Covariation of stream community structure and biomass of algae, invertebrates and fish with forest cover at multiple spatial scales
Bibliographic record
Abstract
Summary 1. To evaluate the spatial extent of the effects of forest cover on stream ecosystems, we measured algae, invertebrate, and fish biomass and invertebrate and fish community structure in 38 small first‐ to third‐order streams in the National Capital Region of Canada along with forest cover at different spatial scales. 2. We considered 55 spatial scales of forest cover including several buffer widths (doubling 10–320 m) and lengths (doubling 10–1280 m, entire riparian distance upstream from sampling area) and entire catchments to determine which spatial scale maximized the correlation with biomass and metrics of community structure. 3. The proportion of variability in biomass and structural metrics explained by forest cover generally increased with increasing scale, suggesting that catchment‐wide disturbances are the most influential determinants of benthic and fish communities. 4. Catchment forest cover explained more variation in algal (adjusted r2 = 0.54), invertebrate (adjusted r2 = 0.51) and fish (adjusted r2 = 0.33) biomass than structural metrics of invertebrates and fish (adjusted r2 = 0.08–0.27). 5. Analyses of the partial effects of forest cover at three scales (reach, riparian and the entire catchment) on biomass and community structure metrics identified catchment and reach scales as being most influential and never detected a significant partial effect of forest cover at the riparian scale. 6. These results suggest that maintenance or protection of reach and riparian buffers alone will not sufficiently protect stream function and structure from catchment‐wide impacts.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".