the litter decomposition rates. The mean contribution of the litter respiration to the total soil respiration was 31.0%–45.9% for the three different-aged forests. The present study found that the total soil respiration was not significantly affected by forest age when P. masonniana stands exceed a certain age (e.g. >20 years old), but it increased significantly with increased soil temperature. Hence, forest management strategies need to protect the understory vegetation to limit soil warming, in order to reduce the CO2 emission under the currently rapid global warming. The contribution of litter decomposition to the total soil respiration varies across spatial and temporal scales. This indicates the need for separate consideration of soil and litter respiration when assessing the climate impacts on forest carbon cycling. PMID:25004164

Scale-dependency of the global mean surface temperature trend and its implication for the recent hiatus of global warming

Science.gov (United States)

Lin, Yong; Franzke, Christian L. E.

2015-01-01

Studies of the global mean surface temperature trend are typically conducted at a single (usually annual or decadal) time scale. The used scale does not necessarily correspond to the intrinsic scales of the natural temperature variability. This scale mismatch complicates the separation of externally forced temperature trends from natural temperature fluctuations. The hiatus of global warming since 1999 has been claimed to show that human activities play only a minor role in global warming. Most likely this claim is wrong due to the inadequate consideration of the scale-dependency in the global surface temperature (GST) evolution. Here we show that the variability and trend of the global mean surface temperature anomalies (GSTA) from January 1850 to December 2013, which incorporate both land and sea surface data, is scale-dependent and that the recent hiatus of global warming is mainly related to natural long-term oscillations. These results provide a possible explanation of the recent hiatus of global warming and suggest that the hiatus is only temporary. PMID:26259555

A Time Series Analysis of Global Soil Moisture Data Products for Water Cycle Studies

Science.gov (United States)

Zhan, X.; Yin, J.; Liu, J.; Fang, L.; Hain, C.; Ferraro, R. R.; Weng, F.

2017-12-01

Water is essential for sustaining life on our planet Earth and water cycle is one of the most important processes of out weather and climate system. As one of the major components of the water cycle, soil moisture impacts significantly the other water cycle components (e.g. evapotranspiration, runoff, etc) and the carbon cycle (e.g. plant/crop photosynthesis and respiration). Understanding of soil moisture status and dynamics is crucial for monitoring and predicting the weather, climate, hydrology and ecological processes. Satellite remote sensing has been used for soil moisture observation since the launch of the Scanning Multi-channel Microwave Radiometer (SMMR) on NASA's Nimbus-7 satellite in 1978. Many satellite soil moisture data products have been made available to the science communities and general public. The soil moisture operational product system (SMOPS) of NOAA NESDIS has been operationally providing global soil moisture data products from each of the currently available microwave satellite sensors and their blends. This presentation will provide an update of SMOPS products. The time series of each of these soil moisture data products are analyzed against other data products, such as precipitation and evapotranspiration from other independent data sources such as the North America Land Data Assimilation System (NLDAS). Temporal characteristics of these water cycle components are explored against some historical events, such as the 2010 Russian, 2010 China and 2012 United States droughts, 2015 South Carolina floods, etc. Finally whether a merged global soil moisture data product can be used as a climate data record is evaluated based on the above analyses.

A methodology for the evaluation of global warming impact on soil moisture and runoff

International Nuclear Information System (INIS)

Valdes, J.B.; Seoane, R.S.; North, G.R.

1993-01-01

Global warming is expected to increase the intensity of the global hydrologic cycle. Precipitation and temperature patterns, soil moisture requirements, and the physical structure of the vegetation canopy play important roles in the hydrologic system of drainage basins. Changes in these phenomena, because of a buildup Of CO 2 and other trace gases, have the potential to affect the quantity, quality, timing, and spatial distribution of water available to satisfy the many demands placed on the resource by society. In this work a methodology for the evaluation of impact on soil moisture concentration and direct surface runoff is presented. The methodology integrates stochastic models of hydroclimatic input variables with a model of water balance in the soil. This allows the derivation of the probability distribution of soil moisture concentration and direct surface runoff for different combinations of climate and soil characteristics, ranging from humid to semi-arid and arid. These PDFs asses, in a comprehensive manner, the impact that climate change have on soil moisture and runoff and allow the water resources planner to make more educated decisions in the planning and design of water resources systems. The methodology was applied to three sites in Texas. To continue in the line of research suggested by Delworth and Manabe the authors computed the autocorrelation function (ACF) and the spectra of both precipitation inputs and soil moisture concentration outputs for all scenarios of climate change

Towards combined global monthly gravity field solutions

Science.gov (United States)

Jaeggi, Adrian; Meyer, Ulrich; Beutler, Gerhard; Weigelt, Matthias; van Dam, Tonie; Mayer-Gürr, Torsten; Flury, Jakob; Flechtner, Frank; Dahle, Christoph; Lemoine, Jean-Michel; Bruinsma, Sean

2014-05-01

Currently, official GRACE Science Data System (SDS) monthly gravity field solutions are generated independently by the Centre for Space Research (CSR) and the German Research Centre for Geosciences (GFZ). Additional GRACE SDS monthly fields are provided by the Jet Propulsion Laboratory (JPL) for validation and outside the SDS by a number of other institutions worldwide. Although the adopted background models and processing standards have been harmonized more and more by the various processing centers during the past years, notable differences still exist and the users are more or less left alone with a decision which model to choose for their individual applications. This procedure seriously limits the accessibility of these valuable data. Combinations are well established in the area of other space geodetic techniques, such as the Global Navigation Satellite Systems (GNSS), Satellite Laser Ranging (SLR), and Very Long Baseline Interferometry (VLBI). Regularly comparing and combining space-geodetic products has tremendously increased the usefulness of the products in a wide range of disciplines and scientific applications. Therefore, we propose in a first step to mutually compare the large variety of available monthly GRACE gravity field solutions, e.g., by assessing the signal content over selected regions, by estimating the noise over the oceans, and by performing significance tests. We make the attempt to assign different solution characteristics to different processing strategies in order to identify subsets of solutions, which are based on similar processing strategies. Using these subsets we will in a second step explore ways to generate combined solutions, e.g., based on a weighted average of the individual solutions using empirical weights derived from pair-wise comparisons. We will also assess the quality of such a combined solution and discuss the potential benefits for the GRACE and GRACE-FO user community, but also address minimum processing

LBA Regional Monthly Climatology for the 20th Century (New et al.)

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: This data set is a subset of "Global Monthly Climatology for the 20th Century (New et al.)" (2000a). This subset characterizes mean monthly surface climate...

The Changing Model of Soil

Science.gov (United States)

Richter, D. D.; Yaalon, D.

2012-12-01

The contemporary genetic model of soil is changing rapidly in response to advances in soil science and to human and environmental forcings in the 21st century (Richter and Yaalon, 2012). Three ongoing changes in the model of soil include that: (1) lower soil boundaries are much deeper than the solum, historically the O to B horizons, (2) most soils are polygenetic paleosols, products of soil-forming processes that have ranged widely over soils' lifetimes, and (3) soils are globally human-natural bodies, no longer natural bodies. Together, these changes in the model of soil mean that human forcings are a global wave of soil polygenesis altering fluxes of matter and energy and transforming soil thermodynamics as potentially very deep systems. Because soils are non-linear systems resulting from high-order interactions of physics, chemistry, and biology, trajectories of how human forcings alter soils over decades are not readily predictable and require long-term soil observations. There is much to learn about how soils are changing internally as central components of management systems and externally in relation to wider environments. To be critical, research has been remarkably superficial in studies of soil, reductionist in approach, and lacking in time-series observations of responses to soil management. While this criticism may sound negative, it creates significant opportunities for contemporary soil scientists.

Assessment of SMAP soil moisture for global simulation of gross primary production

Science.gov (United States)

He, Liming; Chen, Jing M.; Liu, Jane; Bélair, Stéphane; Luo, Xiangzhong

2017-07-01

In this study, high-quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process-based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (r) between simulated GPP from the sunlit leaves and Sun-induced chlorophyll fluorescence (SIF) measured by Global Ozone Monitoring Experiment-2 is used as an indicator to evaluate the performance of the GPP simulation. Areas with SMAP data in low quality (i.e., forests), or with SIF in low magnitude (e.g., deserts), or both are excluded from the analysis. With the assimilated SMAP data, the r value is enhanced for Africa, Asia, and North America by 0.016, 0.013, and 0.013, respectively (p r appears in single-cropping agricultural land where the irrigation is not considered in the model but well captured by SMAP (e.g., 0.09 in North America, p < 0.05). With the assimilation of SMAP, areas with weak model performances are identified in double or triple cropping cropland (e.g., part of North China Plain) and/or mountainous area (e.g., Spain and Turkey). The correlation coefficient is enhanced by 0.01 in global average for shrub, grass, and cropland. This enhancement is small and insignificant because nonwater-stressed areas are included.

LBA Regional Monthly Climatology for the 20th Century (New et al.)

Data.gov (United States)

National Aeronautics and Space Administration — This data set is a subset of "Global Monthly Climatology for the 20th Century (New et al.)" (2000a). This subset characterizes mean monthly surface climate over the...

GLOBAL CLASSIFICATION OF DERMATITIS DISEASE WITH K-MEANS CLUSTERING IMAGE SEGMENTATION METHODS

OpenAIRE

Prafulla N. Aerkewar1 & Dr. G. H. Agrawal2

2018-01-01

The objective of this paper to presents a global technique for classification of different dermatitis disease lesions using the process of k-Means clustering image segmentation method. The word global is used such that the all dermatitis disease having skin lesion on body are classified in to four category using k-means image segmentation and nntool of Matlab. Through the image segmentation technique and nntool can be analyze and study the segmentation properties of skin lesions occurs in...

Grazing reduces soil greenhouse gas fluxes in global grasslands: a meta-analysis

Science.gov (United States)

Tang, Shiming; Tian, Dashuan; Niu, Shuli

2017-04-01

Grazing causes a worldwide degradation in grassland and likely alters soil greenhouse gas fluxes (GHGs). However, the general patterns of grazing-induced changes in grassland soil GHGs and the underlying mechanisms remain unclear. Thus, we synthesized 63 independent experiments in global grasslands that examined grazing impacts on soil GHGs (CO2, CH4 and N2O). We found that grazing with light or moderate intensity did not significantly influence soil GHGs, but consistently depressed them under heavy grazing, reducing CO2 emission by 10.55%, CH4 uptake by 19.24% and N2O emission by 28.04%. The reduction in soil CO2 was mainly due to decreased activity in roots and microbes (soil respiration per unit root and microbial biomass), which was suppressed by less water availability due to higher soil temperature induced by lower community cover under heavy grazing. N2O emission decreased with grazing-caused decline in soil total N. The inhibitory effect on methanotroph activities by water stress is responsible for the decreased CH4 uptake. Furthermore, grazing duration and precipitation also influenced the direction and magnitude of responses in GHGs fluxes. Overall, our results indicate that the reduction in soil CO2 and N2O emission under heavy grazing is partially compensated by the decrease in CH4 uptake, which is mainly regulated by variations in soil moisture.

Soil moisture and its role in growth-climate relationships across an aridity gradient in semiarid Pinus halepensis forests.

Science.gov (United States)

Manrique-Alba, Àngela; Ruiz-Yanetti, Samantha; Moutahir, Hassane; Novak, Klemen; De Luis, Martin; Bellot, Juan

2017-01-01

In Mediterranean areas with limited availability of water, an accurate knowledge of growth response to hydrological variables could contribute to improving management and stability of forest resources. The main goal of this study is to assess the temporal dynamic of soil moisture to better understand the water-growth relationship of Pinus halepensis forests in semiarid areas. The estimates of modelled soil moisture and measured tree growth were used at four sites dominated by afforested Pinus halepensis Mill. in south-eastern Spain with 300 to 609mm mean annual precipitation. Firstly, dendrochronological samples were extracted and the widths of annual tree rings were measured to compute basal area increments (BAI). Secondly, soil moisture was estimated over 20 hydrological years (1992-2012) by means of the HYDROBAL ecohydrological model. Finally, the tree growth was linked, to mean monthly and seasonal temperature, precipitation and soil moisture. Results depict the effect of soil moisture on growth (BAI) and explain 69-73% of the variance in semiarid forests, but only 51% in the subhumid forests. This highlights the fact that that soil moisture is a suitable and promising variable to explain growth variations of afforested Pinus halepensis in semiarid conditions and useful for guiding adaptation plans to respond pro-actively to water-related global challenges. Copyright © 2016 Elsevier B.V. All rights reserved.

A Global Meta-Analysis on the Impact of Management Practices on Net Global Warming Potential and Greenhouse Gas Intensity from Cropland Soils

Science.gov (United States)

Sainju, Upendra M.

2016-01-01

Management practices, such as tillage, crop rotation, and N fertilization, may affect net global warming potential (GWP) and greenhouse gas intensity (GHGI), but their global impact on cropland soils under different soil and climatic conditions need further evaluation. Available global data from 57 experiments and 225 treatments were evaluated for individual and combined effects of tillage, cropping systems, and N fertilization rates on GWP and GHGI which accounted for CO2 equivalents from N2O and CH4 emissions with or without equivalents from soil C sequestration rate (ΔSOC), farm operations, and N fertilization. The GWP and GHGI were 66 to 71% lower with no-till than conventional till and 168 to 215% lower with perennial than annual cropping systems, but 41 to 46% greater with crop rotation than monocroppping. With no-till vs. conventional till, GWP and GHGI were 2.6- to 7.4-fold lower when partial than full accounting of all sources and sinks of greenhouse gases (GHGs) were considered. With 100 kg N ha-1, GWP and GHGI were 3.2 to 11.4 times greater with partial than full accounting. Both GWP and GHGI increased curvilinearly with increased N fertilization rate. Net GWP and GHGI were 70 to 87% lower in the improved combined management that included no-till, crop rotation/perennial crop, and reduced N rate than the traditional combined management that included conventional till, monocopping/annual crop, and recommended N rate. An alternative soil respiration method, which replaces ΔSOC by soil respiration and crop residue returned to soil in the previous year, similarly reduced GWP and GHGI by 133 to 158% in the improved vs. the traditional combined management. Changes in GWP and GHGI due to improved vs. traditional management varied with the duration of the experiment and inclusion of soil and climatic factors in multiple linear regressions improved their relationships. Improved management practices reduced GWP and GHGI compared with traditional management

A Global Meta-Analysis on the Impact of Management Practices on Net Global Warming Potential and Greenhouse Gas Intensity from Cropland Soils.

Science.gov (United States)

Sainju, Upendra M

2016-01-01

Management practices, such as tillage, crop rotation, and N fertilization, may affect net global warming potential (GWP) and greenhouse gas intensity (GHGI), but their global impact on cropland soils under different soil and climatic conditions need further evaluation. Available global data from 57 experiments and 225 treatments were evaluated for individual and combined effects of tillage, cropping systems, and N fertilization rates on GWP and GHGI which accounted for CO2 equivalents from N2O and CH4 emissions with or without equivalents from soil C sequestration rate (ΔSOC), farm operations, and N fertilization. The GWP and GHGI were 66 to 71% lower with no-till than conventional till and 168 to 215% lower with perennial than annual cropping systems, but 41 to 46% greater with crop rotation than monocroppping. With no-till vs. conventional till, GWP and GHGI were 2.6- to 7.4-fold lower when partial than full accounting of all sources and sinks of greenhouse gases (GHGs) were considered. With 100 kg N ha-1, GWP and GHGI were 3.2 to 11.4 times greater with partial than full accounting. Both GWP and GHGI increased curvilinearly with increased N fertilization rate. Net GWP and GHGI were 70 to 87% lower in the improved combined management that included no-till, crop rotation/perennial crop, and reduced N rate than the traditional combined management that included conventional till, monocopping/annual crop, and recommended N rate. An alternative soil respiration method, which replaces ΔSOC by soil respiration and crop residue returned to soil in the previous year, similarly reduced GWP and GHGI by 133 to 158% in the improved vs. the traditional combined management. Changes in GWP and GHGI due to improved vs. traditional management varied with the duration of the experiment and inclusion of soil and climatic factors in multiple linear regressions improved their relationships. Improved management practices reduced GWP and GHGI compared with traditional management

Different Mechanisms of Soil Microbial Response to Global Change Result in Different Outcomes in the MIMICS-CN Model

Science.gov (United States)

Kyker-Snowman, E.; Wieder, W. R.; Grandy, S.

2017-12-01

Microbial-explicit models of soil carbon (C) and nitrogen (N) cycling have improved upon simulations of C and N stocks and flows at site-to-global scales relative to traditional first-order linear models. However, the response of microbial-explicit soil models to global change factors depends upon which parameters and processes in a model are altered by those factors. We used the MIcrobial-MIneral Carbon Stabilization Model with coupled N cycling (MIMICS-CN) to compare modeled responses to changes in temperature and plant inputs at two previously-modeled sites (Harvard Forest and Kellogg Biological Station). We spun the model up to equilibrium, applied each perturbation, and evaluated 15 years of post-perturbation C and N pools and fluxes. To model the effect of increasing temperatures, we independently examined the impact of decreasing microbial C use efficiency (CUE), increasing the rate of microbial turnover, and increasing Michaelis-Menten kinetic rates of litter decomposition, plus several combinations of the three. For plant inputs, we ran simulations with stepwise increases in metabolic litter, structural litter, whole litter (structural and metabolic), or labile soil C. The cumulative change in soil C or N varied in both sign and magnitude across simulations. For example, increasing kinetic rates of litter decomposition resulted in net releases of both C and N from soil pools, while decreasing CUE produced short-term increases in respiration but long-term accumulation of C in litter pools and shifts in soil C:N as microbial demand for C increased and biomass declined. Given that soil N cycling constrains the response of plant productivity to global change and that soils generate a large amount of uncertainty in current earth system models, microbial-explicit models are a critical opportunity to advance the modeled representation of soils. However, microbial-explicit models must be improved by experiments to isolate the physiological and stoichiometric

Soil microbial communities drive the resistance of ecosystem multifunctionality to global change in drylands across the globe.

Science.gov (United States)

Delgado-Baquerizo, Manuel; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Singh, Brajesh K; Maestre, Fernando T

2017-10-01

The relationship between soil microbial communities and the resistance of multiple ecosystem functions linked to C, N and P cycling (multifunctionality resistance) to global change has never been assessed globally in natural ecosystems. We collected soils from 59 dryland ecosystems worldwide to investigate the importance of microbial communities as predictor of multifunctionality resistance to climate change and nitrogen fertilisation. Multifunctionality had a lower resistance to wetting-drying cycles than to warming or N deposition. Multifunctionality resistance was regulated by changes in microbial composition (relative abundance of phylotypes) but not by richness, total abundance of fungi and bacteria or the fungal: bacterial ratio. Our results suggest that positive effects of particular microbial taxa on multifunctionality resistance could potentially be controlled by altering soil pH. Together, our work demonstrates strong links between microbial community composition and multifunctionality resistance in dryland soils from six continents, and provides insights into the importance of microbial community composition for buffering effects of global change in drylands worldwide. © 2017 John Wiley & Sons Ltd/CNRS.

Modeling soil organic carbon dynamics and their driving factors in the main global cereal cropping systems

Directory of Open Access Journals (Sweden)

G. Wang

2017-10-01

Full Text Available Changes in the soil organic carbon (SOC stock are determined by the balance between the carbon input from organic materials and the output from the decomposition of soil C. The fate of SOC in cropland soils plays a significant role in both sustainable agricultural production and climate change mitigation. The spatiotemporal changes of soil organic carbon in croplands in response to different carbon (C input management and environmental conditions across the main global cereal systems were studied using a modeling approach. We also identified the key variables that drive SOC changes at a high spatial resolution (0.1°  ×  0.1° and over a long timescale (54 years from 1961 to 2014. A widely used soil C turnover model (RothC and state-of-the-art databases of soil and climate variables were used in the present study. The model simulations suggested that, on a global average, the cropland SOC density increased at annual rates of 0.22, 0.45 and 0.69 Mg C ha−1 yr−1 under crop residue retention rates of 30, 60 and 90 %, respectively. Increasing the quantity of C input could enhance soil C sequestration or reduce the rate of soil C loss, depending largely on the local soil and climate conditions. Spatially, under a specific crop residue retention rate, relatively higher soil C sinks were found across the central parts of the USA, western Europe, and the northern regions of China. Relatively smaller soil C sinks occurred in the high-latitude regions of both the Northern and Southern hemispheres, and SOC decreased across the equatorial zones of Asia, Africa and America. We found that SOC change was significantly influenced by the crop residue retention rate (linearly positive and the edaphic variable of initial SOC content (linearly negative. Temperature had weak negative effects, and precipitation had significantly negative impacts on SOC changes. The results can help guide carbon input management practices to

Monthly Rainfall Erosivity Assessment for Switzerland

Science.gov (United States)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation

Why must a solar forcing be larger than a CO2 forcing to cause the same global mean surface temperature change?

