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dc.contributor.authorAbades, Sabastián [Univ Mayor, Fac Sci, GEMA Ctr Gen Ecol & Environm, Huechuraba, Chile]es_CL
dc.contributor.authorQiu, Yanning; Teng, Shuqing N.; Zhang, Yong; Santana, Joana; Svenning, Jens-Christian; Reino, Luis; Ma, Haozhi; Yang, Luojun; Wu, Yiqian; Huang, Zheng Y. X.; Xu, Chies_CL
dc.date.accessioned2020-04-12T14:11:55Z
dc.date.accessioned2020-04-14T15:46:12Z
dc.date.available2020-04-12T14:11:55Z
dc.date.available2020-04-14T15:46:12Z
dc.date.issued2019es_CL
dc.identifier.citationQiu, Y., Teng, S. N., Zhang, Y., Santana, J., Svenning, J. C., Reino, L., ... & Huang, Z. Y. (2019). The resolution‐dependent role of landscape attributes in shaping macro‐scale biodiversity patterns. Global Ecology and Biogeography, 28(6), 767-778.es_CL
dc.identifier.issn1466-822Xes_CL
dc.identifier.issn1466-8238es_CL
dc.identifier.urihttps://doi.org/10.1111/geb.12889es_CL
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/abs/10.1111/geb.12889es_CL
dc.identifier.urihttp://repositorio.umayor.cl/xmlui/handle/sibum/6656
dc.description.abstractAim The aim was to assess whether and to what extent the role of local landscape attributes in shaping macroscopic biodiversity patterns is sensitive to spatial and thematic resolutions of land cover data. Location Sub-Saharan Africa and continental China. Time period Early 21st century. Taxa studied Terrestrial mammals. Methods We conducted spatial and thematic scaling analyses to generate land cover datasets of different spatial (0.3, 0.5, 1.0 and 9.0 km) and thematic (two, three and five classes) resolutions. We calculated landscape metrics based on the resulting land cover maps and examined the power of landscape metrics for explaining species richness patterns, using non-spatial (OLS) and spatial (SAR) linear models and random forest (RF) models. We systematically assessed the resolution dependence of explanatory power for different geographical regions, different scaling approaches and different model types. We also compared the explanatory power of landscape attributes with that of macroclimate. Results Collectively, local landscape attributes generally had strong explanatory power for species richness. For the African system, the largest explanatory power was c. 60% based on the OLS models and random forest models and c. 30% based on the non-spatial components of the SAR models. For the Chinese system, the largest explanatory power was c. 35% based on the OLS models and c. 40% based on the SAR and random forest models. We observed a linear scaling relationship, which is robust to studied systems, scaling approaches and model types. In contrast, the scaling relationship varies substantially among single landscape metrics. At coarse resolutions, the addition of landscape attributes collectively would not improve climate-envelope models significantly, whereas at finer resolutions, landscape attributes collectively have explanatory power that is close to or even exceeds climate. Main conclusions Local landscape attributes play an important role in shaping macroscopic biodiversity patterns. However, their strength is highly sensitive to both spatial and thematic resolutions of land cover data, with stronger explanatory power detected at finer resolutions. Strong sensitivity to spatial and thematic resolutions makes landscape attributes highly plastic determinants, leading to contrasting conclusions if based on greatly different resolutions of land cover data. Scaling analyses are needed to examine such cross-scale effects of macroecological determinants systematically.es_CL
dc.description.sponsorshipNational Key R&D Program of China [2017YFC0506200]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31770512, 31870400, 31500383]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [020814380089]; Norte Portugal Regional Operational Programme (NORTE 2020), PORTUGAL 2020 Partnership Agreement, European Regional Development Fund (ERDF) [POCI-01-0145-FEDER-016664]; FCT - Portuguese Science FoundationPortuguese Foundation for Science and Technology [PTDC/AAG-EC/5007/2014]; VILLUM FONDEN [16549]; FEDER funds through the Operational Programme for Competitiveness Factors - COMPETE; FCT - Foundation for Science and TechnologyPortuguese Foundation for Science and Technology [SFRH/BPD/93079/2013]; FONDECYTComision Nacional de Investigacion Cientifica y Tecnologica (CONICYT)CONICYT FONDECYT [1170995]es_CL
dc.description.sponsorshipThe National Key R&D Program of China, Grant/Award Number: 2017YFC0506200; National Natural Science Foundation of China, Grant/Award Number: 31770512, 31870400, and 31500383; The Fundamental Research Funds for the Central Universities, Grant/Award Number: 020814380089; Norte Portugal Regional Operational Programme (NORTE 2020), PORTUGAL 2020 Partnership Agreement, European Regional Development Fund (ERDF), Grant/Award Number: POCI-01-0145-FEDER-016664; National funds through FCT - Portuguese Science Foundation, Grant/Award Number: PTDC/AAG-EC/5007/2014; VILLUM FONDEN, Grant/Award Number: 16549; FEDER funds through the Operational Programme for Competitiveness Factors - COMPETE, National Funds through FCT - Foundation for Science and Technology under the post-doc grant, Grant/Award Number: SFRH/BPD/93079/2013; FONDECYT, Grant/Award Number: 1170995.es_CL
dc.language.isoenes_CL
dc.publisherWILEYes_CL
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.sourceGlob. Ecol. Biogeogr., JUN, 2019. 28(6): p. 767-778
dc.subjectEcology; Geography, Physicales_CL
dc.titleThe resolution-dependent role of landscape attributes in shaping macro-scale biodiversity patternses_CL
dc.typeArtículoes_CL
umayor.facultadCIENCIAS
umayor.politicas.sherpa/romeoRoMEO yellow journal (Puede archivar el pre-print (ie la versión previa a la revisión por pares). Disponible en: http://sherpa.ac.uk/romeo/index.phpes_CL
umayor.indexadoWOS:000467867300004es_CL
umayor.indexadoSIN PMIDes_CL
dc.identifier.doiDOI: 10.1111/geb.12889es_CL]
umayor.indicadores.wos-(cuartil)Q1es_CL
umayor.indicadores.scopus-(scimago-sjr)SCIMAGO/ INDICE H: 127 Hes_CL


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