Evidence map›Paper›PMID 40360678›Full record

ArticleNature ecology & evolution2025

Dominant species predict plant richness and biomass in global grasslands.

Pengfei Zhang, Eric W Seabloom, Jasmine Foo, Andrew S MacDougall, W Stanley Harpole, Peter B Adler, Yann Hautier, Nico Eisenhauer, Marie Spohn, Jonathan D Bakker and 25 more

Abstract read
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Article in Nature ecology & evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

35 authors.

Pengfei ZhangState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, People's Republic of China. zhangpengfei@lzu.edu.cn.ORCID http://orcid.org/0000-0001-7959-9092
Eric W SeabloomDepartment of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA.ORCID http://orcid.org/0000-0001-6780-9259
Jasmine FooSchool of Mathematics, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0001-8238-325X
Andrew S MacDougallDepartment of Integrative Biology, University of Guelph, Guelph, Ontario, Canada.
W Stanley HarpoleDepartment of Physiological Diversity, Helmholtz Center for Environmental Research-UFZ, Leipzig, Germany.ORCID http://orcid.org/0000-0002-3404-9174
Peter B AdlerDepartment of Wildland Resources and the Ecology Center, Utah State University, Logan, UT, USA.ORCID http://orcid.org/0000-0002-4216-4009
Yann HautierEcology and Biodiversity Group, Department of Biology, Utrecht University, Utrecht, The Netherlands.
Nico EisenhauerGerman Centre for Integrative Biodiversity Research (iDiv), Leipzig, Germany.ORCID http://orcid.org/0000-0002-0371-6720
Marie SpohnDepartment of Soil and Environment, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden.ORCID http://orcid.org/0000-0002-1010-7317
Jonathan D BakkerSchool of Environmental and Forest Sciences, University of Washington, Seattle, WA, USA.ORCID http://orcid.org/0000-0002-8973-2771
Ylva LekbergMPG Ranch Missoula, Florence, MT, USA.ORCID http://orcid.org/0000-0003-1033-8032
Alyssa L YoungDepartment of Biology, University of North Carolina Greensboro, Greensboro, NC, USA.ORCID http://orcid.org/0000-0002-2373-4264
Clinton CarbuttSchool of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa.ORCID http://orcid.org/0000-0002-1540-0029
Anita C RischSwiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland.ORCID http://orcid.org/0000-0003-0531-8336
Pablo L PeriInstituto Nacional de Tecnología Agropecuaria (INTA)-Universidad Nacional de la Patagonia Austral (UNAP)-CONICET, Río Gallegos, Argentina.ORCID http://orcid.org/0000-0002-5398-4408
Nicholas G SmithDepartment of Biological Sciences, Texas Tech University, Lubbock, TX, USA.ORCID http://orcid.org/0000-0001-7048-4387
Carly J StevensLancaster Environment Centre, Lancaster University, Lancaster, UK.ORCID http://orcid.org/0000-0002-2390-1763
Suzanne M ProberCSIRO Environment, Canberra, Australian Capital Territory, Australia.
Johannes M H KnopsHealth and Environmental Sciences Department, Xi'an Jiaotong-Liverpool University, Suzhou, People's Republic of China.
Glenda M WardleDesert Ecology Research Group, School of Life and Environmental Sciences and ARC Training Centre in Data Analytics for Resources and Environments (DARE), The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0003-0189-1899
Christopher R DickmanDesert Ecology Research Group, School of Life and Environmental Sciences and ARC Training Centre in Data Analytics for Resources and Environments (DARE), The University of Sydney, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0002-1067-3730
Anne EbelingInstitute of Ecology and Evolution, University Jena, Jena, Germany.ORCID http://orcid.org/0000-0002-3221-4017
Christiane RoscherDepartment of Physiological Diversity, Helmholtz Center for Environmental Research-UFZ, Leipzig, Germany.ORCID http://orcid.org/0000-0001-9301-7909
Holly M MartinsonDepartment of Biology, McDaniel College, Westminster, MD, USA.ORCID http://orcid.org/0000-0003-1462-0051
Jason P MartinaDepartment of Biology, Texas State University, San Marcos, TX, USA.ORCID http://orcid.org/0000-0002-3912-4911
Sally A PowerHawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia.ORCID http://orcid.org/0000-0002-2723-8671
Yujie NiuDepartment of Disturbance Ecology and Vegetation Dynamics, Bayreuth Center of Ecology and Environmental Research (Bayceer), University of Bayreuth, Bayreuth, Germany.ORCID http://orcid.org/0000-0002-0912-8401
Zhengwei RenState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, People's Republic of China.
Guozhen DuState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, People's Republic of China.
Risto VirtanenEcology & Genetics, University of Oulu, Oulu, Finland.ORCID http://orcid.org/0000-0002-8295-8217
Pedro TognettiIFEVA, Facultad de Agronomía, Universidad de Buenos Aires-CONICET, Buenos Aires, Argentina.ORCID http://orcid.org/0000-0001-7358-1334
Michelle J TedderSchool of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa.ORCID http://orcid.org/0000-0001-8021-0929
Anke JentschDepartment of Disturbance Ecology and Vegetation Dynamics, Bayreuth Center of Ecology and Environmental Research (Bayceer), University of Bayreuth, Bayreuth, Germany.ORCID http://orcid.org/0000-0002-2345-8300
Jane A CatfordDepartment of Geography, King's College London, London, UK.ORCID http://orcid.org/0000-0003-0582-5960
Elizabeth T BorerDepartment of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA.ORCID http://orcid.org/0000-0003-2259-5853

Funding

Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) FKZ 031B0516C + 031B1067CDeutsche Forschungsgemeinschaft (German Research Foundation) DFG' FZT 118, 202548816; Ei 862/29-1EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 101002987National Natural Science Foundation of China (National Science Foundation of China) 32101267National Science Foundation (NSF) DEB-2045968National Science Foundation (NSF) NSF-DEB-1042132National Science Foundation (NSF) NSF-DEB-1234162UM | Institute on the Environment, University of Minnesota (IonE) DG-0001-13
6 · The paper itself

Abstract

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.

Indexed as

BiodiversityBiomassGrasslandPlantsModels, Biological

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.