International Nuclear Information System (INIS)

Modak, Angshuman; Bala, Govindasamy; Cao, Long; Caldeira, Ken

2016-01-01

Many previous studies have shown that a solar forcing must be greater than a CO 2 forcing to cause the same global mean surface temperature change but a process-based mechanistic explanation is lacking in the literature. In this study, we investigate the physical mechanisms responsible for the lower efficacy of solar forcing compared to an equivalent CO 2 forcing. Radiative forcing is estimated using the Gregory method that regresses top-of-atmosphere (TOA) radiative flux against the change in global mean surface temperature. For a 2.25% increase in solar irradiance that produces the same long term global mean warming as a doubling of CO 2 concentration, we estimate that the efficacy of solar forcing is ∼80% relative to CO 2 forcing in the NCAR CAM5 climate model. We find that the fast tropospheric cloud adjustments especially over land and stratospheric warming in the first four months cause the slope of the regression between the TOA net radiative fluxes and surface temperature to be steeper in the solar forcing case. This steeper slope indicates a stronger net negative feedback and hence correspondingly a larger solar forcing than CO 2 forcing for the same equilibrium surface warming. Evidence is provided that rapid land surface warming in the first four months sets up a land-sea contrast that markedly affects radiative forcing and the climate feedback parameter over this period. We also confirm the robustness of our results using simulations from the Hadley Centre climate model. Our study has important implications for estimating the magnitude of climate change caused by volcanic eruptions, solar geoengineering and past climate changes caused by change in solar irradiance such as Maunder minimum. (letter)

Global solar irradiation in Italy during 1994 : monthly average daily values for 1614 sites estimated from Meteosat images; Radiazione solare globale al suolo in Italia nel 1994 : valori medi mensili per 1.614 localita` italiane stimate a partire dalle immagini fornite dal satellite Meteosat

Energy Technology Data Exchange (ETDEWEB)

Cogliani, E; Mancini, M; Petrarca, S; Spinelli, F [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Energia

1995-10-01

The global solar radiation over Italy is estimated from Meteosat secondary images in the visible band. The stimation method relies on the fact that the cloud cover on a given area of the Earth`s surface statistically determines the amount of solar radiation falling on that area. Estimated values of the monthly average daily global radiation on a horizontal surface for the 1994 have been compared with values computed from data measured by the stations of the two Italian radiation networks: the Meteorological Service of the Italian Air Force and the National Agrometeorological Network (a total of 36 stations have been considered). The mean percentage difference between estimated and computed values over the year is 6 per cent. In the present report, the monthly maps of radiation over Italy and the estimated monthly average daily values for over 1600 sites (having more than 10,000 inhabitants) are given. In the yearly reports to be issued in the years to come, maps and mean values over the period starting with 1994 will be given as well.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

Science.gov (United States)

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Short-term variations in core surface flow resolved from an improved method of calculating observatory monthly means

Science.gov (United States)

Olsen, Nils; Whaler, Kathryn A.; Finlay, Christopher C.

2014-05-01

Monthly means of the magnetic field measurements taken by ground observatories are a useful data source for studying temporal changes of the core magnetic field and the underlying core flow. However, the usual way of calculating monthly means as the arithmetic mean of all days (geomagnetic quiet as well as disturbed) and all local times (day and night) may result in contributions from external (magnetospheric and ionospheric) origin in the (ordinary, omm) monthly means. Such contamination makes monthly means less favourable for core studies. We calculated revised monthly means (rmm), and their uncertainties, from observatory hourly means using robust means and after removal of external field predictions, using an improved method for characterising the magnetospheric ring current. The utility of the new method for calculating observatory monthly means is demonstrated by inverting their first differences for core surface advective flows. The flow is assumed steady over three consecutive months to ensure uniqueness; the effects of more rapid changes should be attenuated by the weakly conducting mantle. Observatory data are inverted directly for a regularised core flow, rather than deriving it from a secular variation spherical harmonic model. The main field is specified by the CHAOS-4 model. Data from up to 128 observatories between 1997 and 2013 were used to calculate 185 flow models from the omm and rmm, for each possible set of three consecutive months. The full 3x3 (non-diagonal) data covariance matrix was used, and two-norm (least squares) minimisation performed. We are able to fit the data to the target (weighted) misfit of 1, for both omm and rmm inversions, provided we incorporate the full data covariance matrix, and produce consistent, plausible flows. Fits are better for rmm flows. The flows exhibit noticeable changes over timescales of a few months. However, they follow rapid excursions in the omm that we suspect result from external field contamination

Simulations of monthly mean nitrate concentrations in precipitation over East Asia

International Nuclear Information System (INIS)

Junling An; Xinjin Cheng; Ueda, Hiromasa; Kajino, Mizuo

2002-01-01

Monthly mean nitrate concentrations in precipitation over East Asia (10-55 o N, 75-155 o E) in April, July, September, and December of 1999 were simulated by using a regional air quality Eulerian model (RAQM) with meteorological fields four times per day taken from National Centers for Environmental Prediction. The distribution of the nitrate concentration in precipitation depends significantly on the emission patterns of nitrogen oxides (NO x =NO+NO 2 ) and volatile organic compound (VOC) and seasonal precipitation variability. The downward trend is also revealed, particularly on July and December. Highest concentrations are found in the industrialized regions, i.e., the coastal area of the Mainland of China, the Bay of the Huanghai Sea and the Bohai Sea, Korea, and Southern Japan. Long-range transport may cause elevated concentrations in remote areas downwind of the industrialized regions under favorable meteorological conditions, e.g., low precipitation. Comparison of observation and simulations indicates that the RAQM model reasonably predicts synoptic-scale changes in different months (seasons) and simulated nitrate levels in 4 months fit observed data with the discrepancy within a factor of 2. Exclusion of liquid chemistry within clouds is feasible for regional (1 o x1 o ) and long-term (monthly) nitrate simulations. The uncertainty originates mainly from that of the emission data and modeled precipitation amounts and initial and boundary conditions. (author)

Maximum temperature accounts for annual soil CO2 efflux in temperate forests of Northern China

Science.gov (United States)

Zhou, Zhiyong; Xu, Meili; Kang, Fengfeng; Jianxin Sun, Osbert

2015-01-01

It will help understand the representation legality of soil temperature to explore the correlations of soil respiration with variant properties of soil temperature. Soil temperature at 10 cm depth was hourly logged through twelve months. Basing on the measured soil temperature, soil respiration at different temporal scales were calculated using empirical functions for temperate forests. On monthly scale, soil respiration significantly correlated with maximum, minimum, mean and accumulated effective soil temperatures. Annual soil respiration varied from 409 g C m−2 in coniferous forest to 570 g C m−2 in mixed forest and to 692 g C m−2 in broadleaved forest, and was markedly explained by mean soil temperatures of the warmest day, July and summer, separately. These three soil temperatures reflected the maximum values on diurnal, monthly and annual scales. In accordance with their higher temperatures, summer soil respiration accounted for 51% of annual soil respiration across forest types, and broadleaved forest also had higher soil organic carbon content (SOC) and soil microbial biomass carbon content (SMBC), but a lower contribution of SMBC to SOC. This added proof to the findings that maximum soil temperature may accelerate the transformation of SOC to CO2-C via stimulating activities of soil microorganisms. PMID:26179467

Monthly Sea Surface Salinity and Freshwater Flux Monitoring

Science.gov (United States)

Ren, L.; Xie, P.; Wu, S.

2017-12-01

Taking advantages of the complementary nature of the Sea Surface Salinity (SSS) measurements from the in-situ (CTDs, shipboard, Argo floats, etc.) and satellite retrievals from Soil Moisture Ocean Salinity (SMOS) satellite of the European Space Agency (ESA), the Aquarius of a joint venture between US and Argentina, and the Soil Moisture Active Passive (SMAP) of national Aeronautics and Space Administration (NASA), a technique is developed at NOAA/NCEP/CPC to construct an analysis of monthly SSS, called the NOAA Blended Analysis of Sea-Surface Salinity (BASS). The algorithm is a two-steps approach, i.e. to remove the bias in the satellite data through Probability Density Function (PDF) matching against co-located in situ measurements; and then to combine the bias-corrected satellite data with the in situ measurements through the Optimal Interpolation (OI) method. The BASS SSS product is on a 1° by 1° grid over the global ocean for a 7-year period from 2010. Combined with the NOAA/NCEP/CPC CMORPH satellite precipitation (P) estimates and the Climate Forecast System Reanalysis (CFSR) evaporation (E) fields, a suite of monthly package of the SSS and oceanic freshwater flux (E and P) was developed to monitor the global oceanic water cycle and SSS on a monthly basis. The SSS in BASS product is a suite of long-term SSS and fresh water flux data sets with temporal homogeneity and inter-component consistency better suited for the examination of the long-term changes and monitoring. It presents complete spatial coverage and improved resolution and accuracy, which facilitates the diagnostic analysis of the relationship and co-variability among SSS, freshwater flux, mixed layer processes, oceanic circulation, and assimilation of SSS into global models. At the AGU meeting, we will provide more details on the CPC salinity and fresh water flux data package and its applications in the monitoring and analysis of SSS variations in association with the ENSO and other major climate

Soil and air temperatures for different habitats in Mount Rainier National Park.

Science.gov (United States)

Sarah E. Greene; Mark Klopsch

1985-01-01

This paper reports air and soil temperature data from 10 sites in Mount Rainier National Park in Washington State for 2- to 5-year periods. Data provided are monthly summaries for day and night mean air temperatures, mean minimum and maximum air temperatures, absolute minimum and maximum air temperatures, range of air temperatures, mean soil temperature, and absolute...

Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models: Current status and future directions.

Science.gov (United States)

Tian, Hanqin; Lu, Chaoqun; Yang, Jia; Banger, Kamaljit; Huntzinger, Deborah N; Schwalm, Christopher R; Michalak, Anna M; Cook, Robert; Ciais, Philippe; Hayes, Daniel; Huang, Maoyi; Ito, Akihiko; Jain, Atul K; Lei, Huimin; Mao, Jiafu; Pan, Shufen; Post, Wilfred M; Peng, Shushi; Poulter, Benjamin; Ren, Wei; Ricciuto, Daniel; Schaefer, Kevin; Shi, Xiaoying; Tao, Bo; Wang, Weile; Wei, Yaxing; Yang, Qichun; Zhang, Bowen; Zeng, Ning

2015-06-01

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO 2 ) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long (1901-2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 10 15  g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr -1 with a median value of 51 Pg C yr -1 during 2001-2010. The largest uncertainty in SOC stocks exists in the 40-65°N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901-2010 ranges from -70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO 2 and nitrogen deposition over intact ecosystems increased SOC stocks-even though the responses varied

Statistical sampling strategies for survey of soil contamination

NARCIS (Netherlands)

Brus, D.J.

2011-01-01

This chapter reviews methods for selecting sampling locations in contaminated soils for three situations. In the first situation a global estimate of the soil contamination in an area is required. The result of the surey is a number or a series of numbers per contaminant, e.g. the estimated mean

Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey

Science.gov (United States)

Citakoglu, Hatice

2017-10-01

Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient ( R 2 )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 2 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 2 0.93, 0.91) in estimating soil temperature in Turkey.

Month-hour distributions of zenith luminance and diffuse illuminance in Madrid

International Nuclear Information System (INIS)

Soler, Alfonso; Gopinathan, Kannam K.; Robledo, Luis; Ruiz, Enrique

2004-01-01

Month-hour equal mean zenith luminance contours are obtained from one year of data of zenith luminance measurements for cloudless, overcast and partly cloudy skies and also when the combined data for all sky types are considered. For many hours in different months, the overcast sky luminance values are roughly about three times the cloudless sky luminance values and one and a half times the partly cloudy sky values. The dependence of month-hour equal mean zenith luminance contours on the ratio of global to extraterrestrial illuminance on a horizontal surface is also given. From equal mean zenith luminance contours, the approximate values of the mean zenith luminance for different sky conditions and different hours and months of the year can be easily obtained. Month-hour equal mean diffuse illuminance contours are obtained from diffuse illuminance measurements performed during the period 1992-1998. The dependence on solar altitude of the monthly average hourly values of diffuse illuminance is given and compared to the corresponding one obtained from data for Bet Dagan (Israel)

Global warming and South Indian monsoon rainfall-lessons from the Mid-Miocene.

Science.gov (United States)

Reuter, Markus; Kern, Andrea K; Harzhauser, Mathias; Kroh, Andreas; Piller, Werner E

2013-04-01

Precipitation over India is driven by the Indian monsoon. Although changes in this atmospheric circulation are caused by the differential seasonal diabatic heating of Asia and the Indo-Pacific Ocean, it is so far unknown how global warming influences the monsoon rainfalls regionally. Herein, we present a Miocene pollen flora as the first direct proxy for monsoon over southern India during the Middle Miocene Climate Optimum. To identify climatic key parameters, such as mean annual temperature, warmest month temperature, coldest month temperature, mean annual precipitation, mean precipitation during the driest month, mean precipitation during the wettest month and mean precipitation during the warmest month the Coexistence Approach is applied. Irrespective of a ~ 3-4 °C higher global temperature during the Middle Miocene Climate Optimum, the results indicate a modern-like monsoonal precipitation pattern contrasting marine proxies which point to a strong decline of Indian monsoon in the Himalaya at this time. Therefore, the strength of monsoon rainfall in tropical India appears neither to be related to global warming nor to be linked with the atmospheric conditions over the Tibetan Plateau. For the future it implies that increased global warming does not necessarily entail changes in the South Indian monsoon rainfall.

Forecasting the Global Mean Sea Level, a Continuous-Time State-Space Approach

DEFF Research Database (Denmark)

Boldrini, Lorenzo

In this paper we propose a continuous-time, Gaussian, linear, state-space system to model the relation between global mean sea level (GMSL) and the global mean temperature (GMT), with the aim of making long-term projections for the GMSL. We provide a justification for the model specification based......) and the temperature reconstruction from Hansen et al. (2010). We compare the forecasting performance of the proposed specification to the procedures developed in Rahmstorf (2007b) and Vermeer and Rahmstorf (2009). Finally, we compute projections for the sea-level rise conditional on the 21st century SRES temperature...

Soil-landscape modelling using fuzzy c-means clustering of attribute data derived from a Digital Elevation Model (DEM).

NARCIS (Netherlands)

Bruin, de S.; Stein, A.

1998-01-01

This study explores the use of fuzzy c-means clustering of attribute data derived from a digital elevation model to represent transition zones in the soil-landscape. The conventional geographic model used for soil-landscape description is not able to properly deal with these. Fuzzy c-means

Soils and climate: redness and weathering as indicators of mean annual precipitation

Science.gov (United States)

Lucke, Bernhard

2016-04-01

Paleosols can be used as archives of past changes of climate and landscapes, but their interpretation has to be based on modern analogies such as Budyko's law of soil zonality. These can be very useful if the respective processes of soil formation are sufficiently well understood. However, some soils such as the Terra Rossa or Red Mediterranean Soils, that are widespread at the fringes of the steppes and deserts, are still disputed with regard to their genesis and environmental significance. In particular, there is no agreement whether they resemble current environmental conditions, or are inherited from climates or sediments of the past. In this context, a remarkable change of the color of surface soils can be observed when driving from the city of Irbid in Jordan towards the east. Soil color apparently changes slowly, but steadily from dark red to yellow colors. However, attempting to express these color changes in numerical form is challenging, and it seemed questionable whether color is indeed connected with soil weathering intensity, or an optical illusion. However, a systematic comparison of different approaches of calculating soil redness found that the CIELAB-color system is suited for numerical expressions of soil redness and performs better than the Munsell charts. Along the investigated transect in Jordan, soil color seems strongly connected with weathering intensity, since various weathering indicators point to a steady increase of soil development with moisture. This suggests that such indices can well be used in semi-arid areas of 250-600 mm of mean annual precipitation. A very strong correlation of magnetic enhancement and rainfall indicates that the investigated soils are forming in equilibrium with current climatic conditions, and regressions based on this gradient might be suited for estimating paleorainfalls recorded by buried paelosols. It seems therefore that surface Terra Rossa soils in Jordan can be in equilibrium with current climate

A Global comparison of surface soil characteristics across five cities: A test of the urban ecosystem convergence hypothesis.

Science.gov (United States)

Richard V. Pouyat; Ian D. Yesilonis; Miklos Dombos; Katalin Szlavecz; Heikki Setala; Sarel Cilliers; Erzsebet Hornung; D. Johan Kotze; Stephanie Yarwood

2015-01-01

As part of the Global Urban Soil Ecology and Education Network and to test the urban ecosystem convergence hypothesis, we report on soil pH, organic carbon (OC), total nitrogen (TN), phosphorus (P), and potassium (K) measured in four soil habitat types (turfgrass, ruderal, remnant, and reference) in five metropolitan areas (Baltimore, Budapest,...

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

Science.gov (United States)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

Measurement of the denitrification in soil monoliths from grassland and arable soil by means of 15N techniques

International Nuclear Information System (INIS)

Lippold, H.; Foerster, I.

1980-01-01

Losses of fertilizer nitrogen by denitrification were determined in soil monoliths from two sites (loess chernozem and clay ranker). The monoliths were isolated by driving plastic pipes into the plots, and fertilized with 15 N-labelled ammonium nitrate. Emission spectrometric techniques were applied to measure the N 2 and N 2 O quantities released in the isolated atmospheric layer above the monolith. The considerable losses, especially on grassland soils (up to a maximum of 30 kg N/ha), indicate the influence of rainfalls and mean temperature at the 5 dates of sampling (end of March to mid-October). (author)

A global analysis of fine root production as affected by soil nitrogen and phosphorus.

Science.gov (United States)

Yuan, Z Y; Chen, Han Y H

2012-09-22

Fine root production is the largest component of belowground production and plays substantial roles in the biogeochemical cycles of terrestrial ecosystems. The increasing availability of nitrogen (N) and phosphorus (P) due to human activities is expected to increase aboveground net primary production (ANNP), but the response of fine root production to N and P remains unclear. If roots respond to nutrients as ANNP, fine root production is anticipated to increase with increasing soil N and P. Here, by synthesizing data along the nutrient gradient from 410 natural habitats and from 469 N and/or P addition experiments, we showed that fine root production increased in terrestrial ecosystems with an average increase along the natural N gradient of up to 0.5 per cent with increasing soil N. Fine root production also increased with soil P in natural conditions, particularly at P production increased by a global average of 27, 21 and 40 per cent, respectively. However, its responses differed among ecosystems and soil types. The global average increases in fine root production are lower than those of ANNP, indicating that above- and belowground counterparts are coupled, but production allocation shifts more to aboveground with higher soil nutrients. Our results suggest that the increasing fertilizer use and combined N deposition at present and in the future will stimulate fine root production, together with ANPP, probably providing a significant influence on atmospheric CO(2) emissions.

Identification of significant features by the Global Mean Rank test.

Science.gov (United States)

Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

2014-01-01

With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods for the reliable identification of significantly regulated features (genes, proteins, etc.) have been developed. Experimental practice requires these tests to successfully deal with conditions such as small numbers of replicates, missing values, non-normally distributed expression levels, and non-identical distributions of features. With the MeanRank test we aimed at developing a test that performs robustly under these conditions, while favorably scaling with the number of replicates. The test proposed here is a global one-sample location test, which is based on the mean ranks across replicates, and internally estimates and controls the false discovery rate. Furthermore, missing data is accounted for without the need of imputation. In extensive simulations comparing MeanRank to other frequently used methods, we found that it performs well with small and large numbers of replicates, feature dependent variance between replicates, and variable regulation across features on simulation data and a recent two-color microarray spike-in dataset. The tests were then used to identify significant changes in the phosphoproteomes of cancer cells induced by the kinase inhibitors erlotinib and 3-MB-PP1 in two independently published mass spectrometry-based studies. MeanRank outperformed the other global rank-based methods applied in this study. Compared to the popular Significance Analysis of Microarrays and Linear Models for Microarray methods, MeanRank performed similar or better. Furthermore, MeanRank exhibits more consistent behavior regarding the degree of regulation and is robust against the choice of preprocessing methods. MeanRank does not require any imputation of missing values, is easy to understand, and yields results that are easy to interpret. The software implementing the algorithm is freely available for academic and commercial use.

Hungarian contribution to the Global Soil Organic Carbon Map (GSOC17) using advanced machine learning algorithms and geostatistics

Science.gov (United States)

Szatmári, Gábor; Laborczi, Annamária; Takács, Katalin; Pásztor, László

2017-04-01

The knowledge about soil organic carbon (SOC) baselines and changes, and the detection of vulnerable hot spots for SOC losses and gains under climate change and changed land management is still fairly limited. Thus Global Soil Partnership (GSP) has been requested to develop a global SOC mapping campaign by 2017. GSPs concept builds on official national data sets, therefore, a bottom-up (country-driven) approach is pursued. The elaborated Hungarian methodology suits the general specifications of GSOC17 provided by GSP. The input data for GSOC17@HU mapping approach has involved legacy soil data bases, as well as proper environmental covariates related to the main soil forming factors, such as climate, organisms, relief and parent material. Nowadays, digital soil mapping (DSM) highly relies on the assumption that soil properties of interest can be modelled as a sum of a deterministic and stochastic component, which can be treated and modelled separately. We also adopted this assumption in our methodology. In practice, multiple regression techniques are commonly used to model the deterministic part. However, this global (and usually linear) models commonly oversimplify the often complex and non-linear relationship, which has a crucial effect on the resulted soil maps. Thus, we integrated machine learning algorithms (namely random forest and quantile regression forest) in the elaborated methodology, supposing then to be more suitable for the problem in hand. This approach has enable us to model the GSOC17 soil properties in that complex and non-linear forms as the soil itself. Furthermore, it has enable us to model and assess the uncertainty of the results, which is highly relevant in decision making. The applied methodology has used geostatistical approach to model the stochastic part of the spatial variability of the soil properties of interest. We created GSOC17@HU map with 1 km grid resolution according to the GSPs specifications. The map contributes to the GSPs

The fascinating side of dirt: Soil and the global environment course

Science.gov (United States)

Grand, S.; Krzic, M.; Crowley, C.; Lascu, G.; Rosado, J.

