Potential retention effect at fish farms boosts zooplankton abundance

NASA Astrophysics Data System (ADS)

Fernandez-Jover, D.; Toledo-Guedes, K.; Valero-Rodríguez, J. M.; Fernandez-Gonzalez, V.; Sanchez-Jerez, P.

2016-11-01

Coastal aquaculture activities influence wild macrofauna in natural environments due to the introduction of artificial structures, such as floating cages, that provide structural complexity in the pelagic system. This alters the abundance and distribution of the affected species and also their feeding behaviour and diet. Despite this, the effects of coastal aquaculture on zooplankton assemblages and the potential changes in their abundance and distribution remain largely unstudied. Traditional plankton sampling hauls between the farm mooring systems entail some practical difficulties. As an alternative, light traps were deployed at 2 farms in the SW Mediterranean during a whole warm season. Total zooplankton capture by traps at farms was higher than at control locations on every sampling night. It ranged from 3 to 10 times higher for the taxonomic groups: bivalvia, cladocera, cumacea, fish early-life-stages, gastropoda, polychaeta and tanaidacea; 10-20 times higher for amphipoda, chaetognatha, isopoda, mysidacea and ostracoda, and 22 times higher for copepoda and the crustacean juvenile stages zoea and megalopa. Permutational analysis showed significant differences for the most abundant zooplankton groups (copepoda, crustacean larvae, chaetognatha, cladocera, mysidacea and polychaeta). This marked incremental increase in zooplankton taxa at farms was consistent, irrespective of the changing environmental variables registered every night. Reasons for the greater abundance of zooplankton at farms are discussed, although results suggest a retention effect caused by cage structures rather than active attraction through physical or chemical cues.

Zooplankton species composition, abundance and biomass on the eastern Bering Sea shelf during summer: The potential role of water-column stability and nutrients in structuring the zooplankton community

NASA Astrophysics Data System (ADS)

Coyle, Kenneth O.; Pinchuk, Alexei I.; Eisner, Lisa B.; Napp, Jeffrey M.

2008-08-01

The southeastern Bering Sea sustains one of the largest fisheries in the United States, as well as wildlife resources that support valuable tourist and subsistence economies. The fish and wildlife populations in turn are sustained by a food web linking primary producers to apex predators through the zooplankton community. Recent shifts in climate toward warmer conditions may threaten these resources by altering productivity and trophic relationships in the ecosystem on the southeastern Bering Sea shelf. We examined the zooplankton community near the Pribilof Islands and on the middle shelf of the southeastern Bering Sea in summer of 1999 and 2004 to document differences and similarities in species composition, abundance and biomass by region and year. Between August 1999 and August 2004, the summer zooplankton community of the middle shelf shifted from large to small species. Significant declines were observed in the biomass of large scyphozoans ( Chrysaora melanaster), large copepods ( Calanus marshallae), arrow worms ( Sagitta elegans) and euphausiids ( Thysanoessa raschii, T. inermis) between 1999 and 2004. In contrast, significantly higher densities of the small copepods ( Pseudocalanus spp., Oithona similis) and small hydromedusae ( Euphysa flammea) were observed in 2004 relative to 1999. Stomach analyses of young-of-the-year (age 0) pollock ( Theragra chalcogramma) from the middle shelf indicated a dietary shift from large to small copepods in 2004 relative to 1999. The shift in the zooplankton community was accompanied by a 3-fold increase in water-column stability in 2004 relative to 1999, primarily due to warmer water above the thermocline, with a mean temperature of 7.3 °C in 1999 and 12.6 °C in 2004. The elevated water-column stability and warmer conditions may have influenced the zooplankton composition by lowering summer primary production and selecting for species more tolerant of a warm, oligotrophic environment. A time series of temperature from

Distinct zooplankton regime shift patterns across ecoregions of the U.S. Northeast continental shelf Large Marine Ecosystem

NASA Astrophysics Data System (ADS)

Morse, R. E.; Friedland, K. D.; Tommasi, D.; Stock, C.; Nye, J.

2017-01-01

We investigated regime shifts in seasonal zooplankton communities of the Northeast continental shelf Large Marine Ecosystem (NES) and its subcomponent ecoregions over a multi-decadal period (1977-2013). Our cross ecoregion analysis shows that regime shifts in different ecoregions often exhibited very distinct characteristics, emphasizing more granular fluctuations in NES plankton communities relative to previous work. Shifts early in the time series generally reflected an increase in abundance levels. The response of zooplankton abundance within fall communities was more similar among ecoregions than for spring communities. The Gulf of Maine exhibited highly distinct patterns from other ecoregions, with regime shifts identified in the early 1980s, early 2000s, and mid-2000s for spring communities. Regime shifts were identified in the early to mid-1990s for the NES, Georges Bank, and the Mid-Atlantic Bight ecoregions, while the fall communities experienced shifts in the early 1990s and late 1980s for the NES and Georges Bank, but in the late 1990s in the Mid-Atlantic Bight. A constrained correspondence analysis of zooplankton community against local and basin-scale climatological indices suggests that water temperature, stratification, and the Atlantic multidecadal oscillation (AMO) were the predominant factors in driving the zooplankton community composition.

How Do Density Fronts Interact with Zooplankton Distributions to Create Baleen Whale Prey-Fields in Roseway Basin?

NASA Astrophysics Data System (ADS)

Ruckdeschel, G.; Ross, T.; Davies, K. T. A.

2016-02-01

On the Scotian Shelf in the northwest Atlantic, Roseway Basin is a feeding ground for several species of large baleen whales, including the highly endangered North Atlantic right whale. In this habitat, aggregations of zooplankton must be present at concentrations high enough for baleen whales to obtain an energetic benefit. Regions of highly concentrated zooplankton are formed within the habitat through various biophysical interactions, such as fontal accumulation and retention. In Roseway Basin, humpback and fin whales prey on accumulated euphausiids, while right and sei whales forage for deep layers of Calanoid copepods. Right whales are found most often along the southeastern basin margin in Roseway, and this is also where density fronts occur and are associated with zooplankton patches that can form and disaggregate at tidal scales. The temporal persistence and biophysical mechanisms behind the observed interactions of zooplankton and frontal features have not been assessed. To understand how density fronts impact zooplankton distributions at the scale of feeding whales, we deployed Slocum gliders equipped with conductivity-temperature-depth sensors and echosounders in a series of cross-isobath transects along the sloped southeastern margin of Roseway Basin during August to November 2015. By looking for the presence of density fronts that are also regions of elevated acoustic backscatter (primarily from copepods and euphausiids) and quantifying their persistence over time, we aim to determine how these biophysical interactions create whale prey-fields.

Effects of increased zooplankton biomass on phytoplankton and cyanotoxins: A tropical mesocosm study.

PubMed

Dos Santos Severiano, Juliana; Dos Santos Almeida-Melo, Viviane Lúcia; Bittencourt-Oliveira, Maria do Carmo; Chia, Mathias Ahii; do Nascimento Moura, Ariadne

2018-01-01

Zooplankton are important biocontrol agents for algal blooms in temperate lakes, while their potential in tropical and subtropical environments is not well understood. The aim of the present study was to evaluate the influence of increased zooplankton biomass on phytoplankton community and cyanotoxins (microcystins and saxitoxin) content of a tropical reservoir (Ipojuca reservoir, Brazil) using in situ mesocosms. Mesocosms consisted of 50L transparent polyethylene bags suspended in the reservoir for twelve days. Phytoplankton populations were exposed to treatments having 1 (control), 2, 3 and 4 times the biomass of zooplankton found in the reservoir at the beginning of the experiment. Filamentous cyanobacteria such as Planktothrix agardhii and Cylindrospermopsis raciborskii were not negatively influenced by increasing zooplankton biomass. In contrast, the treatments with 3 and 4 times zooplankton biomass negatively affected the cyanobacteria Aphanocapsa sp., Chroococcus sp., Dolichospermum sp., Merismopedia tenuissima, Microcystis aeruginosa and Pseudanabaena sp.; the diatom Cyclotella meneghiniana; and the cryptophyte Cryptomonas sp. Total microcystin concentration both increased and decreased at different times depending on zooplankton treatment, while saxitoxin level was not significantly different between the treatments and control. The results of the present study suggest that zooplankton biomass can be manipulated to control the excessive proliferation of non-filamentous bloom forming cyanobacteria (e.g. M. aeruginosa) and their associated cyanotoxins. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatio-temporal variability of the North Sea cod recruitment in relation to temperature and zooplankton.

PubMed

Nicolas, Delphine; Rochette, Sébastien; Llope, Marcos; Licandro, Priscilla

2014-01-01

The North Sea cod (Gadus morhua, L.) stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS) data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature) and/or indirect (i.e. changes in the quantity and quality of zooplankton prey) effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST) from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability.

Spatio-Temporal Variability of the North Sea Cod Recruitment in Relation to Temperature and Zooplankton

PubMed Central

Nicolas, Delphine; Rochette, Sébastien; Llope, Marcos; Licandro, Priscilla

2014-01-01

The North Sea cod (Gadus morhua, L.) stock has continuously declined over the past four decades linked with overfishing and climate change. Changes in stock structure due to overfishing have made the stock largely dependent on its recruitment success, which greatly relies on environmental conditions. Here we focus on the spatio-temporal variability of cod recruitment in an effort to detect changes during the critical early life stages. Using International Bottom Trawl Survey (IBTS) data from 1974 to 2011, a major spatio-temporal change in the distribution of cod recruits was identified in the late 1990s, characterized by a pronounced decrease in the central and southeastern North Sea stock. Other minor spatial changes were also recorded in the mid-1980s and early 1990s. We tested whether the observed changes in recruits distribution could be related with direct (i.e. temperature) and/or indirect (i.e. changes in the quantity and quality of zooplankton prey) effects of climate variability. The analyses were based on spatially-resolved time series, i.e. sea surface temperature (SST) from the Hadley Center and zooplankton records from the Continuous Plankton Recorder Survey. We showed that spring SST increase was the main driver for the most recent decrease in cod recruitment. The late 1990s were also characterized by relatively low total zooplankton biomass, particularly of energy-rich zooplankton such as the copepod Calanus finmarchicus, which have further contributed to the decline of North Sea cod recruitment. Long-term spatially-resolved observations were used to produce regional distribution models that could further be used to predict the abundance of North Sea cod recruits based on temperature and zooplankton food availability. PMID:24551103

Estimating Diversity of Florida Keys Zooplankton Using New Environmental DNA Methods

NASA Astrophysics Data System (ADS)

Djurhuus, A.; Goldsmith, D. B.; Sawaya, N. A.; Breitbart, M.

2016-02-01

Zooplankton are of great importance in marine food webs, where they serve to link the phytoplankton and bacteria with higher trophic levels. Zooplankton are a diverse group containing molluscs, crustaceans, fish larvae and many other taxa. The sheer number of species and often minor morphological distinctions between species makes it challenging and exceptionally time consuming to identify the species composition of marine zooplankton samples. As a part of the Marine Biodiversity Observation Network (MBON) project, we have developed and groundtruthed an alternative, relatively time-efficient method for zooplankton identification using environmental DNA (eDNA). Samples were collected from Molasses reef, Looe Key, and Western Sambo along the Florida Keys from five bi-monthly cruises on board the RV Walton Smith. Samples were collected for environmental DNA (eDNA) by filtering 1 L of water on to a 0.22 µm filter and zooplankton samples were collected using nets with three mesh sizes (64μm, 200μm, and 500μm) to catch different size fractions. Half of zooplankton samples were fixed in 70% ethanol and half in 10% formalin, for DNA extraction and morphological identification, respectively. Individuals representing visually abundant taxa were picked into individual wells for PCR with universal 18S rRNA gene primers and subsequent sequencing to build a reference barcode database for zooplankton species commonly found in the study region. PCR and Illumina MiSeq next generation sequencing was applied to the eDNA extracted from the 0.22 μm filters and sequences were be compared to our local custom database as well as publicly available databases to determine zooplankton community composition. Finally, composition and diversity analyses were performed to compare results obtained with the new eDNA approach to standard morphological classification of zooplankton communities. Results show that the eDNA approach can enable the determination of zooplankton diversity through

Macrozooplankton biomass in a warm-core Gulf Stream ring: Time series changes in size structure, taxonomic composition, and vertical distribution

NASA Astrophysics Data System (ADS)

Davis, Cabell S.; Wiebe, Peter H.

1985-01-01

Macrozooplankton size structure and taxonomic composition in warm-core ring 82B was examined from a time series (March, April, June) of ring center MOCNESS (1 m) samples. Size distributions of 15 major taxonomic groups were determined from length measurements digitized from silhouette photographs of the samples. Silhouette digitization allows rapid quantification of Zooplankton size structure and taxonomic composition. Length/weight regressions, determined for each taxon, were used to partition the biomass (displacement volumes) of each sample among the major taxonomic groups. Zooplankton taxonomic composition and size structure varied with depth and appeared to coincide with the hydrographic structure of the ring. In March and April, within the thermostad region of the ring, smaller herbivorous/omnivorous Zooplankton, including copepods, crustacean larvae, and euphausiids, were dominant, whereas below this region, larger carnivores, such as medusae, ctenophores, fish, and decapods, dominated. Copepods were generally dominant in most samples above 500 m. Total macrozooplankton abundance and biomass increased between March and April, primarily because of increases in herbivorous taxa, including copepods, crustacean larvae, and larvaceans. A marked increase in total macrozooplankton abundance and biomass between April and June was characterized by an equally dramatic shift from smaller herbivores (1.0-3.0 mm) in April to large herbivores (5.0-6.0 mm) and carnivores (>15 mm) in June. Species identifications made directly from the samples suggest that changes in trophic structure resulted from seeding type immigration and subsequent in situ population growth of Slope Water zooplankton species.

Seasonal cycles of zooplankton from San Francisco Bay

USGS Publications Warehouse

Ambler, Julie W.; Cloern, James E.; Hutchinson, Anne

1985-01-01

Seasonal cycles of zooplankton abundance appear to be constant among years (1978–1981) and are similar in the deep (>10 m) channels and lateral shoals (<3 m). The seasonal zooplankton community dynamics are discussed in relation to: (1) river discharge which alters salinity distribution and residence time of plankton; (2) temperature which induces production and hatching of dormant copepod eggs; (3) coastal hydrography which brings neritic copepods of different zoogeographic affinities into the bay; and (4) seasonal cycles of phytoplankton.

Predicting temporal variation in zooplankton beta diversity is challenging.

PubMed

Lopes, Vanessa Guimarães; Castelo Branco, Christina W; Kozlowsky-Suzuki, Betina; Sousa-Filho, Izidro F; Souza, Leonardo Coimbra E; Bini, Luis Mauricio

2017-01-01

Beta diversity, the spatial variation in species composition, has been related to different explanatory variables, including environmental heterogeneity, productivity and connectivity. Using a long-term time series of zooplankton data collected over 62 months in a tropical reservoir (Ribeirão das Lajes Reservoir, Rio de Janeiro State, Brazil), we tested whether beta diversity (as measured across six sites distributed along the main axis of the reservoir) was correlated with environmental heterogeneity (spatial environmental variation in a given month), chlorophyll-a concentration (a surrogate for productivity) and water level. We did not found evidence for the role of these predictors, suggesting the need to reevaluate predictions or at least to search for better surrogates of the processes that hypothetically control beta diversity variation. However, beta diversity declined over time, which is consistent with the process of biotic homogenization, a worldwide cause of concern.

High evolutionary potential of marine zooplankton

PubMed Central

Peijnenburg, Katja T C A; Goetze, Erica

2013-01-01

Abstract Open ocean zooplankton often have been viewed as slowly evolving species that have limited capacity to respond adaptively to changing ocean conditions. Hence, attention has focused on the ecological responses of zooplankton to current global change, including range shifts and changing phenology. Here, we argue that zooplankton also are well poised for evolutionary responses to global change. We present theoretical arguments that suggest plankton species may respond rapidly to selection on mildly beneficial mutations due to exceptionally large population size, and consider the circumstantial evidence that supports our inference that selection may be particularly important for these species. We also review all primary population genetic studies of open ocean zooplankton and show that genetic isolation can be achieved at the scale of gyre systems in open ocean habitats (100s to 1000s of km). Furthermore, population genetic structure often varies across planktonic taxa, and appears to be linked to the particular ecological requirements of the organism. In combination, these characteristics should facilitate adaptive evolution to distinct oceanographic habitats in the plankton. We conclude that marine zooplankton may be capable of rapid evolutionary as well as ecological responses to changing ocean conditions, and discuss the implications of this view. We further suggest two priority areas for future research to test our hypothesis of high evolutionary potential in open ocean zooplankton, which will require (1) assessing how pervasive selection is in driving population divergence and (2) rigorously quantifying the spatial and temporal scales of population differentiation in the open ocean. Recent attention has focused on the ecological responses of open ocean zooplankton to current global change, including range shifts and changing phenology. Here, we argue that marine zooplankton also are well poised for evolutionary responses to global change. PMID:24567838

UV radiation and freshwater zooplankton: damage, protection and recovery

PubMed Central

Rautio, Milla; Tartarotti, Barbara

2011-01-01

While many laboratory and field studies show that zooplankton are negatively affected when exposed to high intensities of ultraviolet radiation (UVR), most studies also indicate that zooplankton are well adapted to cope with large variations in their UVR exposure in the pelagic zone of lakes. The response mechanisms of zooplankton are diverse and efficient and may explain the success and richness of freshwater zooplankton in optically variable waters. While no single behavioural or physiological protection mechanism seems to be superior, and while several unexplained and contradictory patterns exist in zooplankton UVR ecology, recent increases in our understanding are consistent with UVR playing an important role for zooplankton. This review examines the variability in freshwater zooplankton responses to UVR, with a focus on crustacean zooplankton (Cladocera and Copepoda). We present an overview of UVR-induced damages, and the protection and recovery mechanisms freshwater zooplankton use when exposed to UVR. We review the current knowledge of UVR impact on freshwater zooplankton at species and community levels, and discuss briefly how global change over the last three decades has influenced the UVR milieu in lakes. PMID:21516254

Predicting temporal variation in zooplankton beta diversity is challenging

PubMed Central

Castelo Branco, Christina W.; Kozlowsky-Suzuki, Betina; Sousa-Filho, Izidro F.; Souza, Leonardo Coimbra e; Bini, Luis Mauricio

2017-01-01

Beta diversity, the spatial variation in species composition, has been related to different explanatory variables, including environmental heterogeneity, productivity and connectivity. Using a long-term time series of zooplankton data collected over 62 months in a tropical reservoir (Ribeirão das Lajes Reservoir, Rio de Janeiro State, Brazil), we tested whether beta diversity (as measured across six sites distributed along the main axis of the reservoir) was correlated with environmental heterogeneity (spatial environmental variation in a given month), chlorophyll-a concentration (a surrogate for productivity) and water level. We did not found evidence for the role of these predictors, suggesting the need to reevaluate predictions or at least to search for better surrogates of the processes that hypothetically control beta diversity variation. However, beta diversity declined over time, which is consistent with the process of biotic homogenization, a worldwide cause of concern. PMID:29095892

Determine Age-structure of Gelatinous Zooplankton Using Optical Coherence Tomography

NASA Astrophysics Data System (ADS)

Bi, H.; Shahrestani, S.; He, Y.

2016-02-01

Gelatinous are delicate and transparent by nature, but are conspicuous in many ecosystems when in bloom. Their proliferations are a bothersome and costly nuisance and influencing important food webs and species interactions. More importantly, gelatinous zooplankton respond to climate change rapidly and understanding their upsurge needs information on their recruitment and population dynamics which in turn require their age-structure. However, ageing gelatinous zooplankton is often restricted by the fact that they shrink under unfavorable conditions. In the present study, we examine the potential of using optical coherence tomography (OCT) to age gelatinous zooplankton. OCT is a non-invasive imaging technique that uses light waves to examine 2D or 3D structure of target objects at a resolution of 3-5 µm. We were able to successfully capture both 3D and 2D images of sea nettle muscle fibers. Preliminary results on ctenophores will be discussed. Overall, this non-destructive sampling allows us to scan and capture images of mesoglea from jellyfish cultured in the lab, using the same individual repeatedly through time, documenting its growth which will provide precise measurements to construct an age key that will be applied to gelatinous zooplankton captured in the field. Coupled with information on abundance, we can start to quantify their recruitment timing and success rate.

Indigenous species barcode database improves the identification of zooplankton

PubMed Central

Yang, Jianghua; Zhang, Wanwan; Sun, Jingying; Xie, Yuwei; Zhang, Yimin; Burton, G. Allen; Yu, Hongxia

2017-01-01

Incompleteness and inaccuracy of DNA barcode databases is considered an important hindrance to the use of metabarcoding in biodiversity analysis of zooplankton at the species-level. Species barcoding by Sanger sequencing is inefficient for organisms with small body sizes, such as zooplankton. Here mitochondrial cytochrome c oxidase I (COI) fragment barcodes from 910 freshwater zooplankton specimens (87 morphospecies) were recovered by a high-throughput sequencing platform, Ion Torrent PGM. Intraspecific divergence of most zooplanktons was < 5%, except Branchionus leydign (Rotifer, 14.3%), Trichocerca elongate (Rotifer, 11.5%), Lecane bulla (Rotifer, 15.9%), Synchaeta oblonga (Rotifer, 5.95%) and Schmackeria forbesi (Copepod, 6.5%). Metabarcoding data of 28 environmental samples from Lake Tai were annotated by both an indigenous database and NCBI Genbank database. The indigenous database improved the taxonomic assignment of metabarcoding of zooplankton. Most zooplankton (81%) with barcode sequences in the indigenous database were identified by metabarcoding monitoring. Furthermore, the frequency and distribution of zooplankton were also consistent between metabarcoding and morphology identification. Overall, the indigenous database improved the taxonomic assignment of zooplankton. PMID:28977035

Acoustic classification of zooplankton

NASA Astrophysics Data System (ADS)

Martin Traykovski, Linda V.

1998-11-01

Work on the forward problem in zooplankton bioacoustics has resulted in the identification of three categories of acoustic scatterers: elastic-shelled (e.g. pteropods), fluid-like (e.g. euphausiids), and gas-bearing (e.g. siphonophores). The relationship between backscattered energy and animal biomass has been shown to vary by a factor of ~19,000 across these categories, so that to make accurate estimates of zooplankton biomass from acoustic backscatter measurements of the ocean, the acoustic characteristics of the species of interest must be well-understood. This thesis describes the development of both feature based and model based classification techniques to invert broadband acoustic echoes from individual zooplankton for scatterer type, as well as for particular parameters such as animal orientation. The feature based Empirical Orthogonal Function Classifier (EOFC) discriminates scatterer types by identifying characteristic modes of variability in the echo spectra, exploiting only the inherent characteristic structure of the acoustic signatures. The model based Model Parameterisation Classifier (MPC) classifies based on correlation of observed echo spectra with simplified parameterisations of theoretical scattering models for the three classes. The Covariance Mean Variance Classifiers (CMVC) are a set of advanced model based techniques which exploit the full complexity of the theoretical models by searching the entire physical model parameter space without employing simplifying parameterisations. Three different CMVC algorithms were developed: the Integrated Score Classifier (ISC), the Pairwise Score Classifier (PSC) and the Bayesian Probability Classifier (BPC); these classifiers assign observations to a class based on similarities in covariance, mean, and variance, while accounting for model ambiguity and validity. These feature based and model based inversion techniques were successfully applied to several thousand echoes acquired from broadband (~350 k

Stable carbon isotopes of zooplankton lipid components as a tool to differentiate between pelagic and ice algae as a food source for zooplankton in the Arctic Ocean

NASA Astrophysics Data System (ADS)

Bendle, J. A.; Moossen, H.; Jamieson, R.; Wold, A.; Falk-Peterson, S.

2009-12-01

Every summer in the Arctic, the ice cover melts and releases sea-ice algae into the surrounding waters. How important are these algae, consisting mostly of diatoms, as a major food source for zooplankton and higher trophic levels? The answer to this question is timely, given predictions for the loss of summer sea ice cover this century. We are investigating the use of compound specific carbon isotopes as a tool to differentiate between lipids found in zooplankton which feed on diatoms living in the open ocean and zooplankton which feed on diatoms derived from the ice. To this effect we analyse the carbon isotopic signature of the major fatty acids and alcohols and that of the major sterols collected during the Arctic ICE CHASER expedition aboard the RRV James Clark Ross in 2008. Twenty three zooplankton samples comprised of 11 different species were collected in four different depth intervals at three different sites around Svalbard. The sites had variable ice cover, from open water to solid ice. We analysed the lipid composition of the zooplankton samples with special emphasis on the fatty acids and fatty alcohols bound as esters. Esters are produced by zooplankton to function as an energy reservoir. Initial results such as the occurrence of Brassicasterol, 24 methylencholest 5 en-3β-ol and Desmosterol, high amounts of the C20:5ω3 fatty acid and high C16:1ω7/C16:0-fatty acid ratios suggest that diatoms are an important part of the zooplankton diet.

Zooplankton and the Ocean Carbon Cycle.

PubMed

Steinberg, Deborah K; Landry, Michael R

2017-01-03

Marine zooplankton comprise a phylogenetically and functionally diverse assemblage of protistan and metazoan consumers that occupy multiple trophic levels in pelagic food webs. Within this complex network, carbon flows via alternative zooplankton pathways drive temporal and spatial variability in production-grazing coupling, nutrient cycling, export, and transfer efficiency to higher trophic levels. We explore current knowledge of the processing of zooplankton food ingestion by absorption, egestion, respiration, excretion, and growth (production) processes. On a global scale, carbon fluxes are reasonably constrained by the grazing impact of microzooplankton and the respiratory requirements of mesozooplankton but are sensitive to uncertainties in trophic structure. The relative importance, combined magnitude, and efficiency of export mechanisms (mucous feeding webs, fecal pellets, molts, carcasses, and vertical migrations) likewise reflect regional variability in community structure. Climate change is expected to broadly alter carbon cycling by zooplankton and to have direct impacts on key species.

Feeding and production of zooplankton in the Catalan Sea (NW Mediterranean)

NASA Astrophysics Data System (ADS)

Saiz, Enric; Calbet, Albert; Atienza, Dacha; Alcaraz, Miquel

2007-08-01

Zooplankton are key components of the structure and functioning of marine planktonic food webs. They are the main link of planktonic primary production towards top pelagic consumer levels (fish), and play a relevant role on the nutrient recycling in the water column and on the export of particulate matter out of the photic zone. In this paper, we review the present knowledge on the feeding and production of zooplankton in the Catalan Sea (NW Mediterranean), with special emphasis on copepods. Feeding of zooplankton in the Catalan Sea appears typically food limited, with average daily rations on a yearly basis in the order of 48% body C d -1. Heterotrophic prey constitute a relevant fraction of their diet, as an alternative to the scarce phytoplankton in the area. From a structural point of view, the trophic impact and control of their prey populations are low on standing stocks but, at certain times, zooplankton can exert a meaningful effect on their prey production. Regarding zooplankton production, the available estimates of growth rates in the area are based on the egg production rate of copepods. Egg production rates appear to be limited, especially in summer. Tentative estimates of copepod production in the area are in the order of 20-40 mg C m -2 d -1. In conclusion, this review confirms that the oligotrophic character of the NW Mediterranean constrains the feeding activity and production of zooplankton.

Bridging the gap between marine biogeochemical and fisheries sciences; configuring the zooplankton link

NASA Astrophysics Data System (ADS)

Mitra, Aditee; Castellani, Claudia; Gentleman, Wendy C.; Jónasdóttir, Sigrún H.; Flynn, Kevin J.; Bode, Antonio; Halsband, Claudia; Kuhn, Penelope; Licandro, Priscilla; Agersted, Mette D.; Calbet, Albert; Lindeque, Penelope K.; Koppelmann, Rolf; Møller, Eva F.; Gislason, Astthor; Nielsen, Torkel Gissel; St. John, Michael

2014-12-01

Exploring climate and anthropogenic impacts on marine ecosystems requires an understanding of how trophic components interact. However, integrative end-to-end ecosystem studies (experimental and/or modelling) are rare. Experimental investigations often concentrate on a particular group or individual species within a trophic level, while tropho-dynamic field studies typically employ either a bottom-up approach concentrating on the phytoplankton community or a top-down approach concentrating on the fish community. Likewise the emphasis within modelling studies is usually placed upon phytoplankton-dominated biogeochemistry or on aspects of fisheries regulation. In consequence the roles of zooplankton communities (protists and metazoans) linking phytoplankton and fish communities are typically under-represented if not (especially in fisheries models) ignored. Where represented in ecosystem models, zooplankton are usually incorporated in an extremely simplistic fashion, using empirical descriptions merging various interacting physiological functions governing zooplankton growth and development, and thence ignoring physiological feedback mechanisms. Here we demonstrate, within a modelled plankton food-web system, how trophic dynamics are sensitive to small changes in parameter values describing zooplankton vital rates and thus the importance of using appropriate zooplankton descriptors. Through a comprehensive review, we reveal the mismatch between empirical understanding and modelling activities identifying important issues that warrant further experimental and modelling investigation. These include: food selectivity, kinetics of prey consumption and interactions with assimilation and growth, form of voided material, mortality rates at different age-stages relative to prior nutrient history. In particular there is a need for dynamic data series in which predator and prey of known nutrient history are studied interacting under varied pH and temperature regimes.

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

PubMed

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.

Acoustic Scattering Models of Zooplankton and Microstructure

DTIC Science & Technology

1997-09-30

shelled (gastropods), and gas-bearing ( siphonophores )). 5) LABORATORY EXPERIMENTATION: ZOOPLANKTON. An extensive set of laboratory measurements on the...zooplankton ( siphonophores and pteropods) that have high enough target strengths and occur in sufficiently high numbers that they could interfere with

Microscale nutrient patches produced by zooplankton

PubMed Central

Lehman, John T.; Scavia, Donald

1982-01-01

Both track autoradiography and grain-density autoradiography show that individual zooplankton create miniature patches of dissolved nutrients and that algae exploit those regions to absorb phosphate. The patches are short lived and can be dispersed artificially by small-scale turbulence. Our data support a simple model of encounters between algae and nutrient plumes produced by swimming zooplankton. PMID:16593218

Characterization of Lake Michigan coastal lakes using zooplankton assemblages

USGS Publications Warehouse

Whitman, Richard L.; Nevers, Meredith B.; Goodrich, Maria L.; Murphy, Paul C.; Davis, Bruce M.

2004-01-01

Zooplankton assemblages and water quality were examined bi-weekly from 17 April to 19 October 1998 in 11 northeastern Lake Michigan coastal lakes of similar origin but varied in trophic status and limnological condition. All lakes were within or adjacent to Sleeping Bear Dunes National Lakeshore, Michigan. Zooplankton (principally microcrustaceans and rotifers) from triplicate Wisconsin net (80 I?m) vertical tows taken at each lake's deepest location were analyzed. Oxygen-temperature-pH-specific conductivity profiles and surface water quality were concurrently measured. Bray-Curtis similarity analysis showed small variations among sample replicates but large temporal differences. The potential use of zooplankton communities for environmental lake comparisons was evaluated by means of BIOENV (Primer 5.1) and principal component analyses. Zooplankton analyzed at the lowest identified taxonomic level yielded greatest sensitivity to limnological variation. Taxonomic and ecological aggregations of zooplankton data performed comparably, but less well than the finest taxonomic analysis. Secchi depth, chlorophyll a, and sulfate concentrations combined to give the best correlation with patterns of variation in the zooplankton data set. Principal component analysis of these variables revealed trophic status as the most influential major limnological gradient among the study lakes. Overall, zooplankton abundance was an excellent indicator of variation in trophic status.

Changes in zooplankton community, and seston and zooplankton fatty acid profiles at the freshwater/saltwater interface of the Chowan River, North Carolina

PubMed Central

Rinchard, Jacques; Kimmel, David G.

2017-01-01

The variability in zooplankton fatty acid composition may be an indicator of larval fish habitat quality as fatty acids are linked to fish larval growth and survival. We sampled an anadromous fish nursery, the Chowan River, during spring of 2013 in order to determine how the seston fatty acid composition varied in comparison with the zooplankton community composition and fatty acid composition during the period of anadromous larval fish residency. The seston fatty acid profiles showed no distinct pattern in relation to sampling time or location. The mesozooplankton community composition varied spatially and the fatty acid profiles were typical of freshwater species in April. The Chowan River experienced a saltwater intrusion event during May, which resulted in brackish water species dominating the zooplankton community and the fatty acid profile showed an increase in polyunsaturated fatty acids (PUFA), in particular eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). The saltwater intrusion event was followed by an influx of freshwater due to high precipitation levels in June. The zooplankton community composition once again became dominated by freshwater species and the fatty acid profiles shifted to reflect this change; however, EPA levels remained high, particularly in the lower river. We found correlations between the seston, microzooplankton and mesozooplankton fatty acid compositions. Salinity was the main factor correlated to the observed pattern in species composition, and fatty acid changes in the mesozooplankton. These data suggest that anadromous fish nursery habitat likely experiences considerable spatial variability in fatty acid profiles of zooplankton prey and that are correlated to seston community composition and hydrodynamic changes. Our results also suggest that sufficient prey density as well as a diverse fatty acid composition is present in the Chowan River to support larval fish production. PMID:28828262

Acoustic Scattering Models of Zooplankton and Microstructures

DTIC Science & Technology

1998-09-30

scattering by the seafloor. SCATTERING BY GAS-BEARING ZOOPLANKTON. In earlier work we showed that the scattering by gas-bearing zooplankton ( siphonophores ... siphonophores and pteropods) that have high enough target strengths and occur in sufficiently high numbers that they could interfere with the performance of

GPS Position Time Series @ JPL

NASA Technical Reports Server (NTRS)

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

Effects of Climate on the Zooplankton of the California Current

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.

