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Claim

Data and model code for: Habitat use patterns suggest that climate-driven vegetation changes will negatively impact mammal communities in the Amazon (ACV)

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 26 Jan 2023Publisher:Zenodo
Authors: Sollmann, Rahel; Rocha, Daniel;

doi: 10.5281/zenodo.7565480 , 10.5281/zenodo.7565479

Data and model code for: Habitat use patterns suggest that climate-driven vegetation changes will negatively impact mammal communities in the Amazon (ACV)

Abstract

Viewing data requires R; running models requires R package Nimble.Funding provided by: National Geographic SocietyCrossref Funder Registry ID: http://dx.doi.org/10.13039/100006363Award Number: Funding provided by: Horodas Family Foundation for Conservation Research*Crossref Funder Registry ID: Award Number: Funding provided by: Explorers ClubCrossref Funder Registry ID: http://dx.doi.org/10.13039/100002861Award Number: Funding provided by: Alongside Wildlife Foundation*Crossref Funder Registry ID: Award Number: Funding provided by: Hellman FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100010336Award Number: Funding provided by: Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100002322Award Number: 88881.128140/2016-01

The dataset contains species detection/non-detection data from 5 camera-trap surveys, carried out in 4 protected areas, in the southern Brazilian Amazon, along with camera-specific covariate and effort data. Also provided is R and Nimble code to implement the two community occupancy models described in the main text in Rocha and Sollmann (2023), Habitat use patterns suggest that climate-driven vegetation changes will negatively impact mammal communities in the Amazon, Animal Conservation, in press.

Please see description in the publication.

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Keywords

camera trapping, community occupancy model, terrestrial mammals

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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