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Identification of the predators of bird nests is essential to test ecological and evolutionary hypotheses and to make practical management decisions. A variety of nest monitoring devices have been proposed but many remain difficult to set up in the field. The aim of this study was to test camera traps as a potential tool to study predation of natural nests in a tropical rainforest environment. Specifically, we registered the predators, assessed their size range, and we compared the use of one and two cameras per nest. Of 122 nests from 24 bird species, 45 (37%) were depredated, and the cameras recorded the predator species in 29 of the total of depredated nests (64%). We identified predators in eight of 16 depredated nests (50%) in which we used one camera trap per nest, and we identified predators in 21 of 29 depredated nests (72%) when we used two camera traps per nest. The predators included six species of birds and six species of mammals, with body masses varying from 20 g to 16.5 kg. Causes for 10 of the 16 detection failures were identified and are discussed. These results suggest that camera traps are viable tools to investigate nest predation in a tropical rainforest area.
QL1-991, Atlantic Forest, nesting success, nest predators, nest monitoring, Zoology
QL1-991, Atlantic Forest, nesting success, nest predators, nest monitoring, Zoology
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 29 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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