Impacts of highway crossings on density of brook charr in streams
Bibliographic record
Abstract
Summary 1. Habitat degradation and fragmentation are growing concerns in ecology, yet distinguishing between the effects of these processes can be a challenging task. In riverine landscapes, roads impact fish populations mainly through: (i) restriction of passage of individuals (fragmentation) and (ii) reduction in habitat quality downstream by increases in sediment load (habitat degradation). These two processes can be differentiated during road construction projects. 2. This study examines the impacts of a highway expansion and the presence of existing highway crossings on local population density of brook charr Salvelinus fontinalis in stream reaches traversed by the highway. Density was estimated on three consecutive summers in 212 sections distributed among 36 streams. This extensive sampling design focused on replicated comparison of sites upstream and downstream of highway crossings and included different stages of highway construction (before, during and after) and types of highway crossing (low, intermediate and high passability). Mixed models were used to examine the impacts of the highway on population density. 3. Highway construction activities had no detectable effect on density. However, existing highway crossings appeared to have a strong effect on density, which differed markedly between upstream and downstream sites near highway crossings of intermediate and low passabilities. 4. A Markovian movement model yielded estimates of passability that were consistent with the classification of crossing types and provided evidence for the restriction of upstream movement at crossings as a plausible explanation for observed differences in local population density. 5. Synthesis and applications. Habitat fragmentation resulting from restriction of passage at highway crossings had markedly greater effects on local population density than short‐term impacts arising from construction activities. The modelling approaches used in this study can be useful management tools for the conservation of mobile fish species in fragmented riverine landscapes.
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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 | 0.001 | 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 | 0.000 |
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".