Zooplankton abundance of the Andaman sea

Digital Repository Service at National Institute of Oceanography (India)

Madhupratap, M.; Achuthankutty, C.T.; Nair, S.R.S.; Nair, V.R.

the dominant component followed by Chaetognatha and Tunicata Estimates of zooplankton biomass to dry weight and to organic carbon content are made. The average standing crop of zooplankton is 288.8 mg C m2 for the upper 200 m column...

Organic carbon content of tropical zooplankton

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.

In the Zuari and Mandovi estuaries variations in organic carbon of zooplankton are 26.4-38.8 and 24-39.9% of dry weight respectively. Maximum carbon content of estuarine zooplankton is observed in November. Organic carbon in nearshore and oceanic...

Zooplankton of the Zaporiz’ke Reservoir

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T. V. Mykolaichuk

2006-01-01

Full Text Available The paper is devoted to zooplankton species composition in the Zaporiz’ke Reservoir. The greatest species diversity was found in the macrophyte communities of the upper reservoir’s littoral, but the least zooplankton diversity – in the pelagic zone of the lower reservoir.

Effect of advection on variations in zooplankton at a single location near Cabo Nazca, Peru

Energy Technology Data Exchange (ETDEWEB)

Smith, S L; Brink, K H; Santander, H; Cowles, T J; Huyer, A

1980-04-01

Temporal variations in the biomass and species composition of zooplankton at a single midshelf station in an upwelling area off Peru can be explained to a large extent by onshore-offshore advection in the upper 20 m of the water column. During periods of strong or sustained near-surface onshore flow, peaks in biomass of zooplankton were observed at midshelf and typically oceanic species of copepod were collected. In periods of offshore flow at the surface, a copepod capable of migrating into oxygen-depleted layers deeper than 30 m was collected. A simple translocation model of advection applied to the cross-shelf distribution of Paracalanus parvus suggests that the fluctuations in P. pavus observed in the midshelf time-series were closely related to onshore-offshore flow in the upper 20 m. Fluctuations in abundance of the numerically dominant copepod, Acartia tonsa, were apparently affected by near surface flow also. The population age-structure suggests that A. tonsa was growing at maximal rates, due in part to its positive feeding response to the dinoflagellate/diatom assemblage of phytoplankton.

Diel vertical migration of zooplankton in the Tanzanian waters of ...

African Journals Online (AJOL)

The diel vertical migration of zooplankton was studied in the Southern part of Lake Victoria in January and July 2002. A van dorn water sampler was used to collect zooplankton. In January 2002, zooplankton showed a pronounced diel vertical migration whereby zooplankton were moving upward at around sunset and ...

Potential acidification impacts on zooplankton in CCS leakage scenarios

International Nuclear Information System (INIS)

Halsband, Claudia; Kurihara, Haruko

2013-01-01

Highlights: • Effects of CCS techniques and ocean acidification on zooplankton are under-studied. • Vulnerable zooplankton are meso-, bathypelagic and vertically migrating species. • Impacts include impaired calcification, reproduction, development and survival. • Need for modelling studies combining physico-chemical with ecological impacts. -- Abstract: Carbon capture and storage (CCS) technologies involve localized acidification of significant volumes of seawater, inhabited mainly by planktonic species. Knowledge on potential impacts of these techniques on the survival and physiology of zooplankton, and subsequent consequences for ecosystem health in targeted areas, is scarce. The recent literature has a focus on anthropogenic greenhouse gas emissions into the atmosphere, leading to enhanced absorption of CO 2 by the oceans and a lowered seawater pH, termed ocean acidification. These studies explore the effects of changes in seawater chemistry, as predicted by climate models for the end of this century, on marine biota. Early studies have used unrealistically severe CO 2 /pH values in this context, but are relevant for CCS leakage scenarios. Little studied meso- and bathypelagic species of the deep sea may be especially vulnerable, as well as vertically migrating zooplankton, which require significant residence times at great depths as part of their life cycle

Recent advances in the Mediterranean researches on zooplankton: from spatial–temporal patterns of distribution to processes oriented studies

Directory of Open Access Journals (Sweden)

Serena Fonda Umani

2010-12-01

Full Text Available In this review we focus on research performed by Italian scientists on pelagic communities, from microzooplankton to micronekton, mainly in the Italian Seas. We considered published data, mostly as grey literature, and unpublished ones. Firstly we describe data collected over a time span of more than 30 years, during several cruises all around the Italian peninsula on zooplankton composition and distribution. We identified rare vs. common species, which enhanced biodiversity of the pelagic ecosystem. Time series, some also very long, allowed us to describe seasonal recurrent patterns, interannual fluctuations and recent shifts driven by climatic changes. More recently Italian researches were processes oriented and we analyzed results obtained on the impact of predation of both micro- and mesozooplankton on both autotrophic and heterotrophic preys. Carbon fluxes through zooplankton components were variable in space and time, but accounted for important phytoplankton losses, and when this resource became scarce they relied on heterotrophic production. Through respiration measurements of mesozooplankton another aspect of the C flux was estimated showing an increase in C demand in the most oligotrophic area. Egg production by copepods appeared to be mostly controlled by temperature and quantity/quality of available food.

Zooplankton variability in the Zuari estuary, Goa

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.; Achuthankutty, C.T.; Nair, S.R.S.

Short term variability in the secondary production and composition of zooplankton were studied during February to March 1979 by collecting zooplankton every alternate day from a station located near the mouth of Zuari. Irregularity in the production...

Ingestion of microplastics by natural zooplankton groups in the northern South China Sea.

Science.gov (United States)

Sun, Xiaoxia; Li, Qingjie; Zhu, Mingliang; Liang, Junhua; Zheng, Shan; Zhao, Yongfang

2017-02-15

The ingestion of microplastics by five natural zooplankton groups in the northern South China Sea was studied for the first time and two types of sampling nets (505μm and 160μm in mesh size) were compared. The microplastics were detected in zooplankton sampled from 16 stations, with the fibrous microplastics accounting for the largest proportion (70%). The main component of the found microplastics was polyester. The average length of the microplastics was 125μm and 167μm for Nets I and II, respectively. The encounter rates of microplastics/zooplankton increased with trophic levels. The average encounter rate of microplastics/zooplankton was 5%, 15%, 34%, 49%, and 120% for Net I, and 8%, 21%, 47%, 60%, and 143% for Net II for copepods, chaetognaths, jellyfish, shrimp, and fish larvae, respectively. The average abundance of microplastics that were ingested by zooplankton was 4.1pieces/m 3 for Net I and 131.5pieces/m 3 for Net II. Copyright © 2016 Elsevier Ltd. All rights reserved.

Composition and abundance of the zooplankton community in the ...

African Journals Online (AJOL)

The taxonomic composition of the zooplankton community of the Bitter Lakes, Egypt, was examined in 2003–2004 in relation to the spatial and temporal distribution of environmental factors. Copepoda were dominant, forming 49% of the zooplankton, followed by Protista at 37%. During the autumn, zooplankton in Small ...

Zooplankton use of chemodetection to find and eat particles

DEFF Research Database (Denmark)

Jackson, G.A.; Kiørboe, Thomas

2004-01-01

The ability of raptorial zooplankton to find large particles such as marine aggregates is crucial to their use of the particles as food and to the fate of the particles. Kiorboe & Thygesen (2001) developed a numerical approach to describe particle detection by chemosensory zooplankton. In this pa......The ability of raptorial zooplankton to find large particles such as marine aggregates is crucial to their use of the particles as food and to the fate of the particles. Kiorboe & Thygesen (2001) developed a numerical approach to describe particle detection by chemosensory zooplankton...

Evaluation of factors related to increased zooplankton biomass and altered species composition following impoundment of a Newfoundland reservoir

International Nuclear Information System (INIS)

Campbell, C.E.; Knoechel, R.; Copeman, D.

1998-01-01

An 11-year study of the zooplankton community in Cat Arm Hydroelectric Reservoir in Newfoundland was conducted to assess long-term zooplankton community dynamics in a subarctic system. Zooplankton biomass and species compositions were monitored from 1983 to 1993. The monitoring program documented the trophic evolution of the Cat Arm system as it changed from a shallow lake with short water retention time to a deep reservoir with a much lower flushing rate. Zooplankton biomass increased approximately 19-fold in the oligotrophic hydroelectric reservoir following impoundment in 1984, relative to biomass in the preexisting lake. During the first three years of impoundment, there were no increases in either phytoplankton biomass or primary productivity. Natality of the dominant cladoceran (Daphnia catawba) did not increase. Summer water retention time increased from pre-impoundment levels of 4 days in 1983 to 338 days in 1993. The study showed that zooplankton biomass was greatly correlated with water retention time, and showed no major correlation with phytoplankton biomass, primary productivity, nutrient concentrations, pH, colour, or epilimnetic temperature. It was concluded that changes in the zooplankton community in the hydroelectric reservoir were a result of decreases in losses due to washout. 41 refs., 2 tabs., 6 figs

Empirical relationships between phytoplankton and zooplankton biomass in Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Jayalakshmy, K.V.

and temperature, zooplankton and phytoplankton, zooplankton and PO sub(4)-P and phytoplankton and PO sub(4)-P. Linear regression model is found to be significant at 1% level of significance. Since zooplankton and phytoplankton are significantly positively...

Metabarcoding Reveals Seasonal and Temperature-Dependent Succession of Zooplankton Communities in the Red Sea

KAUST Repository

Casas, Laura; Pearman, John K.; Irigoien, Xabier

2017-01-01

Very little is known about the composition and the annual cycle of zooplankton assemblages in the Red Sea, a confined water body characterized by a high biodiversity and endemism but at the same time one of the most understudied areas in the world in terms of marine biodiversity. This high diversity together with the lack of references for several of the groups poses a problem in obtaining basic information on zooplankton seasonal patterns. In the present work, we used high throughput sequencing to examine the temporal and spatial distribution of the zooplankton communities inhabiting the epipelagic zone in the central Red Sea. The analysis of zooplankton assemblages collected at two sites—coastal and offshore—twice a month at several depth strata by using MANTA, Bongo and WP2 nets provides baseline information of the seasonal patterns of the zooplankton community over 1 year. We show that the seasonal fluctuation of zooplankton communities living in the upper 100 m of the water column is driven mainly by the annual changes in seawater temperature. The 18S rRNA gene was used for metabarcoding of zooplankton assemblages revealing 630 metazoan OTUs (97% similarity) in five phyla, highlighting the richness of the Red Sea community. During colder months, communities were characterized by lower richness and higher biomass than communities found during the hot season. Throughout the year the zooplankton communities were dominated by the class Maxillopoda, mainly represented by copepods and class Hydrozoa. The rise in the water temperature favors the appearance of classes Malacostraca, Cephalopoda, Gastropoda, and Saggitoidea. The present study provides essential baseline information for future monitoring and improves our knowledge of the marine ecosystem in the Red Sea while reporting the main environmental variable structuring zooplankton assemblages in this region.

Metabarcoding Reveals Seasonal and Temperature-Dependent Succession of Zooplankton Communities in the Red Sea

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Laura Casas

2017-08-01

Full Text Available Very little is known about the composition and the annual cycle of zooplankton assemblages in the Red Sea, a confined water body characterized by a high biodiversity and endemism but at the same time one of the most understudied areas in the world in terms of marine biodiversity. This high diversity together with the lack of references for several of the groups poses a problem in obtaining basic information on zooplankton seasonal patterns. In the present work, we used high throughput sequencing to examine the temporal and spatial distribution of the zooplankton communities inhabiting the epipelagic zone in the central Red Sea. The analysis of zooplankton assemblages collected at two sites—coastal and offshore—twice a month at several depth strata by using MANTA, Bongo and WP2 nets provides baseline information of the seasonal patterns of the zooplankton community over 1 year. We show that the seasonal fluctuation of zooplankton communities living in the upper 100 m of the water column is driven mainly by the annual changes in seawater temperature. The 18S rRNA gene was used for metabarcoding of zooplankton assemblages revealing 630 metazoan OTUs (97% similarity in five phyla, highlighting the richness of the Red Sea community. During colder months, communities were characterized by lower richness and higher biomass than communities found during the hot season. Throughout the year the zooplankton communities were dominated by the class Maxillopoda, mainly represented by copepods and class Hydrozoa. The rise in the water temperature favors the appearance of classes Malacostraca, Cephalopoda, Gastropoda, and Saggitoidea. The present study provides essential baseline information for future monitoring and improves our knowledge of the marine ecosystem in the Red Sea while reporting the main environmental variable structuring zooplankton assemblages in this region.

Metabarcoding Reveals Seasonal and Temperature-Dependent Succession of Zooplankton Communities in the Red Sea

KAUST Repository

Casas, Laura

2017-08-02

Very little is known about the composition and the annual cycle of zooplankton assemblages in the Red Sea, a confined water body characterized by a high biodiversity and endemism but at the same time one of the most understudied areas in the world in terms of marine biodiversity. This high diversity together with the lack of references for several of the groups poses a problem in obtaining basic information on zooplankton seasonal patterns. In the present work, we used high throughput sequencing to examine the temporal and spatial distribution of the zooplankton communities inhabiting the epipelagic zone in the central Red Sea. The analysis of zooplankton assemblages collected at two sites—coastal and offshore—twice a month at several depth strata by using MANTA, Bongo and WP2 nets provides baseline information of the seasonal patterns of the zooplankton community over 1 year. We show that the seasonal fluctuation of zooplankton communities living in the upper 100 m of the water column is driven mainly by the annual changes in seawater temperature. The 18S rRNA gene was used for metabarcoding of zooplankton assemblages revealing 630 metazoan OTUs (97% similarity) in five phyla, highlighting the richness of the Red Sea community. During colder months, communities were characterized by lower richness and higher biomass than communities found during the hot season. Throughout the year the zooplankton communities were dominated by the class Maxillopoda, mainly represented by copepods and class Hydrozoa. The rise in the water temperature favors the appearance of classes Malacostraca, Cephalopoda, Gastropoda, and Saggitoidea. The present study provides essential baseline information for future monitoring and improves our knowledge of the marine ecosystem in the Red Sea while reporting the main environmental variable structuring zooplankton assemblages in this region.

Numerical studies of the influence of food ingestion on phytoplankton and zooplankton biomasses

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Lidia Dzierzbicka-G³owacka

2002-03-01

Full Text Available This paper presents the numerical simulations of the influence of food ingestion by a herbivorous copepod on phytoplankton and zooplankton biomasses (PZB in the sea. The numerical studies were carried out using the phytoplankton-zooplankton-nutrient-detritus PhyZooNuDe biological upper layer model. This takes account both of fully developed primary production and regeneration mechanisms and of daily migration of zooplankton. In this model the zooplankton is treated not as a 'biomass' but as organisms having definite patterns of growth, reproduction and mortality. Assuming also that {Zoop} is composed ofi cohorts of copepods with weights Wi and numbers Zi, then {Zoop} = WiZi. The PhyZooNuDe model consists of three coupled, partial second-order differential equations of the diffusion type for phytoplankton, zooplankton and nutrients, and one ordinary first-order differential equation for the benthic detritus pool, together with initial and boundary conditions. The calculations were made during 90 days (April, May and June for the study area P1 (Gdansk Deep in an area 0z<=20 m with a vertical space step of 0.1 m and a time step of 300 s. The simulation given here demonstrated the importance of food ingestion by zooplankton in that it can alter the nature of the interactions of plants and herbivores. The analysis of these numerical studies indicate that the maximal ingestion rate and the half-saturation constant for grazing strongly affect the magnitude of the spring bloom and the cyanobacterial bloom, and also the total zooplankton biomass.

Structural-functional organization of the littoral zooplankton communities of the Kremenchutskiy reservoir

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Z. Burian

2018-03-01

Full Text Available Purpose. To find out the present state of the structural and functional organization of the littoral zooplankton communities of the upper Kremenchuk reservoir in the area of ​​the Kaniv Nature Reserve. Methodology. The material was collected in the summer time of 2016 at six stations of the littoral zone of the upper Kremenchug reservoir. The collection and analysis were carried out using generally accepted methods. The objects of the research were representatives of three main groups of zooplankton (rotifers, cladocerans, copepods, as well as ostracods and larvae of bivalve molluscs. Statistical data processing was done in MS Excel 2013. Findings. The results of the study represent the present state and organisation of littoral zooplankton. The species richness of the littoral zooplankton of the upper Kremenchug reservoir was presented by 48 species. There are 20 species of monogonont rotifers, 18 cladocerans species and copepods – 10. The representatives of the rotifer-cladoceran complex dominated in the taxonomic composition that can be explained by the preservation of the river regime and the rheophilic conditions in this part of the reservoir. The analysis showed that according to the ecological spectrum of zooplankton groups, the representatives of the pelagic group dominated – 47.92%. As for the feeding type, the largest share was represented by the non-predatory group – 64.58%. After analyzing of the quantitative indices (density and biomass of zooplankton, it was found that they were lower than average for overgrown biotopes (112580 ± 129914 ind./m³ і 1.83 ± 2.07 g/m³ and low for open water (26160 ± 19161 ind./m³ і 0,82 ± 0,86 g/m³. Originality. The present state of structural and functional organization of the littoral zooplankton communities of the upper Kremenchug reservoir has been revealed. Practical significance. The conducted studies give the information about the structural and functional organization of the

Zooplankton excretion metabolites stimulate Southern Ocean phytoplankton growth

KAUST Repository

Coello-Camba, A.; Llabré s, M.; Duarte, Carlos M.; Agusti, Susana

2017-01-01

Warming over Antarctica is leading to changes in the zooplankton communities inhabiting the Southern Ocean. It has been observed that zooplankton not only regulates phytoplankton through grazing, but also through the recycling of nutrients that are essential for phytoplankton growth. In this way, the effects of warming on zooplankton populations will change the amount or proportion at which recycled nutrients are restored. To estimate how the recycled nutrients released by zooplankton populations, dominated by krill (Euphausia superba), amphipods or copepods, affect the phytoplankton uptake and communities, we performed four incubation experiments: two close to the Antarctic Peninsula and two at the Southern Atlantic Ocean. Our results showed a stimulating effect of the addition of metabolites on ammonia removal rates and on the net growth of phytoplankton communities, with different responses amongst the different phytoplankton groups. According to our results, phytoplankton net growth and community composition may be altered if this relevant source of nutrients is lost due to projected changes in the abundance or distribution of these zooplankton populations.

Zooplankton excretion metabolites stimulate Southern Ocean phytoplankton growth

KAUST Repository

Coello-Camba, A.

2017-04-24

Warming over Antarctica is leading to changes in the zooplankton communities inhabiting the Southern Ocean. It has been observed that zooplankton not only regulates phytoplankton through grazing, but also through the recycling of nutrients that are essential for phytoplankton growth. In this way, the effects of warming on zooplankton populations will change the amount or proportion at which recycled nutrients are restored. To estimate how the recycled nutrients released by zooplankton populations, dominated by krill (Euphausia superba), amphipods or copepods, affect the phytoplankton uptake and communities, we performed four incubation experiments: two close to the Antarctic Peninsula and two at the Southern Atlantic Ocean. Our results showed a stimulating effect of the addition of metabolites on ammonia removal rates and on the net growth of phytoplankton communities, with different responses amongst the different phytoplankton groups. According to our results, phytoplankton net growth and community composition may be altered if this relevant source of nutrients is lost due to projected changes in the abundance or distribution of these zooplankton populations.

GPS Position Time Series @ JPL

Science.gov (United States)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

Distribution of zooplankton populations within and adjacent to a thermal plume

International Nuclear Information System (INIS)

Evans, M.S.

1981-01-01

Zooplankton distributions in the 1-m stratum differed between ambient waters and the thermal plume of the Donald C. Cook Nuclear Power Plant. Zooplankton were most abundant in the warmest waters of the plume with the region of high densities extending over an approximate area of 0.2 to 0.3 km 2 . Water temperature was not a reliable indicator of alterations in zooplankton populations. Alterations were primarily due to upward vertical displacment of deep-living zooplankton. Large horizontal variability in zooplankton densities and use of conventional sampling procedures (vertically hauled nets, widely spaced stations) prevent traditionally designed monitoring programs from detecting such alterations. Zooplankton may experience indirect mortality losses in the plume if transfer of deep-living zooplankton to the surface layers makes them more visible to visual-feeding fish predators, and turbulences in the plume reduce zooplankters' ability to detect and avoid such predators. (auth)

Effects of Climate on the Zooplankton of the California Current

Science.gov (United States)

Lavaniegos, B. E.

2007-05-01

Almost six decades of sampling of the California Current system, carried out by the CalCOFI program (California Cooperative Fisheries Investigation) complemented by a decade of observations from the IMECOCAL program (Investigaciones Mexicanas de la Corriente de California), have revealed changing patterns in zooplankton abundances, species composition, and distributions over interannual through multidecadal time scales. Interannual changes associated with ENSO variability are manifested as strong but transitory perturbations in the mean annual cycle in seasonal abundances (and distributions) of particular species. An investigation of longer- term change, limited to the region off southern California, shows a persistent decline in zooplankton volumes (a proxy for overall biomass of macrozooplankton) between 1977 and 1998 that is considered to be a response to the well documented shift in basin-scale climate forcing that occurred in 1976-77. Further examination of this decline in zooplankton volumes indicates that it was due principally to the disappearance of several salp species after 1977. Other species and functional groups did not decline after the change in climate regime, while some species have followed persistent secular trends that appear to be associated more with the phenomenon of long-term global warming. Differences in the regional responses to climate change throughout the California Current system have also been observed recently in the spatial distribution of zooplankton biomass and changes in latitudinal ranges of certain species. For example, zooplankton biomass in the Baja California region show typical values for the 1997-98 El Niño that were followed by a decrease during the sharp transition to the cool La Niña conditions in 1999. This contrasts with the nearby region off southern California that was characterized by reduced biomass during the El Niño period and the subsequent recovery during the La Niña. Another regional contrast in

Nutrient supply, surface currents, and plankton dynamics predict zooplankton hotspots in coastal upwelling systems

Science.gov (United States)

Messié, Monique; Chavez, Francisco P.

2017-09-01

A simple combination of wind-driven nutrient upwelling, surface currents, and plankton growth/grazing equations generates zooplankton patchiness and hotspots in coastal upwelling regions. Starting with an initial input of nitrate from coastal upwelling, growth and grazing equations evolve phytoplankton and zooplankton over time and space following surface currents. The model simulates the transition from coastal (large phytoplankton, e.g., diatoms) to offshore (picophytoplankton and microzooplankton) communities, and in between generates a large zooplankton maximum. The method was applied to four major upwelling systems (California, Peru, Northwest Africa, and Benguela) using latitudinal estimates of wind-driven nitrate supply and satellite-based surface currents. The resulting zooplankton simulations are patchy in nature; areas of high concentrations coincide with previously documented copepod and krill hotspots. The exercise highlights the importance of the upwelling process and surface currents in shaping plankton communities.

Time series analysis time series analysis methods and applications

CERN Document Server

Rao, Tata Subba; Rao, C R

2012-01-01

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...

Zooplankton biomass to chlorophyll ratios in relation to trophic status ...

African Journals Online (AJOL)

Rising eutrophication in South African reservoirs is of major concern, leading to the consideration of top-down biomanipulation as a management option – reducing zooplankton-eating fish to sustain zooplankton grazing pressure and thus restrict autotrophic plankton that proliferate with nutrient increases. The biomass ratio ...

Highly comparative time-series analysis: the empirical structure of time series and their methods.

Science.gov (United States)

Fulcher, Ben D; Little, Max A; Jones, Nick S

2013-06-06

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.

Introduction to Time Series Modeling

CERN Document Server

Kitagawa, Genshiro

2010-01-01

In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f

Zooplankton and zoobenthos of the Mokra Sura river

Directory of Open Access Journals (Sweden)

V. Yakovenko

2017-12-01

saprobity indices in these sites. According to CICS index, the sites of 3 km and 2 km upstream from the river mouth were the purest ones as indicated by the greatest development of filter feeding crustaceans and the lowest indices of saprobity compared to the other sites studied. These results indicate a very effective biogenic detoxification and precipitation of toxic substances entering the river in the above-mentioned areas, as well as dilution effects of large water masses from the Dnieper River in the mouth areas of its tributaries Originality. For the first time, the ecological state of the selected sites of the Mokra Sura River was assessed on the basis of the results of a comprehensive study of the structural and functional indicators of zooplankton and zoobenthos during the maximum development of their hydrobiocenosis. Practical value. The obtained results can be used for hydroecological monitoring to detect the dangerous ecological state of small rivers and to prevent further degradation of the ecosystems of small rivers as well as for calculation of fish losses caused by sewage water effects.

Struktur Komunitas Zooplankton di Bendungan Telaga Tunjung, Kabupaten Tabanan-Bali

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Ni Wayan Desy Wahyudiati

2017-05-01

Full Text Available Zooplankton are the heterotroph aquatic organisms and has a week swimming. Zooplankton acts as the first consumer in the waters, which utilize phytoplankton as their food. This research located in Telaga Tunjung reservoir, Timpag Village, Kerambitan Subdistrict, Tabanan Regency. The reservoir is used for industry, irrigation and tourism development. The aim of the research was to determine the community structure of zooplankton in Telaga Tunjung reservoir. This research was conducted from January to February 2016. Water sampling was conducted twice with a sampling interval of 2 weeks in 4 stations. There was a total of 23 species of zooplankton found, consisting of 6 classes: Eurotatoria (8 genera, Ciliatea (1 genera, Branchiopoda (4 genera, Monogononta (1 genera, Tubulinea (1 genera and Maxillopoda (3 genera. The most common species of zooplankton found in the sampling station were Polyarthra vulgaris (3.04 ind/l, Anuraeopsis coelata (1.28 ind/l, Keratella valga (0.43 ind/l, Vorticella sp. (0.49 ind/l, Diaphanosoma brachyurum (0.28 ind/l, Nauplius sp. (0.16 ind/l and Megacyclops viridis (1.16 ind/l. The average abundance of zooplankton was 9.38 ind/l. Based on the abundance of zooplankton, the trophic status of Telaga Tunjung reservoir is mesotrophic.

Zooplankton of an urban coastal lagoon: composition and association with environmental factors and summer fish kill

Directory of Open Access Journals (Sweden)

Leonardo C. e Souza

2011-06-01

Full Text Available Zooplankton may be regarded as a sensitive tool for monitoring environmental variations in coastal lagoons due to their ability to immediately react to changes in the water column trophic features and salinity levels. As a coastal lagoon with a broad history of anthropic influence, Rodrigo de Freitas Lagoon (Rio de Janeiro, Brazil is widely used for water sports and artisanal fishing. The present study aimed to expand the knowledge base about zooplankton in the Rodrigo de Freitas Lagoon by assessing the composition and time-spatial distribution of the major zooplankton groups. Samples were collected fortnightly from at four distinct sampling points August 2001 to July 2002. At each point, salinity, temperature, dissolved oxygen and water transparency were measured. During the study period, the lagoon behaved as an spatially homogeneous environment in what regards the abiotic variables. However, all these variables showed significant differences along the time, mainly related to seasonality (air temperature and rainy and dry periods. The zooplankton community showed low taxonomic richness, with the predominance of species commonly found in coastal lagoons, especially with mesohaline conditions, as well as those found in estuaries. An interesting fact was the rise in zooplankton abundance at all sampling points right after a fish kill event. Such increase was caused mainly by the Brachionus plicatilis O.F. Müller 1786 species. Thus, the zooplankton community was affected by physical and chemical factors, mainly by the dissolved oxygen decline event and variations in the influx of seawater into the lagoon. In addition, phytoplankton availability and fish predation pressure were suggested as important regulating factors of the zooplankton community.

Zooplankton species identities collected from zooplankton net casts in Indian Ocean from 17 February 1960 to 23 July 1962 (NODC Accession 9400059)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Zooplankton species identities and other data were collected using zooplankton net casts in the Indian Ocean. Data were collected from 17 February 1960 to 23 July...

Zooplankton data collected by ELTANIN in Southern Oceans from zooplankton net casts; 13 October 1963 to 06 June 1968 (NODC Accession 9500111)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Zooplankton data were collected using zooplankton net casts from ELTANIN in the Southern Oceans. Data were collected from 13 October 1963 to 06 June 1968 by National...

Zooplankton size selection relative to gill raker spacing in rainbow trout

Science.gov (United States)

Budy, P.; Haddix, T.; Schneidervin, R.

2005-01-01

Rainbow trout Oncorhynchus mykiss are one of the most widely stocked salmonids worldwide, often based on the assumption that they will effectively utilize abundant invertebrate food resources. We evaluated the potential for feeding morphology to affect prey selection by rainbow trout using a combination of laboratory feeding experiments and field observations in Flaming Gorge Reservoir, Utah-Wyoming. For rainbow trout collected from the reservoir, inter-gill raker spacing averaged 1.09 mm and there was low variation among fish overall (SD = 0.28). Ninety-seven percent of all zooplankton observed in the diets of rainbow trout collected in the reservoir were larger than the interraker spacing, while only 29% of the zooplankton found in the environment were larger than the interraker spacing. Over the size range of rainbow trout evaluated here (200-475 mm), interraker spacing increased moderately with increasing fish length; however, the size of zooplankton found in the diet did not increase with increasing fish length. In laboratory experiments, rainbow trout consumed the largest zooplankton available; the mean size of zooplankton observed in the diets was significantly larger than the mean size of zooplankton available. Electivity indices for both laboratory and field observations indicated strong selection for larger-sized zooplankton. The size threshold at which electivity switched from selection against smaller-sized zooplankton to selection for larger-sized zooplankton closely corresponded to the mean interraker spacing for both groups (???1-1.2 mm). The combination of results observed here indicates that rainbow trout morphology limits the retention of different-sized zooplankton prey and reinforces the importance of understanding how effectively rainbow trout can utilize the type and sizes of different prey available in a given system. These considerations may improve our ability to predict the potential for growth and survival of rainbow trout within and

Moonlight Drives Ocean-Scale Mass Vertical Migration of Zooplankton during the Arctic Winter.

Science.gov (United States)

Last, Kim S; Hobbs, Laura; Berge, Jørgen; Brierley, Andrew S; Cottier, Finlo

2016-01-25

In extreme high-latitude marine environments that are without solar illumination in winter, light-mediated patterns of biological migration have historically been considered non-existent [1]. However, diel vertical migration (DVM) of zooplankton has been shown to occur even during the darkest part of the polar night, when illumination levels are exceptionally low [2, 3]. This paradox is, as yet, unexplained. Here, we present evidence of an unexpected uniform behavior across the entire Arctic, in fjord, shelf, slope and open sea, where vertical migrations of zooplankton are driven by lunar illumination. A shift from solar-day (24-hr period) to lunar-day (24.8-hr period) vertical migration takes place in winter when the moon rises above the horizon. Further, mass sinking of zooplankton from the surface waters and accumulation at a depth of ∼50 m occurs every 29.5 days in winter, coincident with the periods of full moon. Moonlight may enable predation of zooplankton by carnivorous zooplankters, fish, and birds now known to feed during the polar night [4]. Although primary production is almost nil at this time, lunar vertical migration (LVM) may facilitate monthly pulses of carbon remineralization, as they occur continuously in illuminated mesopelagic systems [5], due to community respiration of carnivorous and detritivorous zooplankton. The extent of LVM during the winter suggests that the behavior is highly conserved and adaptive and therefore needs to be considered as "baseline" zooplankton activity in a changing Arctic ocean [6-9]. VIDEO ABSTRACT. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The effect of salinity levels on the structure of zooplankton communities

Directory of Open Access Journals (Sweden)

Paturej Ewa

2015-01-01

Full Text Available The objective of this study was to determine the qualitative and quantitative structure of zooplankton communities in the Vistula Lagoon and to establish whether zooplankton abundance and biodiversity are affected by salinity levels. Samples for biological analyses were collected in the summer (June-September of 2007-2011 at eleven sampling sites. Statistical analysis revealed a significant correlation between salinity levels and the number of species (r= -0.2020, abundance (r= 0.1967 and biomass (r= 0.3139 of zooplankton. No significant correlations were found between salinity and the biodiversity of zooplankton. The results of the study suggest that salinity affects the abundance and structure, but not the diversity of zooplankton communities in the Vistula Lagoon.

Effect of Organic Fertilizers on Zooplankton Production | Orji ...

African Journals Online (AJOL)

Effect of Organic Fertilizers on Zooplankton Production. ... Journal of Agriculture and Food Sciences ... The aquaria were thoroughly washed, filled with 20litres of bore-hole water, fertilized with the respective organic manures after 4 days fermentation and inoculated with zooplankton samples collected from an earthen fish ...

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor; Valenzuela, Olga

2017-01-01

This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting.  It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of comput...

Changes in fecal pellet characteristics with depth as indicators of zooplankton repackaging of particles in the mesopelagic zone of the subtropical and subarctic North Pacific Ocean

Science.gov (United States)

Wilson, Stephanie E.; Steinberg, Deborah K.; Buesseler, Ken O.

2008-07-01

We investigated how fecal pellet characteristics change with depth in order to quantify the extent of particle repackaging by mesopelagic zooplankton in two contrasting open-ocean systems. Material from neutrally buoyant sediment traps deployed in the summer of 2004 and 2005 at 150, 300, and 500 m was analyzed from both a mesotrophic (Japanese time-series station K2) and an oligotrophic (Hawaii Ocean Time series—HOT station ALOHA) environment in the Pacific Ocean as part of the VERtical Transport In the Global Ocean (VERTIGO) project. We quantified changes in the flux, size, shape, and color of particles recognizable as zooplankton fecal pellets to determine how these parameters varied with depth and location. Flux of K2 fecal pellet particulate organic carbon (POC) at 150 and 300 m was four to five times higher than at ALOHA, and at all depths, fecal pellets were two to five times larger at K2, reflective of the disparate zooplankton community structure at the two sites. At K2, the proportion of POC flux that consisted of fecal pellets generally decreased with depth from 20% at 150 m to 5% at 500 m, whereas at ALOHA this proportion increased with depth (and was more variable) from 14% to 35%. This difference in the fecal fraction of POC with increasing depth is hypothesized to be due to differences in the extent of zooplankton-mediated fragmentation (coprohexy) and in zooplankton community structure between the two locations. Both regions provided indications of sinking particle repackaging and zooplankton carnivory in the mesopelagic. At ALOHA, this was reflected in a significant increase in the mean flux of larvacean fecal pellets from 150 to 500 m of 3-46 μg C m -2 d -1, respectively, and at K2 a large peak in larvacean mean pellet flux at 300 m of 3.1 mg C m -2 d -1. Peaks in red pellets produced by carnivores occurred at 300 m at K2, and a variety of other fecal pellet classes showed significant changes in their distribution with depth. There was also

Biomass relations between phytoplankton and zooplankton in Goa waters

Digital Repository Service at National Institute of Oceanography (India)

Pant, A.; Matondkar, S.G.P.; Goswami, S.C.

Biomass of phytoplankton and zooplankton, measured as particulate oxidizable carbon, shows that at shallowest stations (5 m) there is large excess of phytoplankton organic carbon over zooplankton carbon in all the samples There is no significant...

Annual variations in zooplankton from a polluted coastal environment

Digital Repository Service at National Institute of Oceanography (India)

Haridas, P.; Menon, P.G.; Madhupratap, M.

Seasonal changes in the composition and distribution of zooplankton from the coastal waters of Trivandrum were studied. The study indicated that the effluent discharged from a nearby titanium dioxide factory did not affect the zooplankton abundance...

Zooplankton composition and community structure in Lake Tiga ...

African Journals Online (AJOL)

Zooplankton in Lake Tiga was identified and its community structure assessed between March 2009 and March 2011. A total of 54 species of zooplankton was recorded, comprising two species of Protozoa, 26 species of Rotifera, eight species of Copepoda, 11 species of Cladocera, four species of Ostracoda and three ...

Zooplankton variability in polluted and unpolluted waters off Bombay

Digital Repository Service at National Institute of Oceanography (India)

Gajbhiye, S.N.; Desai, B.N.

Zooplankton abundance in the waters around Bombay was studied at Versova, Bombay Harbour (less polluted), Mahim and Thana (highly polluted) from October 1977 to December 1978. A rich zooplankton population was observed throughout the period of study...

From Networks to Time Series

Science.gov (United States)

Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi

2012-10-01

In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.

