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Soil and forest structure predicts large-scale patterns of occurrence and local abundance of a widespread Amazonian frog

The distribution of biodiversity within the Amazon basin is often structured by sharp environmental boundaries, such as large rivers. The Amazon region is also characterized by subtle environmental clines, but how they might affect the distributions and abundance of organisms has so far received les...

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Detalles Bibliográficos
Autores principales: Ferreira, Anthony S., Jehle, Robert, Stow, Adam J., Lima, Albertina P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6087616/
https://www.ncbi.nlm.nih.gov/pubmed/30123719
http://dx.doi.org/10.7717/peerj.5424
Descripción
Sumario:The distribution of biodiversity within the Amazon basin is often structured by sharp environmental boundaries, such as large rivers. The Amazon region is also characterized by subtle environmental clines, but how they might affect the distributions and abundance of organisms has so far received less attention. Here, we test whether soil and forest characteristics are associated with the occurrence and relative abundance of the forest-floor dwelling Aromobatid frog, Allobates femoralis. We applied a structured sampling regime along an 880 km long transect through forest of different density. High detection probabilities were estimated for A. femoralis in each of the sampling modules. Using generalized linear mixed-effects models and simple linear regressions that take detectability into account, we show that A. femoralis is more abundant in open forests than in dense forests. The presence and relative abundance of A. femoralis is also positively associated with clay-rich soils, which are poorly drained and therefore likely support the standing water bodies required for reproduction. Taken together, we demonstrate that relatively easy-to-measure environmental features can explain the distribution and abundance of a widespread species at different spatial scales. Such proxies are of clear value to ecologists and conservation managers working in large inaccessible areas such as the Amazon basin.