2012-04-01

Soil has recently been attracting some renewed public attention due to its inextricable link to current environmental challenges such as climate change, food security and water resource protection. It is increasingly acknowledged that the world's future will require a better understanding of soil science. Yet enrolment in soil related programs at universities in North America and around the world has been declining. One of the proposed causes for this drop is the tendency for soil science education to emphasize the agricultural side of soil science, while our increasingly urban and environmentally conscious student population is more interested in environmental sciences. To address this issue, in 2011 we created an on-line, first-year soil science course designed specifically to communicate the significance of soil science to global environmental questions. We propose that this type of course is an effective way to help increase interest in higher level soil courses and reverse the downward trend in enrolments. The course content was centered on prominent environmental issues, which were used to introduce basic concepts of soil science. Course materials emphasized integration with other natural resources disciplines such as ecology, biogeochemistry and hydrology. The online format allowed for a seamless integration of multimedia components and web content into course materials, and is believed to be appealing to technologically savvy new generations of students. Online discussion boards were extensively used to maintain strong student engagement in the course. Discussion topics were based on soil-related news stories that helped demonstrate the relevance of soils to society and illustrate the complex and often controversial nature of environmental issues. Students also made significant use of an online bulletin board to post information about environmental events and share news stories related to the course. This course was offered for the first time in term 1 of

Atrazine determination and some of their degradation products in soils and water by means of liquid chromatography of high resolution

International Nuclear Information System (INIS)

Olarte, Israel; Guerrero, Jairo Arturo; Fuentes, Cilia

1999-01-01

This study describes the validation of the analytical method for the simultaneous determination of atrazine (AT) and its metabolites deisopropylatrazine (DIA) and deetylatrazine (DEA) in irrigation water and agricultural soil. Field samples were collected in a cornfield located in Saldana, (Tolima, Colombia) and treated with 2.9 kg. a.i/ha of atrazine. Samples were collected for three months starting after herbicide treatment. The quantitative determination of the compounds of interest was carried out by HPLC with UV detection in a lichrospher RP-18 column of 125 x 4 mm, 5 , using a gradient of acetonitrile-water as mobile phase. The compounds were extracted from the water matrix and concentrated using solid phase extraction (SPE). From the soil matrix the compounds were extracted with methanol followed by a clean up with dichloromethane and buffer phosphate 0.01 M, pH 10.0. Calibration curves were linear over a concentration range of 6 /L- 30 /L in water and 30 /kg - 200 /kg in soil. The method is specific and sensitive with a detection limit of 0.6 /L for DIA, 0.7 /L for DIA and AT in water, 2.0 /kg for DIA, 2.3 /kg for DIA and AT in soil. Recovery experiments were performed with irrigation water samples yielding average recoveries between 80-100% and performed on soil samples yielding average recoveries between 45-65%. DIA and DEA were not detected in neither water nor soil field samples, but atrazine was found in water after the first month following herbicide application at a concentration level of 5,8 /L, and in soil AT a concentration level of 97 /kg - at the second month, no atrazine was found in water but 42 /kg were detected in soil

The DTU12MDT global mean dynamic topography and ocean circulation model

DEFF Research Database (Denmark)

Knudsen, Per; Andersen, Ole B.

2013-01-01

combined with the DTU10MSS mean sea surface model to construct a global mean dynamic topography model named DTU10MDT. The results of analyses clearly demonstrated the value of the GOCE mission. Both the resolution and the estimation of the surface currents have been improved significantly compared...

Artefactual subcortical hyperperfusion in PET studies normalized to global mean: lessons from Parkinson's disease

DEFF Research Database (Denmark)

Borghammer, Per; Cumming, Paul; Aanerud, Joel

2008-01-01

not be detected with present instrumentation and typically-used sample sizes. CONCLUSION: Imposing focal decreases on cortical CBF in conjunction with global mean normalization gives rise to spurious relative CBF increases in all of the regions reported to be hyperactive in PD. Since no PET study has reported......AIM: Recent studies of Parkinson's disease (PD) report subcortical increases of cerebral blood flow (CBF) or cerebral metabolic rate of glucose (CMRglc), after conventional normalization to the global mean. However, if the global mean CBF or CMRglc is decreased in the PD group, this normalization...... necessarily generates artificial relative increases in regions unaffected by the disease. This potential bias may explain the reported subcortical increases in PD. To test this hypothesis, we performed simulations with manipulation and subsequently analysis of sets of quantitative CBF maps by voxel...

Removal of PAHs from contaminated clayey soil by means of electro-osmosis

KAUST Repository

Lima, Ana T.

2011-06-01

The removal of polycyclic aromatic hydrocarbons (PAHs) from clayey soils is an intricate task. The low porosity of compacted clayey soil hinders bacterial activity and makes convective removal by hydraulic flow impossible. Electro-osmosis is a process that has been used for the mobilization and cleanup of contaminants in clayey soils with varying successes. The present study focuses on the remediation of a contaminated peaty clay soil, located in Olst - the Netherlands, by means of electro-osmosis. The soil was originally contaminated by an asphalt production plant, active from 1903 to 1983, and presents high levels of all 16 priority PAHs indicated by the US Environmental Protection Agency (EPA). Such a long contact times of PAH with the soil (≥100 years) presents a unique study material with well established solid/liquid contaminant partitioning equilibrium, preferable to artificially spiked soil. A batch of 6 electro-osmosis laboratory experiments was carried out to study the removal of 16 PAHs through electro-osmosis. In these experiments, water and a surfactant (Tween 80) were used to enhance the PAH desorption. The electro-osmotic conductivities ranged from 2.88 × 10-10 to a substantial 1.19 × 10-7 m2 V-1 s -1 when applying a current density of 0.005-0.127 A m-2. Electro-osmosis was expected to occur towards the cathode, because of natural soil characteristics (negative zeta potential), but presented scattered directions. The use of reference electrodes proved to be very effective to the prediction of the flow direction. Finally, the addition of Tween 80 as a surfactant enhanced PAH removal up to 30% of the total PAH content of the soil in 9 days. © 2011 Elsevier B.V.

Are there links between responses of soil microbes and ecosystem functioning to elevated CO2, N deposition and warming? A global perspective

NARCIS (Netherlands)

Garcia-Palacios, Pablo; Vandegehuchte, Martijn L.; Shaw, E. Ashley; Dam, Marie; Post, Keith H.; Ramirez, Kelly S.; Sylvain, Zachary A.; de Tomasel, Cecilia Milano; Wall, Diana H.

2015-01-01

In recent years, there has been an increase in research to understand how global changes' impacts on soil biota translate into altered ecosystem functioning. However, results vary between global change effects, soil taxa, and ecosystem processes studied, and a synthesis of relationships is lacking.

Exploring Patterns of Soil Organic Matter Decomposition with Students and the Public Through the Global Decomposition Project (GDP)

Science.gov (United States)

Wood, J. H.; Natali, S.

2014-12-01

The Global Decomposition Project (GDP) is a program designed to introduce and educate students and the general public about soil organic matter and decomposition through a standardized protocol for collecting, reporting, and sharing data. This easy-to-use hands-on activity focuses on questions such as "How do environmental conditions control decomposition of organic matter in soil?" and "Why do some areas accumulate organic matter and others do not?" Soil organic matter is important to local ecosystems because it affects soil structure, regulates soil moisture and temperature, and provides energy and nutrients to soil organisms. It is also important globally because it stores a large amount of carbon, and when microbes "eat", or decompose organic matter they release greenhouse gasses such as carbon dioxide and methane into the atmosphere, which affects the earth's climate. The protocol describes a commonly used method to measure decomposition using a paper made of cellulose, a component of plant cell walls. Participants can receive pre-made cellulose decomposition bags, or make decomposition bags using instructions in the protocol and easily obtained materials (e.g., window screen and lignin-free paper). Individual results will be shared with all participants and the broader public through an online database. We will present decomposition bag results from a research site in Alaskan tundra, as well as from a middle-school-student led experiment in California. The GDP demonstrates how scientific methods can be extended to educate broader audiences, while at the same time, data collected by students and the public can provide new insight into global patterns of soil decomposition. The GDP provides a pathway for scientists and educators to interact and reach meaningful education and research goals.

Global-scale assessment and combination of SMAP with ASCAT (Active) and AMSR2 (Passive) soil moisture products

Science.gov (United States)

Global-scale surface soil moisture (SSM) products retrieved from active and passive microwave remote sensing provide an effective method for monitoring near-real-time SSM content with nearly daily temporal resolution. In the present study, we first inter-compared global-scale error patterns and comb...

Biochar effects on soils: overview and knowledge gaps

Science.gov (United States)

Verheijen, F. G. A.; Jeffery, S.; Bastos, A. C.; van der Velde, M.

2012-04-01

One of the cornerstones of the sustainable biochar concept is to improve, or at least to not deteriorate, soil quality and functioning. The idea of global sustainable biochar systems, with biochar applied to global cropland and grassland soils, has highlighted limitations in: i) current scientific understanding of biochar interactions with soil components, ii) the capacity to assess ecosystem services provided by soils, and iii) the uncertainty in spatio-temporal representation of both (i) and (ii). Pyrolysis conditions and feedstock characteristics largely control the physico-chemical properties of the resulting biochar, which in turn determine the suitability for a given application. Soils are highly heterogeneous systems at a range of scales. Combinations of land use, soil management and changing climatic conditions further enhance this heterogeneity. While this leads to difficulties in identifying the underlying mechanisms behind reported effects in the scientific literature, it also provides an opportunity for 'critical matching' of biochar properties that are best suited to a particular site (depending on soil type, hydrology, climate, land use, soil contaminants, etc.). Biochar's relatively long mean residence times in soils (100s of years) make it a potential instrument for sequestering carbon (if done sustainably). However, that same long mean residence time sets biochar apart from conventional soil amendments (such as manures and other organic fertilizers) that are considered as transient in the soil (1-10s of years). The functional life time of biochar in soils essentially moves biochar from a soil management tool to a geo-engineering technique. One of the consequences is that desired ecosystem services that are provided by soils, have to be projected for the same time period. This presentation aims to discuss critical knowledge gaps in biochar-soil-ecosystem interactions against a background of ecosystem services.

Risks for the global freshwater system at 1.5 °C and 2 °C global warming

Science.gov (United States)

Döll, Petra; Trautmann, Tim; Gerten, Dieter; Müller Schmied, Hannes; Ostberg, Sebastian; Saaed, Fahad; Schleussner, Carl-Friedrich

2018-04-01

To support implementation of the Paris Agreement, the new HAPPI ensemble of 20 bias-corrected simulations of four climate models was used to drive two global hydrological models, WaterGAP and LPJmL, for assessing freshwater-related hazards and risks in worlds approximately 1.5 °C and 2 °C warmer than pre-industrial. Quasi-stationary HAPPI simulations are better suited than transient CMIP-like simulations for assessing hazards at the two targeted long-term global warming (GW) levels. We analyzed seven hydrological hazard indicators that characterize freshwater-related hazards for humans, freshwater biota and vegetation. Using a strict definition for significant differences, we identified for all but one indicator that areas with either significantly wetter or drier conditions (calculated as percent changes from 2006–2015) are smaller in the 1.5 °C world. For example, 7 day high flow is projected to increase significantly on 11% and 21% of the global land area at 1.5 °C and 2 °C, respectively. However, differences between hydrological hazards at the two GW levels are significant on less than 12% of the area. GW affects a larger area and more people by increases—rather than by decreases—of mean annual and 1-in-10 dry year streamflow, 7 day high flow, and groundwater recharge. The opposite is true for 7 day low flow, maximum snow storage, and soil moisture in the driest month of the growing period. Mean annual streamflow shows the lowest projected percent changes of all indicators. Among country groups, low income countries and lower middle income countries are most affected by decreased low flows and increased high flows, respectively, while high income countries are least affected by such changes. The incremental impact between 1.5 °C and 2 °C on high flows would be felt most by low income and lower middle income countries, the effect on soil moisture and low flows most by high income countries.

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

Science.gov (United States)

Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

2015-01-01

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

Mapping monthly rainfall erosivity in Europe.

Science.gov (United States)

Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

2017-02-01

Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be

Atmospheric deposition and soil vertical distribution of {sup 7}Be in a semiarid region of central Argentina

Energy Technology Data Exchange (ETDEWEB)

Lohaiza, Flavia A.; Velasco, Hugo; Ayub, Jimena Juri; Rizzotto, Marcos; Valladares, Diego L. [Grupo de Estudios Ambientales, Instituto de Matematica Aplicada San Luis, Universidad Nacional de San Luis - CONICET, Ejercito de los Andes 950, D5700HHW San Luis (Argentina)

2014-07-01

Beryllium-7 is a potentially powerful tracer of soil erosion but poor information on {sup 7}Be atmospheric deposition and associated soil inventories in a semiarid region of Central Argentina exists. We estimated the {sup 7}Be atmospheric wet deposition and {sup 7}Be inventory in undisturbed soils north of the City of San Luis (S 33 deg. 9'; W 66 deg. 16') and explored its seasonal variation. Rain and soil samples were collected during 2006-2008 and 2009-2012, respectively. The atmospheric wet deposition was estimated considering both the mean activity concentration in rainwater and the precipitation regime of the region. Using the assessed monthly wet deposition of {sup 7}Be, the expected {sup 7}Be areal activity in soil was estimated applying a simple model. These estimated values were confronted with the experimental measurements in soil. The {sup 7}Be rainwater activity concentration ranged from 0.7 to 3.2 Bq l{sup -1}, with a mean of 1.7 Bq l{sup -1} (sd = 0.53 Bq l{sup -1}). A good linear relationship between {sup 7}Be wet deposition and rain magnitude was obtained (R=0.92, p<0.0001). The wet deposition on soil ranged from 1.1 to 120 Bq m{sup -2} with a mean value of 32.7 Bq m-2 (sd = 29.9 Bq m-2). The annual depositional flux was estimated at 1140 ± 120 Bq m{sup -2} y{sup -1}. The {sup 7}Be mass activity (Bq kg{sup -1}) values in soil samples in the wet period (November-April) were higher than in the dry period (May-October). A typical decreasing exponential function of {sup 7}Be areal activity (Bq m{sup -2}) with soil mass depth (kg m{sup -2}) was found and the distribution parameters for each month were determined. The minimum value of areal activity was 51 Bq m{sup -2} in August, reaching the maximum of 438 Bq m{sup -2} in February. The relaxation mass depth ranged from 2.9 kg m{sup -2} in March to 1.3 kg m{sup -2} in August. The confrontation of experimental measurements in soil with the estimated values using the model showed a good agreement

Developing and testing a global-scale regression model to quantify mean annual streamflow

Science.gov (United States)

Barbarossa, Valerio; Huijbregts, Mark A. J.; Hendriks, A. Jan; Beusen, Arthur H. W.; Clavreul, Julie; King, Henry; Schipper, Aafke M.

2017-01-01

Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 106 km2. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process-based global hydrological models.

Modelling soil erosion at European scale: the importance of management practices and the future climate and land use scenarios

Science.gov (United States)

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Poesen, Jean; Lugato, Emanuele; Montanarella, Luca; Alewell, Christine; Borrelli, Pasquale

2017-04-01

The implementation of RUSLE2015 for modelling soil loss by water erosion at European scale has introduced important aspects related to management practices. The policy measurements such as reduced tillage, crop residues, cover crops, grass margins, stone walls and contouring have been incorporated in the RUSLE2015 modelling platform. The recent policy interventions introduced in Good Agricultural Environmental Conditions of Common Agricultural Policy have reduced the rate of soil loss in the EU by an average of 9.5% overall, and by 20% for arable lands (NATURE, 526, 195). However, further economic and political action should rebrand the value of soil as part of ecosystem services, increase the income of rural land owners, involve young farmers and organize regional services for licensing land use changes (Land Degradation and Development, 27 (6): 1547-1551). RUSLE2015 is combining the future policy scenarios and land use changes introduced by predictions of LUISA Territorial Modelling Platform. Latest developments in RUSLE2015 allow also incorporating the climate change scenarios and the forthcoming intensification of rainfall in North and Central Europe contrary to mixed trends in Mediterranean basin. The rainfall erosivity predictions estimate a mean increase by 18% in European Union by 2050. Recently, a module of CENTURY model was coupled with the RUSLE2015 for estimating the effect of erosion in current carbon balance in European agricultural lands (Global Change Biology, 22(5), 1976-1984; 2016). Finally, the monthly erosivity datasets (Science of the Total Environment, 579: 1298-1315) introduce a dynamic component in RUSLE2015 and it is a step towards spatio-temporal soil erosion mapping at continental scale. The monthly mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should apply in different seasons of the year. In the future, the soil erosion-modelling platform will

MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG V006

Data.gov (United States)

National Aeronautics and Space Administration — MODIS/Terra Aerosol Cloud Water Vapor Ozone Monthly L3 Global 1Deg CMG (MOD08_M3). MODIS was launched aboard the Terra satellite on December 18, 1999 (10:30 am...

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015

OpenAIRE

Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and sol...

Soils and Global Change in the Carbon Cycle over Geological Time

Science.gov (United States)

Retallack, G. J.

2003-12-01

Soils play an important role in the carbon cycle as the nutrition of photosynthesized biomass. Nitrogen fixed by microbes from air is a limiting nutrient for ecosystems within the first flush of ecological succession of new ground, and sulfur can limit some components of wetland ecosystems. But over the long term, the limiting soil nutrient is phosphorus extracted by weathering from minerals such as apatite (Vitousek et al., 1997a; Chadwick et al., 1999). Life has an especially voracious appetite for common alkali (Na+ and K+) and alkaline earth (Ca2+ and Mg2+) cations, supplied by hydrolytic weathering, which is in turn amplified by biological acidification (Schwartzmann and Volk, 1991; see Chapter 5.06). These mineral nutrients fuel photosynthetic fixation and chemical reduction of atmospheric CO2 into plants and plantlike microbes, which are at the base of the food chain. Plants and photosynthetic microbes are consumed and oxidized by animals, fungi, and other respiring microbes, which release CO2, methane, and water vapor to the air. These greenhouse gases absorb solar radiation more effectively than atmospheric oxygen and nitrogen, and are important regulators of planetary temperature and albedo (Kasting, 1992). Variations in solar insolation ( Kasting, 1992), mountainous topography ( Raymo and Ruddiman, 1992), and ocean currents ( Ramstein et al., 1997) also play a role in climate, but this review focuses on the carbon cycle. The carbon cycle is discussed in detail in Volume 8 of this Treatise.The greenhouse model for global paleoclimate has proven remarkably robust (Retallack, 2002), despite new challenges ( Veizer et al., 2000). The balance of producers and consumers is one of a number of controls on atmospheric greenhouse gas balance, because CO2 is added to the air from fumaroles, volcanic eruptions, and other forms of mantle degassing (Holland, 1984). Carbon dioxide is also consumed by burial as carbonate and organic matter within limestones and other

Effect of soil warming and rainfall patterns on soil N cycling in northern Europe

DEFF Research Database (Denmark)

Patil, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

2010-01-01

. These changes may affect soil moisture regimes, soil water drainage, soil nitrogen (N) availability and N leaching to aquatic environment and N2O emissions to atmosphere. Thus it is important to study the effects of increased soil temperature and varying rainfall patterns on soil N cycling in arable land from...... temperate climates, which is a major source of N pollution. An open-field lysimeter study was carried out during 2008-2009 in Denmark on loamy sand soil (Typic Hapludult) with three factors: number of rainy days, rainfall amount and soil warming. Number of rainy days included the mean monthly rainy days...... by 5 °C at 0.1 m depth as ‘heated' and non-heated as ‘control' treatments. Automated mobile rain-out shelter and irrigation system, and insulated buried heating cables were used to impose the treatments. Soil warming, compared with unheated control, advanced winter wheat crop development, and increased...

Can climate models be tuned to simulate the global mean absolute temperature correctly?

Science.gov (United States)

Duan, Q.; Shi, Y.; Gong, W.

2016-12-01

The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.

The global extent and determinants of savanna and forest as alternative biome states.

Science.gov (United States)

Staver, A Carla; Archibald, Sally; Levin, Simon A

2011-10-14

Theoretically, fire-tree cover feedbacks can maintain savanna and forest as alternative stable states. However, the global extent of fire-driven discontinuities in tree cover is unknown, especially accounting for seasonality and soils. We use tree cover, climate, fire, and soils data sets to show that tree cover is globally discontinuous. Climate influences tree cover globally but, at intermediate rainfall (1000 to 2500 millimeters) with mild seasonality (less than 7 months), tree cover is bimodal, and only fire differentiates between savanna and forest. These may be alternative states over large areas, including parts of Amazonia and the Congo. Changes in biome distributions, whether at the cost of savanna (due to fragmentation) or forest (due to climate), will be neither smooth nor easily reversible.

On the spectral composition of global radiation

Energy Technology Data Exchange (ETDEWEB)

Major, G

1983-01-01

The global radiation is recorded at several stations on the Earth. The information about its spectral composition is poor. In this paper the spectral composition means the ratio of spectral global radiation measured by coloured glass filter domes to the total global radiation. From the measuements made by Klein and Goldberg it follows that the monthly ratios vary significantly from place to place, while the variations from month to month at one place are significant only at the station which lies near to the North Pole. The Budapest data proved the dominant effect of cloudiness on the spectral composition of global radiation. This effect is in good statistical relationship with the relative global radiation. The regression constant tabulated in this paper do not contain the error of zero point elevation which is due to the overheating of glass filters by the absorbed solar radiation.

Regional amplification of extreme temperatures strongly controlled by soil moisture-temperature feedbacks

Science.gov (United States)

Vogel, M.; Orth, R.; Seneviratne, S. I.

2016-12-01

Land temperatures, and in particular hot extremes, will likely increase by more than 2° C in many regions, even in the case that the global temperature increase with respect to pre-industrial levels can be limited to 2°C. We investigate here the role of soil moisture-temperature feedbacks for projected changes of extreme temperatures by comparing experiments from the GLACE-CMIP5 (Global Land-Atmosphere Coupling Experiment - Coupled Model Intercomparison Project Phase 5) project. In particular, we consider fully coupled experiments with all 6 involved GCMs and corresponding experiments where soil moisture is fixed to the local present-day seasonal cycle until the end of the 21st century. We consider the yearly hottest days and apply a scaling approach whereby we relate changes of hottest days to global mean temperature increase. We find that soil moisture-temperature coupling significantly contributes to additional future warming of extreme temperatures in many regions: In particular, it can explain more than 70% of the warming amplification of hottest days compared to global mean temperature in Central Europe, Central North America and Northern Australia, and around 50% of this signal in the Amazonian Region and Southern Africa.

FUNGAL BIOGEOGRAPHY. Response to Comment on "Global diversity and geography of soil fungi".

Science.gov (United States)

Tedersoo, Leho; Bahram, Mohammad; Põlme, Sergei; Anslan, Sten; Riit, Taavi; Kõljalg, Urmas; Nilsson, R Henrik; Hildebrand, Falk; Abarenkov, Kessy

2015-08-28

Schadt and Rosling (Technical Comment, 26 June 2015, p. 1438) argue that primer-template mismatches neglected the fungal class Archaeorhizomycetes in a global soil survey. Amplicon-based metabarcoding of nine barcode-primer pair combinations and polymerase chain reaction (PCR)-free shotgun metagenomics revealed that barcode and primer choice and PCR bias drive the diversity and composition of microorganisms in general, but the Archaeorhizomycetes were little affected in the global study. We urge that careful choice of DNA markers and primers is essential for ecological studies using high-throughput sequencing for identification. Copyright © 2015, American Association for the Advancement of Science.

Forest Soil Bacteria: Diversity, Involvement in Ecosystem Processes, and Response to Global Change.

