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451 results for “food webs”
Data from: Seasonal shifts in trophic interaction strength drive stability of natural food webs
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Data from: Functional diversity buffers the effects of a pulse perturbation on the dynamics of tritrophic food webs
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Agriculture land-use change seasonally rewires stream food webs: A case study from headwater streams in the Lake Erie watershed
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Scripts and data for: Integrating different facets of diversity into food web models: how adaptation among and within functional groups shape ecosystem functioning
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Data from: Parasite-mediated changes in host traits alter food web dynamics
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Lake food webs: Species invasion progressively disrupts the trophic structure of native food webs
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Data for: Generalist invasion in a complex lake food web
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Long-term data reveal widespread phenological change across major U.S. estuarine food webs
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Quebec Ministry of Agriculture, Fisheries and Food from 2012-2018 web archive collection derivatives
<p>Web archive derivatives of the Quebec Ministry of Agriculture, Fisheries and Food from 2012-2018 collection from the <a href="https://www.banq.qc.ca/accueil/">Bibliothèque et Archives nationales du Québec</a>. The derivatives were created with the <a href="https://github.com/archivesunleashed/aut/">Archives Unleashed Toolkit</a>. Merci beaucoup BAnQ!</p> <p>These derivatives are in the <a href="https://parquet.apache.org/">Apache Parquet format</a>, which is a <a href="http://en.wikipedia.org/wiki/Column-oriented_DBMS">columnar storage</a> format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See <a href="https://github.com/archivesunleashed/notebooks/blob/master/parquet_pandas_example.ipynb">this</a> notebook for examples.</p> <p><strong>Domains</strong></p> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>domain</li> <li>count</li> </ul> <p><strong>Web Pages</strong></p> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>crawl_date</li> <li>url</li> <li>mime_type_web_server</li> <li>mime_type_tika</li> <li>content</li> </ul> <p><strong>Web Graph</strong></p> <pre><code class="language-java">.webgraph()</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>crawl_date</li> <li>src</li> <li>dest</li> <li>anchor</li> </ul> <p><strong>Image Links</strong></p> <pre><code class="language-java">.imageLinks()</code></pre> <p>Produces a DataFrame with the following columns:</p> <ul> <li>src</li> <li>image_url</li> </ul> <p><a href="https://github.com/archivesunleashed/aut-docs/blob/master/current/binary-analysis.md#binary-analysis"><strong>Binary Analysis</strong></a></p> <ul> <li>Audio</li> <li>Images</li> <li>PDFs</li> <li>Presentation program files</li> <li>Spreadsheets</li> <li>Text files</li> <li>Videos</li> <li>Word processor files</li> </ul>
Reconstructing marine plankton food web interactions using DNA metabarcoding - Supplementary Dataset
<p>### This repository contains two separate datasets:</p> <p>1. *16S rRNA* gene dataset and<br> 2. *18S rRNA* gene dataset.</p> <p> </p> <p><br> ### The data is stored as ASV-file</p> <p>(Amplicon sequence variants) including:</p> <p>1. Exact sequence of ASV<br> 2. Taxonomic afiliation<br> 3. Read count matrix per sample sequencing library.</p> <p> </p> <p><br> ### Each dataset comes with a metadata-file.</p> <p>The metadata files contains the following variables:</p> <p>- **NGI.-Sample_ID** The Unique Sequenceing Library ID.<br> - **SAMPLE_ID** Identification of environmental *In_Situ* sample event.<br> - **SAMPLE_date** Date of sampling (YYY-MM-DD).<br> - **SAMPLE_type** Type of sample (Water or Zooplankton).<br> - **SAMPLE_method** Device used for sampling *In-Situ*.<br> - **SAMPLE_depth** Depth of sampling.<br> - **GENE** Marker gene.<br> - **INNER_primer** Primer pair ID used for PCR.<br> - **INNER_blocking** Weather blocking PNA has been used for PCR or not.</p> <p>For Zooplankton saples:<br> <br> - **SORTED_type** Taxonomic affiliation of Zooplankton (Blank for water samples).<br> - **SORTED_genus** Genus of sorted Zooplankton species (Blank for water samples).<br> - **SORTED_number** Number of individuals sorted in the sample.<br> <br> For Water samples:<br> <br> - **FILTER_poresize** Size in micrometer.<br> - **FILTER_material**<br> - **FILTER_volume** Volume of water filtered (L).</p>
The seventh macronutrient: how sodium shortfall ramifies through populations, food webs, and ecosystems
<p>Of the 25 elements required to build most organisms, sodium has a unique set of characteristics that ramify through terrestrial ecology. In plants, sodium is found in low concentrations and has little metabolic function; in plant consumers, particularly animals, sodium is essential to running costly Na-K ATPases. Here I synthesize a diverse literature from physiology, agronomy, and ecology, toward identifying sodium's place as the "7th macronutrient", one whose shortfall targets two trophic levels—herbivores and detritivores. I propose that sodium also plays a central, though unheralded role in herbivore digestion, via its importance to maintaining microbiomes and denaturing tannins. I highlight how sodium availability is a key determinant of consumer abundance and the geography of herbivory and detritivory. And I propose a re-appraisal of the assumption that, because sodium is metabolically unimportant to most plants, it is of little use. Instead, I suggest that sodium's critical role in limiting herbivore performance makes it a commodity used by plants to manipulate their herbivores and mutualists, and by consumers like bison and elephants to generate grazing lawns: dependable sources of sodium.</p>
