The sign and magnitude of tree–grass interaction along a global environmental gradient

Autores
Mazía, Noemí; Moyano, Jaime; Pérez, Luis; Aguiar, Diego Sebastián; Garibaldi, Lucas Alejandro; Tomas, Schlichter
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Fil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
Fil: Moyano, Jaime. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.
Fil: Moyano, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.
Fil: Pérez, Luis. Universidad de Buenos Aires. Buenos Aires, Argentina.
Fil: Aguiar, Sebastián. Universidad de Buenos Aires. Buenos Aires, Argentina.
Fil: Garibaldi, Lucas A. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.
Fil: 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.
Fil: Schlichter, Tomas. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
Aim 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.
.
Materia
Ecología
Aridity Index
Competition
Facilitation
Grass Biomass
Meta-analysis
Plant Interactions
Ecología
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
RID-UNRN (UNRN)
Institución
Universidad Nacional de Río Negro
OAI Identificador
oai:rid.unrn.edu.ar:20.500.12049/7208

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repository_id_str 4369
network_name_str RID-UNRN (UNRN)
spelling The sign and magnitude of tree–grass interaction along a global environmental gradientMazía, NoemíMoyano, JaimePérez, LuisAguiar, Diego SebastiánGaribaldi, Lucas AlejandroTomas, SchlichterEcologíaAridity IndexCompetitionFacilitationGrass BiomassMeta-analysisPlant InteractionsEcologíaFil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.Fil: Moyano, Jaime. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.Fil: Moyano, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.Fil: Pérez, Luis. Universidad de Buenos Aires. Buenos Aires, Argentina.Fil: Aguiar, Sebastián. Universidad de Buenos Aires. Buenos Aires, Argentina.Fil: Garibaldi, Lucas A. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.Fil: 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.Fil: Schlichter, Tomas. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.Aim 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..Wiley2016-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfMazía, 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); 1510-1519.1466-822X1466-8238https://onlinelibrary.wiley.com/doi/abs/10.1111/geb.12518http://rid.unrn.edu.ar/handle/20.500.12049/7208https://doi.org/10.1111/geb.12518enghttp://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1466-823825 (12)Global Ecology and Biogeographyinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/reponame:RID-UNRN (UNRN)instname:Universidad Nacional de Río Negro2025-09-29T14:29:20Zoai:rid.unrn.edu.ar:20.500.12049/7208instacron:UNRNInstitucionalhttps://rid.unrn.edu.ar/jspui/Universidad públicaNo correspondehttps://rid.unrn.edu.ar/oai/snrdrid@unrn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:43692025-09-29 14:29:20.936RID-UNRN (UNRN) - Universidad Nacional de Río Negrofalse
dc.title.none.fl_str_mv The sign and magnitude of tree–grass interaction along a global environmental gradient
title The sign and magnitude of tree–grass interaction along a global environmental gradient
spellingShingle The sign and magnitude of tree–grass interaction along a global environmental gradient
Mazía, Noemí
Ecología
Aridity Index
Competition
Facilitation
Grass Biomass
Meta-analysis
Plant Interactions
Ecología
title_short The sign and magnitude of tree–grass interaction along a global environmental gradient
title_full The sign and magnitude of tree–grass interaction along a global environmental gradient
title_fullStr The sign and magnitude of tree–grass interaction along a global environmental gradient
title_full_unstemmed The sign and magnitude of tree–grass interaction along a global environmental gradient
title_sort The sign and magnitude of tree–grass interaction along a global environmental gradient
dc.creator.none.fl_str_mv Mazía, Noemí
Moyano, Jaime
Pérez, Luis
Aguiar, Diego Sebastián
Garibaldi, Lucas Alejandro
Tomas, Schlichter
author Mazía, Noemí
author_facet Mazía, Noemí
Moyano, Jaime
Pérez, Luis
Aguiar, Diego Sebastián
Garibaldi, Lucas Alejandro
Tomas, Schlichter
author_role author
author2 Moyano, Jaime
Pérez, Luis
Aguiar, Diego Sebastián
Garibaldi, Lucas Alejandro
Tomas, Schlichter
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ecología
Aridity Index
Competition
Facilitation
Grass Biomass
Meta-analysis
Plant Interactions
Ecología
topic Ecología
Aridity Index
Competition
Facilitation
Grass Biomass
Meta-analysis
Plant Interactions
Ecología
dc.description.none.fl_txt_mv Fil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
Fil: Moyano, Jaime. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.
Fil: Moyano, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina. Instituto de Investigaciones en Biodiversidad y Medioambiente. Rio Negro, Argentina.
Fil: Pérez, Luis. Universidad de Buenos Aires. Buenos Aires, Argentina.
Fil: Aguiar, Sebastián. Universidad de Buenos Aires. Buenos Aires, Argentina.
Fil: Garibaldi, Lucas A. Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina.
Fil: 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.
Fil: Schlichter, Tomas. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
Aim 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.
.
description Fil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Buenos Aires, Argentina.
publishDate 2016
dc.date.none.fl_str_mv 2016-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv Mazía, 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.
1466-822X
1466-8238
https://onlinelibrary.wiley.com/doi/abs/10.1111/geb.12518
http://rid.unrn.edu.ar/handle/20.500.12049/7208
https://doi.org/10.1111/geb.12518
identifier_str_mv Mazía, 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.
1466-822X
1466-8238
url https://onlinelibrary.wiley.com/doi/abs/10.1111/geb.12518
http://rid.unrn.edu.ar/handle/20.500.12049/7208
https://doi.org/10.1111/geb.12518
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1466-8238
25 (12)
Global Ecology and Biogeography
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:RID-UNRN (UNRN)
instname:Universidad Nacional de Río Negro
reponame_str RID-UNRN (UNRN)
collection RID-UNRN (UNRN)
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