The sign and magnitude of tree–grass interaction along a global environmental gradient
- Autores
- Mazía, Noemí; Moyano, Jaime; Pérez, Luis; Aguiar, Sebastián; Garibaldi, Lucas Alejandro; Schlichter, Tomas Miguel
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión aceptada
- Descripción
- 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.
Fil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina
Fil: Moyano, Jaime. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina
Fil: Pérez, Luis. Universidad de Buenos Aires. Facultad de Agronomía; Argentina
Fil: Schlichter, Tomas Miguel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina - Fuente
- Global ecology and biogeography 25 (12) : 1510–1519. (December 2016)
- Materia
-
Medio Ambiente
Environment
Grasses
Trees
Gramíneas
Arboles - Nivel de accesibilidad
- acceso restringido
- Condiciones de uso
- Repositorio
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/1621
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The sign and magnitude of tree–grass interaction along a global environmental gradientMazía, NoemíMoyano, JaimePérez, LuisAguiar, SebastiánGaribaldi, Lucas AlejandroSchlichter, Tomas MiguelMedio AmbienteEnvironmentGrassesTreesGramíneasArbolesAim: 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.Fil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; ArgentinaFil: Moyano, Jaime. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; ArgentinaFil: Pérez, Luis. Universidad de Buenos Aires. Facultad de Agronomía; ArgentinaFil: Schlichter, Tomas Miguel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina2017-10-30T13:41:25Z2017-10-30T13:41:25Z2016-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/1621http://onlinelibrary.wiley.com/doi/10.1111/geb.12518/abstract1466-822X (Print)1466-8238 (Online)DOI: 10.1111/geb.12518Global ecology and biogeography 25 (12) : 1510–1519. (December 2016)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-09-29T13:44:13Zoai:localhost:20.500.12123/1621instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:13.397INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
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 Medio Ambiente Environment Grasses Trees Gramíneas Arboles |
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, Sebastián Garibaldi, Lucas Alejandro Schlichter, Tomas Miguel |
author |
Mazía, Noemí |
author_facet |
Mazía, Noemí Moyano, Jaime Pérez, Luis Aguiar, Sebastián Garibaldi, Lucas Alejandro Schlichter, Tomas Miguel |
author_role |
author |
author2 |
Moyano, Jaime Pérez, Luis Aguiar, Sebastián Garibaldi, Lucas Alejandro Schlichter, Tomas Miguel |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Medio Ambiente Environment Grasses Trees Gramíneas Arboles |
topic |
Medio Ambiente Environment Grasses Trees Gramíneas Arboles |
dc.description.none.fl_txt_mv |
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. Fil: Mazía, Noemí. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina Fil: Moyano, Jaime. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; Argentina Fil: Pérez, Luis. Universidad de Buenos Aires. Facultad de Agronomía; Argentina Fil: Schlichter, Tomas Miguel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina |
description |
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. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-12 2017-10-30T13:41:25Z 2017-10-30T13:41:25Z |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
acceptedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/20.500.12123/1621 http://onlinelibrary.wiley.com/doi/10.1111/geb.12518/abstract 1466-822X (Print) 1466-8238 (Online) DOI: 10.1111/geb.12518 |
url |
http://hdl.handle.net/20.500.12123/1621 http://onlinelibrary.wiley.com/doi/10.1111/geb.12518/abstract |
identifier_str_mv |
1466-822X (Print) 1466-8238 (Online) DOI: 10.1111/geb.12518 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
eu_rights_str_mv |
restrictedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
Global ecology and biogeography 25 (12) : 1510–1519. (December 2016) reponame:INTA Digital (INTA) instname:Instituto Nacional de Tecnología Agropecuaria |
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INTA Digital (INTA) |
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INTA Digital (INTA) |
instname_str |
Instituto Nacional de Tecnología Agropecuaria |
repository.name.fl_str_mv |
INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria |
repository.mail.fl_str_mv |
tripaldi.nicolas@inta.gob.ar |
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