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Record W4408474355 · doi:10.1038/s42003-025-07882-7

Forb diversity globally is harmed by nutrient enrichment but can be rescued by large mammalian herbivory

2025· article· en· W4408474355 on OpenAlexaff
Rebecca A. Nelson, Lauren L. Sullivan, Erika I. Hersch‐Green, Eric W. Seabloom, Elizabeth T. Borer, Pedro M. Tognetti, Peter B. Adler, Lori Biederman, Miguel N. Bugalho, Maria C. Caldeira, Juan Pablo Cancela, Luísa G. Carvalheiro, Jane A. Catford, Chris R. Dickman, Aleksandra Dolezal, Ian Donohue, Anne Ebeling, Nico Eisenhauer, Kenneth J. Elgersma, Anu Eskelinen, Catalina Estrada, Magda Garbowski, Pamela Graff, Daniel S. Gruner, Nicole Hagenah, Sylvia Haider, W. Stanley Harpole, Yann Hautier, Anke Jentsch, Nicolina Johanson, Sally E. Koerner, Lucíola Santos Lannes, Andrew S. MacDougall, Holly M. Martinson, John W. Morgan, Harry Olde Venterink, Devyn Orr, Brooke B. Osborne, Pablo L. Peri, Sally A. Power, Xavier Raynaud, Anita C. Risch, Mani Shrestha, Nicholas G. Smith, Carly Stevens, G. F. Veen, Risto Virtanen, Glenda M. Wardle, Amelia A. Wolf, Alyssa L. Young, Susan Harrison

Bibliographic record

VenueCommunications Biology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Guelph
FundersNational Science Foundation
KeywordsForbHerbivoreSpecies richnessGrasslandNutrientEcologyBiologyBiodiversityGrazing

Abstract

fetched live from OpenAlex

Forbs ("wildflowers") are important contributors to grassland biodiversity but are vulnerable to environmental changes. In a factorial experiment at 94 sites on 6 continents, we test the global generality of several broad predictions: (1) Forb cover and richness decline under nutrient enrichment, particularly nitrogen enrichment. (2) Forb cover and richness increase under herbivory by large mammals. (3) Forb richness and cover are less affected by nutrient enrichment and herbivory in more arid climates, because water limitation reduces the impacts of competition with grasses. (4) Forb families will respond differently to nutrient enrichment and mammalian herbivory due to differences in nutrient requirements. We find strong evidence for the first, partial support for the second, no support for the third, and support for the fourth prediction. Our results underscore that anthropogenic nitrogen addition is a major threat to grassland forbs, but grazing under high herbivore intensity can offset these nutrient effects.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.275
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2025
Admission routes1
Has abstractyes

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