{"doi":"10.1002/ecy.4299","title":"<scp>CamTrapAsia</scp>: A dataset of tropical forest vertebrate communities from 239 camera trapping studies","abstract":"Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land-use change and hunting, the latter frequently referred as \"defaunation.\" This is especially true in tropical Asia where there is extensive land-use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera-derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large-scale pressence-only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10-, 20-, and 30-km buffers). We will update the dataset to include broader coverage of temperate Asia and add newer surveys and covariates as they become available. This dataset unlocks immense opportunities for single-species ecological or conservation studies as well as applied ecology, community ecology, and macroecology investigations. The data are fully available to the public for utilization and research. Please cite this data paper when utilizing the data.","journal":"Ecology","year":2024,"id":433943,"datarank":0.422164065350352,"base_score":2.639057329615259,"endowment":2.639057329615259,"self_citation_contribution":0.3958585994422889,"citation_network_contribution":0.02630546590806312,"self_endowment_contribution":0.3958585994422889,"citer_contribution":0.02630546590806312,"corpus_percentile":56.08416492612362,"corpus_rank":5678,"citation_count":13,"citer_count":4,"citers_with_citation_signal":2,"citers_with_endowment":2,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6502,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":41.6667,"fair_percentile":54.173035768878016,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1239656,"name":"Wido Rizki Albert","orcid":"0000-0002-9711-8077","position":1,"is_corresponding":false},{"id":1239657,"name":"Zachary Amir","orcid":"0000-0002-8398-2059","position":2,"is_corresponding":false},{"id":1239658,"name":"Marc Ancrenaz","orcid":"0000-0003-2325-2879","position":3,"is_corresponding":false},{"id":1239659,"name":"Eric Ash","orcid":"0000-0002-8099-269X","position":4,"is_corresponding":false},{"id":1239660,"name":"Badrul Azhar","orcid":"0000-0003-0694-5294","position":5,"is_corresponding":false},{"id":1239661,"name":"Henry Bernard","orcid":"0000-0003-1827-0642","position":6,"is_corresponding":false},{"id":1239662,"name":"Jedediah F. 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[downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/4 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the ecology / environmental repository accession (e.g. from GBIF, PANGAEA or Dryad) in the reference list.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"Data and code are available as Supporting Information (Data S1) and are available in Zenodo at https://doi.org/10.5281/zenodo.10780971.","why":"The dataset identifier appears only in the body text, not as a reference-list entry. [downgraded to 'no' — no verifiable quote from the paper]","gain":8.33,"priority":"important","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open ecology / environmental formats such as CSV or Darwin Core Archive.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No file format token is named for the released data.","gain":8.33,"priority":"important","scored":true},{"key":"x_code_availability","dimension":"R","label":"Analysis code available","action":"Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Data and code are available as Supporting Information (Data S1) and are available in Zenodo at https://doi.org/10.5281/zenodo.10780971.","why":"A machine-resolvable locator (Zenodo DOI) is given for the code. [downgraded to 'partial' — no verifiable quote from the paper]","gain":4.17,"priority":"important","scored":true},{"key":"r_versioning","dimension":"R","label":"Snapshot identified","action":"Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No version token or date is provided to identify a specific snapshot of the data.","gain":4.17,"priority":"useful","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Data and code are available as Supporting Information (Data S1) and are available in Zenodo at https://doi.org/10.5281/zenodo.10780971.","why":"The statement points at a repository record with a DOI, fulfilling Colavizza category 3. [downgraded to 'partial' — no verifiable quote from the paper]","gain":0.0,"priority":"essential","scored":false},{"key":"f_discovery_metadata","dimension":"F","label":"Description of the dataset as an object","action":"Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights","why":"The dataset's content is described in running prose, not in an itemised inventory such as a section or table.","gain":0.0,"priority":"essential","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In ecology / environmental, describe the data with Darwin Core or Ecological Metadata Language (EML).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data or metadata community standard (e.g., MIAME, Darwin Core) is named as being applied to the data.","gain":0.0,"priority":"important","scored":false},{"key":"r_provenance_methods","dimension":"R","label":"Provenance of the data","action":"Name the instruments, kits, and software — with versions — that produced the data, not just the verbs. 'Reads were aligned' is not provenance; 'aligned with STAR v2.7.9a to GRCh38' is, because someone else can rerun it.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats.","why":"The production method is described in generic terms without naming specific instruments, kits, or software. [downgraded to 'no' — no verifiable quote from the paper]","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No documentation object (README, data dictionary, codebook) is named as accompanying the data, and no variable-definition table appears inside the article.","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are not sensitive and no gatekeeper is named; the data are openly available.","gain":0.0,"priority":"useful","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No identifier for any external resource other than the paper's own dataset is provided in the text.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The data are fully available to the public for utilization and research.","why":"The paper states availability timing (now) but does not state a persistence commitment or retention period.","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For ecology / environmental data, deposit in GBIF, PANGAEA or Dryad.","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For ecology / environmental data, deposit in GBIF, PANGAEA or Dryad.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the ecology / environmental repository accession (e.g. from GBIF, PANGAEA or Dryad) in the reference list.","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open ecology / environmental formats such as CSV or Darwin Core Archive."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"unpaywall_pdf"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"unpaywall_pdf","fair_has_llm":true,"fair_computed_at":"2026-07-20T12:12:02.523232Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}