Ontario freshwater fishes demonstrate differing range‐boundary shifts in a warming climate
Bibliographic record
Abstract
Abstract Aim Northerly shifts, related to recent climate warming, have been observed in the distributions of taxa in many ecosystems and ecological roles. However, significant variation occurs among species in the magnitude of these shifts. Few studies have investigated the effects of climate warming on the distributions of freshwater species. Location A total of 1527 lakes across O ntario, C anada. Methods We used contemporary and historical survey data to examine the relationships between species occurrences and climate and to measure the magnitude and direction of northern range‐boundary shifts in 13 warm and coolwater freshwater fishes. We also tested whether range‐boundary shifts differed between baitfishes and sportfishes. We then related differences in species range‐boundary shifts to species traits including those related to dispersal, reproduction and ecological niche breadth. Results Many fishes are now more likely to occur in lakes where climate was historically limiting. Sportfish northern range boundaries shifted northward significantly over nearly 30 years at a rate of approximately 12.9–17.5 km per decade depending on the measure used; in contrast, baitfish northern range boundaries often shifted southward. Also, species traits explained much of the variation in species range boundaries. Main conclusions The northern range boundaries of warm and coolwater sportfishes in Ontario lakes appear to be shifting northward as expected based on observed climate warming. These species are shifting at rates comparable with taxa in marine and terrestrial ecosystems around the globe. In contrast to expectations, the northern range boundaries of small‐bodied baitfishes appear to often contract southward. Differences in range shifts by sportfishes and baitfishes may be related to dispersal, particularly by anglers and/or their ecological roles. Understanding the range‐boundary shifts underway in Ontario lake communities will help predict future shifts by freshwater fishes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 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".