Effect of a change in physical structure and cover on fish and fish habitat in freshwater ecosystems – a review and meta-analysis
Bibliographic record
Abstract
Aquatic resource managers are continually faced with construction or site development proposals which, if allowed to proceed, would ultimately alter the physical structure and cover of fish habitat. In the absence of clear quantitative guidelines linking the change in habitat to fish, resource managers often use the change in habitat area as a basis for decisions. To assess the weight of scientific evidence in support of management decisions, we summarized both the observational and experimental freshwater fish-habitat literature. We then extracted data from experimental studies (where possible) for inclusion in a meta-analysis, to provide a more rigorous assessment of the published results of experimental habitat manipulations. We found relatively strong and consistent correlational evidence linking fish and physical habitat features, yet inconsistent evidence when narratively reviewing the experimental literature. On the whole, decreases in structural habitat complexity are detrimental to fish diversity and can change species composition. Increases in structural complexity showed increases, decreases, or no measurable changes in species and (or) communities. The majority of our meta-analyses resulted in supporting a direct link between habitat and fish abundance or biomass, with fish biomass responding most strongly to habitat change. Habitat alterations are most likely to affect individual species or community structure, and thus evaluating the extent of the effect on a biological basis depends on management objectives.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".