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dc.contributor.authorHua, Fangyuan
dc.contributor.authorWang, Weiyi
dc.contributor.authorNakagawa, Shinichi
dc.contributor.authorLiu, Shuangqi
dc.contributor.authorMiao, Xinran
dc.contributor.authorYu, Le
dc.contributor.authorDu, Zhenrong
dc.contributor.authorAbrahamczyk, Stefan
dc.contributor.authorArias-Sosa, Luis Alejandro
dc.contributor.authorBuda, Kingda
dc.contributor.authorBudka, Michał
dc.contributor.authorCarrière, Stéphanie M.
dc.contributor.authorChandler, Richard B.
dc.contributor.authorChiatante, Gianpasquale
dc.contributor.authorChiavo, David O.
dc.contributor.authorCresswell, Will
dc.contributor.authorEcheverri, Alejandra
dc.contributor.authorGoodale, Eben
dc.contributor.authorHuang, Guohualing
dc.contributor.authorHulme, Mark F.
dc.contributor.authorHutto, Richard L.
dc.contributor.authorImboma, Titus S.
dc.contributor.authorJarrett, Crinan
dc.contributor.authorJiang, Zhigang
dc.contributor.authorKati, Vassiliki I.
dc.contributor.authorKing, David I.
dc.contributor.authorKmecl, Primož
dc.contributor.authorLi, Na
dc.contributor.authorLövei, Gábor L.
dc.contributor.authorMacchi, Leandro
dc.contributor.authorMacGregor-Fors, Ian
dc.contributor.authorMartin, Emily A.
dc.contributor.authorMira, António
dc.contributor.authorMorelli, Frederico
dc.contributor.authorOrtega-Álvarez, Rubén
dc.contributor.authorQuan, Rui-Chang
dc.contributor.authorSalgueiro, Pedro A.
dc.contributor.authorSantos, Sara M.
dc.contributor.authorShahabuddin, Ghazala
dc.contributor.authorSocolar, Jacob B.
dc.contributor.authorSoh, Malcolm C. K.
dc.contributor.authorSreekar, Rachakonda
dc.contributor.authorSrinivasan, Umesh
dc.contributor.authorWilcove, David S.
dc.contributor.authorYamaura, Yuichi
dc.contributor.authorZhou, Liping
dc.contributor.authorElsen, Paul R.
dc.date.accessioned2024-07-04T23:36:47Z
dc.date.available2024-07-04T23:36:47Z
dc.date.issued2024-02
dc.identifier295405184
dc.identifierbc9dcf5d-9aba-4231-8c91-0d6859c4dc85
dc.identifier85181436913
dc.identifier.citationHua , F , Wang , W , Nakagawa , S , Liu , S , Miao , X , Yu , L , Du , Z , Abrahamczyk , S , Arias-Sosa , L A , Buda , K , Budka , M , Carrière , S M , Chandler , R B , Chiatante , G , Chiavo , D O , Cresswell , W , Echeverri , A , Goodale , E , Huang , G , Hulme , M F , Hutto , R L , Imboma , T S , Jarrett , C , Jiang , Z , Kati , V I , King , D I , Kmecl , P , Li , N , Lövei , G L , Macchi , L , MacGregor-Fors , I , Martin , E A , Mira , A , Morelli , F , Ortega-Álvarez , R , Quan , R-C , Salgueiro , P A , Santos , S M , Shahabuddin , G , Socolar , J B , Soh , M C K , Sreekar , R , Srinivasan , U , Wilcove , D S , Yamaura , Y , Zhou , L & Elsen , P R 2024 , ' Ecological filtering shapes the impacts of agricultural deforestation on biodiversity ' , Nature Ecology and Evolution , vol. 8 , pp. 251–266 . https://doi.org/10.1038/s41559-023-02280-wen
dc.identifier.issn2397-334X
dc.identifier.otherORCID: /0000-0002-4684-7624/work/152318063
dc.identifier.urihttps://hdl.handle.net/10023/30097
dc.descriptionFunding: This project was funded by the National Natural Science Foundation of China (Grants 32122057 and 3198810 to FH) and the Ministry of Science and Technology of China (Grant 2022YFF0802300 to FH), and received further support from Tsinghua University Initiative Scientific Research Program (Grant 20223080017 to LY).en
dc.description.abstractThe biodiversity impacts of agricultural deforestation vary widely across regions. Previous efforts to explain this variation have focused exclusively on the landscape features and management regimes of agricultural systems, neglecting the potentially critical role of ecological filtering in shaping deforestation tolerance of extant species assemblages at large geographical scales via selection for functional traits. Here we provide a large-scale test of this role using a global database of species abundance ratios between matched agricultural and native forest sites that comprises 71 avian assemblages reported in 44 primary studies, and a companion database of 10 functional traits for all 2,647 species involved. Using meta-analytic, phylogenetic and multivariate methods, we show that beyond agricultural features, filtering by the extent of natural environmental variability and the severity of historical anthropogenic deforestation shapes the varying deforestation impacts across species assemblages. For assemblages under greater environmental variability—proxied by drier and more seasonal climates under a greater disturbance regime—and longer deforestation histories, filtering has attenuated the negative impacts of current deforestation by selecting for functional traits linked to stronger deforestation tolerance. Our study provides a previously largely missing piece of knowledge in understanding and managing the biodiversity consequences of deforestation by agricultural deforestation.
dc.format.extent29
dc.format.extent1436552
dc.language.isoeng
dc.relation.ispartofNature Ecology and Evolutionen
dc.subjectDASen
dc.titleEcological filtering shapes the impacts of agricultural deforestation on biodiversityen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. Centre for Biological Diversityen
dc.contributor.institutionUniversity of St Andrews. Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews. St Andrews Sustainability Instituteen
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.identifier.doihttps://doi.org/10.1038/s41559-023-02280-w
dc.description.statusPeer revieweden
dc.date.embargoedUntil2024-07-05


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