Elucidating the Interactive Effects of Climate Change and Invasive Species Using a Lotic Fish Species Pair
Bibliographic record
Abstract
Climate change is a primary threat to freshwater biodiversity, negatively affecting the structure and functioning of ecosystems. Freshwater fishes are particularly vulnerable to climate change due to their ectothermy and constrained dispersal ability within dendritic networks. Through shifting environmental conditions, the frequency of species invasions increases, as increased levels of disturbance are known to destabilize ecosystems and create niche space filled by generally adaptable invasive competitors. Although the impacts of invaders through predation and competition with native species are well documented, these processes are largely context- dependent, and shifting thermal and hydrological regimes caused by climate change may limit our ability to make generalized predictions of invasive species impacts to native competitors. Therefore, this thesis examines the context-dependencies of interactions between invasive Round Goby and native White Sucker under shifting environmental conditions. These species were chosen because of the ecological importance of White Sucker to lotic environments and its recent decline, hypothesized to be the result of benthic niche overlap with Round Goby, which may be exacerbated by changing climatic conditions. I tested the prediction that per capita effects of invading species are higher at temperatures that approach a species’ thermal optima, which reflect projected water temperatures and flows in the Great Lakes under climate change. I demonstrate that there is a competitive interaction between these species - the trophic niche of Round Goby significantly overlaps with White Sucker, which expands its prey selectivity to compensate for increased competition. Utilizing field thermal maximum and laboratory feeding experiments, I demonstrate that competition between these species is expected to increase under climate change. As the Round Goby continues to invade Lake Ontario tributaries under climate change, there will be increasing competition with White Sucker for prey items and thermally suitable habitat.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".