Use este identificador para citar ou linkar para este item: https://repositorio.inpa.gov.br/handle/1/14692
Título: Limitations to the use of species-distribution models for environmental-impact assessments in the Amazon
Autor: Carneiro, Lorena Ribeiro de A.
Lima, Albertina Pimental
Machado, Ricardo Bomfim
Magnusson, William Ernest
Palavras-chave: Animals Experiment
Animals Model
Biodiversity
Environmental Impact Assessment
Licensing
Model
Nonhuman
Sampling
Species Distribution
Target Organism
Animals
Biodiversity
Demography
Ecosystem Monitoring
Electric Power Plant
Environment
Environmental Monitoring
Environmental Protection
Geography
Human
Organization And Management
Procedures
Risk Assessment
River
Standards
Theoretical Model
Animalss
Biodiversity
Conservation Of Natural Resources
Demography
Ecological Parameter Monitoring
Environment
Environmental Monitoring
Geography
Humans
Models, Theoretical
Planning Techniques
Power Plants
Risk Assessment
Rivers
Data do documento: 2016
Revista: PLoS ONE
É parte de: Volume 11, Número 1
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 conclude that the use of SDM as evidence to support project-licensing decisions in the Amazon requires much greater area sampling for impact studies, or, alternatively, integrated and comparative survey strategies, to improve biodiversity sampling. When more detailed distribution information is unavailable, SDM will produce results that generate uncertain and untestable decisions regarding impact assessment. In many cases, SDM is unlikely to be better than the use of expert opinion. © 2016 Carneiro et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
DOI: 10.1371/journal.pone.0146543
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