The effects of climate change on the northward range expansion of the smallmouth bass (Micropterus dolomieu) and the consequential impacts on native fish populations
Bibliographic record
Abstract
Increases in temperature due to climate change will have large implications for aquatic ecosystems. Warmwater fish species, such as smailmouth bass, Micropterus dolomieu, may have access to additional favourable thermal habitat under increased surface-water temperatures, thereby shifting the northern limit of the distribution of the species further north in Canada and potentially negatively impacting native fish communities. A database comprised of over 50,000 lakes was assembled consisting of data on geography, lake morphology, water chemistry, climate, and fish community composition. Based on a comparison of several statistical approaches (multiple regression, regression tree, artificial neural networks, and Bayesian multiple regression) and several climate-change scenarios, water temperatures were predicted to increase by as much as 18°C by 2100, with the greatest increase in water temperature in northern Canada. By 2100, smallmouth bass thermal habitat is predicted to shift to the north with the majority of Canadian lakes expected to contain suitable thermal habitat. A comparison of logistic regression, classification tree, linear discriminant analysis, and artificial neural networks indicated that smallmouth bass distribution is predicted by winter and summer air temperatures. Climate-change modeling, in conjunction with artificial neural networks, predicted that smallmouth bass will have suitable thermal habitat throughout the majority of aquatic systems in the continental United States and Canada by 2100. The presence of smallmouth bass will negatively impact native fish communities, particularly native lake trout populations. Lake trout populations residing in smaller lakes are more vulnerable to the effects of smallmouth bass establishment due to the decreased presence of alternate prey resources. Examination of the pelagic and littoral forage fish communities identified nearly 9,700 lake trout populations threatened by 2100AD under climate-change scenarios, due to the potential invasion of smallmouth bass. The current range expansion of smallmouth bass has been facilitated by stocking by governmental agencies, unauthorized and accidental introduction by anglers, and dispersal through drainage networks. This stresses the importance of intensifying public education and regulation to limit the potential dispersal of invasive species, such as smallmouth bass.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".