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
- Institución
- Universidad Nacional de Río Negro
- OAI Identificador
- oai:rid.unrn.edu.ar:20.500.12049/7208
Ver los metadatos del registro completo
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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 |
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info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/4.0/ |
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application/pdf |
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Wiley |
publisher.none.fl_str_mv |
Wiley |
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