Effects of functional diversity loss on ecosystem functions are influenced by compensation
Bibliographic record
Abstract
Abstract Understanding the impacts of biodiversity loss on ecosystem functioning and services has been a central issue in ecology. Experiments in synthetic communities suggest that biodiversity loss may erode a set of ecosystem functions, but studies in natural communities indicate that the effects of biodiversity loss are usually weak and that multiple functions can be sustained by relatively few species. Yet, the mechanisms by which natural ecosystems are able to maintain multiple functions in the face of diversity loss remain poorly understood. With a long‐term and large‐scale removal experiment in the Inner Mongolian grassland, here we showed that losses of plant functional groups ( PFG s) can reduce multiple ecosystem functions, including biomass production, soil NO 3 ‐N use, net ecosystem carbon exchange, gross ecosystem productivity, and ecosystem respiration, but the magnitudes of these effects depended largely on which PFG s were removed. Removing the two dominant PFG s (perennial rhizomatous grasses and perennial bunchgrasses) simultaneously resulted in dramatic declines in all examined functions, but such declines were circumvented when either dominant PFG was present. We identify the major mechanism for this as a compensation effect by which each dominant PFG can mitigate the losses of others. This study provides evidence that compensation ensuing from PFG losses can mitigate their negative consequence, and thus natural communities may be more resilient to biodiversity loss than currently thought if the remaining PFG s have strong compensation capabilities. On the other hand, ecosystems without well‐developed compensatory functional diversity may be much more vulnerable to biodiversity loss.
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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) | 0.001 | 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 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".