Functional trait space expansion explains productivity gains under moderate grazing

Appropriate grazing enhances grassland sustainability by simultaneously promoting biodiversity and productivity; however, the underlying mechanisms remain insufficiently understood. We tested the hypothesis that grazing enhances biomass production by expanding the functional trait space of plant communities thereby improving resource acquisition and utilization efficiency. In a Tibetan alpine meadow, we conducted a yak grazing experiment with four treatments: grazing exclusion, light, moderate, and heavy grazing. We measured 13 functional traits across 22 common plant species, which were categorized grazing increasers, decreasers, or generalists based on their abundance responses to grazing intensity. Grazing increased biomass production by 16.7–28.0% compared to exclusion, with moderate and heavy grazing significantly expanding the functional trait space. This expansion showed a strong positive correlation with biomass production, primarily mediated by increased variation in leaf traits among sedges, legumes, and grazing‐responsive species (i.e. increasers and generalists), which are associated with enhanced photosynthetic efficiency. Our study provides direct evidence for the ecological benefits of appropriate grazing and demonstrates, for the first time, how trait variation and species‐specific responses jointly mediate the effects of grazing on community‐level functional trait space and productivity. These findings advance mechanistic understanding of how individual plant responses to grazing scale up to influence ecosystem functioning and offer valuable insights for sustainable grassland management.

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Publication Details

Journal
Oikos
Published
2025-08-22
DOI
https://doi.org/10.1002/oik.11342
Citations
1
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
2.31
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article

Functional trait space expansion explains productivity gains under moderate grazing

Hongbiao Zi, Jin He, Ning Zhao, Kechang Niu et al.
1 citations
Oikos
Ecology and Vegetation Dynamics Studies
2.31
article

Functional trait space expansion explains productivity gains under moderate grazing

Hongbiao Zi, Jin He, Ning Zhao, Kechang Niu, Zhenhua Zhang, Yue Bai
article en
1 citations

Abstract

Appropriate grazing enhances grassland sustainability by simultaneously promoting biodiversity and productivity; however, the underlying mechanisms remain insufficiently understood. We tested the hypothesis that grazing enhances biomass production by expanding the functional trait space of plant communities thereby improving resource acquisition and utilization efficiency. In a Tibetan alpine meadow, we conducted a yak grazing experiment with four treatments: grazing exclusion, light, moderate, and heavy grazing. We measured 13 functional traits across 22 common plant species, which were categorized grazing increasers, decreasers, or generalists based on their abundance responses to grazing intensity. Grazing increased biomass production by 16.7–28.0% compared to exclusion, with moderate and heavy grazing significantly expanding the functional trait space. This expansion showed a strong positive correlation with biomass production, primarily mediated by increased variation in leaf traits among sedges, legumes, and grazing‐responsive species (i.e. increasers and generalists), which are associated with enhanced photosynthetic efficiency. Our study provides direct evidence for the ecological benefits of appropriate grazing and demonstrates, for the first time, how trait variation and species‐specific responses jointly mediate the effects of grazing on community‐level functional trait space and productivity. These findings advance mechanistic understanding of how individual plant responses to grazing scale up to influence ecosystem functioning and offer valuable insights for sustainable grassland management.

OikosVol. 2025(12)
Chinese Academy of Sciences (CN), Peking University (CN), Yili Normal University (CN), Ministry of Agriculture (EE), Xinjiang Institute of Ecology and Geography (CN)
Openalex Percentile: Top 11%
Ecology and Vegetation Dynamics Studies
2.31
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