The abiotic and biotic factors limiting establishment of predatory fishes at their expanding northern range boundaries in Ontario, Canada
Bibliographic record
Abstract
There is a poor understanding of the importance of biotic interactions in determining species distributions with climate change. Theory from invasion biology suggests that the success of species introductions outside of their historical ranges may be either positively (biotic acceptance) or negatively (biotic resistance) related to native biodiversity. Using data on fish community composition from two survey periods separated by approximately 28 years during which climate was warming, we examined the factors influencing the establishment of three predatory centrarchids: Smallmouth Bass (Micropterus dolomieu), Largemouth Bass (M. salmoides), and Rock Bass (Ambloplites rupestris) in lakes at their expanding northern range boundaries in Ontario. Variance partitioning demonstrated that, at a regional scale, abiotic factors play a stronger role in determining the establishment of these species than biotic factors. Pairing lakes within watersheds where each species had established with lakes sharing similar abiotic conditions where the species had not established revealed both positive and negative relationships between the establishment of centrarchids and the historical presence of other predatory species. The establishment of these species near their northern range boundaries is primarily determined by abiotic factors at a regional scale; however, biotic factors become important at the lake-to-lake scale. Studies of exotic species invasions have previously highlighted how spatial scale mediates the importance of abiotic vs. biotic factors on species establishment. Our study demonstrates how concepts from invasion biology can inform our understanding of the factors controlling species distributions with changing climate.
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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 | 0.002 | 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".