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. 2024 Jun;105(6):e4299.
doi: 10.1002/ecy.4299. Epub 2024 Apr 22.

CamTrapAsia: A dataset of tropical forest vertebrate communities from 239 camera trapping studies

Calebe P Mendes  1   2 Wido R Albert  3 Zachary Amir  2 Marc Ancrenaz  4 Eric Ash  5 Badrul Azhar  6 Henry Bernard  7 Jedediah Brodie  8 Tom Bruce  2 Elliot Carr  2 Gopalasamy Reuben Clements  9 Glyn Davies  10 Nicolas J Deere  11 Yoan Dinata  12 Christl A Donnelly  13 Somphot Duangchantrasiri  14 Gabriella Fredriksson  15 Benoit Goossens  16 Alys Granados  17 Andrew Hearn  5 Jason Hon  18 Tom Hughes  19 Patrick Jansen  20 Kae Kawanishi  21 Margaret Kinnaird  22 Sharon Koh  18 Alice Latinne  23 Matthew Linkie  24 Federica Loi  25 Anthony J Lynam  26 Erik Meijaard  27 Jayasilan Mohd-Azlan  28 Jonathan H Moore  29 Senthilvel K S S Nathan  30 Dusit Ngoprasert  31 Wilson Novarino  32 Ilyas Nursamsi  2 Timothy O'Brien  33 Robert Ong  30 John Payne  30 Dolly Priatna  34 D Mark Rayan  35 Glen Reynolds  36 Rustam Rustam  37 Sasidhran Selvadurai  6 Amanda Shia  4 Muhammad Silmi  38 Pablo Sinovas  39 Kriangsak Sribuarod  40 Robert Steinmetz  41 Matthew J Struebig  11 Ronglarp Sukmasuang  42 Sunarto Sunarto  43 Tarmizi Tarmizi  44 Arjun Thapa  2 Carl Traeholt  45 Oliver R Wearn  46 Hariyo B Wibisono  47 Andreas Wilting  48 Seth Timothy Wong  48 Siew Te Wong  49 Jettie Word  50 Wen Xuan Chiok  1 Zainal Zahari Zainuddin  30 Matthew Scott Luskin  2   51
Affiliations

CamTrapAsia: A dataset of tropical forest vertebrate communities from 239 camera trapping studies

Calebe P Mendes et al. Ecology. 2024 Jun.

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remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management.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.

Keywords: abundance; animal; biodiversity; bird; community; count; distribution; mammal; occurrence; richness; tropical forest; vertebrate.

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