Stable Isotope and Signature Fatty Acid Analyses Suggest Reef Manta Rays Feed on Demersal Zooplankton

PubMed Central

Couturier, Lydie I. E.; Rohner, Christoph A.; Richardson, Anthony J.; Marshall, Andrea D.; Jaine, Fabrice R. A.; Bennett, Michael B.; Townsend, Kathy A.; Weeks, Scarla J.; Nichols, Peter D.

2013-01-01

Assessing the trophic role and interaction of an animal is key to understanding its general ecology and dynamics. Conventional techniques used to elucidate diet, such as stomach content analysis, are not suitable for large threatened marine species. Non-lethal sampling combined with biochemical methods provides a practical alternative for investigating the feeding ecology of these species. Stable isotope and signature fatty acid analyses of muscle tissue were used for the first time to examine assimilated diet of the reef manta ray Manta alfredi, and were compared with different zooplankton functional groups (i.e. near-surface zooplankton collected during manta ray feeding events and non-feeding periods, epipelagic zooplankton, demersal zooplankton and several different zooplankton taxa). Stable isotope δ15N values confirmed that the reef manta ray is a secondary consumer. This species had relatively high levels of docosahexaenoic acid (DHA) indicating a flagellate-based food source in the diet, which likely reflects feeding on DHA-rich near-surface and epipelagic zooplankton. However, high levels of ω6 polyunsaturated fatty acids and slightly enriched δ13C values in reef manta ray tissue suggest that they do not feed solely on pelagic zooplankton, but rather obtain part of their diet from another origin. The closest match was with demersal zooplankton, suggesting it is an important component of the reef manta ray diet. The ability to feed on demersal zooplankton is likely linked to the horizontal and vertical movement patterns of this giant planktivore. These new insights into the habitat use and feeding ecology of the reef manta ray will assist in the effective evaluation of its conservation needs. PMID:24167562

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

PubMed

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.

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

PubMed Central

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

2013-01-01

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. PMID:23554344

ZOOPLANKTON SIZE-SPECTRA IN GREAT LAKES COASTAL WATERS

EPA Science Inventory

Zooplankton mean size and size-distribution are affected by planktivore pressure and potentially reflect the condition of trophic interactions and ecosystem health. We used an optical plankton counter (OPC) to survey and assess zooplankton size-spectra for twenty locations in Lak...

Water quality and zooplankton in tanks with larvae of Brycon Orbignyanus (Valenciennes, 1949).

PubMed

Sipaúba-Tavares, L H; Alvarez, E J da S; Braga, F M de S

2008-02-01

Due to the importance of water variables conditions and available food in the development and survival of fish larvae, the current research evaluates the effects of two different food treatments (ration + zooplankton and only zooplankton) and water quality in tanks with Brycon orbignyanus larvae. Total water transparency (45 cm) has been mainly associated with short residence time, continuous water flow and shallowness. Dissolved oxygen ranged between 1.32 and 7.00 mg.L(-1) in tanks with ration + zooplankton and between 1.82 and 7.60 mg.L(-1) in tanks with only zooplankton treatments. Nutrients were directly affected by the addition of ration in water, with the exception of nitrite. Ten Rotifera species were found represented by high densities, ranging between 8.7 x 10(5) and 1.3 x 10(6) org.m(-3), throughout the experimental period (January to March/1996). Cladocera had the lowest density in the four tanks under analysis and ranged between 4.7 x 10(4) and 2.1 x 10(5) org.m(-3) for the six species. Diaphanosoma birgei has been classified as the most frequent species. Since ration + zooplankton produced better larvae yield, this treatment is recommended for Brycon orbignyanus larvae.

Zooplankton fecal pellets, marine snow, phytodetritus and the ocean's biological pump

NASA Astrophysics Data System (ADS)

Turner, Jefferson T.

2015-01-01

The 'biological pump' is the process by which photosynthetically-produced organic matter in the ocean descends from the surface layer to depth by a combination of sinking particles, advection or vertical mixing of dissolved organic matter, and transport by animals. Particulate organic matter that is exported downward from the euphotic zone is composed of combinations of fecal pellets from zooplankton and fish, organic aggregates known as 'marine snow' and phytodetritus from sinking phytoplankton. Previous reviews by Turner and Ferrante (1979) and Turner (2002) focused on publications that appeared through late 2001. Since that time, studies of the biological pump have continued, and there have been >300 papers on vertical export flux using sediment traps, large-volume filtration systems and other techniques from throughout the global ocean. This review will focus primarily on recent studies that have appeared since 2001. Major topics covered in this review are (1) an overview of the biological pump, and its efficiency and variability, and the role of dissolved organic carbon in the biological pump; (2) zooplankton fecal pellets, including the contribution of zooplankton fecal pellets to export flux, epipelagic retention of zooplankton fecal pellets due to zooplankton activities, zooplankton vertical migration and fecal pellet repackaging, microbial ecology of fecal pellets, sinking velocities of fecal pellets and aggregates, ballasting of sinking particles by mineral contents, phytoplankton cysts, intact cells and harmful algae toxins in fecal pellets, importance of fecal pellets from various types of zooplankton, and the role of zooplankton fecal pellets in picoplankton export; (3) marine snow, including the origins, abundance, and distributions of marine snow, particles and organisms associated with marine snow, consumption and fragmentation of marine snow by animals, pathogens associated with marine snow; (4) phytodetritus, including pulsed export of

Zooplankton size selection relative to gill raker spacing in rainbow trout

USGS Publications Warehouse

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.

PubMed

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.

Changes in seasonal nearshore zooplankton abundance patterns in Lake Ontario following establishment of the exotic predator Cercopagis pengoi

USGS Publications Warehouse

Warner, David M.; Rudstam, Lars G.; Benoit, Hugues; Mills, Edward L.; Johannsson, Ora E.

2006-01-01

Cercopagis pengoi, a zooplanktivore first discovered in Lake Ontario in 1998, may reduce availability of prey for planktivorous fish. Cercoapgis pengoi is most abundant in late summer and fall. Therefore, we hypothesized that abundance of small zooplankton (bosminids and cyclopoids) species would decrease at that time. To determine if the establishment of C. pengoi was followed by changes in the zooplankton community, seasonal patterns in nearshore zooplankton collected from May to October 1995–2000 were examined. Early summer density of small zooplankton was similar in all years while late summer and fall densities were significantly lower in 1998–2000 than in 1995–1997. The declines of small zooplankton coincided seasonally with the peak in C. pengoidensity. Other possible causes for the observed changes in small zooplankton are less likely. High levels of fish predation should have resulted in smaller zooplankton in 1998–2000 than in 1995–1997 and larger declines in Daphnia than other groups. This was not observed. There was no significant decline in chlorophyll-a concentrations or changes in temperature between 1995–1997 and 1998–2000. Therefore, the declines in density of small zooplankton were most likely the result of C. pengoi predation. The effect of C. pengoi establishment on alewives is increased competition for zooplankton prey but C. pengoi has replaced a portion of the zooplankton biomass and adult alewife diet formerly dominated by Diacyclops thomasi and Bosmina longirostris.

Zooplankton intermittency and turbulence

NASA Astrophysics Data System (ADS)

Schmitt, François G.

2010-05-01

Planktonic organisms usually live in a turbulent world. Since marine turbulence is characterized by very high Reynolds numbers, it possesses very intermittent fluctuations which in turn affect marine life. We consider here such influence on zooplankton on 2 aspects. First we consider zooplankton motion in the lab. Many copepods display swimming abilities. More and more species have been recently recorded using normal or high speed cameras, and many trajectories have been extracted from these movies and are now available for analysis. These trajectories can be complex, stochastic, with random switching from low velocity to high velocity events and even jumps. These complex trajectories show that an adequate modeling is necessary to understand and characterize them. Here we review the results published in the literature on copepod trajectories. We discuss the random walk, Levy walk modeling and introduce also multifractal random walks. We discuss the way to discriminate between these different walks using experimental data. Stochastic simulations will be performed to illustrate the different families. Second, we consider zooplankton contact rates in the framework of intermittent turbulence. Intermittency may have influence on plankton contact rates. We consider the Particle Stokes number of copepods, in a intermediate dissipation range affected by intermittent fluctuations. We show that they may display preferential concentration effects, and we consider the influence on contact rates of this effect in the intermediate dissipation range.

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

NASA Astrophysics Data System (ADS)

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

Climate-mediated changes in zooplankton community structure for the eastern Bering Sea

NASA Astrophysics Data System (ADS)

Eisner, Lisa B.; Napp, Jeffrey M.; Mier, Kathryn L.; Pinchuk, Alexei I.; Andrews, Alexander G.

2014-11-01

Zooplankton are critical to energy transfer between higher and lower trophic levels in the eastern Bering Sea ecosystem. Previous studies from the southeastern Bering Sea shelf documented substantial differences in zooplankton taxa in the Middle and Inner Shelf Domains between warm and cold years. Our investigation expands this analysis into the northern Bering Sea and the south Outer Domain, looking at zooplankton community structure during a period of climate-mediated, large-scale change. Elevated air temperatures in the early 2000s resulted in regional warming and low sea-ice extent in the southern shelf whereas the late 2000s were characterized by cold winters, extensive spring sea ice, and a well-developed pool of cold water over the entire Middle Domain. The abundance of large zooplankton taxa such as Calanus spp. (C. marshallae and C. glacialis), and Parasagitta elegans, increased from warm to cold periods, while the abundance of gelatinous zooplankton (Cnidaria) and small taxa decreased. Biomass followed the same trends as abundance, except that the biomass of small taxa in the southeastern Bering Sea remained constant due to changes in abundance of small copepod taxa (increases in Acartia spp. and Pseudocalanus spp. and decreases in Oithona spp.). Statistically significant changes in zooplankton community structure and individual species were greatest in the Middle Domain, but were evident in all shelf domains, and in both the northern and southern portions of the eastern shelf. Changes in community structure did not occur abruptly during the transition from warm to cold, but seemed to begin gradually and build as the influence of the sea ice and cold water temperatures persisted. The change occurred one year earlier in the northern than the southern Middle Shelf. These and previous observations demonstrate that lower trophic levels within the eastern Bering Sea respond to climate-mediated changes on a variety of time scales, including those shorter than

Regenerating time series from ordinal networks.

PubMed

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

Regenerating time series from ordinal networks

NASA Astrophysics Data System (ADS)

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

From Networks to Time Series

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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

Biotic and abiotic factors influencing zooplankton vertical distribution in Lake Huron

USGS Publications Warehouse

Nowicki, Carly J.; Bunnell, David B.; Armenio, Patricia M.; Warner, David M.; Vanderploeg, Henry A.; Cavaletto, Joann F.; Mayer, Christine M.; Adams, Jean V.

2017-01-01

The vertical distribution of zooplankton can have substantial influence on trophic structure in freshwater systems, particularly by determining spatial overlap for predator/prey dynamics and influencing energy transfer. The zooplankton community in some of the Laurentian Great Lakes has undergone changes in composition and declines in total biomass, especially after 2003. Mechanisms underlying these zooplankton changes remain poorly understood, in part, because few studies have described their vertical distributions during daytime and nighttime conditions or evaluated the extent to which predation, resources, or environmental conditions could explain their distribution patterns. Within multiple 24-h periods during July through October 2012 in Lake Huron, we conducted daytime and nighttime sampling of zooplankton, and measured food (chlorophyll-a), temperature, light (Secchi disk depth), and planktivory (biomass of Bythotrephes longimanus and Mysis diluviana). We used linear mixed models to determine whether the densities for 22 zooplankton taxa varied between day and night in the epi-, meta-, and hypolimnion. For eight taxa, higher epilimnetic densities were observed at night than during the day; general linear models revealed these patterns were best explained by Mysis diluviana (four taxa), Secchi disk depth (three taxa), epilimnetic water temperature (three taxa), chlorophyll (one taxon), and biomass of Bythotrephes longimanus (one taxon). By investigating the potential effects of both biotic and abiotic variables on the vertical distribution of crustacean zooplankton and rotifers, we provide descriptions of the Lake Huron zooplankton community and discuss how future changes in food web dynamics or climate change may alter zooplankton distribution in freshwater environments.

Duality between Time Series and Networks

PubMed Central

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

Reduced growth and survival of larval razorback sucker fed selenium-laden zooplankton

USGS Publications Warehouse

Hamilton, Steven J.; Buhl, Kevin J.; Bullard, Fern A.; McDonald, Susan

2005-01-01

Four groups of larval razorback sucker, an endangered fish, were exposed to selenium-laden zooplankton and survival, growth, and whole-body residues were measured. Studies were conducted with 5, 10, 24, and 28-day-old larvae fed zooplankton collected from six sites adjacent to the Green River, Utah. Water where zooplankton were collected had selenium concentrations ranging from <0.4 to 78 μg/L, and concentrations in zooplankton ranged from 2.3 to 91 μg/g dry weight. Static renewal tests were conducted for 20 to 25 days using reference water with selenium concentrations of <1.1 μg/L. In all studies, 80–100% mortality occurred in 15–20 days. In the 28-day-old larvae, fish weight was significantly reduced 25% in larvae fed zooplankton containing 12 μg/g selenium. Whole-body concentrations of selenium ranged from 3.7 to 14.3 μg/g in fish fed zooplankton from the reference site (Sheppard Bottom pond 1) up to 94 μg/g in fish fed zooplankton from North Roadside Pond. Limited information prior to the studies suggested that the Sheppard pond 1 site was relatively clean and suitable as a reference treatment; however, the nearly complete mortality of larvae and elevated concentrations of selenium in larvae and selenium and other elements in zooplankton indicated that this site was contaminated with selenium and other elements. Selenium concentrations in whole-body larvae and in zooplankton from all sites were close to or greater than toxic thresholds where adverse effects occur in fish. Delayed mortality occurred in larvae fed the two highest selenium concentrations in zooplankton and was thought due to an interaction with other elements.

Changes in fatty acid and hydrocarbon composition of zooplankton assemblages related to environmental conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lambert, R.M.

1989-01-01

Changes in zooplankton fatty acid and hydrocarbon patterns are described in relation to changes in environmental conditions and species composition. The regulation of zooplankton abundance by sea nettle-ctenophore interaction was examined in a small Rhode Island coastal pond. Sea nettles were nettles were able to eliminate ctenophores from the pond and subsequently zooplankton abundance increased. During one increase in zooplankton abundance, it was found that polyunsaturated fatty acids decreased while monounsaturated fatty acids increased. It was concluded that this shift in biochemical pattern was due to food limitation. In addition, zooplankton fatty acids were used in multivariate discriminant analysis tomore » classify whether zooplankton were from coastal or estuarine environments. Zooplankton from coastal environments were characterized by higher monounsaturate fatty acids. Zooplankton hydrocarbon composition was affected by species composition and by pollution inputs. The presence of Calanus finmarchicus was detected by increased levels of pristane.« less

Phytoplankton food quality determines time windows for successful zooplankton reproductive pulses.

PubMed

Vargas, Cristian A; Escribano, Rubén; Poulet, Serge

2006-12-01

Recruitment success at the early life stages is a critical process for zooplankton demography. Copepods often dominate the zooplankton in marine coastal zones and are prey of the majority of fish larvae. Hypotheses interpreting variations of copepod recruitment are based on the concepts of "naupliar predation," "nutritional deficiency," and "toxic effect" of diatom diets. Contradictory laboratory and field studies have reached opposite conclusions on the effects of diatoms on copepod reproductive success, blurring our view of marine food-web energy flow from diatoms to higher consumers by means of copepods. Here we report estimates of copepod feeding selectivity and reproduction in response to seasonally changing phytoplankton characteristics measured in a highly productive coastal upwelling area off the coast of central Chile. The variable phytoplankton diversity and changing food quality had a strong and highly significant impact on the feeding selectivity, reproduction, and larval survival of three indigenous copepod species. Seasonal changes in copepod feeding behavior were related to the alternating protozoan-diatom diets, mostly based on dinoflagellates and ciliates during winter and autumn (low highly unsaturated fatty acids [HUFA]/polyunsaturated fatty acids [PUFA] availability), but switched to a diet of centric and chain-forming diatoms (high HUFA/PUFA availability) during the spring/summer upwelling period. Ingestion of diatom cells induced a positive effect on egg production. However, a negative relationship was found between egg hatching success, naupliar survival, and diatom ingestion. Depending on the phytoplankton species, diets had different effects on copepod reproduction and recruitment. In consequence, it seems that the classical marine food web model does not apply to some coastal upwelling systems.

Near-surface enrichment of zooplankton over a shallow back reef: implications for coral reef food webs

NASA Astrophysics Data System (ADS)

Alldredge, A. L.; King, J. M.

2009-12-01

Zooplankton were 3-8 times more abundant during the day near the surface than elsewhere in the water column over a 1-2.4 m deep back reef in Moorea, French Polynesia. Zooplankton were also significantly more abundant near the surface at night although gradients were most pronounced under moonlight. Zooplankton in a unidirectional current became concentrated near the surface within 2 m of departing a well-mixed trough immediately behind the reef crest, indicating that upward swimming behavior, rather than near-bottom depletion by reef planktivores, was the proximal cause of these gradients. Zooplankton were highly enriched near the surface before and after a full lunar eclipse but distributed evenly throughout the water column during the eclipse itself supporting light as a proximal cue for the upward swimming behavior of many taxa. This is the first investigation of the vertical distribution of zooplankton over a shallow back reef typical of island barrier reef systems common around the world. Previous studies on deeper fringing reefs found zooplankton depletion near the bottom but no enrichment aloft. In Moorea, where seawater is continuously recirculated out the lagoon and back across the reef crest onto the back reef, selection for upward swimming behavior may be especially strong, because the surface serves both as a refuge from predation and an optimum location for retention within the reef system. Planktivorous fish and corals that can forage or grow even marginally higher in the water column might have a substantial competitive advantage over those nearer the bottom on shallow reefs. Zooplankton abundance varied more over a few tens of centimeters vertical distance than it did between seasons or even between day and night indicating that great care must be taken to accurately assess the availability of zooplankton as food on shallow reefs.

Retention and characteristics of microplastics in natural zooplankton taxa from the East China Sea.

PubMed

Sun, Xiaoxia; Liu, Tao; Zhu, Mingliang; Liang, Junhua; Zhao, Yongfang; Zhang, Bo

2018-05-30

The ubiquitous presence and persistence of microplastics (MPs) in aquatic environments have become of particular concern in recent years. Biological interactions are among the key processes that affect the impact and fate of MPs in the oceans. Zooplankton is one of the most sensitive taxa because their prey is approximately the same size as MPs. However, the status of MPs in zooplankton within natural marine environments remains largely unknown. By focusing on zooplankton in the East China Sea, the characteristics, bioaccumulated concentration, and retention of MPs for 10 zooplankton groups were systematically studied. Three types of MPs were found in zooplankton: fibres, pellets, and fragments. The fibres (54.6%) were more common than the other two types. The average lengths of the fibres, pellets, and fragments were 295.2 ± 348.6 μm, 20.3 ± 11.0 μm, and 82.4 ± 80.5 μm, respectively. Nineteen polymers were detected in the zooplankton via the Thermo Scientific Nicolet iN10 Infrared Microscope. Polymerized oxidized organic material and polyester were dominant, accounting for 35.9% and 25.6% of the polymers, respectively. The bioaccumulated concentration of MPs in the 10 zooplankton taxa varied from 0.13 pieces/zooplankton for Copepoda to 0.35 pieces/zooplankton for Pteropoda. The bioaccumulated concentration was negatively correlated with the abundance of zooplankton, showing a significant biological dilution effect. The bioaccumulated concentration was also influenced by the feeding mode of zooplankton, showing a trend of omnivorous > carnivorous > herbivorous. High retention of MPs was found in the zooplankton community of the East China Sea, achieving 19.7 ± 22.4 pieces/m 3 . This is much higher than the MP retention in zooplankton from other reported sea areas. By revealing the characteristics and retention of MPs in the natural zooplankton taxa from the East China Sea, this research identified the influence that MPs have

Global dynamics of zooplankton and harmful algae in flowing habitats

NASA Astrophysics Data System (ADS)

Hsu, Sze-Bi; Wang, Feng-Bin; Zhao, Xiao-Qiang

This paper is devoted to the study of two advection-dispersion-reaction models arising from the dynamics of harmful algae and zooplankton in flowing-water habitats where a main channel is coupled to a hydraulic storage zone, representing an ensemble of fringing coves on the shoreline. For the system modeling the dynamics of algae and their toxin that contains little limiting nutrient, we establish a threshold type result on the global attractivity in terms of the basic reproduction ratio for algae. For the model with zooplankton that eat the algae and are inhibited by the toxin produced by algae, we show that there exists a coexistence steady state and the zooplankton is uniformly persistent provided that two basic reproduction ratios for algae and zooplankton are greater than unity.

Multiple Indicator Stationary Time Series Models.

ERIC Educational Resources Information Center

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…

Seasonal variation in the biochemical compositions of phytoplankton and zooplankton communities in the southwestern East/Japan Sea

NASA Astrophysics Data System (ADS)

Jo, Naeun; Kang, Jae Joong; Park, Won Gyu; Lee, Bo Ram; Yun, Mi Sun; Lee, Jang Han; Kim, Su Min; Lee, Dasom; Joo, HuiTae; Lee, Jae Hyung; Ahn, So Hyun; Lee, Sang Heon

2017-09-01

The macromolecular composition of phytoplankton communities and the proximate composition of zooplankton communities were measured monthly in the southwestern East/Japan Sea from April to November 2014 in order to identify seasonal changes in, and relationships among, the biochemical compositions in both phytoplankton and zooplankton. The carbohydrate content of phytoplankton was highest in June, whereas the protein content was highest in August and lipids were highest in April. Overall, carbohydrates were dominant (53.2 ± 12.5%) in the macromolecular composition of phytoplankton during the study period. This composition is believed to result from the dominance of diatoms and/or nutrient-depleted conditions. In comparison, the protein level of zooplankton was highest in November, whereas lipids were slightly higher in May than other months. Overall, proteins were the dominant organic compounds (47.9±8.6% DW) in zooplankton communities, whereas lipids were minor components (5.5±0.6% DW). The high protein content of zooplankton might be related to the abundance of copepods, whereas the low lipid content might be due to a relatively high primary production that could provide a sufficient food supply for zooplankton so that they do not require high lipid storage. A significant positive correlation (r=0.971, n=7, p<0.01) was found between the lipid compositions of phytoplankton and zooplankton during our study period with a time lag, which is consistent with the findings from previous studies. More detailed studies on the biochemical composition of phytoplankton and zooplankton are needed to better understand the East/Japan Sea ecosystem's response to the many environmental changes associated with global warming.

Zooplankton responses to sandbar opening in a tropical eutrophic coastal lagoon

NASA Astrophysics Data System (ADS)

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.

Under the Scope: Bringing Zooplankton Research into the K-12 Classroom

NASA Astrophysics Data System (ADS)

Cohen, J.; Petrone, C.; Wickline, A.

2016-02-01

Despite their small size, zooplankton are dynamic and engaging animals when viewed by researchers, teachers, and students alike. Recognizing this, we are working with K-12 teachers to develop web-based resources for using zooplankton in the classroom. This outreach effort is part of a Delaware Sea Grant-funded research project studying seasonal dynamics of zooplankton in Delaware Bay. The research team, in collaboration with a marine education specialist, initially created a website (www.underthescope.udel.edu) containing: background information on zooplankton and the research project, a magnification tool, an identification tool, and education modules that facilitate directed use of the website content and tools. Local teachers (elementary through high school) were then hosted for a workshop to engage in zooplankton sampling using methods employed in the research project, including zooplankton tows and semi-autonomous identification using a ZooScan imaging system. Teachers then explored the website, evaluating its design, content, and usability for their particular grade level. Specific suggestions from the evaluation were incorporated into the website, with additional implementation planned over the next year. This teacher- researcher partnership was successful in developing the digital resource itself, in building excitement and capacity among a cohort of teachers, and in establishing relationships among teachers and researchers to facilitate adding new dimensions to the collaboration. The latter will include zooplankton sampling by school groups, researcher optical scanning of samples with ZooScan, and subsequent student analysis and reporting on their data.

Small-scale zooplankton aggregations at the front of a Kuroshio warm-core ring

NASA Astrophysics Data System (ADS)

Yamamoto, Tamiji; Nishizawa, Satoshi

1986-11-01

A Longhurst-Hardy Plankton Recorder was used to study the small-scale zooplankton distribution across the front of a Kuroshio warm-core ring in June 1979. Zooplankton were strongly aggregated in the frontal region; patches of zooplankton and phytoplankton were spatially separated. A major part of the zooplankton assemblage consisted of neritic forms such as cladocerans and indicator species of the cold Oyashio water. This implies that lateral entrainment of coastal waters, which is directly influenced by the Oyashio, was an important factor in the formation of the aggregations at the Kuroshio warm-core ring front. Variation in the distribution of abundance peaks of individual zooplankton species was also observed. Futhermore, zooplankton showed more intensive non-randomness (aggregation) than phytoplankton and non-motile euphausiid's eggs. Thus, biological processes, such as motility and prey-predator interaction, also appeared to be regulating the patchiness.

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

NASA Astrophysics Data System (ADS)

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.

Microcystin production by Microcystis aeruginosa exposed to different stages of herbivorous zooplankton.

PubMed

Jang, Min-Ho; Ha, Kyong; Takamura, Noriko

2008-04-01

Microcystin (MC) production by four monoclonal Microcystis aeruginosa strains was evaluated in response to infochemicals (indirect exposure) released from different stages of herbivorous zooplankton (neonate/juvenile and adult Daphnia magna and Moina macrocopa). The intracellular MC and extracellular MC concentrations were significantly different among the control and treatments with zooplankton culture media filtrates (p<0.05), and in most cases MC production was significantly higher (p<0.05) in strains exposed to infochemicals released from adult zooplankton rather than those of neonate/juvenile zooplankton in four strains of M. aeruginosa. Compared to intracellular MC (385.0-5598.6microg g(-1)DW), very low concentrations of extracellular MC (9.9-737.6microg ml(-1)) were released, but both showed similar temporal patterns over the course of the experiment. This result might be attributed to the fact that adult zooplankton produced more infochemical signals than equal numbers of smaller juveniles and neonates. It is the first study to provide evidence that MC production might be impacted by infochemicals released from different stages of zooplankton, mediated with physiological characteristics, body size, and feeding habits.

Seasonal Phenology of Zooplankton Composition in the Southeastern Bering Sea, 2008-2010

NASA Astrophysics Data System (ADS)

Eisner, L. B.; Pinchuk, A. I.; Harpold, C.; Siddon, E. C.; Mier, K.

2016-02-01

The availability of large crustacean zooplankton prey is critical to the condition and survival of forage fish (e.g., age-0 Walleye Pollock), sea birds, and marine mammals in the eastern Bering Sea. Zooplankton community composition and abundances of large lipid-rich copepods (e.g., Calanus spp.) have been evaluated for single seasons, but few studies have investigated seasonal variations in this region. Here, we investigate seasonal changes in taxa (community structure), stage composition (where appropriate), and diversity from spring through late summer/early fall over three consecutive colder than average years. Zooplankton taxonomic samples were collected with oblique bongo tows over the water column during spring (April-May), mid-summer (June-July) and late summer/early fall (August-September) across the southeastern Bering Sea shelf in 2008-2010. Zooplankton abundances were evaluated by oceanographic region, season and year, and related to water mass characteristics (temperature and salinity) and other environmental drivers. Finally, zooplankton phenology was compared to changes in forage fish composition to determine potential overlap of fish predators and zooplankton prey.

Terrestrial carbon is a resource, but not a subsidy, for lake zooplankton

USGS Publications Warehouse

Kelly, Patrick T.; Solomon, Christopher T.; Weidel, Brian C.; Jones, Stuart E.

2014-01-01

Inputs of terrestrial organic carbon (t-OC) into lakes are often considered a resource subsidy for aquatic consumer production. Although there is evidence that terrestrial carbon can be incorporated into the tissues of aquatic consumers, its ability to enhance consumer production has been debated. Our research aims to evaluate the net effect of t-OC input on zooplankton. We used a survey of zooplankton production and resource use in ten lakes along a naturally occurring gradient of t-OC concentration to address these questions. Total and group-specific zooplankton production was negatively related to t-OC. Residual variation in zooplankton production that was not explained by t-OC was negatively related to terrestrial resource use (allochthony) by zooplankton. These results challenge the designation of terrestrial carbon as a resource subsidy; rather, the negative effect of reduced light penetration on the amount of suitable habitat and the low resource quality of t-OC appear to diminish zooplankton production. Our findings suggest that ongoing continental-scale increases in t-OC concentrations of lakes will likely have negative impacts on the productivity of aquatic food webs.

COMPARISONS OF ZOOPLANKTON COMMUNITY SIZE STRUCTURE IN THE GREAT LAKES

EPA Science Inventory

Zooplankton mean-size and size-spectra distribution potentially reflect the condition of trophic interactions and ecosystem health because they are affected by both resource availability and planktivore pressure. We assessed zooplankton mean-size and size-spectra using an optical...

The Impact of Fish Predation and Cyanobacteria on Zooplankton Size Structure in 96 Subtropical Lakes

PubMed Central

Zhang, Jing; Xie, Ping; Tao, Min; Guo, Longgen; Chen, Jun; Li, Li; XueZhen Zhang; Zhang, Lu

2013-01-01

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 aquaculture is widespread

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

PubMed

Zhang, Jing; Xie, Ping; Tao, Min; Guo, Longgen; Chen, Jun; Li, Li; Xuezhen Zhang; Zhang, Lu

2013-01-01

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 aquaculture is widespread

A New Trait-Based Auto-Emergent Model for Zooplankton and Confrontation with Size-Structured Observations from the Bay of Biscay

NASA Astrophysics Data System (ADS)

Vandromme, Pieter; Sourisseau, Marc; Huret, Martin

2013-04-01

Spring-time cruises in the Bay of Biscay. The usefulness of the proposed zooplankton model for large scale biogeochemical models is further discussed.

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

PubMed

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.

Development of a Multimetric Indicator of Pelagic Zooplankton ...

EPA Pesticide Factsheets

We used zooplankton data collected for the 2012 National Lakes Assessment (NLA) to develop multimetric indices (MMIs) for five aggregated ecoregions of the conterminous USA (Coastal Plains, Eastern Highlands, Plains, Upper Midwest, and Western Mountains and Xeric [“West’]). We classified candidate metrics into six categories: We evaluated the performance of candidate metrics, and used metrics that had passed these screens to calculate all possible candidate MMIs that included at least one metric from each category. We selected the candidate MMI that had high responsiveness, a reasonable value for repeatability, low mean pairwise correlation among component metrics, and, when possible, a maximum pairwise correlation among component metrics that was <0.7. We were able to develop MMIs that were sufficiently responsive and repeatable to assess ecological condition for the NLA without the need to reduce the effects of natural variation using models. We did not observe effects of either lake size, lake origin, or site depth on the MMIs. The MMIs appear to respond more strongly to increased nutrient concentrations than to shoreline habitat conditions. Improving our understanding of how zooplankton assemblages respond to increased human disturbance, and obtaining more complete autecological information for zooplankton taxa would likely improve MMIs developed for future assessments. Using zooplankton assemblage data from the 2012 National Lakes Assessment (NLA),

A new modelling approach for zooplankton behaviour

NASA Astrophysics Data System (ADS)

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

PubMed Central

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. PMID:26571115

Visibility Graph Based Time Series Analysis.

PubMed

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.

Ocean acidification reduces demersal zooplankton that reside in tropical coral reefs

NASA Astrophysics Data System (ADS)

Smith, Joy N.; de'Ath, Glenn; Richter, Claudio; Cornils, Astrid; Hall-Spencer, Jason M.; Fabricius, Katharina E.

2016-12-01

The in situ effects of ocean acidification on zooplankton communities remain largely unexplored. Using natural volcanic CO2 seep sites around tropical coral communities, we show a threefold reduction in the biomass of demersal zooplankton in high-CO2 sites compared with sites with ambient CO2. Differences were consistent across two reefs and three expeditions. Abundances were reduced in most taxonomic groups. There were no regime shifts in zooplankton community composition and no differences in fatty acid composition between CO2 levels, suggesting that ocean acidification affects the food quantity but not the quality for nocturnal plankton feeders. Emergence trap data show that the observed reduction in demersal plankton may be partly attributable to altered habitat. Ocean acidification changes coral community composition from branching to massive bouldering coral species, and our data suggest that bouldering corals represent inferior daytime shelter for demersal zooplankton. Since zooplankton represent a major source of nutrients for corals, fish and other planktivores, this ecological feedback may represent an additional mechanism of how coral reefs will be affected by ocean acidification.

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

PubMed

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.