High frequency mesozooplankton monitoring: Can imaging systems and automated sample analysis help us describe and interpret changes in zooplankton community composition and size structure — An example from a coastal site

Science.gov (United States)

Romagnan, Jean Baptiste; Aldamman, Lama; Gasparini, Stéphane; Nival, Paul; Aubert, Anaïs; Jamet, Jean Louis; Stemmann, Lars

2016-10-01

The present work aims to show that high throughput imaging systems can be useful to estimate mesozooplankton community size and taxonomic descriptors that can be the base for consistent large scale monitoring of plankton communities. Such monitoring is required by the European Marine Strategy Framework Directive (MSFD) in order to ensure the Good Environmental Status (GES) of European coastal and offshore marine ecosystems. Time and cost-effective, automatic, techniques are of high interest in this context. An imaging-based protocol has been applied to a high frequency time series (every second day between April 2003 to April 2004 on average) of zooplankton obtained in a coastal site of the NW Mediterranean Sea, Villefranche Bay. One hundred eighty four mesozooplankton net collected samples were analysed with a Zooscan and an associated semi-automatic classification technique. The constitution of a learning set designed to maximize copepod identification with more than 10,000 objects enabled the automatic sorting of copepods with an accuracy of 91% (true positives) and a contamination of 14% (false positives). Twenty seven samples were then chosen from the total copepod time series for detailed visual sorting of copepods after automatic identification. This method enabled the description of the dynamics of two well-known copepod species, Centropages typicus and Temora stylifera, and 7 other taxonomically broader copepod groups, in terms of size, biovolume and abundance-size distributions (size spectra). Also, total copepod size spectra underwent significant changes during the sampling period. These changes could be partially related to changes in the copepod assemblage taxonomic composition and size distributions. This study shows that the use of high throughput imaging systems is of great interest to extract relevant coarse (i.e. total abundance, size structure) and detailed (i.e. selected species dynamics) descriptors of zooplankton dynamics. Innovative

Effects of UV-B irradiated algae on zooplankton grazing

NARCIS (Netherlands)

Lange, de H.J.; Lürling, M.F.L.L.W.

2003-01-01

We tested the effects of UV-B stressed algae on grazing rates of zooplankton. Four algal species ( Chlamydomonas reinhardtii, Cryptomonas sp., Scenedesmus obliquus and Microcystis aeruginosa) were used as food and fed to three zooplankton species ( Daphnia galeata, Bosmina longirostris and

Carbon export by vertically migrating zooplankton

DEFF Research Database (Denmark)

Hansen, Agnethe Nøhr; Visser, André W.

2016-01-01

Through diel vertical migration (DVM), zooplankton add an active transport to the otherwise passive sinking of detrital material that constitutes the biological pump. This active transport has proven difficult to quantify. We present a model that estimates both the temporal and depth characterist...... is transported than at either equatorial or boreal latitudes. We estimate that the amount of carbon transported below the mixed layer by migrating zooplankton in the North Atlantic Ocean constitutes 27% (16–30%) of the total export flux associated with the biological pump in that region...

Net-zooplankton abundance and biomass from Annaba Bay (SW Mediterranean Sea under estuarine influences

Directory of Open Access Journals (Sweden)

M. OUNISSI

2016-07-01

Full Text Available Zooplankton samples were collected in Annaba Bay (Algeria from January 2009-March 2011 at three coastal sites differently affected by estuarine plumes and external currents. Aim of this survey was to analyze zooplankton composition, abundance and biomass and compare the results with previous studies to reveal possible populations and environmental changes. The mean zooplankton abundance varied between 1,200-6,000 ind. m-3 and biomass 6.70-25.70 mg DW m-3, according to the site. Copepods constituted the main fraction of zooplankton community, and Oithona similis and Paracalanus indicus successively dominated during autumn-winter and spring-summer. The dinoflagellate Noctiluca scintillans was one of the major zooplankton components, and developed high numbers during February-April, becoming common in neritic and coastal regions. The singularity of the zooplankton from Annaba Bay is the prevalence of P. indicus throughout the entire bay and the decrease in Acartia discaudata and A. clausi (with respect to previous years, possibly replaced by A. negligens. Additionally, Oithona nana abundance markedly decreased with the large development of O. similis. Annaba Bay also differs from other similar Mediterranean coastal areas by the large development of Centropages ponticus populations during the warm period. Among the identified copepod species, the alien species Pseudodiaptomus australiensis and P. arabicus are reported for the first time in the Mediterranean Sea. The occurrence of copepodid V stages of P. australiensis suggests that this species survives and reproduces in Annaba Bay, but so far without developing an abundant population.

Duality between Time Series and Networks

Science.gov (United States)

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

Monsoon regime in the Indian Ocean and zooplankton variability

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.

and the estuaries in order to show how the monsoon exerts its influence on zooplankton from different types of environment. In the open ocean, the semi-annually reversing system of currents exert profound influence on the shifting of zooplankton populations and its...

Long time series

DEFF Research Database (Denmark)

Hisdal, H.; Holmqvist, E.; Hyvärinen, V.

Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the......Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the...

A Course in Time Series Analysis

CERN Document Server

Peña, Daniel; Tsay, Ruey S

2011-01-01

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a

Zooplankton structure and vertical migration: Using acoustics and biomass to compare stratified and mixed fjord systems

Science.gov (United States)

Díaz-Astudillo, Macarena; Cáceres, Mario A.; Landaeta, Mauricio F.

2017-09-01

The patterns of abundance, composition, biomass and vertical migration of zooplankton in short-time scales (ADCP device mounted on the hull of a ship were used to obtain vertical profiles of current velocity data and intensity of the backscattered acoustic signal, which was used to study the migratory strategies and to relate the echo intensity with zooplankton biomass. Repeated vertical profiles of temperature, salinity and density were obtained with a CTD instrument to describe the density patterns during both experiments. Zooplankton were sampled every 3 h using a Bongo net to determine abundance, composition and biomass. Migrations were diel in the stratified station, semi-diel in the mixed station, and controlled by light in both locations, with large and significant differences in zooplankton abundance and biomass between day and night samples. No migration pattern associated with the effect of tides was found. The depth of maximum backscatter strength showed differences of approximately 30 m between stations and was deeper in the mixed station. The relation between mean volume backscattering strength (dB) computed from echo intensity and log10 of total dry weight (mg m-3) of zooplankton biomass was moderate but significant in both locations. Biomass estimated from biological samples was higher in the mixed station and determined by euphausiids. Copepods were the most abundant group in both stations. Acoustic methods were a useful technique to understand the detailed patterns of migratory strategies of zooplankton and to help estimate zooplankton biomass and abundance in the inner waters of southern Chile.

FORMATION OF BACTERIAL AND ZOOPLANKTON COMPONENT OF NATURAL FOOD BASE UNDER EFFECT OF TRADITIONAL ORGANIC FERTILIZERS

Directory of Open Access Journals (Sweden)

S. Krazhan

2013-12-01

Full Text Available Purpose. Characterization of bacteria and zooplankton in rearing ponds using traditional fertilizers: cattle manure and bird droppings in modern conditions for fish farming. Methodology. Material collection and processing were carried out according to conventional hydrochemical and hydrobiological methods. Findings. We consider forming of bacteria and zooplankton component of natural food base of Irkliiv herbivorous fish nursery rearing ponds under the influenced of traditional organic fertilizers such as bird droppings (0,12 t/ha and cattle manure (2,0 t/ha. Each pond was planted by ongrowing Nyvka carp larvae (40,0 thousand ind./ha with silver carp (1,0 thousand ind./ha and grass carp larvae (1,0 thousand ind./ha. Qualitative and quantitative development of bacteria and zooplankton in fish-breeding ponds was investigated. The results show that in the development of the studied invertebrate groups of zooplankton in production ponds had no significant differences, except for rotifers, which group prevailed by the biomass to 3,6 times in the pond with the introduction of humus. Originality. The parameters of bacteria and zooplankton by the application of traditional organic fertilizers at present fish farming are studied. Practical value. These quantitative indicators of bacteria and zooplankton of fish-rearing ponds with water supply from Kremenchug reservoir, the application of cattle manure and bird droppings could be offered as an optimum data at present fish production stage.

Increased zooplankton PAH concentrations across hydrographic fronts in the East China Sea.

Science.gov (United States)

Hung, Chin-Chang; Ko, Fung-Chi; Gong, Gwo-Ching; Chen, Kuo-Shu; Wu, Jian-Ming; Chiang, Hsin-Lun; Peng, Sen-Chueh; Santschi, Peter H

2014-06-15

The Changjiang has transported large quantities of polycyclic aromatic hydrocarbons (PAHs) to the East China Sea (ECS), but information of these pollutants in zooplankton is limited. To understand PAHs pollution in zooplankton in the ECS, total concentrations of PAHs in zooplankton from surface waters were measured. Values of PAHs ranged from 2 to 3500 ng m(-3) in the ECS, with highest PAHs levels located at the salinity front between the Changjiang Diluted Water (CDW) and the mid-shelf waters. In contrast, concentrations of zooplankton PAHs in the mid-shelf and outer-shelf waters were significantly lower (2-23 ng m(-3)) than those in the CDW. These results demonstrate that PAHs are conspicuously accumulated in zooplankton at the salinity front between the CDW and the mid-shelf waters. These higher levels of PAHs in zooplankton at the salinity front may be further biomagnified in marine organisms of higher trophic levels through their feeding activities. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Kolmogorov Space in Time Series Data

OpenAIRE

Kanjamapornkul, K.; Pinčák, R.

2016-01-01

We provide the proof that the space of time series data is a Kolmogorov space with $T_{0}$-separation axiom using the loop space of time series data. In our approach we define a cyclic coordinate of intrinsic time scale of time series data after empirical mode decomposition. A spinor field of time series data comes from the rotation of data around price and time axis by defining a new extradimension to time series data. We show that there exist hidden eight dimensions in Kolmogorov space for ...

Eclipse effects on field crops and marine zooplankton: the 29 March 2006 total solar eclipse

Science.gov (United States)

Economou, G.; Christou, E. D.; Giannakourou, A.; Gerasopoulos, E.; Georgopoulos, D.; Kotoulas, V.; Lyra, D.; Tsakalis, N.; Tzortziou, M.; Vahamidis, P.; Papathanassiou, E.; Karamanos, A.

2008-08-01

Some effects in the biosphere from the Total Solar Eclipse of 29 March 2006 were investigated in field crops and marine zooplankton. Taking into account the decisive role of light on plant life and productivity, measurements of photosynthesis and stomatal behaviour were conducted on seven important field-grown cereal and leguminous crops. A drop in photosynthetic rates, by more than a factor of 5 in some cases, was observed, and the minimum values of photosynthetic rates ranged between 3.13 and 10.13 μmol CO2 m-2 s-1. The drop in solar irradiance and the increase in mesophyll CO2-concentration during the eclipse did not induce stomatal closure thus not blocking CO2 uptake by plants. Light effects on the photochemical phase of photosynthesis may be responsible for the observed depression in photosynthetic rates. Field studies addressing the migratory responses of marine zooplankton (micro-zooplankton (ciliates), and meso-zooplankton) due to the rapid changes in underwater light intensity were also performed. The light intensity attenuation was simulated with the use of accurate underwater radiative transfer modeling techniques. Ciliates, responded to the rapid decrease in light intensity during the eclipse adopting night-time behaviour. From the meso-zooplankton assemblage, various vertical migratory behaviours were adopted by different species.

On the Use of Running Trends as Summary Statistics for Univariate Time Series and Time Series Association

OpenAIRE

Trottini, Mario; Vigo, Isabel; Belda, Santiago

2015-01-01

Given a time series, running trends analysis (RTA) involves evaluating least squares trends over overlapping time windows of L consecutive time points, with overlap by all but one observation. This produces a new series called the “running trends series,” which is used as summary statistics of the original series for further analysis. In recent years, RTA has been widely used in climate applied research as summary statistics for time series and time series association. There is no doubt that ...

Multiple Indicator Stationary Time Series Models.

Science.gov (United States)

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

Some crustacean zooplankton of Wular lake in Kashmir Himalaya ...

African Journals Online (AJOL)

In a taxonomic survey of crustacean zooplankton collected from Wular lake of Kashmir, a pictorial key was developed. Thirty-six (36) pictures of 25 species of crustacean zooplankton, out of which 21 represented 16 Cladocera taxa belonging to Chydoridae (Alona affinis, A. rectangula and A. monacantha, Chydorus ...

Zooplankton responses to sandbar opening in a tropical eutrophic coastal lagoon

Science.gov (United States)

Santangelo, Jayme M.; de M. Rocha, Adriana; Bozelli, Reinaldo L.; Carneiro, Luciana S.; de A. Esteves, Francisco

2007-02-01

The effects of a disturbance by sandbar opening on the zooplankton community were evaluated through a long-term study in an eutrophic and oligohaline system, Imboassica Lagoon, Rio de Janeiro, Brazil. Zooplankton samples and limnological data were collected monthly from March 2000 to February 2003. Before the sandbar was opened in February 2001, the lagoon showed eutrophic conditions, with high mean nutrient concentrations and low salinity (total nitrogen - TN = 190.28 μM, chlorophyll a content - Chl. a = 104.60 μg/L and salinity = 0.87'). During this period, the zooplankton species present, such as the rotifers Brachionus calyciflorus and Brachionus havanaensis, were typical of freshwater to oligohaline and eutrophic environments. After the sandbar opening, the lagoon changed to a lower trophic status and increased salinity (TN = 55.11 μM, Chl. a = 27.56 μg/L and salinity = 19.64'). As a result, the zooplankton community came to consist largely of the rotifer Brachionus plicatilis, marine copepods and meroplanktonic larvae, mainly Gastropoda. Salinity was the main force structuring the zooplankton community after the sandbar opening. Two years after this episode, the prior zooplankton community had not reestablished itself, indicating a low resilience to this disturbance. The conditions developed prior to a sandbar opening can be crucial to the community responses in the face of this disturbance and for the capacity of the original zooplankton community to re-establish itself.

Time Series Momentum

DEFF Research Database (Denmark)

Moskowitz, Tobias J.; Ooi, Yao Hua; Heje Pedersen, Lasse

2012-01-01

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial...... under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities...

International Work-Conference on Time Series

CERN Document Server

Pomares, Héctor

2016-01-01

This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

Can microcystins affect zooplankton structure community in tropical eutrophic reservoirs?

Directory of Open Access Journals (Sweden)

T. A. S. V. Paes

Full Text Available Abstract The aim of our study was to assess whether cyanotoxins (microcystins can affect the composition of the zooplankton community, leading to domination of microzooplankton forms (protozoans and rotifers. Temporal variations in concentrations of microcystins and zooplankton biomass were analyzed in three eutrophic reservoirs in the semi-arid northeast region of Brazil. The concentration of microcystins in water proved to be correlated with the cyanobacterial biovolume, indicating the contributions from colonial forms such as Microcystis in the production of cyanotoxins. At the community level, the total biomass of zooplankton was not correlated with the concentration of microcystin (r2 = 0.00; P > 0.001, but in a population-level analysis, the biomass of rotifers and cladocerans showed a weak positive correlation. Cyclopoid copepods, which are considered to be relatively inefficient in ingesting cyanobacteria, were negatively correlated (r2 = – 0.01; P > 0.01 with the concentration of cyanotoxins. Surprisingly, the biomass of calanoid copepods was positively correlated with the microcystin concentration (r2 = 0.44; P > 0.001. The results indicate that allelopathic control mechanisms (negative effects of microcystin on zooplankton biomass do not seem to substantially affect the composition of mesozooplankton, which showed a constant and high biomass compared to the microzooplankton (rotifers. These results may be important to better understand the trophic interactions between zooplankton and cyanobacteria and the potential effects of allelopathic compounds on zooplankton.

Pilot Study on Potential Impacts of Fisheries-Induced Changes in Zooplankton Mortality on Marine Biogeochemistry

Science.gov (United States)

Getzlaff, Julia; Oschlies, Andreas

2017-11-01

In this pilot study we link the yield of industrial fisheries to changes in the zooplankton mortality in an idealized way accounting for different target species (planktivorous fish—decreased zooplankton mortality; large predators—increased zooplankton mortality). This indirect approach is used in a global coupled biogeochemistry circulation model to estimate the range of the potential impact of industrial fisheries on marine biogeochemistry. The simulated globally integrated response on phytoplankton and primary production is in line with expectations—a high (low) zooplankton mortality results in a decrease (increase) of zooplankton and an increase (decrease) of phytoplankton. In contrast, the local response of zooplankton and phytoplankton depends on the region under consideration: In nutrient-limited regions, an increase (decrease) in zooplankton mortality leads to a decrease (increase) in both zooplankton and phytoplankton biomass. In contrast, in nutrient-replete regions, such as upwelling regions, we find an opposing response: an increase (decrease) of the zooplankton mortality leads to an increase (decrease) in both zooplankton and phytoplankton biomass. The results are further evaluated by relating the potential fisheries-induced changes in zooplankton mortality to those driven by CO2 emissions in a business-as-usual 21st century emission scenario. In our idealized case, the potential fisheries-induced impact can be of similar size as warming-induced changes in marine biogeochemistry.

US AMLR Program zooplankton dataset

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Zooplankton research in the US AMLR Program focuses on the link between prey production, availability, and climate variability in relation to predator and fishery...

Numerical studies of the influence of food ingestion on phytoplankton and zooplankton biomasses

OpenAIRE

Lidia Dzierzbicka-G³owacka

2002-01-01

This paper presents the numerical simulations of the influence of food ingestion by a herbivorous copepod on phytoplankton and zooplankton biomasses (PZB) in the sea. The numerical studies were carried out using the phytoplankton-zooplankton-nutrient-detritus PhyZooNuDe biological upper layer model. This takes account both of fully developed primary production and regeneration mechanisms and of daily migration of zooplankton. In this model the zooplankton is treated not as a 'biomass' but as ...

Biochemical composition of Antarctic zooplankton from the Indian Ocean sector

Digital Repository Service at National Institute of Oceanography (India)

Ingole, B.S.; Parulekar, A.H.

Zooplankton samples were analysed for faunal composition, organic carbon, protein, carbohydrate and lipid content. Total zooplankton biomass (as displacement volume) varied from 0.032 to 0.500 ml.m sup(-3) (x = 0.23 + or - 0.14) in upper 200 m...

Stochastic models for time series

CERN Document Server

Doukhan, Paul

2018-01-01

This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...

The impact of fish predation and cyanobacteria on zooplankton size structure in 96 subtropical lakes.

Directory of Open Access Journals (Sweden)

Jing Zhang

Full Text Available Zooplankton are relatively small in size in the subtropical regions. This characteristic has been attributed to intense predation pressure, high nutrient loading and cyanobacterial biomass. To provide further information on the effect of predation and cyanobacteria on zooplankton size structure, we analyzed data from 96 shallow aquaculture lakes along the Yangtze River. Contrary to former studies, both principal components analysis and multiple regression analysis showed that the mean zooplankton size was positively related to fish yield. The studied lakes were grouped into three types, namely, natural fishing lakes with low nutrient loading (Type1, planktivorous fish-dominated lakes (Type 2, and eutrophic lakes with high cyanobacterial biomass (Type 3. A marked difference in zooplankton size structure was found among these groups. The greatest mean zooplankton size was observed in Type 2 lakes, but zooplankton density was the lowest. Zooplankton abundance was highest in Type 3 lakes and increased with increasing cyanobacterial biomass. Zooplankton mean size was negatively correlated with cyanobacterial biomass. No obvious trends were found in Type 1 lakes. These results were reflected by the normalized biomass size spectrum, which showed a unimodal shape with a peak at medium sizes in Type 2 lakes and a peak at small sizes in Type 3 lakes. These results indicated a relative increase in medium-sized and small-sized species in Types 2 and 3 lakes, respectively. Our results suggested that fish predation might have a negative effect on zooplankton abundance but a positive effect on zooplankton size structure. High cyanobacterial biomass most likely caused a decline in the zooplankton size and encouraged the proliferation of small zooplankton. We suggest that both planktivorous fish and cyanobacteria have substantial effects on the shaping of zooplankton community, particularly in the lakes in the eastern plain along the Yangtze River where

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

Science.gov (United States)

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Eclipse effects on field crops and marine zooplankton: the 29 March 2006 total solar eclipse

Directory of Open Access Journals (Sweden)

G. Economou

2008-08-01

Full Text Available Some effects in the biosphere from the Total Solar Eclipse of 29 March 2006 were investigated in field crops and marine zooplankton. Taking into account the decisive role of light on plant life and productivity, measurements of photosynthesis and stomatal behaviour were conducted on seven important field-grown cereal and leguminous crops. A drop in photosynthetic rates, by more than a factor of 5 in some cases, was observed, and the minimum values of photosynthetic rates ranged between 3.13 and 10.13 μmol CO₂ m⁻² s⁻¹. The drop in solar irradiance and the increase in mesophyll CO₂-concentration during the eclipse did not induce stomatal closure thus not blocking CO₂ uptake by plants. Light effects on the photochemical phase of photosynthesis may be responsible for the observed depression in photosynthetic rates. Field studies addressing the migratory responses of marine zooplankton (micro-zooplankton (ciliates, and meso-zooplankton due to the rapid changes in underwater light intensity were also performed. The light intensity attenuation was simulated with the use of accurate underwater radiative transfer modeling techniques. Ciliates, responded to the rapid decrease in light intensity during the eclipse adopting night-time behaviour. From the meso-zooplankton assemblage, various vertical migratory behaviours were adopted by different species.

Seasonal succession in zooplankton feeding traits reveals trophic trait coupling

DEFF Research Database (Denmark)

Kenitz, Kasia; Visser, Andre; Mariani, Patrizio

2017-01-01

non-motile cells flourishing in spring and motile community dominating during summer. The zooplankton community is dominated by active feeding-current feeders with peak biomass in the late spring declining during summer. The model reveals how zooplankton grazing reinforces protist plankton seasonal...

Time Series with Long Memory

OpenAIRE

西埜, 晴久

2004-01-01

The paper investigates an application of long-memory processes to economic time series. We show properties of long-memory processes, which are motivated to model a long-memory phenomenon in economic time series. An FARIMA model is described as an example of long-memory model in statistical terms. The paper explains basic limit theorems and estimation methods for long-memory processes in order to apply long-memory models to economic time series.

Selective uptake of 55Fe from seawater by zooplankton

International Nuclear Information System (INIS)

Jennings, C.D.

1978-01-01

Iron-55 was measured in water and mixed zooplankton collected in the South Pacific Ocean. The ratios of the specific activity of 55 Fe (pCi/g Fe) between plankton and water from the same locations appear to be about 100, which suggests that zooplankton took up 55 Fe in preference to stable iron in the South Pacific Ocean

A new modelling approach for zooplankton behaviour

Science.gov (United States)

Keiyu, A. Y.; Yamazaki, H.; Strickler, J. R.

We have developed a new simulation technique to model zooplankton behaviour. The approach utilizes neither the conventional artificial intelligence nor neural network methods. We have designed an adaptive behaviour network, which is similar to BEER [(1990) Intelligence as an adaptive behaviour: an experiment in computational neuroethology, Academic Press], based on observational studies of zooplankton behaviour. The proposed method is compared with non- "intelligent" models—random walk and correlated walk models—as well as observed behaviour in a laboratory tank. Although the network is simple, the model exhibits rich behavioural patterns similar to live copepods.

Visibility Graph Based Time Series Analysis.

Science.gov (United States)

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Visibility Graph Based Time Series Analysis.

Directory of Open Access Journals (Sweden)

Mutua Stephen

Full Text Available Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Procedures Involved in Radioecological Studies with Marine Zooplankton

International Nuclear Information System (INIS)

Fowler, S.W.; Small, L.F.

1976-01-01

Various procedures in marine radio ecological experiments with zooplankton are considered in the light of the possibility of establishing reference methods for marine radiobiological studies. Methods for collection, handling and maintenance prior to and during experiments are suggested for various types of zooplankton. The importance of physiological and physicochemical parameters are discussed in the context of the experimental design with the aim of achieving comparable results among workers involved in this field of research. (author)

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

Science.gov (United States)

Vasseur, David A; Fox, Jeremy W; Gonzalez, Andrew; Adrian, Rita; Beisner, Beatrix E; Helmus, Matthew R; Johnson, Catherine; Kratina, Pavel; Kremer, Colin; de Mazancourt, Claire; Miller, Elizabeth; Nelson, William A; Paterson, Michael; Rusak, James A; Shurin, Jonathan B; Steiner, Christopher F

2014-08-07

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Zooplankton community response to experimental acidification in boreal shield lakes with different ecological histories

Energy Technology Data Exchange (ETDEWEB)

Derry, A.M.; Arnott, S.E. [Queen' s Univ., Kingston, ON (Canada). Dept. of Biology

2007-06-15

This study investigated the adaptive response of crustacean zooplankton to widespread regional acidification at the Killarney Provincial Park in Ontario. Mesocosm experiments were conducted in 2 circumneutral lakes with different acidification histories. A reciprocal transplant field enclosure experiment was conducted to assess whether the zooplankton community within the acid-recovering boreal shield lake showed evidence of increased acid tolerance to historical acidification following a 6 year period in which the lake's pH was 6.0. The enclosures were filled with epilimnetic water from the lake. Zooplankton from other lakes in the area were used. Zooplankton and water samples were collected from the enclosures once a week. Shannon-Wiener indices, species richness, and total abundance of the zooplankton were calculated for each sample day. Repeated measures analyses of variance (RM-ANOVAs) were used to test for the effects of the incubation lake, the zooplankton source, and the pH. Species abundance data were log{sub 10} transformed to improve homogeneity of variances and normality. Principle components analysis was conducted on species abundances to infer the influence of treatments on zooplankton community composition. Zooplankton were also transferred from 1 lake to the other in order to determine if subtle differences in local water chemistry and food conditions were limiting the recovery of species in acid-recovering lakes. The study showed that 2 key species, H. gibberum and L. minutus, contributed to community-level differences to acid tolerance of zooplankton with different acidification histories. It was concluded that zooplankton with adaptable acid tolerances may monopolize resources in acidified and acid-recovering lakes, and may contribute to the delayed recolonization of other taxa. 62 refs., 3 tabs., 6 figs.

Structure, seasonal dynamics and distribution of zooplankton in lake Drukshiai in 1994

International Nuclear Information System (INIS)

Mazheikaite, S.; Pashkauskas, R.

1995-01-01

Investigations on the zooplankton of Lake Drukshiai were carried out in 1994. There were registered 62 taxons of protozoa and 50 taxons of metazoa, and compared with the data of 1979 - 1986 the diversity of species composition decreased 2.1 times. Eurytermic and stenothermic thermophylic species prevailed in the plankton biocenosis. In protozooplankton dominated ciliates of subclasses teolotricha and spirotricha, in metazooplankton -planctonic crustacea (Copopeda and Cladocera). Rotifers (Rotaria) were abundant only in the shallow and heated water outlet area. Seasonal dynamics of protozooplankton indicated one maximum in spring and metazooplankton - in summer. High diferentiation in quantity and biomass of zooplankton in the lake revealed different level of eutrophication of some areas. (author). 7 refs., 5 figs

Zooplankton Hydrodynamics

DEFF Research Database (Denmark)

Wadhwa, Navish

flow disturbances that may attract predators. The first part of this thesis attempts to quantify the trade-offs associated with the swimming behaviour of diverse zooplankton. We measured the swimming kinematics and flow fields around the 'jumping' copepod Acartia tonsa at various stages of its life....... We studied how sensing modes and their respective ranges depend on body size. We investigated the physiological constraints on sense organs, together with the physics of signal generation, transmission, and reception. Our analysis revealed a hierarchy of sensing modes - with increasing size, a larger...

Potential acidification impacts on zooplankton in CCS leakage scenarios.

Science.gov (United States)

Halsband, Claudia; Kurihara, Haruko

2013-08-30

Carbon capture and storage (CCS) technologies involve localized acidification of significant volumes of seawater, inhabited mainly by planktonic species. Knowledge on potential impacts of these techniques on the survival and physiology of zooplankton, and subsequent consequences for ecosystem health in targeted areas, is scarce. The recent literature has a focus on anthropogenic greenhouse gas emissions into the atmosphere, leading to enhanced absorption of CO2 by the oceans and a lowered seawater pH, termed ocean acidification. These studies explore the effects of changes in seawater chemistry, as predicted by climate models for the end of this century, on marine biota. Early studies have used unrealistically severe CO2/pH values in this context, but are relevant for CCS leakage scenarios. Little studied meso- and bathypelagic species of the deep sea may be especially vulnerable, as well as vertically migrating zooplankton, which require significant residence times at great depths as part of their life cycle. Copyright © 2013 Elsevier Ltd. All rights reserved.

A study on the zooplankton of the Burhabalanga Estuary, Orissa Coast

Digital Repository Service at National Institute of Oceanography (India)

Ramaiah, Neelam; Chatterji, A.; Madhupratap, M.

Annual variations in the zooplankton biomass and composition during 1991-92 were studied from the inshore, mouth and upstream regions of the Burhabalanga Estuary located in the Orissa Coast (India). Zooplankton biomass was maximum at all...

Zooplankton as a compound mineralising and synthesizing system: Phosphorus excretion

NARCIS (Netherlands)

Gulati, R.D.; Martinez, C.P.; Siewertsen, K.

1995-01-01

Data on phosphate excretion rates of zooplankton are based on measurements using the pelagic crustacean zoo-plankton of Lake Vechten and laboratory-cultured Daphnia galeata. In case of Daphnia sp we measured the effects of feeding on P-rich algae and P-poor algae (Scenedesmus) as food on the

Using occupancy modeling to compare traditional versus DNA metabarcoding methods for characterizing zooplankton biodiversity

Science.gov (United States)

DNA metabarcoding tools could increase our ability to detect changes in zooplankton communities and to detect invasive zooplankton taxa while they are still rare. Nonetheless, the use of DNA-metabarcoding for characterizing zooplankton biodiversity in the Great Lakes has not bee...

Network structure of multivariate time series.

Science.gov (United States)

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

What marketing scholars should know about time series analysis : time series applications in marketing

NARCIS (Netherlands)

Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

2002-01-01

In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing

ZOOPLANKTON FAUNA OF BİNGÖL FLOATING ISLANDS IN WINTER SEASON

OpenAIRE

Şen Özdemir, Nurgül; Caf, Fatma

2015-01-01

In this study was carried out winter season in 2011; zooplankton faunaof the Bingol Floating Islands. To­tally 18 zooplankton species were determinedas fol­lows; 14 Rotifera, 3 Cladocera and 1 Copepoda. It was determined thatthis zooplanktonic organisms consist­ed of 87.74 % Rotifera, 6.83 % Cladocera, and3.36 %  copepodit stages, 2.07 %  nauplii of copepoda. Rotif­era were thedominant group with regard to both spe­cies numbers, and individual numbers ofspecies. Cy­clops vicinus from Copepoda...

Predictive models for monitoring and analysis of the total zooplankton

Directory of Open Access Journals (Sweden)

Obradović Milica

2014-01-01

Full Text Available In recent years, modeling and prediction of total zooplankton abundance have been performed by various tools and techniques, among which data mining tools have been less frequent. The purpose of this paper is to automatically determine the dependency degree and the influence of physical, chemical and biological parameters on the total zooplankton abundance, through design of the specific data mining models. For this purpose, the analysis of key influencers was used. The analysis is based on the data obtained from the SeLaR information system - specifically, the data from the two reservoirs (Gruža and Grošnica with different morphometric characteristics and trophic state. The data is transformed into optimal structure for data analysis, upon which, data mining model based on the Naïve Bayes algorithm is constructed. The results of the analysis imply that in both reservoirs, parameters of groups and species of zooplankton have the greatest influence on the total zooplankton abundance. If these inputs (group and zooplankton species are left out, differences in the impact of physical, chemical and other biological parameters in dependences of reservoirs can be noted. In the Grošnica reservoir, analysis showed that the temporal dimension (months, nitrates, water temperature, chemical oxygen demand, chlorophyll and chlorides, had the key influence with strong relative impact. In the Gruža reservoir, key influence parameters for total zooplankton are: spatial dimension (location, water temperature and physiological groups of bacteria. The results show that the presented data mining model is usable on any kind of aquatic ecosystem and can also serve for the detection of inputs which could be the basis for the future analysis and modeling.

Nutrient regeneration by zooplankton during a red tide off Peru, with notes on biomass and species composition of zooplankton

Energy Technology Data Exchange (ETDEWEB)

Smith, S.L.

1978-01-01

During March and April 1976, a red tide, dominated by the dinoflagallate Gymnodinium splendens Lebour, developed in the vicinity of 15/sup 0/O6'S and 76/sup 0/31'W off Peru. At the height of the bloom, the euphotic zone was 6 m deep and the chlorophyll a at the surface was 48 ..mu..g 1/sup -1/. A daily collection of zooplankton at 09.00 hrs showed large fluctuations of biomass, from 0.2 to 3.84 g dry weight m/sup -2/ in a water column of 120 m. Copepodids and nauplii dominated the collections. During a period of reduced wind, the adult copepods were a mixture of the species characteristic of the coastal upwelling system and the neritic species associated with more northerly, tropical waters. Nitrogen regeneration by the zooplankton varied with the development of the bloom, the type of zooplankton dominating the experiment, and biomass fluctuations, but never accounted for more than 25% of the nitrogen uptake by phytoplankton.

Data mining in time series databases

CERN Document Server

Kandel, Abraham; Bunke, Horst

2004-01-01

Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.

Models for dependent time series

CERN Document Server

Tunnicliffe Wilson, Granville; Haywood, John

2015-01-01

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater

Overview of the US JGOFS Bermuda Atlantic Time-series Study (BATS): a decade-scale look at ocean biology and biogeochemistry

Science.gov (United States)

Steinberg, Deborah K.; Carlson, Craig A.; Bates, Nicholas R.; Johnson, Rodney J.; Michaels, Anthony F.; Knap, Anthony H.

The Bermuda Atlantic Time-series Study (BATS) commenced monthly sampling in October 1988 as part of the US Joint Global Ocean Flux Study (JGOFS) program. The goals of the US JGOFS time-series research are to better understand the basic processes that control ocean biogeochemistry on seasonal to decadal time-scales, determine the role of the oceans in the global carbon budget, and ultimately improve our ability to predict the effects of climate change on ecosystems. The BATS program samples the ocean on a biweekly to monthly basis, a strategy that resolves major seasonal patterns and interannual variability. The core cruises last 4-5 d during which hydrography, nutrients, particle flux, pigments and primary production, bacterioplankton abundance and production, and often complementary ancillary measurements are made. This overview focuses on patterns in ocean biology and biogeochemistry over a decade at the BATS site, concentrating on seasonal and interannual changes in community structure, and the physical forcing and other factors controlling the temporal dynamics. Significant seasonal and interannual variability in phytoplankton and bacterioplankton production, biomass, and community structure exists at BATS. No strong relationship exists between primary production and particle flux during the 10 yr record, with the relationship slightly improved by applying an artificial lag of 1 week between production and flux. The prokaryotic picoplankton regularly dominate the phytoplankton community; diatom blooms are rare but occur periodically in the BATS time series. The increase in Chl a concentrations during bloom periods is due to increases by most of the taxa present, rather than by any single group, and there is seasonal succession of phytoplankton. The bacterioplankton often dominate the living biomass, indicating the potential to consume large amounts of carbon and play a major ecological role within the microbial food web. Bacterial biomass, production, and

Visual time series analysis

DEFF Research Database (Denmark)

Fischer, Paul; Hilbert, Astrid

2012-01-01

We introduce a platform which supplies an easy-to-handle, interactive, extendable, and fast analysis tool for time series analysis. In contrast to other software suits like Maple, Matlab, or R, which use a command-line-like interface and where the user has to memorize/look-up the appropriate...... commands, our application is select-and-click-driven. It allows to derive many different sequences of deviations for a given time series and to visualize them in different ways in order to judge their expressive power and to reuse the procedure found. For many transformations or model-ts, the user may...... choose between manual and automated parameter selection. The user can dene new transformations and add them to the system. The application contains efficient implementations of advanced and recent techniques for time series analysis including techniques related to extreme value analysis and filtering...

Zooplankton assemblages and biomass during a 4-period survey in a northern Mediterranean coastal lagoon.

Science.gov (United States)

Lam-Hoai, T; Rougier, C

2001-01-01

The authors proposed to examine zooplankton biomass at three stations inside (T and Z) and outside (M) a coastal lagoon of the north-western Mediterranean Sea. Station T represented the lagoon central area, and station Z was positioned in a shellfish farming sector, while the seaside station (M) served as a reference of marine environment. Analyses were designed to outline the net zooplankton assemblages (taxonomic structures and length distributions) in different environmental conditions, including the farming activity. A discriminant analysis of environmental variables determined that temperature, salinity and phytoplankton implied mainly in spatial pattern of the samples. An ordination of taxa biomasses showed two main factors which might contribute to the organisation of the zooplankton assemblages: the geographical position and the thermal period. The geographical position integrated the lagoon-sea water exchange under forcing parameters (habitat, tides and winds). The thermal period reflected both the populations development cycles and the environmental constraints (temperature, salinity, trophic resources). The resulting effects appeared in structured zooplankton assemblages in space and time. The number of 50 microns interval length classes and of taxa decreased from the seaside and the lagoon central area free of farming activity to the shallower farming zone. But the biomass-length distribution profiles did not closely follow such an expected opposition between opened and confined areas: more extended profiles were observed at station Z. Biomass dominant size classes concerned the range up to 300 microns. This size category appeared to collapse in terms of biomass from the seaside or central area of the lagoon towards the farming area, similarly to zooplankton global biomass fluctuations. Difference between biomass levels and between biomass structures suggested that net zooplankton partly acted as food competitors of macro-filtering organisms, and as

A Review of Subsequence Time Series Clustering

Directory of Open Access Journals (Sweden)

Seyedjamal Zolhavarieh

2014-01-01

Full Text Available Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

A review of subsequence time series clustering.

