Marine and freshwater regime changes impact a community of migratory Pacific salmonids in decline
Bibliographic record
Abstract
Marine and freshwater ecosystems are increasingly at risk of large and cascading changes from multiple human activities (termed "regime shifts"), which can impact population productivity, resilience, and ecosystem structure. Pacific salmon exhibit persistent and large fluctuations in their population dynamics driven by combinations of intrinsic (e.g., density dependence) and extrinsic factors (e.g., ecosystem changes, species interactions). In recent years, many Pacific salmon have declined due to regime shifts but clear understanding of the processes driving these changes remains elusive. Here, we unpacked the role of density dependence, ecosystem trends, and stochasticity on productivity regimes for a community of five anadromous Pacific salmonids (Steelhead, Coho Salmon, Pink Salmon, Dolly Varden, and Coastal Cutthroat Trout) across a rich 40-year time-series. We used a Bayesian multivariate state-space model to examine whether productivity shifts had similarly occurred across the community and explored marine or freshwater changes associated with those shifts. Overall, we identified three productivity regimes: an early regime (1976-1990), a compensatory regime (1991-2009), and a declining regime (since 2010) where large declines were observed for Steelhead, Dolly Varden, and Cutthroat Trout, intermediate declines in Coho and no change in Pink Salmon. These regime changes were associated with multiple cumulative effects across the salmon life cycle. For example, increased seal densities and ocean competition were associated with lower adult marine survival in Steelhead. Watershed logging also intensified over the past 40 years and was associated with (all else equal) ≥97% declines in freshwater productivity for Steelhead, Cutthroat, and Coho. For Steelhead, marine and freshwater dynamics played approximately equal roles in explaining trends in total productivity. Collectively, these changing environments limited juvenile production and lowered future adult returns. These results reveal how changes in freshwater and marine environments can jointly shape population dynamics among ecological communities, like Pacific salmon, with cascading consequences to their resilience.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".