Grazing‐induced shifts in community functional composition and soil nutrient availability in Tibetan alpine meadows
Bibliographic record
Abstract
Summary The functional structure of plant communities can be altered by grazing through two main mechanisms: species turnover (i.e. changes in species occurrence and relative abundance) and intraspecific trait variability ( ITV ), which is driven by phenotypic responses of individual plants and shifts in the relative abundance of genotypic variants within species. Studies of grassland ecosystem function under grazing often focus on community changes induced by species turnover, which ignores the effects of ITV on biomass productivity, soil carbon or nutrient availability. By quantifying the relative contribution of both effects on shifts in community‐wide traits, we highlight the role of ITV in community functional response to grazing and its implications for ecosystem function in Tibetan alpine meadows. We measured three chemical traits ( LC : leaf carbon, LN : leaf nitrogen and LP : leaf phosphorus concentrations) and two morphological traits ( SLA : specific leaf area, LDMC : leaf dry matter content) that are critical components of plant production and forage quality in grazed and ungrazed plots. Using variance decomposition of community‐weighted means ( CWM ) for these foliar traits, we distinguished the relative importance of ITV vs. change in species occurrence and abundance in response to grazing and the associated changes in soil carbon and nutrient availability. The CWM for foliar nutrients and SLA CWM increased in response to grazing together with decreases in soil carbon and nutrient stores, especially LP CWM enrichment and loss of available soil P. The LP CWM was strongly negatively correlated with LDMC CWM , which was significantly higher in ungrazed plots. These community‐wide trait responses to grazing were generally best captured by ITV and not changes in species occurrence and abundance, although ITV was consistently correlated with species turnover for all traits. Synthesis and applications . In response to continuous grazing, plants in Tibetan alpine meadows increase specific leaf area and foliar nutrients but tend to have lower leaf dry matter content, a response consistent with faster growth and regrowth under grazing. This intraspecific trait variability response drives a shift in community function from conservative, slow‐growing resource use in ungrazed meadows to exploitative resource use under grazing. This community‐wide functional response enhances forage quality, in turn favouring the secondary productivity of small herbivorous mammal communities, but also contributes to accelerated depletion of soil available phosphorus. We discuss the implications of these results for biodiversity conservation, ecosystem function and rangeland sustainability in the Qinghai–Tibetan Plateau, especially with regard to managing grazing rotation to strike a balance between favouring secondary productivity of domesticated stock vs. small herbivorous mammals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".