Biodiversity-Ecosystem Function Research: Is It Relevant to Conservation?
Bibliographic record
Abstract
▪ Abstract It has often been argued that conserving biodiversity is necessary for maintaining ecosystem functioning. We critically evaluate the current evidence for this argument. Although there is substantial evidence that diversity is able to affect function, particularly for plant communities, it is unclear if these patterns will hold for realistic scenarios of extinctions, multitrophic communities, or larger spatial scales. Experiments are conducted at small spatial scales, the very scales at which diversity tends to increase owing to exotics. Stressors may affect function by many pathways, and diversity-mediated effects on function may be a minor pathway, except in the case of multiple-stressor insurance effects. In general, the conservation case is stronger for stability measures of function than stock and flux measures, in part because it is easier to attribute value unambiguously to stability and in part because stock and flux measures of functions are anticipated to be more affected by multitrophic dynamics. Nor is biodiversity-ecosystem function theory likely to help conservation managers in practical decisions, except in the particular case of restoration. We give recommendations for increasing the relevance of this area of research for conservation.
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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 | 0.032 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".