Limitations to the Use of Species-Distribution Models for Environmental-Impact Assessments in the Amazon

PloS One
Lorena Ribeiro de A CarneiroWilliam E Magnusson

Abstract

Species-distribution models (SDM) are tools with potential to inform environmental-impact studies (EIA). However, they are not always appropriate and may result in improper and expensive mitigation and compensation if their limitations are not understood by decision makers. Here, we examine the use of SDM for frogs that were used in impact assessment using data obtained from the EIA of a hydroelectric project located in the Amazon Basin in Brazil. The results show that lack of knowledge of species distributions limits the appropriate use of SDM in the Amazon region for most target species. Because most of these targets are newly described and their distributions poorly known, data about their distributions are insufficient to be effectively used in SDM. Surveys that are mandatory for the EIA are often conducted only near the area under assessment, and so models must extrapolate well beyond the sampled area to inform decisions made at much larger spatial scales, such as defining areas to be used to offset the negative effects of the projects. Using distributions of better-known species in simulations, we show that geographical-extrapolations based on limited information of species ranges often lead to spurious results. We conclu...Continue Reading

References

Nov 30, 2000·Proceedings of the National Academy of Sciences of the United States of America·C GasconP T Boag
Jun 9, 2010·Systematic Biology·William Godsoe
Jul 29, 2011·Proceedings. Biological Sciences·Camila C RibasJoel Cracraft
Sep 27, 2013·Anais Da Academia Brasileira De Ciências·Leandro Valle FerreiraPia Parolin

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Citations

Jun 6, 2019·Anais Da Academia Brasileira De Ciências·William E Magnusson
Oct 2, 2020·PLoS Neglected Tropical Diseases·Benoit de ThoisyBetânia Paiva Drumond
Jan 14, 2021·Scientific Reports·João Gama MonteiroJoão Canning-Clode

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Software Mentioned

MESS
SpeciesLink
MaxEnt
ArcGIS
DIA
BIOCLIM

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