Science.gov (United States)

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

A Review of Subsequence Time Series Clustering

Science.gov (United States)

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

Studies on zooplankton from the Arabian sea off the south-central west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Sumitra-Vijayaraghavan; Selvakumar, R.A.; Rao, T.S.S.

Zooplankton biomass, composition and biochemical constituents were studied. Estimated average zooplankton biomass was 8.76 ml/100 m super(3). Of the major components constituting the zooplankton biomass, copepods formed the dominant group. Protein...

Analysis of Heavy-Tailed Time Series

DEFF Research Database (Denmark)

Xie, Xiaolei

This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...

Analysis of southeast Australian zooplankton observations of 1938-42 using synoptic oceanographic conditions

Science.gov (United States)

Baird, Mark E.; Everett, Jason D.; Suthers, Iain M.

2011-03-01

The research vessel Warreen obtained 1742 planktonic samples along the continental shelf and slope of southeast Australia from 1938-42, representing the earliest spatially and temporally resolved zooplankton data from Australian marine waters. In this paper, Warreen observations along the southeast Australian seaboard from 28°S to 38°S are interpreted based on synoptic meteorological and oceanographic conditions and ocean climatologies. Meteorological conditions are based on the NOAA-CIRES 20th Century Reanalysis Project; oceanographic conditions use Warreen hydrological observations, and the ocean climatology is the CSIRO Atlas of Regional Seas. The Warreen observations were undertaken in waters on average 0.45 °C cooler than the climatological average, and included the longest duration El Niño of the 20th century. In northern New South Wales (NSW), week time-scale events dominate zooplankton response. In August 1940 an unusual winter upwelling event occurred in northern NSW driven by a stronger than average East Australian Current (EAC) and anomalous northerly winds that resulted in high salp and larvacean abundance. In January 1941 a strong upwelling event between 28° and 33°S resulted in a filament of upwelled water being advected south and alongshore, which was low in zooplankton biovolume. In southern NSW a seasonal cycle in physical and planktonic characteristics is observed. In January 1941 the poleward extension of the EAC was strong, advecting more tropical tunicate species southward. Zooplankton abundance and distribution on the continental shelf and slope are more dependent on weekly to monthly timescales on local oceanographic and meteorological conditions than continental-scale interannual trends. The interpretation of historical zooplankton observations of the waters off southeast Australia for the purpose of quantifying anthropogenic impacts will be improved with the use of regional hindcasts of synoptic ocean and atmospheric weather that can

Adaptive time-variant models for fuzzy-time-series forecasting.

Science.gov (United States)

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

Time Series Analysis and Forecasting by Example

CERN Document Server

Bisgaard, Soren

2011-01-01

An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in

Time series with tailored nonlinearities

Science.gov (United States)

Räth, C.; Laut, I.

2015-10-01

It is demonstrated how to generate time series with tailored nonlinearities by inducing well-defined constraints on the Fourier phases. Correlations between the phase information of adjacent phases and (static and dynamic) measures of nonlinearities are established and their origin is explained. By applying a set of simple constraints on the phases of an originally linear and uncorrelated Gaussian time series, the observed scaling behavior of the intensity distribution of empirical time series can be reproduced. The power law character of the intensity distributions being typical for, e.g., turbulence and financial data can thus be explained in terms of phase correlations.

Recovery after local extinction: factors affecting re-establishment of alpine lake zooplankton.

Science.gov (United States)

Knapp, Roland A; Sarnelle, Orlando

2008-12-01

The introduction of fishes into naturally fishless mountain lakes often results in the extirpation of large-bodied zooplankton species. The ability to predict whether or not particular species will recover following fish removal is critically important for the design and implementation of lake restoration efforts but is currently not possible because of a lack of information on what factors affect recovery. The objective of this study was to identify the factors influencing recovery probability in two large-bodied zooplankton species following fish removal. We predicted that (1) Daphnia melanica would have a higher probability of recovery than Hesperodiaptomus shoshone due to differences in reproductive mode (D. melanica is parthenogenetic, H. shoshone is obligately sexual), (2) recovery probability would be a decreasing function of fish residence time due to the negative relationship between fish residence time and size of the egg bank, and (3) recovery probability would be an increasing function of lake depth as a consequence of a positive relationship between lake depth and egg bank size. To test these predictions, we sampled contemporary zooplankton populations and collected paleolimnological data from 44 naturally fishless lakes that were stocked with trout for varying lengths of time before reverting to a fishless condition. D. melanica had a significantly higher probability of recovery than did H. shoshone (0.82 vs. 0.54, respectively). The probability of recovery for H. shoshone was also significantly influenced by lake depth, fish residence time, and elevation, but only elevation influenced the probability of recovery in D. melanica. These results are consistent with between-species differences in reproductive mode combined with the much greater longevity of diapausing eggs in D. melanica than in H. shoshone. Our data also suggest that H. shoshone will often fail to recover in lakes with fish residence times exceeding 50 years.

Zooplankton assemblage of Oyun Reservoir, Offa, Nigeria

Directory of Open Access Journals (Sweden)

Moshood K Mustapha

2009-12-01

Full Text Available The influence of physico-chemical properties of Oyun Reservoir, Offa, Nigeria (a shallow tropical African reservoir on its zooplankton composition and abundance were investigated at three stations for two years between January 2002 and December 2003. Diversity is not high: only three groups of zooplankton were found: Rotifera with eight genera; and Cladocera and Copepoda with three genera each. Rotifera dominated numerically (71.02%, followed by Cladocera (16.45% and Copepoda (12.53%. The zooplankton was more prevalent during the rainy season, and there were variations in the composition and abundance along the reservoir continuum. Factors such as temperature, nutrients, food availability, shape and hydrodynamics of the reservoir, as well as reproductive strategies of the organisms, strongly influence the generic composition and population density of zooplankton. Prevention of ecological deterioration of the water body would greatly should result in a more productive water body, rich in zooplankton and with better fisheries. Rev. Biol. Trop. 57 (4: 1027-1047. Epub 2009 December 01.La influencia de las propiedades fisicoquímicas del Reservorio Oyun, Offa, Nigeria (un embalse tropical somero sobre la composición y abundancia del zooplancton fue investigada en tres estaciones entre enero de 2002 y diciembre de 2003. La diversidad no resultó muy alta con tres grupos de zooplancton: Rotifera con ocho géneros, y Cladocera y Copepoda con tres géneros cada uno. Rotifera dominó (71.02%, seguido de Cladocera (16.45% y Copepoda (12.53%. El zooplancton fue más común durante la temporada de lluvias, y hubo variaciones en su composición y abundancia a lo largo del embalse. Factores tales como la temperatura, los nutrientes, la disponibilidad de alimentos, la forma y la hidrodinámica del embalse, así como las estrategias reproductivas de los organismos, influyen fuertemente en la composición genérica y la densidad poblacional del zooplancton. La

Diurnal variation in zooplankton in the Zuari Estuary, west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Padmavati, G.; Goswami, S.C.; Vidya, P.S.

Variations in zooplankton biomass and population density in relation to the prevailing hydrographical conditions were studied in Zuari Estuary, Goa. The physico-chemical parameters showed limited variations. Zooplankton biomass was relatively more...

Temporal and spatial variability of zooplankton on the Faroe shelf in spring 1997-2016

Science.gov (United States)

Jacobsen, Sólvá; Gaard, Eilif; Larsen, Karin Margretha Húsgarð; Eliasen, Sólvá Káradóttir; Hátún, Hjálmar

2018-01-01

Zooplankton availability during spring and summer determines the growth and survival of first-feeding fish larvae, and thus impacts the recruitment to both fish prey species and commercial fish stocks. On the Faroe shelf, however, the relative importance of oceanic versus neritic zooplankton species has hitherto not been well understood. In this study, spatio-temporal variability in zooplankton community structure and size spectra on the Faroe shelf is investigated using observations from late April during the period 1997-2016. The main objective was to explore which environmental variables influence the zooplankton community structure in early spring. The zooplankton community in the permanently well mixed central shelf inside the tidal front consists of a mixture of neritic, cosmopolitan and oceanic species. In this region, redundancy analyses showed that chlorophyll concentration had a positive effect on abundance of neritic copepods and meroplankton as well as all zooplankton abundance variability of these species shows increased production around 2000 and 2008-2009. The highest zooplankton abundance, mainly consisting of Calanus finmarchicus, is however observed off-shore from the tidal front, especially on the western side of the Faroe Plateau. A shift in C. finmarchicus phenology occurred around 2007, resulting in earlier reproduction of this species, and this variability could not be explained by the employed regional environmental parameters. Our results indicate that the Faroe shelf biological production is more dependent on the local primary production and neritic zooplankton species than on the large oceanic C. finmarchicus stock.

Clustering of financial time series

Science.gov (United States)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

Zooplankton and ichthyoplankton distribution on the southern Brazilian shelf: an overview

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Rubens M. Lopes

2006-06-01

Full Text Available The southern Brazilian coast is the major fishery ground for the Brazilian sardine (Sardinella brasiliensis, a species responsible for up to 40% of marine fish catches in the region. Fish spawning and recruitment are locally influenced by seasonal advection of nutrient-rich waters from both inshore and offshore sources. Plankton communities are otherwise controlled by regenerative processes related to the oligotrophic nature of the Tropical Water from the Brazil Current. As recorded in other continental margins, zooplankton species diversity increases towards outer shelf and open ocean waters. Peaks of zooplankton biomass and ichthyoplankton abundance are frequent on the inner shelf, either at upwelling sites or off large estuarine systems. However, meandering features of the Brazil Current provide an additional mechanism of upward motion of the cold and nutrient-rich South Atlantic Central Water, increasing phyto- and zooplankton biomass and production on mid- and outer shelves. Cold neritic waters originating off Argentina, and subtropical waters from the Subtropical Convergence exert a strong seasonal influence on zooplankton and ichthyoplankton distribution towards more southern areas. This brief review highlights the need for further experimental studies on zooplankton life cycle strategies in order to understand the major processes controlling food web dynamics in this shelf ecosystem.

Article Review: Lessepsian migration of zooplankton through Suez Canal and its impact on ecological system

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Howaida Y. Zakaria

2015-01-01

Full Text Available The marine environment of the East Mediterranean has been considerably impacted in modern times by two man-made changes: the creation of a waterway between the Indo-Pacific and the Mediterranean basins and the control of the Nile fresh-water outflow. The opening of the Suez Canal caused a migration generally from the Red Sea to the Mediterranean, and rarely in the opposite direction as the Red Sea is generally saltier and more nutrient-poor than the Atlantic, so the Red Sea species have advantages over Atlantic species in the salty and nutrient-poor eastern Mediterranean. Accordingly Red Sea species invaded the Mediterranean ecosystem and not vice versa; this phenomenon is known as the Lessepsian migration or erythrean invasion. The composition of zooplankton in the eastern Mediterranean has been shown to include a large proportion of Indo-Pacific and other circumtropical species which have successfully settled and proliferated in this environment. During the present study, an overview is provided on zooplankton migration through Suez Canal and its impact on the ecological system based on published literature. It is also meant with the hydrographic and zooplankton characteristics of the adjacent seas. It is clear that, except jellyfish Rhopilema nomadica, the negative impact of zooplankton Lessepsian migratory species in the Egyptian Mediterranean waters is not evident. Finally, it would be concluded that, a continuous monitoring programme will be needed to record the recent erythrean zooplankton species and follow up the distribution and abundance of those previously recorded as aliens to assess their impacts on the native biodiversity of the Mediterranean.

Biomass and composition of zooplankton in and around Gulf of Kutch

Digital Repository Service at National Institute of Oceanography (India)

Govindan, K.; Kasinathan, R.; Desai, B.N.

Biomass and composition of zooplankton in the nearshore waters of Thal, Maharashtra, India were studied at 9 stations during Feb. 1980 to Jan. 1981. The recorded variation in zooplankton biomass was 4.8-80.6 ml.(100 m super(3))/1 [av. 22.9 ml.(100 m...

Zooplankton data collected from zooplankton net casts from RESEARCHER I and other platforms in TOGA Area of Pacific Ocean; 16 March 1968 to 02 July 1970 (NODC Accession 9500141)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Zooplankton species identities and other data were collected using zooplankton casts in the TOGA Area of Pacific Ocean from RESEARCHER I and other platforms. Data...

Data Mining Smart Energy Time Series

Directory of Open Access Journals (Sweden)

Janina POPEANGA

2015-07-01

Full Text Available With the advent of smart metering technology the amount of energy data will increase significantly and utilities industry will have to face another big challenge - to find relationships within time-series data and even more - to analyze such huge numbers of time series to find useful patterns and trends with fast or even real-time response. This study makes a small review of the literature in the field, trying to demonstrate how essential is the application of data mining techniques in the time series to make the best use of this large quantity of data, despite all the difficulties. Also, the most important Time Series Data Mining techniques are presented, highlighting their applicability in the energy domain.

Predicting chaotic time series

International Nuclear Information System (INIS)

Farmer, J.D.; Sidorowich, J.J.

1987-01-01

We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ''learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values. We present an error estimate for this technique, and demonstrate its effectiveness by applying it to several examples, including data from the Mackey-Glass delay differential equation, Rayleigh-Benard convection, and Taylor-Couette flow

Spatial variations in zooplankton diversity in waters contaminated with composite effluents

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Asitava CHATTERJEE

2007-08-01

Full Text Available Zooplankton species are cosmopolitan in their clean freshwater habitat and are also found in industrial and municipal wastewaters. The present study records for the first time the aspects of zooplankton diversity in relation to physico-chemical environment of five selected sites of the East Calcutta wetlands, a Ramsar site of Kolkata city, India, heavily contaminated by industrial and municipal wastewaters. The study revealed the occurrence of 22 species of zooplankton, among these 3 species of Cladocera, 2 species of Copepoda, 15 species of Rotifera, and 2 species of Ostracoda were recorded. The copepod Mesocyclops leuckarti was found in all the five sites, rotifers Asplanchna brightwelli, Brachionus angularis, B. calyciflorus and Cladocera Ceriodaphnia cornuta were found in four sites; Moina micrura and Diaphanosoma sarsi were found at three sites. Site wise variation in dominance, diversity, evenness and richness were calculated. Site 1, a fish-pond that stabilized composite wastewater, showed the maximum species richness having 17 species, while Site 2, SWF wastewater carrying canal, showed only 4 species. The calculated Jack 1 values of Sites 1 to 5 were 21.78, 3.77, 18.63, 12.5 and 16.95 respectively. Shannon-Wiener species diversity index (H/ values were almost similar for all the three relatively less polluted sites viz, Site 1 (1.959, Site 4 (2.010, Site 5 (2.047. However, at highly polluted sites viz., 2 and 3, H/ value of 1.336 and 0.984 respectively, were calculated. Simpson’s Dominance index (Dsimp value was highest at Site 3 (0.618 indicating maximum dominance, whereas at Site 5 dominance was lowest (0.1680 and diversity was highest. We discuss the role of zooplankton in the amelioration of wastewater.

210Po/210Pb dynamics in relation to zooplankton biomass and trophic conditions during an annual cycle in northwestern Mediterranean coastal waters

International Nuclear Information System (INIS)

Färber Lorda, Jaime; Fowler, Scott W.; Miquel, Juan-Carlos; Rodriguez y Baena, Alessia; Jeffree, Ross A.

2013-01-01

Monthly sampling in northwestern Mediterranean coastal waters was undertaken to better understand the relationship between zooplankton biomass and the cycling of the natural radionuclide 210 Po/ 210 Pb pair during a one-year period (October 1995–November 1996). In conjunction with mesozooplankton collections and 210 Po/ 210 Pb measurements in seawater, zooplankton and their fecal pellets, the biochemical composition of particulate organic matter (POM) was also examined at three depths (0, 20 and 50 m) as an indicator of trophic conditions. During May 1996, a strong zooplankton “bloom” was observed which was preceded by a prolonged increase in POM (protein + carbohydrates + lipids) starting at the end of March, and further demonstrated by a concomitant increase in the concentration of smaller particles, two features that are typical of mesotrophic waters. Simultaneous measurements of 210 Po in sea water and zooplankton showed an inverse trend between these two parameters during the sampling period, with the two lowest 210 Po concentrations in the dissolved phase of seawater coincident with the highest radionuclide concentrations in the zooplankton; however, this apparent relationship was not statistically significant over the entire year. Freshly excreted mesozooplankton and salp fecal pellets, which have been strongly implicated in the removal and downward transport of these radionuclides from the upper water column, contained 210 Po and 210 Pb levels ranging from 175 to 878 and 7.5–486 Bq kg −1 dry weight, respectively. Salp pellets contained 5 and 10 times more 210 Po and 210 Pb than in fecal pellets produced by mixed zooplankton, a finding most likely related to their different feeding strategies. During the zooplankton biomass peak observed in May, the 210 Po concentration in zooplankton was at a minimum; however, in contrast to what has been reported to occur in some open sea oligotrophic waters, over the year no statistically significant inverse

Measuring multiscaling in financial time-series

International Nuclear Information System (INIS)

Buonocore, R.J.; Aste, T.; Di Matteo, T.

2016-01-01

We discuss the origin of multiscaling in financial time-series and investigate how to best quantify it. Our methodology consists in separating the different sources of measured multifractality by analyzing the multi/uni-scaling behavior of synthetic time-series with known properties. We use the results from the synthetic time-series to interpret the measure of multifractality of real log-returns time-series. The main finding is that the aggregation horizon of the returns can introduce a strong bias effect on the measure of multifractality. This effect can become especially important when returns distributions have power law tails with exponents in the range (2, 5). We discuss the right aggregation horizon to mitigate this bias.

Zooplankton along the Tamil Nadu coast

Digital Repository Service at National Institute of Oceanography (India)

Santhakumari, V.; Saraswathy, M.

Zooplankton abundance along two sectors at Cape Comorin and Tuticorin of Tamil Nadu Coast, southeast coast of India was studied. High biomass contributed by Ostracods, Salps, Chaetognaths etc., were observed along Tuticorin transect. In the Cape...

Planktivory in the changing Lake Huron zooplankton community: Bythotrephes consumption exceeds that of Mysis and fish

Science.gov (United States)

Bunnell, D.B.; Hunter, R. Douglas; Warner, D.M.; Chriscinske, M.A.; Roseman, E.F.

2011-01-01

Oligotrophic lakes are generally dominated by calanoid copepods because of their competitive advantage over cladocerans at low prey densities. Planktivory also can alter zooplankton community structure. We sought to understand the role of planktivory in driving recent changes to the zooplankton community of Lake Huron, a large oligotrophic lake on the border of Canada and the United States. We tested the hypothesis that excessive predation by fish (rainbow smelt Osmerus mordax, bloater Coregonus hoyi) and invertebrates (Mysis relicta, Bythotrephes longimanus) had driven observed declines in cladoceran and cyclopoid copepod biomass between 2002 and 2007. We used a field sampling and bioenergetics modelling approach to generate estimates of daily consumption by planktivores at two 91-m depth sites in northern Lake Huron, U.S.A., for each month, May-October 2007. Daily consumption was compared to daily zooplankton production. Bythotrephes was the dominant planktivore and estimated to have eaten 78% of all zooplankton consumed. Bythotrephes consumption exceeded total zooplankton production between July and October. Mysis consumed 19% of all the zooplankton consumed and exceeded zooplankton production in October. Consumption by fish was relatively unimportant - eating only 3% of all zooplankton consumed. Because Bythotrephes was so important, we explored other consumption estimation methods that predict lower Bythotrephes consumption. Under this scenario, Mysis was the most important planktivore, and Bythotrephes consumption exceeded zooplankton production only in August. Our results provide no support for the hypothesis that excessive fish consumption directly contributed to the decline of cladocerans and cyclopoid copepods in Lake Huron. Rather, they highlight the importance of invertebrate planktivores in structuring zooplankton communities, especially for those foods webs that have both Bythotrephes and Mysis. Together, these species occupy the epi-, meta- and

Time averaging, ageing and delay analysis of financial time series

Science.gov (United States)

Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

Production and associations of zooplankton in estuarine and nearshore waters of Goa

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.

Zooplankton production in the Zuari and Mandovi estuaries indicated 2 peaks-one in November and another in March/April. In the nearshore waters very high value of zooplankton biomass was observed in April associated with Trichodesmium bloom. Mean...

Feeding on dispersed vs. aggregated particles: The effect of zooplankton feeding behavior on vertical flux

DEFF Research Database (Denmark)

Koski, Marja; Boutorh, Julia; De La Rocha, Christina L.

2017-01-01

Zooplankton feeding activity is hypothesized to attenuate the downward flux of elements in the ocean. We investigated whether the zooplankton community composition could influence the flux attenuation, due to the differences of feeding modes (feeding on dispersed vs. aggregated particles) and of ......Zooplankton feeding activity is hypothesized to attenuate the downward flux of elements in the ocean. We investigated whether the zooplankton community composition could influence the flux attenuation, due to the differences of feeding modes (feeding on dispersed vs. aggregated particles...

Applied time series analysis

CERN Document Server

Woodward, Wayne A; Elliott, Alan C

2011-01-01

""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…

Eutrophication and warming effects on long-term variation of zooplankton in Lake Biwa

Directory of Open Access Journals (Sweden)

C. H. Hsieh

2011-05-01

Full Text Available We compiled and analyzed long-term (1961–2005 zooplankton community data in response to environmental variations in Lake Biwa. Environmental data indicate that Lake Biwa had experienced eutrophication (according to the total phosphorus concentration in the late 1960s and recovered to a normal trophic status around 1985, and then has exhibited warming since 1990. Total zooplankton abundance showed a significant correlation with total phytoplankton biomass. Following a classic pattern, the cladoceran/calanoid and cyclopoid/calanoid abundance ratio was related positively to eutrophication. The zooplankton community exhibited a significant response to the boom and bust of phytoplankton biomass as a consequence of eutrophication-reoligotriphication and warming. Moreover, our analyses suggest that the Lake Biwa ecosystem exhibited a hierarchical response across trophic levels; that is, higher trophic levels may show a more delayed response or no response to eutrophication than lower ones.

We tested the hypothesis that the phytoplankton community can better explain the variation of the zooplankton community than bulk environmental variables, considering that the phytoplankton community may directly affect the zooplankton succession through predator-prey interactions. Using a variance partition approach, however, we did not find strong evidence to support this hypothesis. We further aggregated zooplankton according to their feeding types (herbivorous, carnivorous, omnivorous, and parasitic and taxonomic groups, and analyzed the aggregated data. While the pattern remains similar, the results are less clear comparing the results based on finely resolved data. Our research suggests that zooplankton can be bio-indicators of environmental changes; however, the efficacy depends on data resolution.

Entropic Analysis of Electromyography Time Series

Science.gov (United States)

Kaufman, Miron; Sung, Paul

2005-03-01

We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.

High mortality of Red Sea zooplankton under ambient solar radiation.

Science.gov (United States)

Al-Aidaroos, Ali M; El-Sherbiny, Mohsen M O; Satheesh, Sathianeson; Mantha, Gopikrishna; Agustī, Susana; Carreja, Beatriz; Duarte, Carlos M

2014-01-01

High solar radiation along with extreme transparency leads to high penetration of solar radiation in the Red Sea, potentially harmful to biota inhabiting the upper water column, including zooplankton. Here we show, based on experimental assessments of solar radiation dose-mortality curves on eight common taxa, the mortality of zooplankton in the oligotrophic waters of the Red Sea to increase steeply with ambient levels of solar radiation in the Red Sea. Responses curves linking solar radiation doses with zooplankton mortality were evaluated by exposing organisms, enclosed in quartz bottles, allowing all the wavelengths of solar radiation to penetrate, to five different levels of ambient solar radiation (100%, 21.6%, 7.2%, 3.2% and 0% of solar radiation). The maximum mortality rates under ambient solar radiation levels averaged (±standard error of the mean, SEM) 18.4±5.8% h(-1), five-fold greater than the average mortality in the dark for the eight taxa tested. The UV-B radiation required for mortality rates to reach ½ of maximum values averaged (±SEM) 12±5.6 h(-1)% of incident UVB radiation, equivalent to the UV-B dose at 19.2±2.7 m depth in open coastal Red Sea waters. These results confirm that Red Sea zooplankton are highly vulnerable to ambient solar radiation, as a consequence of the combination of high incident radiation and high water transparency allowing deep penetration of damaging UV-B radiation. These results provide evidence of the significance of ambient solar radiation levels as a stressor of marine zooplankton communities in tropical, oligotrophic waters. Because the oligotrophic ocean extends across 70% of the ocean surface, solar radiation can be a globally-significant stressor for the ocean ecosystem, by constraining zooplankton use of the upper levels of the water column and, therefore, the efficiency of food transfer up the food web in the oligotrophic ocean.

High mortality of Red Sea zooplankton under ambient solar radiation.

Directory of Open Access Journals (Sweden)

Ali M Al-Aidaroos

Full Text Available High solar radiation along with extreme transparency leads to high penetration of solar radiation in the Red Sea, potentially harmful to biota inhabiting the upper water column, including zooplankton. Here we show, based on experimental assessments of solar radiation dose-mortality curves on eight common taxa, the mortality of zooplankton in the oligotrophic waters of the Red Sea to increase steeply with ambient levels of solar radiation in the Red Sea. Responses curves linking solar radiation doses with zooplankton mortality were evaluated by exposing organisms, enclosed in quartz bottles, allowing all the wavelengths of solar radiation to penetrate, to five different levels of ambient solar radiation (100%, 21.6%, 7.2%, 3.2% and 0% of solar radiation. The maximum mortality rates under ambient solar radiation levels averaged (±standard error of the mean, SEM 18.4±5.8% h(-1, five-fold greater than the average mortality in the dark for the eight taxa tested. The UV-B radiation required for mortality rates to reach ½ of maximum values averaged (±SEM 12±5.6 h(-1% of incident UVB radiation, equivalent to the UV-B dose at 19.2±2.7 m depth in open coastal Red Sea waters. These results confirm that Red Sea zooplankton are highly vulnerable to ambient solar radiation, as a consequence of the combination of high incident radiation and high water transparency allowing deep penetration of damaging UV-B radiation. These results provide evidence of the significance of ambient solar radiation levels as a stressor of marine zooplankton communities in tropical, oligotrophic waters. Because the oligotrophic ocean extends across 70% of the ocean surface, solar radiation can be a globally-significant stressor for the ocean ecosystem, by constraining zooplankton use of the upper levels of the water column and, therefore, the efficiency of food transfer up the food web in the oligotrophic ocean.

NODC Standard Format Marine Zooplankton (F124) Data (1965-1983) (NODC Accession 0014196)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data type contains data from sampling and analysis of marine zooplankton. Information on zooplankton abundance, distribution and productivity derived from these...

Reaction of fresh water zooplankton community to chronic radiation exposure

Energy Technology Data Exchange (ETDEWEB)

Osipov, D.; Pryakhin, E. [Urals Research Center for Radiation Medicine - URCRM (Russian Federation); Ivanov, I. [FSUE Mayak PA (Russian Federation)

2014-07-01

The characteristic features of ecological community as a whole and cenosis of zooplankton organisms as part of it determine the intensity of the processes of self-purification of water and the formation of a particular body of water. Identifying features of the structure and composition of the zooplankton community of aquatic ecosystems exposed to different levels of radiation exposure, it is necessary to identify patterns of changes in zooplankton and hydro-biocenosis as a whole. Industrial reservoirs, the storage of liquid low-level radioactive waste 'Mayak' for decades, have high radiation load. A large range of levels of radioactive contamination (total volume beta-activity in water varies from 2.2x10{sup 3} to 2.3x10{sup 7} Bq/l, total volume alpha-activity - from 2.6x10{sup -1} to 3.1x10{sup 3} Bq/l) provides a unique opportunity to study ecosystems in a number of reservoirs with increasing impact of radiation factor. We studied five reservoirs that were used as the storage of low-and intermediate-level liquid radioactive waste pond and one comparison water body. In parallel with zooplankton sampling water samples were collected for hydro-chemical analysis. 41 indicators were analysed in order to assess the water chemistry. To determine the content of radionuclides in the various components of the ecosystem samples were collected from water, bottom sediments and plankton. Sampling of zooplankton for the quantitative analysis was performed using the method of weighted average auto bathometer. Apshteyn's plankton net of the surface horizon was used for qualitative analysis of the species composition of zooplankton. Software package ERICA Assessment Tool 2012 was used for the calculation of the absorbed dose rate. Species diversity and biomass of zooplankton, the share of rotifers in the number of species, abundance and biomass decrease with the increase of the absorbed dose rate and salinity. The number of species in a sample decreases with the

Variación diaria de la abundancia del zooplancton en Bahía Magdalena, B.C.S. México Daily cycle of zooplankton abundance in Magdalena Bay, B.C.S. Mexico

Directory of Open Access Journals (Sweden)

Sergio Hernández-Trujillo

2010-12-01

Full Text Available Se presenta la variación diaria de la abundancia de zooplancton en Bahía Magdalena, México a partir de muestreos en una estación fija durante 10 días en febrero de 2002. De 112 taxa identificados, los nauplios de balanos y los cladóceros Penilia avirostris y Pseudevadne tergestina fueron los más comunes y abundantes y con niveles de variación diaria de más del 100%. Los copépodos constituyeron una quinta parte de la abundancia del zooplancton y 7 de las 80 especies encontradas se registran por vez primera en la zona de estudio. La abundancia del zooplancton fue parcialmente coherente con la hidrografía de la bahía, así como con un modelo de retención de partículas. Las 3 especies de copépodos más abundantes fueron más numerosas a inicio de la serie pero tendieron a reducir su densidad hacia el fin del lapso de estudio. La hidrodinámica invernal en la zona se identificó como un factor de concentración de zooplancton, quizá de importancia mayor que la temperatura o la concentración de clorofila a, aún no estimada en la estructura de la comunidad ni en la intensidad de las relaciones interespecíficas.This paper presents the daily variation of the abundance of zooplankton in Magdalena Bay, Mexico from sampling in a fixed-station for 10 days of February 2002. From 112 taxa identified barnacles nauplii and cladocerans Penilia avirostris and Pseudevadne tergestina were the most common and abundant with daily variation levels more than 100%. The copepods constituted one fifth of zooplankton abundance and 7 of the 80 species found were recorded for the first time in the study area. Zooplankton abundance showed partially coherent pattern with the hidrography of the bay as well as particles retention model. The 3 species of copepods more abundant were more numerous at the beginning of the time series but tended to reduce its density toward the end of the time of study. Winter hydrodynamics was identified as a factor of zooplankton

Zooplankton standing stock, community structure and diversity in the northern Arabian Sea

Digital Repository Service at National Institute of Oceanography (India)

Goswami, S.C.; Srivastava, Y.

The effects of large scale oil spill, which occurred during the Gulf War in 1991 on zooplankton standing stock, community structure and diversity in the northern Arabian Sea were studied. Surface (1-0 m) and vertical zooplankton hauls (200-0 m, 250...

Quantifying memory in complex physiological time-series.

Science.gov (United States)

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

Effective Feature Preprocessing for Time Series Forecasting

DEFF Research Database (Denmark)

Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

2006-01-01

Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

Productivity, trophic levels and size spectra of zooplankton in northern Norwegian shelf regions

Science.gov (United States)

Zhou, Meng; Tande, Kurt S.; Zhu, Yiwu; Basedow, Sünnje

2009-10-01

Many studies have been conducted in northern Norwegian shelf regions to assess distributions and abundances of zooplankton in the last decade using towed Scanfish-conductivity, temperature and depth sensors (CTD)-optical plankton counter (OPC), and plankton nets. Significant progresses have been made in understanding dominant species, life histories and behavior, and in using size-structured data to identify dominant species in a certain size range. Using these Scanfish-CTD-OPC data, the analysis of zooplankton community size structures, compositions and their relationships with water types is made along the shelf region from Lofoten, North Cape to Varangerfjorden. From the relationships between the water types and zooplankton communities, the transports and exchanges of zooplankton communities between the Norwegian Coastal and Norwegian Atlantic Waters in regions near Malangsgrunnen and Nordvestbanken are examined. The biovolume (biomass) spectra are further analyzed for the productivity, trophic levels and seasonality of communities in these regions, indicating a steeper slope of the biovolume spectrum for a community dominated by herbivorous species in spring and a flatter slope for a community dominated by carnivorous-omnivorous species in winter. The comparison with the zooplankton biovolume spectra obtained in areas west of Antarctic Peninsula is made to examine and understand the differences in the zooplankton biovolume spectra, their trophic dynamics and potential human impacts between different regions.

Incorporation of nitrogen from N2 fixation into amino acids of zooplankton

DEFF Research Database (Denmark)

Loick-Wilde, Natalie; Dutz, Jörg; Miltner, Anja

2012-01-01

quantified the direct incorporation of 15N tracer from N2-fixing N. spumigena (diazotroph nitrogen) and ammonium-utilizing R. salina into the amino acid nitrogen (AA-N) of zooplankton using complementary gas chromatography– combustion–isotope ratio mass spectrometry, gas chromatography–mass spectrometry...... consistently low in E. affinis when exposed to N. spumigena, suggesting that these animals were reluctant to feed on N. spumigena. Essential isoleucine received most of the diazotroph nitrogen in field zooplankton, while nonessential amino acids received most 15N tracer in E. affinis. N. spumigena was clearly...... an important amino acid nitrogen source for Baltic Sea zooplankton...

Dynamics of zooplankton community of Lake Tarasmozero in long-term anthropogenic pollution

Directory of Open Access Journals (Sweden)

Kuchko Yaroslav Alexandrovich

2014-11-01

Full Text Available In the article the results of zooplankton studies in Lake Tarasmozero (Lizhma river basin are presented. Wastes from the trout-breeding complex "Kedrozero" have been collected in this pond since 1992. The obtained data showed that from 1989 to 2012 a number of changes in zooplankton community take place and it is the evidence of the gradual increase in the trophic status of the reservoir. The average biomass of zooplankton increased from 500 to 1000 mg/m3. According to the trophic index (Myaemets, 1979, Tarasmozero is replaced into the category of mesotrophic water reservoirs (0.5 - 1.0. Saprobity index raised from 0.95 to 1.42. In the composition of the zooplankton there noted such species, as Polyarthra luminosa, Filinia longiseta, Trichocerca insignis, Daphnia longispina, Cyclops kolensis, which serve as indicators of increased trophic level in the conditions of moderate latitudes. After the trout farm started off, Bcrus/Brot indicator considerably decreased indicating to increasing role of rotifers in the formation of the total biomass of the zooplankton. Currently, the dominant species include D. longispina, Bosmina longirostris, Mesocyclops leuckarti, Asplanchna priodonta. In spite of the fact that the current changes are not catastrophic, it is reasonable to monitor regularly the initial links of the trophic chain of the reservoir ecosystem

Zooplankton Structure and Potential Food Web Interactions in the Plankton of a Subtropical Chain-of-Lakes

Directory of Open Access Journals (Sweden)

Karl E. Havens

2002-01-01

Full Text Available This study evaluates the taxonomic and size structure of macro-zooplankton and its potential role in controlling phytoplankton in the Kissimmee Chain-of-Lakes, six shallow interconnected lakes in Florida, U.S. Macro-zooplankton species biomass and standard limnological attributes (temperature, pH, total phosphorus [TP], chlorophyll a [Chl a], and Secchi transparency were quantified on a bimonthly basis from April 1997 to February 1999. Concentrations of TP ranged from below 50 to over 150 μg l-1. Peak concentrations of particulate P coincided with maximal Chl a, and in one instance a high concentration of soluble reactive P followed. The cladoceran zooplankton was dominated by small species, including Eubosmina tubicen, Ceriodaphnia rigaudi, and Daphnia ambigua. The exotic daphnid, D. lumholtzii, periodically was abundant. The copepods were strongly dominated by Diaptomus dorsalis, a species previously shown to be highly resistant to fish predation. These results, and findings of controlled experiments on a nearby lake with a nearly identical zooplankton species complement, suggest that fish predation may be a major factor structuring the macro-zooplankton assemblage. Zooplankton biomass, on the other hand, may be affected by resource availability. There was a significant positive relationship between average biomass of macro-zooplankton and the average concentration of TP among the six lakes. No such relationship existed between zooplankton biomass and Chl a, suggesting that the predominant food web in these systems may be based on bacteria-plankton, as has been documented in nearby Lake Okeechobee. All of the zooplankton taxa encountered in the Kissimmee Chain-of-Lakes (except Mesocyclops edax are known bacteria grazers in Florida lakes. Phytoplankton biomass, measured as Chl a, was strongly associated with TP, both within and across lakes. Phytoplankton biomass was not associated with the biomass of zooplankton. These results, when

137Cs concentration in zooplankton and its relation to taxonomic composition in the western North Pacific Ocean

International Nuclear Information System (INIS)

Kaeriyama, Hideki; Watabe, Teruhisa; Kusakabe, Masashi

2008-01-01

To study the role of zooplankton in the transport of 137 Cs in the ocean, zooplankton samples were collected in October 2005 and June 2006 in the western North Pacific Ocean. The peak zooplankton biomass was observed in the surface layer, and gelatinous plankton was more abundant in October 2005 than in June 2006 reflecting exchange of water masses. The concentrations of 137 Cs in zooplankton varied from 11 to 24 mBq kg wet -1 and were higher in October 2005 than in June 2006. The elevated abundance of gelatinous zooplankton probably led to higher concentration of 137 Cs in zooplankton in October 2005. Annual export fluxes of 137 Cs by ontogenetic vertical migrant copepods were estimated to be 0.8 and 0.6 mBq m -2 year -1 at 200 and 1000 m depths, respectively; this suggested that transport of 137 Cs by zooplankton may be no trivial pathway

Statistical criteria for characterizing irradiance time series.

