An official website of the United States government
ABSTRACT MotivationFreshwater ecosystems have been heavily impacted by land‐use changes, but data syntheses on these impacts are still limited. Here, we compiled a global database encompassing 241 studies with species abundance data (from multiple biological groups and geographic locations) across sites with different land‐use categories. This compilation will be useful for addressing questions regarding land‐use change and its impact on freshwater biodiversity. Main Types of Variables ContainedThe database includes metadata of each study, sites location, sample methods, sample time, land‐use category and abundance of each taxon. Spatial Location and GrainThe database contains data from across the globe, with 85% of the sites having well‐defined geographical coordinates. Major Taxa and Level of MeasurementThe database covers all major freshwater biological groups including algae, macrophytes, zooplankton, macroinvertebrates, fish and amphibians.
more »
« less
This content will become publicly available on May 1, 2026
BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series
ABSTRACT MotivationHere, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables IncludedThe database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and GrainSampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and GrainThe earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of MeasurementThe database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Formatcsv and. SQL.
more »
« less
- PAR ID:
- 10591805
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Global Ecology and Biogeography
- Date Published:
- Journal Name:
- Global Ecology and Biogeography
- Volume:
- 34
- Issue:
- 5
- ISSN:
- 1466-822X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
ABSTRACT MotivationSNAPSHOT USA is an annual, multicontributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables ContainedSNAPSHOT USA 2019–2023 contains 987,979 records of camera trap image sequence data and 9694 records of camera trap deployment metadata. Spatial Location and GrainData were collected across the United States of America in all 50 states, 12 ecoregions and many ecosystems. Time Period and GrainData were collected between 1st August and 29th December each year from 2019 to 2023. Major Taxa and Level of MeasurementThe dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software FormatSNAPSHOT USA 2019–2023 comprises two .csv files. The original data can be found within the SNAPSHOT USA Initiative in the Wildlife Insights platform.more » « less
-
Abstract AimAbundance–occupancy relationships posit that more locally abundant species occupy more sites than less abundant species. Although widely supported, the occurrence and detection of abundance–occupancy relationships is sensitive to sampling and detection processes. Data from large‐scale standardized sampling efforts are key to address abundance–occupancy relationships. We aimed to use such a dataset to evaluate the occurrence of abundance–occupancy relationships across different spatial grains and over time for aquatic and terrestrial taxa. LocationUSA. Time period2014–2019. Major taxa studiedBirds, mammals, beetles, ticks, fishes, macroinvertebrates and zooplankton. MethodsSpecies abundance and occupancy data were obtained from the National Ecological Observatory Network (NEON). Species mean abundance and occupancy (fraction of sampled locations that were occupied) were estimated for three different spatial grains (i.e., plot, site and domain) for all years sampled. Linear models were used to explore the consistency of interspecific abundance–occupancy relationships. The slope coefficients of these models were related to temporal and spatial variables and to species richness while controlling for taxa in a linear mixed‐effects model (LMM) framework. ResultsWe found evidence for positive abundance–occupancy relationships across the three spatial grains and over time for all taxa we studied. However, our linear models had low explanatory power, suggesting that relationships, although general, were weak. Abundance–occupancy relationships were slightly stronger at the smallest spatial grain than at the largest spatial grain, but showed no detectable change over time for any taxa. Finally, species richness was not associated with the strength of these relationships. Main conclusionsTogether, our results suggest that positive interspecific abundance–occupancy relationships are fairly general but are not capable of explaining substantial variation in spatial patterns of abundance, and that other factors, such as species traits and niche, are also likely to influence these relationships.more » « less
-
Abstract MotivationTraits are increasingly being used to quantify global biodiversity patterns, with trait databases growing in size and number, across diverse taxa. Despite growing interest in a trait‐based approach to the biodiversity of the deep sea, where the impacts of human activities (including seabed mining) accelerate, there is no single repository for species traits for deep‐sea chemosynthesis‐based ecosystems, including hydrothermal vents. Using an international, collaborative approach, we have compiled the first global‐scale trait database for deep‐sea hydrothermal‐vent fauna – sFDvent (sDiv‐funded trait database for theFunctionalDiversity ofvents). We formed a funded working group to select traits appropriate to: (a) capture the performance of vent species and their influence on ecosystem processes, and (b) compare trait‐based diversity in different ecosystems. Forty contributors, representing expertise across most known hydrothermal‐vent systems and taxa, scored species traits using online collaborative tools and shared workspaces. Here, we characterise the sFDvent database, describe our approach, and evaluate its scope. Finally, we compare the sFDvent database to similar databases from shallow‐marine and terrestrial ecosystems to highlight how the sFDvent database can inform cross‐ecosystem comparisons. We also make the sFDvent database publicly available online by assigning a persistent, unique DOI. Main types of variable containedSix hundred and forty‐six vent species names, associated location information (33 regions), and scores for 13 traits (in categories: community structure, generalist/specialist, geographic distribution, habitat use, life history, mobility, species associations, symbiont, and trophic structure). Contributor IDs, certainty scores, and references are also provided. Spatial location and grainGlobal coverage (grain size: ocean basin), spanning eight ocean basins, including vents on 12 mid‐ocean ridges and 6 back‐arc spreading centres. Time period and grainsFDvent includes information on deep‐sea vent species, and associated taxonomic updates, since they were first discovered in 1977. Time is not recorded. The database will be updated every 5 years. Major taxa and level of measurementDeep‐sea hydrothermal‐vent fauna with species‐level identification present or in progress. Software format.csv and MS Excel (.xlsx).more » « less
-
Abstract The emergence of SARS-CoV-2 highlights a need for evidence-based strategies to monitor bat viruses. We performed a systematic review of coronavirus sampling (testing for RNA positivity) in bats globally. We identified 110 studies published between 2005 and 2020 that collectively reported positivity from 89,752 bat samples. We compiled 2,274 records of infection prevalence at the finest methodological, spatiotemporal and phylogenetic level of detail possible from public records into an open, static database named datacov, together with metadata on sampling and diagnostic methods. We found substantial heterogeneity in viral prevalence across studies, reflecting spatiotemporal variation in viral dynamics and methodological differences. Meta-analysis identified sample type and sampling design as the best predictors of prevalence, with virus detection maximized in rectal and faecal samples and by repeat sampling of the same site. Fewer than one in five studies collected and reported longitudinal data, and euthanasia did not improve virus detection. We show that bat sampling before the SARS-CoV-2 pandemic was concentrated in China, with research gaps in South Asia, the Americas and sub-Saharan Africa, and in subfamilies of phyllostomid bats. We propose that surveillance strategies should address these gaps to improve global health security and enable the origins of zoonotic coronaviruses to be identified.more » « less
