Dominant species predict plant richness and biomass in global grasslands

Autores
Zhang,  Pengfei; Seabloom, Eric William; Foo,  Jasmine; MacDougall, Andrew S.; Harpole, William Stanley; Adler, Peter B.; Hautier, Yann; Eisenhauer, Nico; Spohn, Marie; Bakker, Jonathan D.; Peri, Pablo Luis; Borer, Elizabeth T.
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The bidirectional relationship between plant species richness and community biomass is often variable and poorly resolved in natural grassland ecosystems, impeding progress in predicting impacts of environmental changes. Most biological communities have long-tailed species abundance distributions (for example, biomass, cover, number of individuals), a general property that may provide predictive power for species richness and community biomass. Here we show mathematical relationships between community characteristics and the abundance of dominant species arising from long-tailed distributions and test these predictions using observational and experimental data from 76 grassland sites across 6 continents. We find that community biomass provides little predictive ability for community richness, consistent with previous findings. By contrast, the relative abundance of dominant species quantitatively predicts species richness, whereas their absolute abundance quantitatively predicts community biomass under both ambient and altered environmental conditions, as expected mathematically. These results are robust to the type of abundance measure used. Three types of simulated data further show the generality of these results. Our integrative framework, arising from a few dominant species and mathematical properties of species abundance distributions, fills a persistent gap in our ability to predict community richness and biomass under ambient and anthropogenically altered conditions.
EEA Santa Cruz, INTA
Fil: Zhang, Pengfei. Lanzhou University. College of Ecology. State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; China.
Fil: Zhang, Pengfei. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados Unidos
Fil: Seabloom, Eric William. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados Unidos
Fil: Foo, Jasmine. University of Minnesota. School of Mathematics; Estados Unidos
Fil: MacDougall, Andrew S. University of Guelph. Department of Integrative Biology; Canadá.
Fil: Harpole, William Stanley. German Centre for Integrative Biodiversity Research (iDiv); Alemania
Fil: Harpole, William Stanley. Helmholtz Centre for Environmental Research – UFZ. Department of Physiological Diversity; Alemania
Fil: Harpole, William Stanley. Martin Luther University Halle-Wittenberg; Alemania
Fil: Adler, Peter B. Utah State University. Department of Wildland Resources and the Ecology Center; Estaodos Unidos
Fil: Hautier, Yann. Utrecht University. Department of Biology. Ecology and Biodiversity Group; Países Bajos
Fil: Eisenhauer, Nico. German Centre for Integrative Biodiversity Research; Alemania
Fil: Eisenhauer, Nico. Leipzig University. Institute of Biology; Alemania
Fil: Spohn, Marie. Swedish University of Agricultural Sciences (SLU). Department of Soil and Environment; Suecia
Fil: Bakker, Jonathan D. University of Washington. School of Environmental and Forest Sciences; Estados Unidos
Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.
Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Borer, Elizabeth T. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados Unidos
Fuente
Nature Ecology & Evolution 9 : 924-936. (May 2025)
Materia
Pastures
Biomass
Dominant Species
Abundance
Pastizales
Biomasa
Especies Dominantes
Abundancia
Plant Richness
Community Biomass
Impacts of Environmental Changes
Community Richness
Riqueza Vegetal
Biomasa Comunitaria
Impactos de los Cambios Ambientales
Riqueza de la Comunidad
Nivel de accesibilidad
acceso restringido
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/22720

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network_name_str INTA Digital (INTA)
spelling Dominant species predict plant richness and biomass in global grasslandsZhang,  PengfeiSeabloom, Eric WilliamFoo,  JasmineMacDougall, Andrew S.Harpole, William StanleyAdler, Peter B.Hautier, YannEisenhauer, NicoSpohn, MarieBakker, Jonathan D.Peri, Pablo LuisBorer, Elizabeth T.PasturesBiomassDominant SpeciesAbundancePastizalesBiomasaEspecies DominantesAbundanciaPlant RichnessCommunity BiomassImpacts of Environmental ChangesCommunity RichnessRiqueza VegetalBiomasa ComunitariaImpactos de los Cambios AmbientalesRiqueza de la ComunidadThe bidirectional relationship between plant species richness and community biomass is often variable and poorly resolved in natural grassland ecosystems, impeding progress in predicting impacts of environmental changes. Most biological communities have long-tailed species abundance distributions (for example, biomass, cover, number of individuals), a general property that may provide predictive power for species richness and community biomass. Here we show mathematical relationships