Integrating climate, ecophysiology, and forest cover to estimate the vulnerability of sloths to climate change

Author:

Tourinho Luara1ORCID,Sinervo Barry2,Caetano Gabriel Henrique de Oliveira3,Giné Gastón Andrés Fernandez4,dos Santos Cinthya Chiva4,Cruz-Neto Ariovaldo Pereira5,Vale Mariana M6

Affiliation:

1. Programa de Pós-Graduação em Ecologia (PPGE), Universidade Federal do Rio de Janeiro (UFRJ) , 550 Pedro Calmon, 21941-901, Rio de Janeiro, Rio de Janeiro , Brazil

2. Department of Ecology and Evolutionary Biology, University of California (UCSC) , 1156 High Street, 95064, Santa Cruz, California , USA

3. The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev , Sede Boqer Campus, 8499000, Boqer, Negev , Israel

4. Applied Ecology & Conservation Lab, Department of Biological Sciences, Universidade Estadual de Santa Cruz , Rodovia Jorge Amado, Km 16, 45662-900 Salobrinho, Ilhéus, Bahia , Brazil

5. Laboratory of Animal Physiology, Department of Biodiversity, Universidade Estadual Paulista (UNESP) , 1515 Av. 24 A Bela Vista, 13506-752, Rio Claro, São Paulo , Brazil

6. Department of Ecology, Biology Institute, Universidade Federal do Rio de Janeiro (UFRJ) , 550 Pedro Calmon, 21941-901, Rio de Janeiro, Rio de Janeiro , Brazil

Abstract

Abstract Global change imposes multiple challenges on species and, thus, a reliable prediction of current and future vulnerability of species must consider multiple stressors and intrinsic traits of species. Climate, physiology, and forest cover, for example, are required to evaluate threat to thermolabile forest-dependent species, such as sloths (Bradypus spp.; Mammalia: Xenarthra). Here, we estimated future changes in the distribution of three sloth species using a metabolic-hybrid model focused on climate (climatic only, i.e., CO approach) and adding forest cover constraints to distribution of species (climate plus land cover, i.e., CL approach). We used an innovative method to generate estimates of physiological parameters for endotherms, validated with field data. The CF approach predicted a future net expansion of distribution of B. torquatus and B. variegatus, and a future net contraction of distribution of B. tridactylus. The inclusion of forest cover constraints, however, reversed the predictions for B. torquatus, with a predicted net distribution contraction. It also reduced expansion of B. variegatus, although still showing a large net expansion. Thus, B. variegatus is not predicted to be threatened in the future; B. tridactylus emerges as the species most vulnerable to climate change, but with no considerable forest losses, while B. torquatus shows the opposite pattern. Our study highlights the importance of incorporating multiple stressors in predictive models in general. To increase resilience of species to climate change, it is key to control deforestation in the Amazon for B. tridactylus, and to promote reforestation in the Atlantic Forest for B. torquatus.

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro

Fundação de Amparo à Pesquisa do estado de São Paulo

National Science Foundation

Financiadora de Estudos e Projetos

Instituto Nacional de Ciência e Tecnologia

Ministério da Ciência, Tecnologia e Inovações

Fundação de Amparo à Pesquisa do Estado de Goiás

Publisher

Oxford University Press (OUP)

Subject

Nature and Landscape Conservation,Genetics,Animal Science and Zoology,Ecology,Ecology, Evolution, Behavior and Systematics

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