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556 results for “Meta Data”
Data from: Responses of insect pollinators to habitat fragmentation: A global meta-analysis
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Data from: Assessing the mechanisms and impacts of shrub invasion in forests: A meta-analysis
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Data and code – Effects of climate on salmonid productivity: A global meta-analysis across freshwater ecosystems
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Data from: Provenance variation in functional traits of European forest trees: Meta-analysis reveals effects of taxa and age despite critical research gaps
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Data for: Resetting our expectations for parasites and their effects on species interactions: A meta-analysis
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Data for a meta-analysis of the effect of kelp forests on fish communities around the world from observational and experimental studies spanning 1983-2020
Data for Pérez-Matus, A., Micheli, F., Konar, B., Shears, N., Low, N., Okamoto, D., Wernberg, T., Krumhansl, K., Ling, S., Kinsgford, M., Navarrete-Fernandez, T., Ruz, C., and Byrnes, J. 2024. Kelp forests as nursery and foundational habitat for reef fish. Ecology. For the definitive analysis, see the paper. Code is at https://github.com/jebyrnes/fish_kelp_meta. This data set concerns the effects of kelp on fish community composition. Data was mined as part of the National Center for Ecological Analysis and Synthesis (NCEAS) working group on "Global impacts of climate change on kelp forest ecosystems." It consists of digitized information from studies searched (see methods) examining fish community composition with and without kelp. To summarize the study, conservation of marine biodiversity requires an understanding of the habitats needed to support and replenish species of interest. It also requires knowledge about the abundance and diversity of multi-species assemblages. Variation in the distribution and composition of kelp forests, one of the most productive marine coastal habitats globally, can have major influences on reef fishes – a group of ecologically and socio-economically important species. In the face of widespread and escalating loss of kelp forests, quantification of these effects is urgently needed to assess and project cascading impacts on biodiversity. Here, we evaluate relationships between kelp forests and associated reef fish populations using a global meta-analysis of experimental kelp removals and comparative surveys of kelp and adjacent non-kelp habitats. These analyses show that kelp forests increase the abundance of reef fishes, though the significance of this effect varied depending on the structural complexity of kelp forests. In experimental studies, kelp forests have a significant positive effect on fish species richness, revealing that kelp act as true foundation species by supporting the diversity of associated multi-species assemblag
Data for a global meta-analysis of passive experimental warming effects on plant traits and community properties
This database contains the data used in a global meta-analysis of warming effects on plants. L0 data are available upon request; they include the raw data from 126 warming experiments. The L1 data are the result of merged L0 data and are cleaned for typos and are standardized names. L1 data contain plant trait and community property measurements in both warmed and ambient conditions. L2 data contain the effect sizes of warming for each study. These data came from 126 warming experiments across the globe.
Meta-analytical data on soil organic, particulate organic, and mineral-associated organic carbon under nitrogen fertilization, elevated atmospheric carbon dioxide, atmospheric warming, increased precipitation, drought, and their combined effects
Data were harvested from journal articles found on the Web of Science Core Collection and the ProQuest Agricultural and Environmental Database that studied soil organic matter fraction carbon responses to global changes (nitrogen fertilization, elevated atmospheric carbon dioxide, atmospheric warming, increased and decreased precipitation, and combined effects). Soil organic carbon fractions were designated as particulate organic carbon or mineral-associated organic carbon based on size and density cutoffs. Relevant metadata, including article information (authors, publication year), environmental information (soil type, climate, and land use), and experiment information (rates, methods) were also added to the dataset.
