The influence of air temperature, groundwater discharge, and climate change on the thermal diversity of stream fishes in southern Ontario watersheds
Bibliographic record
Abstract
The availability of suitable thermal habitat for fishes in streams is influenced by several factors, including flow, channel morphology, riparian vegetation, and land use. This study examined the influence of air temperature and groundwater discharge, predictors of stream temperature, on the thermal diversity (cold-, cool-, and warm-water preferences) of stream fish communities in southern Ontario watersheds. Site-level fish sampling data were used to assess the thermal diversity of 43 quaternary watersheds using three metrics, the proportion of sites within a watershed having (i) cold-, (ii) cool-, and (iii) warm-water fishes. Our results indicated that 53.9% of the variances in cold-water and 54.1% of the variances in warm-water fish distributions within the watersheds could be attributed to groundwater discharge and air temperature variables. Climate change scenarios suggested that watersheds with high groundwater discharge and the associated thermal diversity of fishes within those watersheds are less sensitive to climate change than watersheds with low groundwater discharge. Conservation of groundwater resources will be required to lessen climate change impacts on the thermal habitat and thermal diversity of stream fishes in southern Ontario watersheds.
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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 | 0.001 |
| 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".