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This is a Observational study (also classified as: Literature Review).

August 26, 2025BiotropicaOpen Access

Biases in Amphibian Sampling in the Amazon: Using Infrastructure and Accessibility Data to Identify Sampling Gaps

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Analysis uncovers geographic bias in amphibian sampling in the Amazon, highlighting infrastructure's role in data gaps.

Geographic and temporal biases affect the understanding of amphibian diversity patterns, limiting biogeographic knowledge.
The study shows that rivers are the primary drivers of amphibian sampling, while roads have minimal influence on data collection.
Analysis of georeferenced occurrence records revealed significant distortions in sampling due to infrastructure development like hydroelectric plants.
Collaborative efforts and improved data dissemination are necessary to enhance amphibian research and inform biodiversity conservation efforts.

Penhacek et al. (2025) studied this question.

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August 26, 2025BiotropicaOpen Access

View Full Paper

Ask AI

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Authors

Analysis uncovers geographic bias in amphibian sampling in the Amazon, highlighting infrastructure's role in data gaps.

Geographic and temporal biases affect the understanding of amphibian diversity patterns, limiting biogeographic knowledge.
The study shows that rivers are the primary drivers of amphibian sampling, while roads have minimal influence on data collection.
Analysis of georeferenced occurrence records revealed significant distortions in sampling due to infrastructure development like hydroelectric plants.
Collaborative efforts and improved data dissemination are necessary to enhance amphibian research and inform biodiversity conservation efforts.

Penhacek et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark