Limitations in the use of species distribution models for environmental impact assessments in the Amazon
Species distribution models have been recognized as a potential tool for guiding public decisions, including in the environmental licensing process of large ventures. In this paper, we present a case study using data on frogs that were obtained from the impact assessment of a hydroelectric projec...
| Autor principal: | Carneiro, Lorena Ribeiro de Almeida |
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| Grau: | Dissertação |
| Idioma: | por |
| Publicado em: |
Instituto Nacional de Pesquisas da Amazônia - INPA
2020
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| Assuntos: | |
| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/11927 http://lattes.cnpq.br/8077820380396290 |
| Resumo: |
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Species distribution models have been recognized as a potential tool for guiding public
decisions, including in the environmental licensing process of large ventures. In this paper, we
present a case study using data on frogs that were obtained from the impact assessment of a
hydroelectric project located in Amazon Basin to evaluate the use of SDMs in the decisionmaking
process in this context. Because conservation strategies must prioritize targets, we
defined the priority species and analyzed their respective sampling situations. Based on the
expectations of environmental legislation in Brazil and using the tools recommended in the
literature, we discussed the limitations and potential use of SDM techniques for guiding
mitigation and compensation actions. The results suggest that the lack of knowledge regarding
the distribution of species poses a risk to biodiversity when potentially damaging enterprises are
licensed in the Amazon. However, there were insufficient data for most of the target species to be
included in the distribution models because most of those species have not yet been described.
The mandatory surveys are typically conducted in areas adjacent to the affected areas, and so
models must extrapolate beyond the sampled data to guide decisions, such as defining areas to be
used to offset the negatives effects. The results of geographical extrapolation simulations, were
corroborated by several authors who suggested that predictions can be varied when it is use
different arrangements of data for calibration of the tools, since random data within the range of
many Amazonian species are not available. We conclude that the use of SDMs for supporting
decisions to license projects in the Amazon requires expanded sampling areas for impact studies
or an investment in integrated and comparative survey strategies to improve biodiversity
sampling and to fulfill the prerequisites for the use of such techniques. |