Individual‐based simulations suggest mixed impacts of warmer temperatures and a nonnative predator on Chinook salmon
Bibliographic record
Abstract
Abstract As the climate changes, warmer water temperatures may stress populations of native coldwater fishes. Simultaneously, nonnative warmwater predators may expand their ranges and interact with already at‐risk native fish populations. To explore the independent and combined effects of these two stressors on threatened salmon, we present a case study of simulated Chinook salmon Oncorhynchus tshawytscha and largemouth bass Micropterus salmoides interacting under two thermal regimes in the Snoqualmie River, Washington, USA. We applied an individual‐based and spatially explicit model that tracks fish movement and growth. We evaluated changes in Chinook salmon emergence date, outmigration date, mass, and survival. We ran simulations for four scenarios: (1) Baseline, run without either stressor, (2) Warm, run with warmer temperatures, (3) Predator, run with largemouth bass, and (4) Warm‐Predator, run with both stressors. We assessed outcome metrics relative to the Baseline scenario. In the Warm scenario, salmon emerged 37 d and outmigrated 55 d earlier. There were 61% more subyearling migrants that were 31% smaller, and 72% fewer yearlings. In the Predator scenario, salmon survival decreased 64% for subyearlings and 69% for yearlings, and subyearlings were 7% smaller. In the Warm‐Predator scenario, salmon emerged 39 d and outmigrated 59 d earlier, subyearling survival increased 22%, subyearling mass decreased 37%, and 93% fewer yearlings survived. Our results suggest that warmer temperatures shift emergence and outmigration; predation by nonnative species is a threat to salmon survival; and life history strategies experience these stressors in different ways. Whereas subyearling production benefited from warmer temperatures more than it was hurt by predation, yearling production was depressed by both stressors independently and combined. Managers can use our individual‐based and spatially explicit approach to identify key times and areas to address exposure to extreme temperatures, overlap with nonnative species, and their interactive effects on threatened salmon. Our case study addressed three pressing needs identified in the literature: investigate impacts of nonnative species on threatened native salmon, build tools to evaluate management options where bass and salmon overlap, and explore how freshwater fishes will contend with multiple interactive stressors.
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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) | 0.003 | 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".