Spatial biases
Biases in ERM data were inconsistent across space and taxa. Relative to
their global area, provincial and country boundaries played
disproportionate roles in delineating species ranges, especially in
mammals and amphibians. Political boundaries near temperate-tropical
transitions in particular have high levels of bias, including borders in
South China and northern Southeast Asia (Figure 2, Figure S1), as well
as the southwestern Brazil, making the use of these data for these areas
exceptionally risky. In these cases, careful assessment for the
possibility of strong administrative biases is needed, as using ERMs at
these transitions may cause significant errors in analysis, such that
alternate approaches such as models or trimmed MCPs should be used where
such data exist.