Dead zone or oasis in the open ocean? Zooplankton distribution and migration in low-oxygen modewater eddies

NASA Astrophysics Data System (ADS)

Hauss, H.; Christiansen, S.; Schütte, F.; Kiko, R.; Edvam Lima, M.; Rodrigues, E.; Karstensen, J.; Löscher, C. R.; Körtzinger, A.; Fiedler, B.

2015-11-01

The eastern tropical North Atlantic (ETNA) features a mesopelagic oxygen minimum zone (OMZ) at approximately 300-600 m depth. Here, oxygen concentrations rarely fall below 40 μmol O2 kg-1, but are thought to decline in the course of climate change. The recent discovery of mesoscale eddies that harbour a shallow suboxic (< 5 μmol O2 kg-1) OMZ just below the mixed layer could serve to identify zooplankton groups that may be negatively or positively affected by on-going ocean deoxygenation. In spring 2014, a detailed survey of a suboxic anticyclonic modewater eddy (ACME) was carried out near the Cape Verde Ocean Observatory (CVOO), combining acoustic and optical profiling methods with stratified multinet hauls and hydrography. The multinet data revealed that the eddy was characterized by an approximately 1.5-fold increase in total area-integrated zooplankton abundance. A marked reduction in acoustic target strength (derived from shipboard ADCP, 75kHz) within the shallow OMZ at nighttime was evident. Acoustic scatterers were avoiding the depth range between about 85 to 120 m, where oxygen concentrations were lower than approximately 20 μmol O2 kg-1, indicating habitat compression to the oxygenated surface layer. This observation is confirmed by time-series observations of a moored ADCP (upward looking, 300 kHz) during an ACME transit at the CVOO mooring in 2010. Nevertheless, part of the diurnal vertical migration (DVM) from the surface layer to the mesopelagic continued through the shallow OMZ. Based upon vertically stratified multinet hauls, Underwater Vision Profiler (UVP5) and ADCP data, four strategies have been identified followed by zooplankton in response to the eddy OMZ: (i) shallow OMZ avoidance and compression at the surface (e.g. most calanoid copepods, euphausiids), (ii) migration to the shallow OMZ core during daytime, but paying O2 debt at the surface at nighttime (e.g. siphonophores, Oncaea spp., eucalanoid copepods), (iii) residing in the shallow

Selenium in San Francisco Bay zooplankton: Potential effects of hydrodynamics and food web interactions

USGS Publications Warehouse

Purkerson, D.G.; Doblin, M.A.; Bollens, S.M.; Luoma, S.N.; Cutter, G.A.

2003-01-01

The potential toxicity of elevated selenium (Se) concentrations in aquatic ecosystems has stimulated efforts to measure Se concentrations in benthos, nekton, and waterfowl in San Francisco Bay (SF Bay). In September 1998, we initiated a 14 mo field study to determine the concentration of Se in SF Bay zooplankton, which play a major role in the Bay food web, but which have not previously been studied with respect to Se. Monthly vertical plankton tows were collected at several stations throughout SF Bay, and zooplankton were separated into two operationally defined size classes for Se analyses: 73-2,000 ??m, and ???2,000 ??m. Selenium values ranged 1.02-6.07 ??g Se g-1 dry weight. No spatial differences in zooplankton Se concentrations were found. However, there were inter- and intra-annual differences. Zooplankton Se concentrations were enriched in the North Bay in Fall 1999 when compared to other seasons and locations within and outside SF Bay. The abundance and biovolume of the zooplankton community varied spatially between stations, but not seasonally within each station. Smaller herbivorous-omnivorous zooplankton had higher Se concentrations than larger omnivorous-carnivorous zooplankton. Selenium concentrations in zooplankton were negatively correlated with the proportion of total copepod biovolume comprising the large carnivorous copepod Tortanus dextrilobatus, but positively correlated with the proportion of copepod biovolume comprising smaller copepods of the family Oithonidae, suggesting an important role of trophic level and size in regulating zooplankton Se concentrations.

Community composition, abundance and biomass of zooplankton in Zhangzi Island waters, Northern Yellow Sea

NASA Astrophysics Data System (ADS)

Yin, Jiehui; Zhang, Guangtao; Li, Chaolun; Wang, Shiwei; Zhao, Zengxia; Wan, Aiyong

2017-09-01

Samples were collected monthly from the sea area around Zhangzi Island, northern Yellow Sea, from July 2009 to June 2010. Vertical net towing was used to examine spatial and temporal variability in zooplankton abundance and biomass. Overall, Calanus sinicus and Saggita crassa were the dominant species found during the study period, while the amphipod Themisto gracilipes was dominant in winter and spring. Vast numbers of the ctenophore species of the genus Beroe were found in October and November. It was not possible to count them, but they constituted a large portion of the total zooplankton biomass. Zooplankton species diversity was highest in October, and species evenness was highest in April. Zooplankton abundance (non-jellyfish) and biomass were highest in June and lowest in August, with annual averages of 131.3 ind./m³ and 217.5 mg/m³, respectively. Water temperature may be responsible for the variations in zooplankton abundance and biomass. Beroe biomass was negatively correlated with other zooplankton abundance. Longterm investigations will be carried out to learn more about the influence of the environment on zooplankton assemblages.

Volatility of linear and nonlinear time series

NASA Astrophysics Data System (ADS)

Kalisky, Tomer; Ashkenazy, Yosef; Havlin, Shlomo

2005-07-01

Previous studies indicated that nonlinear properties of Gaussian distributed time series with long-range correlations, ui , can be detected and quantified by studying the correlations in the magnitude series ∣ui∣ , the “volatility.” However, the origin for this empirical observation still remains unclear and the exact relation between the correlations in ui and the correlations in ∣ui∣ is still unknown. Here we develop analytical relations between the scaling exponent of linear series ui and its magnitude series ∣ui∣ . Moreover, we find that nonlinear time series exhibit stronger (or the same) correlations in the magnitude time series compared with linear time series with the same two-point correlations. Based on these results we propose a simple model that generates multifractal time series by explicitly inserting long range correlations in the magnitude series; the nonlinear multifractal time series is generated by multiplying a long-range correlated time series (that represents the magnitude series) with uncorrelated time series [that represents the sign series sgn(ui) ]. We apply our techniques on daily deep ocean temperature records from the equatorial Pacific, the region of the El-Ninõ phenomenon, and find: (i) long-range correlations from several days to several years with 1/f power spectrum, (ii) significant nonlinear behavior as expressed by long-range correlations of the volatility series, and (iii) broad multifractal spectrum.

Zooplankton community analysis in the Changjiang River estuary by single-gene-targeted metagenomics

NASA Astrophysics Data System (ADS)

Cheng, Fangping; Wang, Minxiao; Li, Chaolun; Sun, Song

2014-07-01

DNA barcoding provides accurate identification of zooplankton species through all life stages. Single-gene-targeted metagenomic analysis based on DNA barcode databases can facilitate longterm monitoring of zooplankton communities. With the help of the available zooplankton databases, the zooplankton community of the Changjiang (Yangtze) River estuary was studied using a single-gene-targeted metagenomic method to estimate the species richness of this community. A total of 856 mitochondrial cytochrome oxidase subunit 1 (cox1) gene sequences were determined. The environmental barcodes were clustered into 70 molecular operational taxonomic units (MOTUs). Forty-two MOTUs matched barcoded marine organisms with more than 90% similarity and were assigned to either the species (similarity>96%) or genus level (similarity<96%). Sibling species could also be distinguished. Many species that were overlooked by morphological methods were identified by molecular methods, especially gelatinous zooplankton and merozooplankton that were likely sampled at different life history phases. Zooplankton community structures differed significantly among all of the samples. The MOTU spatial distributions were influenced by the ecological habits of the corresponding species. In conclusion, single-gene-targeted metagenomic analysis is a useful tool for zooplankton studies, with which specimens from all life history stages can be identified quickly and effectively with a comprehensive database.

Potential acidification impacts on zooplankton in CCS leakage scenarios.

PubMed

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.

Factors driving the seasonal distribution of zooplankton in a eutrophicated Mediterranean Lagoon.

PubMed

Ziadi, Boutheina; Dhib, Amel; Turki, Souad; Aleya, Lotfi

2015-08-15

The distribution of the zooplankton community was studied along with environmental factors at five sampling stations in Ghar El Melh Lagoon (GML) (Mediterranean Sea, northern Tunisia). GML is characterized by specific following properties: broad and shallow, freshwater supply (Station 1); connection to the sea (S2); stagnation (S3 especially), and eutrophic conditions with enhanced nutrient concentrations (S4 and S5). Samples were taken twice monthly from February 2011 to January 2012. Twenty-three zooplankton groups comprising 10 larval stages were identified. Zooplankton assemblages were largely dominated by copepods (37.25%), followed respectively by ciliates (21.09%), bivalve larvae (14.88%) and gastropod veligers (12.53%). Redundancy analysis indicated that while no significant difference was found in the distribution of zooplankton at any station, a strong difference was observed according to season. Both temporal and physicochemical fluctuations explain more than 50% of changes in zooplankton abundances. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

EPA Science Inventory

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.

PubMed

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.

Spatial patterns in assemblage structures of pelagic forage fish and zooplankton in western Lake Superior

USGS Publications Warehouse

Johnson, Timothy B.; Hoff, Michael H.; Trebitz, Anett S.; Bronte, Charles R.; Corry, Timothy D.; Kitchell, James F.; Lozano, Stephen J.; Mason, Doran M.; Scharold, Jill V.; Schram, Stephen T.; Schreiner, Donald R.

2004-01-01

We assessed abundance, size, and species composition of forage fish and zooplankton communities of western Lake Superior during August 1996 and July 1997. Data were analyzed for three ecoregions (Duluth-Superior, Apostle Islands, and the open lake) differing in bathymetry and limnological and biological patterns. Zooplankton abundance was three times higher in the Duluth-Superior and Apostle Islands regions than in the open lake due to the large numbers of rotifers. Copepods were far more abundant than Cladocera in all ecoregions. Mean zooplankton size was larger in the open lake due to dominance by large calanoid copepods although size of individual taxa was similar among ecoregions. Forage fish abundance and biomass was highest in the Apostle Islands region and lowest in the open lake ecoregion. Lake herring (Coregonus artedi), rainbow smelt (Osmerus mordax) and deepwater ciscoes (Coregonus spp.) comprised over 90% of the abundance and biomass of fishes caught in midwater trawls and recorded with hydroacoustics. Growth and condition of fish was good, suggesting they were not resource limited. Fish and zooplankton assemblages differed among the three ecoregions of western Lake Superior, due to a combination of physical and limnological factors related to bathymetry and landscape position.

Bioenergetics modeling of the annual consumption of zooplankton by pelagic fish feeding in the Northeast Atlantic

PubMed Central

Utne, Kjell Rong; Jansen, Teunis; Huse, Geir

2018-01-01

The present study uses bioenergetics modeling to estimate the annual consumption of the main zooplankton groups by some of the most commercially important planktivorous fish stocks in the Northeast Atlantic, namely Norwegian spring-spawning (NSS) herring (Clupea harengus), blue whiting (Micromesistius poutassou) and NEA mackerel (Scomber scombrus). The data was obtained from scientific surveys in the main feeding area (Norwegian Sea) in the period 2005–2010. By incorporating novel information about ambient temperature, seasonal growth and changes in the diet from stomach content analyses, annual consumption of the different zooplankton groups by pelagic fish is estimated. The present study estimates higher consumption estimates than previous studies for the three species and suggests that fish might have a greater impact on the zooplankton community as foragers. This way, NEA mackerel, showing the highest daily consumption rates, and NSS herring, annually consume around 10 times their total biomass, whereas blue whiting consume about 6 times their biomass in zooplankton. The three species were estimated to consume an average of 135 million (M) tonnes of zooplankton each year, consisting of 53–85 M tonnes of copepods, 20–32 M tonnes of krill, 8–42 M tonnes of appendicularians and 0.2–1.2 M tonnes of fish, depending on the year. For NSS herring and NEA mackerel the main prey groups are calanoids and appendicularians, showing a peak in consumption during June and June–July, respectively, and suggesting high potential for inter-specific feeding competition between these species. In contrast, blue whiting maintain a low consumption rate from April to September, consuming mainly larger euphausiids. Our results suggest that the three species can coexist regardless of their high abundance, zooplankton consumption rates and overlapping diet. Accordingly, the species might have niche segregation, as they are species specific, showing annual and inter

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

PCR-Based Assessment of Freshwater Zooplankton Feeding on Edible and "Inedible" Prey In Situ.

NASA Astrophysics Data System (ADS)

Nejstgaard, J. C.; Belyaeva, M.; Van den Wyngaert, S.; Berger, S. A.; Grossart, H. P.; Kasprzak, P.

2016-02-01

Microbiota in pelagic ecosystems can affect zooplankton nutrition in several ways that are not readily assessable in situ, using classical approaches. In contrast to classical food web models identifying phytoplankton as the dominant food source for crustacean zooplankton, recent findings increasingly suggest that zooplankton may derive a significant part of the diet from a wide variety of taxa including ciliates, aquatic fungi, bacteria and small metazoan zooplankton (e.g. rotifers), in both marine and freshwaters. Direct quantification of soft-bodied and non-pigmented prey in zooplankton guts as well as symbionts and parasites on the prey and zooplankton itself has so far been impeded by the lack of appropriate methodology. We aim to establish molecular approaches to quantify these yet-understudied interactions in lake food webs. As a first step we have validated the qPCR detection method in laboratory experiments with cladoceran, calanoid and cyclopoid predators and algal prey species (Cryptomonas sp.). We plan to apply the method to study the dietary contribution of aquatic fungi - chytrids, which are parasites on inedible phytoplankton species, thus aiming to provide insights into the Mycoloop - energy transfer from inedible phytoplankton to zooplankton via fungal parasites. The quantitative PCR method, when validated for key zooplankton species and specific prey or parasite groups, has a potential for a broad range of applications in food web research.

Diel variations of the bathymetric distribution of zooplankton groups and biomass in Cap-Ferret Canyon, France

NASA Astrophysics Data System (ADS)

Maycas, Encarna Ribera; Bourdillon, André; Macquart-Moulin, Claude; Passelaigue, Françoise; Patriti, Gilbert

1999-10-01

The bathymetric distribution, abundance and diel vertical migrations (DVM) of zooplankton were investigated along the axis of the Cap-Ferret Canyon (Bay of Biscay, French Atlantic coast) by a consecutive series of synchronous net hauls that sampled the whole water column (0-2000 m in depth) during a diel cycle. The distribution of appendicularians (maximum 189 individuals m -3), cladocerans (maximum 287 individuals m -3), copepods (copepods<4 mm, maximum 773 individuals m -3, copepods>4 mm, maximum 13 individuals m -3), ostracods (maximum 8 individuals m -3), siphonophores (maximum >2 individuals m -3) and peracarids (maximum >600 individuals 1000 m -3) were analysed and represented by isoline diagrams. The biomass of total zooplankton (maximum 18419 μg C m -3, 3780 μg N m -3) and large copepods (>4 mm maximum 2256 μg C m -3, 425 μg N m -3) also were determined. Vertical migration was absent or affected only the epipelagic zone for appendicularians, cladocerans, small copepods and siphonophores. Average amplitude of vertical migration was about 400-500 m for ostracods, some hyperiids and mysids, and large copepods, which were often present in the epipelagic, mesopelagic, and bathypelagic zones. Large copepods can constitute more than 80% of the biomass corresponding to total zooplankton. They may play an important role in the active vertical transfer of carbon and nitrogen.

A Review of Subsequence Time Series Clustering

PubMed Central

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

A review of subsequence time series clustering.

PubMed

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.

Smoothing of climate time series revisited

NASA Astrophysics Data System (ADS)

Mann, Michael E.

2008-08-01

We present an easily implemented method for smoothing climate time series, generalizing upon an approach previously described by Mann (2004). The method adaptively weights the three lowest order time series boundary constraints to optimize the fit with the raw time series. We apply the method to the instrumental global mean temperature series from 1850-2007 and to various surrogate global mean temperature series from 1850-2100 derived from the CMIP3 multimodel intercomparison project. These applications demonstrate that the adaptive method systematically out-performs certain widely used default smoothing methods, and is more likely to yield accurate assessments of long-term warming trends.

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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 with tailored nonlinearities

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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 < 1.2 mm. The 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.

Temporal Variability of Zooplankton (2000-2013) in the Levantine Sea: Significant Changes Associated to the 2005-2010 EMT-like Event?

PubMed Central

Ouba, Anthony; Abboud-Abi Saab, Marie; Stemmann, Lars

2016-01-01

In this study, we investigated, for the first time, the potential impact of environmental changes on zooplankton abundance over a fourteen year period (2000–2013) at an offshore station in the Eastern Mediterranean Sea (the Levantine basin, offshore Lebanon). Samples were collected monthly and analyzed using the semi-automated system ZooScan. Salinity, temperature and phytoplankton abundance (nano and microphytoplankton) were also measured. Results show no significant temporal trend in sea surface temperature over the years. Between 2005–2010, salinity in the upper layer (0–80 m) of the Levantine basin increased (~0.3°C). During this 5 year period, total zooplankton abundance significantly increased. These modifications were concomitant to the activation of Aegean Sea as a source of dense water formation as part of the “Eastern Mediterranean Transient-like” event. The results of the present study suggested that zooplankton benefited from enhanced phytoplankton production during the mixing years of the event. Changes in the phenology of some taxa were observed accordingly with a predominantly advanced peak of zooplankton abundance. In conclusion, long-term changes in zooplankton abundance were related to the Levantine thermohaline circulation rather than sea surface warming. Sampling must be maintained to assess the impact of long-term climate change on zooplankton communities. PMID:27459093

Clustering of financial time series

NASA Astrophysics Data System (ADS)

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.

The Scientific Legacy of the CARIACO Ocean Time-Series Program.

PubMed

Muller-Karger, Frank E; Astor, Yrene M; Benitez-Nelson, Claudia R; Buck, Kristen N; Fanning, Kent A; Lorenzoni, Laura; Montes, Enrique; Rueda-Roa, Digna T; Scranton, Mary I; Tappa, Eric; Taylor, Gordon T; Thunell, Robert C; Troccoli, Luis; Varela, Ramon

2018-06-11

TheCARIACO(Carbon Retention in a Colored Ocean) Ocean Time-Series Program station, located at 10.50°N, 64.66°W, observed biogeochemical and ecological processes in the Cariaco Basin of the southwestern Caribbean Sea from November 1995 to January 2017. The program completed 232 monthly core cruises, 40 sediment trap deployment cruises, and 40 microbiogeochemical process cruises. Upwelling along the southern Caribbean Sea occurs from approximately November to August. High biological productivity (320-628 g C m -2 y -1 ) leads to large vertical fluxes of particulate organic matter, but only approximately 9-10 g C m -2 y -1 fall to the bottom sediments (∼1-3% of primary production). A diverse community of heterotrophic and chemoautotrophic microorganisms, viruses, and protozoa thrives within the oxic-anoxic interface. A decrease in upwelling intensity from approximately 2003 to 2013 and the simultaneous overfishing of sardines in the region led to diminished phytoplankton bloom intensities, increased phytoplankton diversity, and increased zooplankton densities. The deepest waters of the Cariaco Basin exhibited long-term positive trends in temperature, salinity, hydrogen sulfide, ammonia, phosphate, methane, and silica. Earthquakes and coastal flooding also resulted in the delivery of sediment to the seafloor. The program's legacy includes climate-quality data from suboxic and anoxic habitats and lasting relationships between international researchers. Expected final online publication date for the Annual Review of Marine Science Volume 11 is January 3, 2019. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Dissolved and fecal pellet carbon and nitrogen release by zooplankton in tropical waters

NASA Astrophysics Data System (ADS)

Small, Lawrence F.; Fowler, Scott W.; Moore, Stanley A.; LaRosa, Jacques

1983-12-01

Carbon (C) and nitrogen (N) release by tropical zooplankton (mostly copepods) and micronekton (euphausiids, pelagic red crabs, and salps) was investigated near VERTEX particle traps at 18°N, 108°W (in 1981) and 15°40'N, 107°30'W (in 1982). The objective was to assess the significance of fecal pellet release relative to respiratory and dissolved excretory release of C and N and relative to primary production in the same waters. For small (< 300 μm) and large (300 to 500 μm) zooplankton, 38 to 49% more ammonium-nitrogen was excreted than C was respired, relative to body concentrations of N and C, respectively. However, for the same zooplankton, 40 to 54% less fecal N was egested than fecal C, again relative to body C and N contents. This apparent compensation yielded a relatively constant body C:N ratio, and, because of the relatively low ratio of respiratory C to excretory N, implied a protein-based metabolism. The same compensatory relationships were found for euphausiids and red crabs, except the percentages of C and N losses were lower than for the zooplankton. No such compensatory relationship was found for the salps, using respiratory—excretory data from the literature and our own observations of fecal pellet production. Either the literature data were not applicable to our salps, or the salps had a more lipid-based metabolism. Reasonably balanced C and N loss budgets were computed for the small and large zooplankton. Daily fecal pellet C egestion represented only 2 to 3% of both large and small zooplankton body C content, and daily fecal pellet N egestion was <2% of zooplankton body N. Likewise, daily fecal pellet production by small and large zooplankton together accounted for <2% of the daily primary C and N production in the top 100 m of water; that is, 'new' primary production would have had to replace losses of <2% per day to balance fecal pellet losses from large and small zooplankton, presuming all fecal pellets sank below 100 m without being

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

USGS Publications Warehouse

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

DNA Barcoding of Zooplankton in the Hampton Roads Area: A Biodiversity Assessment

NASA Astrophysics Data System (ADS)

Salcedo, A.; Rodríguez, Á. E.; Gibson, D. M.

2016-02-01

The study of zooplankton biodiversity and distribution is crucial to understand oceanic ecosystems and anticipate the effects of climate change. Previously, identification of zooplankton relied in morphological identification employed by expert taxonomists. DNA barcoding, a technique that uses the mitochondrial DNA (mtDNA) Cytochrome Oxidase 1 (CO1) gene is widely used for taxonomic identification. Thus, this molecular technique will be used to begin a detailed characterization of zooplankton diversity, abundance and community structure in the Hampton Roads Area (HRA). Stations 1 (Jones Creek) and 3 (lower Chesapeake Bay) were sampled in June 19, 2015. Stations 1, 2 (James River), and 3 were sampled in September 2015. Zooplankton samples were collected in triplicates with a 0.5m, 200 µm mesh net. Physical parameters (dissolved oxygen, salinity, temperature and, water transparency) were measured. Species identified as Opistonema oglinum (Atlantic Thread Herring) and Paracalanus parvus copepods were found at station 3; Anchoa mitchilli and Acartia tonsa copepods were found at stations 1 and 3. This study indicates that mtDNA-CO1 barcoding is suitable to identify zooplankton to the species level and helps validate DNA barcoding as a faster, more accurate taxonomic approach. The long term objective of this project is to provide a comprehensive assessment of zooplankton in the HRA and to generate a reference record for broad monitoring programs; vital for a better understanding and management of ecologically and commercially important species.

Lake Ontario zooplankton in 2003 and 2008: Community changes and vertical redistribution

USGS Publications Warehouse

Rudstam, Lars G.; Holeck, Kristen T.; Bowen, Kelly L.; Watkins, James M.; Weidel, Brian C.; Luckey, Frederick J.

2014-01-01

Lake-wide zooplankton surveys are critical for documenting and understanding food web responses to ecosystem change. Surveys in 2003 and 2008 during the binational intensive field year in Lake Ontario found that offshore epilimnetic crustacean zooplankton declined by a factor of 12 (density) and factor of 5 (biomass) in the summer with smaller declines in the fall. These declines coincided with an increase in abundance of Bythotrephes and are likely the result of direct predation by, or behavioral responses to this invasive invertebrate predator. Whole water column zooplankton density also declined from 2003 to 2008 in the summer and fall (factor of 4), but biomass only declined in the fall (factor of 2). The decline in biomass was less than the decline in density because the average size of individual zooplankton increased. This was due to changes in the zooplankton community composition from a cyclopoid/bosminid dominated community in 2003 to a calanoid dominated community in 2008. The increase in calanoid copepods was primarily due to the larger species Limnocalanus macrurus and Leptodiaptomus sicilis. These cold water species were found in and below the thermocline associated with a deep chlorophyll layer. In 2008, most of the zooplankton biomass resided in or below the thermocline during the day. Increased importance of copepods in deeper, colder water may favor Cisco and Rainbow Smelt over Alewife because these species are better adapted to cold temperatures than Alewife.

Persistence of an unusual pelagic zooplankton assemblage in a clear, mountain lake

USGS Publications Warehouse

Larson, G.L.; Hoffman, R.L.; C. David, McIntire

2002-01-01

The planktonic zooplankton assemblage in Mowich Lake, Mount Rainier National Park (MORA), was composed almost entirely of rotifers in 1966 and 1967. Adult pelagic crustacean taxa were rare. Their paucity was attributed to predation by kokanee salmon (Oncorhynchus nerka), which had been stocked in 1961. During a park-wide survey of 24 lakes in 1988, Mowich Lake was the only one that did not contain at least one planktonic crustacean species. Given the apparent persistence of the unusual pelagic zooplankton assemblage in Mowich Lake, the first objective of this study was to document the interannual variation in the taxonomic structure of the zooplankton assemblages in the lake from 1988 through 1999. A second objective was to determine if it was possible to predict the taxonomic composition of the pelagic crustacean zooplankton assemblage in Mowich Lake prior to the stocking of kokanee salmon. The Mowich Lake zooplankton assemblages in 1988-1999 were consistent with those in 1966 and 1967. Crustacean taxa were extremely rare, but they included most of the primary taxa collected from 23 MORA lakes surveyed in 1988. Nonetheless, the 1988 collections showed that the September rotifer assemblage in Mowich Lake was similar to 10 of the 24 lakes sampled. Seven of the 10 lakes were dominated by cladocerans, primarily Daphnia rosea and Holopedium gibberum. Therefore, it appeared that either one or both of these species may have numerically dominated the crustacean zooplankton assemblage in the lake prior to 1961.

Persistence of an unusual pelagic zooplankton assemblage in a clear mountain lake

USGS Publications Warehouse

Larson, Gary L.; Hoffman, Robert L.; McIntire, C.D.

2002-01-01

The planktonic zooplankton assemblage in Mowich Lake, Mount Rainier National Park (MORA), was composed almost entirely of rotifers in 1966 and 1967. Adult pelagic crustacean taxa were rare. Their paucity was attributed to predation by kokanee salmon (Oncorhynchus nerka), which had been stocked in 1961. During a park-wide survey of 24 lakes in 1988, Mowich Lake was the only one that did not contain at least one planktonic crustacean species. Given the apparent persistence of the unusual pelagic zooplankton assemblage in Mowich Lake, the first objective of this study was to document the interannual variation in the taxonomic structure of the zooplankton assemblages in the lake from 1988 through 1999. A second objective was to determine if it was possible to predict the taxonomic composition of the pelagic crustacean zooplankton assemblage in Mowich Lake prior to the stocking of kokanee salmon. The Mowich Lake zooplankton assemblages in 1988a??1999 were consistent with those in 1966 and 1967. Crustacean taxa were extremely rare, but they included most of the primary taxa collected from 23 MORA lakes surveyed in 1988. Nonetheless, the 1988 collections showed that the September rotifer assemblage in Mowich Lake was similar to 10 of the 24 lakes sampled. Seven of the 10 lakes were dominated by cladocerans, primarily Daphnia rosea and Holopedium gibberum. Therefore, it appeared that either one or both of these species may have numerically dominated the crustacean zooplankton assemblage in the lake prior to 1961.

Time averaging, ageing and delay analysis of financial time series

NASA Astrophysics Data System (ADS)

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.

Overheated and Out of Breath: Temperature Regulation of Respiration and Oxygen Supply in Coastal Zooplankton

NASA Astrophysics Data System (ADS)

Roman, M.; Elliott, D. T.; Pierson, J. J.

2016-02-01

Increasing global coastal hypoxia occurs under a large range of temperature and salinity conditions. Temperature directly influences oxygen solubility in seawater as well as the oxygen demand of zooplankton, thus oxygen concentration alone is not sufficient to categorize the biological impact of hypoxia for pelagic organisms. To effectively assess the impacts of hypoxic stress on zooplankton habitat space and production, it is necessary to consider the effects of temperature on both oxygen availability and zooplankton metabolism. Our analysis and modeling evaluate available oxygen (partial pressure and concentration) in the context of ambient temperature conditions and zooplankton oxygen demand. We will present allometric models, accounting for both body size and temperature that predict temperature-dependent oxygen supply and demand in coastal zooplankton. Our goal is to develop generalized, functional relationships that describe and quantify the interactive effects of temperature and low oxygen on coastal zooplankton that can lead to improved size-structured models that serve to predict impacts of increasing coastal hypoxia on pelagic food webs.

Trophic accumulation of PSP toxins in zooplankton during Alexandrium fundyense blooms in Casco Bay, Gulf of Maine, April-June 1998. II. . Zooplankton abundance and size-fractionated community composition

NASA Astrophysics Data System (ADS)

Turner, Jefferson T.; Doucette, Gregory J.; Keafer, Bruce A.; Anderson, Donald M.

2005-09-01

During spring blooms of the toxic dinoflagellate Alexandrium fundyense in Casco Bay, Maine in 1998, we investigated vectorial intoxication of various zooplankton size fractions with PSP toxins, including zooplankton community composition from quantitative zooplankton samples (>102 μm), as well as zooplankton composition in relation to toxin levels in various size fractions (20-64, 64-100, 100-200, 200-500, >500 μm). Zooplankton abundance in 102 μm mesh samples was low (most values<10,000 animals m -3) from early April through early May, but increased to maxima in mid-June (cruise mean=121,500 animals m -3). Quantitative zooplankton samples (>102 μm) were dominated by copepod nauplii, and Oithona similis copepodites and adults at most locations except for those furthest inshore. At these inshore locations, Acartia hudsonica copepodites and adults were usually dominant. Larger copepods such as Calanus finmarchicus, Centropages typicus, and Pseudocalanus spp. were found primarily offshore, and at much lower abundances than O. similis. Rotifers, mainly present from late April to late May, were most abundant inshore. The marine cladoceran Evadne nordmani was sporadically abundant, particularly in mid-June. Microplankton in 20-64 μm size fractions was generally dominated by A. fundyense, non-toxic dinoflagellates, and tintinnids. Microplankton in 64-100 μm size fractions was generally dominated by larger non-toxic dinoflagellates, tintinnids, aloricate ciliates, and copepod nauplii, and in early May, rotifers. Some samples (23%) in the 64-100 μm size fractions contained abundant cells of A. fundyense, presumably due to sieve clogging, but most did not contain A. fundyense cells. This suggests that PSP toxin levels in those samples were due to vectorial intoxication of microzooplankters such as heterotrophic dinoflagellates, tintinnids, aloricate ciliates, rotifers, and copepod nauplii via feeding on A. fundyense cells. Dominant taxa in zooplankton fractions varied

Entropic Analysis of Electromyography Time Series

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

Hydroacoustic estimation of zooplankton biomass at two shoal complexes in the Apostle Islands Region of Lake Superior

USGS Publications Warehouse

Holbrook, B.V.; Hrabik, T.R.; Branstrator, D.K.; Yule, D.L.; Stockwell, J.D.

2006-01-01

Hydroacoustics can be used to assess zooplankton populations, however, backscatter must be scaled to be biologically meaningful. In this study, we used a general model to correlate site-specific hydroacoustic backscatter with zooplankton dry weight biomass estimated from net tows. The relationship between zooplankton dry weight and backscatter was significant (p < 0.001) and explained 76% of the variability in the dry weight data. We applied this regression to hydroacoustic data collected monthly in 2003 and 2004 at two shoals in the Apostle Island Region of Lake Superior. After applying the regression model to convert hydroacoustic backscatter to zooplankton dry weight biomass, we used geostatistics to analyze the mean and variance, and ordinary kriging to create spatial zooplankton distribution maps. The mean zooplankton dry weight biomass estimates from plankton net tows and hydroacoustics were not significantly different (p = 0.19) but the hydroacoustic data had a significantly lower coefficient of variation (p < 0.001). The maps of zooplankton distribution illustrated spatial trends in zooplankton dry weight biomass that were not discernable from the overall means.

Homogenising time series: Beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2010-09-01

For obtaining reliable information about climate change and climate variability the use of high quality data series is essentially important, and one basic tool of quality improvements is the statistical homogenisation of observed time series. In the recent decades large number of homogenisation methods has been developed, but the real effects of their application on time series are still not known entirely. The ongoing COST HOME project (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As 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 to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. The author believes that several old theoretical rules have to be re-evaluated. Some examples of the hot questions, a) Statistically detected change-points can be accepted only with the confirmation of metadata information? b) Do semi-hierarchic algorithms for detecting multiple change-points in time series function effectively in practise? c) Is it good to limit the spatial comparison of candidate series with up to five other series in the neighbourhood? Empirical results - those from the COST benchmark, and other experiments too - show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities seem like part of the climatic variability, thus the pure application of 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. The developers and users of homogenisation methods have to bear in mind that

Quantifying memory in complex physiological time-series.

PubMed

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.

Quantifying Memory in Complex Physiological Time-Series

PubMed Central

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. PMID:24039811

The use of chlorine dioxide for the inactivation of copepod zooplankton in drinking water treatment.

