Grazing exclusion unleashes competitive plant responses in Iberian Atlantic mountain grasslands
Bibliographic record
Abstract
Abstract Questions Does the absence of equalizing mechanisms after cessation of grazing unleash strong above‐ground competitors to create large patches in the community? Do these competitive intraspecific aggregations displace and exclude other species, thereby reducing species diversity? Location Atlantic grasslands, Aralar Natural Park, Basque Country, Northern Iberian Peninsula. Methods Large herbivores were experimentally excluded from three sites (50 m × 50 m exclusion fences) during 9 yr in a productive semi‐natural grassland system with a long history of grazing, using adjacent grazed plots as experimental controls. Sampling was carried out by systematically placing 100 quadrats (0.5 m × 0.5 m) in each of the six plots. Floristic composition and abundance, as well as eight hydrological and chemical soil properties, were measured in each quadrat. The spatial structures created by competitive species were analysed usingRDAin conjunction with Moran's eigenvector maps, and soil variables were simultaneously included in the analyses, thus disentangling the structures likely created by niche effects. Competitive exclusion was further determined using linear regressions between species richness and abundance of competitive species. Results Grazing exclusion unleashed competitive species such asFestuca microphyllaandAgrostis capillaris, which became dominant in the exclusion plots and created large spatial patches. Furthermore, a negative linear relationship, consistent across exclusion plots, was observed between species richness and abundance of competitive species, indicating that strong above‐ground competitors outcompeted other species when herbivores were excluded. However, the outcome of grazing exclusion across sites depended to some extent on local environmental conditions (niche effects). Conclusions This work confirms that the powerful equalizing mechanism of disturbance by herbivores is crucial for species co‐existence in productive grasslands. However, important differences observed in environmental effects across sites suggest that, even in highly productive grasslands, plant traits and local environmental characteristics (niche effects) do matter for species co‐existence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".