Energy Technology Data Exchange (ETDEWEB)

Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

2010-10-01

We propose and examine several statistical criteria for characterizing time series of solar irradiance. Time series of irradiance are used in analyses that seek to quantify the performance of photovoltaic (PV) power systems over time. Time series of irradiance are either measured or are simulated using models. Simulations of irradiance are often calibrated to or generated from statistics for observed irradiance and simulations are validated by comparing the simulation output to the observed irradiance. Criteria used in this comparison should derive from the context of the analyses in which the simulated irradiance is to be used. We examine three statistics that characterize time series and their use as criteria for comparing time series. We demonstrate these statistics using observed irradiance data recorded in August 2007 in Las Vegas, Nevada, and in June 2009 in Albuquerque, New Mexico.

Biomass and composition of zooplankton in the nearshore waters of Thal, Maharashtra

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.; Gajbhiye, S.N; Krishnakumari, L; Desai, B.N

Biomass and composition of zooplankton in the nearshore waters of Thal, Maharashtra, India were studied at 9 stations during Feb. 1980 to Jan. 1981. The recorded variation in zooplankton biomass was 4.8-80.6 ml.(100 m super(3))/1 [av. 22.9 ml.(100 m...

Future marine zooplankton research - a perspective

DEFF Research Database (Denmark)

Bathmann, U.; Bundy, M.H.; Clarke, M.E.

2001-01-01

and existence of dominant zooplankton taxa, and (2) the control of biodiversity and biocomplexity, for example, in the tropical ocean where diversity is high. These recommendations come from an assemblage of chemical, physical and biological oceanographers with experience in major interdisciplinary studies...

Magnetic Field Fluctuations Due to Diel Vertical Migrations of Zooplankton

Science.gov (United States)

Dean, C.; Soloviev, A.

2016-12-01

Dean et al. (2016) have indicated that at high zooplankton concentrations, diel vertical migrations (DVM) cause velocity fluctuations and a respective increase of the dissipation rate of turbulent kinetic energy (TKE). In this work, we used a 3D non-hydrostatic computational fluid dynamics model with Lagrangian particle injections (a proxy for migrating organisms) via a discrete phase model to simulate the effect of turbulence generation by DVM. We tested a range of organism concentrations from 1000 to 10,000 organisms/m3. The simulation at an extreme concentration of zooplankton showed an increase in dissipation rate of TKE by two to three orders of magnitude during DVM over background turbulence, 10-8 W kg-1. At lower concentrations (Frank, J. Wood, 2016: Biomixing due to diel vertical migrations of zooplankton. Ocean Modelling 98, 51-64.

Homogenising time series: beliefs, dogmas and facts

Science.gov (United States)

Domonkos, P.

2011-06-01

In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Science.gov (United States)

Michaels, Anthony F.; Knap, Anthony H.

1992-01-01

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

SEAPODYM-LTL: a parsimonious zooplankton dynamic biomass model

Science.gov (United States)

Conchon, Anna; Lehodey, Patrick; Gehlen, Marion; Titaud, Olivier; Senina, Inna; Séférian, Roland

2017-04-01

Mesozooplankton organisms are of critical importance for the understanding of early life history of most fish stocks, as well as the nutrient cycles in the ocean. Ongoing climate change and the need for improved approaches to the management of living marine resources has driven recent advances in zooplankton modelling. The classical modeling approach tends to describe the whole biogeochemical and plankton cycle with increasing complexity. We propose here a different and parsimonious zooplankton dynamic biomass model (SEAPODYM-LTL) that is cost efficient and can be advantageously coupled with primary production estimated either from satellite derived ocean color data or biogeochemical models. In addition, the adjoint code of the model is developed allowing a robust optimization approach for estimating the few parameters of the model. In this study, we run the first optimization experiments using a global database of climatological zooplankton biomass data and we make a comparative analysis to assess the importance of resolution and primary production inputs on model fit to observations. We also compare SEAPODYM-LTL outputs to those produced by a more complex biogeochemical model (PISCES) but sharing the same physical forcings.

Changes of species composition, formation of quantitative structure and peculiarities of development of proto- and meta zooplankton under the impact of ecological factors in Lake Drukshiai

International Nuclear Information System (INIS)

Mazheikaite, S.

1997-01-01

According to 1993-95 research data, water temperature was found to be the most significant factor influencing the structure of zooplankton as well as seasonal development changes. Because of great amount of heated water discharged from Ignalina NPP, determining an increase of the temperature in all water layers and disappearance of the thermal zone below 10 degrees of Centigrade in deep water layers in summer, the species diversity of zooplankton decreased more than twice if compared with 1979-86. Cold-steno thermal species were the first to disappear. At the same time, warm-requiring and eurithermal species predominated. Natural seasonal rise of temperature (till 26.5 degrees of Centigrade) stimulated the development of some groups of meta zooplankton (Cladocera and Copepod a). The abundance of most species of Rotator ia decreased when the water temperature was over 15 degrees of Centigrade. The heated water discharged from Ignalina NPP caused structural changes of meta zooplankton, decrease of its biomass, decrease of the amount and biomass of proto zooplankton in this area. Because of heated water impact, the highest mortality of proto zooplankton was observed in summer. One maximum of quantitative development was characteristic of seasonal dynamics of zooplankton in Lake Drukshiai, while in water basins with natural thermal regime there are 2 seasonal maxima. Dependence of proto zooplankton on phytoplankton nd on Copepod a as well as dependence of meta zooplankton on phytoplankton were investigated. Data on spatial distribution of zooplankton in Lake Drukshiai indicate the eutrophication process in the southwestern part of the lake (because of increase of biogen s concentration). (author)

Flow disturbances generated by feeding and swimming zooplankton

DEFF Research Database (Denmark)

Kiørboe, Thomas; Jiang, Haisong; Goncalves, R. J.

2014-01-01

that zooplankton, in which feeding and swimming are separate processes, produce flow disturbances during swimming with a much faster spatial attenuation (velocity u varies with distance r as u ∝ r−3 to r−4) than that produced by zooplankton for which feeding and propulsion are the same process (u ∝ r−1 to r−2...... vortex rings, or by “breast-stroke swimming.” Both produce rapidly attenuating flows. The more “noisy” swimming of those that are constrained by a need to simultaneously feed is due to constantly beating flagella or appendages that are positioned either anteriorly or posteriorly on the (cell) body...

Multivariate Time Series Decomposition into Oscillation Components.

Science.gov (United States)

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Forecasting Enrollments with Fuzzy Time Series.

Science.gov (United States)

Song, Qiang; Chissom, Brad S.

The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

Variability of zooplankton communities at Condor seamount and surrounding areas, Azores (NE Atlantic)

Science.gov (United States)

Carmo, Vanda; Santos, Mariana; Menezes, Gui M.; Loureiro, Clara M.; Lambardi, Paolo; Martins, Ana

2013-12-01

Seamounts are common topographic features around the Azores archipelago (NE Atlantic). Recently there has been increasing research effort devoted to the ecology of these ecosystems. In the Azores, the mesozooplankon is poorly studied, particularly in relation to these seafloor elevations. In this study, zooplankton communities in the Condor seamount area (Azores) were investigated during March, July and September 2010. Samples were taken during both day and night with a Bongo net of 200 µm mesh that towed obliquely within the first 100 m of the water column. Total abundance, biomass and chlorophyll a concentrations did not vary with sampling site or within the diel cycle but significant seasonal variation was observed. Moreover, zooplankton community composition showed the same strong seasonal pattern regardless of spatial or daily variability. Despite seasonal differences, the zooplankton community structure remained similar for the duration of this study. Seasonal variability better explained our results than mesoscale spatial variability. Spatial homogeneity is probably related with island proximity and local dynamics over Condor seamount. Zooplankton literature for the region is sparse, therefore a short review of the most important zooplankton studies from the Azores is also presented.

Efectos del herbicida Paraquat sobre el zooplancton Effects of Paraquat herbicide on zooplankton

Directory of Open Access Journals (Sweden)

Ana María Gagneten

2002-09-01

Full Text Available The effects of 0.1; 0.2; 0.4 and 0.8 mlPQ/L were analized on a zooplankton community, to determine the most sensitive species and to analize the occurence of physical abnormalities. A total of 40 taxa were determined. Paraquat affected significantly the zooplankton density but not the species richness. A progressive state of deformation of these organisms was also observed. Paraquat showed to be highly toxic for the zooplankton, so this herbicide should be strictly regulated in aquatic and terrestrial ecosystems.

Forecasting Cryptocurrencies Financial Time Series

DEFF Research Database (Denmark)

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely...

Forecasting Cryptocurrencies Financial Time Series

OpenAIRE

Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

2018-01-01

This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely on Dynamic Model Averaging to combine a large set of univariate Dynamic Linear Models and several multivariate Vector Autoregressive models with different forms of time variation. We find statistical si...

Zooplankton trophic niches respond to different water types of the western Tasman Sea: A stable isotope analysis

Science.gov (United States)

Henschke, Natasha; Everett, Jason D.; Suthers, Iain M.; Smith, James A.; Hunt, Brian P. V.; Doblin, Martina A.; Taylor, Matthew D.

2015-10-01

The trophic relationships of 21 species from an oceanic zooplankton community were studied using stable isotopes of carbon and nitrogen. Zooplankton and suspended particulate organic matter (POM) were sampled in three different water types in the western Tasman Sea: inner shelf (IS), a cold core eddy (CCE) and a warm core eddy (WCE). δ15N values ranged from 3.9‰ for the parasitic copepod Sapphirina augusta to 10.2‰ for the euphausiid, Euphausia spinifera. δ13C varied from -22.6 to -19.4‰ as a result of the copepod Euchirella curticauda and E. spinifera. The isotopic composition of POM varied significantly among water types; as did the trophic enrichment of zooplankton over POM, with the lowest enrichment in the recently upwelled IS water type (0.5‰) compared to the warm core eddy (1.6‰) and cold core eddy (2.7‰). The WCE was an oligotrophic environment and was associated with an increased trophic level for omnivorous zooplankton (copepods and euphausiids) to a similar level as carnivorous zooplankton (chaetognaths). Therefore carnivory in zooplankton can increase in response to lower abundance and reduced diversity in their phytoplankton and protozoan prey. Trophic niche width comparisons across three zooplankton species: the salp Thalia democratica, the copepod Eucalanus elongatus and the euphausiid Thysanoessa gregaria, indicated that both niche partitioning and competition can occur within the zooplankton community. We have shown that trophic relationships among the zooplankton are dynamic and respond to different water types. The changes to the zooplankton isotopic niche, however, were still highly variable as result of oceanographic variation within water types.

Spatial variation of the zooplankton community in the western tropical Pacific Ocean during the summer of 2014

Science.gov (United States)

Yang, Guang; Li, Chaolun; Wang, Yanqing; Wang, Xiaocheng; Dai, Luping; Tao, Zhencheng; Ji, Peng

2017-03-01

Knowledge of the zooplankton community in the western tropical Pacific Ocean is poor compared to that of the communities in the central and eastern Pacific Ocean. The zooplankton composition, abundance, biomass and community structure in the western Pacific Ocean were studied based on data collected during a synoptic cruise (August-September 2014). Four zooplankton communities were determined via cluster analysis, and these four clusters were mainly spatially related to four different currents: the Luzon Current (LC), Subtropical Countercurrent (STCC), North Equatorial Current (NEC) and North Equatorial Countercurrent (NECC). The estimated mean abundance and biomass of the zooplankton for the whole surveyed area were 146.7±178.1 ind/m3 and 36.9±40.3 mg/m3, respectively. The zooplankton abundance was dominated by small copepods, such as Clausocalanus furcatus, C. pergens, Oncaea mediterranea and Oithona plumifera. The zooplankton abundance and biomass values were lowest in the STCC region and highest in the NECC region. BEST analysis based on surface environmental factors showed that chlorophyll a (chl a), pH, temperature and salinity were the environmental variables that best explained the distribution pattern of the zooplankton community (pw=0.372). The zooplankton abundance was higher south of the salinity front at 16°N, in accordance with the relatively higher nutrient and chl a levels. Maximum zooplankton biomass was found in regions on the periphery of the cyclonic Mindanao Eddy (ME) and anticyclonic Halmahera Eddy (HE).

Zooplankton resting egg banks in permanent and temporary tropical aquatic systems

Directory of Open Access Journals (Sweden)

Luciana Rabelo Araújo

Full Text Available AIM: We evaluated zooplankton resting egg banks and active communities in five coastal lagoons and in five temporary pools, aiming to compare the active and the dormant communities in such environments. As they differ in hydroperiod, we expected that pools present richer resting egg banks in comparison to those found in lagoons. METHODS: Zooplankton community was sampled twice in 2006 (lagoons and in 2010 (pools and resting egg banks were sampled once in December 2007 (lagoons and in May 2010 (pools. Resting eggs were isolated from the sediment by applying the sugar flotation method. RESULTS: In opposition to our expectation, species richness in the resting egg banks of pools did not differ from those of lagoons. Additionally, no difference was found between the active and the dormant zooplankton communities in each water body for both temporary and permanent environments. However, similarity between active and dormant communities was greater in permanent environments than it was in temporary environments. CONCLUSIONS: It seems that the diapause strategy observed in certain tropical zooplankton populations cannot be predicted based on the awareness of the environment type (permanent or temporary, since hatching cues may be species-specific.

Zooplankton composition and diversity at different location along Kalpakkam coastal sites

International Nuclear Information System (INIS)

Das, Subhashree; Ponnusamy, K.; Verma, Amrata; Munilkumar, S.; Rajaram, S.; Lakra, W.S.; Pal, Asim K.; Sreedevi, K.R.

2015-01-01

Zooplanktons are the base of aquatic food web which constitutes the most vital biological component in an aquatic ecosystem. They form an important link in the food chain from primary to tertiary level leading to the production of fishery and are known to serve as a food for larger organisms such as bivalves, crustaceans and fish. The present study was aimed to assess the composition and diversity among the different species of zooplankton in Kalpakkam coastal sites within 30 kms around Madras Atomic Power Station. Samples were collected using plankton net (mesh size 63 μm, mouth area 20 inch dia) from stations which were fixed using the GPS coordinates. The results of the present studies showed maximum zoo planktonic diversity in station N15 i.e. 15 km away from MAPS (Madras Atomic Power Station), as compared to the other selected sampling stations. Regarding composition of zooplankton at different sites along the MAPS, it was found Copepods dominated among the zooplankton forming up to 60% of total species composition which indicate that copepod species are likely to be good indicators of water-mass influence and changes. (author)

Impacts of zooplankton composition and algal enrichment on the accumulation of mercury in an experimental freshwater food web

Energy Technology Data Exchange (ETDEWEB)

Pickhardt, Paul C. [Department of Biological Sciences, Dartmouth College, Hanover, NH 03755 (United States)]. E-mail: paul.pickhardt@stonybrook.edu; Folt, Carol L. [Department of Biological Sciences, Dartmouth College, Hanover, NH 03755 (United States); Chen, Celia Y. [Department of Biological Sciences, Dartmouth College, Hanover, NH 03755 (United States); Klaue, Bjoern [Department of Geological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); Blum, Joel D. [Department of Geological Sciences, University of Michigan, Ann Arbor, MI 48109 (United States)

2005-03-01

There is a well documented accumulation of mercury in fish to concentrations of concern for human consumption. Variation in fish Hg burden between lakes is often high and may result from differences in Hg transfer through lower levels of the food web where mercury is bioconcentrated to phytoplankton and transferred to herbivorous zooplankton. Prior research derived patterns of mercury accumulation in freshwater invertebrates from field collected animals. This study provides results from controlled mesocosm experiments comparing the effects of zooplankton composition, algal abundance, and the chemical speciation of mercury on the ability of zooplankton to accumulate mercury from phytoplankton and transfer that mercury to planktivores. Experiments were conducted in 550-L mesocosms across a gradient of algal densities manipulated by inorganic nutrient additions. Enriched, stable isotopes of organic (CH{sub 3} {sup 200}HgCl) and inorganic ({sup 201}HgCl{sub 2}) mercury were added to mesocosms and their concentrations measured in water, seston, and three common zooplankton species. After 2 weeks, monomethylmercury (MMHg) concentrations were two to three times lower in the two copepod species, Leptodiaptomus minutus and Mesocyclops edax than in the cladoceran, Daphnia mendotae. All three zooplankton species had higher MMHg concentrations in mesocosms with low versus high initial algal abundance. However, despite higher concentrations of inorganic mercury (Hg{sub I}) in seston from low nutrient mesocosms, there were no significant differences in the Hg{sub I} accumulated by zooplankton across nutrient treatments. Bioaccumulation factors for MMHg in the plankton were similar to those calculated for plankton in natural lakes and a four-compartment (aqueous, seston, macrozooplankton, and periphyton/sediments) mass balance model after 21 days accounted for {approx}18% of the CH{sub 3} {sup 200}Hg and {approx}33% of the {sup 201}Hg added. Results from our experiments

Impacts of zooplankton composition and algal enrichment on the accumulation of mercury in an experimental freshwater food web

International Nuclear Information System (INIS)

Pickhardt, Paul C.; Folt, Carol L.; Chen, Celia Y.; Klaue, Bjoern; Blum, Joel D.

2005-01-01

There is a well documented accumulation of mercury in fish to concentrations of concern for human consumption. Variation in fish Hg burden between lakes is often high and may result from differences in Hg transfer through lower levels of the food web where mercury is bioconcentrated to phytoplankton and transferred to herbivorous zooplankton. Prior research derived patterns of mercury accumulation in freshwater invertebrates from field collected animals. This study provides results from controlled mesocosm experiments comparing the effects of zooplankton composition, algal abundance, and the chemical speciation of mercury on the ability of zooplankton to accumulate mercury from phytoplankton and transfer that mercury to planktivores. Experiments were conducted in 550-L mesocosms across a gradient of algal densities manipulated by inorganic nutrient additions. Enriched, stable isotopes of organic (CH 3 200 HgCl) and inorganic ( 201 HgCl 2 ) mercury were added to mesocosms and their concentrations measured in water, seston, and three common zooplankton species. After 2 weeks, monomethylmercury (MMHg) concentrations were two to three times lower in the two copepod species, Leptodiaptomus minutus and Mesocyclops edax than in the cladoceran, Daphnia mendotae. All three zooplankton species had higher MMHg concentrations in mesocosms with low versus high initial algal abundance. However, despite higher concentrations of inorganic mercury (Hg I ) in seston from low nutrient mesocosms, there were no significant differences in the Hg I accumulated by zooplankton across nutrient treatments. Bioaccumulation factors for MMHg in the plankton were similar to those calculated for plankton in natural lakes and a four-compartment (aqueous, seston, macrozooplankton, and periphyton/sediments) mass balance model after 21 days accounted for ∼18% of the CH 3 200 Hg and ∼33% of the 201 Hg added. Results from our experiments corroborate results from field studies and suggest the

Time series modeling, computation, and inference

CERN Document Server

Prado, Raquel

2010-01-01

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

Time Series Analysis Forecasting and Control

CERN Document Server

Box, George E P; Reinsel, Gregory C

2011-01-01

A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl

Role of zooplankton dynamics for Southern Ocean phytoplankton biomass and global biogeochemical cycles

DEFF Research Database (Denmark)

Le Quéré, Corinne; Buitenhuis, Erik T.; Moriarty, Róisín

2016-01-01

zooplankton community, despite iron limitation of phytoplankton community growth rates. This result has implications for the representation of global biogeochemical cycles in models as zooplankton faecal pellets sink rapidly and partly control the carbon export to the intermediate and deep ocean....

Costationarity of Locally Stationary Time Series Using costat

OpenAIRE

Cardinali, Alessandro; Nason, Guy P.

2013-01-01

This article describes the R package costat. This package enables a user to (i) perform a test for time series stationarity; (ii) compute and plot time-localized autocovariances, and (iii) to determine and explore any costationary relationship between two locally stationary time series. Two locally stationary time series are said to be costationary if there exists two time-varying combination functions such that the linear combination of the two series with the functions produces another time...

Phytoplanktons and zooplanktons diversity in karachi coastal seawater under high and low tide during winter monsoon

International Nuclear Information System (INIS)

Yaqoob, N.; Mashiatullah, A.; Sher, N.; Javed, T.; Ghaffar, A.

2013-01-01

This paper represents the population density of phytoplanktons and zooplanktons recorded during the marine environmental studies at Karachi coast in the month of February 2011. Samples were collected by towing net, preserved and quantification and identification was carried out under light microscope. Twenty-three phytoplanktons species and nine zooplankton groups were recorded in the seawater from the sampling area of 10 square kilometers. Coscinodiscus and Copepods were dominant in the population of phytoplankton and zooplankton, respectively. Phytoplankton population density increased while zooplankton abundance decreased offshore from the coastline in the open sea. (author)

Zooplankton structure in two interconnected ponds: similarities and differences

Directory of Open Access Journals (Sweden)

Špoljar Maria

2016-03-01

Full Text Available The research of zooplankton diversity, abundance and trophic structure was conducted during the summer period in pelagial zone on the longitudinal profile of the Sutla River Backwater. Investigated site consists of two interconnected basins: transparent Upper Basin with submerged macrophytes and turbid Lower Basin without macrophytes in the littoral zone. In the Upper Basin, abundance and diversity of zooplankton in the pelagial was higher in comparison to the Lower Basin, with prevailing species of genus Keratella as microfilter-feeder, and genera of Polyartha and Trihocerca as macrofilter-feeder rotifers. On the contrary, in the Lower Basin, crustaceans dominated in abundance. Microfilter-feeder cladoceran (Bosmina longirostris and larval and adult stages of macrofilter-feeder copepod (Macrocyclops albidus prevailed in the Lower Basin. Fish predation pressure was more pronounced in the pelagial of the Upper Basin, indicated by low cladoceran abundance in the surface layer. Although the studied basins were interconnected, results indicate significant (Mann-Whitney U test, p < 0.05 differences in the zooplankton structure as a potential result of the macrophyte impact on environmental conditions and fish predation pressure.

Detecting nonlinear structure in time series

International Nuclear Information System (INIS)

Theiler, J.

1991-01-01

We describe an approach for evaluating the statistical significance of evidence for nonlinearity in a time series. The formal application of our method requires the careful statement of a null hypothesis which characterizes a candidate linear process, the generation of an ensemble of ''surrogate'' data sets which are similar to the original time series but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original time series against the null hypothesis by checking whether the discriminating statistic computed for the original time series differs significantly from the statistics computed for each of the surrogate sets. While some data sets very cleanly exhibit low-dimensional chaos, there are many cases where the evidence is sketchy and difficult to evaluate. We hope to provide a framework within which such claims of nonlinearity can be evaluated. 5 refs., 4 figs

Introduction to time series and forecasting

CERN Document Server

Brockwell, Peter J

2016-01-01

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space mod...

Diurnal variation of zooplankton off Versova (Bombay)

Digital Repository Service at National Institute of Oceanography (India)

Gajbhiye, S.N.; Nair, V.R.; Desai, B.N.

Physicochemical parameters and diurnal variaion of zooplankton were studied off Versova on 17/18 February 1981. Salinity and dissolved oxygen showed limited variation during the period of study. Nutrient values followed the tidal rhythm and high...

Vertical oceanic transport of alpha-radioactive nuclides by zooplankton fecal pellets

International Nuclear Information System (INIS)

Higgo, J.J.W.; Cherry, R.D.; Heyraud, M.; Fowler, S.W.; Beasley, T.M.

1980-01-01

This paper gives the results of research to explain the role played by marine plankton metabolism in the vertical oceanic transport of the alpha-emitting nuclides. The common Mediterranean euphausiid, Meganyctiphanes norvegica, was selected as the typical zooplanktonic species that is the focus of this work. Measurements of 239 240 Pu, 238 U, 232 Th, and 210 Po are reported in whole euphausiids and in euphausiid fecal pellets and molts. The resulting data are inserted into a simple model that describes the flux of an element through a zooplanktonic animal. Concentrations of the nuclides concerned are high in fecal pellets, at levels which are typical of geological rather than biological material. It is suggested that zooplanktonic fecal pellets play a significant role in the vertical oceanic transport of plutonium, thorium, and polonium

Responses of trophic structure and zooplankton community to salinity and temperature in Tibetan lakes: Implication for the effect of climate warming.

Science.gov (United States)

Lin, Qiuqi; Xu, Lei; Hou, Juzhi; Liu, Zhengwen; Jeppesen, Erik; Han, Bo-Ping

2017-11-01

Warming has pronounced effects on lake ecosystems, either directly by increased temperatures or indirectly by a change in salinity. We investigated the current status of zooplankton communities and trophic structure in 45 Tibetan lakes along a 2300 m altitude and a 76 g/l salinity gradient. Freshwater to hyposaline lakes mainly had three trophic levels: phytoplankton, small zooplankton and fish/Gammarus, while mesosaline to hypersaline lakes only had two: phytoplankton and large zooplankton. Zooplankton species richness declined significantly with salinity, but did not relate with temperature. Furthermore, the decline in species richness with salinity in lakes with two trophic levels was much less abrupt than in lakes with three trophic levels. The structural variation of the zooplankton community depended on the length of the food chain, and was significantly explained by salinity as the critical environmental variable. The zooplankton community shifted from dominance of copepods and small cladoceran species in the lakes with low salinity and three trophic levels to large saline filter-feeding phyllopod species in those lakes with high salinity and two trophic levels. The zooplankton to phytoplankton biomass ratio was positively related with temperature in two-trophic-level systems and vice versa in three-trophic-level systems. As the Tibetan Plateau is warming about three times faster than the global average, our results imply that warming could have a considerable impact on the structure and function of Tibetan lake ecosystems, either via indirect effects of salinization/desalinization on species richness, composition and trophic structure or through direct effects of water temperature on trophic interactions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Zooplankton abundance, species composition and ecology of tropical high-mountain crater lake Wonchi, Ethiopia

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Fasil Degefu

2014-11-01

Full Text Available The highlands of Ethiopia represent some of the remnants of undisturbed aquatic ecosystems; they are however highly threatened by significant socio–economic developments and associated anthropogenic impacts. Lake Wonchi is one of the few remaining fairly pristine high–mountain crater lakes in the central highlands and has never been investigated in detail. We present a first study on zooplankton taxa composition, abundance and biomass conducted over more than one year including the underlying environmental drivers. The lake is basic (pH 7.9-8.9, dilute (specific conductivity 185-245 µS cm-1 and oligotrophic with mean trophic status index of 36. The zooplankton community composition showed low species richness comprising a total of fourteen taxa with six cladocerans, one copepod and seven rotifers. Simpson´s index of diversity with values between 0.6 and 0.8 pointed towards a homogenous taxa occurrence within the single sample units. The overall mean (±SD standing biomass of zooplankton was 62.02±25.76 mg dry mass m-3,which is low compared to other highland and rift valley lakes in Ethiopia. Cyclopoid copepods, in particular Thermocyclops ethiopiensis were the most abundant group and contributed 50% to the total zooplankton abundance followed by cladocerans (38% and rotifers (12%. Non-metric multi-dimensional scaling resulted in a 3-dimensional model, which revealed similar community composition on successive sampling dates except in December/January and May. Temperature, alkalinity, conductivity and nitrate-N had significant influence on this seasonal pattern. A weak, but significant positive correlation (r=0.482, N=20, P=0.037 between Chlorophyll a and zooplankton biomass mirrors a bottom-up effect of phytoplankton biomass on zooplankton dynamics. The zooplankton of Lake Wonchi displayed some degree of segregation along the epi– and metalimnion during this study, but diel vertical migration was not observed. The results show that fish

Implementation of the zooplankton functional response in plankton models: State of the art, recent challenges and future directions

Science.gov (United States)

Morozov, Andrew; Poggiale, Jean-Christophe; Cordoleani, Flora

2012-09-01

The conventional way of describing grazing in plankton models is based on a zooplankton functional response framework, according to which the consumption rate is computed as the product of a certain function of food (the functional response) and the density/biomass of herbivorous zooplankton. A large amount of literature on experimental feeding reports the existence of a zooplankton functional response in microcosms and small mesocosms, which goes a long way towards explaining the popularity of this framework both in mean-field (e.g. NPZD models) and spatially resolved models. On the other hand, the complex foraging behaviour of zooplankton (feeding cycles) as well as spatial heterogeneity of food and grazer distributions (plankton patchiness) across time and space scales raise questions as to the existence of a functional response of herbivores in vivo. In the current review, we discuss limitations of the ‘classical’ zooplankton functional response and consider possible ways to amend this framework to cope with the complexity of real planktonic ecosystems. Our general conclusion is that although the functional response of herbivores often does not exist in real ecosystems (especially in the form observed in the laboratory), this framework can be rather useful in modelling - but it does need some amendment which can be made based on various techniques of model reduction. We also show that the shape of the functional response depends on the spatial resolution (‘frame’) of the model. We argue that incorporating foraging behaviour and spatial heterogeneity in plankton models would not necessarily require the use of individual based modelling - an approach which is now becoming dominant in the literature. Finally, we list concrete future directions and challenges and emphasize the importance of a closer collaboration between plankton biologists and modellers in order to make further progress towards better descriptions of zooplankton grazing.

Migrant biomass and respiratory carbon flux by zooplankton and micronekton in the subtropical northeast Atlantic Ocean (Canary Islands)

Science.gov (United States)

Ariza, A.; Garijo, J. C.; Landeira, J. M.; Bordes, F.; Hernández-León, S.

2015-05-01

Diel Vertical Migration (DVM) in marine ecosystems is performed by zooplankton and micronekton, promoting a poorly accounted export of carbon to the deep ocean. Major efforts have been made to estimate carbon export due to gravitational flux and to a lesser extent, to migrant zooplankton. However, migratory flux by micronekton has been largely neglected in this context, due to its time-consuming and difficult sampling. In this paper, we evaluated gravitational and migratory flux due to the respiration of zooplankton and micronekton in the northeast subtropical Atlantic Ocean (Canary Islands). Migratory flux was addressed by calculating the biomass of migrating components and measuring the electron transfer system (ETS) activity in zooplankton and dominant species representing micronekton (Euphausia gibboides, Sergia splendens and Lobianchia dofleini). Our results showed similar biomass in both components. The main taxa contributing to DVM within zooplankton were juvenile euphausiids, whereas micronekton were mainly dominated by fish, followed by adult euphausiids and decapods. The contribution to respiratory flux of zooplankton (3.4 ± 1.9 mg C m-2 d-1) was similar to that of micronekton (2.9 ± 1.0 mg C m-2 d-1). In summary, respiratory flux accounted for 53% (range 23-71) of the gravitational flux measured at 150 m depth (11.9 ± 5.8 mg C m-2 d-1). However, based on larger migratory ranges and gut clearance rates, micronekton are expected to be the dominant component that contributes to carbon export in deeper waters. Micronekton estimates in this paper as well as those in existing literature, although variable due to regional differences and difficulties in calculating their biomass, suggest that carbon fluxes driven by this community are important for future models of the biological carbon pump.

TIME SERIES ANALYSIS USING A UNIQUE MODEL OF TRANSFORMATION

Directory of Open Access Journals (Sweden)

Goran Klepac

2007-12-01

Full Text Available REFII1 model is an authorial mathematical model for time series data mining. The main purpose of that model is to automate time series analysis, through a unique transformation model of time series. An advantage of this approach of time series analysis is the linkage of different methods for time series analysis, linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. It is worth mentioning that REFII model is not a closed system, which means that we have a finite set of methods. At first, this is a model for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in a domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analysis. The advantage of REFII model is its possible application in many different areas such as finance, medicine, voice recognition, face recognition and text mining.

Seasonal variation of zooplankton abundance and community structure in Prince William Sound, Alaska, 2009-2016

Science.gov (United States)

McKinstry, Caitlin A. E.; Campbell, Robert W.

2018-01-01

Large calanoid copepods and other zooplankters comprise the prey field for ecologically and economically important predators such as juvenile pink salmon, herring, and seabirds in Prince William Sound (PWS).​ From 2009-2016, the Gulf Watch Alaska program collected zooplankton 5-10 times each year at 12 stations in PWS to establish annual patterns. Surveys collected 188 species of zooplankton with Oithona similis, Limacina helicina, Pseudocalanus spp., and Acartia longiremis as the most common species present in 519 samples. Generalized additive models assessed seasonal abundance and showed peak abundance in July (mean: 9826 no. m-3 [95% CI: 7990-12,084]) and lowest abundance in January (503 no. m-3 [373 to 678]). Significantly higher zooplankton abundance occurred in 2010 (542 no. m-3 ± 55 SE) and lowest in 2013 (149 no. m-3 ± 13). The species composition of communities, determined via hierarchical cluster analysis and indicator species analysis, produced six distinct communities based on season and location. The winter community, characterized by warm-water indicator species including Mesocalanus tenuicornis, Calanus pacificus, and Corycaeus anglicus, diverged into four communities throughout the spring and summer. The first spring community, characterized by copepods with affinities for lower salinities, occurred sound-wide. The second spring community, comprised of planktonic larvae, appeared sporadically in PWS bays in 2011-2013. Spring and summer open water stations were defined by the presence of large calanoid copepods. A summer community including the most abundant taxa was common in 2010 and 2011, absent in 2013, then sporadically appeared in 2014 and 2015 suggesting interannual variability of zooplankton assemblages. The zooplankton community shifted to a uniform assemblage characterized by cnidarians in the early autumn. Community assemblages showed significant correlations to a set of environmental variables including SST, mixed layer depth

Frontiers in Time Series and Financial Econometrics

OpenAIRE

Ling, S.; McAleer, M.J.; Tong, H.

2015-01-01

__Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contrib...

Ecological factors affecting the distribution of zooplankton ...

African Journals Online (AJOL)

USER

and ecological functioning of aquatic ecosystems, which must be taken into account ... zooplankton, which is its key position in the trophic chain, gives a fundamental role ..... suspended solids can block the filtering apparatus and impede their ...

Terrestrial carbohydrates support freshwater zooplankton during phytoplankton deficiency.

Science.gov (United States)

Taipale, Sami J; Galloway, Aaron W E; Aalto, Sanni L; Kahilainen, Kimmo K; Strandberg, Ursula; Kankaala, Paula

2016-08-11

Freshwater food webs can be partly supported by terrestrial primary production, often deriving from plant litter of surrounding catchment vegetation. Although consisting mainly of poorly bioavailable lignin, with low protein and lipid content, the carbohydrates from fallen tree leaves and shoreline vegetation may be utilized by aquatic consumers. Here we show that during phytoplankton deficiency, zooplankton (Daphnia magna) can benefit from terrestrial particulate organic matter by using terrestrial-origin carbohydrates for energy and sparing essential fatty acids and amino acids for somatic growth and reproduction. Assimilated terrestrial-origin fatty acids from shoreline reed particles exceeded available diet, indicating that Daphnia may convert a part of their dietary carbohydrates to saturated fatty acids. This conversion was not observed with birch leaf diets, which had lower carbohydrate content. Subsequent analysis of 21 boreal and subarctic lakes showed that diet of herbivorous zooplankton is mainly based on high-quality phytoplankton rich in essential polyunsaturated fatty acids. The proportion of low-quality diets (bacteria and terrestrial particulate organic matter) was <28% of the assimilated carbon. Taken collectively, the incorporation of terrestrial carbon into zooplankton was not directly related to the concentration of terrestrial organic matter in experiments or lakes, but rather to the low availability of phytoplankton.

Indicator Properties of Baltic Zooplankton for Classification of Environmental Status within Marine Strategy Framework Directive.

Science.gov (United States)

Gorokhova, Elena; Lehtiniemi, Maiju; Postel, Lutz; Rubene, Gunta; Amid, Callis; Lesutiene, Jurate; Uusitalo, Laura; Strake, Solvita; Demereckiene, Natalja

2016-01-01

The European Marine Strategy Framework Directive requires the EU Member States to estimate the level of anthropogenic impacts on their marine systems using 11 Descriptors. Assessing food web response to altered habitats is addressed by Descriptor 4 and its indicators, which are being developed for regional seas. However, the development of simple foodweb indicators able to assess the health of ecologically diverse, spatially variable and complex interactions is challenging. Zooplankton is a key element in marine foodwebs and thus comprise an important part of overall ecosystem health. Here, we review work on zooplankton indicator development using long-term data sets across the Baltic Sea and report the main findings. A suite of zooplankton community metrics were evaluated as putative ecological indicators that track community state in relation to Good Environmental Status (GES) criteria with regard to eutrophication and fish feeding conditions in the Baltic Sea. On the basis of an operational definition of GES, we propose mean body mass of zooplankton in the community in combination with zooplankton stock measured as either abundance or biomass to be applicable as an integrated indicator that could be used within the Descriptor 4 in the Baltic Sea. These metrics performed best in predicting zooplankton being in-GES when considering all datasets evaluated. However, some other metrics, such as copepod biomass, the contribution of copepods to the total zooplankton biomass or biomass-based Cladocera: Copepoda ratio, were equally reliable or even superior in certain basin-specific assessments. Our evaluation suggests that in several basins of the Baltic Sea, zooplankton communities currently appear to be out-of-GES, being comprised by smaller zooplankters and having lower total abundance or biomass compared to the communities during the reference conditions; however, the changes in the taxonomic structure underlying these trends vary widely across the sea basins due to

Scale-dependent intrinsic entropies of complex time series.