Coastal SEES Collaborative Research: Non-Market Value Meta-Data on Willingness to Pay for Coastal Marsh Habitat Change
These data represent a meta-dataset of observations on per household economic value - represented by per household willingness-to-pay (WTP) - for improvements in coastal marsh habitat, drawn from stated-preference studies in the research literature. The metadata allow estimation of benefit transfer functions via meta-regression modeling. Within these econometric functions, the dependent variable is a comparable estimate of economic value (e.g., WTP) drawn from extant primary valuation studies. Independent variables represent observable factors hypothesized to explain variation in this value measure across observations. These functions can be used to produce out-of-sample predictions of WTP for coastal marsh habitat improvements at sites for which no primary valuation studies have been conducted. They can also be used to understand the factors associated with systematic variations in marsh habitat values across different sites and studies. These data are described in Vedogbeton, H. and R.J. Johnston. 2020. Commodity Consistent Meta-Analysis of Wetland Values: An Illustration for Coastal Marsh Habitat. Environmental and Resource Economics 75(4), 835-865, and allow replication of the results presented therein. The metadata are extracted from primary studies that estimate total (use and nonuse) per household WTP for changes in the quantity or quality of coastal marsh wildlife habitats or their services, in US and Canada. These studies were identified via a systematic review of the literature. The metadata combine information provided by these primary non-market valuation studies with publicly available external data extracted from sources such as the US Census, US National Historical GIS (https://www.nhgis.org/), and US Fish and Wildlife Service National Wetlands Inventory (https://www.fws.gov/wetlands/Data/Mapper.html). Studies included in the metadata are restricted to those that estimate total per household WTP for coastal wetland habitat changes using generally acce
Data from: A meta-analysis of factors influencing the strength of mate choice copying in animals
Davies et al., (2020) All data and R code <p>Mate-choice copying is a form of social learning in which an individual's choice of mate is influenced by the apparent choices of other individuals of the same sex, and has been observed in more than 20 species across a broad taxonomic range. Though fitness benefits of copying have proven difficult to measure, theory suggests that copying should not be beneficial for all species or contexts. However, the factors influencing the evolution and expression of copying have proven difficult to resolve. We systematically searched the literature for studies of mate-choice copying in non-human animals, and then performed a phylogenetically-controlled meta-analysis to explore which factors influence the expression of copying across species. Across 58 published studies in 23 species, we find strong evidence that animals copy the mate choice of others. The strength of copying was significantly influenced by taxonomic group, however sample size limitations mean it is difficult to draw firm conclusions regarding copying in mammals and arthropods. The strength of copying was also influenced by experimental design: copying was stronger when choosers were tested before and after witnessing a conspecific's mate choice, compared to when choosers with social information were compared to choosers without. Importantly, we did not detect any difference in the strength of copying between males and females, or in relation to the rate of multiple mating. Our search also highlights that more empirical work is needed to investigate copying in a broader range of species, especially those with differing mating systems and levels of reproductive investment.</p>
Data from: Tetra-EU 1.0: a species-level trophic meta-web of European tetrapods
Motivation Documenting potential interactions between species represents a major step to understand and predict the spatial and temporal structure of multi-trophic communities and their functioning. The metaweb concept summarises the potential trophic (and non-trophic) interactions in a given species-pool. As such, it generalises the regional species-pool of community ecology by incorporating the potential relationships between species from different trophic levels along with their functional characteristics. However, while this concept is theoretically very attractive, it has rarely been used to understand the structure of ecological network, mostly because of data availability. Here, we provide a continental scale, species-level, metaweb for all tetrapods (mammals, breeding birds, reptiles, amphibians) occurring in Europe and in the Northern Mediterranean basin. This metaweb is based on data extracted from scientific literature, including published papers, books, and grey literature. Main type of variable contained For each species considered, we built the network of potential 2-way trophic interactions. Spatial location and grain We considered all species occurring in the entire European sub-continent, from Macaronesia (including only the islands politically belonging to Spain and Portugal) to the Ural Mountains (west to east), and from Fennoscandia and UK islands to the Mediterranean (north to south). We included Turkey, geographically part of Asia, to provide a complete picture of the north-eastern Mediterranean coast. Time period The data represent information published and/or collected during the last 50 years. Major taxa studied and level of measurement We focused our metaweb on terrestrial tetrapods occurring in the study area. Only species introduced in historical times and currently naturalized were considered; novel introductions were excluded. In total we included 288 mammals, 509 regularly breeding birds, 250 reptiles, and 104 amphibians. Software format Data are supplied as semi-colon separated text files.