PubMed

Lin, Tao; Chen, Wei; Cai, Bo

2014-01-01

The presence of zooplankton in drinking water treatment system may cause a negative effect on the aesthetic value of drinking water and may also increase the threat to human health due to they being the carriers of bacteria. Very little research has been done on the effects of copepod inactivation and the mechanisms involved in this process. In a series of bench-scale experiments we used a response surface method to assess the sensitivity of copepod to inactivation when chlorine dioxide (ClO₂) was used as a disinfectant. We also assessed the effects of the ClO₂dosage, exposure time, organic matter concentration and temperature. Results indicated that the inactivation rate improved with increasing dosage, exposure time and temperature, whereas it decreased with increasing organic matter concentration. Copepod inactivation was more sensitive to the ClO₂dose than that to the exposure time, while being maintained at the same Ct-value conditions. The activation energy at different temperatures revealed that the inactivation of copepods with ClO₂was temperature-dependent. The presence of organic matter resulted in a lower available dose as well as a shorter available exposure time, which resulted in a decrease in inactivation efficiency.

Trophic ecology and vertical patterns of carbon and nitrogen stable isotopes in zooplankton from oxygen minimum zone regions

NASA Astrophysics Data System (ADS)

Williams, Rebecca L.; Wakeham, Stuart; McKinney, Rick; Wishner, Karen F.

2014-08-01

The unique physical and biogeochemical characteristics of oxygen minimum zones (OMZs) influence plankton ecology, including zooplankton trophic webs. Using carbon and nitrogen stable isotopes, this study examined zooplankton trophic webs in the Eastern Tropical North Pacific (ETNP) OMZ. δ13C values were used to indicate zooplankton food sources, and δ15N values were used to indicate zooplankton trophic position and nitrogen cycle pathways. Vertically stratified MOCNESS net tows collected zooplankton from 0 to 1000 m at two stations along a north-south transect in the ETNP during 2007 and 2008, the Tehuantepec Bowl and the Costa Rica Dome. Zooplankton samples were separated into four size fractions for stable isotope analyses. Particulate organic matter (POM), assumed to represent a primary food source for zooplankton, was collected with McLane large volume in situ pumps. The isotopic composition and trophic ecology of the ETNP zooplankton community had distinct spatial and vertical patterns influenced by OMZ structure. The most pronounced vertical isotope gradients occurred near the upper and lower OMZ oxyclines. Material with lower δ13C values was apparently produced in the upper oxycline, possibly by chemoautotrophic microbes, and was subsequently consumed by zooplankton. Between-station differences in δ15N values suggested that different nitrogen cycle processes were dominant at the two locations, which influenced the isotopic characteristics of the zooplankton community. A strong depth gradient in zooplankton δ15N values in the lower oxycline suggested an increase in trophic cycling just below the core of the OMZ. Shallow POM (0-110 m) was likely the most important food source for mixed layer, upper oxycline, and OMZ core zooplankton, while deep POM was an important food source for most lower oxycline zooplankton (except for samples dominated by the seasonally migrating copepod Eucalanus inermis). There was no consistent isotopic progression among the four

PHYTOPLANKTON AND ZOOPLANKTON SEASONAL DYNAMICS IN A SUBTROPICAL ESTUARY: IMPORTANCE OF CYANOBACTERIA

EPA Science Inventory

Murrell, Michael C. and Emile M. Lores. 2004. Phytoplankton and Zooplankton Seasonal Dynamics in a Subtropical Estuary: Importance of Cyanobacteria. J. Plankton Res. 26(3):371-382. (ERL,GB 1190).

A seasonal study of phytoplankton and zooplankton was conducted from 1999-20...

Seasonal and interannual changes in zooplankton community in the coastal zone of the North-Eastern Black Sea.

NASA Astrophysics Data System (ADS)

Nikishina, A. B.; Arashkevich, E. G.; Louppova, N. E.; Soloviev, K. A.

2009-04-01

obtained using SSC satellite data. For studying vertical distribution of zooplankton depth stratified samples were collected in different seasons. To evaluate seasonal variations in reproduction and offspring development of dominant mesozooplankton populations, we analyzed age structure of five species: four herbivorous copepods - Acartia clausi, Pseudocalanus elongatus, Paracalanus parvus and Calanus euxinus, and carnivorous chaethognaths Parasagitta setosa. Periods of mass reproduction varied in different years. The possible reason for this variation is the effect of climate change and top-predators on seasonal shift in zooplankton dynamics. Whereas timing of reproduction is related to life strategy of species, an intensity of reproduction and success of new generations depend on food supply. The impact of food conditions on abundance and age structure of herbivores was studied in the different seasons. Vertical distribution of different species also altered from year to year. Thus, in "warm" July 2007 (sea surface temperature 27°C) most of the Calanus euxinus population concentrated in the deeper layers than in "cold" July 2005 (sea surface temperature 22°C).

Homogenising time series: beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

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

NASA Technical Reports Server (NTRS)

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

NASA Astrophysics Data System (ADS)

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.

Lake St. Clair zooplankton: Evidence for post-Dreissena changes

USGS Publications Warehouse

David, Katherine A.; Davis, Bruce M.; Hunter, R. Douglas

2009-01-01

We surveyed the zooplankton of Lake St. Clair at 12 sites over ten dates from May to October 2000. Mean zooplankton density by site and date was 168.6 individuals/L, with Dreissena spp. veligers the most abundant taxon at 122.7 individuals/L. Rotifers, copepods, and cladocerans were far lower in mean abundance than in the early 1970s (rotifers, 20.9/L; copepods, 18.1/L; and cladocerans, 6.8/L). Species richness of zooplankton taxa in 2000 was 147, which was virtually unchanged from that of the first reported survey in 1894. Overall, the decline in abundance was greatest for rotifers (-90%) and about equal for cladocerans (-69%) and copepods (-66%). The decrease in abundance of Daphnia spp. was especially dramatic in Canadian waters. The decline in the southeastern region was significant for all three major groups of zooplankton, whereas in the northwestern region the decline was significant only for rotifers. From June to August 2000, Lake St. Clair open waters were numerically dominated by Dreissena spp. veligers, with a reduced abundance of rotifers and crustaceans compared to pre-Dreissena spp. surveys. Mean nutrient concentrations were not different from the 1970s, but Secchi depth (greater) and chlorophyll a concentration (lower) were. Disproportionate reduction in rotifer abundance is consistent with hypotheses implicating direct consumption by settled Dreissena spp. Reduction of crustaceans is likely due to more complex interactions including removal of nauplii as well as resource competition for phytoplankton.

A compilation of quantitative functional traits for marine and freshwater crustacean zooplankton.

PubMed

Hébert, Marie-Pier; Beisner, Beatrix E; Maranger, Roxane

2016-04-01

This data compilation synthesizes 8609 individual observations and ranges of 13 traits from 201 freshwater and 191 marine crustacean taxa belonging to either Copepoda or Cladocera, two important zooplankton groups across all major aquatic habitats. Most data were gathered from the literature, with the balance being provided by zooplankton ecologists. With the aim of more fully assessing zooplankton effects on elemental processes such as nitrogen (N), phosphorus (P) and carbon (C) stocks and fluxes in aquatic ecosystems, this data set provides information on the following traits: body size (length and mass), trophic group, elemental and biochemical corporal composition (N, P, C, lipid and protein content), respiration rates, N- and P-excretion rates, as well as stoichiometric ratios. Although relationships for zooplankton metabolism as a function of body mass or requirements have been explored in the past three decades, data have not been systematically compiled nor examined from an integrative and large-scale perspective across crustacean taxa and habitat types. While this contribution likely represents the most comprehensive assembly of traits for both marine and freshwater species, this data set is not exhaustive either. As a result, this compilation also identifies knowledge gaps: a fact that should encourage researchers to disclose information they may have to help complete such databases. This trait matrix is made available for the first time in this data paper; prior to its release, the data set has been analyzed in a meta-analysis published as a companion paper. This data set should prove extremely valuable for aquatic ecologists for trait-based characterization of plankton community structure as well as biogeochemical modeling. These data are also well-suited for deriving shortcut relationships that predict more difficult to measure trait values, most of which can be directly related to ecosystem properties (i.e., effect traits), from simpler traits (e

Multivariate Time Series Decomposition into Oscillation Components.

PubMed

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.

Lessons learned from multifrequency acoustic studies of zooplankton and micronekton in the western Antarctic Peninsula and the Gulf of Maine

NASA Astrophysics Data System (ADS)

Lavery, Andone C.; Lawson, Gareth L.; Wiebe, Peter H.

2005-09-01

A series of acoustic surveys of zooplankton and micronekton have been performed in the Gulf of Maine (GOM), off the northeast United States, and along the western Antarctic Peninsula (WAP). Similar techniques were used to survey these regions, including multifrequency acoustic backscatter (43, 120, 200, 420, 1000 kHz), MOCNESS, CTD, VPR, and in some instances physical microstructure measurements. The GOM is characterized by heterogeneous zooplankton communities in which biomass is dominated by abundant millimeter sized copepods, but the scattering is frequently dominated by a smaller number of strong scatterers, such as shelled pteropods and gas-bearing siphonophores. Heterogeneous zooplankton communities are also observed in the WAP, but patches of comparatively large (40 mm) Antarctic krill are present and often dominate the scattering. In both regions, striking patterns are evident in the backscatter that can be related to the biological community structure and physical processes. Differences in community structure, however, strongly affect the quantitative inferences that can be made based on the acoustic data. Combining direct biological and environmental information with recently developed scattering models has allowed dominant scatterers to be identified and inferences to be made regarding the physical factors influencing backscatter variability, though only under limited conditions. Highlights from these studies and lessons learned regarding our ability to interpret multifrequency acoustics are presented.

Forecasting Enrollments with Fuzzy Time Series.

ERIC Educational Resources Information Center

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…

CHEMICAL TIME-SERIES SAMPLING

EPA Science Inventory

The rationale for chemical time-series sampling has its roots in the same fundamental relationships as govern well hydraulics. Samples of ground water are collected as a function of increasing time of pumpage. The most efficient pattern of collection consists of logarithmically s...

Examining shifts in zooplankton community as a response of environmental change in Lakes

NASA Astrophysics Data System (ADS)

Ghadouani, Anas; Mines, Conor; Legendre, Pierre; Yan, Norman

2014-05-01

We examined 20 years of zooplankton samples from Harp Lake for shifts in zooplankton variability following invasion by zooplankton predator Bythotrephes longimanus, using organism body size—as measured at high resolution by Laser Optical Plankton Counter (LOPC)—as the primary metric of investigation. A period of transitory high variability in the 2yr post-invasion was observed for both body size compositional variability and aggregate variability metrics, with both measures of variability shifting from low or intermediate to high variability immediately following invasion, before shifting again to intermediate variability, 2 yr post-invasion. Aggregate and compositional variability dynamics were also considered in combination over the study period, revealing that the period of transitory high variability coincided with a shift from a community-wide stasis variability pattern to one of asynchrony, before a shift back to stasis 2 yr post-invasion. These dynamics were related to changes in the significant zooplankton species within the Harp Lake community over the pre- and post- invasion periods, and are likely to be indicative of changes in the stability in the zooplankton community following invasion by Bythotrephes. The dual consideration of aggregate and compositional variability as measured by LOPC was found to provide a valuable means to assess the ecological effects of biological invasion on zooplankton communities as a whole, extending our knowledge of the effects of invasion beyond that already revealed through more traditional taxonomic investigation.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Late-summer zooplankton community structure, abundance, and distribution in the Hudson Bay system (Canada) and their relationships with environmental conditions, 2003-2006

NASA Astrophysics Data System (ADS)

Estrada, Rafael; Harvey, Michel; Gosselin, Michel; Starr, Michel; Galbraith, Peter S.; Straneo, Fiammetta

2012-08-01

Zooplankton communities were examined for the first time in three different hydrographic regions of the Hudson Bay system (HBS) in early August to early September from 2003 to 2006. Sampling was conducted at 50 stations distributed along different transects located in Hudson Bay (HB), Hudson Strait (HS), and Foxe Basin (FB). Variations in zooplankton biomass, abundance, taxonomic composition, and diversity in relation to environmental variables were studied using multivariate techniques. During all sampling years, the total zooplankton biomass was on average four times lower in HB than in HS and FB. Clustering samples by their relative species compositions revealed no interannual variation in zooplankton community but showed a marked interregional variability between the three regions. Water column stratification explained the greatest proportion (25%) of this spatial variability. According to redundancy analysis (RDA), the zooplankton taxa that contribute most to the separation of the three regions are Microcalanus spp., Oithona similis, Oncaea borealis, Aeginopsis laurentii, Sagitta elegans, Fritillaria sp., and larvae of cnidaria, chaetognatha, and pteropoda in HB; hyperiid amphipods in FB; and Pseudocalanus spp. CI-CV, Calanus glacialis CI-CVI, Calanus finmarchicus CI-CVI, Calanus hyperboreus CV-CVI, Acartia longiremis CI-CV, Metridia longa N3-N6 CI-CIII CVIf, Eukrohnia hamata, larvae of echinodermata, mollusca, cirripedia, appendicularia, and polychaeta in the northwestern and southeastern HS transects. For the HB transect, the RDA analyzed allowed us to distinguish three regions (HB west, central, and east) with different environmental gradients and zooplankton assemblages, in particular higher concentration of Pseudocalanus spp. nauplii and CI-CVI, as well as benthic macrozooplankton and meroplankton larvae in western HB. In HS, Calanoid species (mainly C. finmarchicus and C. glacialis) were mostly observed at the north shore stations associated with the

Neustonic microplastic and zooplankton in the North Western Mediterranean Sea.

PubMed

Collignon, Amandine; Hecq, Jean-Henri; Glagani, François; Voisin, Pierre; Collard, France; Goffart, Anne

2012-04-01

Neustonic microplastic and zooplankton abundance was determined in the North Western Mediterranean Sea during a summer cruise between July 9th and August 6th 2010, with a break between July 22 th and 25th due to a strong wind event. Ninety percent of the 40 stations contained microplastic particles (size 0.3-5mm) of various compositions: e.g., filaments, polystyrene, thin plastic films. An average concentration of 0.116 particles/m(2) was observed. The highest abundances (>0.36 particles/m(2)) were observed in shelf stations. The neustonic plastic particles concentrations were 5 times higher before than after the strong wind event which increased the mixing and the vertical repartition of plastic particles in the upper layers of the water column. The values rise in the same order of magnitude than in the North Pacific Gyre. The average ratio between microplastics and mesozooplankton weights was 0.5 for the whole survey and might induce a potential confusion for zooplankton feeders. Copyright © 2012 Elsevier Ltd. All rights reserved.

Learning time series for intelligent monitoring

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug

1994-01-01

We address the problem of classifying time series according to their morphological features in the time domain. In a supervised machine-learning framework, we induce a classification procedure from a set of preclassified examples. For each class, we infer a model that captures its morphological features using Bayesian model induction and the minimum message length approach to assign priors. In the performance task, we classify a time series in one of the learned classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. We report results from experiments in a monitoring domain of interest to NASA.

Variations in the structural and functional diversity of zooplankton over vertical and horizontal environmental gradients en route to the Arctic Ocean through the Fram Strait.

PubMed

Gluchowska, Marta; Trudnowska, Emilia; Goszczko, Ilona; Kubiszyn, Anna Maria; Blachowiak-Samolyk, Katarzyna; Walczowski, Waldemar; Kwasniewski, Slawomir

2017-01-01

A multi-scale approach was used to evaluate which spatial gradient of environmental variability is the most important in structuring zooplankton diversity in the West Spitsbergen Current (WSC). The WSC is the main conveyor of warm and biologically rich Atlantic water to the Arctic Ocean through the Fram Strait. The data set included 85 stratified vertical zooplankton samples (obtained from depths up to 1000 metres) covering two latitudinal sections (76°30'N and 79°N) located across the multi-path WSC system. The results indicate that the most important environmental variables shaping the zooplankton structural and functional diversity and standing stock variability are those associated with depth, whereas variables acting in the horizontal dimension are of lesser importance. Multivariate analysis of the zooplankton assemblages, together with different univariate descriptors of zooplankton diversity, clearly illustrated the segregation of zooplankton taxa in the vertical plane. The epipelagic zone (upper 200 m) hosted plentiful, Oithona similis-dominated assemblages with a high proportion of filter-feeding zooplankton. Although total zooplankton abundance declined in the mesopelagic zone (200-1000 m), zooplankton assemblages in that zone were more diverse and more evenly distributed, with high contributions from both herbivorous and carnivorous taxa. The vertical distribution of integrated biomass (mg DW m-2) indicated that the total zooplankton biomass in the epipelagic and mesopelagic zones was comparable. Environmental gradients acting in the horizontal plane, such as the ones associated with different ice cover and timing of the spring bloom, were reflected in the latitudinal variability in protist community structure and probably caused differences in succession in the zooplankton community. High abundances of Calanus finmarchicus in the WSC core branch suggest the existence of mechanisms advantageous for higher productivity or/and responsible for physical

Directionality volatility in electroencephalogram time series

NASA Astrophysics Data System (ADS)

Mansor, Mahayaudin M.; Green, David A.; Metcalfe, Andrew V.

2016-06-01

We compare time series of electroencephalograms (EEGs) from healthy volunteers with EEGs from subjects diagnosed with epilepsy. The EEG time series from the healthy group are recorded during awake state with their eyes open and eyes closed, and the records from subjects with epilepsy are taken from three different recording regions of pre-surgical diagnosis: hippocampal, epileptogenic and seizure zone. The comparisons for these 5 categories are in terms of deviations from linear time series models with constant variance Gaussian white noise error inputs. One feature investigated is directionality, and how this can be modelled by either non-linear threshold autoregressive models or non-Gaussian errors. A second feature is volatility, which is modelled by Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) processes. Other features include the proportion of variability accounted for by time series models, and the skewness and the kurtosis of the residuals. The results suggest these comparisons may have diagnostic potential for epilepsy and provide early warning of seizures.

Identifying zooplankton community changes between shallow and upper-mesophotic reefs on the Mesoamerican Barrier Reef, Caribbean.

PubMed

Andradi-Brown, Dominic A; Head, Catherine E I; Exton, Dan A; Hunt, Christina L; Hendrix, Alicia; Gress, Erika; Rogers, Alex D

2017-01-01

Mesophotic coral ecosystems (MCEs, reefs 30-150 m) are understudied, yet the limited research conducted has been biased towards large sessile taxa, such as scleractinian corals and sponges, or mobile taxa such as fishes. Here we investigate zooplankton communities on shallow reefs and MCEs around Utila on the southern Mesoamerican Barrier Reef using planktonic light traps. Zooplankton samples were sorted into broad taxonomic groups. Our results indicate similar taxonomic zooplankton richness and overall biomass between shallow reefs and MCEs. However, the abundance of larger bodied (>2 mm) zooplanktonic groups, including decapod crab zoea, mysid shrimps and peracarid crustaceans, was higher on MCEs than shallow reefs. Our findings highlight the importance of considering zooplankton when identifying broader reef community shifts across the shallow reef to MCE depth gradient.

Clustering Financial Time Series by Network Community Analysis

NASA Astrophysics Data System (ADS)

Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

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

PubMed

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.

The Lake Ontario zooplankton community before (1987-1991) and after (2001-2005) invasion-induced ecosystem change

USGS Publications Warehouse

Stewart, T.J.; Johannsson, O.E.; Holeck, K.; Sprules, W.G.; O'Gorman, R.

2010-01-01

We assessed changes in Lake Ontario zooplankton biomass, production, and community composition before (1987–1991) and after (2001–2005) invasion-induced ecosystem changes. The ecosystem changes were associated with establishment of invasive dreissenid mussels and invasive predatory cladocerans (Bythotrephes and Cercopagis). Whole-lake total epilimnetic plus metalimnetic zooplankton production declined by approximately half from 42.45 (g dry wt∙m−2∙ year−1) during 1987–1991 to 21.91 (g dry wt∙m−2∙ year−1) in 2003 and averaged 21.01 (g dry wt∙m−2∙ year−1) during 2001–2005. Analysis of two independent data sets indicates that the mean biomass and biomass proportion of cyclopoid copepods declined while the same measures increased for the invasive predatory cladocerans. Changes in means and proportions of all other zooplankton groups were not consistent between the data sets. Cyclopoid copepod biomass and production declined by factors ranging from 3.6 to 5.7. Invasive predatory cladoceran biomass averaged from 5.0% to 8.0% of the total zooplankton biomass. The zooplankton community was otherwise resilient to the invasion-induced disruption as zooplankton species richness and diversity were unaffected. Zooplankton production was likely reduced by declines in primary productivity but may have declined further due to increased predation by alewives and invasive predatory cladocerans. Shifts in zooplankton community structure were consistent with increased predation pressure on cyclopoid copepods by alewives and invasive predatory cladocerans. Predicted declines in the proportion of small cladocerans were not evident. This study represents the first direct comparison of changes in Lake Ontario zooplankton production before and after the invasion-induced disruption and will be important to food web-scale investigations of invasion effects.

[Effects of temperature increase on zooplankton size spectra in thermal discharge seawaters near a power plant, China].

PubMed

Yu, Jing; Zhu, Yi Feng; Dai, Mei Xia; Lin, Xia; Mao, Shuo Qian

2017-05-18

Utilizing the plankton 1 (505 Μm), 2 (160 Μm), 3 (77 Μm) nets to seasonally collect zooplankton samples at 10 stations and the corresponding abundance data was obtained. Based on individual zooplankton biovolume, size groups were classified to test the changes in spatiotemporal characteristics of both Sheldon and normalized biovolume size spectra in thermal discharge seawaters near the Guohua Power Plant, so as to explore the effects of temperature increase on zooplankton size spectra in the seawaters. The results showed that the individual biovolume of zooplankton ranged from 0.00012 to 127.0 mm 3 ·ind -1 , which could be divided into 21 size groups, and corresponding logarithmic ranges were from -13.06 to 6.99. According to Sheldon size spectra, the predominant species to form main peaks of the size spectrum in different months were Copepodite larvae, Centropages mcmurrichi, Calanus sinicus, fish larvae, Sagitta bedoti, Sagitta nagae and Pleurobrachia globosa, and minor peaks mostly consisted of individuals with smaller larvae, Cyclops and Paracalanus aculeatus. In different warming sections, Copepodite larvae, fish eggs and Cyclops were mostly unaffected by the temperature increase, while the macrozooplankton such as S. bedoti, S. nagae, P. globosa, C. sinicus and Beroe cucumis had an obvious tendency to avoid the outfall of the power plant. Based on the results of normalized size spectra, the intercepts from low to high occurred in November, February, May and August, respectively. At the same time, the minimum slope was found in February, and similarly bigger slopes were observed in May and August. These results indicated that the proportion of small zooplankton was highest in February, while the proportions of the meso- and macro-zooplankton were relatively high in May and August. Among different sections, the slope in the 0.2 km section was minimum, which increased with the increase of section distance to the outfall. The result obviously demonstrated

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Coherence of long-term variations of zooplankton in two sectors of the California Current System

NASA Astrophysics Data System (ADS)

Lavaniegos, Bertha E.; Ohman, Mark D.

2007-10-01

We analyzed long-term (56-year) variations in springtime biomass of the zooplankton of the California Current System from two primary regions sampled by CalCOFI: Southern California (SC) and Central California (CC) waters. All organisms were enumerated from the plankton samples and converted to organic carbon biomass using length-carbon relationships, then aggregated into 19 major taxa. Planktonic copepods dominate the carbon biomass in both SC (59%) and CC (46%), followed by euphausiids (18% and 25% of mean biomass in SC and CC, respectively). Pelagic tunicates, especially salps and doliolids, constituted a higher fraction of the biomass in CC (13%) than in SC (5%). There was no long-term trend detectable in total zooplankton carbon biomass, in marked contrast to a decline in zooplankton displacement volume in both regions. The difference between these biomass metrics is accounted for by a long-term decline in pelagic tunicates (particularly salps), which have a relatively high ratio of biovolume:carbon. The decline in pelagic tunicates was accompanied by a long-term increase in water column density stratification. No other taxa showed a decline over the duration of the study, apart from salps and pyrosomes in SC and doliolids in CC. Some zooplankton taxa showed compensatory increases over the same time period (ostracods, large decapods, and calycophoran siphonophores in both SC and CC; appendicularians and polychaetes in SC). Two tests for ecosystem shifts, a sequential algorithm and the cumulative sum of anomalies (CuSum) approach, failed to detect changes in 1976-1977 in total carbon biomass, displacement volume, or most individual major taxa, suggesting that aggregated biomass is an insensitive indicator of climate forcing. In contrast, both techniques revealed a cluster of step-like changes associated with the La Niña of 1999. The major El Niño’s in the past half century have consistently depressed total zooplankton biomass and biomass of many major taxa

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

NASA Astrophysics Data System (ADS)

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

EVALUATION OF OPTICALLY ACQUIRED ZOOPLANKTON SIZE-SPECTRUM DATA AS A POTENTIAL TOOL FOR ASSESSMENT OF CONDITION IN THE GREAT LAKES

EPA Science Inventory

An optical zooplankton counter (OPC) potentially provides as assessment tool for zooplankton condition in ecosystems that is rapid, economical, and spatially extensive. We collected zooplankton data with an optical zooplankton counter in 20 near-shore regions of four of the Laure...

Effect of Main-stem Dams on Zooplankton Communities of the Missouri River (USA)

EPA Science Inventory

We examined the distribution and abundance of zooplankton from 146 sites on the Missouri River and found large shifts in the dominance of major taxa between management zones of this regulated river. Crustacean zooplankton were dominant in the inter-reservoir zone of the river, an...

Time Series Model Identification by Estimating Information.

DTIC Science & Technology

1982-11-01

principle, Applications of Statistics, P. R. Krishnaiah , ed., North-Holland: Amsterdam, 27-41. Anderson, T. W. (1971). The Statistical Analysis of Time Series...E. (1969). Multiple Time Series Modeling, Multivariate Analysis II, edited by P. Krishnaiah , Academic Press: New York, 389-409. Parzen, E. (1981...Newton, H. J. (1980). Multiple Time Series Modeling, II Multivariate Analysis - V, edited by P. Krishnaiah , North Holland: Amsterdam, 181-197. Shibata, R

Terrestrial carbohydrates support freshwater zooplankton during phytoplankton deficiency.

PubMed

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.

Terrestrial carbohydrates support freshwater zooplankton during phytoplankton deficiency

PubMed Central

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

2016-01-01

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. PMID:27510848

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

PubMed

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

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

PubMed

Koski, Marja; Boutorh, Julia; de la Rocha, Christina

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 metabolic rates. We fed 5 copepod species-three calanoid, one harpacticoid and one poecilamastoid-microplankton food, in either dispersed or aggregated form and measured rates of respiration, fecal pellet production and egg production. Calanoid copepods were able to feed only on dispersed food; when their food was introduced as aggregates, their pellet production and respiration rates decreased to rates observed for starved individuals. In contrast, harpacticoids and the poecilamastoid copepod Oncaea spp. were able to feed only when the food was in the form of aggregates. The sum of copepod respiration, pellet production and egg production rates was equivalent to a daily minimum carbon demand of ca. 10% body weight-1 for all non-feeding copepods; the carbon demand of calanoids feeding on dispersed food was 2-3 times greater, and the carbon demand of harpacticoids and Oncaea spp. feeding on aggregates was >7 times greater, than the resting rates. The zooplankton species composition combined with the type of available food strongly influences the calculated carbon demand of a copepod community, and thus also the attenuation of vertical carbon flux.

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

PubMed Central

Boutorh, Julia; de la Rocha, Christina

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 metabolic rates. We fed 5 copepod species—three calanoid, one harpacticoid and one poecilamastoid–microplankton food, in either dispersed or aggregated form and measured rates of respiration, fecal pellet production and egg production. Calanoid copepods were able to feed only on dispersed food; when their food was introduced as aggregates, their pellet production and respiration rates decreased to rates observed for starved individuals. In contrast, harpacticoids and the poecilamastoid copepod Oncaea spp. were able to feed only when the food was in the form of aggregates. The sum of copepod respiration, pellet production and egg production rates was equivalent to a daily minimum carbon demand of ca. 10% body weight-1 for all non-feeding copepods; the carbon demand of calanoids feeding on dispersed food was 2–3 times greater, and the carbon demand of harpacticoids and Oncaea spp. feeding on aggregates was >7 times greater, than the resting rates. The zooplankton species composition combined with the type of available food strongly influences the calculated carbon demand of a copepod community, and thus also the attenuation of vertical carbon flux. PMID:28545095

Scale-dependent intrinsic entropies of complex time series.

PubMed

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).

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

PubMed

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

NASA Astrophysics Data System (ADS)

Boudraa, Abdel-Ouahab; Cexus, Jean-Christophe; Groussat, Mathieu; Brunagel, Pierre

2007-12-01

A new similarity measure, called SimilB, for time series analysis, based on the cross-[InlineEquation not available: see fulltext.]-energy operator (2004), is introduced. [InlineEquation not available: see fulltext.] 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 [InlineEquation not available: see fulltext.] are presented. Particularly, we show that [InlineEquation not available: see fulltext.] 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.

Detecting chaos in irregularly sampled time series.

PubMed

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.

Phase walk analysis of leptokurtic time series.

PubMed

Schreiber, Korbinian; Modest, Heike I; Räth, Christoph

2018-06-01

The Fourier phase information play a key role for the quantified description of nonlinear data. We present a novel tool for time series analysis that identifies nonlinearities by sensitively detecting correlations among the Fourier phases. The method, being called phase walk analysis, is based on well established measures from random walk analysis, which are now applied to the unwrapped Fourier phases of time series. We provide an analytical description of its functionality and demonstrate its capabilities on systematically controlled leptokurtic noise. Hereby, we investigate the properties of leptokurtic time series and their influence on the Fourier phases of time series. The phase walk analysis is applied to measured and simulated intermittent time series, whose probability density distribution is approximated by power laws. We use the day-to-day returns of the Dow-Jones industrial average, a synthetic time series with tailored nonlinearities mimicing the power law behavior of the Dow-Jones and the acceleration of the wind at an Atlantic offshore site. Testing for nonlinearities by means of surrogates shows that the new method yields strong significances for nonlinear behavior. Due to the drastically decreased computing time as compared to embedding space methods, the number of surrogate realizations can be increased by orders of magnitude. Thereby, the probability distribution of the test statistics can very accurately be derived and parameterized, which allows for much more precise tests on nonlinearities.

Zooplankton assemblages in montane lakes and ponds of Mount Rainier National Park, Washington State, USA

USGS Publications Warehouse

Larson, G.L.; Hoffman, R.; McIntire, C.D.; Lienkaemper, G.; Samora, B.

2009-01-01

Water quality and zooplankton samples were collected during the ice-free periods between 1988 and 2005 from 103 oligotrophic montane lakes and ponds located in low forest to alpine vegetation zones in Mount Rainier National Park, Washington State, USA. Collectively, 45 rotifer and 44 crustacean taxa were identified. Most of the numerically dominant taxa appeared to have wide niche breadths. The average number of taxa per lake decreased with elevation and generally increased as maximum lake depths increased (especially for rotifers). With one exception, fish presence/absence did not explain the taxonomic compositions of crustacean zooplankton assemblages. Many rotifer species were common members of zooplankton assemblages in montane lakes and ponds in western North America, whereas the crustacean taxa were common to some areas of the west, but not others. Constraints of the environmental variables did not appear to provide strong gradients to separate the distributions of most zooplankton species. This suggests that interspecific competitive interactions and stochastic processes regulate the taxonomic structures of the zooplankton assemblages at the landscape level. Crustacean species that had broad niche breadths were associated with different rotifer taxa across the environmental gradients. Studies of zooplankton assemblages need to address both crustacean and rotifer taxa, not one or the other.

FATS: Feature Analysis for Time Series

NASA Astrophysics Data System (ADS)

Nun, Isadora; Protopapas, Pavlos; Sim, Brandon; Zhu, Ming; Dave, Rahul; Castro, Nicolas; Pichara, Karim

2017-11-01

FATS facilitates and standardizes feature extraction for time series data; it quickly and efficiently calculates a compilation of many existing light curve features. Users can characterize or analyze an astronomical photometric database, though this library is not necessarily restricted to the astronomical domain and can also be applied to any kind of time series data.

Protocol for Automated Zooplankton Analysis

DTIC Science & Technology

2010-01-01

on maximum dimension on the smallest axis: organisms > 50 microns (urn) (nominally zooplankton), organisms > 10 um to < 50 um (nominally protists ...viability of protists . Recent work has focused on performing measurements at a variety of geographic locations to demonstrate that these stains...provide a location-independent means to identify viable protists in test samples. NRL recommends staining samples with a combination of two vital stains

Time-dependent limited penetrable visibility graph analysis of nonstationary time series

NASA Astrophysics Data System (ADS)

Gao, Zhong-Ke; Cai, Qing; Yang, Yu-Xuan; Dang, Wei-Dong

2017-06-01

Recent years have witnessed the development of visibility graph theory, which allows us to analyze a time series from the perspective of complex network. We in this paper develop a novel time-dependent limited penetrable visibility graph (TDLPVG). Two examples using nonstationary time series from RR intervals and gas-liquid flows are provided to demonstrate the effectiveness of our approach. The results of the first example suggest that our TDLPVG method allows characterizing the time-varying behaviors and classifying heart states of healthy, congestive heart failure and atrial fibrillation from RR interval time series. For the second example, we infer TDLPVGs from gas-liquid flow signals and interestingly find that the deviation of node degree of TDLPVGs enables to effectively uncover the time-varying dynamical flow behaviors of gas-liquid slug and bubble flow patterns. All these results render our TDLPVG method particularly powerful for characterizing the time-varying features underlying realistic complex systems from time series.