Science.gov (United States)

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

Elements of nonlinear time series analysis and forecasting

CERN Document Server

De Gooijer, Jan G

2017-01-01

This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible...

210Po/210Pb dynamics in relation to zooplankton biomass and trophic conditions during an annual cycle in northwestern Mediterranean coastal waters.

Science.gov (United States)

Färber Lorda, Jaime; Fowler, Scott W; Miquel, Juan-Carlos; Rodriguez y Baena, Alessia; Jeffree, Ross A

2013-01-01

Monthly sampling in northwestern Mediterranean coastal waters was undertaken to better understand the relationship between zooplankton biomass and the cycling of the natural radionuclide (210)Po/(210)Pb pair during a one-year period (October 1995-November 1996). In conjunction with mesozooplankton collections and (210)Po/(210)Pb measurements in seawater, zooplankton and their fecal pellets, the biochemical composition of particulate organic matter (POM) was also examined at three depths (0, 20 and 50 m) as an indicator of trophic conditions. During May 1996, a strong zooplankton "bloom" was observed which was preceded by a prolonged increase in POM (protein + carbohydrates + lipids) starting at the end of March, and further demonstrated by a concomitant increase in the concentration of smaller particles, two features that are typical of mesotrophic waters. Simultaneous measurements of (210)Po in sea water and zooplankton showed an inverse trend between these two parameters during the sampling period, with the two lowest (210)Po concentrations in the dissolved phase of seawater coincident with the highest radionuclide concentrations in the zooplankton; however, this apparent relationship was not statistically significant over the entire year. Freshly excreted mesozooplankton and salp fecal pellets, which have been strongly implicated in the removal and downward transport of these radionuclides from the upper water column, contained (210)Po and (210)Pb levels ranging from 175 to 878 and 7.5-486 Bq kg(-1) dry weight, respectively. Salp pellets contained 5 and 10 times more (210)Po and (210)Pb than in fecal pellets produced by mixed zooplankton, a finding most likely related to their different feeding strategies. During the zooplankton biomass peak observed in May, the (210)Po concentration in zooplankton was at a minimum; however, in contrast to what has been reported to occur in some open sea oligotrophic waters, over the year no statistically significant inverse

An Energy-Based Similarity Measure for Time Series

Directory of Open Access Journals (Sweden)

Pierre Brunagel

2007-11-01

Full Text Available A new similarity measure, called SimilB, for time series analysis, based on the cross-ΨB-energy operator (2004, is introduced. ΨB is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED or the Pearson correlation coefficient (CC, SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of ΨB are presented. Particularly, we show that ΨB as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.

Considerations on the biochemical composition of some freshwater zooplankton species.

Directory of Open Access Journals (Sweden)

Nicoletta RICCARDI

1999-02-01

Full Text Available The mean elemental (C, H, N and biochemical composition (lipids, carbohydrates and proteins of some abundant crustacean zooplankton species of Italian insubric lakes has been estimated by the analysis of samples collected at different seasons from various environments (Lake Maggiore, Lake Varese, Lake Comabbio, Lake Monate. From each sample an adequate number of specimens of each abundant species was sorted and analyzed by a CHN elemental analyzer. The percentage of lipids, carbohydrates and proteins and the calorific content were calculated from the elemental composition according to Gnaiger & Bitterlich (1984. Inter- and intraspecific variability of biochemical composition was quite high, while elemental composition and calorific content were less variable. An estimate of the mean elemental and biochemical composition of each species was obtained by pooling the data. These mean values have been used to estimate the pools of elements and compounds in the crustacean zooplankton of Lake Comabbio to provide an example of the importance of a multiple approach in zooplankton studies.

Detecting chaos in irregularly sampled time series.

Science.gov (United States)

Kulp, C W

2013-09-01

Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a time series' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other time series characterization algorithms, requires that the time series be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled time series. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled time series. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars.

Building Chaotic Model From Incomplete Time Series

Science.gov (United States)

Siek, Michael; Solomatine, Dimitri

2010-05-01

This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual

Multivariate Time Series Search

Data.gov (United States)

National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

Analysing Stable Time Series

National Research Council Canada - National Science Library

Adler, Robert

1997-01-01

We describe how to take a stable, ARMA, time series through the various stages of model identification, parameter estimation, and diagnostic checking, and accompany the discussion with a goodly number...

Neural Network Models for Time Series Forecasts

OpenAIRE

Tim Hill; Marcus O'Connor; William Remus

1996-01-01

Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R. Winkler. 1982. The accuracy of extrapolation (time series) methods: Results of a ...

Zooplankton data: Vertical distributions of zooplankton in the Norweigian and Greenland Seas during summer, 1989

Energy Technology Data Exchange (ETDEWEB)

Lane, P.V.Z.; Smith, S.L.; Schwarting, E.M.

1993-08-01

Recent studies of zooplankton populations in the Greenland Sea have focused on processes at the Marginal Ice Zone (MIZ) and the areas immediately adjacent to it under the ice and in open water. These studies have shown a relatively short period of intense secondary productivity which is closely linked temporally and spatially to phytoplankton blooms occurring near the ice edge in spring and early summer. During the summer of 1989 we participated in a project focusing on benthic and water column processes in the basins of the Norwegian and Greenland Seas. This study allowed us to compare biological processes at the MIZ with those occurring in the open waters of the Greenland Sea, and to compare processes at both of these locations with those in the Norwegian Sea. The data presented in this report are the results of zooplankton net tows covering the upper 1000 meters of the water column over the Norwegian Sea basin and the Greenland Sea basin, and the upper 500 meters of open water adjacent to the MIZ in the Greenland Sea. Sampling was conducted between 12 and 29 July 1989.

Time Series Observations in the North Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Shenoy, D.M.; Naik, H.; Kurian, S.; Naqvi, S.W.A.; Khare, N.

Ocean and the ongoing time series study (Candolim Time Series; CaTS) off Goa. In addition, this article also focuses on the new time series initiative in the Arabian Sea and the Bay of Bengal under Sustained Indian Ocean Biogeochemistry and Ecosystem...

Zooplankton ecology of the mangrove habitats of Goa

Digital Repository Service at National Institute of Oceanography (India)

Goswami, S.C.

and fish larvae constituted bulk of zooplankton. Majority of these organisms were stragglers. The zooplankters showing better eco-physiological adaptations colonized in pools surroundEd. by thick mangroves vegetation...

Zooplankton Distribution and Species Composition Along an Oxygen Gradient in Puget Sound, WA

Science.gov (United States)

Keister, J. E.; Essington, T.; Li, L.; Horne, J. K.; Sato, M.; Parker-Stetter, S. L.; Moriarty, P.

2016-02-01

Low dissolved oxygen (hypoxia) is one of the most pronounced, pervasive, and significant disturbances in marine ecosystems, yet our understanding of its effects is incomplete, particularly with respect to impacts on lower trophic levels. As part of a study of how hypoxia affects predator-prey relationships and energy flow through marine food webs, we are studying relationships between ocean chemistry and zooplankton in Puget Sound, Washington—a deep, seasonally hypoxic fjord in the Pacific Northwest that supports a productive and diverse pelagic community. From summer through fall in two years that differed in the timing and intensity of hypoxia, we conducted multi-frequency bioacoustic surveys, CTD casts, and depth-stratified zooplankton sampling to examine changes in distribution and species composition of animals in relation to oxygen concentrations. We exploited a natural gradient in oxygen along the axis of the fjord by sampling at moderately hypoxic and normoxic sites with otherwise similar hydrography and species composition to disentangle the effects of oxygen from changes in other environmental factors. Our results support the hypothesis that zooplankton species composition and vertical distributions are altered by hypoxia, but only when examined at the species and life-stage level. Relatively few taxa showed clear responses to hypoxia, and bioacoustic backscatter data (which was dominated by adult euphausiids and amphipods) indicated that those taxa were not affected by the levels of hypoxia we observed. Examination of net tow data revealed more subtle changes, including behavioral avoidance of low oxygen by some copepods and young euphausiid life stages. Overall, the high species diversity and relatively low susceptibility of many zooplankton to hypoxia in Puget Sound may confer ecosystem resilience to near-future projected changes in this region.

ZOOPLANKTON COMMUNITY STRUCTURE OF THE SEA SURFACE MICROLAYER NEAR NUCLEAR POWER PLANTS AND MARINE FISH CULTURE ZONES IN DAYA BAY

Institute of Scientific and Technical Information of China (English)

杨宇峰; 王肇鼎; 潘明祥; 焦念志

2002-01-01

The authors' surveys in May-June 1999 (two cruises) at six sampling stations near nuclear power plants (NPP) and marine fish culture zones in Daya Bay, Guangdong, revealed species composition, densities and body-size of thesea surface microlayer (SM) zooplankton (>35 μm). Results showed that protozoans and copepod nauplii were the predominant components, accounting for 65.40% to95.56% of total zooplankton in abundance. The size-frequency distributions showed that the frequency of micro-zooplankton (0.02-0.2 mm) reached 0.8235. The SM zooplankton community structure revealed in the present study was quite different from that revealed by investigations in the 1980s in Daya Bay. Difference of sampling method has important influence on the obtained zooplankton community structure. SM zooplankton consisted of micro- and mesozooplankton (0.2-2.0 mm), with micro-zooplankton being predominant. Some possible cause-effect relations between the zooplankton community structure and mariculture, nuclear power plants cooling systems and sampling method are discussed.``

Geometric noise reduction for multivariate time series.

Science.gov (United States)

Mera, M Eugenia; Morán, Manuel

2006-03-01

We propose an algorithm for the reduction of observational noise in chaotic multivariate time series. The algorithm is based on a maximum likelihood criterion, and its goal is to reduce the mean distance of the points of the cleaned time series to the attractor. We give evidence of the convergence of the empirical measure associated with the cleaned time series to the underlying invariant measure, implying the possibility to predict the long run behavior of the true dynamics.

BRITS: Bidirectional Recurrent Imputation for Time Series

OpenAIRE

Cao, Wei; Wang, Dong; Li, Jian; Zhou, Hao; Li, Lei; Li, Yitan

2018-01-01

Time series are widely used as signals in many classification/regression tasks. It is ubiquitous that time series contains many missing values. Given multiple correlated time series data, how to fill in missing values and to predict their class labels? Existing imputation methods often impose strong assumptions of the underlying data generating process, such as linear dynamics in the state space. In this paper, we propose BRITS, a novel method based on recurrent neural networks for missing va...

Efficient Algorithms for Segmentation of Item-Set Time Series

Science.gov (United States)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

Studies on time series applications in environmental sciences

CERN Document Server

Bărbulescu, Alina

2016-01-01

Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code. .

Global Population Density Grid Time Series Estimates

Data.gov (United States)

National Aeronautics and Space Administration — Global Population Density Grid Time Series Estimates provide a back-cast time series of population density grids based on the year 2000 population grid from SEDAC's...

Prediction and Geometry of Chaotic Time Series

National Research Council Canada - National Science Library

Leonardi, Mary

1997-01-01

This thesis examines the topic of chaotic time series. An overview of chaos, dynamical systems, and traditional approaches to time series analysis is provided, followed by an examination of state space reconstruction...

Zooplankton community of Parnaíba River, Northeastern Brazil

Directory of Open Access Journals (Sweden)

Ludmilla Cavalcanti Antunes Lucena

2015-03-01

Full Text Available Aim:The objective of the present work is to present a list of species of zooplankton (Rotifera, Cladocera and Copepoda from the Parnaíba River. Additionally, we provide comments on their distribution along the river, and between dry and wet seasons.MethodsZooplankton was collected with a plankton net (60 µm mesh and concentrated into a volume of 80 mL for further analysis, during the dry (October 2010 and wet (April 2011 seasons. Sampling was restricted to the marginal areas at depths between 80 and 150 cm.ResultsA total of 132 species was recorded among the three zooplankton groups studied. During the dry season a total of 82 species was registered and 102 species was registered for the wet season. Rotifera contributed with 66.7% of the species, followed by Cladocera (26.5% and Copepoda (6.8%.ConclusionsThe richness of species observed was high compared to other large rivers in Brazil. In the context of current policies for water management and river diversions in northeastern Brazil, the present study highlights the importance of this river system for biodiversity conservation.

Sensor-Generated Time Series Events: A Definition Language

Science.gov (United States)

Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

2012-01-01

There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

Zooplankton standing stock and composition in coastal waters of Goa, west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Goswami, S.C.

Temporal and spatial variability in standing stock and zooplankton composition at 5 stations along the Goa Coast, India during 1975-76 were studied. Standing stock values ranged from 22.81 to 53.65 mg C.m/3. Zooplankton community was diverse...

Distribution of toxic metals, Hg, Cd and Pb in zooplankton along the Indian coasts

Digital Repository Service at National Institute of Oceanography (India)

Sengupta, R.; Kureishy, T.W.

Distribution of toxic metals such as Hg, Cd and Pb in zooplankton is assessed with a view to correlate it with the prevalent environmental conditions along the Indian coast. While Hg could not be detected in zooplankton the concentrations of Cd...

impact of physicochemical factors on zooplankton species richness

African Journals Online (AJOL)

DR. AMINU

This study revealed that physicochemical fluctuations was negative impact on the zooplankton species ... of convergence of wastewater streams, of which Jakara River carries ..... Discharge on Physicochemical Parameters and Some Heavy ...

Nonresonant Double Hopf Bifurcation in Toxic Phytoplankton-Zooplankton Model with Delay

Science.gov (United States)

Yuan, Rui; Jiang, Weihua; Wang, Yong

This paper investigates a toxic phytoplankton-zooplankton model with Michaelis-Menten type phytoplankton harvesting. The model has rich dynamical behaviors. It undergoes transcritical, saddle-node, fold, Hopf, fold-Hopf and double Hopf bifurcation, when the parameters change and go through some of the critical values, the dynamical properties of the system will change also, such as the stability, equilibrium points and the periodic orbit. We first study the stability of the equilibria, and analyze the critical conditions for the above bifurcations at each equilibrium. In addition, the stability and direction of local Hopf bifurcations, and the completion bifurcation set by calculating the universal unfoldings near the double Hopf bifurcation point are given by the normal form theory and center manifold theorem. We obtained that the stable coexistent equilibrium point and stable periodic orbit alternate regularly when the digestion time delay is within some finite value. That is, we derived the pattern for the occurrence, and disappearance of a stable periodic orbit. Furthermore, we calculated the approximation expression of the critical bifurcation curve using the digestion time delay and the harvesting rate as parameters, and determined a large range in terms of the harvesting rate for the phytoplankton and zooplankton to coexist in a long term.

Interannual abundance changes of gelatinous carnivore zooplankton unveil climate-driven hydrographic variations in the Iberian Peninsula, Portugal.

Science.gov (United States)

D'Ambrosio, Mariaelena; Molinero, Juan C; Azeiteiro, Ulisses M; Pardal, Miguel A; Primo, Ana L; Nyitrai, Daniel; Marques, Sónia C

2016-09-01

The persistent massive blooms of gelatinous zooplankton recorded during recent decades may be indicative of marine ecosystem changes. In this study, we investigated the potential influence of the North Atlantic climate (NAO) variability on decadal abundance changes of gelatinous carnivore zooplankton in the Mondego estuary, Portugal, over the period 2003-2013. During the 11-year study, the community of gelatinous carnivores encompassed a larger diversity of hydromedusae than siphonophores; the former dominated by Obelia spp., Lizzia blondina, Clythia hemisphaerica, Liriope tetraphylla and Solmaris corona, while the latter dominated by Muggiaea atlantica. Gelatinous carnivore zooplankton displayed marked interannual variability and mounting species richness over the period examined. Their pattern of abundance shifted towards larger abundances ca. 2007 and significant phenological changes. The latter included a shift in the mean annual pattern (from unimodal to bimodal peak, prior and after 2007 respectively) and an earlier timing of the first annual peak concurrent with enhanced temperatures. These changes were concurrent with the climate-driven environmental variability mainly controlled by the NAO, which displayed larger variance after 2007 along with an enhanced upwelling activity. Structural equation modelling allowed depicting cascading effects derived from the NAO influence on regional climate and upwelling variability further shaping water temperature. Such cascading effect percolated the structure and dynamics of the community of gelatinous carnivore zooplankton in the Mondego estuary. Copyright © 2016 Elsevier Ltd. All rights reserved.

Correlation and multifractality in climatological time series

International Nuclear Information System (INIS)

Pedron, I T

2010-01-01

Climate can be described by statistical analysis of mean values of atmospheric variables over a period. It is possible to detect correlations in climatological time series and to classify its behavior. In this work the Hurst exponent, which can characterize correlation and persistence in time series, is obtained by using the Detrended Fluctuation Analysis (DFA) method. Data series of temperature, precipitation, humidity, solar radiation, wind speed, maximum squall, atmospheric pressure and randomic series are studied. Furthermore, the multifractality of such series is analyzed applying the Multifractal Detrended Fluctuation Analysis (MF-DFA) method. The results indicate presence of correlation (persistent character) in all climatological series and multifractality as well. A larger set of data, and longer, could provide better results indicating the universality of the exponents.

Mercury concentration variability in the zooplankton of the southern Baltic coastal zone

Science.gov (United States)

Bełdowska, Magdalena; Mudrak-Cegiołka, Stella

2017-12-01

Being a toxic element, mercury is introduced to the human organism through the consumption of fish and seafood, which in turn often feed on zooplankton. The bioaccumulation of Hg by zooplankton is an important factor influencing the magnitude of the mercury load introduced with food into the predator organism. Therefore the present article attempts to identify the processes and factors influencing Hg concentration in the zooplankton of the coastal zone, an area where marine organisms - an attractive food source for humans - thrive. This is particularly important in areas where climate changes influence the species composition and quantity of plankton. The studies were carried out on three test sites in the coastal zone of the southern Baltic Sea in the period from December 2011 to May 2013. The obtained results show that the shorting of the winter season is conducive to Hg increase in zooplankton and, consequently, in the trophic chain. High mercury concentrations were measured in genus Synchaeta and Keratella when Mesodinium rubrum were predominant in phytoplankton, while other sources of this metal in the plankton fauna were epilithon, epiphton and microbenthos. This is of particular importance when it comes to sheltered bays and estuaries with low water dynamics.

Acoustic discrimination of Southern Ocean zooplankton

Science.gov (United States)

Brierley, Andrew S.; Ward, Peter; Watkins, Jonathan L.; Goss, Catherine

Acoustic surveys in the vicinity of the sub-Antarctic island of South Georgia during a period of exceptionally calm weather revealed the existence of a number of horizontally extensive yet vertically discrete scattering layers in the upper 250 m of the water column. These layers were fished with a Longhurst-Hardy plankton recorder (LHPR) and a multiple-opening 8 m 2 rectangular mid-water trawl (RMT8). Analysis of catches suggested that each scattering layer was composed predominantly of a single species (biovolume>95%) of either the euphausiids Euphausia frigida or Thysanöessa macrura, the hyperiid amphipod Themisto gaudichaudii, or the eucalaniid copepod Rhincalanus gigas. Instrumentation on the nets allowed their trajectories to be reconstructed precisely, and thus catch data to be related directly to the corresponding acoustic signals. Discriminant function analysis of differences between mean volume backscattering strength at 38, 120 and 200 kHz separated echoes originating from each of the dominant scattering layers, and other signals identified as originating from Antarctic krill ( Euphausia superba), with an overall correct classification rate of 77%. Using echo intensity data alone, gathered using hardware commonly employed for fishery acoustics, it is therefore possible to discriminate in situ between several zooplanktonic taxa, taxa which in some instances exhibit similar gross morphological characteristics and have overlapping length- frequency distributions. Acoustic signals from the mysid Antarctomysis maxima could also be discriminated once information on target distribution was considered, highlighting the value of incorporating multiple descriptors of echo characteristics into signal identification procedures. The ability to discriminate acoustically between zooplankton taxa could be applied to provide improved acoustic estimates of species abundance, and to enhance field studies of zooplankton ecology, distribution and species interactions.

Time Series Forecasting with Missing Values

Directory of Open Access Journals (Sweden)

Shin-Fu Wu

2015-11-01

Full Text Available Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, on the other hand, may alter the original time series. In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM. We employ the input patterns with the temporal information which is defined as local time index (LTI. Time series data as well as local time indexes are fed to LSSVM for doing forecasting without imputation. We compare the forecasting performance of our method with other imputation methods. Experimental results show that the proposed method is promising and is worth further investigations.

Impacts of algal blooms removal by chitosan-modified soils on zooplankton community in Taihu Lake,China

Institute of Scientific and Technical Information of China (English)

Jiajia Ni; Yuhe Yu; Weisong Feng; Qingyun Yan; Gang pan; Bo Yang; Xiang Zhang; Xuemei Li

2010-01-01

It is important to assess the effect on zooplankton when perform the environmental protection or restoration technology,especially removing algal blooms,because algae were the major primary producer in algal lakes.The influence on zooplankton community after half a year of algal blooms removed by chitosan-modified soils in Taihu Lake was assessed and the rationality of carrying out the process semiannually was evaluated in the present study.Morphological composition and genetic diversity of zooplankton community were investigated by microscope checkup and polymerase chain reaction-denatured gradient gel electrophoresis (PCR-DGGE).A total of 44 zooplankton taxa (23 protozoa,17 rotifers,3 copepoda and 1 cladocera) were detected by microscope checkup,and a total of 91 bands (28 bands amplified by primers F1427-GC and R1616,63 bands amplified by primers Fung-G-C and NS1) were detected by PCR-DGGE.The results of cluster analysis or detrended correspondence analysis indicated that there was no considerable difference in morphological composition of zooplankton and DGGE profiles between experimental and control sites,and DGGE profiles could represent the biologic diversity.The study showed that zooplankton community could recover original condition after half year of algal blooms removed by chitosan-modified soils and it was acceptable to apply this process semiannually.In addition,the results revealed that PCR-DGGE could be applied to investigate the impacts of the environmental protection or restoration engineering on zooplankton community diversity.

The effects of juvenile American shad planktivory on zooplankton production in Columbia River food webs

Science.gov (United States)

Haskell, Craig A.; Tiffan, Kenneth F.; Rondorf, Dennis W.

2013-01-01

Columbia River reservoirs support a large population of nonnative American Shad Alosa sapidissima that consume the zooplankton that native fishes also rely on. We hypothesized that the unprecedented biomass of juvenile American Shad in John Day Reservoir is capable of altering the zooplankton community if these fish consume a large portion of the zooplankton production. We derived taxon-specific estimates of zooplankton production using field data and a production model from the literature. Empirical daily ration was estimated for American Shad and expanded to population-level consumption using abundance and biomass data from hydroacoustic surveys. Daphnia spp. production was high in early summer but declined to near zero by September as shad abundance increased. American Shad sequentially consumed Daphnia spp., copepods, and Bosmina spp., which tracked the production trends of these taxa. American Shad evacuation rates ranged from 0.09 to 0.24/h, and daily rations ranged from 0.008 to 0.045 g·g−1·d−1 (dry weight) over all years. We observed peak American Shad biomass (45.2 kg/ha) in 1994, and daily consumption (1.6 kg/ha) approached 30% (5.3 kg/ha) of zooplankton production. On average, American Shad consumed 23.6% of the available zooplankton production (range, food web in John Day Reservoir, potentially affecting native fishes, including Pacific salmon Oncorhynchus spp.

Reconstruction of ensembles of coupled time-delay systems from time series.

Science.gov (United States)

Sysoev, I V; Prokhorov, M D; Ponomarenko, V I; Bezruchko, B P

2014-06-01

We propose a method to recover from time series the parameters of coupled time-delay systems and the architecture of couplings between them. The method is based on a reconstruction of model delay-differential equations and estimation of statistical significance of couplings. It can be applied to networks composed of nonidentical nodes with an arbitrary number of unidirectional and bidirectional couplings. We test our method on chaotic and periodic time series produced by model equations of ensembles of diffusively coupled time-delay systems in the presence of noise, and apply it to experimental time series obtained from electronic oscillators with delayed feedback coupled by resistors.

The analysis of time series: an introduction

National Research Council Canada - National Science Library

Chatfield, Christopher

1989-01-01

.... A variety of practical examples are given to support the theory. The book covers a wide range of time-series topics, including probability models for time series, Box-Jenkins forecasting, spectral analysis, linear systems and system identification...

Time series modeling in traffic safety research.

Science.gov (United States)

Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

2018-08-01

The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

Time series prediction: statistical and neural techniques

Science.gov (United States)

Zahirniak, Daniel R.; DeSimio, Martin P.

1996-03-01

In this paper we compare the performance of nonlinear neural network techniques to those of linear filtering techniques in the prediction of time series. Specifically, we compare the results of using the nonlinear systems, known as multilayer perceptron and radial basis function neural networks, with the results obtained using the conventional linear Wiener filter, Kalman filter and Widrow-Hoff adaptive filter in predicting future values of stationary and non- stationary time series. Our results indicate the performance of each type of system is heavily dependent upon the form of the time series being predicted and the size of the system used. In particular, the linear filters perform adequately for linear or near linear processes while the nonlinear systems perform better for nonlinear processes. Since the linear systems take much less time to be developed, they should be tried prior to using the nonlinear systems when the linearity properties of the time series process are unknown.

Effectiveness of Multivariate Time Series Classification Using Shapelets

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2015-01-01

Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.

Zooplankton community structure in the Yellow Sea and East China Sea in autumn

Directory of Open Access Journals (Sweden)

Hongju Chen

2015-12-01

Full Text Available Abstract Study on zooplankton spatial distribution is essential for understanding food web dynamics in marine ecosystems and fishery management. Here we elucidated the composition and distribution of large mesozooplankton on the continental shelf of the Yellow Sea and East China Sea, and explored the zooplankton community structure in these water masses. Sixty vertical hauls (bottom or 200 m in deep water to surface using a ring net (diameter 0.8 m, 505-μm mesh were exploited in November 2007. The biogeographic patterns of zooplankton communities were investigated using multivariate analysis methods; copepod biodiversity was analyzed using univariate indices. Copepods and protozoans were dominate in the communities. Based on the species composition, we divided the study areas into six station groups. Significant differences in zooplankton assemblages were detected between the Yellow Sea and East China Sea. Species richness was higher in East China Sea groups than those in Yellow Sea, whereas taxonomic distinctness was higher in Yellow Sea than in East China Sea. There was a clear relationship between the species composition and water mass group.

Zooplankton in littoral waters of a tropical lake: a revisited biodiversity

Directory of Open Access Journals (Sweden)

PM. Maia-Barbosa

Full Text Available The present study was carried out in Lake Dom Helvécio, in the state of Minas Gerais, with two main objectives: to demonstrate the contribution of the littoral zone, in order to better characterize zooplankton fauna; and to assess the distribution of zooplankton species in different habitats, i.e., the littoral zone with and without aquatic vegetation. The samples were collected in February and July 2006, throughout the littoral zone of the lake, in areas with and without aquatic vegetation. We identified a total of 188 species, of which 130 are new records for Lake Dom Helvécio. One hundred and eighty-four species were identified in the littoral zone with aquatic vegetation, and 117 in the zone with no vegetation. The higher zooplankton richness in areas of the littoral zone with aquatic vegetation can be related to the greater environmental heterogeneity. Compared to previous studies on the littoral zones of lakes along the middle River Doce, the present study expended greater sampling effort, and identified many more species. In relation to biological conservation, this study demonstrated the importance of the littoral zone for better characterization and conservation of the zooplankton fauna, especially when it is colonized by aquatic vegetation. Underestimating the richness of species may provide inaccurate data on the biota, as well as on the ecological conditions in an environment.

Time-series-analysis techniques applied to nuclear-material accounting

International Nuclear Information System (INIS)

Pike, D.H.; Morrison, G.W.; Downing, D.J.

1982-05-01

This document is designed to introduce the reader to the applications of Time Series Analysis techniques to Nuclear Material Accountability data. Time series analysis techniques are designed to extract information from a collection of random variables ordered by time by seeking to identify any trends, patterns, or other structure in the series. Since nuclear material accountability data is a time series, one can extract more information using time series analysis techniques than by using other statistical techniques. Specifically, the objective of this document is to examine the applicability of time series analysis techniques to enhance loss detection of special nuclear materials. An introductory section examines the current industry approach which utilizes inventory differences. The error structure of inventory differences is presented. Time series analysis techniques discussed include the Shewhart Control Chart, the Cumulative Summation of Inventory Differences Statistics (CUSUM) and the Kalman Filter and Linear Smoother

Clinical and epidemiological rounds. Time series

Directory of Open Access Journals (Sweden)

León-Álvarez, Alba Luz

2016-07-01

Full Text Available Analysis of time series is a technique that implicates the study of individuals or groups observed in successive moments in time. This type of analysis allows the study of potential causal relationships between different variables that change over time and relate to each other. It is the most important technique to make inferences about the future, predicting, on the basis or what has happened in the past and it is applied in different disciplines of knowledge. Here we discuss different components of time series, the analysis technique and specific examples in health research.

Integer-valued time series

NARCIS (Netherlands)

van den Akker, R.

2007-01-01

This thesis adresses statistical problems in econometrics. The first part contributes statistical methodology for nonnegative integer-valued time series. The second part of this thesis discusses semiparametric estimation in copula models and develops semiparametric lower bounds for a large class of

Trophic structure and levels of selected metals in the zooplankton community of Thane-Bassein Creek, Bombay

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.; Krishnamurti, A.J.; Gajbhiye, S.N.

-83% to total zooplankton population. Decapods were relatively more in the outer (av. 11%) as compared to interior zone (av. 7%). Population density of carnivores were 2-4 times more in the polluted interior segment. Among the different metals studied Cu and Zn...

Robust Forecasting of Non-Stationary Time Series

NARCIS (Netherlands)

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable

On uses, misuses and potential abuses of fractal analysis in zooplankton behavioral studies: A review, a critique and a few recommendations

Science.gov (United States)

Seuront, Laurent

2015-08-01

Fractal analysis is increasingly used to describe, and provide further understanding to, zooplankton swimming behavior. This may be related to the fact that fractal analysis and the related fractal dimension D have the desirable properties to be independent of measurement scale and to be very sensitive to even subtle behavioral changes that may be undetectable to other behavioral variables. As early claimed by Coughlin et al. (1992), this creates "the need for fractal analysis" in behavioral studies, which has hence the potential to become a valuable tool in zooplankton behavioral ecology. However, this paper stresses that fractal analysis, as well as the more elaborated multifractal analysis, is also a risky business that may lead to irrelevant results, without paying extreme attention to a series of both conceptual and practical steps that are all likely to bias the results of any analysis. These biases are reviewed and exemplified on the basis of the published literature, and remedial procedures are provided not only for geometric and stochastic fractal analyses, but also for the more complicated multifractal analysis. The concept of multifractals is finally introduced as a direct, objective and quantitative tool to identify models of motion behavior, such as Brownian motion, fractional Brownian motion, ballistic motion, Lévy flight/walk and multifractal random walk. I finally briefly review the state of this emerging field in zooplankton behavioral research.

Current status of zooplankton in reservoir R-3 of the 'Mayak' production association

Energy Technology Data Exchange (ETDEWEB)

Osipova, O.; Pryakhin, E. [Urals Research Center for Radiation Medicine - URCRM (Russian Federation); Ivanov, I. [FSUE Mayak PA (Russian Federation)

2014-07-01

One of the commonly used objects for the study of human influence on aquatic ecosystems is zooplankton. Zooplankton community is a sensitive component of biota in reservoir which can change their functional parameters and species composition in response to exposure to different factors. The role of zooplankton in the transformation of energy and in the biotic cycling of the substance is very important. The study of the responses of this element in the water ecosystem with anthropogenic influences, including radioactive contamination, is an important task. The object of the study was the zooplankton in the reservoir R-3, Chelyabinsk region, Russia. R-3 is located in the buffer zone of the 'Mayak' PA and is the storage for low-level radioactive waste. In addition to the high content of radionuclides (the average specific activity of {sup 90}Sr in water was 2.8 kBq/l, {sup 137}Cs - 0.7 kBq/l), this reservoir is characterized by high values of dichromate oxidizability and phosphate contamination. Previously, the study of the zooplankton of this reservoir was conducted in 1952, regular observations were not organized. Assessment of the current status of the community, more than half a century residing in the conditions of radioactive and chemical contamination, seems highly interesting. Sampling was carried out in 2011-2012 at three stations: in the upper, middle, and near the dam of the reservoir by the method of weighted average of samples with bathometer. Analysis of samples showed that the zooplankton community consists of the following major groups: rotifers and cladocerans and copepods crustaceans. In total in R-3 27 species of zooplankton, including 19 species of rotifers, 3 species of copepod and 3 species of cladocerans, as well as two species of ciliates were discovered. Zooplankton abundance in 2011 was 9±9 million individuals/m{sup 3} (given the mean and standard deviation), in 2012 - 26.0±0.9 million individuals/m{sup 3}. The main contribution

[Phytoplankton and zooplankton of the industrial reservoir R-9 (Lake Karachay)].

Science.gov (United States)

Priakhin, E A; Triapitsina, G A; Atamaniuk, N I; Osipov, D I; Stukalov, P M; Ivanov, I A; Popova, I Ia; Akleev, A V

2012-01-01

Planktonic communities of the Reservoir-9 (Lake Karachay, storage reservoir of liquid medium-level radioactive waste of the Mayak Production Association) are exposed to the severe radioactive forcing (in 2010 the total beta-activity of the water was 1.8 x 10(7) Bq/L, total alpha-activity was 1.1 x 10(4) Bq/L), aswell as to the chemical contamination (level of nitrates in water 4.1 g/L). The calculated values of the absorbed dose rate were 130 Gy/day for phytoplankton and 4.0 Gy/day for zooplankton. Extremely low species diversity, the overwhelming dominance of one species (phytoplankton is close to a monoculture of ubiquitous cyanobacteria Geitlerinema amphibium, zooplankton--to a monoculture of rotifers Hexarthrafennica), wide fluctuations in numbers of algae, a low number of zooplankton were the most substantial characteristics of the plankton communities in Lake Karachay. So, plankton communities status is a sign of environmental retrogress in this ecosystem.

Zooplankton Distribution in Four Western Norwegian Fjords

Science.gov (United States)

Gorsky, G.; Flood, P. R.; Youngbluth, M.; Picheral, M.; Grisoni, J.-M.

2000-01-01

A multi-instrumental array constructed in the Laboratoire d'Ecologie du Plancton Marin in Villefranche sur mer, France, named the Underwater Video Profiler (UVP), was used to investigate the vertical distribution of zooplankton in four western Norwegian fjords in the summer 1996. Six distinct zoological groups were monitored. The fauna included: (a) small crustaceans (mainly copepods), (b) ctenophores (mainly lobates), (c) siphonophores (mainly physonects), (d) a scyphomedusa Periphylla periphylla, (e) chaetognaths and (f) appendicularians. The use of the non-disturbing video technique demonstrated that the distribution of large zooplankton is heterogeneous vertically and geographically. Furthermore, the abundance of non-migrating filter feeders in the deep basins of the fjords indicates that there is enough food (living and non-living particulate organic matter) to support their dietary needs. This adaptation may be considered as a strategy for survival in fjords. Specifically, living in dark, deep water reduces visual predation and population loss encountered in the upper layer due to advective processes.

Diurnal variation of zooplankton in Malad creek, Bombay

Digital Repository Service at National Institute of Oceanography (India)

Gajbhiye, S.N.; Nair, V.R.; Desai, B.N.

stock and total population were higher in night than in day collections. Abundance and diversity of zooplankton were directly correlated to the prevailing tide and pollution load. Copepods formed the predominant group followed by decapods, gastropods...

Characterizing time series via complexity-entropy curves

Science.gov (United States)

Ribeiro, Haroldo V.; Jauregui, Max; Zunino, Luciano; Lenzi, Ervin K.

2017-06-01

The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis q entropy) and after considering the proper generalization of the statistical complexity (q complexity), we build up a parametric curve (the q -complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.

