Taxonomic and functional diversity in Mediterranean pastures: insights on the biodiversity–productivity trade‐off
Bibliographic record
Abstract
Summary Agricultural intensification is one of the main causes of biodiversity loss world‐wide. The inclusion of semi‐natural features in agricultural landscapes is suggested as a means of enhancing farm biodiversity, but this practice may have potential negative effects on yield production. Moreover, little evidence exists for effects of semi‐natural features on other components of biodiversity, such as functional diversity. Yet this could provide a more comprehensive understanding of biodiversity–productivity trade‐offs. Here, we report the effects of semi‐natural woody vegetation on taxonomic and functional diversity, and biomass production of herbaceous species at the field and farm scales by sampling 50 fields, ranging from 0 to 90% woody vegetation cover, on nine similarly managed farms in central‐western Spain. We found significant differences in herbaceous species richness among farms. Both taxonomic and functional β‐diversity exhibited significant negative relationships with herbage production, highlighting the trade‐off between biodiversity and productivity in these agroecosystems. Woody vegetation cover had a significant negative relationship with biomass production and a unimodal relationship with species richness at the field scale. At high values of woody vegetation cover, species richness and functional diversity indices were decoupled, suggesting that at this extreme of the woody vegetation gradient, only herbaceous species with contrasting trait values were present. Our results showed both convergent and divergent patterns of trait values, suggesting that different assembly processes are acting concurrently along the gradient of woody vegetation. Synthesis and applications . Our result indicates that management of woody vegetation may indeed increase both taxonomic and functional diversity, but this may come at the expense of key ecosystem services or other management goals, namely herbage production. Optimization of the trade‐off between herbage diversity and productivity can be reached with a woody vegetation cover of c. 30% at the field scale.
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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 | 0.000 | 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) | 0.000 | 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".