Trace metal dynamics in zooplankton from the Bay of Bengal during summer monsoon.

PubMed

Rejomon, G; Kumar, P K Dinesh; Nair, M; Muraleedharan, K R

2010-12-01

Trace metal (Fe, Co, Ni, Cu, Zn, Cd, and Pb) concentrations in zooplankton from the mixed layer were investigated at 8 coastal and 20 offshore stations in the western Bay of Bengal during the summer monsoon of 2003. The ecotoxicological importance of trace metal uptake was apparent within the Bay of Bengal zooplankton. There was a distinct spatial heterogeneity of metals, with highest concentrations in the upwelling zones of the southeast coast, moderate concentrations in the cyclonic eddy of the northeast coast, and lowest concentrations in the open ocean warm gyre regions. The average trace metal concentrations (μg g⁻¹) in coastal zooplankton (Fe, 44894.1 ± 12198.2; Co, 46.2 ± 4.6; Ni, 62.8 ± 6.5; Cu, 84.9 ± 6.7; Zn, 7546.8 ± 1051.7; Cd, 46.2 ± 5.6; Pb, 19.2 ± 2.6) were higher than in offshore zooplankton (Fe, 3423.4 ± 681.6; Co, 19.5 ± 3.81; Ni, 25.3 ± 7.3; Cu, 29.4 ± 4.2; Zn, 502.3 ± 124.3; Cd, 14.3 ± 2.9; Pb, 3.2 ± 2.0). A comparison of average trace metal concentrations in zooplankton from the Bay of Bengal showed enrichment of Fe, Co, Ni, Cu, Zn, Cd, and Pb in coastal zooplankton may be related to metal absorption from primary producers, and differences in metal concentrations in phytoplankton from coastal waters (upwelling zone and cyclonic eddy) compared with offshore waters (warm gyre). Zooplankton showed a great capacity for accumulations of trace metals, with average concentration factors of 4 867 929 ± 569 971, 246 757 ± 51 321, 337 180 ± 125 725, 43 480 ± 11 212, 1 046 371 ± 110 286, 601 679 ± 213 949, and 15 420 ± 9201 for Fe, Co, Ni, Cu, Zn, Cd, and Pb with respect to dissolved concentrations in coastal and offshore waters of the Bay of Bengal. © 2009 Wiley Periodicals, Inc. Environ Toxicol, 2009. Copyright © 2009 Wiley Periodicals, Inc.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 atmore » 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.« less

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

NASA Astrophysics Data System (ADS)

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 responses to increasing sea surface temperatures in the southeastern Australia global marine hotspot

NASA Astrophysics Data System (ADS)

Kelly, Paige; Clementson, Lesley; Davies, Claire; Corney, Stuart; Swadling, Kerrie

2016-10-01

Southeastern Australia is a 'hotspot' for oceanographic change. Here, rapidly increasing sea surface temperatures, rising at more than double the global trend, are largely associated with a southerly extension of the East Australian Current (EAC) and its eddy field. Maria Island, situated at the southern end of the EAC extension at 42°S, 148°E, has been used as a site to study temperature-driven biological trends in this region of accelerated change. Zooplankton have short life cycles (usually < 1 year) and are highly sensitive to environmental change, making them an ideal indicator of the biological effects of an increased southward flow of the EAC. Data from in-situ net drops and the Continuous Plankton Recorder (CPR), collected since 2009, together with historical zooplankton abundance data, have been analysed in this study. Like the North Atlantic, zooplankton communities of southeastern Australia are responding to increased temperatures through relocation, long-term increases in warm-water species and a shift towards a zooplankton community dominated by small copepods. The biological trends present evidence of extended EAC influence at Maria Island into autumn and winter months, which has allowed for the rapid establishment of warm-water species during these seasons, and has increased the similarity between Maria Island and the more northerly Port Hacking zooplankton community. Generalised Linear Models (GLM) suggest the high salinity and low nutrient properties of EAC-water to be the primary drivers of increasing abundances of warm-water species off southeastern Australia. Changes in both the species composition and size distribution of the Maria Island zooplankton community will have effects for pelagic fisheries. This study provides an indication of how zooplankton communities influenced by intensifying Western Boundary currents may respond to rapid environmental change.

Efficient Algorithms for Segmentation of Item-Set Time Series

NASA Astrophysics Data System (ADS)

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.

Dynamics of Marine Zooplankton: Social Behavior, Ecological Interactions, and Physically-Induced Variability

DTIC Science & Technology

2008-02-01

97 3.3.2 Steady-state solutions ..... ........................ 100 3.4 Ecosystem dynamics ...... ............................. 102 3.4.1 Fast ...zooplankton motion is decoupled from biological ac- tivities, as calculated in Flier] et al. (1999). When the diffusion rate is fast compared to phytoplankton...homogenize the zooplankton distribution, which remains spatially more intermit - tent than a passive scalar field. The last panel shows the index for

Distribution and abundance of zooplankton populations in Crater Lake, Oregon

USGS Publications Warehouse

Larson, G.L.; McIntire, C.D.; Buktenica, M.W.; Girdner, S.F.; Truitt, R.E.

2007-01-01

The zooplankton assemblages in Crater Lake exhibited consistency in species richness and general taxonomic composition, but varied in density and biomass during the period between 1988 and 2000. Collectively, the assemblages included 2 cladoceran taxa and 10 rotifer taxa (excluding rare taxa). Vertical habitat partitioning of the water column to a depth of 200 m was observed for most species with similar food habits and/or feeding mechanisms. No congeneric replacement was observed. The dominant species in the assemblages were variable, switching primarily between periods of dominance of Polyarthra-Keratella cochlearis and Daphnia. The unexpected occurrence and dominance of Asplanchna in 1991 and 1992 resulted in a major change in this typical temporal shift between Polyarthra-K. cochlearis and Daphnia. Following a collapse of the zooplankton biomass in 1993 that was probably caused by predation from Asplanchna, Kellicottia dominated the zooplankton assemblage biomass between 1994 and 1997. The decline in biomass of Kellicottia by 1998 coincided with a dramatic increase in Daphnia biomass. When Daphnia biomass declined by 2000, Keratella biomass increased again. Thus, by 1998 the assemblage returned to the typical shift between Keratella-Polyarthra and Daphnia. Although these observations provided considerable insight about the interannual variability of the zooplankton assemblages in Crater Lake, little was discovered about mechanisms behind the variability. When abundant, kokanee salmon may have played an important role in the disappearance of Daphnia in 1990 and 2000 either through predation, inducing diapause, or both. ?? 2007 Springer Science+Business Media B.V.

Dead zone or oasis in the open ocean? Zooplankton distribution and migration in low-oxygen modewater eddies

NASA Astrophysics Data System (ADS)

Hauss, Helena; Christiansen, Svenja; Schütte, Florian; Kiko, Rainer; Edvam Lima, Miryam; Rodrigues, Elizandro; Karstensen, Johannes; Löscher, Carolin R.; Körtzinger, Arne; Fiedler, Björn

2016-04-01

The eastern tropical North Atlantic (ETNA) features a mesopelagic oxygen minimum zone (OMZ) at approximately 300-600 m depth. Here, oxygen concentrations rarely fall below 40 µmol O2 kg-1, but are expected to decline under future projections of global warming. The recent discovery of mesoscale eddies that harbour a shallow suboxic (< 5 µmol O2 kg-1) OMZ just below the mixed layer could serve to identify zooplankton groups that may be negatively or positively affected by ongoing ocean deoxygenation. In spring 2014, a detailed survey of a suboxic anticyclonic modewater eddy (ACME) was carried out near the Cape Verde Ocean Observatory (CVOO), combining acoustic and optical profiling methods with stratified multinet hauls and hydrography. The multinet data revealed that the eddy was characterized by an approximately 1.5-fold increase in total area-integrated zooplankton abundance. At nighttime, when a large proportion of acoustic scatterers is ascending into the upper 150 m, a drastic reduction in mean volume backscattering (Sv) at 75 kHz (shipboard acoustic Doppler current profiler, ADCP) within the shallow OMZ of the eddy was evident compared to the nighttime distribution outside the eddy. Acoustic scatterers avoided the depth range between approximately 85 to 120 m, where oxygen concentrations were lower than approximately 20 µmol O2 kg-1, indicating habitat compression to the oxygenated surface layer. This observation is confirmed by time series observations of a moored ADCP (upward looking, 300 kHz) during an ACME transit at the CVOO mooring in 2010. Nevertheless, part of the diurnal vertical migration (DVM) from the surface layer to the mesopelagic continued through the shallow OMZ. Based upon vertically stratified multinet hauls, Underwater Vision Profiler (UVP5) and ADCP data, four strategies followed by zooplankton in response to in response to the eddy OMZ have been identified: (i) shallow OMZ avoidance and compression at the surface (e.g. most calanoid

Sensor-Generated Time Series Events: A Definition Language

PubMed Central

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.

Remote Sensing Time Series Product Tool

NASA Technical Reports Server (NTRS)

Predos, Don; Ryan, Robert E.; Ross, Kenton W.

2006-01-01

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced

Increasing zooplankton size diversity enhances the strength of top-down control on phytoplankton through diet niche partitioning.

PubMed

Ye, Lin; Chang, Chun-Yi; García-Comas, Carmen; Gong, Gwo-Ching; Hsieh, Chih-Hao

2013-09-01

1. The biodiversity-ecosystem functioning debate is a central topic in ecology. Recently, there has been a growing interest in size diversity because body size is sensitive to environmental changes and is one of the fundamental characteristics of organisms linking many ecosystem properties. However, how size diversity affects ecosystem functioning is an important yet unclear issue. 2. To fill the gap, with large-scale field data from the East China Sea, we tested the novel hypothesis that increasing zooplankton size diversity enhances top-down control on phytoplankton (H1) and compared it with five conventional hypotheses explaining the top-down control: flatter zooplankton size spectrum enhances the strength of top-down control (H2); nutrient enrichment lessens the strength of top-down control (H3); increasing zooplankton taxonomic diversity enhances the strength of top-down control (H4); increasing fish predation decreases the strength of top-down control of zooplankton on phytoplankton through trophic cascade (H5); increasing temperature intensifies the strength of top-down control (H6). 3. The results of univariate analyses support the hypotheses based on zooplankton size diversity (H1), zooplankton size spectrum (H2), nutrient (H3) and zooplankton taxonomic diversity (H4), but not the hypotheses based on fish predation (H5) and temperature (H6). More in-depth analyses indicate that zooplankton size diversity is the most important factor in determining the strength of top-down control on phytoplankton in the East China Sea. 4. Our results suggest a new potential mechanism that increasing predator size diversity enhances the strength of top-down control on prey through diet niche partitioning. This mechanism can be explained by the optimal predator-prey body-mass ratio concept. Suppose each size group of zooplankton predators has its own optimal phytoplankton prey size, increasing size diversity of zooplankton would promote diet niche partitioning of predators

Extending nonlinear analysis to short ecological time series.

PubMed

Hsieh, Chih-hao; Anderson, Christian; Sugihara, George

2008-01-01

Nonlinearity is important and ubiquitous in ecology. Though detectable in principle, nonlinear behavior is often difficult to characterize, analyze, and incorporate mechanistically into models of ecosystem function. One obvious reason is that quantitative nonlinear analysis tools are data intensive (require long time series), and time series in ecology are generally short. Here we demonstrate a useful method that circumvents data limitation and reduces sampling error by combining ecologically similar multispecies time series into one long time series. With this technique, individual ecological time series containing as few as 20 data points can be mined for such important information as (1) significantly improved forecast ability, (2) the presence and location of nonlinearity, and (3) the effective dimensionality (the number of relevant variables) of an ecological system.

Impact of moderate silver carp biomass gradient on zooplankton communities in a eutrophic reservoir. Consequences for the use of silver carp in biomanipulation.

PubMed

Domaizon, I; Dévaux, J

1999-07-01

We examined the impacts of moderate gradient silver carp biomass (five levels from 0 to 36 g.m-3, i.e. about 0-792 kg.ha-1) on zooplankton communities of the eutrophic Villerest reservoir (France). During our mesocosm experiment changes in zooplankton assemblages were dependent on silver carp biomass. In the fishless and low fish biomass treatments, zooplankton abundance increased through time, owing to a peak in cladoceran density, but decreased (mainly cladocerans) at highest fish biomass. Copepods and rotifers were less affected at the highest fish biomass and dominated zooplankton communities. We highlighted that the presence of high silver carp biomass could lead to changes in phytoplankton assemblage via the impact on herbivorous zooplankton. Since silver carp efficiently graze on particles > 20 microns, the suppression of herbivorous cladocerans could result in an increase in small size algae (< 20 microns) abundance since these species would be released from grazers as well as competitors (large algae grazed by silver carp) and nutrients levels would be enhanced by fish internal loading. Our results showed that the use of low silver carp biomass (< 200 kg.ha-1) would allow us to minimize these negative effects.

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

PubMed

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.

Financial Time-series Analysis: a Brief Overview

NASA Astrophysics Data System (ADS)

Chakraborti, A.; Patriarca, M.; Santhanam, M. S.

Prices of commodities or assets produce what is called time-series. Different kinds of financial time-series have been recorded and studied for decades. Nowadays, all transactions on a financial market are recorded, leading to a huge amount of data available, either for free in the Internet or commercially. Financial time-series analysis is of great interest to practitioners as well as to theoreticians, for making inferences and predictions. Furthermore, the stochastic uncertainties inherent in financial time-series and the theory needed to deal with them make the subject especially interesting not only to economists, but also to statisticians and physicists [1]. While it would be a formidable task to make an exhaustive review on the topic, with this review we try to give a flavor of some of its aspects.

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

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.

Material properties of zooplankton and nekton from the California current

NASA Astrophysics Data System (ADS)

Becker, Kaylyn

This study measured the material properties of zooplankton, Pacific hake (Merluccius productus), Humboldt squid (Dosidicus gigas), and two species of myctophids (Symbolophorus californiensis and Diaphus theta) collected from the California Current ecosystem. The density contrast (g) was measured for euphausiids, decapods (Sergestes similis), amphipods (Primno macropa, Phronima sp., and Hyperiid spp.), siphonophore bracts, chaetognaths, larval fish, crab megalopae, larval squid, and medusae. Morphometric data (length, width, and height) were collected for these taxa. Density contrasts varied within and between zooplankton taxa. The mean and standard deviation for euphausiid density contrast were 1.059 +/- 0.009. Relationships between zooplankton density contrast and morphometric measurements, geographic location, and environmental conditions were investigated. Site had a significant effect on euphausiid density contrast. Density contrasts of euphausiids collected in the same geographic area approximately 4-10 days apart were significantly higher (p < 0.001). Sound speed contrast (h) was measured for euphausiids and pelagic decapods (S. similis) and it varied between taxa. The mean and standard deviation for euphausiid sound speed were 1.019 +/- 0.009. Euphausiid mass was calculated from density measurements and volume, and a relationship between euphausiid mass and length was produced. We determined that euphausiid from volumes could be accurately estimated two dimensional measurements of animal body shape, and that biomass (or biovolume) could be accurately calculated from digital photographs of animals. Density contrast (g) was measured for zooplankton, pieces of hake flesh, myctophid flesh, and of the following Humboldt squid body parts: mantle, arms, tentacle, braincase, eyes, pen, and beak. The density contrasts varied within and between fish taxa, as well as among squid body parts. Effects of animal length and environmental conditions on nekton density

Estimation of coupling between time-delay systems from time series

NASA Astrophysics Data System (ADS)

Prokhorov, M. D.; Ponomarenko, V. I.

2005-07-01

We propose a method for estimation of coupling between the systems governed by scalar time-delay differential equations of the Mackey-Glass type from the observed time series data. The method allows one to detect the presence of certain types of linear coupling between two time-delay systems, to define the type, strength, and direction of coupling, and to recover the model equations of coupled time-delay systems from chaotic time series corrupted by noise. We verify our method using both numerical and experimental data.

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

PubMed

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.

Time Series Model Identification and Prediction Variance Horizon.

DTIC Science & Technology

1980-06-01

stationary time series Y(t). -6- In terms of p(v), the definition of the three time series memory types is: No Memory Short Memory Long Memory X IP (v)I 0 0...X lp(v)l < - I IP (v) = v=1 v=l v=l Within short memory time series there are three types whose classification in terms of correlation functions is...1974) "Some Recent Advances in Time Series Modeling", TEEE Transactions on Automatic ControZ, VoZ . AC-19, No. 6, December, 723-730. Parzen, E. (1976) "An

Time series smoother for effect detection.

PubMed

You, Cheng; Lin, Dennis K J; Young, S Stanley

2018-01-01

In environmental epidemiology, it is often encountered that multiple time series data with a long-term trend, including seasonality, cannot be fully adjusted by the observed covariates. The long-term trend is difficult to separate from abnormal short-term signals of interest. This paper addresses how to estimate the long-term trend in order to recover short-term signals. Our case study demonstrates that the current spline smoothing methods can result in significant positive and negative cross-correlations from the same dataset, depending on how the smoothing parameters are chosen. To circumvent this dilemma, three classes of time series smoothers are proposed to detrend time series data. These smoothers do not require fine tuning of parameters and can be applied to recover short-term signals. The properties of these smoothers are shown with both a case study using a factorial design and a simulation study using datasets generated from the original dataset. General guidelines are provided on how to discover short-term signals from time series with a long-term trend. The benefit of this research is that a problem is identified and characteristics of possible solutions are determined.

Time series smoother for effect detection

PubMed Central

Lin, Dennis K. J.; Young, S. Stanley

2018-01-01

In environmental epidemiology, it is often encountered that multiple time series data with a long-term trend, including seasonality, cannot be fully adjusted by the observed covariates. The long-term trend is difficult to separate from abnormal short-term signals of interest. This paper addresses how to estimate the long-term trend in order to recover short-term signals. Our case study demonstrates that the current spline smoothing methods can result in significant positive and negative cross-correlations from the same dataset, depending on how the smoothing parameters are chosen. To circumvent this dilemma, three classes of time series smoothers are proposed to detrend time series data. These smoothers do not require fine tuning of parameters and can be applied to recover short-term signals. The properties of these smoothers are shown with both a case study using a factorial design and a simulation study using datasets generated from the original dataset. General guidelines are provided on how to discover short-term signals from time series with a long-term trend. The benefit of this research is that a problem is identified and characteristics of possible solutions are determined. PMID:29684033

Fate of thiamethoxam in mesocosms and response of the zooplankton community.

PubMed

Lobson, C; Luong, K; Seburn, D; White, M; Hann, B; Prosser, R S; Wong, C S; Hanson, M L

2018-05-14

Thiamethoxam is a neonicotinoid insecticide that can reach wetlands in agro-ecosystems through runoff. The fate and effects of thiamethoxam on non-target organisms in shallow wetland ecosystems have not been well characterized. To this end, a mesocosm study was conducted with a focus on characterizing zooplankton community responses. A single pulse application of thiamethoxam (0, 25, 50, 100, 250, and 500 μg/L; n = 3) was applied to experimental systems and monitored for 8 weeks. The mean half-life of thiamethoxam among the different treatments was 3.7 days in the water column with concentrations of <0.8 μg/L in the majority of mesocosms by 56 days. Principal response curve analysis did not show any significant concentration-dependent differences in the zooplankton community among treatments over the course of the study. The minimum detectable difference (MDD%) values for abundance of potentially sensitive arthropod taxa (nauplius larvae, cyclopoid copepods) allowed the detections from controls as low as 42 and 59% effect, respectively. The MDD% values for total abundance of zooplankton (including the potentially less sensitive taxonomic group of Rotifera) allowed the detection from controls as low as 41% effect. There were no statistically significant differences in zooplankton abundance or diversity between control and treated mesocosms at the end of the study. There were also no statistically significant differences for individual taxa that were sustained between sampling points, or manifested as a concentration-response. We conclude that acute exposure to thiamethoxam at environmentally relevant concentrations (typically ng/L) likely does not represent a significant adverse ecological risk to wetland zooplankton community abundance and structure. Copyright © 2018 Elsevier B.V. All rights reserved.

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

USGS Publications Warehouse

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, <1–83%). The changes in the zooplankton community are consistent with a top-down effect of planktivory by American Shad associated with their unprecedented biomass and consumption, but the effects are likely constrained by temperature, nutrient flux, and the seasonal production patterns of zooplankton in John Day Reservoir. American Shad add to the planktivory exerted by other species like Neomysis mercedis to reduce the capacity of the reservoir to support other planktivorous fishes. The introduction of American Shad and other nonnative species will continue to alter the food web in John Day Reservoir, potentially affecting native fishes, including Pacific salmon Oncorhynchus spp.

Time series modeling in traffic safety research.

PubMed

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.

Multifrequency acoustic observations of zooplankton in Knight Inlet, B.C

NASA Astrophysics Data System (ADS)

Trevorrow, Mark V.; Mackas, David L.; Benfield, Mark C.

2004-05-01

A collaborative investigation of midwater zooplankton aggregations in a coastal fjord was conducted in November 2002. Midwater aggregations of zooplankton in a coastal fjord were sampled and mapped using a calibrated, three-frequency (38, 120, and 200 kHz) vessel-based echo-sounder system, a multinet towed zooplankton net (BIONESS), and a high-resolution in situ camera system (ZOOVIS). Dense daytime layers of euphausiids and amphipods near 70- to 90-m depth were found in the lower reaches of the inlet, especially concentrated by tidal flows around a sill which rises above the layer. Quantitative euphausiid and amphipod backscattering measurements, combined with in situ species, size, and abundance estimates, were found to agree closely with recent size- and orientation-averaged fluid-cylinder scattering models produced by Stanton et al. Also, in situ scattering measurements of physonect siphonophores were found to have a much stronger low-frequency (38 kHz) scattering strength, in agreement with a simple bubble scattering model. [Work supported by Dr. J. Eckman, ONR code 322BC.

Size and species diversity of zooplankton communities in fluctuating Mediterranean salt marshes

NASA Astrophysics Data System (ADS)

Brucet, Sandra; Boix, Dani; López-Flores, Rocío; Badosa, Anna; Quintana, Xavier D.

2006-04-01

Differences in size and species diversity were analysed in a zooplankton community of a Mediterranean salt marsh (Empordà wetlands, NE Iberian Peninsula), where the dominance of a single species was frequent. In the permanent salt marsh, species diversity and size diversity had similar patterns along zooplankton succession. In the temporary salt marsh species diversity was high after flooding and diminished once water inputs ceased. As species diversity declined size diversity increased. Eventually, one species of calanoid dominated the zooplankton community. The high size diversity in situations of calanoid dominance was possibly due to the co-occurrence of different developmental stages, each of which have different diets. Size diversity would thus indicate trophic niche segregation among different sizes. The combined use of species and size diversity values allows the identification of the successional phases.

Time series of the northeast Pacific

NASA Astrophysics Data System (ADS)

Peña, M. Angelica; Bograd, Steven J.

2007-10-01

In July 2006, the North Pacific Marine Science Organization (PICES) and Fisheries & Oceans Canada sponsored the symposium “Time Series of the Northeast Pacific: A symposium to mark the 50th anniversary of Line P”. The symposium, which celebrated 50 years of oceanography along Line P and at Ocean Station Papa (OSP), explored the scientific value of the Line P and other long oceanographic time series of the northeast Pacific (NEP). Overviews of the principal NEP time-series were presented, which facilitated regional comparisons and promoted interaction and exchange of information among investigators working in the NEP. More than 80 scientists from 8 countries attended the symposium. This introductory essay is a brief overview of the symposium and the 10 papers that were selected for this special issue of Progress in Oceanography.

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

NASA Astrophysics Data System (ADS)

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.

Acoustic Scattering Classification of Zooplankton and Microstructure

DTIC Science & Technology

2001-09-30

As part of this investigation, we have been observing concentrations of siphonulae, a larval form of the gas-bearing zooplankton siphonophore . The...situ measurements of acoustic target strengths of siphonophores , a gas-bearing zooplankter,” ICES J. Mar. Sci. 58: 740-749. Warren, J.D., T.K

Aging of microplastics promotes their ingestion by marine zooplankton.

PubMed

Vroom, Renske J E; Koelmans, Albert A; Besseling, Ellen; Halsband, Claudia

2017-12-01

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 weathering and biofouling alter the characteristics of plastic particles in the marine environment. We investigated zooplankton ingestion of polystyrene beads (15 and 30 μm) and fragments (≤30 μm), and tested the hypothesis that microplastics previously exposed to marine conditions (aged) are ingested at higher rates than pristine microplastics. Polystyrene beads were aged by soaking in natural local seawater for three weeks. Three zooplankton taxa ingested microplastics, excluding the copepod Pseudocalanus spp., but the proportions of individuals ingesting plastic and the number of particles ingested were taxon and life stage specific and dependent on plastic size. All stages of Calanus finmarchicus ingested polystyrene fragments. Aged microbeads were preferred over pristine ones by females of Acartia longiremis as well as juvenile copepodites CV and adults of Calanus finmarchicus. The preference for aged microplastics may be attributed to the formation of a biofilm. Such a coating, made up of natural microbes, may contain similar prey as the copepods feed on in the water column and secrete chemical exudates that aid chemodetection and thus increase the attractiveness of the particles as food items. Much of the ingested plastic was, however, egested within a short time period (2-4 h) and the survival of adult Calanus females was not affected in an 11-day exposure. Negative effects of microplastics ingestion were thus limited. Our findings emphasize, however, that aging plays an important role in the transformation of microplastics at sea and ingestion by grazers, and should thus be considered in future microplastics ingestion studies and estimates of microplastics

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

PubMed

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.

Nonlinear parametric model for Granger causality of time series

NASA Astrophysics Data System (ADS)

Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

2006-06-01

The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.

Pearson correlation estimation for irregularly sampled time series

NASA Astrophysics Data System (ADS)

Rehfeld, K.; Marwan, N.; Heitzig, J.; Kurths, J.

2012-04-01

Many applications in the geosciences call for the joint and objective analysis of irregular time series. For automated processing, robust measures of linear and nonlinear association are needed. Up to now, the standard approach would have been to reconstruct the time series on a regular grid, using linear or spline interpolation. Interpolation, however, comes with systematic side-effects, as it increases the auto-correlation in the time series. We have searched for the best method to estimate Pearson correlation for irregular time series, i.e. the one with the lowest estimation bias and variance. We adapted a kernel-based approach, using Gaussian weights. Pearson correlation is calculated, in principle, as a mean over products of previously centralized observations. In the regularly sampled case, observations in both time series were observed at the same time and thus the allocation of measurement values into pairs of products is straightforward. In the irregularly sampled case, however, measurements were not necessarily observed at the same time. Now, the key idea of the kernel-based method is to calculate weighted means of products, with the weight depending on the time separation between the observations. If the lagged correlation function is desired, the weights depend on the absolute difference between observation time separation and the estimation lag. To assess the applicability of the approach we used extensive simulations to determine the extent of interpolation side-effects with increasing irregularity of time series. We compared different approaches, based on (linear) interpolation, the Lomb-Scargle Fourier Transform, the sinc kernel and the Gaussian kernel. We investigated the role of kernel bandwidth and signal-to-noise ratio in the simulations. We found that the Gaussian kernel approach offers significant advantages and low Root-Mean Square Errors for regular, slightly irregular and very irregular time series. We therefore conclude that it is a good

Zooplankton Distribution in Four Western Norwegian Fjords

NASA Astrophysics Data System (ADS)

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.

Characterizing time series via complexity-entropy curves

NASA Astrophysics Data System (ADS)

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

NASA Astrophysics Data System (ADS)

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.

Analysis of Nonstationary Time Series for Biological Rhythms Research.

PubMed

Leise, Tanya L

2017-06-01

This article is part of a Journal of Biological Rhythms series exploring analysis and statistics topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article on time series analysis for biological rhythms, we describe some methods for assessing the rhythmic properties of time series, including tests of whether a time series is indeed rhythmic. Because biological rhythms can exhibit significant fluctuations in their period, phase, and amplitude, their analysis may require methods appropriate for nonstationary time series, such as wavelet transforms, which can measure how these rhythmic parameters change over time. We illustrate these methods using simulated and real time series.

Forbidden patterns in financial time series

NASA Astrophysics Data System (ADS)

Zanin, Massimiliano

2008-03-01

The existence of forbidden patterns, i.e., certain missing sequences in a given time series, is a recently proposed instrument of potential application in the study of time series. Forbidden patterns are related to the permutation entropy, which has the basic properties of classic chaos indicators, such as Lyapunov exponent or Kolmogorov entropy, thus allowing to separate deterministic (usually chaotic) from random series; however, it requires fewer values of the series to be calculated, and it is suitable for using with small datasets. In this paper, the appearance of forbidden patterns is studied in different economical indicators such as stock indices (Dow Jones Industrial Average and Nasdaq Composite), NYSE stocks (IBM and Boeing), and others (ten year Bond interest rate), to find evidence of deterministic behavior in their evolutions. Moreover, the rate of appearance of the forbidden patterns is calculated, and some considerations about the underlying dynamics are suggested.

Complex network approach to fractional time series

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manshour, Pouya

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 adjacencymore » 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.« less

Advanced spectral methods for climatic time series

USGS Publications Warehouse

Ghil, M.; Allen, M.R.; Dettinger, M.D.; Ide, K.; Kondrashov, D.; Mann, M.E.; Robertson, A.W.; Saunders, A.; Tian, Y.; Varadi, F.; Yiou, P.

2002-01-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal- to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

Role of predation by zooplankton in transport and fate of protozoan (oo)cysts in granular activated carbon filtration.

PubMed

Bichai, Françoise; Barbeau, Benoit; Dullemont, Yolanda; Hijnen, Wim

2010-02-01

The significance of zooplankton in the transport and fate of pathogenic organisms in drinking water is poorly understood, although many hints of the role of predation in the persistence of microorganisms through water treatment processes can be found in literature. The objective of this study was to assess the impact of predation by natural zooplankton on the transport and fate of protozoan (oo)cysts in granular activated carbon (GAC) filtration process. UV-irradiated unlabelled Cryptosporidium parvum and Giardia lamblia (oo)cysts were seeded into two pilot-scale GAC filtration columns operated under full-scale conditions. In a two-week period after seeding, a reduction of free (oo)cysts retained in the filter bed was observed. Zooplankton was isolated from the filter bed and effluent water on a 30 microm net before and during the two-week period after seeding; it was enumerated and identified. Rotifers, which are potential predators of (oo)cysts, accounted for the major part of the isolated zooplankton. Analytical methods were developed to detect (oo)cysts internalized in natural zooplankton isolated from the filter bed and effluent water. Sample sonication was optimized to disrupt zooplankton organisms and release internalized microorganisms. (Oo)cysts released from zooplankton after sonication were isolated by IMS and stained (EasyStain) for microscopic counting. Both Cryptosporidium and Giardia (oo)cysts were detected in association with zooplankton in the filter bed samples as well as in the effluent of GAC filters. The results of this study suggest that predation by zooplankton can play a role in the remobilization of persistent pathogens such as Cryptosporidium and Giardia (oo)cysts retained in GAC filter beds, and consequently in the transmission of these pathogens in drinking water. Copyright 2009 Elsevier Ltd. All rights reserved.

Degree-Pruning Dynamic Programming Approaches to Central Time Series Minimizing Dynamic Time Warping Distance.

PubMed

Sun, Tao; Liu, Hongbo; Yu, Hong; Chen, C L Philip

2016-06-28

The central time series crystallizes the common patterns of the set it represents. In this paper, we propose a global constrained degree-pruning dynamic programming (g(dp)²) approach to obtain the central time series through minimizing dynamic time warping (DTW) distance between two time series. The DTW matching path theory with global constraints is proved theoretically for our degree-pruning strategy, which is helpful to reduce the time complexity and computational cost. Our approach can achieve the optimal solution between two time series. An approximate method to the central time series of multiple time series [called as m_g(dp)²] is presented based on DTW barycenter averaging and our g(dp)² approach by considering hierarchically merging strategy. As illustrated by the experimental results, our approaches provide better within-group sum of squares and robustness than other relevant algorithms.

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

PubMed

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

PubMed Central

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

Stochastic nature of series of waiting times.

PubMed

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H; Salehi, E; Behjat, E; Qorbani, M; Nezhad, M Khazaei; 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.

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

NASA Astrophysics Data System (ADS)

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

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

NASA Astrophysics Data System (ADS)

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

Vertical redistribution of zooplankton in an oligotrophic lake associated with reduction in ultraviolet radiation by wildfire smoke

NASA Astrophysics Data System (ADS)

Urmy, Samuel S.; Williamson, Craig E.; Leach, Taylor H.; Schladow, S. Geoffrey; Overholt, Erin P.; Warren, Joseph D.

