Dominant species predict plant richness and biomass in global grasslands

• Autores: Zhang, Pengfei; Seabloom, Eric; Foo, Jasmine; MacDougall, Andrew S.; Harpole, W. Stanley; Adler, Peter; Hautier, Yann; Eisenhauer, Nico; Spohn, Marie; Bakker, Jonathan; Lekberg, Ylva; Young, Alyssa L.; Carbutt, Clinton; Risch, Anita C.; Peri, Pablo Luis; Smith, Nicholas G.; Stevens, Carly J.; Prober, Suzanne M.; Knops, Johannes M. H.; Wardle, Glenda M.; Dickman, Christopher R.; Ebeling, Anne; Roscher, Christiane; Martinson, Holly M.; Martina, Jason P.; Power, Sally A.; Niu, Yujie; Ren, Zhengwei; Du, Guozhen; Virtanen, Risto; Tognetti, Pedro Maximiliano; Tedder, Michelle J.; Jentsch, Anke; Catford, Jane A.; Borer, Elizabeth
• Año de publicación: 2025
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Plant species richness; Community biomass; Dominant species; Grasslands
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

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.
Fil: Zhang, Pengfei. University of Minnesota; Estados Unidos. Lanzhou University; China
Fil: Seabloom, Eric. University of Minnesota; Estados Unidos
Fil: Foo, Jasmine. University of Minnesota; Estados Unidos
Fil: MacDougall, Andrew S.. University of Guelph; Canadá
Fil: Harpole, W. Stanley. Helmholtz Centre for Environmental Research; Alemania. German Centre for Integrative Biodiversity Research; Alemania. Martin Luther University Halle-Wittenberg; Alemania
Fil: Adler, Peter. University of Utah; Estados Unidos
Fil: Hautier, Yann. Utrecht University; Países Bajos
Fil: Eisenhauer, Nico. German Centre for Integrative Biodiversity Research; Alemania. Universitat Leipzig; Alemania
Fil: Spohn, Marie. Swedish University of Agricultural Sciences; Suecia
Fil: Bakker, Jonathan. University of Washington; Estados Unidos
Fil: Lekberg, Ylva. University of Montana; Estados Unidos
Fil: Young, Alyssa L.. University of North Carolina; Estados Unidos
Fil: Carbutt, Clinton. University of KwaZulu-Natal; Sudáfrica. Ezemvelo KZN Wildlife; Sudáfrica
Fil: Risch, Anita C.. Swiss Federal Institute for Forest, Snow and Landscape Research; Suiza
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Smith, Nicholas G.. Texas Tech University; Estados Unidos
Fil: Stevens, Carly J.. Lancaster University; Reino Unido
Fil: Prober, Suzanne M.. CSIRO Environment; Australia
Fil: Knops, Johannes M. H.. Xi’an Jiaotong-Liverpool University; China
Fil: Wardle, Glenda M.. University of Sydney; Australia
Fil: Dickman, Christopher R.. University of Sydney; Australia
Fil: Ebeling, Anne. Universitat Jena; Alemania
Fil: Roscher, Christiane. Helmholtz Centre for Environmental Research; Alemania. German Centre for Integrative Biodiversity Research; Alemania
Fil: Martinson, Holly M.. McDaniel College; Estados Unidos
Fil: Martina, Jason P.. Texas State University; Estados Unidos
Fil: Power, Sally A.. University of Western Sydney; Australia
Fil: Niu, Yujie. University of Bayreuth; Alemania. Gansu Agricultural University; China
Fil: Ren, Zhengwei. Lanzhou University; China
Fil: Du, Guozhen. Lanzhou University; China
Fil: Virtanen, Risto. University Of Oulu (oy);
Fil: Tognetti, Pedro Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina
Fil: Tedder, Michelle J.. University of KwaZulu-Natal; Sudáfrica
Fil: Jentsch, Anke. University of Bayreuth; Alemania
Fil: Catford, Jane A.. Kings College London (kcl);
Fil: Borer, Elizabeth. University of Minnesota; Estados Unidos