Diversity increases carbon storage and tree productivity in <scp>S</scp>panish forests
Bibliographic record
Abstract
Abstract Aim Biodiversity loss could reduce primary productivity and the carbon storage provided by forests; however, the mechanisms underpinning the effects of biodiversity on multiple ecosystem functions are not completely understood. Spanish forests are of particular interest because of the broad variation in environmental conditions and management history. We tested for the existence of a relationship between diversity effects and both carbon storage and tree productivity, and examined the relative importance of complementarity and selection mechanisms in a wide variety of forests, from cold deciduous Atlantic to xeric Mediterranean evergreen forests. Location Continental S pain. Methods We used c . 54,000 plots of the S panish F orest I nventory and maximum likelihood techniques to quantify how climate, stand structure and diversity shape carbon storage and tree productivity. Diversity effects included both complementarity and selection mechanisms, measured respectively through functional diversity and functional identity measures. Results Diversity had a significant effect on both carbon storage and tree productivity, even when controlling for confounding factors of climate and stand structure. A consistent positive effect of functional diversity on carbon storage and tree productivity was observed in all seven forest types studied. This relationship was not linear, and the largest changes in carbon storage and tree productivity were observed at low levels of functional diversity. However, the importance of complementarity effects was not consistent with the productivity of different forest types. Selection effects were particularly important in deciduous and Mediterranean pine forests, but had very little effect on mountain pines. Main conclusions We found a generally positive effect of diversity on carbon storage and tree productivity, supported by both complementarity and selection mechanisms. Thus, both functionally diverse forests and functionally important species should be maintained to adequately preserve and promote key ecosystem functions such as carbon storage and tree productivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".