2016-04-01

We used a natural experiment to test whether wildfire smoke induced changes in the vertical distribution of zooplankton in Lake Tahoe by decreasing incident ultraviolet radiation (UV). Fires have a variety of effects on aquatic ecosystems, but these impacts are poorly understood and have rarely been observed directly. UV is an important driver of zooplankton vertical migration, and wildfires may alter it over large spatial scales. We measured UV irradiance and the distribution of zooplankton on two successive days. On one day, smoke haze from a nearby wildfire reduced incident UV radiation by up to 9%, but not irradiance in the visible spectrum. Zooplankton responded by positioning themselves, on average, 4.1 m shallower in the lake. While a limited data set such as this requires cautious interpretation, our results suggest that smoke from wildfires can change the UV environment and distribution of zooplankton. This process may be important in drought-prone regions with increasingly frequent wildfires, and globally due to widespread biomass burning.

SPATIAL PATTERNS IN ASSEMBLAGE STRUCTURES OF PELAGIC FORAGE FISH AND ZOOPLANKTON IN WESTERN LAKE SUPERIOR

EPA Science Inventory

This manuscript reports on the spatial distribution of zooplankton and forage fish in western Lake Superior. Fish and zooplankton assemblages are shown to differ substantially in abundance and size structure both between the open lake and nearshore regions and between two differe...

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Species Composition and Distribution of Zooplankton from Northeastern Sakhalin Shelf (Sea of Okhotsk)

NASA Astrophysics Data System (ADS)

Kasyan, V. V.

2018-03-01

The species composition, density, biomass, and distribution of zooplankton of the northeastern Sakhalin shelf, Sea of Okhotsk (Chaivo, Pil'tunskii, and Morskoi regions) were studied in October 2014. Zooplankton was represented by 15 taxonomic groups, which were dominated by Copepoda (13 species). The average density and biomass was highest in the Chaivo region (14112 ± 4322 ind./m3, 395 ± 107 mg/m3) and in the Pil'tunskii region (16692 ± 10707 ind./m3, 346 ± 233 mg/m3); the abundance of detected taxonomic groups was minimal (8-12). The average density and biomass of zooplankton was up to 4304 ± 2441 ind./m3, 133 ± 77 mg/m3 in the Morskoi region and increased with depth; the abundance of taxa was maximum (15). Four species of copepods made up the majority of the density and biomass of zooplankton: Acartia hudsonica, Eurytemora herdmani, Pseudocalanus newmani, and Oithona similis. In the Chaivo region, species of the genera Acartia, Eurytemora, and Oithona dominated and subdominated; in Pil'tunskii region, species of the genera Acartia and Oithona dominated and subdominated; and in the Morskoi region, species of the genera Oithona, Pseudocalanus, and Acartia dominated and subdominated.

Ingestion of Microplastics by Zooplankton in the Northeast Pacific Ocean.

PubMed

Desforges, Jean-Pierre W; Galbraith, Moira; Ross, Peter S

2015-10-01

Microplastics are increasingly recognized as being widespread in the world's oceans, but relatively little is known about ingestion by marine biota. In light of the potential for microplastic fibers and fragments to be taken up by small marine organisms, we examined plastic ingestion by two foundation species near the base of North Pacific marine food webs, the calanoid copepod Neocalanus cristatus and the euphausiid Euphausia pacifia. We developed an acid digestion method to assess plastic ingestion by individual zooplankton and detected microplastics in both species. Encounter rates resulting from ingestion were 1 particle/every 34 copepods and 1/every 17 euphausiids (euphausiids > copepods; p = 0.01). Consistent with differences in the size selection of food between these two zooplankton species, the ingested particle size was greater in euphausiids (816 ± 108 μm) than in copepods (556 ± 149 μm) (p = 0.014). The contribution of ingested microplastic fibres to total plastic decreased with distance from shore in euphausiids (r (2) = 70, p = 0.003), corresponding to patterns in our previous observations of microplastics in seawater samples from the same locations. This first evidence of microplastic ingestion by marine zooplankton indicate that species at lower trophic levels of the marine food web are mistaking plastic for food, which raises fundamental questions about potential risks to higher trophic level species. One concern is risk to salmon: We estimate that consumption of microplastic-containing zooplankton will lead to the ingestion of 2-7 microplastic particles/day by individual juvenile salmon in coastal British Columbia, and ≤91 microplastic particles/day in returning adults.

Delay differential analysis of time series.

PubMed

Lainscsek, Claudia; Sejnowski, Terrence J

2015-03-01

Nonlinear dynamical system analysis based on embedding theory has been used for modeling and prediction, but it also has applications to signal detection and classification of time series. An embedding creates a multidimensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The delay embedding is composed of delayed versions of the signal, and the derivative embedding is composed of successive derivatives of the signal. The delay embedding has been extended to nonuniform embeddings to take multiple timescales into account. Both embeddings provide information on the underlying dynamical system without having direct access to all the system variables. Delay differential analysis is based on functional embeddings, a combination of the derivative embedding with nonuniform delay embeddings. Small delay differential equation (DDE) models that best represent relevant dynamic features of time series data are selected from a pool of candidate models for detection or classification. We show that the properties of DDEs support spectral analysis in the time domain where nonlinear correlation functions are used to detect frequencies, frequency and phase couplings, and bispectra. These can be efficiently computed with short time windows and are robust to noise. For frequency analysis, this framework is a multivariate extension of discrete Fourier transform (DFT), and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short or sparse time series and can be extended to cross-trial and cross-channel spectra if multiple short data segments of the same experiment are available. Together, this time-domain toolbox provides higher temporal resolution, increased frequency and phase coupling information, and it allows an easy and straightforward implementation of higher-order spectra across time

GNSS Network time series analysis

NASA Astrophysics Data System (ADS)

Normand, M.; Balodis, J.; Janpaule, I.; Haritonova, D.

2012-12-01

Time series of GNSS station results of both the EUPOS®-Riga and LatPos networks have been developed at the Institute of Geodesy and Geoinformation (University of Latvia) using Bernese v.5.0 software. The base stations were selected among the EPN and IGS stations in surroundings of Latvia at the distances up to 700 km. The results of time series are analysed and coordinate velocity vectors have been determined. The background of the map of tectonic faults helps to interpret the GNSS station coordinate velocity vector behaviour in proper environment. The outlying situations recognized. The question still aroused on the nature of the some of outlying situations. The dependence from various influences has been tested.

Zooplankton community response to the winter 2013 deep convection process in the NW Mediterranean Sea

NASA Astrophysics Data System (ADS)

Donoso, Katty; Carlotti, François; Pagano, Marc; Hunt, Brian P. V.; Escribano, Rubén.; Berline, Léo.

2017-03-01

The Gulf of Lion is an important area of deep convection, where intense winter vertical mixing brings nutrients up from deeper layers, promoting the largest bloom in the Mediterranean at the end of winter/early spring. The DEWEX program conducted cruises in February and April 2013 to investigate the ecosystem level impacts of deep water convection. Zooplankton data were collected through net sampling and imaging with an Underwater Vision Profiler. In winter, low zooplankton abundance and biomass were observed in the Deep Convection Zone (DCZ) and higher values on its periphery. In spring, this pattern reversed with high biomass in the DCZ and lower values on the periphery. On average for the whole area, the potential grazing impact was estimated to increase by one order of magnitude from winter to spring. In April, all areas except the DCZ incurred top-down control by zooplankton on the phytoplankton stock. In the DCZ, the chlorophyll-a values remained high despite the high zooplankton biomass and carbon demand, indicating a sustained bottom-up control. The zooplankton community composition was comparable for both periods, typified by high copepod dominance, but with some differences between the DCZ and peripheral regions. In spring the DCZ was characterized by a strong increase in herbivorous species such as Centropages typicus and Calanus helgolandicus, and an increase in the number of large zooplankton individuals. Our study indicates that the DCZ is likely an area of both enhanced energy transfer to higher trophic levels and organic matter export in the North Western Mediterranean Sea.

River flow, zooplankton and dominant zooplanktivorous fish dynamics in a warm-temperate South African estuary.

PubMed

Mbandzi, N; Wasserman, R J; Deyzel, S H P; Vine, N G; Whitfield, A K

2018-06-01

The possible links between river flow, zooplankton abundance and the responses of zooplanktivorous fishes to physico-chemical and food resource changes are assessed. To this end, the seasonal abundance, distribution and diet of the estuarine round-herring Gilchristella aestuaria and Cape silverside Atherina breviceps were studied in the Kariega Estuary. Spatio-temporal differences were determined for selected physico-chemical variables, zooplankton abundance and zooplanktivorous fish abundance and distribution. Results indicated that, following a river flood event in winter (>30 m 3  s -1 ), altered physico-chemical conditions occurred throughout the estuary and depressed zooplankton stocks. Abundance of G. aestuaria was highest in spring, with this species dominant in the upper and middle zones of the estuary, while A. breviceps was dominant in summer and preferred the middle and lower zones. The catch per unit of effort of both zooplanktivores also declined significantly following the flooding, thus suggesting that these fishes are reliant on zooplankton as a primary food source for healthy populations. Copepods dominated the stomach contents of both fish species, indicating a potential for strong interspecific competition for food, particularly in the middle reaches. Temporal differences were evident in dietary overlap between the two zooplanktivorous fish species and were correlated with river flow, zooplankton availability and fish distribution. The findings of this study emphasize the close trophic linkages between zooplankton and zooplanktivorous fishes under changing estuarine environmental conditions, particularly river flow and provide important baseline information for similar studies elsewhere in South Africa and the rest of the world. © 2018 The Fisheries Society of the British Isles.

Stochastic nature of series of waiting times

NASA Astrophysics Data System (ADS)

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.

Characterizing artifacts in RR stress test time series.

PubMed

Astudillo-Salinas, Fabian; Palacio-Baus, Kenneth; Solano-Quinde, Lizandro; Medina, Ruben; Wong, Sara

2016-08-01

Electrocardiographic stress test records have a lot of artifacts. In this paper we explore a simple method to characterize the amount of artifacts present in unprocessed RR stress test time series. Four time series classes were defined: Very good lead, Good lead, Low quality lead and Useless lead. 65 ECG, 8 lead, records of stress test series were analyzed. Firstly, RR-time series were annotated by two experts. The automatic methodology is based on dividing the RR-time series in non-overlapping windows. Each window is marked as noisy whenever it exceeds an established standard deviation threshold (SDT). Series are classified according to the percentage of windows that exceeds a given value, based upon the first manual annotation. Different SDT were explored. Results show that SDT close to 20% (as a percentage of the mean) provides the best results. The coincidence between annotators classification is 70.77% whereas, the coincidence between the second annotator and the automatic method providing the best matches is larger than 63%. Leads classified as Very good leads and Good leads could be combined to improve automatic heartbeat labeling.

Coupling between populations of copepod taxa within an estuarine ecosystem and the adjacent offshore regions

NASA Astrophysics Data System (ADS)

McGinty, N.; Johnson, M. P.; Power, A. M.

2012-07-01

Population dynamics in open systems are complicated by the interactions of local demography and local environmental forcing with processes occurring at larger scales. A local system such as an estuary or bay may contain a zooplankton population that effectively becomes independent of regional dynamics or the local dynamics may be closely coupled to a broader scale pattern. As an alternative, the details of migration and advection may mean that dynamics in a local system are coupled to other specific areas rather than tracking the overall dynamics at a larger scale. We used a reconstructed time series (1973-1987) for copepod taxa to examine the extent to which zooplankton dynamics in Galway Bay reflect processes in broader areas of the NE Atlantic. Continuous Plankton Recorder (CPR) counts were used to establish time series for nine offshore ecoregions, with the regions themselves defined using underlying patterns of chlorophyll variability. The open nature of Galway Bay was reflected in strong associations between bay zooplankton counts and offshore CPR data in a majority of cases (7/10). For each zooplankton taxon, there were large differences among regions in the degree of association with Galway Bay time series. Akaike weights indicated that one ecoregion tended to be the dominant link for each taxon. This indicates that the zooplankton of the Bay reflect more than the local modification of a regional signal and that different zooplankton in the bay may have separate source regions. The data from Galway Bay also fall within a 'sampling shadow' of the CPR. Later years of the time series showed evidence for changes in phenology, with spring zooplankton peaks generally occurring earlier in the year for smaller species.

Changes to the hydrography and zooplankton in the northern California Current in response to `the Blob'of 2014-2015

NASA Astrophysics Data System (ADS)

Peterson, W. T.

2016-02-01

Fortnightly measurements of hydrography and zooplankton species composition have been sustained along the Newport Hydrographic line since 1996. From this 20 year time series we have established that zooplankton abundance and species composition closely tracks the phase of the Pacific Decadal Oscillation and the El Nino Southern Oscillation. During positive (warm) phase of the PDO, a warm water `southern' subtropical coastal community is found whereas during negative (cold) phase a cold water `northern'coastal community dominates. The Blob though was a rule-changer. The Blob began to move slowly ashore at Newport on 14 September 2014 with the seasonal relaxation of upwelling, and within 5 h SST increased 6°C to 19.4°C. On the 25 and 30 September cruises, copepod species richness increased as well, with an anomaly of 2 and 9 species respectively, greater than the 20 year climatology for September. We continued to monitor the plankton throughout the autumn 2014 and winter, spring and summer 2015 and found a total of seventeen copepod species that were either new to Oregon or have occurred only rarely in the past. Many of these species are oceanic with sub-tropical or tropical affinities thus are indicators of tropical waters, suggesting that the Blob water which came ashore in central Oregon had its origins offshore rather than from coastal waters to the south. Some of the copepod species that were new or rarely seen included Subeucalanus crassus, Eucalanus hyalinus, Mecynocera clausi, Calocalanus pavo, Centropages bradyii, and Pleuromamma borealis and P. xiphias. Krill biomass was the lowest in our 20 year time series. The southern California Current neritic krill species Nyctiphanes simplex appears off Oregon during major El Niño events (1983, 1998), but none were seen during The Blob event which again suggests that the origin of the Blob water which appeared off Oregon was from far offshore, not from coastal waters to the south. Note in the figure below that

A meta-analysis of zooplankton functional traits influencing ecosystem function.

PubMed

Hébert, Marie-Pier; Beisner, Beatrix E; Maranger, Roxane

2016-04-01

The use of functional traits to characterize community composition has been proposed as a more effective way to link community structure to ecosystem functioning. Organismal morphology, body stoichiometry, and physiology can be readily linked to large-scale ecosystem processes through functional traits that inform on interspecific and species-environment interactions; yet such effect traits are still poorly included in trait-based approaches. Given their key trophic position in aquatic ecosystems, individual zooplankton affect energy fluxes and elemental processing. We compiled a large database of zooplankton traits contributing to carbon, nitrogen, and phosphorus cycling and examined the effect of classification and habitat (marine vs. freshwater) on trait relationships. Respiration and nutrient excretion rates followed mass-dependent scaling in both habitats, with exponents ranging from 0.70 to 0.90. Our analyses revealed surprising differences in allometry and respiration between habitats, with freshwater species having lower length-specific mass and three times higher mass-specific respiration rates. These differences in traits point to implications for ecological strategies as well as overall carbon storage and fluxes based on habitat type. Our synthesis quantifies multiple trait relationships and links organisms to ecosystem processes they influence, enabling a more complete integration of aquatic community ecology and biogeochemistry through the promising use of effect traits.

A novel weight determination method for time series data aggregation

NASA Astrophysics Data System (ADS)

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.

Time series, periodograms, and significance

NASA Astrophysics Data System (ADS)

Hernandez, G.

1999-05-01

The geophysical literature shows a wide and conflicting usage of methods employed to extract meaningful information on coherent oscillations from measurements. This makes it difficult, if not impossible, to relate the findings reported by different authors. Therefore, we have undertaken a critical investigation of the tests and methodology used for determining the presence of statistically significant coherent oscillations in periodograms derived from time series. Statistical significance tests are only valid when performed on the independent frequencies present in a measurement. Both the number of possible independent frequencies in a periodogram and the significance tests are determined by the number of degrees of freedom, which is the number of true independent measurements, present in the time series, rather than the number of sample points in the measurement. The number of degrees of freedom is an intrinsic property of the data, and it must be determined from the serial coherence of the time series. As part of this investigation, a detailed study has been performed which clearly illustrates the deleterious effects that the apparently innocent and commonly used processes of filtering, de-trending, and tapering of data have on periodogram analysis and the consequent difficulties in the interpretation of the statistical significance thus derived. For the sake of clarity, a specific example of actual field measurements containing unevenly-spaced measurements, gaps, etc., as well as synthetic examples, have been used to illustrate the periodogram approach, and pitfalls, leading to the (statistical) significance tests for the presence of coherent oscillations. Among the insights of this investigation are: (1) the concept of a time series being (statistically) band limited by its own serial coherence and thus having a critical sampling rate which defines one of the necessary requirements for the proper statistical design of an experiment; (2) the design of a critical

Entropy of electromyography time series

NASA Astrophysics Data System (ADS)

Kaufman, Miron; Zurcher, Ulrich; Sung, Paul S.

2007-12-01

A nonlinear analysis based on Renyi entropy is applied to electromyography (EMG) time series from back muscles. The time dependence of the entropy of the EMG signal exhibits a crossover from a subdiffusive regime at short times to a plateau at longer times. We argue that this behavior characterizes complex biological systems. The plateau value of the entropy can be used to differentiate between healthy and low back pain individuals.

Recurrent Neural Network Applications for Astronomical Time Series

NASA Astrophysics Data System (ADS)

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.

Visualizing frequent patterns in large multivariate time series

NASA Astrophysics Data System (ADS)

Hao, M.; Marwah, M.; Janetzko, H.; Sharma, R.; Keim, D. A.; Dayal, U.; Patnaik, D.; Ramakrishnan, N.

2011-01-01

The detection of previously unknown, frequently occurring patterns in time series, often called motifs, has been recognized as an important task. However, it is difficult to discover and visualize these motifs as their numbers increase, especially in large multivariate time series. To find frequent motifs, we use several temporal data mining and event encoding techniques to cluster and convert a multivariate time series to a sequence of events. Then we quantify the efficiency of the discovered motifs by linking them with a performance metric. To visualize frequent patterns in a large time series with potentially hundreds of nested motifs on a single display, we introduce three novel visual analytics methods: (1) motif layout, using colored rectangles for visualizing the occurrences and hierarchical relationships of motifs in a multivariate time series, (2) motif distortion, for enlarging or shrinking motifs as appropriate for easy analysis and (3) motif merging, to combine a number of identical adjacent motif instances without cluttering the display. Analysts can interactively optimize the degree of distortion and merging to get the best possible view. A specific motif (e.g., the most efficient or least efficient motif) can be quickly detected from a large time series for further investigation. We have applied these methods to two real-world data sets: data center cooling and oil well production. The results provide important new insights into the recurring patterns.

Robust extrema features for time-series data analysis.

PubMed

Vemulapalli, Pramod K; Monga, Vishal; Brennan, Sean N

2013-06-01

The extraction of robust features for comparing and analyzing time series is a fundamentally important problem. Research efforts in this area encompass dimensionality reduction using popular signal analysis tools such as the discrete Fourier and wavelet transforms, various distance metrics, and the extraction of interest points from time series. Recently, extrema features for analysis of time-series data have assumed increasing significance because of their natural robustness under a variety of practical distortions, their economy of representation, and their computational benefits. Invariably, the process of encoding extrema features is preceded by filtering of the time series with an intuitively motivated filter (e.g., for smoothing), and subsequent thresholding to identify robust extrema. We define the properties of robustness, uniqueness, and cardinality as a means to identify the design choices available in each step of the feature generation process. Unlike existing methods, which utilize filters "inspired" from either domain knowledge or intuition, we explicitly optimize the filter based on training time series to optimize robustness of the extracted extrema features. We demonstrate further that the underlying filter optimization problem reduces to an eigenvalue problem and has a tractable solution. An encoding technique that enhances control over cardinality and uniqueness is also presented. Experimental results obtained for the problem of time series subsequence matching establish the merits of the proposed algorithm.

Experimental whole-lake increase of dissolved organic carbon concentration produces unexpected increase in crustacean zooplankton density

USGS Publications Warehouse

Kelly, Patrick T.; Craig, Nicola; Solomon, Christopher T.; Weidel, Brian C.; Zwart, Jacob A.; Jones, Stuart E.

2016-01-01

The observed pattern of lake browning, or increased terrestrial dissolved organic carbon (DOC) concentration, across the northern hemisphere has amplified the importance of understanding how consumer productivity varies with DOC concentration. Results from comparative studies suggest these increased DOC concentrations may reduce crustacean zooplankton productivity due to reductions in resource quality and volume of suitable habitat. Although these spatial comparisons provide an expectation for the response of zooplankton productivity as DOC concentration increases, we still have an incomplete understanding of how zooplankton respond to temporal increases in DOC concentration within a single system. As such, we used a whole-lake manipulation, in which DOC concentration was increased from 8 to 11 mg L−1 in one basin of a manipulated lake, to test the hypothesis that crustacean zooplankton production should subsequently decrease. In contrast to the spatially derived expectation of sharp DOC-mediated decline, we observed a small increase in zooplankton densities in response to our experimental increase in DOC concentration of the treatment basin. This was due to significant increases in gross primary production and resource quality (lower seston carbon-to-phosphorus ratio; C:P). These results demonstrate that temporal changes in lake characteristics due to increased DOC may impact zooplankton in ways that differ from those observed in spatial surveys. We also identified significant interannual variability across our study region, which highlights potential difficulty in detecting temporal responses of organism abundances to gradual environmental change (e.g., browning).

Analysis and generation of groundwater concentration time series

NASA Astrophysics Data System (ADS)

Crăciun, Maria; Vamoş, Călin; Suciu, Nicolae

2018-01-01

Concentration time series are provided by simulated concentrations of a nonreactive solute transported in groundwater, integrated over the transverse direction of a two-dimensional computational domain and recorded at the plume center of mass. The analysis of a statistical ensemble of time series reveals subtle features that are not captured by the first two moments which characterize the approximate Gaussian distribution of the two-dimensional concentration fields. The concentration time series exhibit a complex preasymptotic behavior driven by a nonstationary trend and correlated fluctuations with time-variable amplitude. Time series with almost the same statistics are generated by successively adding to a time-dependent trend a sum of linear regression terms, accounting for correlations between fluctuations around the trend and their increments in time, and terms of an amplitude modulated autoregressive noise of order one with time-varying parameter. The algorithm generalizes mixing models used in probability density function approaches. The well-known interaction by exchange with the mean mixing model is a special case consisting of a linear regression with constant coefficients.

Transition Icons for Time-Series Visualization and Exploratory Analysis.

PubMed

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.

Multiscale structure of time series revealed by the monotony spectrum.

PubMed

Vamoş, Călin

2017-03-01

Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.

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

PubMed

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.

Data imputation analysis for Cosmic Rays time series

NASA Astrophysics Data System (ADS)

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.

Algorithm for Compressing Time-Series Data

NASA Technical Reports Server (NTRS)

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

USGS Publications Warehouse

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.

Layered Ensemble Architecture for Time Series Forecasting.

PubMed

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.

Time series regression studies in environmental epidemiology.

PubMed

Bhaskaran, Krishnan; Gasparrini, Antonio; Hajat, Shakoor; Smeeth, Liam; Armstrong, Ben

2013-08-01

Time series regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of time series data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in time series regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed ('lagged') associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model.

Roles of predation, food, and temperature in structuring the epilimnetic zooplankton populations in Lake Ontario, 1981-1986

USGS Publications Warehouse

Johannsson, Ora E.; O'Gorman, Robert

1991-01-01

We sampled phytoplankton, zooplankton, and alewives Alosa pseudoharengus and measured water temperature in Lake Ontario during 1981–1986. Through the use of general linear regression models we then sought evidence of control of the eplimnetic zooplankton community (mid-July to mid-October) by producers, consumers, and temperature. Our measures of the zooplankton community were total biomass, cladoceran biomass, and the ratio of large to small Daphnia spp. (D. galeata mendotae andD. retrocurva). Zooplankton population variables assessed were abundance, egg ratio, and productivity. Through factor analysis, factors were created from the standardized, transformed independent variables for use in the regression analyses. Regression models showed significant inverse relationships (P < 0.05) between alewives and Bosmina longirostris (abundance, production, and egg ratio), Ceriodaphnia lacustris (egg ratio), andDaphnia retrocurva (egg ratio). Bosmina longirostris and D. retrocurva egg ratios were inversely related to algae biomass (<20 μm), thus the smaller algae might be controlled in part by the zooplankton community. Production of C. lacustris was directly related to temperature, as was the production and abundance of Tropocyclops prasinus. The annual size-frequency distributions of B. longirostris and D. retrocurva were inversely related to yearling alewife abundance and directly related to adult alewife abundance, which suggested that yearlings use a particulate-feeding mode on these zooplankton species more frequently than adults. We found no significant negative correlations among the zooplankton species, which suggested that interzooplankton predation and competition were not as important in structuring the community as were planktivory and temperature.

Community structure of zooplankton in the main entrance of Bahía Magdalena, México during 1996.

PubMed

Gómez-Gutiérrez, J; Palomares-García, R; Hernández-Trujillo, S; Carballido-Carranza, A

2001-06-01

The zooplankton community structure, including copepods, euphausiids, chaetognaths, and decapod larvae, was monitored during six circadian cycles using Bongo net (500 microns mesh net) samples from Bahía Magdalena, on the southwest coast of Baja California, México. Samples were obtained during three oceanographic surveys (March, July, and December 1996) to describe the changes in the zooplankton community structure throughout the main mouth of Bahía Magdalena. The zooplankton community structure showed strong changes with a close relation to environmental conditions. During March, a well-mixed water column with low temperature and salinity indicated an influence of the California Current water and local upwelling processes. During July, temperature increased and a wide salinity range was recorded. The stratification of the water column was intense during summer, enhancing the thermocline. The highest temperatures and salinity were recorded in December, related to the presence of the Costa Rica Coastal Current (CRCC). The thermocline deepened as water temperature increased. A typical temperate community structure with low specific richness dominated by Calanus pacificus, Nyctiphanes simplex, and Acartia clausi and high zooplankton biomass (average 9.3 and 5.5 ml 1000 m-3 respectively) during March and July shifted to a more complex tropical community structure with a low zooplankton biomass in December (average 0.37 ml 1000 m-3). The mouth of Bahía Magdalena has a vigorous exchange of water caused by tidal currents. The zooplankton community structure was not significantly different between the central part of Bahía Magdalena and the continental shelf outside the bay for all months. The results suggest a more dynamic inside-outside interaction of zooplankton assemblages than first thought.

Exploratory Causal Analysis in Bivariate Time Series Data

NASA Astrophysics Data System (ADS)

McCracken, James M.

Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data

A window-based time series feature extraction method.

PubMed

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.

Simulation of time series by distorted Gaussian processes

NASA Technical Reports Server (NTRS)

Greenhall, C. A.

1977-01-01

Distorted stationary Gaussian process can be used to provide computer-generated imitations of experimental time series. A method of analyzing a source time series and synthesizing an imitation is shown, and an example using X-band radiometer data is given.

Long-range correlations in time series generated by time-fractional diffusion: A numerical study

NASA Astrophysics Data System (ADS)

Barbieri, Davide; Vivoli, Alessandro

2005-09-01

Time series models showing power law tails in autocorrelation functions are common in econometrics. A special non-Markovian model for such kind of time series is provided by the random walk introduced by Gorenflo et al. as a discretization of time fractional diffusion. The time series so obtained are analyzed here from a numerical point of view in terms of autocorrelations and covariance matrices.

Zooplankton diel vertical migration and contribution to deep active carbon flux in the NW Mediterranean

NASA Astrophysics Data System (ADS)

Isla, Alejandro; Scharek, Renate; Latasa, Mikel

2015-03-01

The diel vertical migration (DVM) of zooplankton contributes to the biological pump transporting material from surface to deep waters. We examined the DVM of the zooplankton community in different size fractions (53-200 μm, 200-500 μm, 500-1000 μm, 1000-2000 μm and > 2000 μm) during three cruises carried out in the open NW Mediterranean Sea. We assessed their metabolic rates from empirical published relationships and estimated the active fluxes of dissolved carbon to the mesopelagic zone driven by migrant zooplankton. Within the predominantly oligotrophic Mediterranean Sea, the NW region is one of the most productive ones, with a seasonal cycle characterized by a prominent spring bloom. The study area was visited at three different phases of the seasonal cycle: during the spring bloom, the post-bloom, and strongly stratified oligotrophic conditions. We found seasonal differences in DVM, less evident during the bloom. Changes in DVM intensity were related to the composition of the zooplanktonic assemblage, which also varied between cruises. Euphausiids appeared as the most active migrants in all seasons, and their life cycle conditioned the observed pattern. Immature stages, which are unable to perform large diel vertical movements, dominated during the bloom, in contrast to the higher relative importance of migrating adults in the other two sampling periods. The amount of dissolved carbon exported was determined by the migrant zooplankton biomass, being highest during the post-bloom (2.2 mmol C respired m- 2 d- 1, and up to 3.1 mmol C exported m- 2 d- 1 when DOC release estimations are added). The active transport by diel migrants represented a substantial contribution to total carbon export to deep waters, especially under stratified oligotrophic conditions, revealing the importance of zooplankton in the biological pump operating in the study area.

Annual cycle of zooplankton abundance and species composition in Izmit Bay (the northeastern Marmara Sea)

NASA Astrophysics Data System (ADS)

Isinibilir, Melek; Kideys, Ahmet E.; Tarkan, Ahmet N.; Yilmaz, I. Noyan

2008-07-01

The monthly abundance, biomass and taxonomic composition of zooplankton of Izmit Bay (the northeastern Marmara Sea) were studied from October 2001 to September 2002. Most species within the zooplankton community displayed a clear pattern of succession throughout the year. Generally copepods and cladocerans were the most abundant groups, while the contribution of meroplankton increased at inner-most stations and dominated the zooplankton. Both species number ( S) and diversity ( H') were positively influenced by the increase in salinity of upper layers ( r = 0.30 and r = 0.31, p < 0.001, respectively), while chlorophyll a was negatively affected ( r = -0.36, p < 0.001). Even though Noctiluca scintillans had a significant seasonality ( F11,120 = 8.45, p < 0.001, ANOVA), abundance was not related to fluctuations in temperature and only chlorophyll a was adversely correlated ( r = -0.35, p < 0.001). In general, there are some minor differences in zooplankton assemblages of upper and lower layers. A comparison of the species composition and abundance of Izmit Bay with other Black Sea bays reveals a high similarity between them.

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

NASA Astrophysics Data System (ADS)

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

Bottom-up linkages between primary production, zooplankton, and fish in a shallow, hypereutrophic lake.

PubMed

Matsuzaki, Shin-Ichiro S; Suzuki, Kenta; Kadoya, Taku; Nakagawa, Megumi; Takamura, Noriko

2018-06-09

Nutrient supply is a key bottom-up control of phytoplankton primary production in lake ecosystems. Top-down control via grazing pressure by zooplankton also constrains primary production, and primary production may simultaneously affect zooplankton. Few studies have addressed these bidirectional interactions. We used convergent cross-mapping (CCM), a numerical test of causal associations, to quantify the presence and direction of the causal relationships among environmental variables (light availability, surface water temperature, NO 3 -N, and PO 4 -P), phytoplankton community composition, primary production, and the abundances of five functional zooplankton groups (large-cladocerans, small-cladocerans, rotifers, calanoids, and cyclopoids) in Lake Kasumigaura, a shallow, hypereutrophic lake in Japan. CCM suggested that primary production was causally influenced by NO 3 -N and phytoplankton community composition; there was no detectable evidence of a causal effect of zooplankton on primary production. Our results also suggest that rotifers and cyclopoids were forced by primary production, and cyclopoids were further influenced by rotifers. However, our CCM suggested that primary production was weakly influenced by rotifers (i.e., bidirectional interaction). These findings may suggest complex linkages between nutrients, primary production, and rotifers and cyclopoids, a pattern that has not been previously detected or has been neglected. We used linear regression analysis to examine the relationships between the zooplankton community and pond smelt (Hypomesus nipponensis), the most abundant planktivore and the most important commercial fish species in Lake Kasumigaura. The relative abundance of pond smelt was significantly and positively correlated with the abundances of rotifers and cyclopoids, which were causally influenced by primary production. This finding suggests that bottom-up linkages between nutrient, primary production, and zooplankton abundance might be a

Trend time-series modeling and forecasting with neural networks.

PubMed

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.

Acoustically-inferred zooplankton distribution in relation to hydrography west of the Antarctic Peninsula

NASA Astrophysics Data System (ADS)

Lawson, Gareth L.; Wiebe, Peter H.; Ashjian, Carin J.; Gallager, Scott M.; Davis, Cabell S.; Warren, Joseph D.

