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dc.contributor.authorHilário, R. R.
dc.contributor.authorCarvalho, W. D.
dc.contributor.authorGheler-Costa, C.
dc.contributor.authorRosalino, L. M.C.
dc.contributor.authorMarques, T. A.
dc.contributor.authorAdania, C. H.
dc.contributor.authorPaulino, J. S.
dc.contributor.authorAlmeida, P. M.
dc.contributor.authorMustin, K.
dc.date.accessioned2022-06-23T23:35:53Z
dc.date.available2022-06-23T23:35:53Z
dc.date.issued2021-11-10
dc.identifier275669484
dc.identifier39f02df1-38b9-41c6-8ed4-5122c1d9318e
dc.identifier85108887961
dc.identifier.citationHilário , R R , Carvalho , W D , Gheler-Costa , C , Rosalino , L M C , Marques , T A , Adania , C H , Paulino , J S , Almeida , P M & Mustin , K 2021 , ' Drivers of human-wildlife impact events involving mammals in Southeastern Brazil ' , Science of the Total Environment , vol. 794 , 148600 . https://doi.org/10.1016/j.scitotenv.2021.148600en
dc.identifier.issn0048-9697
dc.identifier.otherORCID: /0000-0002-2581-1972/work/99465759
dc.identifier.urihttps://hdl.handle.net/10023/25562
dc.descriptionFunding Information: LMR thanks FCT / MCTES financial support to cE3c ( UIDB/00329/2020 ), through national funds, and the co-funding by the FEDER , within the PT2020 Partnership Agreement and Compete 2020. RRH thanks the support of the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior —Brasil (CAPES - Process 88881.314420/2019-01 ). WDC thanks CAPES for post-doctoral (PNPD/CAPES) scholarships. TAM thanks partial support by CEAUL (funded by FCT - Fundação para a Ciência e a Tecnologia , Portugal, through the project UIDB/00006/2020 ).en
dc.description.abstractAnnually millions of animals are killed as a result of human-wildlife impacts. Each year the NGO Associação Mata Ciliar (NGOMC), in Southeastern Brazil, receives and rehabilitates thousands of animals. We evaluated how natural and anthropogenic characteristics affect the risk of different types of human-wildlife impacts for mammals that arrive at the NGOMC; and explore the relationship between both the animal's size and the type of human-wildlife impact event, survival rates and the likelihood that these animals can be fully rehabilitated. To test our hypotheses regarding the drivers and consequences of the total number of human-wildlife impact events, traffic collisions, electrocutions, and requested removals, we used records of the mammals that arrived at the NGOMC between 2012 and 2018, and obtained data on environmental attributes and anthropogenic factors at the municipality level, as well as species weights. The total number of human-wildlife impact events and of requested removals were both positively correlated with deforestation rate and urban area. The number of traffic collisions was positively related to the number of fires. Municipalities with larger urban areas were more likely to have at least one electrocuted mammal. Temporally, the number of fires two months before was positively correlated with the number of human-wildlife impact events. Traffic collisions and electrocutions more frequently resulted in the death of the animal, than did other events. Animals that died were heavier on average than those that remained in captivity or were successfully released back into the wild. We conclude that human-wildlife impact event rates should decline with lower rates of deforestation, less anthropogenic fires and the adoption of other specific measures to avoid both traffic collisions with fauna and electrocutions.
dc.format.extent9
dc.format.extent741867
dc.language.isoeng
dc.relation.ispartofScience of the Total Environmenten
dc.subjectBiodiversity conservationen
dc.subjectHuman-wildlife conflicten
dc.subjectPowerlineen
dc.subjectRoaden
dc.subjectWild-Faunaen
dc.subjectGF Human ecology. Anthropogeographyen
dc.subjectQL Zoologyen
dc.subjectEnvironmental Chemistryen
dc.subjectEnvironmental Engineeringen
dc.subjectPollutionen
dc.subjectWaste Management and Disposalen
dc.subjectNDASen
dc.subjectACen
dc.subject.lccGFen
dc.subject.lccQLen
dc.titleDrivers of human-wildlife impact events involving mammals in Southeastern Brazilen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.identifier.doi10.1016/j.scitotenv.2021.148600
dc.description.statusPeer revieweden
dc.date.embargoedUntil2022-06-24


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