Spatial patterns of littoral zooplankton assemblages along a salinity gradient in a brackish sea: A functional diversity perspective

Science.gov (United States)

Helenius, Laura K.; Leskinen, Elina; Lehtonen, Hannu; Nurminen, Leena

2017-11-01

The distribution patterns and diversity of littoral zooplankton are both key baseline information for understanding the functioning of coastal ecosystems, and for identifying the mechanisms by which the impacts of recently increased eutrophication are transferred through littoral food webs. In this study, zooplankton community structure and diversity along a shallow coastal area of the northern Baltic Sea were determined in terms of horizontal environmental gradients. Spatial heterogeneity of the zooplankton community was examined along the gradient. Altogether 31 sites in shallow sandy bays on the coast of southwest Finland were sampled in the summer periods of 2009 and 2010 for zooplankton and environmental variables (surface water temperature, salinity, turbidity, wave exposure, macrophyte coverage, chlorophyll a and nutrients). Zooplankton diversity was measured as both taxonomic as well as functional diversity, using trait-based classification of planktonic crustaceans. Salinity, and to a lesser extent turbidity and temperature, were found to be the main predictors of the spatial patterns and functional diversity of the zooplankton community. Occurrence of cyclopoid copepods, as well as abundances of the calanoid copepod genus Acartia and the rotifer genus Keratella were found to be key factors in differentiating sites along the gradient. As far as we know, this is the first extensive study of functional diversity in Baltic Sea coastal zooplankton communities.

Effect of tide on the variability of zooplankton in the nearshore waters of Thal, Maharashtra

Digital Repository Service at National Institute of Oceanography (India)

Gajbhiye, S.N; Nair, V.R.; Krishnakumari, L; Desai, B.N

Quantitative and qualitative difference in zooplankton in relation to the tide were studied along 3 transects located off Thal, Maharashtra, India during Feb. 1980 to Jan. 1981. Variation in zooplankton biomass for the flood and ebb period were 2...

Stratification of zooplankton in the northwestern Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Paulinose, V.T.; Gopalakrishnan, T.C.; Nair, K.K.C.; Aravindakshan, P.N.

Study on stratification of zooplankton in the north western Indian Ocean was carried out with special reference to its relative abundance and distribution. Samples were collected using multiple plankton net, during first cruise of ORV Sagar Kanya...

Zooplankton composition in Dharamtar creek adjoining Bombay harbour

Digital Repository Service at National Institute of Oceanography (India)

Tiwari, L.R.; Nair, V.R.

bedoti was the true inhabitant. In general zooplankton production indicated 1.5 fold increase towards the upper reaches of the creek where salinity variations were drastic. A more diversified faunal assemblage of oceanic and neritic species characterised...

Evaluation of sound extinction and echo interference in densely aggregated zooplankton

Directory of Open Access Journals (Sweden)

Natalia Gorska

2000-09-01

Full Text Available The investigation of sound extinction and echo interference is important as regards the accurate assessment of the abundance of densely aggregated zooplankton. To study these effects,the analytical model describing sound backscattering by an aggregation of isotropic scatterers (Rytov et al. 1978, Sun & Gimenez 1992 has been extended to the case of densely aggregated elongated zooplankton. The evaluation of the effects in the case of a dense krill aggregation demonstrates that they can be significant and should be taken into account.

Analyzing the trophic link between the mesopelagic microbial loop and zooplankton from observed depth profiles of bacteria and protozoa

Directory of Open Access Journals (Sweden)

T. Tanaka

2005-01-01

Full Text Available It is widely recognized that organic carbon exported to the ocean aphotic layer is significantly consumed by heterotrophic organisms such as bacteria and zooplankton in the mesopelagic layer. However, very little is known for the trophic link between bacteria and zooplankton or the function of the microbial loop in this layer. In the northwestern Mediterranean, recent studies have shown that viruses, bacteria, heterotrophic nanoflagellates, and ciliates distribute down to 2000 m with group-specific depth-dependent decreases, and that bacterial production decreases with depth down to 1000 m. Here we show that such data can be analyzed using a simple steady-state food chain model to quantify the carbon flow from bacteria to zooplankton over the mesopelagic layer. The model indicates that bacterial mortality by viruses is similar to or 1.5 times greater than that by heterotrophic nanoflagellates, and that heterotrophic nanoflagellates transfer little of bacterial production to higher trophic levels.

Complex network approach to fractional time series

Energy Technology Data Exchange (ETDEWEB)

Manshour, Pouya [Physics Department, Persian Gulf University, Bushehr 75169 (Iran, Islamic Republic of)

2015-10-15

In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacency matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.

The effects of power plant passage on zooplankton mortalities: Eight years of study at the Donald C. Cook Nuclear Plant

International Nuclear Information System (INIS)

Evans, M.S.; Warren, G.J.; Page, D.I.

1986-01-01

Zooplankton mortalities resulting from passage through the Donald C. Cook Nuclear Plant (southeastern Lake Michigan) were studied over an 8-year (1975-1982) period. The power plant operated at a low ΔT ( 0 C) and discharge water temperatures did not exceed 35 0 C (except September 1978). While zooplankton mortalities were significantly greater in discharge than intake waters, differences were small, averaging <3%. There was no evidence of additional delayed effects on zooplankton mortality following plant passage. There was no relationship between zooplankton mortalities and temperature (ΔT, discharge water temperature). Mechanical stresses appeared to be the major cause of zooplankton mortality. The authors hypothesize that fish predation, rather than power plant operation, probably was the major source of zooplankton mortality in inshore waters during much of the year. (author)

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2008-01-01

An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

Science.gov (United States)

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

Science.gov (United States)

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Dredging induced changes in zooplankton community and water ...

African Journals Online (AJOL)

user

water characteristics and zooplankton community structure in Dal Lake. An assessment was done ... et al., 2007; Zhang et al., 2010). In aquatic ecosystems, .... generally high in fine grain sediment (Fisher et al., 1982;. Valiela, 1995). In post ...

The foundations of modern time series analysis

CERN Document Server

Mills, Terence C

2011-01-01

This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.

Time series clustering in large data sets

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2011-01-01

Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.

Estuarine and marine diets of out-migrating Chinook Salmon smolts in relation to local zooplankton populations, including harmful blooms

Science.gov (United States)

Chittenden, C. M.; Sweeting, R.; Neville, C. M.; Young, K.; Galbraith, M.; Carmack, E.; Vagle, S.; Dempsey, M.; Eert, J.; Beamish, R. J.

2018-01-01

Changes in food availability during the early marine phase of wild Chinook Salmon (O. tshawytscha) are being investigated as a cause of their recent declines in the Salish Sea. The marine survival of hatchery smolts, in particular, has been poor. This part of the Salish Sea Marine Survival Project examined the diet of young out-migrating Chinook Salmon for four consecutive years in the Cowichan River estuary and in Cowichan Bay, British Columbia, Canada. Local zooplankton communities were monitored during the final year of the study in the Cowichan River estuary, Cowichan Bay, and eastward to the Salish Sea to better understand the bottom-up processes that may be affecting Chinook Salmon survival. Rearing environment affected body size, diet, and distribution in the study area. Clipped smolts (hatchery-reared) were larger than the unclipped smolts (primarily naturally-reared), ate larger prey, spent very little time in the estuary, and disappeared from the bay earlier, likely due to emigration or mortality. Their larger body size may be a disadvantage for hatchery smolts if it necessitates their leaving the estuary prematurely to meet energy needs; the onset of piscivory began at a forklength of approximately 74 mm, which was less than the average forklength of the clipped fish in this study. The primary zooplankton bloom occurred during the last week of April/first week of May 2013, whereas the main release of hatchery-reared Chinook Salmon smolts occurs each year in mid-May-this timing mismatch may reduce their survival. Gut fullness was correlated with zooplankton biomass; however, both the clipped and unclipped smolts were not observed in the bay until the bloom of harmful Noctiluca was finished-20 days after the maximum recorded zooplankton abundance. Jellyfish medusa flourished in nearshore areas, becoming less prevalent towards the deeper waters of the Salish Sea. The sizable presence of Noctiluca and jellyfish in the zooplankton blooms may be repelling

The impact of different hydrographic conditions and zooplankton communities on provisioning Little Auks along the West coast of Spitsbergen

Science.gov (United States)

Kwasniewski, Slawomir; Gluchowska, Marta; Jakubas, Dariusz; Wojczulanis-Jakubas, Katarzyna; Walkusz, Wojciech; Karnovsky, Nina; Blachowiak-Samolyk, Katarzyna; Cisek, Malgorzata; Stempniewicz, Lech

2010-10-01

Composition and abundance of zooplankton were studied simultaneously with feeding ecology of planktivorous Little Auks ( Alle alle) in two different sea shelf areas of West Spitsbergen, Norway, in summer 2007. Zooplankton was collected adjacent to bird colonies in Magdalenefjorden (influenced by Atlantic West Spitsbergen Current) and Hornsund (dominated by the Arctic Sørkapp Current). In spite of different hydrological situations, the abundance of prey preferred by Little Auks, Arctic Calanus glacialis copepodids stage V, among zooplankton was similar in both localities. However, there was much more of Atlantic Calanus finmarchicus on the shelf outside Magdalenefjorden compared to Hornsund, resulting in different abundance ratios of Arctic to Atlantic copepods in the two areas (1:14 and 1:1, respectively). Even greater differences between the two areas occurred in the ratio of C. glacialis CV to other zooplankters, amounting to 1:40 in Magdalenefjorden and 1:6 in Hornsund. In both Little Auk colonies food brought by parents to their chicks contained mainly C. glacialis CV, albeit the proportion of this copepod in meals was significantly higher in Hornsund. Meals delivered to Little Auk chicks in Hornsund had also higher zooplankton numbers, biomass and energy content. In Magdalenefjorden, on the other hand, a higher number of feedings and longer duration of foraging trips were recorded. These differences became more apparent with increasing energy requirements of the fast growing nestlings. This was probably a consequence of lower relative abundance of the Little Auks’ preferred prey in the sea adjacent to Magdalenefjorden colony. It seems that searching for the preferred food items, such as C. glacialis, among abundant but less favored C. finmarchicus, may require more time and energy demanding foraging behavior. As a consequence, foraging effort of the Little Auk parents from Magdalenefjorden was higher, and feeding efficiency lower, than those of birds from

Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

Science.gov (United States)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

The characteristic of a zooplankton in the contaminated bottom stream of the Pripyat' river and backwaters

International Nuclear Information System (INIS)

Zarubaw, A.I.; Malatkow, D.V.

1994-01-01

The researches of zooplankton are conducted on two stations on the Pripyat' river, but also on two backwaters which are in the Chernobyl NPP contamination zone. The rotifera is dominant group of zooplankton. Their quantity is more than 10 samples/litter. An absolute and relative fertility of rotifera is determined. It is established an structural and functional reorganization of the rotifera dominant complexes occurs. Any influence of contamination on a zooplankton condition is not found out. 5 refs., 2 tabs., 2 figs

Lag space estimation in time series modelling

DEFF Research Database (Denmark)

Goutte, Cyril

1997-01-01

The purpose of this article is to investigate some techniques for finding the relevant lag-space, i.e. input information, for time series modelling. This is an important aspect of time series modelling, as it conditions the design of the model through the regressor vector a.k.a. the input layer...

Time-series prediction and applications a machine intelligence approach

CERN Document Server

Konar, Amit

2017-01-01

This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at...

A Time Series Forecasting Method

Directory of Open Access Journals (Sweden)

Wang Zhao-Yu

2017-01-01

Full Text Available This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally. If a data pattern is not similar enough to an existing cluster, it forms a new cluster of its own. However, if a data pattern is similar enough to an existing cluster, it is removed from the cluster it currently belongs to and added to the most similar cluster. During the clustering process, weights are learned for each cluster. Given a series of time-stamped data up to time t, we divide it into a set of training patterns. By using the weighted self-constructing clustering, the training patterns are grouped into a set of clusters. To estimate the value at time t + 1, we find the k nearest neighbors of the input pattern and use these k neighbors to decide the estimation. Experimental results are shown to demonstrate the effectiveness of the proposed approach.

Stochastic nature of series of waiting times

Science.gov (United States)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2time distribution. We find that the logarithmic difference of waiting times series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.

Biochemical composition of zooplankton from the Andaman Sea

Digital Repository Service at National Institute of Oceanography (India)

Goswami, S.C.; Rao, T.S.S.; Matondkar, S.G.P.

Protein was the dominant constituent in mixed zooplankton major planktonic groups and some common species collected from the Andaman Sea. Overall mean values, calculated as a percentage of dry weight, were 45,14 protein, 10.6 lipid, 4.2 carbohydrate...

Foraging mode and prey size spectra of suspension-feeding copepods and other zooplankton

DEFF Research Database (Denmark)

Kiørboe, Thomas

2016-01-01

Prey size spectra of suspension-feeding zooplankton may be predicted from foraging mode and a mechanistic understanding of prey perception and capture. I examine this for suspension-feeding copepods where 2 foraging modes can be distinguished: ambush feeding and active (i.e. cruising and feeding-...... the prediction. I also make qualitative predictions of food size spectra in zooplankton with other prey perception mechanisms that accord with observations....

Efficient Approximate OLAP Querying Over Time Series

DEFF Research Database (Denmark)

Perera, Kasun Baruhupolage Don Kasun Sanjeewa; Hahmann, Martin; Lehner, Wolfgang

2016-01-01

The ongoing trend for data gathering not only produces larger volumes of data, but also increases the variety of recorded data types. Out of these, especially time series, e.g. various sensor readings, have attracted attention in the domains of business intelligence and decision making. As OLAP...... queries play a major role in these domains, it is desirable to also execute them on time series data. While this is not a problem on the conceptual level, it can become a bottleneck with regards to query run-time. In general, processing OLAP queries gets more computationally intensive as the volume...... of data grows. This is a particular problem when querying time series data, which generally contains multiple measures recorded at fine time granularities. Usually, this issue is addressed either by scaling up hardware or by employing workload based query optimization techniques. However, these solutions...

Stable isotope methods: The effect of gut contents on isotopic ratios of zooplankton

Science.gov (United States)

Hill, J. M.; McQuaid, C. D.

2011-05-01

In the past decade there has been an increased awareness of the potential for methodological bias resulting from multiple pre-analytical procedures in foodweb interpretations based on stable isotope techniques. In the case of small organisms, this includes the effect of gut contents on whole body signatures. Although gut contents may not reflect actual assimilation, their carbon and nitrogen values will be isotopically lighter than after the same material has been assimilated. The potential skewing of isotopic ratios in whole organism samples is especially important for aquatic environments as many studies involve trophic relationships among small zooplankton. This is particularly important in pelagic waters, where herbivorous zooplankton comprise small taxa. Hence this study investigated the effect of gut contents on the δ13C and δ15N ratios of three size classes of zooplankton (1.0-2.0, 2.0-4.0 and >4.0 mm) collected using bongo net tows in the tropical waters of the south-west Indian Ocean. Animals were collected at night, when they were likely to be feeding, sieved into size classes and separated into genera. We focused on Euphausia spp which dominated zooplankton biomass. Three treatment types were processed: bulk animals, bulk animals without guts and tail muscle from each size class at 10 bongo stations. The δ15N ratios were influenced by zooplankton size class, presumably reflecting ontogenetic changes in diet. ANOVA post hoc results and correlations in δ15N signatures among treatments suggest that gut contents may not affect overall nitrogen signatures of Euphausia spp., but that δ13C signatures may be significantly altered by their presence. Carbon interpretations however, were complicated by potential effects of variation in chitin, lipids and metabolism among tissues and the possibility of opportunistic omnivory. Consequently we advocate gut evacuation before sacrifice in euphausiids if specific tissue dissection is impractical and recommend

A Dynamic Fuzzy Cluster Algorithm for Time Series

Directory of Open Access Journals (Sweden)

Min Ji

2013-01-01

clustering time series by introducing the definition of key point and improving FCM algorithm. The proposed algorithm works by determining those time series whose class labels are vague and further partitions them into different clusters over time. The main advantage of this approach compared with other existing algorithms is that the property of some time series belonging to different clusters over time can be partially revealed. Results from simulation-based experiments on geographical data demonstrate the excellent performance and the desired results have been obtained. The proposed algorithm can be applied to solve other clustering problems in data mining.

A novel weight determination method for time series data aggregation

Science.gov (United States)

Xu, Paiheng; Zhang, Rong; Deng, Yong

2017-09-01

Aggregation in time series is of great importance in time series smoothing, predicting and other time series analysis process, which makes it crucial to address the weights in times series correctly and reasonably. In this paper, a novel method to obtain the weights in time series is proposed, in which we adopt induced ordered weighted aggregation (IOWA) operator and visibility graph averaging (VGA) operator and linearly combine the weights separately generated by the two operator. The IOWA operator is introduced to the weight determination of time series, through which the time decay factor is taken into consideration. The VGA operator is able to generate weights with respect to the degree distribution in the visibility graph constructed from the corresponding time series, which reflects the relative importance of vertices in time series. The proposed method is applied to two practical datasets to illustrate its merits. The aggregation of Construction Cost Index (CCI) demonstrates the ability of proposed method to smooth time series, while the aggregation of The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) illustrate how proposed method maintain the variation tendency of original data.

Zooplankton data from zooplankton net casts and other instruments in the Delaware Bay and North Atlantic Ocean as part of the Ocean Continental Shelf (OCS - Mid Atlantic) project, 03 November 1976 - 18 November 1977 (NODC Accession 7800340)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Zooplankton data were collected using zooplankton net casts and other instruments in the Delaware Bay and North Atlantic Ocean from November 3, 1976 to November 18,...

Foundations of Sequence-to-Sequence Modeling for Time Series

OpenAIRE

Kuznetsov, Vitaly; Mariet, Zelda

2018-01-01

The availability of large amounts of time series data, paired with the performance of deep-learning algorithms on a broad class of problems, has recently led to significant interest in the use of sequence-to-sequence models for time series forecasting. We provide the first theoretical analysis of this time series forecasting framework. We include a comparison of sequence-to-sequence modeling to classical time series models, and as such our theory can serve as a quantitative guide for practiti...

Climate Prediction Center (CPC) Global Precipitation Time Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal...

Climate Prediction Center (CPC) Global Temperature Time Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The global temperature time series provides time series charts using station based observations of daily temperature. These charts provide information about the...

Diel variations in zooplankton and their biochemical composition from Vengurla to Ratnagiri, west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Goswami, S.C.; KrishnaKumari, L.; Shrivastava, Y.

Diel variations in zooplankton biomass, common groups and proximate composition zooplankton at stations between Vengurla to Ratnagiri, along west coast of India were studied. Higher biomass values were obtained for the night samples (av = 80 ml/100...

Recurrent Neural Network Applications for Astronomical Time Series

Science.gov (United States)

Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.

Biomass and composition of zooplankton in Auranga, Ambika, Purna and Mindola estuaries of south Gujarat

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.; Gajbhiye, S.N.; JiyalalRam, M.J.; Desai, B.N.

Biomass and composition of zooplankton in the nearshore waters of Thal, Maharashtra, India were studied at 9 stations during Feb. 1980 to Jan. 1981. The recorded variation in zooplankton biomass was 4.8-80.6 ml.(100 m super(3))/1 [av. 22.9 ml.(100 m...

Zooplankton assessment of Iyikpesu river Aragba- Orogun, Delta ...

African Journals Online (AJOL)

48.0 (39±9) mg CaCO3/L. All parameters were within permissible limits. Eighty– three (83) species of zooplankton belonging to five (5) taxonomic groups were identified. Rotifers contributed the highest number of taxa (36) followed by copepods ...

Zooplankton abundance in the River Kars, Northeast Turkey: Impact ...

African Journals Online (AJOL)

PRECIOUS

2009-11-02

Nov 2, 2009 ... Turkey: Impact of environmental variables. H. Özbay1* and ... in the river. Key words: River Kars, zooplankton, running water, environmental factors. ..... tergestina (Branchiopoda: Onychopoda) in Guanabara Bay, Brazil. Braz.

Transition Icons for Time-Series Visualization and Exploratory Analysis.

Science.gov (United States)

Nickerson, Paul V; Baharloo, Raheleh; Wanigatunga, Amal A; Manini, Todd M; Tighe, Patrick J; Rashidi, Parisa

2018-03-01

The modern healthcare landscape has seen the rapid emergence of techniques and devices that temporally monitor and record physiological signals. The prevalence of time-series data within the healthcare field necessitates the development of methods that can analyze the data in order to draw meaningful conclusions. Time-series behavior is notoriously difficult to intuitively understand due to its intrinsic high-dimensionality, which is compounded in the case of analyzing groups of time series collected from different patients. Our framework, which we call transition icons, renders common patterns in a visual format useful for understanding the shared behavior within groups of time series. Transition icons are adept at detecting and displaying subtle differences and similarities, e.g., between measurements taken from patients receiving different treatment strategies or stratified by demographics. We introduce various methods that collectively allow for exploratory analysis of groups of time series, while being free of distribution assumptions and including simple heuristics for parameter determination. Our technique extracts discrete transition patterns from symbolic aggregate approXimation representations, and compiles transition frequencies into a bag of patterns constructed for each group. These transition frequencies are normalized and aligned in icon form to intuitively display the underlying patterns. We demonstrate the transition icon technique for two time-series datasets-postoperative pain scores, and hip-worn accelerometer activity counts. We believe transition icons can be an important tool for researchers approaching time-series data, as they give rich and intuitive information about collective time-series behaviors.

Multifractal analysis of visibility graph-based Ito-related connectivity time series.

Science.gov (United States)

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

Blooms of phytoplankton along the west coast of India associated with nutrient enrichment and the response of zooplankton

Digital Repository Service at National Institute of Oceanography (India)

Nair, S.R.S.; Devassy, V.P.; Madhupratap, M.

and dinoflagellates are also common Spectacular bloom formations of Trichodesmium is a regular phenomenon during the later part of the NE monsoon season At times, these blooms cover hundreds of kilometres Very often successions of phyto- and zooplankton communities...

Mathematical foundations of time series analysis a concise introduction

CERN Document Server

Beran, Jan

2017-01-01

This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.

Time series analysis in the social sciences the fundamentals

CERN Document Server

Shin, Youseop

2017-01-01

Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re

Data imputation analysis for Cosmic Rays time series

Science.gov (United States)

Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

2017-05-01

The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.

Zooplankton grazing in a eutrophic lake: implications of diel vertical migration

International Nuclear Information System (INIS)

Lampert, W.; Taylor, B.E.

1985-01-01

During summer and fall, depth profiles of zooplankton community grazing were determined in situ during day and night in the Schoehsee, a small eutrophic lake. Labeled algae of two different sizes were mixed with the natural suspension of phytoplankton in a grazing chamber. A small blue-green alga (Synechococcus, 1 μm) was labeled with 32 P; a larger green alga (Scenedesmus, 4-15 μm) was labeled with 14 C. During summer, grazing in the upper 5 m was negligible during day but strong at night. Hence, algae grow relatively unimpeded by grazing during daytime but are harvested at night. Vertical and diel differences in grazing rates disappeared when the vertical migration ceased in fall. Selectivity of grazing was controlled by the zooplankton species composition. Eudiaptomus showed a strong preference for Scenedesmus. Daphnia showed a slight preference for Scenedesmus, but Ceriodaphnia preferred Synechococcus. Cyclopoid copepodites did not ingest the small blue-green. Because Daphnia and Eudiaptomus were dominant, grazing rates on larger cells were usually higher than grazing rates on the small cells. Negative electivity indices for scenedesmus occurred only when the biomass of large crustaceans was extremely low (near the surface, during day). Zooplankton biomass was the main factor controlling both vertical and seasonal variations in grazing. Highest grazing rates (65%/d) were measured during fall when zooplankton abundance was high. Because differential losses can produce substantial errors in the results, it was necessary to process the samples on the boat immediately after collection, without preservation

Algorithm for Compressing Time-Series Data

Science.gov (United States)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Food habits of Juvenile American Shad and dynamics of zooplankton in the lower Columbia River

Science.gov (United States)

Haskell, C.A.; Tiffan, K.F.; Rondorf, D.W.

2006-01-01

As many as 2.4 million adult American shad annually pass John Day Dam, Columbia River to spawn upriver, yet food web interactions of juvenile shad rearing in John Day Reservoir are unexplored. We collected zooplankton and conducted mid-water trawls in McNary (June-July) and John Day reservoirs (August-November) from 1994 through 1996 during the outmigration of subyearling American shad and Chinook salmon. Juvenile American shad were abundant and represented over 98% of the trawl catch in late summer. The five major taxa collected in zooplankton tows were Bosmina longirostris, Daphnia, cyclopoid cope-pods, rotifers, and calanoid copepods. We evaluated total crustacean zooplankton abundance and Daphnia biomass in relation to water temperature, flow, depth, diel period, and cross-sectional location using multiple regression. Differences in zooplankton abundance were largely due to differences in water temperature and flow. Spatial variation in total zooplankton abundance was observed in McNary Reservoir, but not in John Day Reservoir. Juvenile American shad generally fed on numerically abundant prey, despite being less preferred than larger bodied zooplankton. A decrease in cladoceran abundance and size in August coupled with large percentages of Daphnia in juvenile American shad stomachs indicated heavy planktivory. Smaller juvenile American shad primarily fed on Daphnia in August, but switched to more evasive copepods as the mean size of fish increased and Daphnia abundance declined. Because Daphnia are particularly important prey items for subyearling Chinook salmon in mainstem reservoirs in mid to late summer, alterations in the cladoceran food base is of concern for the management of outmigrating salmonids and other Columbia River fishes. ?? 2006 by the Northwest Scientific Association. All rights reserved.

Modeling of Volatility with Non-linear Time Series Model

OpenAIRE

Kim Song Yon; Kim Mun Chol

2013-01-01

In this paper, non-linear time series models are used to describe volatility in financial time series data. To describe volatility, two of the non-linear time series are combined into form TAR (Threshold Auto-Regressive Model) with AARCH (Asymmetric Auto-Regressive Conditional Heteroskedasticity) error term and its parameter estimation is studied.

Layered Ensemble Architecture for Time Series Forecasting.

Science.gov (United States)

Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

2016-01-01

Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

Zooplankton community structure and dynamics during the transition ...

African Journals Online (AJOL)

This study investigates the zooplankton community structure and dynamics of Kufena Rock Pool during the transition from dry season (March to April) to rainy season (May to June) in Zaria, Nigeria. Physicochemical parameters such as temperature, hydrogen ion concentration, electrical conductivity and total dissolved ...

Metal and proton toxicity to lake zooplankton: A chemical speciation based modelling approach

International Nuclear Information System (INIS)

Stockdale, Anthony; Tipping, Edward; Lofts, Stephen; Fott, Jan; Garmo, Øyvind A.; Hruska, Jakub; Keller, Bill; Löfgren, Stefan; Maberly, Stephen C.; Majer, Vladimir; Nierzwicki-Bauer, Sandra A.; Persson, Gunnar; Schartau, Ann-Kristin; Thackeray, Stephen J.

2014-01-01

The WHAM-F TOX model quantifies the combined toxic effects of protons and metal cations towards aquatic organisms through the toxicity function (F TOX ), a linear combination of the products of organism-bound cation and a toxic potency coefficient for each cation. We describe the application of the model to predict an observable ecological field variable, species richness of pelagic lake crustacean zooplankton, studied with respect to either acidification or the impacts of metals from smelters. The fitted results give toxic potencies increasing in the order H + TOX to relate combined toxic effects of protons and metal cations towards lake crustacean zooplankton. • The fitted results give toxic potencies increasing in the order H + TOX model has been applied to field data for pelagic lake crustacean zooplankton. The fitted results give metal toxic potencies increasing in the order H + < Al < Cu < Zn < Ni

A window-based time series feature extraction method.

Science.gov (United States)

Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

2017-10-01

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Metals in coastal zooplanktons - A coastal living resource hazard

Digital Repository Service at National Institute of Oceanography (India)

Paimpillil, J.S.; Joseph, T.; Rejomon, G.; Gerson, V.J.

are linked to bioaccumulation. The biological concentration factor and metal contents in zooplankton is appreciably varied for all the elements except for iron and zinc. The above findings clearly indicates the importance of bioavailability of metals...

Zooplankton characteristics of the coastal ecosystem off Bombay, India

Digital Repository Service at National Institute of Oceanography (India)

Nair, V.R.; Ramaiah, Neelam

spinicauda) dominated the copepod community. Four species of chaetognaths were found in the area with predominance of Sagitta bedoti. Among the penaeid larvae Metapenaeus offinis was the most common species. Population of omnivores dominated the zooplankton...

Effect of pig dung fertilizer on zooplankton production

African Journals Online (AJOL)

SARAH

2014-12-29

Dec 29, 2014 ... Key-words: pig dung, fertilization, zooplankton production. ... an already widespread practice in many Asian countries (fukusho, et al., ..... Elsevier Scientific Publishing Company,. New York ... Effect on Water Quality, pond productivity and. Growth of ... McQueen DJ, Johannes MRS, Post JR, Stewart TJ, Lean.

Secondary production and zooplankton abundance in the coastal waters from Vengurla to Malpe, west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Goswami, S.C.

Secondary production and zooplankton abundance in surface and vertical hauls at different stations along 7 transects from Vengurla to Malpe, Maharashtra, India were studied. Zooplankton production varied with the depth of sampling station and type...

Rapid reassessment of the eutrophication status of Kingston Harbour, Jamaica using the zooplankton community

Directory of Open Access Journals (Sweden)

Patrice A. Francis

2014-09-01

Full Text Available Previous extensive studies of zooplankton distribution in the eutrophic Kingston Harbour established that it was being continuously contaminated. We assessed the community in 2011, 17 years after a previous study and five years after the introduction of a tertiary waste water system. Sampling was conducted for four weeks at eight stations identical to those sampled in a previous study. We used horizontal surface tows with a 200µm net. A total of 73 zooplankton taxa were identified and copepods dominated with 20 species. Mean total abundances were high, ranging from a minimum of 2 383 animals m-3 in the southern region of Hunts Bay to 194 166 animals m-3at the Inner Harbour. Five zooplankton taxa (Acartia tonsa, Paracalanus spp., Temora turbinata, Penilia avirostris and Lucifer faxoni that were previously identified as indicators, were again important in the Harbour. The overall zooplankton abundances were similar and in some cases higher than the previous study. There was no significant improvement in the water quality since the introduction of the treatment system at Soapberry. This may be a result of unknown nutrient inputs or of nutrient remaining in the sediments.

ZOOPLANKTON DIVERSITY AND ITS RELATIONSHIP WITH PHYSICO-CHEMICAL PARAMETERS IN MANI RESERVOIR OF WESTERN GHATS, REGION, HOSANAGAR TALUK, SHIVAMOGA DISTRICT KARNATAKA, INDIA

Directory of Open Access Journals (Sweden)

D. N. Veerendra

2012-01-01

Full Text Available Studies on relationship between zooplankton abundance and water quality parameter in Mani reservoir were made between January 2008 and December 2008. In the current investigation, impact of different physico-chemical parameters on zooplankton population was found. Ten genera of zooplankton were identified. The relationship between zooplankton and water quality parameters was varied from place to place depending upon the condition of the reservoir water.

Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales

Science.gov (United States)

Razavi, Saman; Vogel, Richard

2018-02-01

Prewhitening, the process of eliminating or reducing short-term stochastic persistence to enable detection of deterministic change, has been extensively applied to time series analysis of a range of geophysical variables. Despite the controversy around its utility, methodologies for prewhitening time series continue to be a critical feature of a variety of analyses including: trend detection of hydroclimatic variables and reconstruction of climate and/or hydrology through proxy records such as tree rings. With a focus on the latter, this paper presents a generalized approach to exploring the impact of a wide range of stochastic structures of short- and long-term persistence on the variability of hydroclimatic time series. Through this approach, we examine the impact of prewhitening on the inferred variability of time series across time scales. We document how a focus on prewhitened, residual time series can be misleading, as it can drastically distort (or remove) the structure of variability across time scales. Through examples with actual data, we show how such loss of information in prewhitened time series of tree rings (so-called "residual chronologies") can lead to the underestimation of extreme conditions in climate and hydrology, particularly droughts, reconstructed for centuries preceding the historical period.

The Impacts of Recently Established Fish Populations on Zooplankton Communities in a Desert Spring, and Potential Conflicts in Setting Conservation Goals

Directory of Open Access Journals (Sweden)

Sujan M. Henkanaththegedara

2015-01-01

Full Text Available Desert springs, which harbor diverse and endemic invertebrate assemblages, are often used as refuge habitats for protected fish species. Additionally, many of these springs have been colonized by invasive fish species. However, the potential impacts of recently established fish populations on invertebrate communities in desert springs have been relatively unexplored. We conducted a mesocosm experiment to assess the impact of both protected and invasive fish on community structure of spring-dwelling invertebrates focusing on zooplankton. Experimental populations of spring zooplankton communities were established and randomly assigned to one of three treatments, (1 invasive western mosquitofish (Gambusia affinis; (2 endangered Mohave tui chub (Siphateles bicolor mohavensis; and (3 fishless control. Final populations of zooplankton and fish were sampled, sorted, identified and counted. The treatment differences of zooplankton communities were analyzed by comparing the densities of six major zooplankton taxa. Further, we performed nonmetric multidimensional scaling (NMDS to visualize the patterns of zooplankton community assemblages. Four zooplankton taxa, crustacean nauplii, cladocera, calanoid and cyclopoid copepods had significantly lower densities in fish treatments compared to fishless control. Overall, invasive mosquitofish caused a 78.8% reduction in zooplankton density, while Mohave tui chub caused a 65.1% reduction. Both protected and invasive fish had similar effects on zooplankton except for cladocerans where tui chub caused a 60% reduction in density, whereas mosquitofish virtually eliminated cladocerans. The presence of fish also had a significant effect on zooplankton community structure due to population declines and local extirpations presumably due to fish predation. This work shows that conservation-translocations undertaken to conserve protected fish species may impact spring-dwelling invertebrate communities, and such impacts are

Dynamics of the zooplankton assemblage of Ojirami Reservoir, Edo ...

African Journals Online (AJOL)

Zooplankton form an important trophic link between phytoplankton and fish in ... with water temperature and water level; and positive with alkalinity, free CO2 and phosphate. The study revealed low pollution indicator species in the reservoir ...

Understanding cyanobacteria-zooplankton interactions in a more eutrophic world

NARCIS (Netherlands)

Ger, K.A.; Hansson, L.; Lurling, M.F.L.L.W.

2014-01-01

1.We review and update recent observations of cyanobacteria–zooplankton interactions, identify theoretical and methodological limitations and evaluate approaches necessary for understanding the effects of increasing cyanobacterial blooms on plankton dynamics. 2.The emphasis on oversimplified studies

Diversity and seasonal variation of zooplankton of Lake Hlan ...

African Journals Online (AJOL)

SARAH

2016-06-30

Jun 30, 2016 ... The taxonomic composition and the species ... Keywords: Biodiversity; Community structure; Hydrological season; Zooplankton .... Table 1: Seasonal change in recorded environmental parameters ..... reproduction, growth and life duration (Fernandez de .... Spatial temporal patterns and relationships with.

DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

Effects of natural banks of free-floating plants on zooplankton community in a shallow subtropical lake in Southern Brazil

Directory of Open Access Journals (Sweden)

Vanessa Gazulha

2011-08-01

Full Text Available The aim of this study was to test the effects of natural free-floating plants on zooplankton distribution in a shallow subtropical lake. First, the hypothesis that free-floating plants have an effect on physico-chemicals, leading to a decrease on nutrient availability and influencing the phytoplankton biomass and zooplankton community was tested. Second, the hypothesis that free-floating plants act as a refuge for zooplankton was tested. Three microhabitats were selected: free-floating plants, littoral area and open water. Results demonstrated that the effects of different microhabitats on phytoplankton biomass and physico-chemicals were not significant, indicating a weak influence of the plants. Zooplankton densities were higher in free-floating plants and littoral area, although the effect of microhabitats was weak for most of the predominant genera. The absence of free-floating plant effects on phytoplankton and physico-chemicals showed that it was not a factor influencing the microcrustacean distribution in the microhabitats. Low differences in densities of zooplankton among microhabitats and low abundance of large-bodied cladocerans led to reject the hypothesis that free-floating plants act as a refuge for zooplankton.

Increased fitness of a key appendicularian zooplankton species under warmer, acidified seawater conditions.

Directory of Open Access Journals (Sweden)

Jean-Marie Bouquet

Full Text Available Ocean warming and acidification (OA may alter the fitness of species in marine pelagic ecosystems through community effects or direct physiological impacts. We used the zooplanktonic appendicularian, Oikopleura dioica, to assess temperature and pH effects at mesocosm and microcosm scales. In mesocosms, both OA and warming positively impacted O. dioica abundance over successive generations. In microcosms, the positive impact of OA, was observed to result from increased fecundity. In contrast, increased pH, observed for example during phytoplankton blooms, reduced fecundity. Oocyte fertility and juvenile development were equivalent under all pH conditions, indicating that the positive effect of lower pH on O. dioica abundance was principally due to increased egg number. This effect was influenced by food quantity and quality, supporting possible improved digestion and assimilation at lowered pH. Higher temperature resulted in more rapid growth, faster maturation and earlier reproduction. Thus, increased temperature and reduced pH had significant positive impacts on O. dioica fitness through increased fecundity and shortened generation time, suggesting that predicted future ocean conditions may favour this zooplankton species.