2004-08-01

The relationship between the distribution of zooplankton, especially euphausiids ( Euphausia and Thysanoessa spp.), and hydrographic regimes of the Western Antarctic Peninsula continental shelf in and around Marguerite Bay was studied as part of the Southern Ocean GLOBEC program. Surveys were conducted from the RVIB N.B. Palmer in austral fall (April-June) and winter (July-August) of 2001. Acoustic, video, and environmental data were collected along 13 transect lines running across the shelf and perpendicular to the Western Antarctic Peninsula coastline, between 65°S and 70°S. Depth-stratified net tows conducted at selected locations provided ground-truthing for acoustic observations. In fall, acoustic volume backscattering strength at 120 kHz was greatest in the southern reaches of the survey area and inside Marguerite Bay, suggestive of high zooplankton and micronekton biomass in these regions. Vertically, highest backscattering was in the 150-450 m depth range, associated with modified Circumpolar Deep Water (CDW). The two deep troughs that intersect the shelf break were characterized by reduced backscattering, similar to levels observed off-shelf and indicative of lower zooplankton biomass in recent intrusions of CDW onto the continental shelf. Estimates of dynamic height suggested that geostrophic circulation likely caused both along- and across-shelf transport of zooplankton. By winter, scattering had decreased by an order of magnitude (10 dB) in the upper 300 m of the water column in most areas, and high backscattering levels were found primarily in a deep (>300 m) scattering layer present close to the bottom. The seasonal decrease is potentially explained by advection of zooplankton, vertical and horizontal movements, and mortality. Predictions of expected backscattering levels based on net samples suggested that large euphausiids were the dominant source of backscattering only at very particular locations and depths, and that copepods, siphonophores, and

Wavelet analysis and scaling properties of time series

NASA Astrophysics Data System (ADS)

Manimaran, P.; Panigrahi, Prasanta K.; Parikh, Jitendra C.

2005-10-01

We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multifractal behavior.

Non-parametric characterization of long-term rainfall time series

NASA Astrophysics Data System (ADS)

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.

Time Series Decomposition into Oscillation Components and Phase Estimation.

PubMed

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.

Deconvolution of mixing time series on a graph

PubMed Central

Blocker, Alexander W.; Airoldi, Edoardo M.

2013-01-01

In many applications we are interested in making inference on latent time series from indirect measurements, which are often low-dimensional projections resulting from mixing or aggregation. Positron emission tomography, super-resolution, and network traffic monitoring are some examples. Inference in such settings requires solving a sequence of ill-posed inverse problems, yt = Axt, where the projection mechanism provides information on A. We consider problems in which A specifies mixing on a graph of times series that are bursty and sparse. We develop a multilevel state-space model for mixing times series and an efficient approach to inference. A simple model is used to calibrate regularization parameters that lead to efficient inference in the multilevel state-space model. We apply this method to the problem of estimating point-to-point traffic flows on a network from aggregate measurements. Our solution outperforms existing methods for this problem, and our two-stage approach suggests an efficient inference strategy for multilevel models of multivariate time series. PMID:25309135

RADON CONCENTRATION TIME SERIES MODELING AND APPLICATION DISCUSSION.

PubMed

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.

Nonstationary time series prediction combined with slow feature analysis

NASA Astrophysics Data System (ADS)

Wang, G.; Chen, X.

2015-07-01

Almost all climate time series have some degree of nonstationarity due to external driving forces perturbing the observed system. Therefore, these external driving forces should be taken into account when constructing the climate dynamics. This paper presents a new technique of obtaining the driving forces of a time series from the slow feature analysis (SFA) approach, and then introduces them into a predictive model to predict nonstationary time series. The basic theory of the technique is to consider the driving forces as state variables and to incorporate them into the predictive model. Experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted to test the model. The results showed improved prediction skills.

Time Series Econometrics for the 21st Century

ERIC Educational Resources Information Center

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)…

The examination of headache activity using time-series research designs.

PubMed

Houle, Timothy T; Remble, Thomas A; Houle, Thomas A

2005-05-01

The majority of research conducted on headache has utilized cross-sectional designs which preclude the examination of dynamic factors and principally rely on group-level effects. The present article describes the application of an individual-oriented process model using time-series analytical techniques. The blending of a time-series approach with an interactive process model allows consideration of the relationships of intra-individual dynamic processes, while not precluding the researcher to examine inter-individual differences. The authors explore the nature of time-series data and present two necessary assumptions underlying the time-series approach. The concept of shock and its contribution to headache activity is also presented. The time-series approach is not without its problems and two such problems are specifically reported: autocorrelation and the distribution of daily observations. The article concludes with the presentation of several analytical techniques suited to examine the time-series interactive process model.

Semi-autonomous remote sensing time series generation tool

NASA Astrophysics Data System (ADS)

Babu, Dinesh Kumar; Kaufmann, Christof; Schmidt, Marco; Dhams, Thorsten; Conrad, Christopher

2017-10-01

High spatial and temporal resolution data is vital for crop monitoring and phenology change detection. Due to the lack of satellite architecture and frequent cloud cover issues, availability of daily high spatial data is still far from reality. Remote sensing time series generation of high spatial and temporal data by data fusion seems to be a practical alternative. However, it is not an easy process, since it involves multiple steps and also requires multiple tools. In this paper, a framework of Geo Information System (GIS) based tool is presented for semi-autonomous time series generation. This tool will eliminate the difficulties by automating all the steps and enable the users to generate synthetic time series data with ease. Firstly, all the steps required for the time series generation process are identified and grouped into blocks based on their functionalities. Later two main frameworks are created, one to perform all the pre-processing steps on various satellite data and the other one to perform data fusion to generate time series. The two frameworks can be used individually to perform specific tasks or they could be combined to perform both the processes in one go. This tool can handle most of the known geo data formats currently available which makes it a generic tool for time series generation of various remote sensing satellite data. This tool is developed as a common platform with good interface which provides lot of functionalities to enable further development of more remote sensing applications. A detailed description on the capabilities and the advantages of the frameworks are given in this paper.

Time Series Analysis of Insar Data: Methods and Trends

NASA Technical Reports Server (NTRS)

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

NASA Astrophysics Data System (ADS)

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

Self-affinity in the dengue fever time series

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

Comparing seasonal dynamics of the Lake Huron zooplankton community between 1983-1984 and 2007 and revisiting the impact of Bythotrephes planktivory

USGS Publications Warehouse

Bunnell, David B.; Keeler, Kevin M.; Puchala, Elizabeth A.; Davis, Bruce M.; Pothoven, Steven A.

2012-01-01

Zooplankton community composition can be influenced by lake productivity as well as planktivory by fish or invertebrates. Previous analyses based on long-term Lake Huron zooplankton data from August reported a shift in community composition between the 1980s and 2000s: proportional biomass of calanoid copepods increased while that of cyclopoid copepods and herbivorous cladocerans decreased. Herein, we used seasonally collected data from Lake Huron in 1983–1984 and 2007 and reported similar shifts in proportional biomass. We also used a series of generalized additive models to explore differences in seasonal abundance by species and found that all three cyclopoid copepod species (Diacyclops thomasi, Mesocylops edax, Tropocyclops prasinus mexicanus) exhibited higher abundance in 1983–1984 than in 2007. Surprisingly, only one (Epischura lacustris) of seven calanoid species exhibited higher abundance in 2007. The results for cladocerans were also mixed with Bosmina spp. exhibiting higher abundance in 1983–1984, while Daphnia galeata mendotae reached a higher level of abundance in 2007. We used a subset of the 2007 data to estimate not only the vertical distribution of Bythotrephes longimanus and their prey, but also the consumption by Bythotrephes in the top 20 m of water. This epilimnetic layer was dominated by copepod copepodites and nauplii, and consumption either exceeded (Hammond Bay site) or equaled 65% (Detour site) of epilimnetic zooplankton production. The lack of spatial overlap between Bythotrephes and herbivorous cladocerans and cyclopoid copepod prey casts doubt on the hypothesis that Bythotrephes planktivory was the primary driver underlying the community composition changes in the 2000s.

Developing consistent time series landsat data products

USDA-ARS?s Scientific Manuscript database

The Landsat series satellite has provided earth observation data record continuously since early 1970s. There are increasing demands on having a consistent time series of Landsat data products. In this presentation, I will summarize the work supported by the USGS Landsat Science Team project from 20...

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

PubMed

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.

Nonstationary time series prediction combined with slow feature analysis

NASA Astrophysics Data System (ADS)

Wang, G.; Chen, X.

2015-01-01

Almost all climate time series have some degree of nonstationarity due to external driving forces perturbations of the observed system. Therefore, these external driving forces should be taken into account when reconstructing the climate dynamics. This paper presents a new technique of combining the driving force of a time series obtained using the Slow Feature Analysis (SFA) approach, then introducing the driving force into a predictive model to predict non-stationary time series. In essence, the main idea of the technique is to consider the driving forces as state variables and incorporate them into the prediction model. To test the method, experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted. The results showed improved and effective prediction skill.

Fast Algorithms for Mining Co-evolving Time Series

DTIC Science & Technology

2011-09-01

Keogh et al., 2001, 2004] and (b) forecasting, like an autoregressive integrated moving average model ( ARIMA ) and related meth- ods [Box et al., 1994...computing hardware? We develop models to mine time series with missing values, to extract compact representation from time sequences, to segment the...sequences, and to do forecasting. For large scale data, we propose algorithms for learning time series models , in particular, including Linear Dynamical

Spatial variations in zooplankton community structure along the Japanese coastline in the Japan Sea: influence of the coastal current

NASA Astrophysics Data System (ADS)

Kodama, Taketoshi; Wagawa, Taku; Iguchi, Naoki; Takada, Yoshitake; Takahashi, Takashi; Fukudome, Ken-Ichi; Morimoto, Haruyuki; Goto, Tsuneo

2018-06-01

This study evaluates spatial variations in zooplankton community structure and potential controlling factors along the Japanese coast under the influence of the coastal branch of the Tsushima Warm Current (CBTWC). Variations in the density of morphologically identified zooplankton in the surface layer in May were investigated for a 15-year period. The density of zooplankton (individuals per cubic meter) varied between sampling stations, but there was no consistent west-east trend. Instead, there were different zooplankton community structures in the west and east, with that in Toyama Bay particularly distinct: Corycaeus affinis and Calanus sinicus were dominant in the west and Oithona atlantica was dominant in Toyama Bay. Distance-based redundancy analysis (db-RDA) was used to characterize the variation in zooplankton community structure, and four axes (RD1-4) provided significant explanation. RD2-4 only explained < 4.8 % of variation in the zooplankton community and did not show significant spatial difference; however, RD1, which explained 89.9 % of variation, did vary spatially. Positive and negative species scores on RD1 represent warm- and cold-water species, respectively, and their variation was mainly explained by water column mean temperature, and it is considered to vary spatially with the CBTWC. The CBTWC intrusion to the cold Toyama Bay is weak and occasional due to the submarine canyon structure of the bay. Therefore, the varying bathymetric characteristics along the Japanese coast of the Japan Sea generate the spatial variation in zooplankton community structure, and dominance of warm-water species can be considered an indicator of the CBTWC.

Use of zooplankton to assess the movement and distribution of alewife (Alosa pseudoharengus) in south-central Lake Ontario in spring

USGS Publications Warehouse

O'Gorman, Robert; Mills, Edward L.; DeGisi, Joe

1991-01-01

Data from assessments of fish and zooplankton conducted during April and May-June 1986-88 in south-central Lake Ontario were examined for evidence that zooplankton size structure can be used to follow the movement of alewife (Alosa pseudoharengus). The spring influx of alewife into nearshore waters was linked with water temperature and coincided with a decline in the mean length of crustacean zooplankton and the virtual disappearance of zooplankters a?Y 0.9 mm. Alewife moving inshore to spawn fed heavily on the largest zooplankters, negating the possibility that changes in zooplankton size were wholly a response to seasonal recruitment as waters warm and the competition shifts to Bosmina. Offshore, there was usually no significant (P < 0.05) change in mean lengths of zooplankton in the upper water column between April and May-June, and zooplankters a?Y 0.9 mm always remained abundant, suggesting that few alewife were there from April through mid-June. We conclude that in large freshwater lakes where a planktivore is abundant, yet spatially concentrated, changes in size of crustacean zooplankton can facilitate understanding of the fish's movement and distribution.

Characterization of time series via Rényi complexity-entropy curves

NASA Astrophysics Data System (ADS)

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.

Characterizing Time Series Data Diversity for Wind Forecasting: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Brian S; Chartan, Erol Kevin; Feng, Cong

Wind forecasting plays an important role in integrating variable and uncertain wind power into the power grid. Various forecasting models have been developed to improve the forecasting accuracy. However, it is challenging to accurately compare the true forecasting performances from different methods and forecasters due to the lack of diversity in forecasting test datasets. This paper proposes a time series characteristic analysis approach to visualize and quantify wind time series diversity. The developed method first calculates six time series characteristic indices from various perspectives. Then the principal component analysis is performed to reduce the data dimension while preserving the importantmore » information. The diversity of the time series dataset is visualized by the geometric distribution of the newly constructed principal component space. The volume of the 3-dimensional (3D) convex polytope (or the length of 1D number axis, or the area of the 2D convex polygon) is used to quantify the time series data diversity. The method is tested with five datasets with various degrees of diversity.« less

Quantifying Selection with Pool-Seq Time Series Data.

PubMed

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

NASA Astrophysics Data System (ADS)

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.

PubMed

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.

Online Conditional Outlier Detection in Nonstationary Time Series.

PubMed

Liu, Siqi; Wright, Adam; Hauskrecht, Milos

2017-05-01

The objective of this work is to develop methods for detecting outliers in time series data. Such methods can become the key component of various monitoring and alerting systems, where an outlier may be equal to some adverse condition that needs human attention. However, real-world time series are often affected by various sources of variability present in the environment that may influence the quality of detection; they may (1) explain some of the changes in the signal that would otherwise lead to false positive detections, as well as, (2) reduce the sensitivity of the detection algorithm leading to increase in false negatives. To alleviate these problems, we propose a new two-layer outlier detection approach that first tries to model and account for the nonstationarity and periodic variation in the time series, and then tries to use other observable variables in the environment to explain any additional signal variation. Our experiments on several data sets in different domains show that our method provides more accurate modeling of the time series, and that it is able to significantly improve outlier detection performance.

A multidisciplinary database for geophysical time series management

NASA Astrophysics Data System (ADS)

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.

Noise analysis of GPS time series in Taiwan

NASA Astrophysics Data System (ADS)

Lee, You-Chia; Chang, Wu-Lung

2017-04-01

Global positioning system (GPS) usually used for researches of plate tectonics and crustal deformation. In most studies, GPS time series considered only time-independent noises (white noise), but time-dependent noises (flicker noise, random walk noise) which were found by nearly twenty years are also important to the precision of data. The rate uncertainties of stations will be underestimated if the GPS time series are assumed only time-independent noise. Therefore studying the noise properties of GPS time series is necessary in order to realize the precision and reliability of velocity estimates. The lengths of our GPS time series are from over 500 stations around Taiwan with time spans longer than 2.5 years up to 20 years. The GPS stations include different monument types such as deep drill braced, roof, metal tripod, and concrete pier, and the most common type in Taiwan is the metal tripod. We investigated the noise properties of continuous GPS time series by using the spectral index and amplitude of the power law noise. During the process we first remove the data outliers, and then estimate linear trend, size of offsets, and seasonal signals, and finally the amplitudes of the power-law and white noise are estimated simultaneously. Our preliminary results show that the noise amplitudes of the north component are smaller than that of the other two components, and the largest amplitudes are in the vertical. We also find that the amplitudes of white noise and power-law noises are positively correlated in three components. Comparisons of noise amplitudes of different monument types in Taiwan reveal that the deep drill braced monuments have smaller data uncertainties and therefore are more stable than other monuments.

Higher-Order Hurst Signatures: Dynamical Information in Time Series

NASA Astrophysics Data System (ADS)

Ferenbaugh, Willis

2005-10-01

Understanding and comparing time series from different systems requires characteristic measures of the dynamics embedded in the series. The Hurst exponent is a second-order dynamical measure of a time series which grew up within the blossoming fractal world of Mandelbrot. This characteristic measure is directly related to the behavior of the autocorrelation, the power-spectrum, and other second-order things. And as with these other measures, the Hurst exponent captures and quantifies some but not all of the intrinsic nature of a series. The more elusive characteristics live in the phase spectrum and the higher-order spectra. This research is a continuing quest to (more) fully characterize the dynamical information in time series produced by plasma experiments or models. The goal is to supplement the series information which can be represented by a Hurst exponent, and we would like to develop supplemental techniques in analogy with Hurst's original R/S analysis. These techniques should be another way to plumb the higher-order dynamics.

Analysis of Time-Series Quasi-Experiments. Final Report.

ERIC Educational Resources Information Center

Glass, Gene V.; Maguire, Thomas O.

The objective of this project was to investigate the adequacy of statistical models developed by G. E. P. Box and G. C. Tiao for the analysis of time-series quasi-experiments: (1) The basic model developed by Box and Tiao is applied to actual time-series experiment data from two separate experiments, one in psychology and one in educational…

A Computer Evolution in Teaching Undergraduate Time Series

ERIC Educational Resources Information Center

Hodgess, Erin M.

2004-01-01

In teaching undergraduate time series courses, we have used a mixture of various statistical packages. We have finally been able to teach all of the applied concepts within one statistical package; R. This article describes the process that we use to conduct a thorough analysis of a time series. An example with a data set is provided. We compare…

Evaluation of the Zooplankton Community of Livingston Reservoir, Texas, as Related to Paddlefish Food Resources

DTIC Science & Technology

1993-12-01

EVALUATION OF THE ZOOPLANKTON COMMUNITY OF LIVINGSTON RESERVOIR. TEXAS, AS RELATED TO PADDLEFISH FOOD RESOURCES A Thesis by CASEY KENNETH MOORE...OF LIVINGSTON RESERVOIR, TEXAS. AS RELATED TO PADDLEFISH FOOD RESOURCES A Thesis by CASEY KENNETH MOORE Submitted to Texas A&M University in partial...Fisheries Sciences iii ABSTRACT Evaluation of the Zooplankton Community of Livingston Reservoir, Texas, as Related to Paddlefish Food Resources

Modeling Time Series Data for Supervised Learning

ERIC Educational Resources Information Center

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…

Empirical method to measure stochasticity and multifractality in nonlinear time series

NASA Astrophysics Data System (ADS)

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)

NASA Astrophysics Data System (ADS)

Laß, K.; Bange, H. W.; Friedrichs, G.

2013-02-01

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. We suggest that indeed sloppy feeding of zooplankton together with photochemical and/or microbial processing of organic precursor compounds are 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)

NASA Astrophysics Data System (ADS)

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.

Looking inside the Ocean: Toward an Autonomous Imaging System for Monitoring Gelatinous Zooplankton

PubMed Central

Corgnati, Lorenzo; Marini, Simone; Mazzei, Luca; Ottaviani, Ennio; Aliani, Stefano; Conversi, Alessandra; Griffa, Annalisa

2016-01-01

Marine plankton abundance and dynamics in the open and interior ocean is still an unknown field. The knowledge of gelatinous zooplankton distribution is especially challenging, because this type of plankton has a very fragile structure and cannot be directly sampled using traditional net based techniques. To overcome this shortcoming, Computer Vision techniques can be successfully used for the automatic monitoring of this group.This paper presents the GUARD1 imaging system, a low-cost stand-alone instrument for underwater image acquisition and recognition of gelatinous zooplankton, and discusses the performance of three different methodologies, Tikhonov Regularization, Support Vector Machines and Genetic Programming, that have been compared in order to select the one to be run onboard the system for the automatic recognition of gelatinous zooplankton. The performance comparison results highlight the high accuracy of the three methods in gelatinous zooplankton identification, showing their good capability in robustly selecting relevant features. In particular, Genetic Programming technique achieves the same performances of the other two methods by using a smaller set of features, thus being the most efficient in avoiding computationally consuming preprocessing stages, that is a crucial requirement for running on an autonomous imaging system designed for long lasting deployments, like the GUARD1. The Genetic Programming algorithm has been installed onboard the system, that has been operationally tested in a two-months survey in the Ligurian Sea, providing satisfactory results in terms of monitoring and recognition performances. PMID:27983638

A review of zooplankton investigations of the Black Sea over the last decade

NASA Astrophysics Data System (ADS)

Kideys, Ahmet E.; Kovalev, Alexander V.; Shulman, Gregory; Gordina, Anna; Bingel, Ferit

2000-03-01

Investigations performed in the last decade indicate that there have been important changes in the zooplankton composition and structure in the Black Sea. However, contrasting events taking place in different regions of the Black Sea indicate a non-uniform structure of its ecosystem. Several fodder zooplankton species have either disappeared from or substantially decreased in number at different sampling sites of the Black Sea over the last one or two decades. Some other species adapted to thrive in eutrophic conditions have either appeared or increased in quantity. Meanwhile the biomass of the fodder zooplankton has also fluctuated considerably through the years. However, there seems to be a reverse trend in the long-term variation of fodder zooplankton between the shallow western and deep eastern areas. Over the last few decades the abundance of fish larvae has decreased significantly when compared either to past records or with larval abundances of other seas. This was shown to be due mainly to malnutrition of larvae. One of the most striking changes in the ichthyoplankton has been the shift in the spawning areas of the main fish species, the anchovy Engraulis encrasicolus from the northwestern to the southeastern Black Sea. Even the invading ctenophore Mnemiopsis were found to be starving. The condition of other species ( Calanus euxinus and Pleurobrachia pileus) disclosed the fact that cyclonic regions where chlorophyll and nutrient concentrations are high, provide better nutrition than anticyclonic regions.

Predator evasion in zooplankton is suppressed by polyunsaturated fatty acid limitation.

PubMed

Brzeziński, Tomasz; von Elert, Eric

2015-11-01

Herbivorous zooplankton avoid size-selective predation by vertical migration to a deep, cold water refuge. Adaptation to low temperatures in planktonic poikilotherms depends on essential dietary lipids; the availability of these lipids often limits growth and reproduction of zooplankton. We hypothesized that limitation by essential lipids may affect habitat preferences and predator avoidance behavior in planktonic poikilotherms. We used a liposome supplementation technique to enrich the green alga Scenedesmus obliquus and the cyanobacterium Synecchococcus elongatus with the essential lipids, cholesterol and eicosapentaenoic acid (EPA), and an indoor system with a stratified water-column (plankton organ) to test whether the absence of these selected dietary lipids constrains predator avoidance (habitat preferences) in four species of the key-stone pelagic freshwater grazer Daphnia. We found that the capability of avoiding fish predation through habitat shift to the deeper and colder environment was suppressed in Daphnia unless the diet was supplemented with EPA; however, the availability of cholesterol did not affect habitat preferences of the tested taxa. Thus, their ability to access a predator-free refuge and the outcome of predator-prey interactions depends upon food quality (i.e. the availability of an essential fatty acid). Our results suggest that biochemical food quality limitation, a bottom-up factor, may affect the top-down control of herbivorous zooplankton.

Determinants of community structure of zooplankton in heavily polluted river ecosystems

NASA Astrophysics Data System (ADS)

Xiong, Wei; Li, Jie; Chen, Yiyong; Shan, Baoqing; Wang, Weimin; Zhan, Aibin

2016-02-01

River ecosystems are among the most affected habitats globally by human activities, such as the release of chemical pollutants. However, it remains largely unknown how and to what extent many communities such as zooplankton are affected by these environmental stressors in river ecosystems. Here, we aim to determine major factors responsible for shaping community structure of zooplankton in heavily polluted river ecosystems. Specially, we use rotifers in the Haihe River Basin (HRB) in North China as a case study to test the hypothesis that species sorting (i.e. species are “filtered” by environmental factors and occur at environmental suitable sites) plays a key role in determining community structure at the basin level. Based on an analysis of 94 sites across the plain region of HRB, we found evidence that both local and regional factors could affect rotifer community structure. Interestingly, further analyses indicated that local factors played a more important role in determining community structure. Thus, our results support the species sorting hypothesis in highly polluted rivers, suggesting that local environmental constraints, such as environmental pollution caused by human activities, can be stronger than dispersal limitation caused by regional factors to shape local community structure of zooplankton at the basin level.

Possible association of diazotrophs with marine zooplankton in the Pacific Ocean.

PubMed

Azimuddin, Kazi Md; Hirai, Junya; Suzuki, Shotaro; Haider, Md Nurul; Tachibana, Aiko; Watanabe, Keigo; Kitamura, Minoru; Hashihama, Fuminori; Takahashi, Kazutaka; Hamasaki, Koji

2016-12-01

Dinitrogen fixation, the biological reduction in N 2 gas to ammonia contributes to the supply of new nitrogen in the surface ocean. To understand the diversity and abundance of potentially diazotrophic (N 2 fixing) microorganisms associated with marine zooplankton, especially copepods, the nifH gene was studied using zooplankton samples collected in the Pacific Ocean. In total, 257 nifH sequences were recovered from 23 nifH-positive DNA extracts out of 90 copepod samples. The nifH genes derived from cyanobacteria related to Trichodesmium, α- and γ-subdivisions of proteobacteria, and anaerobic euryarchaeota related to Methanosaeta concilii were detected. Our results indicated that Pleuromamma, Pontella, and Euchaeta were the major copepod genera hosting dinitrogen fixers, though we found no species-specific association between copepods and dinitrogen fixers. Also, the digital PCR provided novel data on the number of copies of the nifH gene in individual copepods, which we report the range from 30 to 1666 copies per copepod. This study is the first systematic study of zooplankton-associated diazotrophs, covering a large area of the open ocean, which provide a clue to further study of a possible new hotspot of N 2 fixation. © 2016 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

GNSS Network Time Series Analysis

NASA Astrophysics Data System (ADS)

Balodis, J.; Janpaule, I.; Haritonova, D.; Normand, M.; Silabriedis, G.; Zarinjsh, A.; Zvirgzds, J.

2012-04-01

Time series of GNSS station results of both the EUPOS®-RIGA and LATPOS networks has been developed at the Institute of Geodesy and Geoinformation (University of Latvia) using Bernese v.5.0 software. The base stations were selected among the EPN and IGS stations in surroundings of Latvia. In various day solutions the base station selection has been miscellaneous. Most frequently 5 - 8 base stations were selected from a set of stations {BOR1, JOEN, JOZE, MDVJ, METS, POLV, PULK, RIGA, TORA, VAAS, VISO, VLNS}. The rejection of "bad base stations" was performed by Bernese software depending on the quality of proper station data in proper day. This caused a reason of miscellaneous base station selection in various days. The results of time series are analysed. The question aroused on the nature of some outlying situations. The seasonal effect of the behaviour of the network has been identified when distance and elevation changes between stations has been analysed. The dependence from various influences has been recognised.

Evaluation of Scaling Invariance Embedded in Short Time Series

PubMed Central

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 . Calculations with specified Hurst exponent values of 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 () and sharp confidential interval (standard deviation ). 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. PMID:25549356

Clinical time series prediction: towards a hierarchical dynamical system framework

PubMed Central

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

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

PubMed

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.

Characterizing time series: when Granger causality triggers complex networks

NASA Astrophysics Data System (ADS)

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.

Filter-based multiscale entropy analysis of complex physiological time series.

PubMed

Xu, Yuesheng; Zhao, Liang

2013-08-01

Multiscale entropy (MSE) has been widely and successfully used in analyzing the complexity of physiological time series. We reinterpret the averaging process in MSE as filtering a time series by a filter of a piecewise constant type. From this viewpoint, we introduce filter-based multiscale entropy (FME), which filters a time series to generate multiple frequency components, and then we compute the blockwise entropy of the resulting components. By choosing filters adapted to the feature of a given time series, FME is able to better capture its multiscale information and to provide more flexibility for studying its complexity. Motivated by the heart rate turbulence theory, which suggests that the human heartbeat interval time series can be described in piecewise linear patterns, we propose piecewise linear filter multiscale entropy (PLFME) for the complexity analysis of the time series. Numerical results from PLFME are more robust to data of various lengths than those from MSE. The numerical performance of the adaptive piecewise constant filter multiscale entropy without prior information is comparable to that of PLFME, whose design takes prior information into account.

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

PubMed

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 (< 1 day) and high suspended load (> 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.

Acoustic Scattering Models of Zooplankton and Microstructure

DTIC Science & Technology

1999-09-30

1998, a remotely operated vehicle was used to deploy acoustic transducers so that the acoustic scattering by siphonophores , a gas-bearing animal, could...their high frequency acoustics systems. 4) In addition, we have identified two types of zooplankton ( siphonophores and pteropods) that have high...Benfield, P.H. Wiebe, and D. Chu, 1999. “In situ measurements of acoustic target strengths of siphonophores ,” Proceedings of the 2nd EAA

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

PubMed

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.

Contribution and pathways of diazotroph-derived nitrogen to zooplankton during the VAHINE mesocosm experiment in the oligotrophic New Caledonia lagoon

NASA Astrophysics Data System (ADS)

Hunt, Brian P. V.; Bonnet, Sophie; Berthelot, Hugo; Conroy, Brandon J.; Foster, Rachel A.; Pagano, Marc

2016-05-01

In oligotrophic tropical and subtropical oceans, where strong stratification can limit the replenishment of surface nitrate, dinitrogen (N2) fixation by diazotrophs can represent a significant source of nitrogen (N) for primary production. The VAHINE (VAriability of vertical and tropHIc transfer of fixed N2 in the south-wEst Pacific) experiment was designed to examine the fate of diazotroph-derived nitrogen (DDN) in such ecosystems. In austral summer 2013, three large ( ˜ 50 m3) in situ mesocosms were deployed for 23 days in the New Caledonia lagoon, an ecosystem that typifies the low-nutrient, low-chlorophyll environment, to stimulate diazotroph production. The zooplankton component of the study aimed to measure the incorporation of DDN into zooplankton biomass, and assess the role of direct diazotroph grazing by zooplankton as a DDN uptake pathway. Inside the mesocosms, the diatom-diazotroph association (DDA) het-1 predominated during days 5-15 while the unicellular diazotrophic cyanobacteria UCYN-C predominated during days 15-23. A Trichodesmium bloom was observed in the lagoon (outside the mesocosms) towards the end of the experiment. The zooplankton community was dominated by copepods (63 % of total abundance) for the duration of the experiment. Using two-source N isotope mixing models we estimated a mean ˜ 28 % contribution of DDN to zooplankton nitrogen biomass at the start of the experiment, indicating that the natural summer peak of N2 fixation in the lagoon was already contributing significantly to the zooplankton. Stimulation of N2 fixation in the mesocosms corresponded with a generally low-level enhancement of DDN contribution to zooplankton nitrogen biomass, but with a peak of ˜ 73 % in mesocosm 1 following the UCYN-C bloom. qPCR analysis targeting four of the common diazotroph groups present in the mesocosms (Trichodesmium, het-1, het-2, UCYN-C) demonstrated that all four were ingested by copepod grazers, and that their abundance in copepod

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

PubMed

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.

Signatures of ecological processes in microbial community time series.

PubMed

Faust, Karoline; Bauchinger, Franziska; Laroche, Béatrice; de Buyl, Sophie; Lahti, Leo; Washburne, Alex D; Gonze, Didier; Widder, Stefanie

2018-06-28

Growth rates, interactions between community members, stochasticity, and immigration are important drivers of microbial community dynamics. In sequencing data analysis, such as network construction and community model parameterization, we make implicit assumptions about the nature of these drivers and thereby restrict model outcome. Despite apparent risk of methodological bias, the validity of the assumptions is rarely tested, as comprehensive procedures are lacking. Here, we propose a classification scheme to determine the processes that gave rise to the observed time series and to enable better model selection. We implemented a three-step classification scheme in R that first determines whether dependence between successive time steps (temporal structure) is present in the time series and then assesses with a recently developed neutrality test whether interactions between species are required for the dynamics. If the first and second tests confirm the presence of temporal structure and interactions, then parameters for interaction models are estimated. To quantify the importance of temporal structure, we compute the noise-type profile of the community, which ranges from black in case of strong dependency to white in the absence of any dependency. We applied this scheme to simulated time series generated with the Dirichlet-multinomial (DM) distribution, Hubbell's neutral model, the generalized Lotka-Volterra model and its discrete variant (the Ricker model), and a self-organized instability model, as well as to human stool microbiota time series. The noise-type profiles for all but DM data clearly indicated distinctive structures. The neutrality test correctly classified all but DM and neutral time series as non-neutral. The procedure reliably identified time series for which interaction inference was suitable. Both tests were required, as we demonstrated that all structured time series, including those generated with the neutral model, achieved a moderate to high

Neural network versus classical time series forecasting models

NASA Astrophysics Data System (ADS)

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.

Zooplankton variability and larval striped bass foraging: Evaluating potential match/mismatch regulation

USGS Publications Warehouse

Chick, J.H.; Van Den Avyle, M.J.

1999-01-01

We quantified temporal and spatial variability of zooplankton in three potential nursery sites (river, transition zone, lake) for larval striped bass (Morone saxatilis) in Lake Marion, South Carolina, during April and May 1993-1995. In two of three years, microzooplankton (rotifers and copepod nauplii) density was significantly greater in the lake site than in the river or transition zone. Macrozooplankton (>200 ??m) composition varied among the three sites in all years with adult copepods and cladocerans dominant at the lake, and juvenile Corbicula fluminea dominant at the river and transition zone. Laboratory feeding experiments, simulating both among-site (site treatments) and within-site (density treatments) variability, were conducted in 1995 to quantify the effects of the observed zooplankton variability on foraging success of larval striped bass. A greater proportion of larvae fed in the lake than in the river or transition-zone treatments across all density treatments: mean (x), 10x and 100x. Larvae also ingested significantly more dry mass of prey in the lake treatment in both the mean and 10x density treatments. Field zooplankton and laboratory feeding data suggest that both spatial and temporal variability of zooplankton influence larval striped bass foraging. Prey density levels that supported successful foraging in our feeding experiments occurred in the lake during late April and May in 1994 and 1995 but were never observed in the river or transition zone. Because the rivers flowing into Lake Marion are regulated, it may be possible to devise flow management schemes that facilitate larval transport to the lake and thereby increase the proportion of larvae matched to suitable prey resources.