Science.gov (United States)

Lladó, Salvador; López-Mondéjar, Rubén; Baldrian, Petr

2017-06-01

The ecology of forest soils is an important field of research due to the role of forests as carbon sinks. Consequently, a significant amount of information has been accumulated concerning their ecology, especially for temperate and boreal forests. Although most studies have focused on fungi, forest soil bacteria also play important roles in this environment. In forest soils, bacteria inhabit multiple habitats with specific properties, including bulk soil, rhizosphere, litter, and deadwood habitats, where their communities are shaped by nutrient availability and biotic interactions. Bacteria contribute to a range of essential soil processes involved in the cycling of carbon, nitrogen, and phosphorus. They take part in the decomposition of dead plant biomass and are highly important for the decomposition of dead fungal mycelia. In rhizospheres of forest trees, bacteria interact with plant roots and mycorrhizal fungi as commensalists or mycorrhiza helpers. Bacteria also mediate multiple critical steps in the nitrogen cycle, including N fixation. Bacterial communities in forest soils respond to the effects of global change, such as climate warming, increased levels of carbon dioxide, or anthropogenic nitrogen deposition. This response, however, often reflects the specificities of each studied forest ecosystem, and it is still impossible to fully incorporate bacteria into predictive models. The understanding of bacterial ecology in forest soils has advanced dramatically in recent years, but it is still incomplete. The exact extent of the contribution of bacteria to forest ecosystem processes will be recognized only in the future, when the activities of all soil community members are studied simultaneously. Copyright © 2017 American Society for Microbiology.

Statistical sampling approaches for soil monitoring

NARCIS (Netherlands)

Brus, D.J.

2014-01-01

This paper describes three statistical sampling approaches for regional soil monitoring, a design-based, a model-based and a hybrid approach. In the model-based approach a space-time model is exploited to predict global statistical parameters of interest such as the space-time mean. In the hybrid

Integrated Global Radiosonde Archive (IGRA) - Monthly Means (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous...

Optimization of sampling for the determination of the mean Radium-226 concentration in surface soil

International Nuclear Information System (INIS)

Williams, L.R.; Leggett, R.W.; Espegren, M.L.; Little, C.A.

1987-08-01

This report describes a field experiment that identifies an optimal method for determination of compliance with the US Environmental Protection Agency's Ra-226 guidelines for soil. The primary goals were to establish practical levels of accuracy and precision in estimating the mean Ra-226 concentration of surface soil in a small contaminated region; to obtain empirical information on composite vs. individual soil sampling and on random vs. uniformly spaced sampling; and to examine the practicality of using gamma measurements in predicting the average surface radium concentration and in estimating the number of soil samples required to obtain a given level of accuracy and precision. Numerous soil samples were collected on each six sites known to be contaminated with uranium mill tailings. Three types of samples were collected on each site: 10-composite samples, 20-composite samples, and individual or post hole samples; 10-composite sampling is the method of choice because it yields a given level of accuracy and precision for the least cost. Gamma measurements can be used to reduce surface soil sampling on some sites. 2 refs., 5 figs., 7 tabs

Metal-contaminated soil remediation by means of paper mill sludges addition: chemical and ecotoxicological evaluation

International Nuclear Information System (INIS)

Calace, N.; Campisi, T.; Iacondini, A.; Leoni, M.; Petronio, B.M.; Pietroletti, M.

2005-01-01

Metal pollution of soils is a great environmental problem. The major risks due to metal pollution of soil consist of leaching to groundwater and potential toxicity to plants and/or animals. The objective of this study is to evaluate by means of chemical and ecotoxicological approach the effects of paper mill sludge addition on the mobile metal fraction of polluted metal soils. The study was carried out on acidic soil derived from mining activities and thus polluted with heavy metals, and on two paper mill sludges having different chemical features. The results obtained by leaching experiments showed that the addition of a paper mill sludge, consisting mainly of carbonates, silicates and organic matter, to a heavy-metal polluted soil produces a decrease of available metal forms. The carbonate content seems to play a key role in the chemical stabilisation of metals and consequently in a decrease of toxicity of soil. The leached solutions have a non-toxic effect. The mild remediation by addition of sludge has moreover a lasting effect. - Paper mill sludge decreased available metals

A call to strengthen the global strategy against schistosomiasis and soil-transmitted helminthiasis: the time is now.

Science.gov (United States)

Lo, Nathan C; Addiss, David G; Hotez, Peter J; King, Charles H; Stothard, J Russell; Evans, Darin S; Colley, Daniel G; Lin, William; Coulibaly, Jean T; Bustinduy, Amaya L; Raso, Giovanna; Bendavid, Eran; Bogoch, Isaac I; Fenwick, Alan; Savioli, Lorenzo; Molyneux, David; Utzinger, Jürg; Andrews, Jason R

2017-02-01

In 2001, the World Health Assembly (WHA) passed the landmark WHA 54.19 resolution for global scale-up of mass administration of anthelmintic drugs for morbidity control of schistosomiasis and soil-transmitted helminthiasis, which affect more than 1·5 billion of the world's poorest people. Since then, more than a decade of research and experience has yielded crucial knowledge on the control and elimination of these helminthiases. However, the global strategy has remained largely unchanged since the original 2001 WHA resolution and associated WHO guidelines on preventive chemotherapy. In this Personal View, we highlight recent advances that, taken together, support a call to revise the global strategy and guidelines for preventive chemotherapy and complementary interventions against schistosomiasis and soil-transmitted helminthiasis. These advances include the development of guidance that is specific to goals of morbidity control and elimination of transmission. We quantify the result of forgoing this opportunity by computing the yearly disease burden, mortality, and lost economic productivity associated with maintaining the status quo. Without change, we estimate that the population of sub-Saharan Africa will probably lose 2·3 million disability-adjusted life-years and US$3·5 billion of economic productivity every year, which is comparable to recent acute epidemics, including the 2014 Ebola and 2015 Zika epidemics. We propose that the time is now to strengthen the global strategy to address the substantial disease burden of schistosomiasis and soil-transmitted helminthiasis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparing soil moisture memory in satellite observations and models

Science.gov (United States)

Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

2013-04-01

A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the

Carbon budgets of biological soil crusts at micro-, meso-, and global scales

Science.gov (United States)

Sancho, Leopoldo G; Belnap, Jayne; Colesie, Claudia; Raggio, Jose; Weber, Bettina

2016-01-01

The importance of biocrusts in the ecology of arid lands across all continents is widely recognized. In spite of this broad distribution, contributions of biocrusts to the global biogeochemical cycles have only recently been considered. While these studies opened a new view on the global role of biocrusts, they also clearly revealed the lack of data for many habitats and of overall standards for measurements and analysis. In order to understand carbon cycling in biocrusts and the progress which has been made during the last 15 years, we offer a multi-scale approach covering different climatic regions. We also include a discussion on available measurement techniques at each scale: A micro-scale section focuses on the individual organism level, including modeling based on the combination of field and lab data. The meso-scale section addresses the CO2 exchange of a complete ecosystem or at the community level. Finally, we consider the contribution of biocrusts at a global scale, giving a general perspective of the most relevant findings regarding the role of biological soil crusts in the global terrestrial carbon cycle.

Constraining global methane emissions and uptake by ecosystems

International Nuclear Information System (INIS)

Spahni, R.; Wania, R.; Neef, L.; Van Weele, M.; Van Velthoven, P.; Pison, I.; Bousquet, P.

2011-01-01

Natural methane (CH 4 ) emissions from wet ecosystems are an important part of today's global CH 4 budget. Climate affects the exchange of CH 4 between ecosystems and the atmosphere by influencing CH 4 production, oxidation, and transport in the soil. The net CH 4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH 4 emissions for different ecosystems: northern peat-lands (45 degrees-90 degrees N), naturally inundated wetlands (60 degrees S-45 degrees N), rice agriculture and wet mineral soils. Mineral soils are a potential CH 4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003-2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH 4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a significant reduction in the emissions from northern peat-lands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH 4 over the period 1990-2008. Over the whole period we infer an increase of global ecosystem CH 4 emissions of +1.11 TgCH 4 yr -1 , not considering potential additional changes in wetland extent. The increase in simulated CH 4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long term decline of the atmospheric CH 4 growth rate from 1990

Classification of hemispheric monthly mean stratospheric potential vorticity fields

Directory of Open Access Journals (Sweden)

R. Huth

Full Text Available Monthly mean NCEP reanalysis potential vorticity fields at the 650 K isentropic level over the Northern and Southern Hemispheres between 1979 and 1997 were studied using multivariate analysis tools. Principal component analysis in the T-mode was applied to demonstrate the validity of such statistical techniques for the study of stratospheric dynamics and climatology. The method, complementarily applied to both the raw and anomaly fields, was useful in determining and classifying the characteristics of winter and summer PV fields on both hemispheres, in particular, the well-known differences in the behaviour and persistence of the polar vortices. It was possible to identify such features as sudden warming events in the Northern Hemisphere and final warming dates in both hemispheres. The stratospheric impact of other atmospheric processes, such as volcanic eruptions, also identified though the results, must be viewed at this stage as tentative. An interesting change in behaviour around 1990 was detected over both hemispheres.

Key words. Meteorology and atmospheric dynamics (middle atmosphere dynamics; general circulation; climatology

Response of the mean global vegetation distribution to interannual climate variability

Energy Technology Data Exchange (ETDEWEB)

Notaro, Michael [University of Wisconsin-Madison, Center for Climatic Research, Madison, WI (United States)

2008-06-15

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States' ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. (orig.)

Scaling future tropical cyclone damage with global mean temperature

Science.gov (United States)

Geiger, T.; Bresch, D.; Frieler, K.

2017-12-01

Tropical cyclones (TC) are one of the most damaging natural hazards and severely affectmany countries around the globe each year. Their nominal impact is projected to increasesubstantially as the exposed coastal population grows, per capita income increases, andanthropogenic climate change manifests. The magnitude of this increase, however, variesacross regions and is obscured by the stochastic behaviour of TCs, so far impeding arigorous quantification of trends in TC damage with global mean temperature (GMT) rise. Here, we build on the large sample of spatially explicit TCs simulations generated withinISIMIP(2b) for 1) pre-industrial conditions, 2) the historical period, and 3) future projectionsunder RCP2.6 and RCP6.0 to estimate future TC damage assuming fixed present-daysocio-economic conditions or SSP-based future projections of population patterns andincome. Damage estimates will be based on region-specific empirical damage modelsderived from reported damages and accounting for regional characteristics of vulnerability.Different combinations of 1) socio-economic drivers with pre-industrial climate or 2) changingclimate with fixed socio-economic conditions will be used to derive functional relationshipsbetween regionally aggregated changes in damages on one hand and global meantemperature and socio-economic predictors on the other hand. The obtained region-specific scaling of future TC damage with GMT provides valuable inputfor IPCC's special report on the impacts of global warming of 1.5°C by quantifying theincremental changes in impact with global warming. The approach allows for an update ofdamage functions used in integrated assessment models, and contributes to assessing theadequateness of climate mitigation and adaptation strategies.

Are soils in urban ecosystems compacted? A citywide analysis.

Science.gov (United States)

Edmondson, Jill L; Davies, Zoe G; McCormack, Sarah A; Gaston, Kevin J; Leake, Jonathan R

2011-10-23

Soil compaction adversely influences most terrestrial ecosystem services on which humans depend. This global problem, affecting over 68 million ha of agricultural land alone, is a major driver of soil erosion, increases flood frequency and reduces groundwater recharge. Agricultural soil compaction has been intensively studied, but there are no systematic studies investigating the extent of compaction in urban ecosystems, despite the repercussions for ecosystem function. Urban areas are the fastest growing land-use type globally, and are often assumed to have highly compacted soils with compromised functionality. Here, we use bulk density (BD) measurements, taken to 14 cm depth at a citywide scale, to compare the extent of surface soil compaction between different urban greenspace classes and agricultural soils. Urban soils had a wider BD range than agricultural soils, but were significantly less compacted, with 12 per cent lower mean BD to 7 cm depth. Urban soil BD was lowest under trees and shrubs and highest under herbaceous vegetation (e.g. lawns). BD values were similar to many semi-natural habitats, particularly those underlying woody vegetation. These results establish that, across a typical UK city, urban soils were in better physical condition than agricultural soils and can contribute to ecosystem service provision.

Predictions of soil-water potentials in the north-western Sonoran Desert

Energy Technology Data Exchange (ETDEWEB)

Young, D.R.; Nobel, P.S.

1986-03-01

A simple computer model was developed to predict soil-water potential at a Sonoran Desert site. The variability of precipitation there, coupled with the low water-holding capacity of the sandy soil, result in large temporal and spatial variations in soil-water potential. Predicted soil-water potentials for depths of 5, 10 and 20 cm were in close agreement with measured values as the soil dried after an application of water. Predicted values at a depth of 10 cm, the mean rooting depth of Agave deserti and other succulents common at the study site, also agreed with soil-water potentials measured in the field throughout 1 year. Both soil-water potential and evaporation from the soil surface were very sensitive to simulated changes in the hydraulic conductivity of the soil. The annual duration of soil moisture adequate for succulents was dependent on the rainfall as well as on the spacing and amount of individual rainfalls. The portion of annual precipitation evaporated from the soil surface varied from 73% in a dry year (77 mm precipitation) to 59% in a wet year (597 mm). Besides using the actual precipitation events, simulations were performed using the figures for total monthly precipitation. Based on the average number of rainfalls for a particular month, the rainfall was distributed throughout the month in the model. Predictions using both daily and monthly inputs were in close agreement, especially for the number of days during a year when the soil-water potential was sufficient for water absorption by the succulent plants (above -0.5 MPa).

Global-scale high-resolution ( 1 km) modelling of mean, maximum and minimum annual streamflow

Science.gov (United States)

Barbarossa, Valerio; Huijbregts, Mark; Hendriks, Jan; Beusen, Arthur; Clavreul, Julie; King, Henry; Schipper, Aafke

2017-04-01

Quantifying mean, maximum and minimum annual flow (AF) of rivers at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. AF metrics can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict AF metrics based on climate and catchment characteristics. Yet, so far, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. We developed global-scale regression models that quantify mean, maximum and minimum AF as function of catchment area and catchment-averaged slope, elevation, and mean, maximum and minimum annual precipitation and air temperature. We then used these models to obtain global 30 arc-seconds (˜ 1 km) maps of mean, maximum and minimum AF for each year from 1960 through 2015, based on a newly developed hydrologically conditioned digital elevation model. We calibrated our regression models based on observations of discharge and catchment characteristics from about 4,000 catchments worldwide, ranging from 100 to 106 km2 in size, and validated them against independent measurements as well as the output of a number of process-based global hydrological models (GHMs). The variance explained by our regression models ranged up to 90% and the performance of the models compared well with the performance of existing GHMs. Yet, our AF maps provide a level of spatial detail that cannot yet be achieved by current GHMs.

Range of monthly mean hourly land surface air temperature diurnal cycle over high northern latitudes

Science.gov (United States)

Wang, Aihui; Zeng, Xubin

2014-05-01

Daily maximum and minimum temperatures over global land are fundamental climate variables, and their difference represents the diurnal temperature range (DTR). While the differences between the monthly averaged DTR (MDTR) and the range of monthly averaged hourly temperature diurnal cycle (RMDT) are easy to understand qualitatively, their differences have not been quantified over global land areas. Based on our newly developed in situ data (Climatic Research Unit) reanalysis (Modern-Era Retrospective analysis for Research and Applications) merged hourly temperature data from 1979 to 2009, RMDT in January is found to be much smaller than that in July over high northern latitudes, as it is much more affected by the diurnal radiative forcing than by the horizontal advection of temperature. In contrast, MDTR in January is comparable to that in July over high northern latitudes, but it is much larger than January RMDT, as it primarily reflects the movement of lower frequency synoptic weather systems. The area-averaged RMDT trends north of 40°N are near zero in November, December, and January, while the trends of MDTR are negative. These results suggest the need to use both the traditional MDTR and RMDT suggested here in future observational and modeling studies. Furthermore, MDTR and its trend are more sensitive to the starting hour of a 24 h day used in the calculations than those for RMDT, and this factor also needs to be considered in model evaluations using observational data.

The Implement of a Multi-layer Frozen Soil Scheme into SSiB3 and its Evaluation over Cold Regions

Science.gov (United States)

Li, Q.

2016-12-01

The SSiB3 is a biophysics-based model of land-atmosphere interactions and is designed for global and regional studies. It has three soil layers, three snow layers, as well as one vegetation layer. Soil moisture of the three soil layers, interception water store for the canopy, subsurface soil temperature, ground temperature, canopy temperature and snow water equivalent are all predicted based on the water and energy balance at canopy, soil and snow. SSiB3 substantially enhances the model's capability for cold season studies and produces reasonable results compared with observations. However, frozen soil processes are ignored in the SSiB3 and may have effects on the interannual variability of soil temperature and deep soil memory. A multi-layer comprehensive frozen soil scheme (FSM), which is developed for climate study has been implemented into the SSiB3 to describe soil heat transfer and water flow affected by frozen processed in soil. In the coupled SSiB3-FSM, both liquid water and ice content have been taken into account in the frozen soil hydrologic and thermal property parameterization. The maximum soil layer depth could reach 10 meters thick depending on land conditions. To better evaluate the models' performance, the coupled offline SSiB3-FSM and SSiB3 have been driven from 1948 to 1958 by the Princeton global meteorological data set, respectively. For the 10yrs run, the coupled SSiB3-FSM almost captures the features over different regions, especially cold regions. In order to analysis and compare the differences of SSIB3-FSM and SSIB3 in detail, monthly mean surface temperature for different regions are compared with CAMS data. The statistical results of surface skin temperature show that high latitude regions, Africa, Eastern Australia, and North American monsoon regions have been greatly improved in SSIB3-FSM. For the global statistics, the RMSE of the surface temperature simulated by SSiB3-FSM can be improved about 0.6K compared to SSiB3. In this study

The Role of Therapy Education of Islamic Meaning to Overcome Today’s Global Human Crisis

Directory of Open Access Journals (Sweden)

Nina Aminah

2016-02-01

Full Text Available Modern community are exposed to current issues related to the very complex personality. Islam offers a therapeutic meaning to overcome the global human crisis through the holy Qu’ran. This study aims to provide a qualitative analysis of logotherapy alternative to global human who experience critical conditions such as the door of death (sakaratul maut, acute illnesses, HIV Aids, kidney illness, stroke, coma, depression / stress, due to the hazards, and other refractory disease. The study showed that the therapy of Islamic meaning based on the holy Qur’an is broader and more comprehensive than the meaning therapy by Viktor E. Frankl.

Assessment of the SMAP Passive Soil Moisture Product

Science.gov (United States)

Chan, Steven K.; Bindlish, Rajat; O'Neill, Peggy E.; Njoku, Eni; Jackson, Tom; Colliander, Andreas; Chen, Fan; Burgin, Mariko; Dunbar, Scott; Piepmeier, Jeffrey;

Does a General Temperature-Dependent Q10 Model of Soil Respiration Exist at Biome and Global Scale?

Institute of Scientific and Technical Information of China (English)

Hua CHEN; Han-Qin TIAN

2005-01-01

Soil respiration (SR) is commonly modeled by a Q10 (an indicator of temperature sensitivity)function in ecosystem models. Q10is usually treated as a constant of 2 in these models, although Q10 value of SR often decreases with increasing temperatures. It remains unclear whether a general temperaturedependent Q10 model of SR exists at biome and global scale. In this paper, we have compiled the long-term Q10 data of 38 SR studies ranging from the Boreal, Temperate, to Tropical/Subtropical biome on four continents.Our analysis indicated that the general temperature-dependent biome Q10 models of SR existed, especially in the Boreal and Temperate biomes. A single-exponential model was better than a simple linear model in fitting the average Q10 values at the biome scale. Average soil temperature is a better predictor of Q10 value than average air temperature in these models, especially in the Boreal biome. Soil temperature alone could explain about 50% of the Q10 variations in both the Boreal and Temperate biome single-exponential Q10 model. Q10 value of SR decreased with increasing soil temperature but at quite different rates among the three biome Q10 models. The k values (Q10 decay rate constants) were 0.09, 0.07, and 0.02/℃ in the Boreal, Temperate, and Tropical/Subtropical biome, respectively, suggesting that Q10 value is the most sensitive to soil temperature change in the Boreal biome, the second in the Temperate biome, and the least sensitive in the Tropical/Subtropical biome. This also indirectly confirms that acclimation of SR in many soil warming experiments probably occurs. The k value in the "global" single-exponential Q10 model which combined both the Boreal and Temperate biome data set was 0.08/℃. However, the global general temperature-dependent Q10model developed using the data sets of the three biomes is not adequate for predicting Q10 values of SR globally.The existence of the general temperature-dependent Q10 models of SR in the Boreal and

Monthly fluctuation of termite caste proportions (Isoptera) within fire ant mounds (hymenoptera: formicidae)

Science.gov (United States)

Thomas G. Shelton; J.T. Vogt; Marla J. Tanley; Arthur G. Appel

2003-01-01

Monthly abundance and caste proportions of subterranean termites (Reticulitennes spp.) inhabiting red imported fire ant (Solenopsis invicta Buren) mounds were recorded during 1999 and 2000 from a relatively undisturbed forest edge in Tuskegee, Alabama. Temperature data were also recorded at these mounds; mean air, soil, and mound temperatures followed a sine model over...