Data from: City sicker? a meta-analysis of wildlife health and urbanization
Urban development can alter resource availability, land use, and community composition, in turn influencing wildlife health. Generalizable relationships between wildlife health and urbanization have yet to be quantified, and could vary across health metrics and animal taxonomy. We present a phylogenetic meta-analysis of 516 records spanning 81 wildlife species from 106 studies comparing the toxicant loads, parasitism, body condition, or stress of urban and non-urban wildlife populations in 30 countries. We find a significantly negative relationship between urbanization and wildlife health, driven by higher toxicant loads and greater parasitism by parasites transmitted through close contact. Invertebrates and amphibians were particularly affected, with higher toxicant loads and physiological stress in urban populations as compared to their non-urban counterparts. We also found strong geographic and taxonomic bias in research effort, highlighting future research needs. Our results suggest urban wildlife experience several health risks with potential threats to conservation.
Data from: A meta-analysis of plant interaction networks reveals competitive hierarchies as well as facilitation and intransitivity
The extent to which competitive interactions and niche differentiation structure communities has been highly controversial. To quantify evidence for key features of plant community structure, I recharacterized published data from interaction experiments as networks of competitive and facilitative interactions. I measured the network structure of 31 woody and herbaceous communities, including the intensity, distribution, and diversity of interactions at the species-pair and community level to determine the generality of competition, winner-loser relationships, and unequal interaction allocation. I developed novel methodology using meta-analysis to incorporate interaction uncertainty into estimates of structural metrics among independent networks. Plant communities were competitive, but intraspecific interactions were sometimes more intense than interspecific interactions. On the whole, interactions were imbalanced and communities were transitive. However, facilitation, balanced interactions, and intransitivity were common in individual communities. Synthesizing network metrics using meta-analysis is an original approach with which to generalize community structure in a systematic way.
Data from: Large-scale meta-analysis on rheumatoid arthritis across East Asian and European populations
<p><span><span><span><b>Objective:</b> Nearly 110 susceptibility loci for rheumatoid arthritis (RA) with modest effect sizes have been identified by population-based genetic association studies, suggesting a large number of undiscovered variants behind a highly polygenic genetic architecture of RA. Here, we performed the largest-ever trans-ancestral meta-analysis with the aim to identify new RA loci and to better understand RA biology underlying genetic associations.</span></span></span></p> <p><span><span><span><b>Methods:</b> Genome-wide RA association summary statistics in three large case-control collections consisting of 311,292 individuals of Korean, Japanese, and European populations were used in an inverse-variance-weighted fixed-effects meta-analysis. Several computational analyses using public omics resources were conducted to prioritize causal variants and genes, RA variant-implicating features (tissues, pathways, and transcription factors), and potentially repurposable drugs for RA treatment. </span></span></span></p> <p><span><span><span><b>Results:</b> We identified 11 new RA susceptibility loci that explained 6.9% and 1.8% of the SNP-based heritability in East Asians and Europeans, respectively, and confirmed 71 known non-HLA susceptibility loci, identifying 90 independent association signals. The RA variants were preferentially located in binding sites of various transcription factors and in cell type-specific transcription-activation histone marks that simultaneously highlighted the importance of CD4<sup>+</sup> T-cell activation and the potential role of non-immune organs in RA pathogenesis. A total of 615 plausible effector genes, based on gene-based associations, expression-associated variants, and chromatin interaction, included targets of drugs approved for RA treatments and potentially repurposable drugs approved for other indications.</span></span></span></p> <p><span><span><span><b>Conclusion:</b> Our findings provide useful insights regarding RA genetic etiology and variant-driven RA pathogenesis.</span></span></span></p>
Data from: Individual differences in behaviour explain variation in survival: a meta-analysis
