Testing for broad-scale relationships between freshwater habitat pressure indicators and Pacific salmon population trends
Bibliographic record
Abstract
Global freshwater biodiversity is declining at rates greater than in terrestrial or marine environments, largely due to habitat alteration and loss. Pacific salmon are declining throughout much of their southern range due to a combination of pressures in their marine and freshwater habitats. There is, therefore, an urgent need to understand the main drivers of decline to inform both fisheries and land-use management. Here, we draw on a suite of freshwater habitat pressure indicators to test whether we can detect relationships between them and trends in Pacific salmon spawner abundance throughout British Columbia. We related trends in spawner abundance (n = 3691 populations) to ten habitat pressure indicators that represent a snapshot in time of the level of degradation in salmon freshwater spawning habitats (e.g., Equivalent Clearcut Area, percent watershed area impacted by urban development or agriculture). Evidence of relationships between freshwater habitat pressure indicators and trends in spawner abundance was weak at the province-wide scale, while variable in both direction and magnitude at the watershed scale likely due to the mediating effects of regional biological and physical factors. We used these empirical relationships to assess the vulnerability of individual species and regions to increasing habitat pressures. Vulnerability was highest when multiple conditions coincided: when salmon were sensitive to the habitat pressure indicator, the current level of disturbance under that indicator was moderate or low, and populations were declining but not yet at rates high enough to be deemed “threatened”. These findings highlight the need to consider the current state of the landscape and of populations when assessing where habitat protection might have the greatest benefit for biodiversity conservation. Strategic recovery planning for Pacific salmon requires multi-scale approaches that account for the diversity and complexity of relationships between habitat disturbance and population dynamics.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".