Testing for nonlinearity in non-stationary physiological time series.

PubMed

Guarín, Diego; Delgado, Edilson; Orozco, Álvaro

2011-01-01

Testing for nonlinearity is one of the most important preprocessing steps in nonlinear time series analysis. Typically, this is done by means of the linear surrogate data methods. But it is a known fact that the validity of the results heavily depends on the stationarity of the time series. Since most physiological signals are non-stationary, it is easy to falsely detect nonlinearity using the linear surrogate data methods. In this document, we propose a methodology to extend the procedure for generating constrained surrogate time series in order to assess nonlinearity in non-stationary data. The method is based on the band-phase-randomized surrogates, which consists (contrary to the linear surrogate data methods) in randomizing only a portion of the Fourier phases in the high frequency domain. Analysis of simulated time series showed that in comparison to the linear surrogate data method, our method is able to discriminate between linear stationarity, linear non-stationary and nonlinear time series. Applying our methodology to heart rate variability (HRV) records of five healthy patients, we encountered that nonlinear correlations are present in this non-stationary physiological signals.

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

PubMed

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.

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

PubMed

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

NASA Astrophysics Data System (ADS)

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.

Determination of lead in samples of zooplankton, water, and sediments in a Mexican reservoir: evidence for lead biomagnification in lower/intermediate trophic levels?

PubMed

Rubio-Franchini, Isidoro; Mejía Saavedra, Jesús; Rico-Martínez, Roberto

2008-08-01

We have determined lead concentration of water, sediment, and zooplankton samples of El Niágara, a reservoir in Aguascalientes, Mexico. Our results include the first report of bioconcentration factor (BCF) obtained in an actual ecosystem (as opposed to the experimental setups in the laboratory) for a rotifer species; Asplanchna brigthwellii (BCF ca. 49 300). The BCF of this predatory zooplanktonic species (A. brigthwellii) are up to four times greater than those of two grazing zooplanktonic species (Daphnia similis and Moina micrura). In this contaminated reservoir that lacks fishes, Asplanchna, and Culex sp. together with ducks and other bigger invertebrates might represent the top predators. Our data suggest that biomagnification of lead through at least one trophic level can occur in freshwater systems. Biomagnification in A. brigthwellii might be explained in part by predation of this voracious predator on young of the herbivorous cladoceran, M. micrura. Our findings stand opposite to the current theoretical framework where lead biomagnification occurs only in lower trophic levels.

Time series momentum and contrarian effects in the Chinese stock market

NASA Astrophysics Data System (ADS)

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

NASA Technical Reports Server (NTRS)

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.

Alternative predictors in chaotic time series

NASA Astrophysics Data System (ADS)

Alves, P. R. L.; Duarte, L. G. S.; da Mota, L. A. C. P.

2017-06-01

In the scheme of reconstruction, non-polynomial predictors improve the forecast from chaotic time series. The algebraic manipulation in the Maple environment is the basis for obtaining of accurate predictors. Beyond the different times of prediction, the optional arguments of the computational routines optimize the running and the analysis of global mappings.

Online Conditional Outlier Detection in Nonstationary Time Series

PubMed Central

Liu, Siqi; Wright, Adam; Hauskrecht, Milos

2017-01-01

The objective of this work is to develop methods for detecting outliers in time series data. Such methods can become the key component of various monitoring and alerting systems, where an outlier may be equal to some adverse condition that needs human attention. However, real-world time series are often affected by various sources of variability present in the environment that may influence the quality of detection; they may (1) explain some of the changes in the signal that would otherwise lead to false positive detections, as well as, (2) reduce the sensitivity of the detection algorithm leading to increase in false negatives. To alleviate these problems, we propose a new two-layer outlier detection approach that first tries to model and account for the nonstationarity and periodic variation in the time series, and then tries to use other observable variables in the environment to explain any additional signal variation. Our experiments on several data sets in different domains show that our method provides more accurate modeling of the time series, and that it is able to significantly improve outlier detection performance. PMID:29644345

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

PubMed

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.

PubMed

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.

Bacterial bioluminescence as a lure for marine zooplankton and fish.

PubMed

Zarubin, Margarita; Belkin, Shimshon; Ionescu, Michael; Genin, Amatzia

2012-01-17

The benefits of bioluminescence for nonsymbiotic marine bacteria have not been elucidated fully. One of the most commonly cited explanations, proposed more than 30 y ago, is that bioluminescence augments the propagation and dispersal of bacteria by attracting fish to consume the luminous material. This hypothesis, based mostly on the prevalence of luminous bacteria in fish guts, has not been tested experimentally. Here we show that zooplankton that contacts and feeds on the luminescent bacterium Photobacterium leiognathi starts to glow, and demonstrate by video recordings that glowing individuals are highly vulnerable to predation by nocturnal fish. Glowing bacteria thereby are transferred to the nutritious guts of fish and zooplankton, where they survive digestion and gain effective means for growth and dispersal. Using bioluminescence as bait appears to be highly beneficial for marine bacteria, especially in food-deprived environments of the deep sea.

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

PubMed

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.

Evaluation of scaling invariance embedded in short time series.

PubMed

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.

Using SAR satellite data time series for regional glacier mapping

NASA Astrophysics Data System (ADS)

Winsvold, Solveig H.; Kääb, Andreas; Nuth, Christopher; Andreassen, Liss M.; van Pelt, Ward J. J.; Schellenberger, Thomas

2018-03-01

With dense SAR satellite data time series it is possible to map surface and subsurface glacier properties that vary in time. On Sentinel-1A and RADARSAT-2 backscatter time series images over mainland Norway and Svalbard, we outline how to map glaciers using descriptive methods. We present five application scenarios. The first shows potential for tracking transient snow lines with SAR backscatter time series and correlates with both optical satellite images (Sentinel-2A and Landsat 8) and equilibrium line altitudes derived from in situ surface mass balance data. In the second application scenario, time series representation of glacier facies corresponding to SAR glacier zones shows potential for a more accurate delineation of the zones and how they change in time. The third application scenario investigates the firn evolution using dense SAR backscatter time series together with a coupled energy balance and multilayer firn model. We find strong correlation between backscatter signals with both the modeled firn air content and modeled wetness in the firn. In the fourth application scenario, we highlight how winter rain events can be detected in SAR time series, revealing important information about the area extent of internal accumulation. In the last application scenario, averaged summer SAR images were found to have potential in assisting the process of mapping glaciers outlines, especially in the presence of seasonal snow. Altogether we present examples of how to map glaciers and to further understand glaciological processes using the existing and future massive amount of multi-sensor time series data.

Non-linear forecasting in high-frequency financial time series

NASA Astrophysics Data System (ADS)

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.

Pseudo-random bit generator based on lag time series

NASA Astrophysics Data System (ADS)

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.

miniSEED: The Backbone Data Format for Seismological Time Series

NASA Astrophysics Data System (ADS)

Ahern, T. K.; Benson, R. B.; Trabant, C. M.

2017-12-01

In 1987, the International Federation of Digital Seismograph Networks (FDSN), adopted the Standard for the Exchange of Earthquake Data (SEED) format to be used for data archiving and exchange of seismological time series data. Since that time, the format has evolved to accommodate new capabilities and features. For example, a notable change in 1992 allowed the format, which includes both the comprehensive metadata and the time series samples, to be used in two additional forms: a container for metadata only called "dataless SEED", and 2) a stand-alone structure for time series called "miniSEED". While specifically designed for seismological data and related metadata, this format has proven to be a useful format for a wide variety of geophysical time series data. Many FDSN data centers now store temperature, pressure, infrasound, tilt and other time series measurements in this internationally used format. Since April 2016, members of the FDSN have been in discussions to design a next generation miniSEED format to accommodate current and future needs, to further generalize the format, and to address a number of historical problems or limitations. We believe the correct approach is to simplify the header, allow for arbitrary header additions, expand the current identifiers, and allow for anticipated future identifiers which are currently unknown. We also believe the primary goal of the format is for efficient archiving, selection and exchange of time series data. By focusing on these goals we avoid trying to generalize the format too broadly into specialized areas such as efficient, low-latency delivery, or including unbounded non-time series data. Our presentation will provide an overview of this format and highlight its most valuable characteristics for time series data from any geophysical domain or beyond.

Zooplankton Gut Passage Mobilizes Lithogenic Iron for Ocean Productivity.

PubMed

Schmidt, Katrin; Schlosser, Christian; Atkinson, Angus; Fielding, Sophie; Venables, Hugh J; Waluda, Claire M; Achterberg, Eric P

2016-10-10

Iron is an essential nutrient for phytoplankton, but low concentrations limit primary production and associated atmospheric carbon drawdown in large parts of the world's oceans [1, 2]. Lithogenic particles deriving from aeolian dust deposition, glacial runoff, or river discharges can form an important source if the attached iron becomes dissolved and therefore bioavailable [3-5]. Acidic digestion by zooplankton is a potential mechanism for iron mobilization [6], but evidence is lacking. Here we show that Antarctic krill sampled near glacial outlets at the island of South Georgia (Southern Ocean) ingest large amounts of lithogenic particles and contain 3-fold higher iron concentrations in their muscle than specimens from offshore, which confirms mineral dissolution in their guts. About 90% of the lithogenic and biogenic iron ingested by krill is passed into their fecal pellets, which contain ∼5-fold higher proportions of labile (reactive) iron than intact diatoms. The mobilized iron can be released in dissolved form directly from krill or via multiple pathways involving microbes, other zooplankton, and krill predators. This can deliver substantial amounts of bioavailable iron and contribute to the fertilization of coastal waters and the ocean beyond. In line with our findings, phytoplankton blooms downstream of South Georgia are more intensive and longer lasting during years with high krill abundance on-shelf. Thus, krill crop phytoplankton but boost new production via their nutrient supply. Understanding and quantifying iron mobilization by zooplankton is essential to predict ocean productivity in a warming climate where lithogenic iron inputs from deserts, glaciers, and rivers are increasing [7-10]. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Rhodes, Carl; Morari, Manfred

1997-05-01

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.

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

PubMed

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.

Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 datamore » points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.« less

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

Arctic complexity: a case study on diel vertical migration of zooplankton

PubMed Central

Berge, Jørgen; Cottier, Finlo; Varpe, Øystein; Renaud, Paul E.; Falk-Petersen, Stig; Kwasniewski, Sawomir; Griffiths, Colin; Søreide, Janne E.; Johnsen, Geir; Aubert, Anais; Bjærke, Oda; Hovinen, Johanna; Jung-Madsen, Signe; Tveit, Martha; Majaneva, Sanna

2014-01-01

Diel vertical migration (DVM) of zooplankton is a global phenomenon, characteristic of both marine and limnic environments. At high latitudes, patterns of DVM have been documented, but rather little knowledge exists regarding which species perform this ecologically important behaviour. Also, in the Arctic, the vertically migrating components of the zooplankton community are usually regarded as a single sound scattering layer (SSL) performing synchronized patterns of migration directly controlled by ambient light. Here, we present evidence for hitherto unknown complexity of Arctic marine systems, where zooplankton form multiple aggregations through the water column seen via acoustics as distinct SSLs. We show that while the initiation of DVM during the autumnal equinox is light mediated, the vertical positioning of the migrants during day is linked more to the thermal characteristics of water masses than to irradiance. During night, phytoplankton biomass is shown to be the most important factor determining the vertical positioning of all migrating taxa. Further, we develop a novel way of representing acoustic data in the form of a Sound Image (SI) that enables a direct comparison of the relative importance of each potential scatterer based upon the theoretical contribution of their backscatter. Based on our comparison of locations with contrasting hydrography, we conclude that a continued warming of the Arctic is likely to result in more complex ecotones across the Arctic marine system. PMID:25221372

Abundance, composition, and distribution of crustacean zooplankton in relation to hypolimnetic oxygen depletion in west-central Lake Erie

USGS Publications Warehouse

Heberger, Roy F.; Reynolds, James B.

1977-01-01

Samples of crustacean zooplankton were collected monthly in west-central Lake Erie in April and June to October 1968, and in July and August 1970, before and during periods of hypolimnetic dissolved oxygen (DO) depletion. The water column at offshore stations was thermally stratified from June through September 1968, and the hypolimnion contained no DO in mid-August of 1968 or 1970. Composition, abundance, and vertical distribution of crustacean zooplankton changed coincidentally with oxygen depletion. From July to early August, zooplankton abundance dropped 79% in 1968 and 50% in 1970. The declines were attributed largely to a sharp decrease in abundance of planktonic Cyclops bicuspidatus thomasi. Zooplankton composition shifted from mainly cyclopoid copepods in July to mainly cladocerans and copepod nauplii in middle to late August. We believe that mortality of adults and dormancy of copepodites in response to anoxia was the probable reason for the late summer decline in planktonic C. b. thomasi.

Using Time-Series Regression to Predict Academic Library Circulations.

ERIC Educational Resources Information Center

Brooks, Terrence A.

1984-01-01

Four methods were used to forecast monthly circulation totals in 15 midwestern academic libraries: dummy time-series regression, lagged time-series regression, simple average (straight-line forecasting), monthly average (naive forecasting). In tests of forecasting accuracy, dummy regression method and monthly mean method exhibited smallest average…

JWST NIRCam Time Series Observations

NASA Technical Reports Server (NTRS)

Greene, Tom; Schlawin, E.

2017-01-01

We explain how to make time-series observations with the Near-Infrared camera (NIRCam) science instrument of the James Webb Space Telescope. Both photometric and spectroscopic observations are described. We present the basic capabilities and performance of NIRCam and show examples of how to set its observing parameters using the Space Telescope Science Institute's Astronomer's Proposal Tool (APT).

Time series analysis of InSAR data: Methods and trends

NASA Astrophysics Data System (ADS)

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

2016-05-01

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.

CauseMap: fast inference of causality from complex time series.

PubMed

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

Approximate Entropies for Stochastic Time Series and EKG Time Series of Patients with Epilepsy and Pseudoseizures

NASA Astrophysics Data System (ADS)

Vyhnalek, Brian; Zurcher, Ulrich; O'Dwyer, Rebecca; Kaufman, Miron

2009-10-01

A wide range of heart rate irregularities have been reported in small studies of patients with temporal lobe epilepsy [TLE]. We hypothesize that patients with TLE display cardiac dysautonomia in either a subclinical or clinical manner. In a small study, we have retrospectively identified (2003-8) two groups of patients from the epilepsy monitoring unit [EMU] at the Cleveland Clinic. No patients were diagnosed with cardiovascular morbidities. The control group consisted of patients with confirmed pseudoseizures and the experimental group had confirmed right temporal lobe epilepsy through a seizure free outcome after temporal lobectomy. We quantified the heart rate variability using the approximate entropy [ApEn]. We found similar values of the ApEn in all three states of consciousness (awake, sleep, and proceeding seizure onset). In the TLE group, there is some evidence for greater variability in the awake than in either the sleep or proceeding seizure onset. Here we present results for mathematically-generated time series: the heart rate fluctuations ξ follow the γ statistics i.e., p(ξ)=γ-1(k) ξ^k exp(-ξ). This probability function has well-known properties and its Shannon entropy can be expressed in terms of the γ-function. The parameter k allows us to generate a family of heart rate time series with different statistics. The ApEn calculated for the generated time series for different values of k mimic the properties found for the TLE and pseudoseizure group. Our results suggest that the ApEn is an effective tool to probe differences in statistics of heart rate fluctuations.

FORAGE FISH AND ZOOPLANKTON COMMUNITY COMPOSITION IN WESTERN LAKE SUPERIOR

EPA Science Inventory

We assessed the abundance, size, and species composition of the fish and zooplankton communities of western Lake Superior during 1996 and 1997. Data were analyzed for 3 ecoregions (Duluth-Superior (1), Apostle Islands (2), Minnesota coast (3) differing in lake bathymetry, phsiodo...

Providing web-based tools for time series access and analysis

NASA Astrophysics Data System (ADS)

Eberle, Jonas; Hüttich, Christian; Schmullius, Christiane

2014-05-01

Time series information is widely used in environmental change analyses and is also an essential information for stakeholders and governmental agencies. However, a challenging issue is the processing of raw data and the execution of time series analysis. In most cases, data has to be found, downloaded, processed and even converted in the correct data format prior to executing time series analysis tools. Data has to be prepared to use it in different existing software packages. Several packages like TIMESAT (Jönnson & Eklundh, 2004) for phenological studies, BFAST (Verbesselt et al., 2010) for breakpoint detection, and GreenBrown (Forkel et al., 2013) for trend calculations are provided as open-source software and can be executed from the command line. This is needed if data pre-processing and time series analysis is being automated. To bring both parts, automated data access and data analysis, together, a web-based system was developed to provide access to satellite based time series data and access to above mentioned analysis tools. Users of the web portal are able to specify a point or a polygon and an available dataset (e.g., Vegetation Indices and Land Surface Temperature datasets from NASA MODIS). The data is then being processed and provided as a time series CSV file. Afterwards the user can select an analysis tool that is being executed on the server. The final data (CSV, plot images, GeoTIFFs) is visualized in the web portal and can be downloaded for further usage. As a first use case, we built up a complimentary web-based system with NASA MODIS products for Germany and parts of Siberia based on the Earth Observation Monitor (www.earth-observation-monitor.net). The aim of this work is to make time series analysis with existing tools as easy as possible that users can focus on the interpretation of the results. References: Jönnson, P. and L. Eklundh (2004). TIMESAT - a program for analysing time-series of satellite sensor data. Computers and Geosciences 30

PRESEE: An MDL/MML Algorithm to Time-Series Stream Segmenting

PubMed Central

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. PMID:23956693

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

PubMed

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.

Local normalization: Uncovering correlations in non-stationary financial time series

NASA Astrophysics Data System (ADS)

Schäfer, Rudi; Guhr, Thomas

2010-09-01

The measurement of correlations between financial time series is of vital importance for risk management. In this paper we address an estimation error that stems from the non-stationarity of the time series. We put forward a method to rid the time series of local trends and variable volatility, while preserving cross-correlations. We test this method in a Monte Carlo simulation, and apply it to empirical data for the S&P 500 stocks.

Emergent Macrophytes Support Zooplankton in a Shallow Tropical Lake: A Basis for Wetland Conservation

NASA Astrophysics Data System (ADS)

Gebrehiwot, Mesfin; Kifle, Demeke; Triest, Ludwig

2017-12-01

Understanding the biodiversity value of littoral zones of lakes is a priority for aquatic biodiversity conservation. However, less emphasis has been given to the littoral part of tropical African lakes, with many of the previous researches focusing only on the open water side. The aim of the present study was, therefore, to investigate the impact of the littoral zone of a shallow freshwater tropical lake (Ziway, Ethiopia), dominated by two emergent macrophytes, on zooplankton community structure. We hypothesized that the wetland vegetation serves as a preferred microhabitat for zooplankton communities. A lake with substantial coverage of emergent macrophytes was monitored monthly from January to August, 2016. The monitoring included the measurements of physical, chemical, and biological parameters. Sampling sites were selected to represent areas of the macrophyte vegetation ( Typha latifolia and Phragmites australis) and the open water part of the lake. Sites with macrophyte vegetation were found to be the home of more dense and diverse zooplankton community. However, during the period of high vegetation loss, the density of crustacean zooplankton showed significant reduction within the patches of macrophytes. From biodiversity conservation perspective, it was concluded that the preservation of such small areas of macrophytes covering the littoral zone of lakes could be as important as protecting the whole lake. However, the rapid degradation of wetland vegetation by human activities is a real threat to the lake ecosystem. In the not-too-far future, it could displace and evict riparian vegetation and the biota it supports.

Bacterial bioluminescence as a lure for marine zooplankton and fish

PubMed Central

Zarubin, Margarita; Belkin, Shimshon; Ionescu, Michael; Genin, Amatzia

2012-01-01

The benefits of bioluminescence for nonsymbiotic marine bacteria have not been elucidated fully. One of the most commonly cited explanations, proposed more than 30 y ago, is that bioluminescence augments the propagation and dispersal of bacteria by attracting fish to consume the luminous material. This hypothesis, based mostly on the prevalence of luminous bacteria in fish guts, has not been tested experimentally. Here we show that zooplankton that contacts and feeds on the luminescent bacterium Photobacterium leiognathi starts to glow, and demonstrate by video recordings that glowing individuals are highly vulnerable to predation by nocturnal fish. Glowing bacteria thereby are transferred to the nutritious guts of fish and zooplankton, where they survive digestion and gain effective means for growth and dispersal. Using bioluminescence as bait appears to be highly beneficial for marine bacteria, especially in food-deprived environments of the deep sea. PMID:22203999

Fuzzy time-series based on Fibonacci sequence for stock price forecasting

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

2007-07-01

Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

Sound scattering by several zooplankton groups. II. Scattering models.

PubMed

Stanton, T K; Chu, D; Wiebe, P H

1998-01-01

Mathematical scattering models are derived and compared with data from zooplankton from several gross anatomical groups--fluidlike, elastic shelled, and gas bearing. The models are based upon the acoustically inferred boundary conditions determined from laboratory backscattering data presented in part I of this series [Stanton et al., J. Acoust. Soc. Am. 103, 225-235 (1998)]. The models use a combination of ray theory, modal-series solution, and distorted wave Born approximation (DWBA). The formulations, which are inherently approximate, are designed to include only the dominant scattering mechanisms as determined from the experiments. The models for the fluidlike animals (euphausiids in this case) ranged from the simplest case involving two rays, which could qualitatively describe the structure of target strength versus frequency for single pings, to the most complex case involving a rough inhomogeneous asymmetrically tapered bent cylinder using the DWBA-based formulation which could predict echo levels over all angles of incidence (including the difficult region of end-on incidence). The model for the elastic shelled body (gastropods in this case) involved development of an analytical model which takes into account irregularities and discontinuities of the shell. The model for gas-bearing animals (siphonophores) is a hybrid model which is composed of the summation of the exact solution to the gas sphere and the approximate DWBA-based formulation for arbitrarily shaped fluidlike bodies. There is also a simplified ray-based model for the siphonophore. The models are applied to data involving single pings, ping-to-ping variability, and echoes averaged over many pings. There is reasonable qualitative agreement between the predictions and single ping data, and reasonable quantitative agreement between the predictions and variability and averages of echo data.

Comparison of airborne lidar measurements with 420 kHz echo-sounder measurements of zooplankton.

PubMed

Churnside, James H; Thorne, Richard E

2005-09-10

Airborne lidar has the potential to survey large areas quickly and at a low cost per kilometer along a survey line. For this reason, we investigated the performance of an airborne lidar for surveys of zooplankton. In particular, we compared the lidar returns with echo-sounder measurements of zooplankton in Prince William Sound, Alaska. Data from eight regions of the Sound were compared, and the correlation between the two methods was 0.78. To obtain this level of agreement, a threshold was applied to the lidar return to remove the effects of scattering from phytoplankton.

Analyses of Inhomogeneities in Radiosonde Temperature and Humidity Time Series.

NASA Astrophysics Data System (ADS)

Zhai, Panmao; Eskridge, Robert E.

1996-04-01

Twice daily radiosonde data from selected stations in the United States (period 1948 to 1990) and China (period 1958 to 1990) were sorted into time series. These stations have one sounding taken in darkness and the other in sunlight. The analysis shows that the 0000 and 1200 UTC time series are highly correlated. Therefore, the Easterling and Peterson technique was tested on the 0000 and 1200 time series to detect inhomogeneities and to estimate the size of the biases. Discontinuities were detected using the difference series created from the 0000 and 1200 UTC time series. To establish that the detected bias was significant, a t test was performed to confirm that the change occurs in the daytime series but not in the nighttime series.Both U.S. and Chinese radiosonde temperature and humidity data include inhomogeneities caused by changes in radiosonde sensors and observation times. The U.S. humidity data have inhomogeneities that were caused by instrument changes and the censoring of data. The practice of reporting relative humidity as 19% when it is lower than 20% or the temperature is below 40°C is called censoring. This combination of procedural and instrument changes makes the detection of biases and adjustment of the data very difficult. In the Chinese temperatures, them are inhomogeneities related to a change in the radiation correction procedure.Test results demonstrate that a modified Easterling and Peterson method is suitable for use in detecting and adjusting time series radiosonde data.Accurate stations histories are very desirable. Stations histories can confirm that detected inhomogeneities are related to instrument or procedural changes. Adjustments can then he made to the data with some confidence.

Self-organising mixture autoregressive model for non-stationary time series modelling.

PubMed

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

Aggregated Indexing of Biomedical Time Series Data

PubMed Central

Woodbridge, Jonathan; Mortazavi, Bobak; Sarrafzadeh, Majid; Bui, Alex A.T.

2016-01-01

Remote and wearable medical sensing has the potential to create very large and high dimensional datasets. Medical time series databases must be able to efficiently store, index, and mine these datasets to enable medical professionals to effectively analyze data collected from their patients. Conventional high dimensional indexing methods are a two stage process. First, a superset of the true matches is efficiently extracted from the database. Second, supersets are pruned by comparing each of their objects to the query object and rejecting any objects falling outside a predetermined radius. This pruning stage heavily dominates the computational complexity of most conventional search algorithms. Therefore, indexing algorithms can be significantly improved by reducing the amount of pruning. This paper presents an online algorithm to aggregate biomedical times series data to significantly reduce the search space (index size) without compromising the quality of search results. This algorithm is built on the observation that biomedical time series signals are composed of cyclical and often similar patterns. This algorithm takes in a stream of segments and groups them to highly concentrated collections. Locality Sensitive Hashing (LSH) is used to reduce the overall complexity of the algorithm, allowing it to run online. The output of this aggregation is used to populate an index. The proposed algorithm yields logarithmic growth of the index (with respect to the total number of objects) while keeping sensitivity and specificity simultaneously above 98%. Both memory and runtime complexities of time series search are improved when using aggregated indexes. In addition, data mining tasks, such as clustering, exhibit runtimes that are orders of magnitudes faster when run on aggregated indexes. PMID:27617298

Space Object Classification Using Fused Features of Time Series Data

NASA Astrophysics Data System (ADS)

Jia, B.; Pham, K. D.; Blasch, E.; Shen, D.; Wang, Z.; Chen, G.

In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.

Indispensable finite time corrections for Fokker-Planck equations from time series data.

PubMed

Ragwitz, M; Kantz, H

2001-12-17

The reconstruction of Fokker-Planck equations from observed time series data suffers strongly from finite sampling rates. We show that previously published results are degraded considerably by such effects. We present correction terms which yield a robust estimation of the diffusion terms, together with a novel method for one-dimensional problems. We apply these methods to time series data of local surface wind velocities, where the dependence of the diffusion constant on the state variable shows a different behavior than previously suggested.

Relating the large-scale structure of time series and visibility networks.

PubMed

Rodríguez, Miguel A

2017-06-01

The structure of time series is usually characterized by means of correlations. A new proposal based on visibility networks has been considered recently. Visibility networks are complex networks mapped from surfaces or time series using visibility properties. The structures of time series and visibility networks are closely related, as shown by means of fractional time series in recent works. In these works, a simple relationship between the Hurst exponent H of fractional time series and the exponent of the distribution of edges γ of the corresponding visibility network, which exhibits a power law, is shown. To check and generalize these results, in this paper we delve into this idea of connected structures by defining both structures more properly. In addition to the exponents used before, H and γ, which take into account local properties, we consider two more exponents that, as we will show, characterize global properties. These are the exponent α for time series, which gives the scaling of the variance with the size as var∼T^{2α}, and the exponent κ of their corresponding network, which gives the scaling of the averaged maximum of the number of edges, 〈k_{M}〉∼N^{κ}. With this representation, a more precise connection between the structures of general time series and their associated visibility network is achieved. Similarities and differences are more clearly established, and new scaling forms of complex networks appear in agreement with their respective classes of time series.

Nonlinear time-series-based adaptive control applications

NASA Technical Reports Server (NTRS)

Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.

1991-01-01

A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.

The Prediction of Teacher Turnover Employing Time Series Analysis.

ERIC Educational Resources Information Center

Costa, Crist H.

The purpose of this study was to combine knowledge of teacher demographic data with time-series forecasting methods to predict teacher turnover. Moving averages and exponential smoothing were used to forecast discrete time series. The study used data collected from the 22 largest school districts in Iowa, designated as FACT schools. Predictions…

Detection of "noisy" chaos in a time series

NASA Technical Reports Server (NTRS)

Chon, K. H.; Kanters, J. K.; Cohen, R. J.; Holstein-Rathlou, N. H.

1997-01-01

Time series from biological system often displays fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". The output from most biological systems is probably the result of both the internal dynamics of the systems, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

The Value of Interrupted Time-Series Experiments for Community Intervention Research

PubMed Central

Biglan, Anthony; Ary, Dennis; Wagenaar, Alexander C.

2015-01-01

Greater use of interrupted time-series experiments is advocated for community intervention research. Time-series designs enable the development of knowledge about the effects of community interventions and policies in circumstances in which randomized controlled trials are too expensive, premature, or simply impractical. The multiple baseline time-series design typically involves two or more communities that are repeatedly assessed, with the intervention introduced into one community at a time. It is particularly well suited to initial evaluations of community interventions and the refinement of those interventions. This paper describes the main features of multiple baseline designs and related repeated-measures time-series experiments, discusses the threats to internal validity in multiple baseline designs, and outlines techniques for statistical analyses of time-series data. Examples are given of the use of multiple baseline designs in evaluating community interventions and policy changes. PMID:11507793

Recurrent Neural Networks for Multivariate Time Series with Missing Values.

PubMed

Che, Zhengping; Purushotham, Sanjay; Cho, Kyunghyun; Sontag, David; Liu, Yan

2018-04-17

Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values. In time series prediction and other related tasks, it has been noted that missing values and their missing patterns are often correlated with the target labels, a.k.a., informative missingness. There is very limited work on exploiting the missing patterns for effective imputation and improving prediction performance. In this paper, we develop novel deep learning models, namely GRU-D, as one of the early attempts. GRU-D is based on Gated Recurrent Unit (GRU), a state-of-the-art recurrent neural network. It takes two representations of missing patterns, i.e., masking and time interval, and effectively incorporates them into a deep model architecture so that it not only captures the long-term temporal dependencies in time series, but also utilizes the missing patterns to achieve better prediction results. Experiments of time series classification tasks on real-world clinical datasets (MIMIC-III, PhysioNet) and synthetic datasets demonstrate that our models achieve state-of-the-art performance and provide useful insights for better understanding and utilization of missing values in time series analysis.

Inference of scale-free networks from gene expression time series.

PubMed

Daisuke, Tominaga; Horton, Paul

2006-04-01

Quantitative time-series observation of gene expression is becoming possible, for example by cell array technology. However, there are no practical methods with which to infer network structures using only observed time-series data. As most computational models of biological networks for continuous time-series data have a high degree of freedom, it is almost impossible to infer the correct structures. On the other hand, it has been reported that some kinds of biological networks, such as gene networks and metabolic pathways, may have scale-free properties. We hypothesize that the architecture of inferred biological network models can be restricted to scale-free networks. We developed an inference algorithm for biological networks using only time-series data by introducing such a restriction. We adopt the S-system as the network model, and a distributed genetic algorithm to optimize models to fit its simulated results to observed time series data. We have tested our algorithm on a case study (simulated data). We compared optimization under no restriction, which allows for a fully connected network, and under the restriction that the total number of links must equal that expected from a scale free network. The restriction reduced both false positive and false negative estimation of the links and also the differences between model simulation and the given time-series data.

Trophic pathways of phytoplankton size classes through the zooplankton food web over the spring transition period in the north-west Mediterranean Sea

NASA Astrophysics Data System (ADS)

Hunt, Brian P. V.; Carlotti, François; Donoso, Katty; Pagano, Marc; D'Ortenzio, Fabrizio; Taillandier, Vincent; Conan, Pascal

2017-08-01

Knowledge of the relative contributions of phytoplankton size classes to zooplankton biomass is necessary to understand food-web functioning and response to climate change. During the Deep Water formation Experiment (DEWEX), conducted in the north-west Mediterranean Sea in winter (February) and spring (April) of 2013, we investigated phytoplankton-zooplankton trophic links in contrasting oligotrophic and eutrophic conditions. Size fractionated particulate matter (pico-POM, nano-POM, and micro-POM) and zooplankton (64 to >4000 μm) composition and carbon and nitrogen stable isotope ratios were measured inside and outside the nutrient-rich deep convection zone in the central Liguro-Provencal basin. In winter, phytoplankton biomass was low (0.28 mg m-3) and evenly spread among picophytoplankton, nanophytoplankton, and microphytoplankton. Using an isotope mixing model, we estimated average contributions to zooplankton biomass by pico-POM, nano-POM, and micro-POM of 28, 59, and 15%, respectively. In spring, the nutrient poor region outside the convection zone had low phytoplankton biomass (0.58 mg m-3) and was dominated by pico/nanophytoplankton. Estimated average contributions to zooplankton biomass by pico-POM, nano-POM, and micro-POM were 64, 28 and 10%, respectively, although the model did not differentiate well between pico-POM and nano-POM in this region. In the deep convection zone, spring phytoplankton biomass was high (1.34 mg m-3) and dominated by micro/nano phytoplankton. Estimated average contributions to zooplankton biomass by pico-POM, nano-POM, and micro-POM were 42, 42, and 20%, respectively, indicating that a large part of the microphytoplankton biomass may have remained ungrazed.