<p>Research focusing on among-individual differences in behaviour ("animal personality") has been blooming for over a decade. One of the central theories explaining the maintenance of such behavioural variation posits that individuals expressing greater "risky" behaviours should suffer higher mortality. Here, for the first time, we synthesize the existing empirical evidence for this key prediction. Our results did not support this prediction as there was no directional relationship between riskier behaviour and greater mortality; however there was a significant absolute relationship between behaviour and survival. In total, behaviour explained a significant, but small, portion (5.8%) of the variance in survival. We also found that risky (versus "shy") behavioural types live significantly longer in the wild, but not in the laboratory. This suggests that individuals expressing risky behaviours might be of overall higher quality but the lack of predation pressure and resource restrictions mask this effect in laboratory environments. Our work implies that individual differences in behaviour explain important differences in survival but not in the direction predicted by theory. Importantly, this suggests that the models predicting survival trade-offs may need revision and/or empiricists may need to reconsider their proxies of risky behaviours when testing such theory.</p>
Data from: Explaining global variation in the latitudinal diversity gradient: meta-analysis confirms known patterns and uncovers new ones
Aim: The pattern of increasing biological diversity from high latitudes to the equator [latitudinal diversity gradient (LDG)] has been recognized for > 200 years. Empirical studies have documented this pattern across many different organisms and locations. Our goal was to quantify the evidence for the global LDG and the associated spatial, taxonomic and environmental factors. We performed a meta-analysis on a large number of individual LDGs that have been published in the 14 years since Hillebrand's ground-breaking meta-analysis of the LDG, using meta-analysis and meta-regression approaches largely new to the fields of ecology and biogeography. Location: Global. Time period: January 2003–September 2015. Major taxa studied: Bacteria, protists, plants, fungi and animals. Methods: We synthesized the outcomes of 389 individual cases of LDGs from 199 papers published since 2003, using hierarchical mixed-effects meta-analysis and multiple meta-regression. Additionally, we re-analysed Hillebrand's original dataset using modern methods. Results: We confirmed the generality of the LDG, but found the pattern to be weaker than was found in Hillebrand's study. We identified previously unreported variation in LDG strength and slope across longitude, with evidence that the LDG is strongest in the Western Hemisphere. Locational characteristics, such as habitat and latitude range, contributed significantly to LDG strength, whereas organismal characteristics, including taxonomic group and trophic level, did not. Modern meta-analytical models that incorporate hierarchical structure led to more conservative and sometimes contrasting effect size estimates relative to Hillebrand's initial analysis, whereas meta-regression revealed underlying patterns in Hillebrand's dataset that were not apparent with a traditional analysis. Main conclusions: We present evidence of global latitudinal, longitudinal and habitat-based patterns in the LDG, which are apparent across both marine and terrestrial realms and over a broad taxonomic range of organisms, from bacteria to plants and vertebrates.
Database including meta data and R script for bachelor thesis biology on ground beetles as bioindicator 2017
<p>Database including meta data and R script for bachelor thesis biology on ground beetles as bioindicator 2017</p>
The raw data from the article "KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling"
<p>The raw data from the article "KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling"</p>
Data for: The Clam Before the Storm: A Meta Analysis Showing the Effect of Combined Climate Change Stressors on Bivalves
<p>These data were used to conduct a meta-analysis (as descirbed in the pre-print; The Clam Before the Storm: A Meta Analysis Showing the Effect of Combined Climate Change Stressors on Bivalves). These data can be used to reproduce our analysis.</p>
Data for: The meta-analysis of the effects of spatial sampling bias correction on presence only species distribution models
<p>This dataset contains information extracted from 70 studies identified through a systematic review of the peer-reviewed literature (Web of Science and SCOPUS databases both searched on the 13/02/2023) to evaluate the effect of spatial sampling bias correction methods in presence-only species distribution models.</p>
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.