Variable Selection in Time Series Forecasting Using Random Forests

Directory of Open Access Journals (Sweden)

Hristos Tyralis

2017-10-01

Full Text Available Time series forecasting using machine learning algorithms has gained popularity recently. Random forest is a machine learning algorithm implemented in time series forecasting; however, most of its forecasting properties have remained unexplored. Here we focus on assessing the performance of random forests in one-step forecasting using two large datasets of short time series with the aim to suggest an optimal set of predictor variables. Furthermore, we compare its performance to benchmarking methods. The first dataset is composed by 16,000 simulated time series from a variety of Autoregressive Fractionally Integrated Moving Average (ARFIMA models. The second dataset consists of 135 mean annual temperature time series. The highest predictive performance of RF is observed when using a low number of recent lagged predictor variables. This outcome could be useful in relevant future applications, with the prospect to achieve higher predictive accuracy.

Grazing experiments and model simulations of the role of zooplankton in Phaeocystis food webs

Science.gov (United States)

Verity, P. G.

2000-08-01

A combined empirical and modelling study was conducted to further examine the potential importance of grazing by zooplankton in pelagic food webs in which Phaeocystis is a significant or dominant component. Laboratory experiments were designed to measure ingestion of Phaeocystis and other potential prey items which co-occur with Phaeocystis. Grazers included copepods and ciliates, and prey included Phaeocystis colonies and solitary cells, diatoms, ciliates, bacteria, and detritus. These data were expressed in the model currency of nitrogen units, and fit to hyperbolic tangent equations which included minimum prey thresholds. These equations and literature data were used to constrain a food web model whose purpose was to investigate trophic interactions rather than to mimic actual events. Nevertheless, the model output was similar to the general pattern and magnitude of development of Phaeocystis-diatom communities in some environments where they occur, e.g. north Norwegian waters. The model included three forms of nitrogen, three phytoplankton groups, bacteria, two zooplankton groups, and detritus, with detailed flows between compartments. An important component of the model was inclusion of variable prey preferences for zooplankton. The experiments and model simulations suggest several salient conclusions. Phaeocystis globosa colonies were eaten by a medium-sized copepod species, but ingestion appeared to be strongly dependent upon a proper size match between grazer and prey. If not, colonies were eaten little if at all. Phaeocystis solitary cells were ingested rapidly by ciliate microzooplankton, in agreement with prior literature observations. In contrast, detritus was eaten comparatively slowly by both ciliates and copepods. Both types of zooplankton exhibited apparent minimum prey thresholds below which grazing did not occur or was inconsequential. Model simulations implied that transitions between life cycle stages of Phaeocystis may potentially be important

Trace metal concentrations in marine zooplankton from the western Bay of Bengal

Digital Repository Service at National Institute of Oceanography (India)

Rejomon, G.; Balachandran, K.K.; Nair, M.; Joseph, T.

on the interrelationships of zooplankton and phytoplankton. – Journal of Marine Biological Association U.K 32: 375-445. [2] Brooks, R.R., Presley, B.J., Kaplan, I.R. (1967): APDC-MIBK extraction system for the determination of trace elements in saline waters by Atomic... of contaminants in the food web dynamics as well as in the biogeochemical cycling of trace elements. Zooplanktons are the most abundant animals in the sea, which play an important role in the marine food chain. They mostly feed on phytoplankton and in turn...

Trend time-series modeling and forecasting with neural networks.

Science.gov (United States)

Qi, Min; Zhang, G Peter

2008-05-01

Despite its great importance, there has been no general consensus on how to model the trends in time-series data. Compared to traditional approaches, neural networks (NNs) have shown some promise in time-series forecasting. This paper investigates how to best model trend time series using NNs. Four different strategies (raw data, raw data with time index, detrending, and differencing) are used to model various trend patterns (linear, nonlinear, deterministic, stochastic, and breaking trend). We find that with NNs differencing often gives meritorious results regardless of the underlying data generating processes (DGPs). This finding is also confirmed by the real gross national product (GNP) series.

Segmentation of Nonstationary Time Series with Geometric Clustering

DEFF Research Database (Denmark)

Bocharov, Alexei; Thiesson, Bo

2013-01-01

We introduce a non-parametric method for segmentation in regimeswitching time-series models. The approach is based on spectral clustering of target-regressor tuples and derives a switching regression tree, where regime switches are modeled by oblique splits. Such models can be learned efficiently...... from data, where clustering is used to propose one single split candidate at each split level. We use the class of ART time series models to serve as illustration, but because of the non-parametric nature of our segmentation approach, it readily generalizes to a wide range of time-series models that go...

Non-parametric characterization of long-term rainfall time series

Science.gov (United States)

Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

The statistical study of rainfall time series is one of the approaches for efficient hydrological system design. Identifying, and characterizing long-term rainfall time series could aid in improving hydrological systems forecasting. In the present study, eventual statistics was applied for the long-term (1851-2006) rainfall time series under seven meteorological regions of India. Linear trend analysis was carried out using Mann-Kendall test for the observed rainfall series. The observed trend using the above-mentioned approach has been ascertained using the innovative trend analysis method. Innovative trend analysis has been found to be a strong tool to detect the general trend of rainfall time series. Sequential Mann-Kendall test has also been carried out to examine nonlinear trends of the series. The partial sum of cumulative deviation test is also found to be suitable to detect the nonlinear trend. Innovative trend analysis, sequential Mann-Kendall test and partial cumulative deviation test have potential to detect the general as well as nonlinear trend for the rainfall time series. Annual rainfall analysis suggests that the maximum changes in mean rainfall is 11.53% for West Peninsular India, whereas the maximum fall in mean rainfall is 7.8% for the North Mountainous Indian region. The innovative trend analysis method is also capable of finding the number of change point available in the time series. Additionally, we have performed von Neumann ratio test and cumulative deviation test to estimate the departure from homogeneity. Singular spectrum analysis has been applied in this study to evaluate the order of departure from homogeneity in the rainfall time series. Monsoon season (JS) of North Mountainous India and West Peninsular India zones has higher departure from homogeneity and singular spectrum analysis shows the results to be in coherence with the same.

Water Browning Influences the Behavioral Effects of Ultraviolet Radiation on Zooplankton

Directory of Open Access Journals (Sweden)

Raoul Wolf

2018-03-01

Full Text Available In the last decades, limnic water bodies in the Northern hemisphere have experienced a noticeable browning, i.e., increasing levels of dissolved organic matter (DOM. While the effects on primary producers is usually considered negative (light attenuation, zooplankton is thought to benefit from increased DOM, which absorbs harmful ultraviolet radiation (UVR. However, behavioral alterations due to browning in zooplankton have not yet been studied. We investigated the effects of a DOM gradient, alone and in combination with UVR, on the swimming behavior of Daphnia magna. Making use of a computer-controlled imaging system, we repeatedly filmed individuals over 6 h and analyzed the video material to unravel effects on exploration behavior and other motility patterns. The results show that increasing DOM buffers the detrimental effects of UVR on swimming behavior. This is likely due to attenuation of UVR by DOM. Interestingly, DOM also raised the overall swimming activity independent of UVR exposure. Our findings highlight the importance of DOM in freshwater systems, not only because of its physico-chemical properties, but also due to its higher-level effects on zooplankton communities.

Time Series Decomposition into Oscillation Components and Phase Estimation.

Science.gov (United States)

Matsuda, Takeru; Komaki, Fumiyasu

2017-02-01

Many time series are naturally considered as a superposition of several oscillation components. For example, electroencephalogram (EEG) time series include oscillation components such as alpha, beta, and gamma. We propose a method for decomposing time series into such oscillation components using state-space models. Based on the concept of random frequency modulation, gaussian linear state-space models for oscillation components are developed. In this model, the frequency of an oscillator fluctuates by noise. Time series decomposition is accomplished by this model like the Bayesian seasonal adjustment method. Since the model parameters are estimated from data by the empirical Bayes' method, the amplitudes and the frequencies of oscillation components are determined in a data-driven manner. Also, the appropriate number of oscillation components is determined with the Akaike information criterion (AIC). In this way, the proposed method provides a natural decomposition of the given time series into oscillation components. In neuroscience, the phase of neural time series plays an important role in neural information processing. The proposed method can be used to estimate the phase of each oscillation component and has several advantages over a conventional method based on the Hilbert transform. Thus, the proposed method enables an investigation of the phase dynamics of time series. Numerical results show that the proposed method succeeds in extracting intermittent oscillations like ripples and detecting the phase reset phenomena. We apply the proposed method to real data from various fields such as astronomy, ecology, tidology, and neuroscience.

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2015-01-01

Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

Multi-Scale Dissemination of Time Series Data

DEFF Research Database (Denmark)

Guo, Qingsong; Zhou, Yongluan; Su, Li

2013-01-01

In this paper, we consider the problem of continuous dissemination of time series data, such as sensor measurements, to a large number of subscribers. These subscribers fall into multiple subscription levels, where each subscription level is specified by the bandwidth constraint of a subscriber......, which is an abstract indicator for both the physical limits and the amount of data that the subscriber would like to handle. To handle this problem, we propose a system framework for multi-scale time series data dissemination that employs a typical tree-based dissemination network and existing time...

Assessment of Zooplankton Community Structure of the Bahir Dar ...

African Journals Online (AJOL)

In general, species richness, evenness, and diversity increased as average abundance increased in the littoral zones of the lake. The dominant zooplankton were Bosmina longirostris, Daphnia lumholtzi, Thermodiaptomus galebi, Thermocyclops ethiopiensis, Diaphanosoma sarsi, Keratella sp., Brachionus sp., Filinia sp.

RADON CONCENTRATION TIME SERIES MODELING AND APPLICATION DISCUSSION.

Science.gov (United States)

Stránský, V; Thinová, L

2017-11-01

In the year 2010 a continual radon measurement was established at Mladeč Caves in the Czech Republic using a continual radon monitor RADIM3A. In order to model radon time series in the years 2010-15, the Box-Jenkins Methodology, often used in econometrics, was applied. Because of the behavior of radon concentrations (RCs), a seasonal integrated, autoregressive moving averages model with exogenous variables (SARIMAX) has been chosen to model the measured time series. This model uses the time series seasonality, previously acquired values and delayed atmospheric parameters, to forecast RC. The developed model for RC time series is called regARIMA(5,1,3). Model residuals could be retrospectively compared with seismic evidence of local or global earthquakes, which occurred during the RCs measurement. This technique enables us to asses if continuously measured RC could serve an earthquake precursor. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Similarity estimators for irregular and age uncertain time series

Science.gov (United States)

Rehfeld, K.; Kurths, J.

2013-09-01

Paleoclimate time series are often irregularly sampled and age uncertain, which is an important technical challenge to overcome for successful reconstruction of past climate variability and dynamics. Visual comparison and interpolation-based linear correlation approaches have been used to infer dependencies from such proxy time series. While the first is subjective, not measurable and not suitable for the comparison of many datasets at a time, the latter introduces interpolation bias, and both face difficulties if the underlying dependencies are nonlinear. In this paper we investigate similarity estimators that could be suitable for the quantitative investigation of dependencies in irregular and age uncertain time series. We compare the Gaussian-kernel based cross correlation (gXCF, Rehfeld et al., 2011) and mutual information (gMI, Rehfeld et al., 2013) against their interpolation-based counterparts and the new event synchronization function (ESF). We test the efficiency of the methods in estimating coupling strength and coupling lag numerically, using ensembles of synthetic stalagmites with short, autocorrelated, linear and nonlinearly coupled proxy time series, and in the application to real stalagmite time series. In the linear test case coupling strength increases are identified consistently for all estimators, while in the nonlinear test case the correlation-based approaches fail. The lag at which the time series are coupled is identified correctly as the maximum of the similarity functions in around 60-55% (in the linear case) to 53-42% (for the nonlinear processes) of the cases when the dating of the synthetic stalagmite is perfectly precise. If the age uncertainty increases beyond 5% of the time series length, however, the true coupling lag is not identified more often than the others for which the similarity function was estimated. Age uncertainty contributes up to half of the uncertainty in the similarity estimation process. Time series irregularity

Similarity estimators for irregular and age-uncertain time series

Science.gov (United States)

Rehfeld, K.; Kurths, J.

2014-01-01

Paleoclimate time series are often irregularly sampled and age uncertain, which is an important technical challenge to overcome for successful reconstruction of past climate variability and dynamics. Visual comparison and interpolation-based linear correlation approaches have been used to infer dependencies from such proxy time series. While the first is subjective, not measurable and not suitable for the comparison of many data sets at a time, the latter introduces interpolation bias, and both face difficulties if the underlying dependencies are nonlinear. In this paper we investigate similarity estimators that could be suitable for the quantitative investigation of dependencies in irregular and age-uncertain time series. We compare the Gaussian-kernel-based cross-correlation (gXCF, Rehfeld et al., 2011) and mutual information (gMI, Rehfeld et al., 2013) against their interpolation-based counterparts and the new event synchronization function (ESF). We test the efficiency of the methods in estimating coupling strength and coupling lag numerically, using ensembles of synthetic stalagmites with short, autocorrelated, linear and nonlinearly coupled proxy time series, and in the application to real stalagmite time series. In the linear test case, coupling strength increases are identified consistently for all estimators, while in the nonlinear test case the correlation-based approaches fail. The lag at which the time series are coupled is identified correctly as the maximum of the similarity functions in around 60-55% (in the linear case) to 53-42% (for the nonlinear processes) of the cases when the dating of the synthetic stalagmite is perfectly precise. If the age uncertainty increases beyond 5% of the time series length, however, the true coupling lag is not identified more often than the others for which the similarity function was estimated. Age uncertainty contributes up to half of the uncertainty in the similarity estimation process. Time series irregularity

Robust Forecasting of Non-Stationary Time Series

OpenAIRE

Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.

2010-01-01

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estima...

Meso-zooplankton movement through the newly constructed Mfolozi ...

African Journals Online (AJOL)

Results show that the beach spillway has facilitated recruitment into St Lucia from the ocean and the Mfolozi River. Further research is needed to ascertain what effect this recruitment has on long-term zooplankton community structure. Key words: iSimangaliso Wetland Park, relinkage, Mfolozi channel, ebb and flood tides, ...

Time Series Econometrics for the 21st Century

Science.gov (United States)

Hansen, Bruce E.

2017-01-01

The field of econometrics largely started with time series analysis because many early datasets were time-series macroeconomic data. As the field developed, more cross-sectional and longitudinal datasets were collected, which today dominate the majority of academic empirical research. In nonacademic (private sector, central bank, and governmental)…

Behind the impact of introduced trout in high altitude lakes: adult, not juvenile fish are responsible of the selective predation on crustacean zooplankton

Directory of Open Access Journals (Sweden)

Rocco Tiberti

2014-05-01

Full Text Available Introduced fish seriously affect zooplankton communities in mountain lakes, often leading to the loss of large species. Selective predation is recognized to be the ultimate cause of such a strong impact. Here we describe the selection of zooplankton prey by analyzing the stomach contents of more than 300 brook trout (Salvelinus fontinalis inhabiting seven alpine lakes in the Gran Paradiso National Park (western Italian Alps. Our results show that planktivory is much more common in young fish, which feed on a larger number of taxa, but also adult fish maintain the ability to feed on zooplankton. There is a direct dependence between the length of zooplankton prey and the length of their fish predators, and adult, not juvenile fish are responsible of the selective predation on large crustacean zooplankton, which drive the impact of introduced fish throughout the entire zooplankton community. In some rare cases, large zooplankton populations develop in the presence of brook trout, and planktivory can become an important temporary resource for adult fish during the ice-free season. Thus, in the early stages of the establishment of non-native trout in alpine lakes, large-bodied zooplankton may represent an important food resource.

Effectiveness of firefly algorithm based neural network in time series ...

African Journals Online (AJOL)

Effectiveness of firefly algorithm based neural network in time series forecasting. ... In the experiments, three well known time series were used to evaluate the performance. Results obtained were compared with ... Keywords: Time series, Artificial Neural Network, Firefly Algorithm, Particle Swarm Optimization, Overfitting ...

A simple and efficient total genomic DNA extraction method for individual zooplankton.

Science.gov (United States)

Fazhan, Hanafiah; Waiho, Khor; Shahreza, Md Sheriff

2016-01-01

Molecular approaches are widely applied in species identification and taxonomic studies of minute zooplankton. One of the most focused zooplankton nowadays is from Subclass Copepoda. Accurate species identification of all life stages of the generally small sized copepods through molecular analysis is important, especially in taxonomic and systematic assessment of harpacticoid copepod populations and to understand their dynamics within the marine community. However, total genomic DNA (TGDNA) extraction from individual harpacticoid copepods can be problematic due to their small size and epibenthic behavior. In this research, six TGDNA extraction methods done on individual harpacticoid copepods were compared. The first new simple, feasible, efficient and consistent TGDNA extraction method was designed and compared with the commercial kit and modified available TGDNA extraction methods. The newly described TGDNA extraction method, "Incubation in PCR buffer" method, yielded good and consistent results based on the high success rate of PCR amplification (82%) compared to other methods. Coupled with its relatively consistent and economical method the "Incubation in PCR buffer" method is highly recommended in the TGDNA extraction of other minute zooplankton species.

Time Series Analysis of Insar Data: Methods and Trends

Science.gov (United States)

Osmanoglu, Batuhan; Sunar, Filiz; Wdowinski, Shimon; Cano-Cabral, Enrique

2015-01-01

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

Interpretation of a compositional time series

Science.gov (United States)

Tolosana-Delgado, R.; van den Boogaart, K. G.

2012-04-01

Common methods for multivariate time series analysis use linear operations, from the definition of a time-lagged covariance/correlation to the prediction of new outcomes. However, when the time series response is a composition (a vector of positive components showing the relative importance of a set of parts in a total, like percentages and proportions), then linear operations are afflicted of several problems. For instance, it has been long recognised that (auto/cross-)correlations between raw percentages are spurious, more dependent on which other components are being considered than on any natural link between the components of interest. Also, a long-term forecast of a composition in models with a linear trend will ultimately predict negative components. In general terms, compositional data should not be treated in a raw scale, but after a log-ratio transformation (Aitchison, 1986: The statistical analysis of compositional data. Chapman and Hill). This is so because the information conveyed by a compositional data is relative, as stated in their definition. The principle of working in coordinates allows to apply any sort of multivariate analysis to a log-ratio transformed composition, as long as this transformation is invertible. This principle is of full application to time series analysis. We will discuss how results (both auto/cross-correlation functions and predictions) can be back-transformed, viewed and interpreted in a meaningful way. One view is to use the exhaustive set of all possible pairwise log-ratios, which allows to express the results into D(D - 1)/2 separate, interpretable sets of one-dimensional models showing the behaviour of each possible pairwise log-ratios. Another view is the interpretation of estimated coefficients or correlations back-transformed in terms of compositions. These two views are compatible and complementary. These issues are illustrated with time series of seasonal precipitation patterns at different rain gauges of the USA

Capturing Structure Implicitly from Time-Series having Limited Data

OpenAIRE

Emaasit, Daniel; Johnson, Matthew

2018-01-01

Scientific fields such as insider-threat detection and highway-safety planning often lack sufficient amounts of time-series data to estimate statistical models for the purpose of scientific discovery. Moreover, the available limited data are quite noisy. This presents a major challenge when estimating time-series models that are robust to overfitting and have well-calibrated uncertainty estimates. Most of the current literature in these fields involve visualizing the time-series for noticeabl...

Carbon and nitrogen stable isotope ratios of pelagic zooplankton elucidate ecohydrographic features in the oligotrophic Red Sea

KAUST Repository

Kü rten, Benjamin; Al-Aidaroos, Ali M.; Kurten, Saskia; El-Sherbiny, Mohsen M.; Devassy, Reny P.; Struck, Ulrich; Zarokanellos, Nikolaos; Jones, Burton; Hansen, Thomas; Bruss, Gerd; Sommer, Ulrich

2015-01-01

Although zooplankton occupy key roles in aquatic biogeochemical cycles, little is known about the pelagic food web and trophodynamics of zooplankton in the Red Sea. Natural abundance stable isotope analysis (SIA) of carbon (δ13C) and N (δ15N) is one

Self-affinity in the dengue fever time series

Science.gov (United States)

Azevedo, S. M.; Saba, H.; Miranda, J. G. V.; Filho, A. S. Nascimento; Moret, M. A.

2016-06-01

Dengue is a complex public health problem that is common in tropical and subtropical regions. This disease has risen substantially in the last three decades, and the physical symptoms depict the self-affine behavior of the occurrences of reported dengue cases in Bahia, Brazil. This study uses detrended fluctuation analysis (DFA) to verify the scale behavior in a time series of dengue cases and to evaluate the long-range correlations that are characterized by the power law α exponent for different cities in Bahia, Brazil. The scaling exponent (α) presents different long-range correlations, i.e. uncorrelated, anti-persistent, persistent and diffusive behaviors. The long-range correlations highlight the complex behavior of the time series of this disease. The findings show that there are two distinct types of scale behavior. In the first behavior, the time series presents a persistent α exponent for a one-month period. For large periods, the time series signal approaches subdiffusive behavior. The hypothesis of the long-range correlations in the time series of the occurrences of reported dengue cases was validated. The observed self-affinity is useful as a forecasting tool for future periods through extrapolation of the α exponent behavior. This complex system has a higher predictability in a relatively short time (approximately one month), and it suggests a new tool in epidemiological control strategies. However, predictions for large periods using DFA are hidden by the subdiffusive behavior.

Improved protocols to accelerate the assembly of DNA barcode reference libraries for freshwater zooplankton.

Science.gov (United States)

Elías-Gutiérrez, Manuel; Valdez-Moreno, Martha; Topan, Janet; Young, Monica R; Cohuo-Colli, José Angel

2018-03-01

Currently, freshwater zooplankton sampling and identification methodologies have remained virtually unchanged since they were first established in the beginning of the XX century. One major contributing factor to this slow progress is the limited success of modern genetic methodologies, such as DNA barcoding, in several of the main groups. This study demonstrates improved protocols which enable the rapid assessment of most animal taxa inhabiting any freshwater system by combining the use of light traps, careful fixation at low temperatures using ethanol, and zooplankton-specific primers. We DNA-barcoded 2,136 specimens from a diverse array of taxonomic assemblages (rotifers, mollusks, mites, crustaceans, insects, and fishes) from several Canadian and Mexican lakes with an average sequence success rate of 85.3%. In total, 325 Barcode Index Numbers (BINs) were detected with only three BINs (two cladocerans and one copepod) shared between Canada and Mexico, suggesting a much narrower distribution range of freshwater zooplankton than previously thought. This study is the first to broadly explore the metazoan biodiversity of freshwater systems with DNA barcodes to construct a reference library that represents the first step for future programs which aim to monitor ecosystem health, track invasive species, or improve knowledge of the ecology and distribution of freshwater zooplankton.

Micro-zooplankton and its abundance relative to the larger zooplankton and other seston components, 08 February 1967 to 27 February 1967 (NODC Accession 0000916)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Micro-zooplankton populations in the upper 100 m were sampled from 5 marine environments in the northeast Pacific Ocean extending from slope waters off San Diego to...

On the plurality of times: disunified time and the A-series | Nefdt ...

African Journals Online (AJOL)

Then, I attempt to show that disunified time is a problem for a semantics based on the A-series since A-truthmakers are hard to come by in a universe of temporally disconnected time-series. Finally, I provide a novel argument showing that presentists should be particularly fearful of such a universe. South African Journal of ...

Time-series modeling of long-term weight self-monitoring data.

Science.gov (United States)

Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka

2015-08-01

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

Aging of microplastics promotes their ingestion by marine zooplankton

NARCIS (Netherlands)

Vroom, Renske J.E.; Koelmans, Bart; Besseling, Ellen

2017-01-01

Microplastics (<5 mm) are ubiquitous in the marine environment and are ingested by zooplankton with possible negative effects on survival, feeding, and fecundity. The majority of laboratory studies has used new and pristine microplastics to test their impacts, while aging processes such as

Time series prediction of apple scab using meteorological ...

African Journals Online (AJOL)

A new prediction model for the early warning of apple scab is proposed in this study. The method is based on artificial intelligence and time series prediction. The infection period of apple scab was evaluated as the time series prediction model instead of summation of wetness duration. Also, the relations of different ...

Correspondence of zooplankton assemblage and water quality in wetlands of Cachar, Assam, India: Implications for environmental management

Directory of Open Access Journals (Sweden)

Kar Sulata

2018-03-01

Full Text Available The zooplankton assemblage of selected wetlands of Assam, India was assessed to deduce the structural variation in the context of water quality parameters. A two year study between 2012 and 2014 comprising of 530 samples from the five wetlands revealed the presence of 46 taxa, 26 Rotifera, 15 Cladocera, 4 Copepoda and 1 Ostracoda, in varying density. The rotifers dominated in terms of abundance (48 ind. cm−3 followed by the cladocerans (28 ind. cm−3 and the copepods (19 ind. cm−3 and showed significant (p <0.05 correlations with turbidity, alkalinity, hardness and phosphate contents of the water samples. The diversity and the richness of the zooplankton showed an increasing trend with the water temperature. Among the different taxa, Brachionus sp. was most abundant followed by Mesocyclops sp. while Beauchampiella sp. was represented in the least numbers. Application of the cluster analysis allowed the segregation of the different zooplankton based on the similarities of abundance in the samples. The water quality parameters like temperature, alkalinity, turbidity, magnesium and calcium were observed to be significant contributors in shaping the zooplankton community composition of the wetlands, revealed through the correlations and canonical correspondence analysis. As an extension, the information can be used in monitoring the quality of the freshwater habitats of the concerned and similar geographical regions, using the zooplankton as the major constituents. The variations in the abundance of cladoceran, copepod and rotifer zooplanktons can be used to understand the mechanisms that sustain the food webs of the aquatic community of the freshwater bodies.

Simulation Modeling of Zooplankton and Benthos in Reservoirs: Documentation and Development of Model Constructs.

Science.gov (United States)

1980-03-01

additional food sources were available. 111. Porter (1973), who examined in situ the selective grazing of algae by a zooplankton community in Fuller Pond...large green algae increased. 112. Anabaena affinis and A. flos- aguae were rarely consumed by the zooplankton and were unaffected by increased grazing...grazing rates over the limited temperature range of 170 to 21*C. Nauwerck (1959), who conducted in situ experiments at Lake Erken, Sweden, with Daphnia

Characterization of time series via Rényi complexity-entropy curves

Science.gov (United States)

Jauregui, M.; Zunino, L.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2018-05-01

One of the most useful tools for distinguishing between chaotic and stochastic time series is the so-called complexity-entropy causality plane. This diagram involves two complexity measures: the Shannon entropy and the statistical complexity. Recently, this idea has been generalized by considering the Tsallis monoparametric generalization of the Shannon entropy, yielding complexity-entropy curves. These curves have proven to enhance the discrimination among different time series related to stochastic and chaotic processes of numerical and experimental nature. Here we further explore these complexity-entropy curves in the context of the Rényi entropy, which is another monoparametric generalization of the Shannon entropy. By combining the Rényi entropy with the proper generalization of the statistical complexity, we associate a parametric curve (the Rényi complexity-entropy curve) with a given time series. We explore this approach in a series of numerical and experimental applications, demonstrating the usefulness of this new technique for time series analysis. We show that the Rényi complexity-entropy curves enable the differentiation among time series of chaotic, stochastic, and periodic nature. In particular, time series of stochastic nature are associated with curves displaying positive curvature in a neighborhood of their initial points, whereas curves related to chaotic phenomena have a negative curvature; finally, periodic time series are represented by vertical straight lines.

Quantifying Selection with Pool-Seq Time Series Data.

Science.gov (United States)

Taus, Thomas; Futschik, Andreas; Schlötterer, Christian

2017-11-01

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Transformation-cost time-series method for analyzing irregularly sampled data.

Science.gov (United States)

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations-with associated costs-to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

Transformation-cost time-series method for analyzing irregularly sampled data

Science.gov (United States)

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G. Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations—with associated costs—to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

A multidisciplinary database for geophysical time series management

Science.gov (United States)

Montalto, P.; Aliotta, M.; Cassisi, C.; Prestifilippo, M.; Cannata, A.

2013-12-01

The variables collected by a sensor network constitute a heterogeneous data source that needs to be properly organized in order to be used in research and geophysical monitoring. With the time series term we refer to a set of observations of a given phenomenon acquired sequentially in time. When the time intervals are equally spaced one speaks of period or sampling frequency. Our work describes in detail a possible methodology for storage and management of time series using a specific data structure. We designed a framework, hereinafter called TSDSystem (Time Series Database System), in order to acquire time series from different data sources and standardize them within a relational database. The operation of standardization provides the ability to perform operations, such as query and visualization, of many measures synchronizing them using a common time scale. The proposed architecture follows a multiple layer paradigm (Loaders layer, Database layer and Business Logic layer). Each layer is specialized in performing particular operations for the reorganization and archiving of data from different sources such as ASCII, Excel, ODBC (Open DataBase Connectivity), file accessible from the Internet (web pages, XML). In particular, the loader layer performs a security check of the working status of each running software through an heartbeat system, in order to automate the discovery of acquisition issues and other warning conditions. Although our system has to manage huge amounts of data, performance is guaranteed by using a smart partitioning table strategy, that keeps balanced the percentage of data stored in each database table. TSDSystem also contains modules for the visualization of acquired data, that provide the possibility to query different time series on a specified time range, or follow the realtime signal acquisition, according to a data access policy from the users.

Zooplankton standing and diversity in the Gulf of Kachchh with special reference to larvae of decapoda and pisces

Digital Repository Service at National Institute of Oceanography (India)

Paulinose, V.T.; Devi, C.B.L.; Nair, V.R.; Ramaiah, Neelam; Gajbhiye, S.N.

Zooplankton characteristics of the Gulf of Kachchh including the major creek systems of Nakti, Kandla and Hansthal were studied for monsoon, postmonsoon and pre- monsoon periods. Zooplankton collections were made at 7 locations. The area was very...

Modeling financial time series with S-plus

CERN Document Server

Zivot, Eric

2003-01-01

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics This is the first book to show the power of S-PLUS for the analysis of time series data It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department at the University of Washington, and is co-director of the nascent Professional Master's Program in Computational Finance He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the He...

Application of Time Series Analysis in Determination of Lag Time in Jahanbin Basin

Directory of Open Access Journals (Sweden)

Seied Yahya Mirzaee

2005-11-01

    One of the important issues that have significant role in study of hydrology of basin is determination of lag time. Lag time has significant role in hydrological studies. Quantity of rainfall related lag time depends on several factors, such as permeability, vegetation cover, catchments slope, rainfall intensity, storm duration and type of rain. Determination of lag time is important parameter in many projects such as dam design and also water resource studies. Lag time of basin could be calculated using various methods. One of these methods is time series analysis of spectral density. The analysis is based on fouries series. The time series is approximated with Sinuous and Cosines functions. In this method harmonically significant quantities with individual frequencies are presented. Spectral density under multiple time series could be used to obtain basin lag time for annual runoff and short-term rainfall fluctuation. A long lag time could be due to snowmelt as well as melting ice due to rainfalls in freezing days. In this research the lag time of Jahanbin basin has been determined using spectral density method. The catchments is subjected to both rainfall and snowfall. For short term rainfall fluctuation with a return period  2, 3, 4 months, the lag times were found 0.18, 0.5 and 0.083 month, respectively.

Modeling Time Series Data for Supervised Learning

Science.gov (United States)

Baydogan, Mustafa Gokce

2012-01-01

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

The concentration of 137Cs and stable Cs in zooplankton in the western North Pacific in relation to their taxonomic composition

International Nuclear Information System (INIS)

Kaeriyama, Hideki; Watabe, Teruhisa; Kusakabe, Masashi

2008-01-01

The objective of this study is to obtain information on the background level of 137 Cs in zooplankton in the waters close to Rokkasho-mura in Aomori Prefecture, Japan, where a large-scale project has been progressively promoted to establish the nuclear fuel cycle. Prior to the full-scale operation of the spent nuclear fuel reprocessing plant, zooplankton samples were collected in May and October 2005, June 2006, and June 2007 from the surface water (0-5 m depth). The samples were analyzed to determine the concentrations of 137 Cs and stable Cs in relation to taxonomic composition. The numerical abundance of the plankton varied from 253 to 1514 inds. m -3 . Taxonomic composition differed between the two sampling periods. Although copepods formed the most abundant taxonomic group during both seasons, gelatinous plankton (chaetognaths, siphonophores, appendicularians and doliolids) were more abundant in October 2005 than in June 2006 and June 2007. The concentration of 137 Cs in zooplankton varied from 11 to 24 mBq kg-WW -1 . At the same station, the 137 Cs concentration in zooplankton in October 2005 was almost twice as much as that in June 2006, although the concentration of 137 Cs in seawater did not show a difference. The concentration of stable Cs was measured for each taxonomic group: that in gelatinous zooplankton (chaetognaths) was higher than that in crustacean zooplankton (copepods, euphausiids and amphipods). These results suggest that the concentration of 137 Cs in zooplankton is affected by the occurrence of gelatinous zooplankton. (author)

Empirical method to measure stochasticity and multifractality in nonlinear time series

Science.gov (United States)

Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping

2013-12-01

An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.

Seasonal signatures in SFG vibrational spectra of the sea surface nanolayer at Boknis Eck Time Series Station (SW Baltic Sea

Directory of Open Access Journals (Sweden)

K. Laß

2013-08-01

Full Text Available The very thin sea surface nanolayer on top of the sea surface microlayer, sometimes just one monomolecular layer thick, forms the interface between ocean and atmosphere. Due to the small dimension and tiny amount of substance, knowledge about the development of the layer in the course of the year is scarce. In this work, the sea surface nanolayer at Boknis Eck Time Series Station (BE, southwestern Baltic Sea, has been investigated over a period of three and a half years. Surface water samples were taken monthly by screen sampling and were analyzed in terms of organic content and composition by sum frequency generation spectroscopy, which is specifically sensitive to interfacial layers. A yearly periodicity has been observed with a pronounced abundance of sea surface nanolayer material (such as carbohydrate-rich material during the summer months. On the basis of our results we conclude that the abundance of organic material in the nanolayer at Boknis Eck is not directly related to phytoplankton abundance alone. We speculate that indeed sloppy feeding of zooplankton together with photochemical and/or microbial processing of organic precursor compounds is responsible for the pronounced seasonality.

Seasonal signatures in SFG vibrational spectra of the sea surface nanolayer at Boknis Eck Time Series Station (SW Baltic Sea)

Science.gov (United States)

Laß, K.; Bange, H. W.; Friedrichs, G.

2013-08-01

The very thin sea surface nanolayer on top of the sea surface microlayer, sometimes just one monomolecular layer thick, forms the interface between ocean and atmosphere. Due to the small dimension and tiny amount of substance, knowledge about the development of the layer in the course of the year is scarce. In this work, the sea surface nanolayer at Boknis Eck Time Series Station (BE), southwestern Baltic Sea, has been investigated over a period of three and a half years. Surface water samples were taken monthly by screen sampling and were analyzed in terms of organic content and composition by sum frequency generation spectroscopy, which is specifically sensitive to interfacial layers. A yearly periodicity has been observed with a pronounced abundance of sea surface nanolayer material (such as carbohydrate-rich material) during the summer months. On the basis of our results we conclude that the abundance of organic material in the nanolayer at Boknis Eck is not directly related to phytoplankton abundance alone. We speculate that indeed sloppy feeding of zooplankton together with photochemical and/or microbial processing of organic precursor compounds is responsible for the pronounced seasonality.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Clinical time series prediction: towards a hierarchical dynamical system framework

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

Turbulencelike Behavior of Seismic Time Series

International Nuclear Information System (INIS)

Manshour, P.; Saberi, S.; Sahimi, Muhammad; Peinke, J.; Pacheco, Amalio F.; Rahimi Tabar, M. Reza

2009-01-01

We report on a stochastic analysis of Earth's vertical velocity time series by using methods originally developed for complex hierarchical systems and, in particular, for turbulent flows. Analysis of the fluctuations of the detrended increments of the series reveals a pronounced transition in their probability density function from Gaussian to non-Gaussian. The transition occurs 5-10 hours prior to a moderate or large earthquake, hence representing a new and reliable precursor for detecting such earthquakes

Characterizing time series: when Granger causality triggers complex networks

Science.gov (United States)

Ge, Tian; Cui, Yindong; Lin, Wei; Kurths, Jürgen; Liu, Chong

2012-08-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIHMassachusetts Institute of Technology-Beth Israel Hospital. human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.

Characterizing time series: when Granger causality triggers complex networks

International Nuclear Information System (INIS)

Ge Tian; Cui Yindong; Lin Wei; Liu Chong; Kurths, Jürgen

2012-01-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length. (paper)

River discharge as a major driving force on spatial and temporal variations in zooplankton biomass and community structure in the Godavari estuary India.

