An invader in salmonid rearing habitat: current and future distributions of smallmouth bass (<i>Micropterus dolomieu</i>) in the Columbia River Basin
Bibliographic record
Abstract
Invasive species and climate change are leading threats to freshwater ecosystems. In the Columbia River Basin (CRB), nonnative fishes are a critical consideration in salmon recovery, yet managers lament a lack of distribution information. Combining a species distribution model (SDM) with environmental DNA (eDNA), we locate range boundary regions of nonnative smallmouth bass (Micropterus dolomieu) and evaluate its overlap with native salmonids. A combination of thermal, hydrological, and geomorphic variables predict that smallmouth bass is distributed across ∼18 000 river kilometres and overlaps with 3%–62% of rearing habitat of salmonids (species-dependent) in the CRB. Under a moderate climate change scenario, smallmouth bass is predicted to expand its range by two-thirds (totaling ∼30 000 river kilometres) by 2080. Basin-wide models were sufficiently accurate to identify upstream invasion extents to within 15 km of the eDNA-based boundary, and including eDNA data improved model performance at critical range boundary regions without sacrificing broadscale model performance. Our study highlights how eDNA approaches can supplement large geospatial data sets to result in more accurate SDM predictions, guiding nonnative species management.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".