between community characteristics and the abundance of dominant species arising from long-tailed distributions and test these predictions using observational and experimental data from 76 grassland sites across 6 continents. We find that community biomass provides little predictive ability for community richness, consistent with previous findings. By contrast, the relative abundance of dominant species quantitatively predicts species richness, whereas their absolute abundance quantitatively predicts community biomass under both ambient and altered environmental conditions, as expected mathematically. These results are robust to the type of abundance measure used. Three types of simulated data further show the generality of these results. Our integrative framework, arising from a few dominant species and mathematical properties of species abundance distributions, fills a persistent gap in our ability to predict community richness and biomass under ambient and anthropogenically altered conditions.EEA Santa Cruz, INTAFil: Zhang, Pengfei. Lanzhou University. College of Ecology. State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; China.Fil: Zhang, Pengfei. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados UnidosFil: Seabloom, Eric William. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados UnidosFil: Foo, Jasmine. University of Minnesota. School of Mathematics; Estados UnidosFil: MacDougall, Andrew S. University of Guelph. Department of Integrative Biology; Canadá.Fil: Harpole, William Stanley. German Centre for Integrative Biodiversity Research (iDiv); AlemaniaFil: Harpole, William Stanley. Helmholtz Centre for Environmental Research – UFZ. Department of Physiological Diversity; AlemaniaFil: Harpole, William Stanley. Martin Luther University Halle-Wittenberg; AlemaniaFil: Adler, Peter B. Utah State University. Department of Wildland Resources and the Ecology Center; Estaodos UnidosFil: Hautier, Yann. Utrecht University. Department of Biology. Ecology and Biodiversity Group; Países BajosFil: Eisenhauer, Nico. German Centre for Integrative Biodiversity Research; AlemaniaFil: Eisenhauer, Nico. Leipzig University. Institute of Biology; AlemaniaFil: Spohn, Marie. Swedish University of Agricultural Sciences (SLU). Department of Soil and Environment; SueciaFil: Bakker, Jonathan D. University of Washington. School of Environmental and Forest Sciences; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Borer, Elizabeth T. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados UnidosSpringer Nature2025-06-19T10:11:47Z2025-06-19T10:11:47Z2025-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/22720https://www.nature.com/articles/s41559-025-02701-yZhang P.; Seabloom E.W.; Foo J.; Macdougall A.S.; Harpole W.S.; Adler P.B.; Hautier Y.; Eisenhauer N.; Muraina T.O.; Spohn M.; Bakker J.D.; (…); Peri P.L.; et al. (2025) Dominant species predict plant richness and biomass in global grasslands. Nature Ecology & Evolution 9: 924-936. https://doi.org/10.1038/s41559-025-02701-y2397-334X (online)https://doi.org/10.1038/s41559-025-02701-yNature Ecology & Evolution 9 : 924-936. (May 2025)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-16T09:32:21Zoai:localhost:20.500.12123/22720instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:32:21.75INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Dominant species predict plant richness and biomass in global grasslands
title Dominant species predict plant richness and biomass in global grasslands
spellingShingle Dominant species predict plant richness and biomass in global grasslands
Zhang,  Pengfei
Pastures
Biomass
Dominant Species
Abundance
Pastizales
Biomasa
Especies Dominantes
Abundancia
Plant Richness
Community Biomass
Impacts of Environmental Changes
Community Richness
Riqueza Vegetal
Biomasa Comunitaria
Impactos de los Cambios Ambientales
Riqueza de la Comunidad
title_short Dominant species predict plant richness and biomass in global grasslands
title_full Dominant species predict plant richness and biomass in global grasslands
title_fullStr Dominant species predict plant richness and biomass in global grasslands
title_full_unstemmed Dominant species predict plant richness and biomass in global grasslands
title_sort Dominant species predict plant richness and biomass in global grasslands
dc.creator.none.fl_str_mv Zhang,  Pengfei
Seabloom, Eric William
Foo,  Jasmine
MacDougall, Andrew S.
Harpole, William Stanley
Adler, Peter B.
Hautier, Yann
Eisenhauer, Nico
Spohn, Marie
Bakker, Jonathan D.
Peri, Pablo Luis
Borer, Elizabeth T.
author Zhang,  Pengfei
author_facet Zhang,  Pengfei
Seabloom, Eric William
Foo,  Jasmine
MacDougall, Andrew S.
Harpole, William Stanley
Adler, Peter B.
Hautier, Yann
Eisenhauer, Nico
Spohn, Marie
Bakker, Jonathan D.
Peri, Pablo Luis
Borer, Elizabeth T.
author_role author
author2 Seabloom, Eric William
Foo,  Jasmine
MacDougall, Andrew S.
Harpole, William Stanley
Adler, Peter B.
Hautier, Yann
Eisenhauer, Nico
Spohn, Marie
Bakker, Jonathan D.
Peri, Pablo Luis
Borer, Elizabeth T.
