A Meta-Analysis of Community Response Predictability to Anthropogenic Disturbances
Bibliographic record
Abstract
Disturbances often lead to changes in average values of community properties; however, disturbances can also affect the predictability of a community's response. We performed a meta-analysis to determine how response predictability, defined as among-replicate variance in diversity and community abundance, is affected by species removals, species invasions, nutrient addition, temperature increase, and habitat loss/fragmentation, and we further determined whether response predictability differed according to habitat and trophic role. Species removals and nutrient addition decreased response predictability, while species invasions increased response predictability. In aquatic habitats, disturbances generally led to a decrease in response predictability, whereas terrestrial habitats showed no overall change in response predictability, suggesting that differences in food web and ecosystem structure affect how communities respond to disturbance. Producers were also more likely to show decreases in response predictability, particularly following species removals, highlighting widespread destabilizing effects of species loss at the producer level. Overall, our results show that whether disturbances cause changes in response predictability is highly contingent on disturbance type, habitat, and trophic role. The nature of changes in response predictability--for example, strong decreases following species invasions and increases following species removals--will likely play a major role in how communities recover from disturbance.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".