Science.gov (United States)

Venkataramana, V; Sarma, V V S S; Matta Reddy, Alavala

2017-08-28

Variability in horizontal zooplankton biomass distribution was investigated over 13 months in the Godavari estuary, along with physical (river discharge, temperature, salinity), chemical (nutrients, particulate organic matter), biological (phytoplankton biomass), and geological (suspended matter) properties to examine the influencing factors on their spatial and temporal variabilities. The entire estuary was filled with freshwater during peak discharge period and salinity near zero, increased to ~ 34 psu during dry period with relatively high nutrient levels during former than the latter period. Due to low flushing time ( 500 mg L -1 ) during peak discharge period, picoplankton (cyanophyceae) contributed significantly to the phytoplankton biomass (Chl-a) whereas microplankton and nanoplankton (bacillariophyceae, and chlorophyceae) during moderate and mostly microplankton during dry period. Zooplankton biomass was the lowest during peak discharge period and increased during moderate followed by dry period. The zooplankton abundance was controlled by dead organic matter during peak discharge period, while both phytoplankton biomass and dead organic matter during moderate discharge and mostly phytoplankton biomass during dry period. This study suggests that significant modification of physico-chemical properties by river discharge led to changes in phytoplankton composition and dead organic matter concentrations that alters biomass, abundance, and composition of zooplankton in the Godavari estuary.

Zooplankton composition of the Kalpeni and Agatti atolls, Lakshadweep archiplago

Digital Repository Service at National Institute of Oceanography (India)

Achuthankutty, C.T.; Nair, S.R.S.; Haridas, P.; Madhupratap, M.

Composition of zooplankton in the lagoons was quite different from that of the sea and to a large extent, was independent of oceanic influence While copepods were dominant in the sea, meroplankton, particularly brachyuran zoeae constituted...

Multivariate time series analysis with R and financial applications

CERN Document Server

Tsay, Ruey S

2013-01-01

Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-worl

Measurements of spatial population synchrony: influence of time series transformations.

Science.gov (United States)

Chevalier, Mathieu; Laffaille, Pascal; Ferdy, Jean-Baptiste; Grenouillet, Gaël

2015-09-01

Two mechanisms have been proposed to explain spatial population synchrony: dispersal among populations, and the spatial correlation of density-independent factors (the "Moran effect"). To identify which of these two mechanisms is driving spatial population synchrony, time series transformations (TSTs) of abundance data have been used to remove the signature of one mechanism, and highlight the effect of the other. However, several issues with TSTs remain, and to date no consensus has emerged about how population time series should be handled in synchrony studies. Here, by using 3131 time series involving 34 fish species found in French rivers, we computed several metrics commonly used in synchrony studies to determine whether a large-scale climatic factor (temperature) influenced fish population dynamics at the regional scale, and to test the effect of three commonly used TSTs (detrending, prewhitening and a combination of both) on these metrics. We also tested whether the influence of TSTs on time series and population synchrony levels was related to the features of the time series using both empirical and simulated time series. For several species, and regardless of the TST used, we evidenced a Moran effect on freshwater fish populations. However, these results were globally biased downward by TSTs which reduced our ability to detect significant signals. Depending on the species and the features of the time series, we found that TSTs could lead to contradictory results, regardless of the metric considered. Finally, we suggest guidelines on how population time series should be processed in synchrony studies.

Some ecological implications of a neem (azadirachtin) insecticide disturbance to zooplankton communities in forest pond enclosures.

Science.gov (United States)

Kreutzweiser, David P; Sutton, Trent M; Back, Richard C; Pangle, Kevin L; Thompson, Dean G

2004-04-28

A neem-based insecticide, Neemix 4.5, was applied to forest pond enclosures at concentrations of 10, 17, and 28 microg l(-1) azadirachtin (the active ingredient). At these test concentrations, significant, concentration-dependent reductions in numbers of adult copepods were observed, but immature copepod and cladoceran populations were unaffected. There was no evidence of recovery of adult copepods within the sampling season (May to October). The ecological significance of this disturbance to the zooplankton community was examined by determining biomass as a measure of food availability for higher predators, plankton community respiration, dissolved oxygen (DO) concentrations, and conductivity as functional indicators of ecosystem stress, and zooplankton food web stability as a measure of effects on trophic structure. The selective removal or reduction of adult copepods was sufficient to measurably reduce total zooplankton biomass for several weeks mid-season. During the period of maximal impact (about 4-9 weeks after the applications), total plankton community respiration was significantly reduced, and this appeared to contribute to significant, concentration-dependent increases in dissolved oxygen and decreases in conductivity among treated enclosures. The reductions in adult copepods resulted in negative effects on zooplankton food web stability through eliminations of a trophic link and reduced interactions and connectance. Comparing the results here to those from a previous study with tebufenozide, which was selectively toxic to cladocerans and had little effect on food web stability, indicates that differential sensitivity among taxa can influence the ecological significance of pesticide effects on zooplankton communities.

Stochastic time series analysis of hydrology data for water resources

Science.gov (United States)

Sathish, S.; Khadar Babu, S. K.

2017-11-01

The prediction to current publication of stochastic time series analysis in hydrology and seasonal stage. The different statistical tests for predicting the hydrology time series on Thomas-Fiering model. The hydrology time series of flood flow have accept a great deal of consideration worldwide. The concentration of stochastic process areas of time series analysis method are expanding with develop concerns about seasonal periods and global warming. The recent trend by the researchers for testing seasonal periods in the hydrologic flowseries using stochastic process on Thomas-Fiering model. The present article proposed to predict the seasonal periods in hydrology using Thomas-Fiering model.

Neural network versus classical time series forecasting models

Science.gov (United States)

Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

2017-05-01

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

Nonlinear time series analysis of the human electrocardiogram

International Nuclear Information System (INIS)

Perc, Matjaz

2005-01-01

We analyse the human electrocardiogram with simple nonlinear time series analysis methods that are appropriate for graduate as well as undergraduate courses. In particular, attention is devoted to the notions of determinism and stationarity in physiological data. We emphasize that methods of nonlinear time series analysis can be successfully applied only if the studied data set originates from a deterministic stationary system. After positively establishing the presence of determinism and stationarity in the studied electrocardiogram, we calculate the maximal Lyapunov exponent, thus providing interesting insights into the dynamics of the human heart. Moreover, to facilitate interest and enable the integration of nonlinear time series analysis methods into the curriculum at an early stage of the educational process, we also provide user-friendly programs for each implemented method

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

Science.gov (United States)

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Hidden Markov Models for Time Series An Introduction Using R

CERN Document Server

Zucchini, Walter

2009-01-01

Illustrates the flexibility of HMMs as general-purpose models for time series data. This work presents an overview of HMMs for analyzing time series data, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts and categorical observations.

Constructing ordinal partition transition networks from multivariate time series.

Science.gov (United States)

Zhang, Jiayang; Zhou, Jie; Tang, Ming; Guo, Heng; Small, Michael; Zou, Yong

2017-08-10

A growing number of algorithms have been proposed to map a scalar time series into ordinal partition transition networks. However, most observable phenomena in the empirical sciences are of a multivariate nature. We construct ordinal partition transition networks for multivariate time series. This approach yields weighted directed networks representing the pattern transition properties of time series in velocity space, which hence provides dynamic insights of the underling system. Furthermore, we propose a measure of entropy to characterize ordinal partition transition dynamics, which is sensitive to capturing the possible local geometric changes of phase space trajectories. We demonstrate the applicability of pattern transition networks to capture phase coherence to non-coherence transitions, and to characterize paths to phase synchronizations. Therefore, we conclude that the ordinal partition transition network approach provides complementary insight to the traditional symbolic analysis of nonlinear multivariate time series.

Permutation entropy of finite-length white-noise time series.

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Little, Douglas J; Kane, Deb M

2016-08-01

Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a time series. While the PE of white noise is well understood in the long time-series limit, analysis in the general case is currently lacking. Here the expectation value and variance of white-noise PE are derived as functions of the number of ordinal pattern trials, N, and the embedding dimension, D. It is demonstrated that the probability distribution of the white-noise PE converges to a χ^{2} distribution with D!-1 degrees of freedom as N becomes large. It is further demonstrated that the PE variance for an arbitrary time series can be estimated as the variance of a related metric, the Kullback-Leibler entropy (KLE), allowing the qualitative N≫D! condition to be recast as a quantitative estimate of the N required to achieve a desired PE calculation precision. Application of this theory to statistical inference is demonstrated in the case of an experimentally obtained noise series, where the probability of obtaining the observed PE value was calculated assuming a white-noise time series. Standard statistical inference can be used to draw conclusions whether the white-noise null hypothesis can be accepted or rejected. This methodology can be applied to other null hypotheses, such as discriminating whether two time series are generated from different complex system states.

Multiresolution analysis of Bursa Malaysia KLCI time series

Science.gov (United States)

Ismail, Mohd Tahir; Dghais, Amel Abdoullah Ahmed

2017-05-01

In general, a time series is simply a sequence of numbers collected at regular intervals over a period. Financial time series data processing is concerned with the theory and practice of processing asset price over time, such as currency, commodity data, and stock market data. The primary aim of this study is to understand the fundamental characteristics of selected financial time series by using the time as well as the frequency domain analysis. After that prediction can be executed for the desired system for in sample forecasting. In this study, multiresolution analysis which the assist of discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transform (MODWT) will be used to pinpoint special characteristics of Bursa Malaysia KLCI (Kuala Lumpur Composite Index) daily closing prices and return values. In addition, further case study discussions include the modeling of Bursa Malaysia KLCI using linear ARIMA with wavelets to address how multiresolution approach improves fitting and forecasting results.

Size-dependent responses of zooplankton to submerged macrophyte restoration in a subtropical shallow lake

Science.gov (United States)

Zeng, Lei; He, Feng; Zhang, Yi; Liu, Biyun; Dai, Zhigang; Zhou, Qiaohong; Wu, Zhenbin

2018-03-01

To explore the size-dependent responses of zooplankton to submerged macrophyte restoration, we collected macrophyte, zooplankton and water quality samples seasonally from a subtropical shallow lake from 2010 to 2012. Special attention was given to changes in rotifers and crustaceans (cladocerans and copepods). The rotifers were grouped into three size classes (400 μm) to explore their size-related responses to macrophyte restoration. The results showed that during the restoration, the annual mean biomass and macrophyte coverage increased significantly from 0 to 637 g/m2 and 0 to 27%, respectively. In response, the density and biomass of crustaceans and the crustacean-to-rotifer ratio increased significantly, while the rotifer density decreased significantly. Moreover, rotifers showed significant sizedependent responses to macrophyte restoration. Specially, rotifers sized zooplankton tended to boom, while that of small rotifers was inhibited during macrophyte restoration. Redundancy analysis (RDA) revealed positive correlations between macrophytes and crustaceans, rotifers and COD or Chl- a, but negative correlations between macrophytes and COD or Chl- a, and between crustaceans and Chl- a. Moreover, the results indicate that increased predation on phytoplankton by large-sized zooplankton might be an important mechanism for macrophyte restoration during development of aquatic ecosystems, and that this mechanism played a very important role in promoting the formation of a clear-water state in subtropical shallow lakes.

Modelling bursty time series

International Nuclear Information System (INIS)

Vajna, Szabolcs; Kertész, János; Tóth, Bálint

2013-01-01

Many human-related activities show power-law decaying interevent time distribution with exponents usually varying between 1 and 2. We study a simple task-queuing model, which produces bursty time series due to the non-trivial dynamics of the task list. The model is characterized by a priority distribution as an input parameter, which describes the choice procedure from the list. We give exact results on the asymptotic behaviour of the model and we show that the interevent time distribution is power-law decaying for any kind of input distributions that remain normalizable in the infinite list limit, with exponents tunable between 1 and 2. The model satisfies a scaling law between the exponents of interevent time distribution (β) and autocorrelation function (α): α + β = 2. This law is general for renewal processes with power-law decaying interevent time distribution. We conclude that slowly decaying autocorrelation function indicates long-range dependence only if the scaling law is violated. (paper)

Timing calibration and spectral cleaning of LOFAR time series data

NARCIS (Netherlands)

Corstanje, A.; Buitink, S.; Enriquez, J. E.; Falcke, H.; Horandel, J. R.; Krause, M.; Nelles, A.; Rachen, J. P.; Schellart, P.; Scholten, O.; ter Veen, S.; Thoudam, S.; Trinh, T. N. G.

We describe a method for spectral cleaning and timing calibration of short time series data of the voltage in individual radio interferometer receivers. It makes use of phase differences in fast Fourier transform (FFT) spectra across antenna pairs. For strong, localized terrestrial sources these are

Time series momentum and contrarian effects in the Chinese stock market

Science.gov (United States)

Shi, Huai-Long; Zhou, Wei-Xing

2017-10-01

This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-specific characteristics. Our findings indicate that there is a time series momentum effect in the short run and a contrarian effect in the long run in the Chinese stock market. The performances of the time series momentum and contrarian strategies are highly dependent on the look-back and holding periods and firm-specific characteristics.

Time-Series Analysis: A Cautionary Tale

Science.gov (United States)

Damadeo, Robert

2015-01-01

Time-series analysis has often been a useful tool in atmospheric science for deriving long-term trends in various atmospherically important parameters (e.g., temperature or the concentration of trace gas species). In particular, time-series analysis has been repeatedly applied to satellite datasets in order to derive the long-term trends in stratospheric ozone, which is a critical atmospheric constituent. However, many of the potential pitfalls relating to the non-uniform sampling of the datasets were often ignored and the results presented by the scientific community have been unknowingly biased. A newly developed and more robust application of this technique is applied to the Stratospheric Aerosol and Gas Experiment (SAGE) II version 7.0 ozone dataset and the previous biases and newly derived trends are presented.

Characterizing interdependencies of multiple time series theory and applications

CERN Document Server

Hosoya, Yuzo; Takimoto, Taro; Kinoshita, Ryo

2017-01-01

This book introduces academic researchers and professionals to the basic concepts and methods for characterizing interdependencies of multiple time series in the frequency domain. Detecting causal directions between a pair of time series and the extent of their effects, as well as testing the non existence of a feedback relation between them, have constituted major focal points in multiple time series analysis since Granger introduced the celebrated definition of causality in view of prediction improvement. Causality analysis has since been widely applied in many disciplines. Although most analyses are conducted from the perspective of the time domain, a frequency domain method introduced in this book sheds new light on another aspect that disentangles the interdependencies between multiple time series in terms of long-term or short-term effects, quantitatively characterizing them. The frequency domain method includes the Granger noncausality test as a special case. Chapters 2 and 3 of the book introduce an i...

A perturbative approach for enhancing the performance of time series forecasting.

Science.gov (United States)

de Mattos Neto, Paulo S G; Ferreira, Tiago A E; Lima, Aranildo R; Vasconcelos, Germano C; Cavalcanti, George D C

2017-04-01

This paper proposes a method to perform time series prediction based on perturbation theory. The approach is based on continuously adjusting an initial forecasting model to asymptotically approximate a desired time series model. First, a predictive model generates an initial forecasting for a time series. Second, a residual time series is calculated as the difference between the original time series and the initial forecasting. If that residual series is not white noise, then it can be used to improve the accuracy of the initial model and a new predictive model is adjusted using residual series. The whole process is repeated until convergence or the residual series becomes white noise. The output of the method is then given by summing up the outputs of all trained predictive models in a perturbative sense. To test the method, an experimental investigation was conducted on six real world time series. A comparison was made with six other methods experimented and ten other results found in the literature. Results show that not only the performance of the initial model is significantly improved but also the proposed method outperforms the other results previously published. Copyright © 2017 Elsevier Ltd. All rights reserved.

Drunk driving detection based on classification of multivariate time series.

Science.gov (United States)

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Seasonal and inter-annual variations in methyl mercury concentrations in zooplankton from boreal lakes impacted by deforestation or natural forest fires.

Science.gov (United States)

Garcia, Edenise; Carignan, Richard; Lean, David R S

2007-08-01

We compared the effects of natural and anthropogenic watershed disturbances on methyl mercury (MeHg) concentration in bulk zooplankton from boreal Shield lakes. MeHg in zooplankton was monitored for three years in nine lakes impacted by deforestation, in nine lakes impacted by wildfire, and in twenty lakes with undisturbed catchments. Lakes were sampled during spring, mid- and late summer. MeHg in zooplankton showed a seasonal trend: concentrations were the lowest in spring, then peaked in mid-summer and decreased in late summer. Over the three study years, MeHg concentrations observed in mid-summer in zooplankton from forest harvested lakes were significantly higher than in reference and fire-impacted lakes, whereas differences between these two groups of lakes were not significant. The pattern of distribution of MeHg in zooplankton during the different seasons paralleled that of dissolved organic carbon (DOC), which is known as a vector of Hg from watershed soils to lake water. Besides DOC, MeHg in zooplankton also showed a positive significant correlation with epilimnetic temperature and sulfate concentrations. An inter-annual decreasing trend in MeHg was observed in zooplankton from reference and fire-impacted lakes. In forest harvested lakes, however, MeHg concentrations remained higher and nearly constant over three years following the impact. Overall these results indicate that the MeHg pulse observed in zooplankton following deforestation by harvesting is relatively long-lived, and may have repercussions to the accumulation of MeHg along the food chain. Therefore, potential effects of deforestation on the Hg contamination of fish should be taken into account in forest management practices.

Evaluation of scaling invariance embedded in short time series.

Directory of Open Access Journals (Sweden)

Xue Pan

Full Text Available Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2. Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03 and sharp confidential interval (standard deviation ≤0.05. Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

Evaluation of scaling invariance embedded in short time series.

Science.gov (United States)

Pan, Xue; Hou, Lei; Stephen, Mutua; Yang, Huijie; Zhu, Chenping

2014-01-01

Scaling invariance of time series has been making great contributions in diverse research fields. But how to evaluate scaling exponent from a real-world series is still an open problem. Finite length of time series may induce unacceptable fluctuation and bias to statistical quantities and consequent invalidation of currently used standard methods. In this paper a new concept called correlation-dependent balanced estimation of diffusion entropy is developed to evaluate scale-invariance in very short time series with length ~10(2). Calculations with specified Hurst exponent values of 0.2,0.3,...,0.9 show that by using the standard central moving average de-trending procedure this method can evaluate the scaling exponents for short time series with ignorable bias (≤0.03) and sharp confidential interval (standard deviation ≤0.05). Considering the stride series from ten volunteers along an approximate oval path of a specified length, we observe that though the averages and deviations of scaling exponents are close, their evolutionary behaviors display rich patterns. It has potential use in analyzing physiological signals, detecting early warning signals, and so on. As an emphasis, the our core contribution is that by means of the proposed method one can estimate precisely shannon entropy from limited records.

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

Science.gov (United States)

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

The temporal dynamics of zooplankton communities of different types of water bodies within Ichniansky National Park

Directory of Open Access Journals (Sweden)

Z. V. Burian

2017-05-01

Full Text Available In recent decades, the influence of anthropogenic impact on aquatic ecosystems has increased. This has led to a restructuring of aquatic ecosystems and affected the structural and functional organization of groups of aquatic organisms, causing qualitative and quantitative changes. Particular attention is drawn to the different types of water bodies of protected areas like IchnyanskyNational Park, which is located in Ichnyansky district of Chernihiv region. This park is a newly created one, so the reduction in intensity of anthropogenic pressure can be traced within its waters. Zooplankton plays an important role in the functioning of trophic networks because it transfers energy from producers and primary consumers to young fish and planktonophagous fish. Therefore, three main groups of zooplankton were chosen as the object of study: rotifers (class Eurotatoria, cladocerans (class Branchiopoda, order Cladocera, different age stages of copepods (class Copepoda, and also ostracods (Class Ostracoda. The zooplankton used as research material was collected in the daytime in spring (April, summer (late July – early August and autumn (late September – early October in the years 2015–2016 from ten experimental stations. During this period 81 species of zooplankton were recorded within heterogeneous reservoirs of IchnianskyNational Park. Monogonont rotifers (subclass Monogononta included 35 species (43% of all species and bdelloid rotifers (subclass Bdelloidea, cladocerns, comprised 28 species (35%, and copepods included 18 species (22%. The faunal range of zooplankton over different years and seasons was characterized by the predominance of the rotator complex in spring, rotator-cladocerans and cladocerans in summer, and of the cladocerans complex in autumn. This was due to the formation during spring and summer of favourable conditions in the waters for filter feeders, which consist generally of rotifers and cladocerans. In autumn the water

Effect of planktivores, zooplankton, and macrobenthos on material flow in a small lake

International Nuclear Information System (INIS)

Starkel, W.M.

1985-01-01

Planktivores, zooplankton grazers, and macrobenthos were studied to determine how changes in animal community structure may alter the flow of material in Dunham Pond, CT. Chaoborus and chironomid larvae were studied to determine how they affect the flux of matter across the sediment/water interface. This was done by incubating undisturbed cores in situ and relating changes in water chemistry to larval density. The log-transformed flux rates of iron, manganese, and phosphorus were linearly related to larval biomass. Functional groups may be successfully used to predict rates of material flow. Changes in the mass of macroinvertebrates affect the flux rates of redox-active substances across the sediment/water interface. The use of population densities and feeding characteristics to estimate trophic transfer in Dunham Pond indicate that (1) visual planktivory by larval perch may result in overutilization of prey, (2) ambush planktivory by univoltine Chaoborus appears to under utilize prey, and (3) zooplankton grazing tracks net primary productivity, regardless of zooplankton community structure. Animal groups cycle 30-100% of the phosphorus required for 14 C productivity in Dunham Pond

Geomechanical time series and its singularity spectrum analysis

Czech Academy of Sciences Publication Activity Database

Lyubushin, Alexei A.; Kaláb, Zdeněk; Lednická, Markéta

2012-01-01

Roč. 47, č. 1 (2012), s. 69-77 ISSN 1217-8977 R&D Projects: GA ČR GA105/09/0089 Institutional research plan: CEZ:AV0Z30860518 Keywords : geomechanical time series * singularity spectrum * time series segmentation * laser distance meter Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 0.347, year: 2012 http://www.akademiai.com/content/88v4027758382225/fulltext.pdf

Pseudo-random bit generator based on lag time series

Science.gov (United States)

García-Martínez, M.; Campos-Cantón, E.

2014-12-01

In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped xn against xn+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

Non-linear forecasting in high-frequency financial time series

Science.gov (United States)

Strozzi, F.; Zaldívar, J. M.

2005-08-01

A new methodology based on state space reconstruction techniques has been developed for trading in financial markets. The methodology has been tested using 18 high-frequency foreign exchange time series. The results are in apparent contradiction with the efficient market hypothesis which states that no profitable information about future movements can be obtained by studying the past prices series. In our (off-line) analysis positive gain may be obtained in all those series. The trading methodology is quite general and may be adapted to other financial time series. Finally, the steps for its on-line application are discussed.

Analysis of JET ELMy time series

International Nuclear Information System (INIS)

Zvejnieks, G.; Kuzovkov, V.N.

2005-01-01

Full text: Achievement of the planned operational regime in the next generation tokamaks (such as ITER) still faces principal problems. One of the main challenges is obtaining the control of edge localized modes (ELMs), which should lead to both long plasma pulse times and reasonable divertor life time. In order to control ELMs the hypothesis was proposed by Degeling [1] that ELMs exhibit features of chaotic dynamics and thus a standard chaos control methods might be applicable. However, our findings which are based on the nonlinear autoregressive (NAR) model contradict this hypothesis for JET ELMy time-series. In turn, it means that ELM behavior is of a relaxation or random type. These conclusions coincide with our previous results obtained for ASDEX Upgrade time series [2]. [1] A.W. Degeling, Y.R. Martin, P.E. Bak, J. B.Lister, and X. Llobet, Plasma Phys. Control. Fusion 43, 1671 (2001). [2] G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm, Physics of Plasmas 11, 5658 (2004)

Cyanobacteria dominance influences resource use efficiency and community turnover in phytoplankton and zooplankton communities.

Science.gov (United States)

Filstrup, Christopher T; Hillebrand, Helmut; Heathcote, Adam J; Harpole, W Stanley; Downing, John A

2014-04-01

Freshwater biodiversity loss potentially disrupts ecosystem services related to water quality and may negatively impact ecosystem functioning and temporal community turnover. We analysed a data set containing phytoplankton and zooplankton community data from 131 lakes through 9 years in an agricultural region to test predictions that plankton communities with low biodiversity are less efficient in their use of limiting resources and display greater community turnover (measured as community dissimilarity). Phytoplankton resource use efficiency (RUE = biomass per unit resource) was negatively related to phytoplankton evenness (measured as Pielou's evenness), whereas zooplankton RUE was positively related to phytoplankton evenness. Phytoplankton and zooplankton RUE were high and low, respectively, when Cyanobacteria, especially Microcystis sp., dominated. Phytoplankton communities displayed slower community turnover rates when dominated by few genera. Our findings, which counter findings of many terrestrial studies, suggest that Cyanobacteria dominance may play important roles in ecosystem functioning and community turnover in nutrient-enriched lakes. © 2014 John Wiley & Sons Ltd/CNRS.

The Statistical Analysis of Time Series

CERN Document Server

Anderson, T W

2011-01-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George

Analysis of time series and size of equivalent sample

International Nuclear Information System (INIS)

Bernal, Nestor; Molina, Alicia; Pabon, Daniel; Martinez, Jorge

2004-01-01

In a meteorological context, a first approach to the modeling of time series is to use models of autoregressive type. This allows one to take into account the meteorological persistence or temporal behavior, thereby identifying the memory of the analyzed process. This article seeks to pre-sent the concept of the size of an equivalent sample, which helps to identify in the data series sub periods with a similar structure. Moreover, in this article we examine the alternative of adjusting the variance of the series, keeping in mind its temporal structure, as well as an adjustment to the covariance of two time series. This article presents two examples, the first one corresponding to seven simulated series with autoregressive structure of first order, and the second corresponding to seven meteorological series of anomalies of the air temperature at the surface in two Colombian regions

Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

Energy Technology Data Exchange (ETDEWEB)

Simmhan, Yogesh; Noor, Muhammad Usman

2013-10-09

Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 data points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.

Forecasting with nonlinear time series models

DEFF Research Database (Denmark)

Kock, Anders Bredahl; Teräsvirta, Timo

In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econo- metrics are presented and some of their properties discussed. This in- cludes two models based on universal approximators: the Kolmogorov- Gabor polynomial model...... applied to economic fore- casting problems, is briefly highlighted. A number of large published studies comparing macroeconomic forecasts obtained using different time series models are discussed, and the paper also contains a small simulation study comparing recursive and direct forecasts in a partic...... and two versions of a simple artificial neural network model. Techniques for generating multi-period forecasts from nonlinear models recursively are considered, and the direct (non-recursive) method for this purpose is mentioned as well. Forecasting with com- plex dynamic systems, albeit less frequently...

The crustacean zooplankton assemblage of a relatively pristine Utor ...

African Journals Online (AJOL)

The water quality and crustacean zooplankton of Utor River, a relatively pristine freshwater body in Edo State, Nigeria was investigated at four stations. The Utor River is slightly acidic, well oxygenated, oligotrophic and low in solids, conductivity, cations and heavy metals. A total of 380 individuals comprising eleven taxa ...

Inter- and intra-specific diurnal habitat selection of zooplankton during the spring bloom observed by Video Plankton Recorder

DEFF Research Database (Denmark)

Sainmont, Julie; Gislason, Astthor; Heuschele, Jan

2014-01-01

Recorder (VPR), a tool that allows mapping of vertical zooplankton distributions with a far greater spatial resolution than conventional zooplankton nets. The study took place over a full day–night cycle in Disko Bay, Greenland, during the peak of the phytoplankton spring bloom. The sampling revealed...

Nonparametric factor analysis of time series

OpenAIRE

Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

1998-01-01

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

Zooplankton diversity of a protected and vulnerable wetland system in southern South America (Llancanelo area, Argentina

Directory of Open Access Journals (Sweden)

D. Sabina D’Ambrosio

2016-02-01

Full Text Available Abstract In arid regions, climatic conditions exert a great control on the aquatic systems present, but recent changes in climate have produced an enhanced salinization of the aquatic environments located there. Consequently, a major reduction in biodiversity would be expected in those wetlands that were originally fresh water. Salinity is a principal cause of reduced biodiversity particularly in zooplankton because few of those species can adapt to the salt pressure of saline environments. Therefore, the aim of this study was to gain essential information on the diversity of aquatic invertebrates in Llancanelo basin by focussing the analysis on the zooplankton community and exploring seasonal and spatial differences in the zooplankton assemblages of this vulnerable wetland system within an arid region of Argentina. Seasonal samples were taken at nine sites in the basin (a shallow lake, 4 springs, streams, and the Malargüe River. A total of 45 species were identified. The zooplankton abundance in the lake displayed a clear seasonal contrast and was higher than that recorded in the springs and lotic environments. Boeckella poopoensis, Fabrea salina, and Brachionus plicatilis predominated in the lake, indicating their halophilia. The presence of the crustaceans Alona sp., Macrocyclops albidus, and Paracyclops fimbriatus was restricted to the springs; whereas Notholca labis and Notholca squamula were found only in running water. The zooplankton species richness in the Llancanelo area is low because of both the salt content in the lake and the irregularity of freshwater entry in all locations during the annual cycle.

Time Series Outlier Detection Based on Sliding Window Prediction

Directory of Open Access Journals (Sweden)

Yufeng Yu

2014-01-01

Full Text Available In order to detect outliers in hydrological time series data for improving data quality and decision-making quality related to design, operation, and management of water resources, this research develops a time series outlier detection method for hydrologic data that can be used to identify data that deviate from historical patterns. The method first built a forecasting model on the history data and then used it to predict future values. Anomalies are assumed to take place if the observed values fall outside a given prediction confidence interval (PCI, which can be calculated by the predicted value and confidence coefficient. The use of PCI as threshold is mainly on the fact that it considers the uncertainty in the data series parameters in the forecasting model to address the suitable threshold selection problem. The method performs fast, incremental evaluation of data as it becomes available, scales to large quantities of data, and requires no preclassification of anomalies. Experiments with different hydrologic real-world time series showed that the proposed methods are fast and correctly identify abnormal data and can be used for hydrologic time series analysis.

Metagenomics meets time series analysis: unraveling microbial community dynamics

NARCIS (Netherlands)

Faust, K.; Lahti, L.M.; Gonze, D.; Vos, de W.M.; Raes, J.

2015-01-01

The recent increase in the number of microbial time series studies offers new insights into the stability and dynamics of microbial communities, from the world's oceans to human microbiota. Dedicated time series analysis tools allow taking full advantage of these data. Such tools can reveal periodic

Time series forecasting based on deep extreme learning machine

NARCIS (Netherlands)

Guo, Xuqi; Pang, Y.; Yan, Gaowei; Qiao, Tiezhu; Yang, Guang-Hong; Yang, Dan

2017-01-01

Multi-layer Artificial Neural Networks (ANN) has caught widespread attention as a new method for time series forecasting due to the ability of approximating any nonlinear function. In this paper, a new local time series prediction model is established with the nearest neighbor domain theory, in

False-nearest-neighbors algorithm and noise-corrupted time series

International Nuclear Information System (INIS)

Rhodes, C.; Morari, M.

1997-01-01

The false-nearest-neighbors (FNN) algorithm was originally developed to determine the embedding dimension for autonomous time series. For noise-free computer-generated time series, the algorithm does a good job in predicting the embedding dimension. However, the problem of predicting the embedding dimension when the time-series data are corrupted by noise was not fully examined in the original studies of the FNN algorithm. Here it is shown that with large data sets, even small amounts of noise can lead to incorrect prediction of the embedding dimension. Surprisingly, as the length of the time series analyzed by FNN grows larger, the cause of incorrect prediction becomes more pronounced. An analysis of the effect of noise on the FNN algorithm and a solution for dealing with the effects of noise are given here. Some results on the theoretically correct choice of the FNN threshold are also presented. copyright 1997 The American Physical Society

Biochemical studies on some zooplankton off the west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Goswami, S.C.; Rao, T.S.S.; Matondkar, S.G.P.

Proximate biochemical analyses on twelve zooplankton species showed that protein was the predominant biochemical component followed by lipid. Carbohydrate content was very low especially in species with high water content or calcareous shell...

Elemental (C, H, N) composition of zooplankton from north Arabian Sea

Digital Repository Service at National Institute of Oceanography (India)

Matondkar, S.G.P.; Bhat, K.L.; Ansari, Z.A.; Parulekar, A.H.

found to be much lower than the values presently used in routine conversion factors. Such factors are now essentially needed for accounting role of zooplankton in sediment trap collections in Arabian Sea region...

CauseMap: fast inference of causality from complex time series.

Science.gov (United States)

Maher, M Cyrus; Hernandez, Ryan D

2015-01-01

Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data. Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM), a method for establishing causality from long time series data (≳25 observations). Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens' Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement CCM in Julia, a

CauseMap: fast inference of causality from complex time series

Directory of Open Access Journals (Sweden)

M. Cyrus Maher

2015-03-01

Full Text Available Background. Establishing health-related causal relationships is a central pursuit in biomedical research. Yet, the interdependent non-linearity of biological systems renders causal dynamics laborious and at times impractical to disentangle. This pursuit is further impeded by the dearth of time series that are sufficiently long to observe and understand recurrent patterns of flux. However, as data generation costs plummet and technologies like wearable devices democratize data collection, we anticipate a coming surge in the availability of biomedically-relevant time series data. Given the life-saving potential of these burgeoning resources, it is critical to invest in the development of open source software tools that are capable of drawing meaningful insight from vast amounts of time series data.Results. Here we present CauseMap, the first open source implementation of convergent cross mapping (CCM, a method for establishing causality from long time series data (≳25 observations. Compared to existing time series methods, CCM has the advantage of being model-free and robust to unmeasured confounding that could otherwise induce spurious associations. CCM builds on Takens’ Theorem, a well-established result from dynamical systems theory that requires only mild assumptions. This theorem allows us to reconstruct high dimensional system dynamics using a time series of only a single variable. These reconstructions can be thought of as shadows of the true causal system. If reconstructed shadows can predict points from opposing time series, we can infer that the corresponding variables are providing views of the same causal system, and so are causally related. Unlike traditional metrics, this test can establish the directionality of causation, even in the presence of feedback loops. Furthermore, since CCM can extract causal relationships from times series of, e.g., a single individual, it may be a valuable tool to personalized medicine. We implement

Time domain series system definition and gear set reliability modeling

International Nuclear Information System (INIS)

Xie, Liyang; Wu, Ningxiang; Qian, Wenxue

2016-01-01

Time-dependent multi-configuration is a typical feature for mechanical systems such as gear trains and chain drives. As a series system, a gear train is distinct from a traditional series system, such as a chain, in load transmission path, system-component relationship, system functioning manner, as well as time-dependent system configuration. Firstly, the present paper defines time-domain series system to which the traditional series system reliability model is not adequate. Then, system specific reliability modeling technique is proposed for gear sets, including component (tooth) and subsystem (tooth-pair) load history description, material priori/posterior strength expression, time-dependent and system specific load-strength interference analysis, as well as statistically dependent failure events treatment. Consequently, several system reliability models are developed for gear sets with different tooth numbers in the scenario of tooth root material ultimate tensile strength failure. The application of the models is discussed in the last part, and the differences between the system specific reliability model and the traditional series system reliability model are illustrated by virtue of several numerical examples. - Highlights: • A new type of series system, i.e. time-domain multi-configuration series system is defined, that is of great significance to reliability modeling. • Multi-level statistical analysis based reliability modeling method is presented for gear transmission system. • Several system specific reliability models are established for gear set reliability estimation. • The differences between the traditional series system reliability model and the new model are illustrated.

Track Irregularity Time Series Analysis and Trend Forecasting

Directory of Open Access Journals (Sweden)

Jia Chaolong

2012-01-01

Full Text Available The combination of linear and nonlinear methods is widely used in the prediction of time series data. This paper analyzes track irregularity time series data by using gray incidence degree models and methods of data transformation, trying to find the connotative relationship between the time series data. In this paper, GM (1,1 is based on first-order, single variable linear differential equations; after an adaptive improvement and error correction, it is used to predict the long-term changing trend of track irregularity at a fixed measuring point; the stochastic linear AR, Kalman filtering model, and artificial neural network model are applied to predict the short-term changing trend of track irregularity at unit section. Both long-term and short-term changes prove that the model is effective and can achieve the expected accuracy.

PRESEE: an MDL/MML algorithm to time-series stream segmenting.

Science.gov (United States)

Xu, Kaikuo; Jiang, Yexi; Tang, Mingjie; Yuan, Changan; Tang, Changjie

2013-01-01

Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmenting mainly focused on the issue of ameliorating precision instead of paying much attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream.

Biomass, organic carbon and calorific content of zooplankton from the Arabian Sea off Central West coast of India

Digital Repository Service at National Institute of Oceanography (India)

Krishnakumari, L.; Nair, V.R.

Organic carbon content and calorific values of zooplankton varied from 18.35 to 32.49% (av. 27.8%) and from 2.56 to 4.71 k cal. g-1 dry wt (av. 3.99) respectively. Areawise off Gujarat sustained higher standing stock of zooplankton (77.18 mg m-3...

Time-varying surrogate data to assess nonlinearity in nonstationary time series: application to heart rate variability.

Science.gov (United States)

Faes, Luca; Zhao, He; Chon, Ki H; Nollo, Giandomenico