Protecting global soil resources for future generations

Science.gov (United States)

Montanarella, Luca

2017-04-01

The latest Status of World's Soil Resources report has highlighted that soils are increasingly under pressure by numerous human induced degradation processes in most parts of the world. The limits of our planetary boundaries concerning vital soil resources have been reached and without reversing this negative trend there will be a serious lack of necessary soil resources for future generations. It has been therefore of the highest importance to include soils within some of the Sustainable Development Goals (SDG) recently approved by the United Nations. Sustainable development can not be achieved without protecting the limited, non-renewable, soil resources of our planet. There is the need to limit on-going soil degradation processes and to implement extensive soil restoration activities in order to strive towards a land degradation neutral (LDN) world, as called upon by SDG 15. Sustainable soil management needs to be placed at the core of any LDN strategy and therefore it is of highest importance that the recently approved Voluntary Guidelines for Sustainable Soil Management (VGSSM) of FAO get fully implemented at National and local scale.Sustainable soil management is not only relevant for the protection of fertile soils for food production, but also to mitigate and adopt to climate change at to preserve the large soil biodiversity pool. Therefore the VGSSM are not only relevant to FAO, but also the the climate change convention (UNFCCC) and the biodiversity convention (CBD). An integrated assessment of the current land degradation processes and the available land restoration practices is needed in order to fully evaluate the potential for effectively achieving LDN by 2030. The on-going Land Degradation and Restoration Assessment (LDRA) of the Intergovernmental Platform for Biodiversity and Ecosystem Services (IPBES) will provide the necessary scientific basis for the full implementation of the necessary measures for achieving the planned SGS's relevant to land

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

Science.gov (United States)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good

Large Differences in Global and Regional Total Soil Carbon Stock Estimates Based on SoilGrids, HWSD, and NCSCD: Intercomparison and Evaluation Based on Field Data From USA, England, Wales, and France

Science.gov (United States)

Tifafi, Marwa; Guenet, Bertrand; Hatté, Christine

2018-01-01

Soils are the major component of the terrestrial ecosystem and the largest organic carbon reservoir on Earth. However, they are a nonrenewable natural resource and especially reactive to human disturbance and climate change. Despite its importance, soil carbon dynamics is an important source of uncertainty for future climate predictions and there is a growing need for more precise information to better understand the mechanisms controlling soil carbon dynamics and better constrain Earth system models. The aim of our work is to compare soil organic carbon stocks given by different global and regional databases that already exist. We calculated global and regional soil carbon stocks at 1 m depth given by three existing databases (SoilGrids, the Harmonized World Soil Database, and the Northern Circumpolar Soil Carbon Database). We observed that total stocks predicted by each product differ greatly: it is estimated to be around 3,400 Pg by SoilGrids and is about 2,500 Pg according to Harmonized World Soil Database. This difference is marked in particular for boreal regions where differences can be related to high disparities in soil organic carbon concentration. Differences in other regions are more limited and may be related to differences in bulk density estimates. Finally, evaluation of the three data sets versus ground truth data shows that (i) there is a significant difference in spatial patterns between ground truth data and compared data sets and that (ii) data sets underestimate by more than 40% the soil organic carbon stock compared to field data.

Western US high June 2015 temperatures and their relation to global warming and soil moisture

NARCIS (Netherlands)

Philip, Sjoukje Y.; Kew, Sarah F.; Hauser, Mathias; Guillod, Benoit P.; Teuling, Adriaan J.; Whan, Kirien; Uhe, Peter; Oldenborgh, van Geert Jan

2018-01-01

The Western US states Washington (WA), Oregon (OR) and California (CA) experienced extremely high temperatures in June 2015. The temperature anomalies were so extreme that they cannot be explained with global warming alone. We investigate the hypothesis that soil moisture played an important role

Adding a soil fertility dimension to the global farming systems approach, with cases from Africa

NARCIS (Netherlands)

Smaling, E.M.A.; Dixon, J.

2006-01-01

The global farming systems (GFS) approach is extended by adding a soil fertility and nutrient management dimension for Africa's forest-based, maize mixed, cereal¿root crop mixed, and agro-pastoral millet/sorghum farming systems. Use is made of sustainable livelihood concepts, translated into farmer

Nitrous oxide and methane exchange in two small temperate forest catchments - effects of hydrological gradients and implications for global warming potentials of forest soils

DEFF Research Database (Denmark)

Christiansen, Jesper Riis; Vesterdal, Lars; Gundersen, Per

2012-01-01

half the catchment area at both sites, the global warming potential (GWP) derived from N2O and CH4 was more than doubled when accounting for these wet areas in the catchments. The results stress the importance of wet soils in assessments of forest soil global warming potentials, as even small...

The Role of Low-severity Fire and Thermal Alteration of Soil Organic Matter in Carbon Preservation and GHG Flux From Global Peatlands

Science.gov (United States)

Flanagan, N. E.; Wang, H.; Hodgkins, S. B.; Richardson, C. J.

2017-12-01

Many global peatlands are dominated by fire-adapted plant communities and are subject to frequent wildfires with return intervals ranging between 3 to 100 years. Wildfires in peatlands are typically low-severity events that occur in winter and spring when vegetation is desiccated and soil moisture content is high. As a result, most wildfires consume aboveground fuels in a matter of minutes without igniting the nearly saturated peat. In such fires, surface soil layers are subjected to flash heating with a rapid loss of soil moisture but little loss of soil organic matter (SOM). Such fires have the potential to alter the chemical structure of SOM, even in the absence of combustion, through Maillard's Reaction and similar chemical processes, and through structural changes that protect SOM from decomposition. This study examines the effects of low-intensity surface fires on the recalcitrance of SOM from fire-adapted communities located in subtropical, temperate and sub-boreal peatlands. In addition, soil from a non-fire-adapted Peruvian palm peatland was examined for response to thermal alteration. The timing and temperatures of low-intensity fires were measured in the field during prescribed burns and replicated in simulated fires. The effects of fire on the chemical structure of SOM were examined with FTIR, SEM and XPS. Burned and unburned peat replicates were incubated at three temperatures (5oC, 15oC, 25oC) in controlled chambers for more than six months. Burned replicates initially showed higher CO2, CH4 and NO2 emissions. Yet, within four weeks emissions from the burned replicates dropped below those of unburned replicates and remained significantly lower (10-50%) for the duration of the experiment. In addition, thermal alteration significantly reduced the temperature sensitivity (Q10) of thermally altered peat. After accounting for small initial losses of organic matter (<10 %) during the fire simulations, thermal alteration of SOM resulted in a net long

Cross-cutting activities: Soil quality and soil metagenomics

OpenAIRE

Motavalli, Peter P.; Garrett, Karen A.

2008-01-01

This presentation reports on the work of the SANREM CRSP cross-cutting activities "Assessing and Managing Soil Quality for Sustainable Agricultural Systems" and "Soil Metagenomics to Construct Indicators of Soil Degradation." The introduction gives an overview of the extensiveness of soil degradation globally and defines soil quality. The objectives of the soil quality cross cutting activity are: CCRA-4 (Soil Metagenomics)

Inter-Comparison of Retrieved and Modelled Soil Moisture and Coherency of Remotely Sensed Hydrology Data

Science.gov (United States)

Kolassa, Jana; Aires, Filipe

2013-04-01

A neural network algorithm has been developed for the retrieval of Soil Moisture (SM) from global satellite observations. The algorithm estimates soil moisture from a synergy of passive and active microwave, infrared and visible satellite observations in order to capture the different SM variabilities that the individual sensors are sensitive to. The advantages and drawbacks of each satellite observation have been analysed and the information type and content carried by each observation have been determined. A global data set of monthly mean soil moisture for the 1993-2000 period has been computed with the neural network algorithm (Kolassa et al., in press, 2012). The resulting soil moisture retrieval product has then been used in an inter-comparison study including soil moisture from (1) the HTESSEL model (Balsamo et al., 2009), (2) the WACMOS satellite product (Liu et al., 2011), and (3) in situ measurements from the International Soil Moisture Network (Dorigo et al., 2011). The analysis showed that the satellite remote sensing products are well-suited to capture the spatial variability of the in situ data and even show the potential to improve the modelled soil moisture. Both satellite retrievals also display a good agreement with the temporal structures of the in situ data, however, HTESSEL appears to be more suitable for capturing the temporal variability (Kolassa et al., in press, 2012). The use of this type of neural network approach is currently being investigated as a retrieval option for the SMOS mission. Our soil moisture retrieval product has also been used in a coherence study with precipitation data from GPCP (Adler et al., 2003) and inundation estimates from GIEMS (Prigent et al., 2007). It was investigated on a global scale whether the three observation-based datasets are coherent with each other and show the expected behaviour. For most regions of the Earth, the datasets were consistent and the behaviour observed could be explained with the known

Data Descriptor: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

Science.gov (United States)

John T. Abatzoglou; Solomon Z. Dobrowski; Sean A. Parks; Katherine C. Hegewisch

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from...

Global numbers of infection and disease burden of soil transmitted helminth infections in 2010.

Science.gov (United States)

Pullan, Rachel L; Smith, Jennifer L; Jasrasaria, Rashmi; Brooker, Simon J

2014-01-21

Quantifying the burden of parasitic diseases in relation to other diseases and injuries requires reliable estimates of prevalence for each disease and an analytic framework within which to estimate attributable morbidity and mortality. Here we use data included in the Global Atlas of Helminth Infection to derive new global estimates of numbers infected with intestinal nematodes (soil-transmitted helminths, STH: Ascaris lumbricoides, Trichuris trichiura and the hookworms) and use disability-adjusted life years (DALYs) to estimate disease burden. Prevalence data for 6,091 locations in 118 countries were sourced and used to estimate age-stratified mean prevalence for sub-national administrative units via a combination of model-based geostatistics (for sub-Saharan Africa) and empirical approaches (for all other regions). Geographical variation in infection prevalence within these units was approximated using modelled logit-normal distributions, and numbers of individuals with infection intensities above given thresholds estimated for each species using negative binomial distributions and age-specific worm/egg burden thresholds. Finally, age-stratified prevalence estimates for each level of infection intensity were incorporated into the Global Burden of Disease Study 2010 analytic framework to estimate the global burden of morbidity and mortality associated with each STH infection. Globally, an estimated 438.9 million people (95% Credible Interval (CI), 406.3 - 480.2 million) were infected with hookworm in 2010, 819.0 million (95% CI, 771.7 - 891.6 million) with A. lumbricoides and 464.6 million (95% CI, 429.6 - 508.0 million) with T. trichiura. Of the 4.98 million years lived with disability (YLDs) attributable to STH, 65% were attributable to hookworm, 22% to A. lumbricoides and the remaining 13% to T. trichiura. The vast majority of STH infections (67%) and YLDs (68%) occurred in Asia. When considering YLDs relative to total populations at risk however, the burden

An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

Science.gov (United States)

Wu, Qing; Luu, Quang-Hung; Tkalich, Pavel; Chen, Ge

2018-04-01

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections.

Feasibility of High-Resolution Soil Erosion Measurements by Means of Rainfall Simulations and SfM Photogrammetry

Directory of Open Access Journals (Sweden)

Phoebe Hänsel

2016-11-01

Full Text Available The silty soils of the intensively used agricultural landscape of the Saxon loess province, eastern Germany, are very prone to soil erosion, mainly caused by water erosion. Rainfall simulations, and also increasingly structure-from-motion (SfM photogrammetry, are used as methods in soil erosion research not only to assess soil erosion by water, but also to quantify soil loss. This study aims to validate SfM photogrammetry determined soil loss estimations with rainfall simulations measurements. Rainfall simulations were performed at three agricultural sites in central Saxony. Besides the measured data runoff and soil loss by sampling (in mm, terrestrial images were taken from the plots with digital cameras before and after the rainfall simulation. Subsequently, SfM photogrammetry was used to reconstruct soil surface changes due to soil erosion in terms of high resolution digital elevation models (DEMs for the pre- and post-event (resolution 1 × 1 mm. By multi-temporal change detection, the digital elevation model of difference (DoD and an averaged soil loss (in mm is received, which was compared to the soil loss by sampling. Soil loss by DoD was higher than soil loss by sampling. The method of SfM photogrammetry-determined soil loss estimations also include a comparison of three different ground control point (GCP approaches, revealing that the most complex one delivers the most reliable soil loss by DoD. Additionally, soil bulk density changes and splash erosion beyond the plot were measured during the rainfall simulation experiments in order to separate these processes and associated surface changes from the soil loss by DoD. Furthermore, splash was negligibly small, whereas higher soil densities after the rainfall simulations indicated soil compaction. By means of calculated soil surface changes due to soil compaction, the soil loss by DoD achieved approximately the same value as the soil loss by rainfall simulation.

Using dynamical downscaling to close the gap between global change scenarios and local permafrost dynamics

DEFF Research Database (Denmark)

Stendel, Martin; Romanovsky, Vladimir E.; Christensen, Jens H.

2007-01-01

Even though we can estimate the zonation of present-day permafrost from deep-soil temperatures obtained from global coupled atmosphere-ocean general circulation models (GCMs) by accounting for heat conduction in the frozen soil, it is impossible to explicitly resolve soil properties, vegetation......, in particular in mountainous regions. By using global climate change scenarios as driving fields, one can obtain permafrost dynamics in high temporal resolution on the order of years. For the 21st century under the IPCC SRES scenarios A2 and B2, we find an increase of mean annual ground temperature by up to 6 K...

Response of Soil Temperature to Climate Change in the CMIP5 Earth System Models

Science.gov (United States)

Phillips, C. L.; Torn, M. S.; Koven, C. D.

2014-12-01

Predictions of soil temperature changes are as critical to policy development and climate change adaptation as predictions of air temperature, but have received comparatively little attention. Soil temperature determines seed germination and growth of wild and agricultural plants, and impacts climate through both geophysical and carbon-cycle feedbacks. The Intergovernmental Panel on Climate Change 5th Assessment Report does not report soil temperature predictions, but focuses instead on surface air temperatures, despite the fact that mean annual soil temperatures and mean surface air temperatures are often different from each other. Here we aim to fill this important knowledge gap by reporting soil temperature and moisture predictions for 15 earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison 5 Project (CMIP5). Under the RCP 4.5 and 8.5 emissions scenarios, soil warming is predicted to almost keep pace with soil air warming, with about 10% less warming in soil than air, globally. The slower warming of soil compared to air is likely related to predictions of soil drying, with drier soils having reduced soil heat capacity and thermal conductivity. Mollisol soils, which are typically regarded as the most productive soil order for cultivating cereal crops, are anticipated to see warming in North America of 3.5 to 5.5 °C at the end of the 21st century (2080-2100) compared to 1986-2005. One impact of soil warming is likely to be an acceleration of germination timing, with the 3°C temperature threshold for wheat germination anticipated to advance by several weeks in Mollisol regions. Furthermore, soil warming at 1 m depth is predicted to be almost equivalent to warming at 1 cm depth in frost-free regions, indicating vulnerability of deep soil carbon pools to destabilization. To assess model performance we compare the models' predictions with observations of damping depth, and offsets between mean annual soil and air temperature

Linking soil permeability and soil aggregate stability with root development: a pots experiment (preliminary results)

Science.gov (United States)

Vergani, Chiara; Graf, Frank; Gerber, Werner

2015-04-01

Quantifying and monitoring the contribution of vegetation to the stability of the slopes is a key issue for implementing effective soil bioengineering measures. This topic is being widely investigated both from the hydrological and mechanical point of view. Nevertheless, due to the high variability of the biological components, we are still far from a comprehensive understanding of the role of plants in slope stabilization, especially if the different succession phases and the temporal development of vegetation is considered. Graf et al., 2014, found within the scope of aggregate stability investigations that the root length per soil volume of alder specimen grown for 20 weeks under laboratory conditions is comparable to the one of 20 years old vegetation in the field. This means that already relatively short time scales can provide meaningful information at least for the first stage of colonization of soil bioengineering measures, which is also the most critical. In the present study we analyzed the effect of root growth on two soil properties critical to evaluate the performance of vegetation in restoring and re-stabilizing slopes: permeability and soil aggregate stability. We set up a laboratory experiment in order to work under controlled conditions and limit as much as possible the natural variability. Alnus incana was selected as the study species as it is widely used in restoration projects in the Alps, also because of its capacity to fix nitrogen and its symbiosis with both ecto and arbuscular mycorrhizal fungi. After the first month of growth in germination pots, we planted one specimen each in big quasi cylindrical pots of 34 cm diameter and 35 cm height. The pots were filled with the soil fraction smaller than 10 mm coming from an oven dried moraine collected in a subalpine landslide area (Hexenrübi catchment, central Switzerland). The targeted dry unit weight was 16 kN/m3. The plants have been maintained at a daily temperature of 25°C and relative

Tropical interannual variability in a global coupled GCM: Sensitivity to mean climate state

Energy Technology Data Exchange (ETDEWEB)

Moore, A.M. [Bureau of Meterology Research Centre, Melbourne, Victoria (Australia)

1995-04-01

A global coupled ocean-atmosphere-sea ice general circulation model is used to study interannual variability in the Tropics. Flux correction is used to control the mean climate of the coupled system, and in one configuration of the coupled model, interannual variability in the tropical Pacific is dominated by westward moving anomalies. Through a series of experiments in which the equatorial ocean wave speeds and ocean-atmosphere coupling strength are varied, it is demonstrated that these westward moving disturbances are probably some manifestation of what Neelin describes as an {open_quotes}SST mode.{close_quotes} By modifying the flux correction procedure, the mean climate of the coupled model can be changed. A fairly modest change in the mean climate is all that is required to excite eastward moving anomalies in place of the westward moving SST modes found previously. The apparent sensitivity of the nature of tropical interannual variability to the mean climate state in a coupled general circulation model such as that used here suggests that caution is advisable if we try to use such models to answer questions relating to changes in ENSO-like variability associated with global climate change. 41 refs., 23 figs., 1 tab.

Estimating soil water-holding capacities by linking the Food and Agriculture Organization Soil map of the world with global pedon databases and continuous pedotransfer functions

Science.gov (United States)

Reynolds, C. A.; Jackson, T. J.; Rawls, W. J.

2000-12-01

Spatial soil water-holding capacities were estimated for the Food and Agriculture Organization (FAO) digital Soil Map of the World (SMW) by employing continuous pedotransfer functions (PTF) within global pedon databases and linking these results to the SMW. The procedure first estimated representative soil properties for the FAO soil units by statistical analyses and taxotransfer depth algorithms [Food and Agriculture Organization (FAO), 1996]. The representative soil properties estimated for two layers of depths (0-30 and 30-100 cm) included particle-size distribution, dominant soil texture, organic carbon content, coarse fragments, bulk density, and porosity. After representative soil properties for the FAO soil units were estimated, these values were substituted into three different pedotransfer functions (PTF) models by Rawls et al. [1982], Saxton et al. [1986], and Batjes [1996a]. The Saxton PTF model was finally selected to calculate available water content because it only required particle-size distribution data and results closely agreed with the Rawls and Batjes PTF models that used both particle-size distribution and organic matter data. Soil water-holding capacities were then estimated by multiplying the available water content by the soil layer thickness and integrating over an effective crop root depth of 1 m or less (i.e., encountered shallow impermeable layers) and another soil depth data layer of 2.5 m or less.

Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) 0-10cm Soil-Moisture Forecast Product

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast 0-10cm soil-moisture data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near...

Effect of soil moisture, over field capacity, on growth of beans plants (phaseolus vulgaris L.) during the first growing month

International Nuclear Information System (INIS)

Mazon, M.P.; Ballesteros, M.

1985-01-01

The effect of soil moisture, over field capacity, on growth and photosynthesis of three moisture levels (20, 30 and 40%) was studied. The first moisture level was near field capacity while the others exceeded. Weekly dry weight of different plant parts, chlorophyll content, net CO 2 exchange rate in light and darkness, 14 CO 2 assimilated rate and stomatal aperture were determined. Results show a positive effect of soil moisture over field capacity on growth, photosynthesis and transpiration of beans during the first growing month. (author)

Soil carbon model alternatives for ECHAM5/JSBACH climate model: Evaluation and impacts on global carbon cycle estimates

DEFF Research Database (Denmark)

Thum, T.; Raisanen, P.; Sevanto, S.

2011-01-01

The response of soil organic carbon to climate change might lead to significant feedbacks affecting global warming. This response can be studied by coupled climate-carbon cycle models but so far the description of soil organic carbon cycle in these models has been quite simple. In this work we used...... the coupled climate-carbon cycle model ECHAM5/JSBACH (European Center/Hamburg Model 5/Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg) with two different soil carbon modules, namely (1) the original soil carbon model of JSBACH called CBALANCE and (2) a new soil carbon model Yasso07, to study...... the interaction between climate variability and soil organic carbon. Equivalent ECHAM5/JSBACH simulations were conducted using both soil carbon models, with freely varying atmospheric CO2 for the last 30 years (1977-2006). In this study, anthropogenic CO2 emissions and ocean carbon cycle were excluded. The new...

Litter decay controlled by temperature, not soil properties, affecting future soil carbon.

Science.gov (United States)

Gregorich, Edward G; Janzen, Henry; Ellert, Benjamin H; Helgason, Bobbi L; Qian, Budong; Zebarth, Bernie J; Angers, Denis A; Beyaert, Ronald P; Drury, Craig F; Duguid, Scott D; May, William E; McConkey, Brian G; Dyck, Miles F

2017-04-01

Widespread global changes, including rising atmospheric CO 2 concentrations, climate warming and loss of biodiversity, are predicted for this century; all of these will affect terrestrial ecosystem processes like plant litter decomposition. Conversely, increased plant litter decomposition can have potential carbon-cycle feedbacks on atmospheric CO 2 levels, climate warming and biodiversity. But predicting litter decomposition is difficult because of many interacting factors related to the chemical, physical and biological properties of soil, as well as to climate and agricultural management practices. We applied 13 C-labelled plant litter to soil at ten sites spanning a 3500-km transect across the agricultural regions of Canada and measured its decomposition over five years. Despite large differences in soil type and climatic conditions, we found that the kinetics of litter decomposition were similar once the effect of temperature had been removed, indicating no measurable effect of soil properties. A two-pool exponential decay model expressing undecomposed carbon simply as a function of thermal time accurately described kinetics of decomposition. (R 2  = 0.94; RMSE = 0.0508). Soil properties such as texture, cation exchange capacity, pH and moisture, although very different among sites, had minimal discernible influence on decomposition kinetics. Using this kinetic model under different climate change scenarios, we projected that the time required to decompose 50% of the litter (i.e. the labile fractions) would be reduced by 1-4 months, whereas time required to decompose 90% of the litter (including recalcitrant fractions) would be reduced by 1 year in cooler sites to as much as 2 years in warmer sites. These findings confirm quantitatively the sensitivity of litter decomposition to temperature increases and demonstrate how climate change may constrain future soil carbon storage, an effect apparently not influenced by soil properties. © 2016 Her Majesty

Quantifying the temperature-independent effect of stratospheric aerosol geoengineering on global-mean precipitation in a multi-model ensemble

International Nuclear Information System (INIS)

Ferraro, Angus J; Griffiths, Hannah G

2016-01-01

The reduction in global-mean precipitation when stratospheric aerosol geoengineering is used to counterbalance global warming from increasing carbon dioxide (CO 2 ) concentrations has been mainly attributed to the temperature-independent effect of CO 2 on atmospheric radiative cooling. We demonstrate here that stratospheric sulphate aerosol itself also acts to reduce global-mean precipitation independent of its effects on temperature. The temperature-independent effect of stratospheric aerosol geoenginering on global-mean precipitation is calculated by removing temperature-dependent effects from climate model simulations of the Geoengineering Model Intercomparison Project (GeoMIP). When sulphate aerosol is injected into the stratosphere at a rate of 5 Tg SO 2 per year the aerosol reduces global-mean precipitation by approximately 0.2 %, though multiple ensemble members are required to separate this effect from internal variability. For comparison, the precipitation reduction from the temperature-independent effect of increasing CO 2 concentrations under the RCP4.5 scenario of the future is approximately 0.5 %. The temperature-independent effect of stratospheric sulphate aerosol arises from the aerosol’s effect on tropospheric radiative cooling. Radiative transfer calculations show this is mainly due to increasing downward emission of infrared radiation by the aerosol, but there is also a contribution from the stratospheric warming the aerosol causes. Our results suggest climate model simulations of solar dimming can capture the main features of the global-mean precipitation response to stratospheric aerosol geoengineering. (letter)

Biochar amendment reduces paddy soil nitrogen leaching but increases net global warming potential in Ningxia irrigation, China.

