Idiosyncratic responses of Pacific salmon species to land cover, fragmentation, and scale
Bibliographic record
Abstract
Salmon are critical to the ecology and livelihood of the Pacific Northwest, and are declining throughout much of their range. While much of their life cycle occurs in open ocean, freshwater conditions also contribute to population trends. Because stream habitats are connected to uplands by water flow, salmon can be influenced by the characteristics of terrestrial systems. We analyzed the relationships between the population trends of Pacific salmon (1953–2006) and land cover, fragmentation, and forest age derived from remotely‐sensed, landscape level datasets. Analyses included 425 populations of all native salmon species in 156 watersheds on Vancouver Island, British Columbia, Canada. Vancouver Island salmon escapements exhibited general patterns of decline, which may be largely controlled by broad‐scale marine conditions. The spatial variation in these population trends was related to landscape variables at watershed and riparian scales with regression trees. Results were found to be species specific, but characteristics indicating a legacy of historic and current forest management (such as fragmented forests and non‐forested or early‐successional forest cover) generally had negative effects, driven by a small subset of highly fragmented watersheds. Chum and coho had strong negative relationships with fragmentation, pink had a strong positive relationship with wetland abundance, and Chinook and sockeye were most closely related to geomorphology. There was no ‘single best’ scale of analysis. Salmon trends were generally more closely related to variables estimated over the entire watershed, however, the relative importances of watershed and riparian level predictors varied by both variable and species. Efforts to restore salmon habitat will be complicated by marine and freshwater processes, terrestrial conditions throughout watersheds, and the idiosyncratic requirements of each species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".