Projected impacts of climate change on three freshwater fishes and potential novel competitive interactions
Bibliographic record
Abstract
Abstract Aim As global air temperatures continue to rise in response to climate change, environmental conditions for many freshwater fish species will change. Warming air temperatures may lead to warming lake temperatures, and subsequently, the availability of suitable thermal habitat space. Our objectives are to identify the responses of three fish species from three thermal guilds to climate change in Ontario and consequently, the potential for novel competitive interactions between two top predators. We focus on lakes in Ontario because it is a dynamic region that encapsulates the northern and southern range extents of warm and cold‐water fish species. Location Ontario, Canada. Methods Using lake morphology, water chemistry, climate and fish occurrence data for smallmouth bass (warmwater predator), walleye (coolwater predator) and cisco (cold‐water forage fish), we modelled the occurrence rates of three fish in 2050 and 2070 under 126 scenarios of climate change. We also calculated the percentage change in co‐occurrence of walleye and smallmouth bass in 2050 and 2070. Results Smallmouth bass occurrence rates were predicted to increase by ~306% (ranging between 55 and 422%) by 2070 relative to their current distributions. Walleye were projected to decline by 22% (−42 to a +6% change) and cisco by 26% (−7 to −47%) by 2070. By 2070, walleye–smallmouth bass co‐occurrence was predicted to increase by 11%, with walleye in central and northern Ontario at greatest vulnerability due to increased competition with smallmouth bass. Main conclusions These results highlight three unique responses to climate change: range expansion, northward range shift, and range contraction for warmwater, coolwater and cold‐water fish species, respectively. Alterations in distributions of these three ecologically important fish species may lead to shifts in fish community structure and novel species interactions in Ontario lakes, exacerbating the vulnerability of native coolwater predators to climate change.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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 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".