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Pastures
Biomass
Dominant Species
Abundance
Pastizales
Biomasa
Especies Dominantes
Abundancia
Plant Richness
Community Biomass
Impacts of Environmental Changes
Community Richness
Riqueza Vegetal
Biomasa Comunitaria
Impactos de los Cambios Ambientales
Riqueza de la Comunidad
topic Pastures
Biomass
Dominant Species
Abundance
Pastizales
Biomasa
Especies Dominantes
Abundancia
Plant Richness
Community Biomass
Impacts of Environmental Changes
Community Richness
Riqueza Vegetal
Biomasa Comunitaria
Impactos de los Cambios Ambientales
Riqueza de la Comunidad
dc.description.none.fl_txt_mv The bidirectional relationship between plant species richness and community biomass is often variable and poorly resolved in natural grassland ecosystems, impeding progress in predicting impacts of environmental changes. Most biological communities have long-tailed species abundance distributions (for example, biomass, cover, number of individuals), a general property that may provide predictive power for species richness and community biomass. Here we show mathematical relationships between community characteristics and the abundance of dominant species arising from long-tailed distributions and test these predictions using observational and experimental data from 76 grassland sites across 6 continents. We find that community biomass provides little predictive ability for community richness, consistent with previous findings. By contrast, the relative abundance of dominant species quantitatively predicts species richness, whereas their absolute abundance quantitatively predicts community biomass under both ambient and altered environmental conditions, as expected mathematically. These results are robust to the type of abundance measure used. Three types of simulated data further show the generality of these results. Our integrative framework, arising from a few dominant species and mathematical properties of species abundance distributions, fills a persistent gap in our ability to predict community richness and biomass under ambient and anthropogenically altered conditions.
EEA Santa Cruz, INTA
Fil: Zhang, Pengfei. Lanzhou University. College of Ecology. State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems; China.
Fil: Zhang, Pengfei. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados Unidos
Fil: Seabloom, Eric William. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados Unidos
Fil: Foo, Jasmine. University of Minnesota. School of Mathematics; Estados Unidos
Fil: MacDougall, Andrew S. University of Guelph. Department of Integrative Biology; Canadá.
Fil: Harpole, William Stanley. German Centre for Integrative Biodiversity Research (iDiv); Alemania
Fil: Harpole, William Stanley. Helmholtz Centre for Environmental Research – UFZ. Department of Physiological Diversity; Alemania
Fil: Harpole, William Stanley. Martin Luther University Halle-Wittenberg; Alemania
Fil: Adler, Peter B. Utah State University. Department of Wildland Resources and the Ecology Center; Estaodos Unidos
Fil: Hautier, Yann. Utrecht University. Department of Biology. Ecology and Biodiversity Group; Países Bajos
Fil: Eisenhauer, Nico. German Centre for Integrative Biodiversity Research; Alemania
Fil: Eisenhauer, Nico. Leipzig University. Institute of Biology; Alemania
Fil: Spohn, Marie. Swedish University of Agricultural Sciences (SLU). Department of Soil and Environment; Suecia
Fil: Bakker, Jonathan D. University of Washington. School of Environmental and Forest Sciences; Estados Unidos
Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.
Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fil: Borer, Elizabeth T. University of Minnesota. Department of Ecology, Evolution, and Behavior; Estados Unidos
description The bidirectional relationship between plant species richness and community biomass is often variable and poorly resolved in natural grassland ecosystems, impeding progress in predicting impacts of environmental changes. Most biological communities have long-tailed species abundance distributions (for example, biomass, cover, number of individuals), a general property that may provide predictive power for species richness and community biomass. Here we show mathematical relationships between community characteristics and the abundance of dominant species arising from long-tailed distributions and test these predictions using observational and experimental data from 76 grassland sites across 6 continents. We find that community biomass provides little predictive ability for community richness, consistent with previous findings. By contrast, the relative abundance of dominant species quantitatively predicts species richness, whereas their absolute abundance quantitatively predicts community biomass under both ambient and altered environmental conditions, as expected mathematically. These results are robust to the type of abundance measure used. Three types of simulated data further show the generality of these results. Our integrative framework, arising from a few dominant species and mathematical properties of species abundance distributions, fills a persistent gap in our ability to predict community richness and biomass under ambient and anthropogenically altered conditions.
publishDate 2025
dc.date.none.fl_str_mv 2025-06-19T10:11:47Z
2025-06-19T10:11:47Z
2025-06
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 http://hdl.handle.net/20.500.12123/22720
https://www.nature.com/articles/s41559-025-02701-y
Zhang P.; Seabloom E.W.; Foo J.; Macdougall A.S.; Harpole W.S.; Adler P.B.; Hautier Y.; Eisenhauer N.; Muraina T.O.; Spohn M.; Bakker J.D.; (…); Peri P.L.; et al. (2025) Dominant species predict plant richness and biomass in global grasslands. Nature Ecology & Evolution 9: 924-936. https://doi.org/10.1038/s41559-025-02701-y
2397-334X (online)
https://doi.org/10.1038/s41559-025-02701-y
url http://hdl.handle.net/20.500.12123/22720
https://www.nature.com/articles/s41559-025-02701-y
https://doi.org/10.1038/s41559-025-02701-y
identifier_str_mv Zhang P.; Seabloom E.W.; Foo J.; Macdougall A.S.; Harpole W.S.; Adler P.B.; Hautier Y.; Eisenhauer N.; Muraina T.O.; Spohn M.; Bakker J.D.; (…); Peri P.L.; et al. (2025) Dominant species predict plant richness and biomass in global grasslands. Nature Ecology & Evolution 9: 924-936. https://doi.org/10.1038/s41559-025-02701-y
2397-334X (online)
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv restrictedAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv Nature Ecology & Evolution 9 : 924-936. (May 2025)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection 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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