Spatial and taxonomic biases in bat records: Drivers and conservation implications in a megadiverse country

Veronica Zamora-Gutierrez, Veronica Zamora‐Gutierrez, Tatsuya Amano & Kate E. Jones
Biases in data availability have serious consequences on scientific inferences that can be derived. The potential consequences of these biases could be more detrimental in the less-studied megadiverse regions, often characterized by high biodiversity and serious risks of human threats, as conservation and management actions could be misdirected. Here, focusing on 134 bat species in Mexico, we analyze spatial and taxonomic biases and their drivers in occurrence data; and identify priority areas for further data...
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These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
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