Skip navigation
Por favor, use este identificador para citar o enlazar este ítem: http://rid.unrn.edu.ar/handle/20.500.12049/7208

Registro completo de metadatos
Campo DC Valor Lengua/Idioma
dc.contributor.authorMazía, Noemí-
dc.contributor.authorMoyano, Jaime-
dc.contributor.authorPérez, Luis-
dc.contributor.authorAguiar, Diego Sebastián-
dc.contributor.authorGaribaldi, Lucas Alejandro-
dc.contributor.authorTomas, Schlichter-
dc.date.accessioned2021-06-08T11:40:41Z-
dc.date.available2021-06-08T11:40:41Z-
dc.date.issued2016-09-
dc.identifier.citationMazía, N., Moyano, J., Perez, L., Aguiar, S., Garibaldi, L. A., & Schlichter, T. (2016). The sign and magnitude of tree–grass interaction along a global environmental gradient. Global Ecology and Biogeography; 25 (12); 1510-1519.es_ES
dc.identifier.issn1466-822Xes_ES
dc.identifier.issn1466-8238es_ES
dc.identifier.otherhttps://onlinelibrary.wiley.com/doi/abs/10.1111/geb.12518es_ES
dc.identifier.urihttp://rid.unrn.edu.ar/handle/20.500.12049/7208-
dc.description.abstractAim The ecological literature posits that positive interactions are preponderant in stressful environments; however, the net balance between positive and negative interactions at the community level is still under debate. This study analysed the effect of trees on grass biomass in natural and cultivated woody systems distributed along a global aridity index (AI) gradient. Location Global. Methods We conducted a meta-analysis including eight natural biomes and tree plantations distributed in five continents. The final database consisted of 93 data pairs across 65 locations spanning a gradient from AI = 0.1 to AI = 2.1, which covered annual precipitation ranging from 70 to 3500 mm. Effect size was calculated as the difference between above-ground grass biomass beneath and outside the tree canopy. We built linear models to evaluate the importance of different biotic and abiotic variables as potential drivers of the effect size. Multimodel inference, based on the Akaike information criterion (AICc) was used to select the best models. Results The whole data set shows a shift from net facilitation to net competition along an increasing AI gradient. AI had the highest relative importance in explaining the sign and magnitude of the effect size. Tree characteristics (deciduous–evergreen and leguminous–non-leguminous) were the other predictive variables consistently included in almost all the 10 best models. Deciduous and leguminous trees enhanced grass biomass growing beneath them. Increasing soil sand content, C4 grasses and tropical and natural systems all increased the biomass of grasses growing beneath trees, but their relative importance was substantially lower than that of the AI and tree characteristics. Main conclusions The results of our global meta-analysis showed that climatic context and the characteristics of benefactor trees both represent the main drivers of the sign and magnitude of tree–grass interactions. These findings may contribute to advancing knowledge of the mechanisms behind the global patterns.es_ES
dc.format.extentp. 1510-1519es_ES
dc.language.isoenes_ES
dc.publisherWileyes_ES
dc.relation.urihttp://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1466-8238es_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/-
dc.titleThe sign and magnitude of tree–grass interaction along a global environmental gradientes_ES
dc.typeArticuloes_ES
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)-
dc.description.filiationFil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.es_ES
dc.description.filiationFil: Moyano, Jaime. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.es_ES
dc.description.filiationFil: Moyano, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.es_ES
dc.description.filiationFil: Pérez, Luis. Universidad de Buenos Aires. Buenos Aires, Argentina.es_ES
dc.description.filiationFil: Aguiar, Sebastián. Universidad de Buenos Aires. Buenos Aires, Argentina.es_ES
dc.description.filiationFil: Garibaldi, Lucas A. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.es_ES
dc.description.filiationFil: Garibaldi, Lucas A. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.es_ES
dc.description.filiationFil: Schlichter, Tomas. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.es_ES
dc.subject.keywordAridity Indexes_ES
dc.subject.keywordCompetitiones_ES
dc.subject.keywordFacilitationes_ES
dc.subject.keywordGrass Biomasses_ES
dc.subject.keywordMeta-analysises_ES
dc.subject.keywordPlant Interactionses_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.subject.materiaEcologíaes_ES
dc.origin.lugarDesarrolloUniversidad de Buenos Aireses_ES
dc.relation.journalissue25 (12)es_ES
dc.description.reviewtruees_ES
dc.description.resumen.es_ES
dc.identifier.doihttps://doi.org/10.1111/geb.12518-
dc.relation.journalTitleGlobal Ecology and Biogeographyes_ES
Aparece en las colecciones: Artículos

Archivos en este ítem:
Archivo Descripción Tamaño Formato  
0b3a91_cc2b318ad34d44859ca50550224b44ba.pdf306,9 kBAdobe PDFVisualizar/Abrir

Este documento es resultado del financiamiento otorgado por el Estado Nacional, por lo tanto queda sujeto al cumplimiento de la Ley N° 26.899


Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons Creative Commons