Science.gov (United States)

Wang, Yongsheng; Liu, Yansui; Liu, Ruliang; Zhang, Aiping; Yang, Shiqi; Liu, Hongyuan; Zhou, Yang; Yang, Zhengli

2017-05-09

The efficacy of biochar as an environmentally friendly agent for non-point source and climate change mitigation remains uncertain. Our goal was to test the impact of biochar amendment on paddy rice nitrogen (N) uptake, soil N leaching, and soil CH 4 and N 2 O fluxes in northwest China. Biochar was applied at four rates (0, 4.5, 9 and13.5 t ha -1 yr -1 ). Biochar amendment significantly increased rice N uptake, soil total N concentration and the abundance of soil ammonia-oxidizing archaea (AOA), but it significantly reduced the soil NO 3 - -N concentration and soil bulk density. Biochar significantly reduced NO 3 - -N and NH 4 + -N leaching. The C2 and C3 treatments significantly increased the soil CH 4 flux and reduced the soil N 2 O flux, leading to significantly increased net global warming potential (GWP). Soil NO 3 - -N rather than NH 4 + -N was the key integrator of the soil CH 4 and N 2 O fluxes. Our results indicate that a shift in abundance of the AOA community and increased rice N uptake are closely linked to the reduced soil NO 3 - -N concentration under biochar amendment. Furthermore, soil NO 3 - -N availability plays an important role in regulating soil inorganic N leaching and net GWP in rice paddies in northwest China.

Global Design and Local Histories: Culturally Embedded Meaning-Making for Inclusive Education

Science.gov (United States)

Mukherjee, Mousumi

2017-01-01

This article provides an account of the recent literature on inclusive education, addressing its meaning and significance for school education in postcolonial India. I engage with the major theoretical debates in the academic literature on inclusive education and examine their historical trajectories globally through policy documents. I then…

Improvement of Global and Regional Mean Sea Level Trends Derived from all Altimetry Missions.

Science.gov (United States)

Ablain, Michael; Benveniste, Jérôme; Faugere, Yannice; Larnicol, Gilles; Cazenave, Anny; Johannessen, Johnny A.; Stammer, Detlef; Timms, Gary

2012-07-01

The global mean sea level (GMSL) has been calculated on a continual basis since January 1993 using data from satellite altimetry missions. The global mean sea level (MSL) deduced from TOPEX/Poseidon, Jason-1 and Jason-2 is increasing with a global trend of 3.2 mm from 1993 to 2010 applying the post glacial rebound (MSL Aviso website http://www.jason.oceanobs.com/msl). Besides, the regional sea level trends bring out an inhomogeneous repartition of the ocean elevation with local MSL slopes ranging from +/- 8 mm/year. A study published in 2009 [Ablain et al., 2009] has shown that the global MSL trend uncertainty was estimated at +/-0.6 mm/year with a confidence interval of 90%. The main sources of errors at global and regional scales are due to the orbit calculation and the wet troposphere correction. But others sea-level components have also a significant impact on the long-term stability of MSL as for instance the stability of instrumental parameters and the atmospheric corrections. Thanks to recent studies performed in Sea Level Essential Climate Variable Project in the frame of the Climate Change Initiative, an ESA Programme, in addition to activities performed within the SALP/CNES, strong improvements have been provided for the estimation of the global and regional MSL trends. In this paper, we propose to describe them; they concern the orbit calculation thanks to new gravity fields, the atmospheric corrections thanks to ERA-interim reanalyses, the wet troposphere corrections thanks to the stability improvement, and also empirical corrections allowing us to link regional time series together better. These improvements are described at global and regional scale for all the altimetry missions.

Can We Use Regression Modeling to Quantify Mean Annual Streamflow at a Global-Scale?

Science.gov (United States)

Barbarossa, V.; Huijbregts, M. A. J.; Hendriks, J. A.; Beusen, A.; Clavreul, J.; King, H.; Schipper, A.

2016-12-01

Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF using observations of discharge and catchment characteristics from 1,885 catchments worldwide, ranging from 2 to 106 km2 in size. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB [van Beek et al., 2011] by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area, mean annual precipitation and air temperature, average slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error values were lower (0.29 - 0.38 compared to 0.49 - 0.57) and the modified index of agreement was higher (0.80 - 0.83 compared to 0.72 - 0.75). Our regression model can be applied globally at any point of the river network, provided that the input parameters are within the range of values employed in the calibration of the model. The performance is reduced for water scarce regions and further research should focus on improving such an aspect for regression-based global hydrological models.

Personal and social meanings of wilderness: Constructing and contesting places in a global village

Science.gov (United States)

Daniel R. Williams

2000-01-01

Description: This paper takes a social constructionist approach to examine the nature and dynamics of personal and social meanings of wilderness. The paper builds on geographic and social theory to discuss the ways in which conflicts over the meaning and value of wilderness are significant consequences of modernization and globalization. The process of modernization...

Improvement of global and regional mean sea level derived from satellite altimetry multi missions

Science.gov (United States)

Ablain, M.; Faugere, Y.; Larnicol, G.; Picot, N.; Cazenave, A.; Benveniste, J.

2012-04-01

With the satellite altimetry missions, the global mean sea level (GMSL) has been calculated on a continual basis since January 1993. 'Verification' phases, during which the satellites follow each other in close succession (Topex/Poseidon--Jason-1, then Jason-1--Jason-2), help to link up these different missions by precisely determining any bias between them. Envisat, ERS-1 and ERS-2 are also used, after being adjusted on these reference missions, in order to compute Mean Sea Level at high latitudes (higher than 66°N and S), and also to improve spatial resolution by combining all these missions together. The global mean sea level (MSL) deduced from TOPEX/Poseidon, Jason-1 and Jason-2 provide a global rate of 3.2 mm from 1993 to 2010 applying the post glacial rebound (MSL aviso website http://www.jason.oceanobs.com/msl). Besides, the regional sea level trends bring out an inhomogeneous repartition of the ocean elevation with local MSL slopes ranging from + 8 mm/yr to - 8 mm/year. A study published in 2009 [Ablain et al., 2009] has shown that the global MSL trend unceratainty was estimated at +/-0.6 mm/year with a confidence interval of 90%. The main sources of errors at global and regional scales are due to the orbit calculation and the wet troposphere correction. But others sea-level components have also a significant impact on the long-term stability of MSL as for instance the stability of instrumental parameters and the atmospheric corrections. Thanks to recent studies performed in the frame of the SALP project (supported by CNES) and Sea-level Climate Change Initiative project (supported by ESA), strong improvements have been provided for the estimation of the global and regional MSL trends. In this paper, we propose to describe them; they concern the orbit calculation thanks to new gravity fields, the atmospheric corrections thanks to ERA-interim reanalyses, the wet troposphere corrections thanks to the stability improvement, and also empirical corrections

Soil functional types: surveying the biophysical dimensions of soil security

Science.gov (United States)

Cécillon, Lauric; Barré, Pierre

2015-04-01

Soil is a natural capital that can deliver key ecosystem services (ES) to humans through the realization of a series of soil processes controlling ecosystem functioning. Soil is also a diverse and endangered natural resource. A huge pedodiversity has been described at all scales, which is strongly altered by global change. The multidimensional concept soil security, encompassing biophysical, economic, social, policy and legal frameworks of soils has recently been proposed, recognizing the role of soils in global environmental sustainability challenges. The biophysical dimensions of soil security focus on the functionality of a given soil that can be viewed as the combination of its capability and its condition [1]. Indeed, all soils are not equal in term of functionality. They show different processes, provide different ES to humans and respond specifically to global change. Knowledge of soil functionality in space and time is thus a crucial step towards the achievement soil security. All soil classification systems incorporate some functional information, but soil taxonomy alone cannot fully describe the functioning, limitations, resistance and resilience of soils. Droogers and Bouma [2] introduced functional variants (phenoforms) for each soil type (genoform) so as to fit more closely to soil functionality. However, different genoforms can have the same functionality. As stated by McBratney and colleagues [1], there is a great need of an agreed methodology for defining the reference state of soil functionality. Here, we propose soil functional types (SFT) as a relevant classification system for the biophysical dimensions of soil security. Following the definition of plant functional types widely used in ecology, we define a soil functional type as "a set of soil taxons or phenoforms sharing similar processes (e.g. soil respiration), similar effects on ecosystem functioning (e.g. primary productivity) and similar responses to global change (land-use, management or

Permafrost degradation and associated ground settlement estimation under 2 °C global warming

Science.gov (United States)

Guo, Donglin; Wang, Huijun

2017-10-01

Global warming of 2 °C above preindustrial levels has been considered to be the threshold that should not be exceeded by the global mean temperature to avoid dangerous interference with the climate system. However, this global mean target has different implications for different regions owing to the globally nonuniform climate change characteristics. Permafrost is sensitive to climate change; moreover, it is widely distributed in high-latitude and high-altitude regions where the greatest warming is predicted. Permafrost is expected to be severely affected by even the 2 °C global warming, which, in turn, affects other systems such as water resources, ecosystems, and infrastructures. Using air and soil temperature data from ten coupled model intercomparison project phase five models combined with observations of frozen ground, we investigated the permafrost thaw and associated ground settlement under 2 °C global warming. Results show that the climate models produced an ensemble mean permafrost area of 14.01 × 106 km2, which compares reasonably with the area of 13.89 × 106 km2 (north of 45°N) in the observations. The models predict that the soil temperature at 6 m depth will increase by 2.34-2.67 °C on area average relative to 1990-2000, and the increase intensifies with increasing latitude. The active layer thickness will also increase by 0.42-0.45 m, but dissimilar to soil temperature, the increase weakens with increasing latitude due to the distinctly cooler permafrost at higher latitudes. The permafrost extent will obviously retreat north and decrease by 24-26% and the ground settlement owing to permafrost thaw is estimated at 3.8-15 cm on area average. Possible uncertainties in this study may be mostly attributed to the less accurate ground ice content data and coarse horizontal resolution of the models.

A global mean ocean circulation estimation using goce gravity models - the DTU12MDT mean dynamic topography model

DEFF Research Database (Denmark)

Knudsen, Per; Andersen, Ole Baltazar

2012-01-01

The Gravity and Ocean Circulation Experiment - GOCE satellite mission measure the Earth gravity field with unprecedented accuracy leading to substantial improvements in the modelling of the ocean circulation and transport. In this study of the performance of GOCE, a newer gravity model have been...... combined with the DTU10MSS mean sea surface model to construct a global mean dynamic topography model named DTU10MDT. The results of preliminary analyses using preliminary GOCE gravity models clearly demonstrated the potential of GOCE mission. Both the resolution and the estimation of the surface currents...... have been improved significantly compared to results obtained using pre-GOCE gravity field models. The results of this study show that geostrophic surface currents associated with the mean circulation have been further improved and that currents having speeds down to 5 cm/s have been recovered....

Assessment of the potential forecasting skill of a global hydrological model in reproducing the occurrence of monthly flow extremes

Directory of Open Access Journals (Sweden)

N. Candogan Yossef

2012-11-01

Full Text Available As an initial step in assessing the prospect of using global hydrological models (GHMs for hydrological forecasting, this study investigates the skill of the GHM PCR-GLOBWB in reproducing the occurrence of past extremes in monthly discharge on a global scale. Global terrestrial hydrology from 1958 until 2001 is simulated by forcing PCR-GLOBWB with daily meteorological data obtained by downscaling the CRU dataset to daily fields using the ERA-40 reanalysis. Simulated discharge values are compared with observed monthly streamflow records for a selection of 20 large river basins that represent all continents and a wide range of climatic zones.

We assess model skill in three ways all of which contribute different information on the potential forecasting skill of a GHM. First, the general skill of the model in reproducing hydrographs is evaluated. Second, model skill in reproducing significantly higher and lower flows than the monthly normals is assessed in terms of skill scores used for forecasts of categorical events. Third, model skill in reproducing flood and drought events is assessed by constructing binary contingency tables for floods and droughts for each basin. The skill is then compared to that of a simple estimation of discharge from the water balance (P−E.

The results show that the model has skill in all three types of assessments. After bias correction the model skill in simulating hydrographs is improved considerably. For most basins it is higher than that of the climatology. The skill is highest in reproducing monthly anomalies. The model also has skill in reproducing floods and droughts, with a markedly higher skill in floods. The model skill far exceeds that of the water balance estimate. We conclude that the prospect for using PCR-GLOBWB for monthly and seasonal forecasting of the occurrence of hydrological extremes is positive. We argue that this conclusion applies equally to other similar GHMs and

Soil friability - Concept, Assessment and Effects of Soil Properties and Management

DEFF Research Database (Denmark)

Munkholm, Lars Juhl

Soil friability is a key soil physical property yielding valuable information on the ease of productin a favorable seed- and root beds during tillage operations. Therefore, soil friability is acrucial soil property in relation to the ability of soil to support plant growth and to minimzethe energy...... required for tillage. The topic has interested farmers and soil scientiest for centuries, but is was the paper by Utomo and Dexter (1981) that significantly put the topic on the soil science agenda. The awareness of soil friability is growing, both in practiceand in soil science. This must be viewed...... in the light of the present renewed focus on global food security together with a focus on fossil fuel consumption and greenhouse gas emissions in crop production. Certainly, the demand for well-functioning, arable soils is rising to meet the global challenges....

Soil moisture content with global warming

International Nuclear Information System (INIS)

Vinnikov, K.Ya.

1990-01-01

The potential greenhouse-gas-induced changes in soil moisture, particularly the desiccation of the Northern Hemisphere contents in summer, are discussed. To check the conclusions based on climate models the authors have used long-term measurements of contemporary soil moisture in the USSR and reconstructions of soil moisture for the last two epochs that were warmer than the present, namely, the Holocene optimum, 5,000-6,000 years ago, and the last interglacial, about 125,000 years ago. The analysis shows that there is a considerable disagreement between the model results and the empirical data

Impact of land use and soil data specifications on COSMO-CLM simulations in the CORDEX-MED area

Directory of Open Access Journals (Sweden)

Gerhard Smiatek

2016-05-01

Full Text Available The impact of the ECOCLIMAP land use and the Harmonized World Soil Database (HWSD data on simulations with the Consortium for Small-scale Modeling model in CLimate Mode (CCLM regional climate model is investigated. ECOCLIMAP has information about vegetation characteristics as monthly data for 215 climatic units. With the HWSD implementation in CCLM, the spatial resolution of the soil data has been increased to 30 arc seconds and has an improved texture definition and handling in the soil model TERRA_ML. Simulations in the MED-CORDEX modeling domain over the period 1986–2000 reveal that differences of up to 1.8 K in the area monthly mean temperature as well as of up to 21 % in the area monthly mean precipitation can be attributed to the differences in the soil data time-invariant boundary input. Differences related to changes in land use are with 0.4 K and 5 % moderate. Differences resulting from the soil data and its processing in CCLM indicate that regional climate model simulations might benefit from further improvements in this area.

Long acting risperidone in Australian patients with chronic schizophrenia: 24-month data from the e-STAR database

Directory of Open Access Journals (Sweden)

Lambert Tim

2012-03-01

Full Text Available Abstract Background This observational study was designed to collect treatment outcomes data in patients using the electronic Schizophrenia Treatment Adherence Registry (e-STAR. Methods Patients with schizophrenia or schizoaffective disorder in Australia who were prescribed risperidone long-acting injection (RLAI between 2003 and 2007 were assessed 12-months retrospectively, at baseline and 24-months prospectively at 3-monthly intervals. The intent-to-treat population, defined as all patients who received at least one dose of RLAI at baseline, was used for the efficacy and safety analyses. Results At total of 784 patients (74% with schizophrenia, 69.8% male with a mean age of 37.1 ± 12.5 years and 10.6 ± 9.5 years since diagnosis were included in this Australian cohort. A significant improvement in mean Clinical Global Impression - severity score was observed at 24-months (4.52 ± 1.04 at baseline, 3.56 ± 1.10 at 24-months. Most of this improvement was seen by 3-months and was also reflected in mean Global Assessment of Functioning score, which improved significantly at 24-months (42.9 ± 14.5 at baseline, 59 ± 15.4 at 24-months. For patients still receiving RLAI at 24-months there was an increase from a mean baseline RLAI dose of 26.4 ± 5 mg to 43.4 ± 15.7 mg. Sixty-six percent of patients discontinued RLAI before the 24-month period--this decreased to 46% once patients lost to follow-up were excluded. Conclusion Over the 24-month period, initiation of RLAI was associated with improved patient functioning and illness severity in patients with schizophrenia or schizoaffective disorder. Improved outcomes were observed early and sustained throughout the study. Trial Registration Clinical Trials Registration Number, NCT00283517.

Jointly structuring triadic spaces of meaning and action: book sharing from 3 months on.

Directory of Open Access Journals (Sweden)

Nicole eRossmanith

2014-12-01

Full Text Available This study explores the emergence of triadic interactions through the example of book sharing. As part of a naturalistic study, 10 infants were visited in their homes from 3-12 months. We report that (1 book sharing as a form of infant-caregiver-object interaction occurred from as early as 3 months. Using qualitative video analysis at a micro-level adapting methodologies from conversation and interaction analysis, we demonstrate that caregivers and infants practiced book sharing in a highly co-ordinated way, with caregivers carving out interaction units and shaping actions into action arcs and infants actively participating and co-ordinating their attention between mother and object from the beginning. We also (2 sketch a developmental trajectory of book sharing over the first year and show that the quality and dynamics of book sharing interactions underwent considerable change as the ecological situation was transformed in parallel with the infants' development of attention and motor skills. Social book sharing interactions reached an early peak at 6 months with the infants becoming more active in the coordination of attention between caregiver and book. From 7-9 months, the infants shifted their interest largely to solitary object exploration, in parallel with newly emerging postural and object manipulation skills, disrupting the social coordination and the cultural frame of book sharing. In the period from 9-12 months, social book interactions resurfaced, as infants began to effectively integrate object actions within the socially shared activity. In conclusion, to fully understand the development and qualities of triadic cultural activities such as book sharing, we need to look especially at the hitherto overlooked early period from 4-6 months, and investigate how shared spaces of meaning and action are structured together in and through interaction, creating the substrate for continuing cooperation and cultural learning.

Jointly structuring triadic spaces of meaning and action: book sharing from 3 months on.

Science.gov (United States)

Rossmanith, Nicole; Costall, Alan; Reichelt, Andreas F; López, Beatriz; Reddy, Vasudevi

2014-01-01

This study explores the emergence of triadic interactions through the example of book sharing. As part of a naturalistic study, 10 infants were visited in their homes from 3-12 months. We report that (1) book sharing as a form of infant-caregiver-object interaction occurred from as early as 3 months. Using qualitative video analysis at a micro-level adapting methodologies from conversation and interaction analysis, we demonstrate that caregivers and infants practiced book sharing in a highly co-ordinated way, with caregivers carving out interaction units and shaping actions into action arcs and infants actively participating and co-ordinating their attention between mother and object from the beginning. We also (2) sketch a developmental trajectory of book sharing over the first year and show that the quality and dynamics of book sharing interactions underwent considerable change as the ecological situation was transformed in parallel with the infants' development of attention and motor skills. Social book sharing interactions reached an early peak at 6 months with the infants becoming more active in the coordination of attention between caregiver and book. From 7 to 9 months, the infants shifted their interest largely to solitary object exploration, in parallel with newly emerging postural and object manipulation skills, disrupting the social coordination and the cultural frame of book sharing. In the period from 9 to 12 months, social book interactions resurfaced, as infants began to effectively integrate manual object actions within the socially shared activity. In conclusion, to fully understand the development and qualities of triadic cultural activities such as book sharing, we need to look especially at the hitherto overlooked early period from 4 to 6 months, and investigate how shared spaces of meaning and action are structured together in and through interaction, creating the substrate for continuing cooperation and cultural learning.

The history of human-induced soil erosion: Geomorphic legacies, early descriptions and research, and the development of soil conservation—A global synopsis

Science.gov (United States)

Dotterweich, Markus

2013-11-01

This paper presents a global synopsis about the geomorphic evidence of soil erosion in humid and semihumid areas since the beginning of agriculture. Historical documents, starting from ancient records to data from the mid-twentieth century and numerous literature reviews form an extensive assortment of examples that show how soil erosion has been perceived previously by scholars, land surveyors, farmers, land owners, researchers, and policy makers. Examples have been selected from ancient Greek and Roman Times and from central Europe, southern Africa, North America, the Chinese Loess Plateau, Australia, New Zealand, and Easter Island. Furthermore, a comprehensive collection on the development of soil erosion research and soil conservation has been provided, with a particular focus on Germany and the USA. Geomorphic evidence shows that most of the agriculturally used slopes in the Old and New Worlds had already been affected by soil erosion in earlier, prehistoric times. Early descriptions of soil erosion are often very vague. With regard to the Roman Times, geomorphic evidence shows seemingly opposing results, ranging from massive devastation to landscapes remaining stable for centuries. Unfortunately, historical documentation is lacking. In the following centuries, historical records become more frequent and more precise and observations on extreme soil erosion events are prominent. Sometimes they can be clearly linked to geomorphic evidence in the field. The advent of professional soil conservation took place in the late eighteenth century. The first extensive essay on soil conservation known to the Western world was published in Germany in 1815. The rise of professional soil conservation occurred in the late nineteenth and early twentieth centuries. Soil remediation and flood prevention programs were initiated, but the long-term success of these actions remains controversial. In recent years, increasing interest is to recover any traditional knowledge of soil

Mapping Monthly Water Scarcity in Global Transboundary Basins at Country-Basin Mesh Based Spatial Resolution.

