Ecological impacts of invasive alien species along temperature gradients: testing the role of environmental matching
Bibliographic record
Abstract
Invasive alien species (IAS) can cause substantive ecological impacts, and the role of temperature in mediating these impacts may become increasingly significant in a changing climate. Habitat conditions and physiological optima offer predictive information for IAS impacts in novel environments. Here, using meta-analysis and laboratory experiments, we tested the hypothesis that the impacts of IAS in the field are inversely correlated with the difference in their ambient and optimal temperatures. A meta-analysis of 29 studies of consumptive impacts of IAS in inland waters revealed that the impacts of fishes and crustaceans are higher at temperatures that more closely match their thermal growth optima. In particular, the maximum impact potential was constrained by increased differences between ambient and optimal temperatures, as indicated by the steeper slope of a quantile regression on the upper 25th percentile of impact data compared to that of a weighted linear regression on all data with measured variances. We complemented this study with an experimental analysis of the functional response (the relationship between predation rate and prey supply) of two invasive predators (freshwater mysid shrimp, Hemimysis anomala and Mysis diluviana) across. relevant temperature gradients; both of these species have previously been found to exert strong community-level impacts that are corroborated by their functional responses to different prey items. The functional response experiments showed that maximum feeding rates of H. anomala and M. diluviana have distinct peaks near their respective thermal optima. Although variation in impacts may be caused by numerous abiotic or biotic habitat characteristics, both our analyses point to temperature as a key mediator of IAS impact levels in inland waters and suggest that IAS management should prioritize habitats in the invaded range that more closely match the thermal optima of targeted invaders.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".