ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2023
Camera trapping expands the view into global biodiversity and its change.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Bridging monitoring gaps in global drylands with big data and collaboration.npj biodiversity · 2026Review
- Host Community Traits Driving Crimean-Congo Hemorrhagic Fever Virus Maintenance in Iberian Ecosystems.Transboundary and emerging diseases · 2026Article
- Motion detection or time-lapse? A comparison of camera trap triggers for monitoring breeding taiga bean geese (Anser fabalis fabalis).PloS one · 2026Article
- A theoretical framework for scaling ecological niches from individuals to species.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Developing custom computer vision models with Njobvu-AI: A collaborative, user-friendly platform for ecological research.Ecological applications : a publication of the Ecological Society of America · 2025Article
- The biodiversity survey of the Cape (BioSCape), integrating remote sensing with biodiversity science.npj biodiversity · 2025Review
- Article
- Estimating distribution and abundance of wide-ranging species with integrated spatial models: Opportunities revealed by the first wolf assessment in south-central Italy.Ecology and evolution · 2024Article
- The Potential of Diffusion-Based Near-Infrared Image Colorization.Sensors (Basel, Switzerland) · 2024Article
- The first use of a photogrammetry drone to estimate population abundance and predict age structure of threatened Sumatran elephants.Scientific reports · 2023Article
- Camera trapping expands the view into global biodiversity and its change.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Economic factors underlying biodiversity loss.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Bridging adaptive management and reinforcement learning for more robust decisions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Detecting and attributing the causes of biodiversity change: needs, gaps and solutions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
Corrections and comments
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Authors and funding
11 authors.
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Abstract
Growing threats to biodiversity demand timely, detailed information on species occurrence, diversity and abundance at large scales. Camera traps (CTs), combined with computer vision models, provide an efficient method to survey species of certain taxa with high spatio-temporal resolution. We test the potential of CTs to close biodiversity knowledge gaps by comparing CT records of terrestrial mammals and birds from the recently released Wildlife Insights platform to publicly available occurrences from many observation types in the Global Biodiversity Information Facility. In locations with CTs, we found they sampled a greater number of days (mean = 133 versus 57 days) and documented additional species (mean increase of 1% of expected mammals). For species with CT data, we found CTs provided novel documentation of their ranges (93% of mammals and 48% of birds). Countries with the largest boost in data coverage were in the historically underrepresented southern hemisphere. Although embargoes increase data providers' willingness to share data, they cause a lag in data availability. Our work shows that the continued collection and mobilization of CT data, especially when combined with data sharing that supports attribution and privacy, has the potential to offer a critical lens into biodiversity. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.
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