Science.gov (United States)

Degefu, Dagmawi Mulugeta; Weijun, He; Zaiyi, Liao; Liang, Yuan; Zhengwei, Huang; Min, An

2018-02-01

Currently fresh water scarcity is an issue with huge socio-economic and environmental impacts. Transboundary river and lake basins are among the sources of fresh water facing this challenge. Previous studies measured blue water scarcity at different spatial and temporal resolutions. But there is no global water availability and footprint assessment done at country-basin mesh based spatial and monthly temporal resolutions. In this study we assessed water scarcity at these spatial and temporal resolutions. Our results showed that around 1.6 billion people living within the 328 country-basin units out of the 560 we assessed in this study endures severe water scarcity at least for a month within the year. In addition, 175 country-basin units goes through severe water scarcity for 3-12 months in the year. These sub-basins include nearly a billion people. Generally, the results of this study provide insights regarding the number of people and country-basin units experiencing low, moderate, significant and severe water scarcity at a monthly temporal resolution. These insights might help these basins' sharing countries to design and implement sustainable water management and sharing schemes.

New era of satellite chlorophyll fluorescence and soil moisture observations leads to advances in the predictive understanding of global terrestrial coupled carbon-water cycles

Science.gov (United States)

Qiu, B.; Xue, Y.; Fisher, J.; Guo, W.

2017-12-01

The terrestrial carbon cycle and water cycle are coupled through a multitude of connected processes among soil, roots, leaves, and the atmosphere. The strength and sensitivity of these couplings are not yet well known at the global scale, which contributes to uncertainty in predicting the terrestrial water and carbon budgets. For the first time, we now have synchronous, high fidelity, global-scale satellite observations of critical terrestrial carbon and water cycle components: sun-induced chlorophyll fluorescence (SIF) and soil moisture. We used these observations within the framework of a well-established global terrestrial biosphere model (Simplified Simple Biosphere Model version 2.0, SSiB2) to investigate carbon-water coupling processes. We updated SSiB2 to include a mechanistic representation of SIF and tested the sensitivity of model parameters to improve the simulation of both SIF and soil moisture with the ultimate objective of improving the first-order terrestrial carbon component, gross primary production (GPP). Although several vegetation parameters, such as leaf area index (LAI) and green leaf fraction, improved the simulated SIF, and several soil parameters, such as hydraulic conductivity, improved simulated soil moisture, their effects were mainly limited to their respective cycles. One parameter emerged as the key coupler between the carbon and water cycles: the wilting point. Updates to the wilting point significantly improved the simulations for both soil moisture and SIF, as well as GPP. This study demonstrates the value of synchronous global measurements of the terrestrial carbon and water cycles in improving the understanding of coupled carbon-water cycles.

The moisture response of soil heterotrophic respiration: interaction with soil properties

DEFF Research Database (Denmark)

Moyano, F E; Vasilyeva, N; Bouckaert, L

2012-01-01

the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data......Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model......-driven analysis of soil moisture-respiration relations based on 90 soils. With the use of linear models we show how the relationship between soil heterotrophic respiration and different measures of soil moisture is consistently affected by soil properties. The empirical models derived include main effects...

Global patterns of plant root colonization intensity by mycorrhizal fungi explained by climate and soil chemistry

NARCIS (Netherlands)

Soudzilovskaia, N.A.; Douma, J.C.; Akhmetzhanova, A.A.; van Bodegom, P.M.; Cornwell, W.K.; Moens, E.J.; Treseder, K.K.; Tibbett, M.; Wang, Y.P.; Cornelissen, J.H.C.

2015-01-01

Aim Most vascular plants on Earth form mycorrhizae, a symbiotic relationship between plants and fungi. Despite the broad recognition of the importance of mycorrhizae for global carbon and nutrient cycling, we do not know how soil and climate variables relate to the intensity of colonization of plant

International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Daily

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Daily

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

Long-term and realistic global change manipulations had low impact on diversity of soil biota in temperate heathland

DEFF Research Database (Denmark)

Holmstrup, Martin; Damgaard, Christian; Schmidt, Inger K

2017-01-01

C:N ratio. After eight years of treatment, however, the CO2-increased litter C:N ratio did not influence the diversity in any of the four fauna groups. The number of significant correlations between treatments, food source quality, and soil biota diversities was reduced from six to three after two...... and eight years, respectively. These results suggest a remarkable resilience within the soil biota against global climate change treatments in the long term....

Negative soil moisture-precipitation feedback in dry and wet regions.

Science.gov (United States)

Yang, Lingbin; Sun, Guoqing; Zhi, Lu; Zhao, Jianjun

2018-03-05

Soil moisture-precipitation (SM-P) feedback significantly influences the terrestrial water and energy cycles. However, the sign of the feedback and the associated physical mechanism have been debated, leaving a research gap regarding global water and climate changes. Based on Koster's framework, we estimate SM-P feedback using satellite remote sensing and ground observation data sets. Methodologically, the sign of the feedback is identified by the correlation between monthly soil moisture and next-month precipitation. The physical mechanism is investigated through coupling precipitation and soil moisture (P-SM), soil moisture ad evapotranspiration (SM-E) and evapotranspiration and precipitation (E-P) correlations. Our results demonstrate that although positive SM-P feedback is predominant over land, non-negligible negative feedback occurs in dry and wet regions. Specifically, 43.75% and 40.16% of the negative feedback occurs in the arid and humid climate zones. Physically, negative SM-P feedback depends on the SM-E correlation. In dry regions, evapotranspiration change is soil moisture limited. In wet regions, evapotranspiration change is energy limited. We conclude that the complex SM-E correlation results in negative SM-P feedback in dry and wet regions, and the cause varies based on the environmental and climatic conditions.

Climate Warming Can Increase Soil Carbon Fluxes Without Decreasing Soil Carbon Stocks in Boreal Forests

Science.gov (United States)

Ziegler, S. E.; Benner, R. H.; Billings, S. A.; Edwards, K. A.; Philben, M. J.; Zhu, X.; Laganiere, J.

2016-12-01

Ecosystem C fluxes respond positively to climate warming, however, the net impact of changing C fluxes on soil organic carbon (SOC) stocks over decadal scales remains unclear. Manipulative studies and global-scale observations have informed much of the existing knowledge of SOC responses to climate, providing insights on relatively short (e.g. days to years) and long (centuries to millennia) time scales, respectively. Natural climate gradient studies capture integrated ecosystem responses to climate on decadal time scales. Here we report the soil C reservoirs, fluxes into and out of those reservoirs, and the chemical composition of inputs and soil organic matter pools along a mesic boreal forest climate transect. The sites studied consist of similar forest composition, successional stage, and soil moisture but differ by 5.2°C mean annual temperature. Carbon fluxes through these boreal forest soils were greatest in the lowest latitude regions and indicate that enhanced C inputs can offset soil C losses with warming in these forests. Respiration rates increased by 55% and the flux of dissolved organic carbon from the organic to mineral soil horizons tripled across this climate gradient. The 2-fold increase in litterfall inputs to these soils coincided with a significant increase in the organic horizon C stock with warming, however, no significant difference in the surface mineral soil C stocks was observed. The younger mean age of the mineral soil C ( 70 versus 330 YBP) provided further evidence for the greater turnover of SOC in the warmer climate soils. In spite of these differences in mean radiocarbon age, mineral SOC exhibited chemical characteristics of highly decomposed material across all regions. In contrast with depth trends in soil OM diagenetic indices, diagenetic shifts with latitude were limited to increases in C:N and alkyl to O-alkyl ratios in the overlying organic horizons in the warmer relative to the colder regions. These data indicate that the

Production of nitrous oxide and consumption of methane by forest soils

Science.gov (United States)

Keller, M.; Wofsy, S. C.; Kaplan, W. A.; Mcelroy, M. B.; Goreau, T. J.

1983-01-01

Soils in an Amazonian rainforest are observed to release N2O at a rate larger than the global mean by about a factor of 20. Emissions from a New England hardwood forest are approximately 30 times smaller then Brazilian values. Atmospheric methane is consumed by soils in both systems. Tropical forests would provide a major source of atmospheric N2O if the Brazilian results are representative.

Performance of Sayigh's universal formula in the estimation of global solar radiation in Ghana

International Nuclear Information System (INIS)

Oduro Afriyie, K.

1995-10-01

The performance of Sayigh's universal formula for the estimation of global solar radiation is tested against that of Angstrom-Black model for 13 stations in Ghana, using monthly mean daily global solar radiation averaged over the years 1957-1981. Sayigh's model is found not to perform as credibility as the Angstrom-Black model in the estimation of monthly global solar radiation in Ghana. Of the 156 values of monthly global solar radiation estimated by Sayigh's model, 123 (or 78.8%) had discrepancies of more than 10% with the measured values. The corresponding value for the Angstrom-Black model was 7 (or 4.5%). (author). 5 refs

Significant influences of global mean temperature and ENSO on extreme rainfall over Southeast Asia

Science.gov (United States)

Villafuerte, Marcelino, II; Matsumoto, Jun

2014-05-01

Along with the increasing concerns on the consequences of global warming, and the accumulating records of disaster related to heavy rainfall events in Southeast Asia, this study investigates whether a direct link can be detected between the rising global mean temperature, as well as the El Niño-Southern Oscillation (ENSO), and extreme rainfall over the region. The maximum likelihood modeling that allows incorporating covariates on the location parameter of the generalized extreme value (GEV) distribution is employed. The GEV model is fitted to annual and seasonal rainfall extremes, which were taken from a high-resolution gauge-based gridded daily precipitation data covering a span of 57 years (1951-2007). Nonstationarities in extreme rainfall are detected over the central parts of Indochina Peninsula, eastern coasts of central Vietnam, northwest of the Sumatra Island, inland portions of Borneo Island, and on the northeastern and southwestern coasts of the Philippines. These nonstationarities in extreme rainfall are directly linked to near-surface global mean temperature and ENSO. In particular, the study reveals that a kelvin increase in global mean temperature anomaly can lead to an increase of 30% to even greater than 45% in annual maximum 1-day rainfall, which were observed pronouncedly over central Vietnam, southern coast of Myanmar, northwestern sections of Thailand, northwestern tip of Sumatra, central portions of Malaysia, and the Visayas island in central Philippines. Furthermore, a pronounced ENSO influence manifested on the seasonal maximum 1-day rainfall; a northward progression of 10%-15% drier condition over Southeast Asia as the El Niño develops from summer to winter is revealed. It is important therefore, to consider the results obtained here for water resources management as well as for adaptation planning to minimize the potential adverse impact of global warming, particularly on extreme rainfall and its associated flood risk over the region

Regional scaling of annual mean precipitation and water availability with global temperature change

Science.gov (United States)

Greve, Peter; Gudmundsson, Lukas; Seneviratne, Sonia I.

2018-03-01

Changes in regional water availability belong to the most crucial potential impacts of anthropogenic climate change, but are highly uncertain. It is thus of key importance for stakeholders to assess the possible implications of different global temperature thresholds on these quantities. Using a subset of climate model simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), we derive here the sensitivity of regional changes in precipitation and in precipitation minus evapotranspiration to global temperature changes. The simulations span the full range of available emission scenarios, and the sensitivities are derived using a modified pattern scaling approach. The applied approach assumes linear relationships on global temperature changes while thoroughly addressing associated uncertainties via resampling methods. This allows us to assess the full distribution of the simulations in a probabilistic sense. Northern high-latitude regions display robust responses towards wetting, while subtropical regions display a tendency towards drying but with a large range of responses. Even though both internal variability and the scenario choice play an important role in the overall spread of the simulations, the uncertainty stemming from the climate model choice usually accounts for about half of the total uncertainty in most regions. We additionally assess the implications of limiting global mean temperature warming to values below (i) 2 K or (ii) 1.5 K (as stated within the 2015 Paris Agreement). We show that opting for the 1.5 K target might just slightly influence the mean response, but could substantially reduce the risk of experiencing extreme changes in regional water availability.

Variability of soil CO2 efflux in a semi-arid grassland in Arizona

Science.gov (United States)

Krishnan, P.; Meyers, T. P.; Heuer, M.

2017-12-01

Soil surface CO2 efflux or soil respiration (RS) is one of the most important components of the global carbon cycle. So it is critical to evaluate the response of soil respiration to environmental conditions to predict how future climate and land cover changes influence the ecosystem carbon balance. Continuous half-hourly measurements of RS were made between the end of March to December 2015 in a semi-arid temperate grassland located on the Audubon Research Ranch in south western Arizona (31.5907N, 110.5104W, elevation 1496 m), USA. This first time measurements of Rs over this site using an automated soil chamber were used to investigate the seasonal and diurnal variation of Rs and its relationship to environmental variables. The mean annual air temperature and precipitation at this site were 16 deg C and 370 mm with more than 60% of the annual precipitation was received during the North American monsoon period (July-September). Following the onset of the monsoon, drastic changes in vegetation growth occured turning the ecosystem to a carbon sink by August. Temporal variability in Rs was closely related to the changes in near surface soil temperature at 2 cm (Ts) and soil water content at 5 cm (θ). Half -hourly Rs varied from nearly 0.1 μmol m-2 s-1 in the winter months to a maximum of 5 μmol m-2 s-1 in the peak growing season in August. During the dry pre-monsoon period (May -June), Rs was relatively low ( 0.0.08 m3 m-3, RS was positively correlated to soil temperature at the 2 cm depth following an exponential relationship. Below this value of θ, RS was largely decoupled from TS dropping to less than half of their maximum values during wet soil conditions. Analysis of daily mean nighttime Rs for the year showed that for periods with θ below the threshold, the sensitivity of RS to temperature were substantially reduced resulting in a Q10 significantly < 2, thereby confirming that RS was less affected by soil temperature under low soil water conditions at this

Decomposition of Diethylstilboestrol in Soil

DEFF Research Database (Denmark)

Gregers-Hansen, Birte

1964-01-01

The rate of decomposition of DES-monoethyl-1-C14 in soil was followed by measurement of C14O2 released. From 1.6 to 16% of the added C14 was recovered as C14O2 during 3 months. After six months as much as 12 to 28 per cent was released as C14O2.Determination of C14 in the soil samples after the e...... not inhibit the CO2 production from the soil.Experiments with γ-sterilized soil indicated that enzymes present in the soil are able to attack DES.......The rate of decomposition of DES-monoethyl-1-C14 in soil was followed by measurement of C14O2 released. From 1.6 to 16% of the added C14 was recovered as C14O2 during 3 months. After six months as much as 12 to 28 per cent was released as C14O2.Determination of C14 in the soil samples after...

Prediction of monthly global solar radiation using adaptive neuro fuzzy inference system (ANFIS) technique over the state of Tamilnadu (India): a comparative study

International Nuclear Information System (INIS)

Sumithira, T. R.; Nirmal, Kumar A.

2012-01-01

Enormous potential of solar energy as a clean and pollution free source enrich the global power generation. India, being a tropical country, has high solar radiation and it lies to the north of equator between 8 degree 4' and 37 degree 6' North latitude and 68 degree 7' , and 97 degree 5' East longitude. In south india, Tamilnadu is located in the extreme south east with an average temperature of grater than 27.5 degree (> 81.5 F). In this study, an adaptive neuro-fuzzy inference system (ANFIS) based modelling approach to predict the monthly global solar radiation (MGSR) in Tamilnadu is presented using the real meteorological solar radiation data from the 31 districts of Tamilnadu with different latitude and longitude. The purpose of the study is to compare the accuracy of ANFIS and other soft computing models as found in literature to assess the solar radiation. The performance of the proposed model was tested and compared with other earth region in a case study. The statistical performance parameters such as root mean square error (RMSE), mean bias error (MBE), and coefficient of determination (R2) are presented and compared to validate the performance. The comparative test results prove the ANFIS based prediction are better than other models and furthermore proves its prediction capability for any geographical area with changing meteorological conditions. (author)

TOMS EP UV Aerosol Index Daily and Monthly Zonal Means V008 (TOMSEPL3zaer) at GES DISC

Data.gov (United States)

National Aeronautics and Space Administration — This data product contains TOMS/EP UV Aerosol Index Daily and Monthly Zonal Means Version 8 data in ASCII format.The Total Ozone Mapping Spectrometer (TOMS) Version...

GOZCARDS Source Data for Ozone Monthly Zonal Means on a Geodetic Latitude and Pressure Grid V1.01

Data.gov (United States)

National Aeronautics and Space Administration — The GOZCARDS Source Data for Ozone Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozSmlpO3) contains zonal means and related information...

GOZCARDS Merged Data for Ozone Monthly Zonal Means on a Geodetic Latitude and Pressure Grid V1.01

Data.gov (United States)

National Aeronautics and Space Administration — The GOZCARDS Merged Data for Ozone Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozMmlpO3) contains zonal means and related information...

Levels and patterns of polycyclic aromatic hydrocarbons (PAHs) in soils after forest fires in South Korea.

Science.gov (United States)

Kim, Eun Jung; Choi, Sung-Deuk; Chang, Yoon-Seok

2011-11-01

To investigate the influence of biomass burning on the levels of polycyclic aromatic hydrocarbons (PAHs) in soils, temporal trends and profiles of 16 US Environmental Protection Agency priority PAHs were studied in soil and ash samples collected 1, 5, and 9 months after forest fires in South Korea. The levels of PAHs in the burnt soils 1 month after the forest fires (mean, 1,200 ng/g dry weight) were comparable with those of contaminated urban soils. However, 5 and 9 months after the forest fires, these levels decreased considerably to those of general forest soils (206 and 302 ng/g, respectively). The burnt soils and ash were characterized by higher levels of light PAHs with two to four rings, reflecting direct emissions from biomass burning. Five and 9 months after the forest fires, the presence of naphthalene decreased considerably, which indicates that light PAHs were rapidly volatilized or degraded from the burnt soils. The temporal trend and pattern of PAHs clearly suggests that soils in the forest-fire region can be contaminated by PAHs directly emitted from biomass burning. However, the fire-affected soils can return to the pre-fire conditions over time through the washout and wind dissipation of the ash with high content of PAHs as well as vaporization or degradation of light PAHs.

Author Correction: Global patterns in mangrove soil carbon stocks and losses

Science.gov (United States)

Atwood, Trisha B.; Connolly, Rod M.; Almahasheer, Hanan; Carnell, Paul E.; Duarte, Carlos M.; Lewis, Carolyn J. Ewers; Irigoien, Xabier; Kelleway, Jeffrey J.; Lavery, Paul S.; Macreadie, Peter I.; Serrano, Oscar; Sanders, Christian J.; Santos, Isaac; Steven, Andrew D. L.; Lovelock, Catherine E.

2018-03-01

In the version of this Article originally published, the potential carbon loss from soils as a result of mangrove deforestation was incorrectly given as `2.0-75 Tg C yr-1'; this should have read `2-8 Tg C yr-1'. The corresponding emissions were incorrectly given as ` 7.3-275 Tg of CO2e'; this should have read ` 7-29 Tg of CO2e'. The corresponding percentage equivalent of these emissions compared with those from global terrestrial deforestation was incorrectly given as `0.2-6%'; this should have read `0.6-2.4%'. These errors have now been corrected in all versions of the Article.

The carbon cycle and global warming

International Nuclear Information System (INIS)

Anon.

1991-01-01

Five land-use-based approaches can be used to slow the buildup of CO 2 in the atmosphere: slowing or stopping the loss of existing forests, thus preserving current carbon reservoirs; adding to the planet's vegetative cover through reforestation or other means, thus enlarging living terrestrial carbon reservoirs; increasing the carbon stored in nonliving carbon reservoirs such as agricultural soils; increasing the carbon stored in artificial reservoirs, including timber products; and substituting sustainable biomass energy sources for fossil fuel consumption, thus reducing energy-related carbon emissions. These approaches are all based on the same basic premise: adding to the planet's net carbon stores in vegetative cover or soil, or preventing any net loss, will help moderate global warming by keeping atmospheric CO 2 levels lower than they would otherwise be. Because biotic policy options appear capable of contributing significantly to the mitigation of global warming while also furthering many other public policy objectives, their role deserves careful consideration on a country-by-country basis

Modelling monthly runoff generation processes following land use changes: groundwater–surface runoff interactions

Directory of Open Access Journals (Sweden)

M. Bari

2004-01-01

Full Text Available A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, 'Ernies' (control, fully forested and 'Lemon' (54% cleared are in a zone of mean annual rainfall of 725 mm, while 'Salmon' (control, fully forested and 'Wights' (100% cleared are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i immediately after clearing due to reduced evapotranspiration, and (ii through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i an upper zone unsaturated store, (ii a transient stream zone store, (ii a lower zone unsaturated store and (iv a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and

Soil solution phosphorus turnover: derivation, interpretation, and insights from a global compilation of isotope exchange kinetic studies

Science.gov (United States)

Helfenstein, Julian; Jegminat, Jannes; McLaren, Timothy I.; Frossard, Emmanuel

2018-01-01

The exchange rate of inorganic phosphorus (P) between the soil solution and solid phase, also known as soil solution P turnover, is essential for describing the kinetics of bioavailable P. While soil solution P turnover (Km) can be determined by tracing radioisotopes in a soil-solution system, few studies have done so. We believe that this is due to a lack of understanding on how to derive Km from isotopic exchange kinetic (IEK) experiments, a common form of radioisotope dilution study. Here, we provide a derivation of calculating Km using parameters obtained from IEK experiments. We then calculated Km for 217 soils from published IEK experiments in terrestrial ecosystems, and also that of 18 long-term P fertilizer field experiments. Analysis of the global compilation data set revealed a negative relationship between concentrations of soil solution P and Km. Furthermore, Km buffered isotopically exchangeable P in soils with low concentrations of soil solution P. This finding was supported by an analysis of long-term P fertilizer field experiments, which revealed a negative relationship between Km and phosphate-buffering capacity. Our study highlights the importance of calculating Km for understanding the kinetics of P between the soil solid and solution phases where it is bioavailable. We argue that our derivation can also be used to calculate soil solution turnover of other environmentally relevant and strongly sorbing elements that can be traced with radioisotopes, such as zinc, cadmium, nickel, arsenic, and uranium.

