Dataset Information

Comprehensive model of annual plankton succession based on the whole-plankton time series approach.

ABSTRACT: Ecological succession provides a widely accepted description of seasonal changes in phytoplankton and mesozooplankton assemblages in the natural environment, but concurrent changes in smaller (i.e. microbes) and larger (i.e. macroplankton) organisms are not included in the model because plankton ranging from bacteria to jellies are seldom sampled and analyzed simultaneously. Here we studied, for the first time in the aquatic literature, the succession of marine plankton in the whole-plankton assemblage that spanned 5 orders of magnitude in size from microbes to macroplankton predators (not including fish or fish larvae, for which no consistent data were available). Samples were collected in the northwestern Mediterranean Sea (Bay of Villefranche) weekly during 10 months. Simultaneously collected samples were analyzed by flow cytometry, inverse microscopy, FlowCam, and ZooScan. The whole-plankton assemblage underwent sharp reorganizations that corresponded to bottom-up events of vertical mixing in the water-column, and its development was top-down controlled by large gelatinous filter feeders and predators. Based on the results provided by our novel whole-plankton assemblage approach, we propose a new comprehensive conceptual model of the annual plankton succession (i.e. whole plankton model) characterized by both stepwise stacking of four broad trophic communities from early spring through summer, which is a new concept, and progressive replacement of ecological plankton categories within the different trophic communities, as recognised traditionally.

SUBMITTER: Romagnan JB

PROVIDER: S-EPMC4363592 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Comprehensive model of annual plankton succession based on the whole-plankton time series approach.

Romagnan Jean-Baptiste JB Legendre Louis L Guidi Lionel L Jamet Jean-Louis JL Jamet Dominique D Mousseau Laure L Pedrotti Maria-Luiza ML Picheral Marc M Gorsky Gabriel G Sardet Christian C Stemmann Lars L

PloS one 20150317 3

Ecological succession provides a widely accepted description of seasonal changes in phytoplankton and mesozooplankton assemblages in the natural environment, but concurrent changes in smaller (i.e. microbes) and larger (i.e. macroplankton) organisms are not included in the model because plankton ranging from bacteria to jellies are seldom sampled and analyzed simultaneously. Here we studied, for the first time in the aquatic literature, the succession of marine plankton in the whole-plankton ass ...[more]

PMID: 25780912

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Project description:In this paper, we introduce a novel model selection approach to time series forecasting. For linear stationary processes, such as AR processes, the direction of time is independent of the model parameters. By combining theoretical principles of time-reversibility in time series with conventional modeling approaches such as information criteria, we construct a criterion that employs the backwards prediction (backcast) as a proxy for the forecast. Hereby, we aim to adopt a theoretically grounded, data-driven approach to model selection. The novel criterion is named the backwards validated information criterion (BVIC). The BVIC identifies suitable models by trading off a measure of goodness-of-fit and a models ability to predict backwards. We test the performance of the BVIC by conducting experiments on synthetic and real data. In each experiment, the BVIC is examined in contrast to conventionally employed criteria. Our experimental results suggest that the BVIC has comparable performance as conventional information criteria. Specifically, in most of the experiments performed, we did not find statistically significant differences between the forecast error of the BVIC under certain parameterizations and that of the different information criteria. Nonetheless, it is worth emphasizing that the BVIC guarantees are established by design where the model order penalization term depends on strong mathematical properties of time-reversible time series forecasting properties and a finite data assessment. In particular, the penalization term is replaced by a weighted trade-off between functional dimensions pertaining to forecasting.That said, we observed that the BVIC recovered more accurately the real order of the underlying process than the other criteria, which rely on a static penalization of the model order. Lastly, leveraging the latter property we perform the assessment of the order model (or, memory) of time series pertaining to epileptic seizures recorded using electrocorticographic data. Our results provide converging evidence that the order of the model increases during the epileptic events.

Project description:Despite progress understanding microbial communities involved in terrestrial vertebrate decomposition, little is known about the microbial decomposition of aquatic vertebrates from a functional and environmental context. Here, we analyzed temporal changes in the "necrobiome" of rainbow darters, which are common North American fish that are sensitive indicators of water quality. By combining 16S rRNA gene and shotgun metagenomic sequence data from four time points, we studied the progression of decomposers from both taxonomic and functional perspectives. The 16S rRNA gene profiles revealed strong community succession, with early decomposition stages associated with Aeromonas and Clostridium taxa and later stages dominated by members of the Rikenellaceae (i.e., Alistipes/Acetobacteroides genera). These results were reproducible and independent of environmental perturbation, given that exposure to wastewater treatment plant effluent did not substantially influence the necrobiome composition of fish or the associated water sample microbiota. Metagenomic analysis revealed significant changes throughout decomposition in degradation pathways for amino acids, carbohydrates/glycans, and other compounds, in addition to putrefaction pathways for production of putrescine, cadaverine, and indole. Binning of contigs confirmed a predominance of Aeromonas genome assemblies, including those from novel strains related to the pathogen Aeromonas veronii These bins of Aeromonas genes also encoded known hemolysin toxins (e.g., aerolysin) that were particularly abundant early in the process, potentially contributing to host cell lysis during decomposition. Overall, our results demonstrate that wild-caught fish have a reproducible decomposer succession and that the fish necrobiome serves as a potential source of putative pathogens and toxigenic bacteria.IMPORTANCE The microbial decomposition of animal tissues is an important ecological process that impacts nutrient cycling in natural environments. We studied the microbial decomposition of a common North American fish (rainbow darters) over four time points, combining 16S rRNA gene and shotgun metagenomic sequence data to obtain both taxonomic and functional perspectives. Our data revealed a strong community succession that was reproduced across different fish and environments. Decomposition time point was the main driver of community composition and functional potential; fish environmental origin (upstream or downstream of a wastewater treatment plant) had a secondary effect. We also identified strains related to the putative pathogen Aeromonas veronii as dominant members of the decomposition community. These bacteria peaked early in decomposition and coincided with the metagenomic abundance of hemolytic toxin genes. Our work reveals a strong decomposer succession in wild-caught fish, providing functional and taxonomic insights into the vertebrate necrobiome.

Dataset Information

Comprehensive model of annual plankton succession based on the whole-plankton time series approach.

Publications

Comprehensive model of annual plankton succession based on the whole-plankton time series approach.

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