Large-Scale Variation in Combined Impacts of Canopy Loss and Disturbance on Community Structure and Ecosystem Functioning
Bibliographic record
Abstract
Ecosystems are under pressure from multiple human disturbances whose impact may vary depending on environmental context. We experimentally evaluated variation in the separate and combined effects of the loss of a key functional group (canopy algae) and physical disturbance on rocky shore ecosystems at nine locations across Europe. Multivariate community structure was initially affected (during the first three to six months) at six locations but after 18 months, effects were apparent at only three. Loss of canopy caused increases in cover of non-canopy algae in the three locations in southern Europe and decreases in some northern locations. Measures of ecosystem functioning (community respiration, gross primary productivity, net primary productivity) were affected by loss of canopy at five of the six locations for which data were available. Short-term effects on community respiration were widespread, but effects were rare after 18 months. Functional changes corresponded with changes in community structure and/or species richness at most locations and times sampled, but no single aspect of biodiversity was an effective predictor of longer-term functional changes. Most ecosystems studied were able to compensate in functional terms for impacts caused by indiscriminate physical disturbance. The only consistent effect of disturbance was to increase cover of non-canopy species. Loss of canopy algae temporarily reduced community resistance to disturbance at only two locations and at two locations actually increased resistance. Resistance to disturbance-induced changes in gross primary productivity was reduced by loss of canopy algae at four locations. Location-specific variation in the effects of the same stressors argues for flexible frameworks for the management of marine environments. These results also highlight the need to analyse how species loss and other stressors combine and interact in different environmental contexts.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".