Data supporting Food web complexity weakens size-based constraints on the pyramids of life
<p>Marine ecosystems are generally expected to have bottom-heavy trophic structure (more plants than animals) due to size-based constraints arising from increased metabolic requirements and inefficient energy transfer. However, size-based (allometric) approaches are often limited to confined trophic level windows where energy transfer is predicted by size alone, and are constrained to bottom-up control at steady state. In real food webs, energy flow is more complex and top-down processes can also shape trophic structure. We expand size-based theory to account for complex food webs, and show that moderate levels of food web connectance allow for inverted trophic structure more often than predicted, especially in marine ecosystems. Trophic structure inversion occurs due to incorporation of complex energy pathways and top-down effects on ecosystems. Our results suggest that marine ecosystems should be top-heavy, and observed bottom-heavy trophic structure may be a result of human defaunation of the ocean that has been more extreme than presently recognized.</p>
Data from: Feeding environment and other traits shape species' roles in marine food webs
Food webs and meso-scale motifs allow us to understand the structure of ecological communities and define species' roles within them. This species-level perspective on networks permits tests for relationships between species' traits and their patterns of direct and indirect interactions. Such relationships could allow us to predict food-web structure based on more easily-obtained trait information. Here we calculated the roles of species (as vectors of motif position frequencies) in six well-resolved marine food webs and identified the motif positions associated with the greatest variation in species' roles. We then tested whether the frequencies of these positions varied with species' traits. Despite the coarse-grained traits we used, our approach identified several strong associations between traits and motifs. Feeding environment was a key trait in our models and may shape species' roles by affecting encounter probabilities. Incorporating environment into future food web models may improve predictions of an unknown network structure.
Eco‐evolutionary dynamics driven by fishing: from single species models to dynamic evolution within complex food webs
<p>Evidence of contemporary evolution across ecological time scales stimulated research on the eco-evolutionary dynamics of natural populations. Aquatic systems provide a good setting to study eco-evolutionary dynamics owing to a wealth of long-term monitoring data and the detected trends in fish life-history traits across intensively harvested marine and freshwater systems. In the present study, we focus on modelling approaches to simulate eco-evolutionary dynamics of fishes and their ecosystems. Firstly, we review the development of modelling from single-species to multispecies approaches. Secondly, we advance the current state-of-the-art methodology by implementing evolution of life-history traits of a top predator into the context of complex food web dynamics as described by the allometric trophic network (ATN) framework. The functioning of our newly developed eco-evolutionary ATNE framework is illustrated using a well-studied lake food web. Our simulations show how both natural selection arising from feeding interactions and size-selective fishing cause evolutionary changes in the top predator and how those feed back to its prey species and further cascade down to lower trophic levels. Finally, we discuss future directions, particularly the need to integrate genomic discoveries into eco-evolutionary projections.</p>
Data from: Unveiling the food webs of tetrapods across Europe through the prism of the Eltonian niche
<p>Aim</p> <p>Despite the recent calls on integrating the interaction networks into the study of large‐scale biodiversity patterns, we still lack a basic understanding of the functional characteristics of large interaction networks and how they are structured across environments. Here, building on recent advances in network science around the Eltonian niche concept, we aim to characterize the trophic groups in a large food web, and understand how these trophic groups vary across space.</p> <p>Location</p> <p>Europe and Anatolia.</p> <p>Taxon</p> <p>Tetrapods (1,136 species).</p> <p>Methods</p> <p>We combined an expert‐based metaweb of all European tetrapods with their spatial distributions and biological traits. To understand the functional structure of the metaweb, we first used a stochastic block model to group species with similar Eltonian niches, and then analysed these groups with species' functional traits and network metrics. We then combined these groups with species distributions to understand how trophic diversity varies across space, in function of the environment, and between the European ecoregions.</p> <p>Results</p> <p>We summarized the 1,136 interacting species within the metaweb into 46 meaningful trophic groups of species with a similar role in the metaweb. Specific aspects of the ecology of species, such as their activity time, nesting habitat and diet explained these trophic groups. Across space, trophic diversity was driven by both biotic and abiotic factors (species richness, climate and primary productivity), and the representation of trophic groups differed among European ecoregions.</p> <p>Main conclusions</p> <p>We have characterized the Eltonian niche of species in a large food web, both in terms of species interactions and functional traits, and then using this to understand the spatial variation of food webs at a functional level, thus bringing together network science, functional ecology and biogeography. Our results highlight the need to integrate multiple aspects of species ecology in global change research. Further, our approach is strongly relevant for conservation biology as it could help predict the impact of species translocations on trophic diversity.</p>
