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      Margay ( Leopardus wiedii) in the southernmost Atlantic Forest: Density and activity patterns under different levels of anthropogenic disturbance

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          Abstract

          The margay ( Leopardus wiedii) is a small Neotropical arboreal wild cat. This species is thought to be forest-dependent, although few studies so far have directly evaluated the relationships between spatiotemporal aspects of its ecology and landscape characteristics. The aim of this study was to estimate margay population density and activity patterns in six areas with different habitat types and levels of anthropogenic disturbance in the southernmost Atlantic Forest of Brazil. Our working hypothesis was that density and activity patterns differed between areas in response to differences in forest cover and anthropogenic disturbance. Margay records were obtained using camera trapping, during spring and summer from 2017 to 2019. In all areas, the sampling scheme consisted of 20 un-baited stations, set 1km apart, each containing two paired cameras. We assessed the potential effects of environmental variables, including anthropogenic factors, on margay density, rate of detection and space use by comparing nine spatial capture-recapture (SCR) models. Activity patterns of the margay, its potential prey, and competitors were described and compared using the date and time of the records. We obtained 66 records of margay. Two of the six sampled areas were excluded from subsequent analyses due to the small number of records. The density estimated by the top-ranked model varied from 9.6±6.4 individuals/100km 2 in the area with the highest human disturbance to 37.4±15.1 individuals/100km 2 in a less disturbed area. Margay densities responded positively to vegetation cover, supporting the hypothesis of forest dependence by the species. Both the margay and their potential prey (small rodents and marsupials) were found to be mostly nocturnal. Margay activity also overlapped with that of the ocelot, Leopardus pardalis, and with mammals associated with human presence (wild boar, cattle, domestic dogs and cats). This is the first multi-area study on patterns of density and activity of the margay in the Brazilian Atlantic Forest. We concluded that the margay is mostly nocturnal, and while its densities are positively influenced by forest cover and negatively influenced by human disturbance, the activity pattern of the species does not seem to change across landscapes with distinct levels of human modification. Margay populations seem to be able to persist under moderate levels of habitat modification, highlighting the importance of preserving even small native forest remnants in the highly fragmented Atlantic Forest.

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          On the Relationship between Abundance and Distribution of Species

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            Spatially explicit maximum likelihood methods for capture-recapture studies.

            Live-trapping capture-recapture studies of animal populations with fixed trap locations inevitably have a spatial component: animals close to traps are more likely to be caught than those far away. This is not addressed in conventional closed-population estimates of abundance and without the spatial component, rigorous estimates of density cannot be obtained. We propose new, flexible capture-recapture models that use the capture locations to estimate animal locations and spatially referenced capture probability. The models are likelihood-based and hence allow use of Akaike's information criterion or other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its dependence on spatial or temporal covariates is therefore straightforward. Additional (nonspatial) variation in capture probability may be modeled as in conventional capture-recapture. The method is tested by simulation, using a model in which capture probability depends only on location relative to traps. Point estimators are found to be unbiased and standard error estimators almost unbiased. The method is used to estimate the density of Red-eyed Vireos (Vireo olivaceus) from mist-netting data from the Patuxent Research Refuge, Maryland, U.S.A. Estimates agree well with those from an existing spatially explicit method based on inverse prediction. A variety of additional spatially explicit models are fitted; these include models with temporal stratification, behavioral response, and heterogeneous animal home ranges.
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              sdm: a reproducible and extensible R platform for species distribution modelling

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Funding acquisitionRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 May 2020
                2020
                : 15
                : 5
                : e0232013
                Affiliations
                [1 ] Departamento de Zoologia, Programa de Pós-Graduação em Biologia Animal, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
                [2 ] Centre for Environmental and Marine Studies, Universidade de Aveiro, Aveiro, Portugal
                [3 ] Departamento de Biodiversidade, Setor de Mastozoologia, Museu de Ciências Naturais, Secretaria de Meio Ambiente e Infraestrutura, Porto Alegre, Rio Grande do Sul, Brazil
                [4 ] Instituto Pró-Carnívoros, Atibaia, São Paulo, Brazil
                [5 ] Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Escola de Ciências da Saúde e da Vida, Porto Alegre, Rio Grande do Sul, Brazil
                University of Sydney, AUSTRALIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                [¤]

                Current address: Departamento de Zoologia, Programa de Pós-Graduação em Biologia Animal, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

                Author information
                http://orcid.org/0000-0002-9197-5545
                Article
                PONE-D-19-34409
                10.1371/journal.pone.0232013
                7202647
                32374736
                d6bac08a-2986-4301-abf4-c646b9f6e624
                © 2020 Horn 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.

                History
                : 12 December 2019
                : 5 April 2020
                Page count
                Figures: 9, Tables: 5, Pages: 25
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100002322, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100002322, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100012311, Panthera;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100007463, Rufford Foundation;
                Award Recipient :
                PEH: CAPES MSc Schoolarship FPT: PNPD/CAPES Fellowship MJRP: CNPq Productivity Grant EE: CNPq Productivity Grant CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior ( https://www.capes.gov.br/) CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico ( https://www.cnpq.br) Panthera ( https://www.panthera.org) The Rufford Foundation ( https://www.rufford.org/) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Forests
                Ecology and Environmental Sciences
                Terrestrial Environments
                Forests
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Cats
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Cats
                Ocelots
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Birds
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Population Density
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Animal Types
                Domestic Animals
                Biology and Life Sciences
                Zoology
                Animal Types
                Domestic Animals
                Ecology and Environmental Sciences
                Conservation Science
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                All relevant data are within the paper and its Supporting Information files.

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