Scenario and modelling uncertainty in global mean temperature change derived from emission driven Global Climate Models

Science.gov (United States)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D.

2012-09-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10-90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

Science.gov (United States)

Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D. M. H.

2013-04-01

We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10-90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie

Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models

Directory of Open Access Journals (Sweden)

B. B. B. Booth

2013-04-01

Full Text Available We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM. These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario. A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5 and even under aggressive mitigation (RCP2.6 temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs, the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high

Establishing the Global Fresh Water Sensor Web

Science.gov (United States)

Hildebrand, Peter H.

2005-01-01

This paper presents an approach to measuring the major components of the water cycle from space using the concept of a sensor-web of satellites that are linked to a data assimilation system. This topic is of increasing importance, due to the need for fresh water to support the growing human population, coupled with climate variability and change. The net effect is that water is an increasingly valuable commodity. The distribution of fresh water is highly uneven over the Earth, with both strong latitudinal distributions due to the atmospheric general circulation, and even larger variability due to landforms and the interaction of land with global weather systems. The annual global fresh water budget is largely a balance between evaporation, atmospheric transport, precipitation and runoff. Although the available volume of fresh water on land is small, the short residence time of water in these fresh water reservoirs causes the flux of fresh water - through evaporation, atmospheric transport, precipitation and runoff - to be large. With a total atmospheric water store of approx. 13 x 10(exp 12)cu m, and an annual flux of approx. 460 x 10(exp 12)cu m/y, the mean atmospheric residence time of water is approx. 10 days. River residence times are similar, biological are approx. 1 week, soil moisture is approx. 2 months, and lakes and aquifers are highly variable, extending from weeks to years. The hypothesized potential for redistribution and acceleration of the global hydrological cycle is therefore of concern. This hypothesized speed-up - thought to be associated with global warming - adds to the pressure placed upon water resources by the burgeoning human population, the variability of weather and climate, and concerns about anthropogenic impacts on global fresh water availability.

Immobilization of lead in shooting range soils by means of cement, quicklime, and phosphate amendments.

Science.gov (United States)

Cao, Xinde; Dermatas, Dimitris; Xu, Xuanfeng; Shen, Gang

2008-03-01

formed calcite. Phosphate-induced Pb immobilization was mainly attributed to formation of less soluble PbHPO4. The results indicate that effectiveness of cementitious treatments (cement and quicklime) in immobilizing Pb varies in two soils, being effective in SR1 soil but less in SR2 soil. For one given soil, no difference was observed of the effeciveness between cement and quicklime treatments, whereas phosphate amendment emerges as a most effective treatment means for stabilizing Pb in both two soils, and it also shows a faster immobilization process and little effect on the soil acid buffering capacity. Recommendations and Perspectives. Overall, our study reveals that immobilizing Pb can be one of the best management practices for Pb contamination at shooting range sites. Phosphate amendment is most effective in immobilizing Pb in any kind of the soil ranges to minimize negative Pb impacts on the shooting range sites.

Evaluation of Applicability of Global Solar Radiation Prediction Models for Kocaeli

Directory of Open Access Journals (Sweden)

Nurullah ARSLANOĞLU

2016-04-01

Full Text Available Design and analyses of solar energy systems needs value of global solar radiation falling on the surface of the earth. In this study,  thirty relative sunshine duration based regression models in the literature for determining the monthly average daily global solar radiation on a horizontal surface for Kocaeli were investigated. To indicate the performance of the models, the following statistical test methods are used: mean absolute bias error (MABE, mean bias error (MBE, mean absolute percent error (MAPE, mean percent error (MPE, root mean square error (RMSE. According to the statistical performance, Lewis model (Model 23, Model-18 (Jin et al. and Model 8 (Bahel et al. showed the best estimation of the global solar radiation on a horizontal surface for Kocaeli.

Soils in Schools: Embedding Soil Science in STEM

Science.gov (United States)

Bryce, Alisa

2015-01-01

Soil science, though relevant to a variety of subjects including science, geography, mathematics, social sciences and history, is typically perceived as a subgenre of agriculture. With a global need for soil scientists, and declining numbers in university soil courses, there's a growing gap between science needs and providers. One way to promote…

Influence of soil properties on the behavior of heated on bottom pipelines

Energy Technology Data Exchange (ETDEWEB)

Hallai, Julian [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil)

2005-07-01

Offshore pipelines have increasingly been operating at high temperatures and high pressures. Compression due to these loads can lead to global buckling, either laterally and/or vertically, depending on the burial depth and soil properties. The amount of embedment of pipelines directly laid on the seabed depends on the soil properties and influences the behavior of pipelines in operation. This work investigates the interaction between the vertical and lateral buckling modes, based on the analytical approach proposed for pipeline global buckling analysis by Hobbs. Furthermore, it presents a sensitivity study characterizing the impact of the determination of accurate soil properties. Finally, a conceptual design procedure, which takes into account the particular case of short pipelines, is provided. The method is presented by means of an example case. (author)

Improved ground hydrology calculations for global climate models (GCMs) - Soil water movement and evapotranspiration

Science.gov (United States)

Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

1988-01-01

A physically based ground hydrology model is presented that includes the processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff. Data from the Goddard Institute for Space Studies GCM were used as inputs for off-line tests of the model in four 8 x 10 deg regions, including Brazil, Sahel, Sahara, and India. Soil and vegetation input parameters were caculated as area-weighted means over the 8 x 10 deg gridbox; the resulting hydrological quantities were compared to ground hydrology model calculations performed on the 1 x 1 deg cells which comprise the 8 x 10 deg gridbox. Results show that the compositing procedure worked well except in the Sahel, where low soil water levels and a heterogeneous land surface produce high variability in hydrological quantities; for that region, a resolution better than 8 x 10 deg is needed.

Assimilation of global radar backscatter and radiometer brightness temperature observations to improve soil moisture and land evaporation estimates

NARCIS (Netherlands)

Lievens, H.; Martens, B.; Verhoest, N.E.C.; Hahn, S.; Reichle, R.H.; Gonzalez Miralles, D.

2016-01-01

Active radar backscatter (σ°) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model

Modelling global change impacts on soil carbon contents of agro-silvo-pastoral Mediterranean systems

Science.gov (United States)

Lozano-García, Beatriz; Muñoz-Rojas, Miriam; Parras-Alcántara, Luis

2016-04-01

To assess the impact of climate change on soil organic C (SOC) stocks in agro-silvo-pastoral environments, different models have been applied worldwide at local or regional scales, such as as RothC (Francaviglia et al., 2012) or CENTURY (Alvaro-Fuentes et al., 2012). However, some of these models may require a high number of input parameters or can underestimate the effect of soil depth. CarboSOIL (Muñoz-Rojas et al., 2013) is an empirical model based on regression techniques and developed to predict SOC contents at standard soil depths (0-25, 25-50 and 50-75 cm) under a range of climate and/or land use change scenarios. CarboSOIL has been successfully applied in different Mediterranean areas ,e.g. Southern Spain (Muñoz-Rojas et al., 2013; Abd-Elmabod et al., 2014), Northern Egypt (Muñoz-Rojas et al., 2014) and Italy (Muñoz-Rojas et al., 2015). In this study, CarboSOIL was applied in the Cardeña and Montoro mountain range Natural Park. This area covers 385 km2 and is located within Sierra Morena (Córdoba, South Spain) and has a semiarid Mediterranean climate. It is characterized by agro-silvo-pastoral systems. The Mediterranean evergreen oak woodland (MEOW-dehesa) is savanna-like open woodland ecosystem characterized by silvopastoral uses, being an ancient human modified Mediterranean landscape (Corral-Fernández et al., 2013; Lozano-García and Parras-Alcántara 2013). The most representative soils in the Cardeña and Montoro mountain range Natural Park are Cambisols, Regosols, Leptosols and Fluvisols. These soils are characterized by low fertility, poor physical conditions and marginal capacity for agricultural use, together with low organic matter (OM) content due to climate conditions (semiarid Mediterranean climate) and soil texture (sandy). The model was applied at different soil depths: 0-25, 25-50 and 50-75 cm (Parras-Alcántara et al., 2015) considering land use and climate changes scenarios based on available global climate models (IPPC, 2007). A

A simple model for variations in global mean temperature: implications for decadal variability, the global warming hiatus, and recent temperature rise

Science.gov (United States)

Hu, S.; Fedorov, A. V.

2017-12-01

Global mean surface temperature (GMST) has steadily risen since the mid-19th century, and at the same time experienced significant variations on interannual and decadal timescales. Various mechanisms have been proposed to explain such variations, ranging from the Pacific decadal oscillation to volcanic eruptions. In this study, we construct a simple, physically-based model of GMST variations that incorporates greenhouse gas emissions, ENSO forcing, and stratospheric sulfate aerosols. The model closely reproduces the history of GMST changes since 1880 with the mean squared error about 0.05°C for the past 60 years, smaller than the typical error of GMST observations (see the figure attached). It also accurately captures decadal GMST variations, including the global warming hiatus in the early 21stcentury. This model can be used to understand the causes of the observed GMST variations and requires little computational resource. Our results confirm that weak El Niño activity was the major cause of the recent global warming hiatus, while the rapid temperature rise since 2014 is due to atmospheric heat release during 2014-2016 El Niño conditions in addition to the continuing background global warming trend. The model can be also used to make predictions for next-year GMST in the short term, and future climate projections in the long term. We will also discuss the implications of this simple model for paleoclimate reconstructions and GCM performance evaluations.

Historical and future perspectives of global soil carbon response to climate and land-use changes

Science.gov (United States)

Eglin, T.; Ciais, P.; Piao, S. L.; Barre, P.; Bellassen, V.; Cadule, P.; Chenu, C.; Gasser, T.; Koven, C.; Reichstein, M.; Smith, P.

2010-11-01

ABSTRACT In this paper, we attempt to analyse the respective influences of land-use and climate changes on the global and regional balances of soil organic carbon (SOC) stocks. Two time periods are analysed: the historical period 1901-2000 and the period 2000-2100. The historical period is analysed using a synthesis of published data as well as new global and regional model simulations, and the future is analysed using models only. Historical land cover changes have resulted globally in SOC release into the atmosphere. This human induced SOC decrease was nearly balanced by the net SOC increase due to higher CO2 and rainfall. Mechanization of agriculture after the 1950s has accelerated SOC losses in croplands, whereas development of carbon-sequestering practices over the past decades may have limited SOC loss from arable soils. In some regions (Europe, China and USA), croplands are currently estimated to be either a small C sink or a small source, but not a large source of CO2 to the atmosphere. In the future, according to terrestrial biosphere and climate models projections, both climate and land cover changes might cause a net SOC loss, particularly in tropical regions. The timing, magnitude, and regional distribution of future SOC changes are all highly uncertain. Reducing this uncertainty requires improving future anthropogenic CO2 emissions and land-use scenarios and better understanding of biogeochemical processes that control SOC turnover, for both managed and un-managed ecosystems.

Soil carbon 4 per mille

NARCIS (Netherlands)

Mulder, V.L.

2017-01-01

The ‘4 per mille Soils for Food Security and Climate’ was launched at the COP21 with an aspiration to increase global soil organic matter stocks by 4 per 1000 (or 0.4 %) per year as a compensation for the global emissions of greenhouse gases by anthropogenic sources. This paper surveyed the soil

Is research on soil erosion hazard and mitigation in the Global South still needed? (Alexander von Humbold Medal Lecture)

Science.gov (United States)

Poesen, Jean

2016-04-01

Soil erosion represents a geomorphological and geological hazard that may cause environmental damage (land degradation), property damage, loss of livelihoods and services as well as social and economic disruption. Erosion not only lowers the quality of our soils on site, resulting in a drastic reduction of their ecosystem functions that play a vital role in daily life, but causes also significant sediment-related problems off site. To curb soil erosion problems, a range of soil conservation techniques and strategies have been designed and are being applied. Worldwide, ca. 62 000 research papers on soil erosion and 116 000 on soil conservation have been published (Web of Science, Dec. 2015). The number of such papers dealing with the Global South represents less than 20 % of all papers, despite the fact that many regions in this part of the world face significant soil erosion problems, aggravated by a rapidly growing population and major environmental changes. Given the large number of research papers on this topic, one might therefore conclude that we now know almost everything about the various soil erosion processes and rates, their factors and consequences as well as their control so that little new knowledge can still be added to the vast amount of available information. We refute this conclusion by pointing to some major research gaps that still need to be addressed if we want to use our soils in a more sustainable way. More specifically the following topics need more research attention: 1) improved understanding of both natural and anthropogenic soil erosion processes and their interactions, 2) scaling up soil erosion processes and rates in space and time, and 3) innovative techniques and strategies to prevent or reduce erosion rates. This will be illustrated with case studies from the Global South. If future research focuses on these research gaps, we will 1) better understand processes and their interactions operating at a range of spatial and temporal

An initial assessment of a SMAP soil moisture disaggregation scheme using TIR surface evaporation data over the continental United States

Science.gov (United States)

Mishra, Vikalp; Ellenburg, W. Lee; Griffin, Robert E.; Mecikalski, John R.; Cruise, James F.; Hain, Christopher R.; Anderson, Martha C.

2018-06-01

The Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36-40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of -0.022 and -0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (>55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E.

Toxicity of a metal(loid)-polluted agricultural soil to Enchytraeus crypticus changes under a global warming perspective: Variations in air temperature and soil moisture content.

Science.gov (United States)

González-Alcaraz, M Nazaret; van Gestel, Cornelis A M

2016-12-15

This study aimed to assess how the current global warming perspective, with increasing air temperature (20°C vs. 25°C) and decreasing soil moisture content (50% vs. 30% of the soil water holding capacity, WHC), affected the toxicity of a metal(loid)-polluted agricultural soil to Enchytraeus crypticus. Enchytraeids were exposed for 21d to a dilution series of the agricultural soil with Lufa 2.2 control soil under four climate situations: 20°C+50% WHC (standard conditions), 20°C+30% WHC, 25°C+50% WHC, and 25°C+30% WHC. Survival, reproduction and bioaccumulation of As, Cd, Co, Cu, Fe, Mn, Ni, Pb and Zn were obtained as endpoints. Reproduction was more sensitive to both climate factors and metal(loid) pollution. High soil salinity (electrical conductivity~3dSm -1 ) and clay texture, even without the presence of high metal(loid) concentrations, affected enchytraeid performance especially at drier conditions (≥80% reduction in reproduction). The toxicity of the agricultural soil increased at drier conditions (10% reduction in EC10 and EC50 values for the effect on enchytraeid reproduction). Changes in enchytraeid performance were accompanied by changes in As, Fe, Mn, Pb and Zn bioaccumulation, with lower body concentrations at drier conditions probably due to greater competition with soluble salts in the case of Fe, Mn, Pb and Zn. This study shows that apart from high metal(loid) concentrations other soil properties (e.g. salinity and texture) may be partially responsible for the toxicity of metal(loid)-polluted soils to soil invertebrates, especially under changing climate conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

WoSIS – World Soil Information Service

NARCIS (Netherlands)

Batjes, N.H.; Carvalho Ribeiro, E.D.; Oostrum, van A.J.M.; Mendes de Jesus, J.S.

2016-01-01

ISRIC - World Soil Information (WDC-Soils) has a mission to serve the international community as custodian of global soil data and information, and to increase awareness and understanding of soils in major global issues. With partners we have implemented a server database based on PostgreSQL, known

Landscape-scale soil moisture heterogeneity and its influence on surface fluxes at the Jornada LTER site: Evaluating a new model parameterization for subgrid-scale soil moisture variability

Science.gov (United States)

Baker, I. T.; Prihodko, L.; Vivoni, E. R.; Denning, A. S.

2017-12-01

Arid and semiarid regions represent a large fraction of global land, with attendant importance of surface energy and trace gas flux to global totals. These regions are characterized by strong seasonality, especially in precipitation, that defines the level of ecosystem stress. Individual plants have been observed to respond non-linearly to increasing soil moisture stress, where plant function is generally maintained as soils dry down to a threshold at which rapid closure of stomates occurs. Incorporating this nonlinear mechanism into landscape-scale models can result in unrealistic binary "on-off" behavior that is especially problematic in arid landscapes. Subsequently, models have `relaxed' their simulation of soil moisture stress on evapotranspiration (ET). Unfortunately, these relaxations are not physically based, but are imposed upon model physics as a means to force a more realistic response. Previously, we have introduced a new method to represent soil moisture regulation of ET, whereby the landscape is partitioned into `BINS' of soil moisture wetness, each associated with a fractional area of the landscape or grid cell. A physically- and observationally-based nonlinear soil moisture stress function is applied, but when convolved with the relative area distribution represented by wetness BINS the system has the emergent property of `smoothing' the landscape-scale response without the need for non-physical impositions on model physics. In this research we confront BINS simulations of Bowen ratio, soil moisture variability and trace gas flux with soil moisture and eddy covariance observations taken at the Jornada LTER dryland site in southern New Mexico. We calculate the mean annual wetting cycle and associated variability about the mean state and evaluate model performance against this variability and time series of land surface fluxes from the highly instrumented Tromble Weir watershed. The BINS simulations capture the relatively rapid reaction to wetting

Global approach of mean service satisfaction assessment

Directory of Open Access Journals (Sweden)

Ahmed Dooguy Kora

2014-01-01

Full Text Available A theoretical expression for mobile service satisfaction assessment has been proposed. Mobile networks users’ satisfaction is a major concern for the operators and regulators. Therefore a certain level of network qualification is required to be offered to consumers by operators thanks to the decisions initiated by the regulation authority. For the assessment of the level of satisfaction, several methodologies and tools (measuring and monitoring have emerged. Ranking in two broad categories, namely the objective and subjective methods, both have advantages as well as disadvantages. This Letter has proposed a unified approach to evaluate more objectively users’ level of satisfaction of a service based on the most common network key performance indicators (KPIs rate following the different methods. This approach's main advantage is that it has taken advantages of the different positive aspects of the existing methods and outperformed their limitations thanks to the introduced concept of global KPI. In addition, the size of samples according to each method has been considered. A mean service satisfaction theoretical expression has been proposed to regulation authority, consumers association and operators as common base of service satisfaction assessment.

SOIL Geo-Wiki: A tool for improving soil information

Science.gov (United States)

Skalský, Rastislav; Balkovic, Juraj; Fritz, Steffen; See, Linda; van der Velde, Marijn; Obersteiner, Michael

2014-05-01

Crowdsourcing is increasingly being used as a way of collecting data for scientific research, e.g. species identification, classification of galaxies and unravelling of protein structures. The WorldSoilProfiles.org database at ISRIC is a global collection of soil profiles, which have been 'crowdsourced' from experts. This system, however, requires contributors to have a priori knowledge about soils. Yet many soil parameters can be observed in the field without specific knowledge or equipment such as stone content, soil depth or color. By crowdsourcing this information over thousands of locations, the uncertainty in current soil datasets could be radically reduced, particularly in areas currently without information or where multiple interpretations are possible from different existing soil maps. Improved information on soils could benefit many research fields and applications. Better soil data could enhance assessments of soil ecosystem services (e.g. soil carbon storage) and facilitate improved process-based ecosystem modeling from local to global scales. Geo-Wiki is a crowdsourcing tool that was developed at IIASA for land cover validation using satellite imagery. Several branches are now available focused on specific aspects of land cover validation, e.g. validating cropland extent or urbanized areas. Geo-Wiki Pictures is a smart phone application for collecting land cover related information on the ground. The extension of Geo-Wiki to a mobile environment provides a tool for experts in land cover validation but is also a way of reaching the general public in the validation of land cover. Here we propose a Soil Geo-Wiki tool that builds on the existing functionality of the Geo-Wiki application, which will be largely designed for the collection and sharing of soil information. Two distinct applications are envisaged: an expert-oriented application mainly for scientific purposes, which will use soil science related language (e.g. WRB or any other global reference

Response of soil respiration to soil temperature and moisture in a 50-year-old oriental arborvitae plantation in China.

Science.gov (United States)

Yu, Xinxiao; Zha, Tianshan; Pang, Zhuo; Wu, Bin; Wang, Xiaoping; Chen, Guopeng; Li, Chunping; Cao, Jixin; Jia, Guodong; Li, Xizhi; Wu, Hailong

2011-01-01

China possesses large areas of plantation forests which take up great quantities of carbon. However, studies on soil respiration in these plantation forests are rather scarce and their soil carbon flux remains an uncertainty. In this study, we used an automatic chamber system to measure soil surface flux of a 50-year-old mature plantation of Platycladus orientalis at Jiufeng Mountain, Beijing, China. Mean daily soil respiration rates (R(s)) ranged from 0.09 to 4.87 µmol CO(2) m(-2) s(-1), with the highest values observed in August and the lowest in the winter months. A logistic model gave the best fit to the relationship between hourly R(s) and soil temperature (T(s)), explaining 82% of the variation in R(s) over the annual cycle. The annual total of soil respiration estimated from the logistic model was 645±5 g C m(-2) year(-1). The performance of the logistic model was poorest during periods of high soil temperature or low soil volumetric water content (VWC), which limits the model's ability to predict the seasonal dynamics of R(s). The logistic model will potentially overestimate R(s) at high T(s) and low VWC. Seasonally, R(s) increased significantly and linearly with increasing VWC in May and July, in which VWC was low. In the months from August to November, inclusive, in which VWC was not limiting, R(s) showed a positively exponential relationship with T(s). The seasonal sensitivity of soil respiration to T(s) (Q(10)) ranged from 0.76 in May to 4.38 in October. It was suggested that soil temperature was the main determinant of soil respiration when soil water was not limiting.