Legacy effect of grazing intensity mediates the bottom-up controls of resource addition on soil food webs
<p>1. Large-scale studies have demonstrated that nitrogen (N) and water (W) availability greatly affect terrestrial ecosystems worldwide, and this is especially true for the resource-poor semi-arid grasslands. Yet, experimental evidence is lacking for how N and W availability affect soil food webs across historical grazing intensity-altered environments at a local scale.</p> <p>2. Here, we included N- and W-addition treatments in an 8-year grazing experiment (with four grazing intensities) to determine how the legacy effects of grazing intensity mediate the responses of key components of soil food webs (plants, microorganisms, and nematodes) to resource addition in a semi-arid grassland.</p> <p>3. After 4 years of N- and W-addition treatments (with no grazing during that 4-year period), we found that a legacy of grazing, even light grazing, had significant negative effects on the components of plant community and soil food webs. Both N and W addition increased above- and below-ground plant biomass, especially under moderate and heavy grazing. N addition had negative effects on the biomass of bacteria under no grazing, while W addition increased the biomass of actinomycetes under light grazing. N addition decreased the abundance of omnivorous + carnivorous nematodes under light and heavy grazing, while W addition increased their abundance under heavy grazing. Overall, the effects of resource addition on soil food webs progressively decreased from the lowest trophic level (primary producers, i.e., plants), to intermediate tropic levels (microorganisms and root-feeding nematodes), to higher trophic levels (microbial-feeding nematodes and omnivorous + carnivorous nematodes).</p> <p>4. Synthesis and applications. Our results, which are the first data concerning the effects of resource addition on key components of soil food webs across a historical grazing-induced environmental gradient, show that the strong bottom-up controls of resource addition on soil food webs are mediated by the legacy of grazing intensity. These finding should be useful for predicting the responses of grassland ecosystems to future climate change and suggest that the recovery of degraded grasslands will require more than restoration measure of resource inputs alone.</p>
Data from: Climate change-driven regime shifts in a planktonic food web
<p>Predicting how food webs will respond to global environmental change is difficult because of the complex interplay between the abiotic forcing and biotic interactions. Mechanistic models of species interactions in seasonal environments can help understand the effects of global change in different ecosystems. Seasonally ice-covered lakes are warming faster than many other ecosystems and undergoing pronounced food web changes, making the need to forecast those changes especially urgent. Using a seasonally forced food web model with a generalist zooplankton grazer and competing cold-adapted winter and warm-adapted summer phytoplankton, we show that with declining ice cover, the food web moves through different dynamic regimes, from annual to biennial cycles, with decreasing and then disappearing winter phytoplankton blooms and a shift of maximum biomass to summer season. Interestingly, when predator-prey interactions were not included, a declining ice cover did not cause regime shifts, suggesting that both are needed for regime transitions. A cluster analysis of long-term data from Lake Baikal, Siberia supports model results, revealing a change from regularly occurring winter blooms of endemic diatoms to less-frequent winter bloom years with decreasing ice cover. Together, the results show that even gradual environmental change, such as declining ice cover duration, may cause discontinuous or abrupt transitions between dynamic regimes in food webs.</p>
Data from: Food webs obscure the strength of plant diversity effects on primary productivity
Plant diversity experiments generally find that increased diversity causes increased productivity; however, primary productivity is typically measured in the presence of a diverse food web, including pathogens, mutualists and herbivores. If food web impacts on productivity vary with plant diversity, as predicted by both theoretical and empirical studies, estimates of the effect of plant diversity on productivity may be biased. We experimentally removed arthropods, foliar fungi and soil fungi from the longest-running plant diversity experiment. We found that fungi and arthropods removed a constant, large proportion of biomass leading to a greater reduction of total biomass in high diversity plots. As a result, the effect of diversity on measured plant productivity was much higher in the absence of fungi and arthropods. Thus, diversity increases productivity more than reported in previous studies that did not control for the effects of heterotrophic consumption.
