Article ; Online: AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest.
2022 Volume 103, Issue 9, Page(s) e3738
Abstract: The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an ... ...
| Abstract | The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive data set of inventories of mammal, bird, and reptile species ever assembled for the area. The complete data set comprises 154,123 records of 317 species (185 birds, 119 mammals, and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname, and Venezuela). The most frequently recorded species per taxa were: mammals: Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles: Tupinambis teguixin (716 records). The information detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change, and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when using its data in publications and we also request that researchers and educators inform us of how they are using these data. |
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| MeSH term(s) | Animals ; Biodiversity ; Birds ; Brazil ; Forests ; Humans ; Mammals ; Reptiles ; Vertebrates |
| Language | English |
| Publishing date | 2022-07-18 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2010140-5 |
| ISSN | 1939-9170 ; 0012-9658 |
| ISSN (online) | 1939-9170 |
| ISSN | 0012-9658 |
| DOI | 10.1002/ecy.3738 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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