2024
DOI: 10.1111/ecog.06988
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Modelling 21st century refugia and impact of climate change on Amazonia's largest primates

Thiago Cavalcante,
Adrian A. Barnett,
Jasper Van doninck
et al.

Abstract: Edaphic and vegetation conditions can render climatically suitable sites inadequate for a species to persist, constraining the amount of suitable habitat and the possibilities of tracking preferred climatic conditions as they shift in response to climate change. We combined climatic and remotely sensed data to model current and future distributions of nine extant taxa of ateline primates across the Amazon basin. We used the models to identify and quantify potential range changes and refugia of suitable habitat… Show more

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Cited by 1 publication
(2 citation statements)
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“…Predicting potential future range shift in biodiversity is fundamental to identify priority areas for conservation (e.g., climatic refugia, Cavalcante et al, 2024), but it requires to include the main shift drivers in the modelling exercise. Our results point out that the implications of non-including land use change variables are non-negligible and should be considered on a taxon-specific basis.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Predicting potential future range shift in biodiversity is fundamental to identify priority areas for conservation (e.g., climatic refugia, Cavalcante et al, 2024), but it requires to include the main shift drivers in the modelling exercise. Our results point out that the implications of non-including land use change variables are non-negligible and should be considered on a taxon-specific basis.…”
Section: Discussionmentioning
confidence: 99%
“…In a context of global changes, species are often responding by shifting their distribution (Pecl et al 2017). Obtaining reliable predictions of future species distribution under global change scenarios is therefore fundamental for the identification of priority sites for conservation (e.g., climatic refugia; Cavalcante et al, 2024;Serafini et al submitted). Correlative species distribution models (SDMs) allow to predict environmental-driven range shifts by estimating a link between presence data and environmental variables and then forecast the species niche to future values of such variables (Elith et al, 2010).…”
Section: Introductionmentioning
confidence: 99%