Data from: Ecosystem function in predator-prey food webs - confronting dynamic models with empirical data
1. Most ecosystem functions and related services involve species interactions across trophic levels, e.g. pollination and biological pest control. Despite this, our understanding of ecosystem function in multi-trophic communities is poor, and research has been limited to either manipulations in small communities or statistical descriptions in larger ones. 2. Recent advances in food web ecology may allow us to overcome the trade-off between mechanistic insight and ecological realism. Molecular tools now simplify the detection of feeding interactions, and trait-based approaches allow the application of dynamic food web models to real ecosystems. We performed the first test of an allometric food web model's ability to replicate temporally non-aggregated abundance data from the field, and to provide mechanistic insight into the function of predation. 3. We aimed to reproduce and explore the drivers of the population dynamics of the aphid herbivore Rhopalosiphum padi observed in ten Swedish barley fields. We used a dynamic food web model, taking observed interactions and abundances of predators and alternative prey as input data, allowing us to examine the role of predation in aphid population control. The inverse problem methods were used for simultaneous model fit optimization and model parameterization. 4. The model captured >70% of the variation in aphid abundance in five of ten fields, supporting the model-embodied hypothesis that body-size can be an important determinant of predation in the arthropod community. We further demonstrate how in-depth model analysis can disentangle the likely drivers of function, such as the community's abundance and trait composition. Analyzing the variability in model performance revealed knowledge gaps, such as the source of episodic aphid mortality, and general method development needs that, if addressed, would further increase model success and enable stronger inference about ecosystem function. 5. The results demonstrate that confronting dynamic food web models with abundance data from the field is a viable approach to evaluate ecological theory and to aid our understanding of function in real ecosystems. However, to realize the full potential of food web models, in ecosystem function research and beyond, trait-based parameterization must be refined and extended to include more traits than body size.
Data from: Integrating abundance and diet data to improve inferences of food web dynamics
1. Both population abundances and chemical tracers are useful tools for studying consumer-resource interactions. Food web models parameterized with abundances are often used to understand how interactions structure communities and to inform management decisions of complex ecological systems. Unfortunately, collecting abundance data to parameterize these models is often expensive and time-consuming. Another approach is to use chemical tracers to estimate the proportional diets of consumers by relating the tracers in their tissues to those found in their food sources. Although tracer data are often inexpensive to collect relative to abundances, diet proportions provide little information on the per-capita consumption rates of consumers. Here, we show how integrating these data sources can be used to better estimate of consumption rates. 2. Our modeling approach informs traditional multispecies population abundance models using proportional diet data. We used simulations to determine whether integrated food web datasets were more informative than traditional abundance datasets and demonstrated the use of our integrated approach by estimating consumption rates of humpback whales (\textit{Megaptera novaeangliae}) in the western Gulf of Alaska using abundances coupled with stable isotopes as a tracer. 3. Our simulations demonstrated that integrated models improved the ability to resolve alternative hypotheses about the functional response and yielded more precise parameter estimates relative to standard food web models. The integrated data approach was especially informative under low sample sizes or high process variance. Our application of the integrated modeling approach to humpback whale indicated that fish averaged about 25\% of whale diets, though this proportion declined over the course of the study. We also found that traditional abundance model estimates of humpback whale consumption were non-estimable and that the integrated food web model led to estimable consumption rates. 4. Our results show that integrating stable isotopes and abundance datasets provides an exciting way forward for parameterizing multispecies models in data-limited systems. We expect that future developments of these integrated approaches will extend current food web theory by allowing ecologists to study predation dynamics over seasonal time scales and at the individual level.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.