Climate change alters global invasion vulnerability among ecoregions
Bibliographic record
Abstract
Abstract Aim We assess climate similarity among global freshwater and terrestrial ecoregions under historical and future climate scenarios to determine where climate change will impact the climate filter of invasion process. Location Global. Methods We used the Climatch algorithm to conduct a climate‐match analysis to quantify the climate similarity between freshwater and terrestrial ecoregions of the world. Climate match was modelled between all freshwater and terrestrial ecoregions. The analysis was conducted under historical climates and projected climates of 2081–2100 (2090) under three shared socioeconomic pathways SSP2‐4.5, SSP3‐7.0, SSP5‐8.5. Climate matches of each ecoregion were presented as mean climate match to all other ecoregions of the same set. Friedman's non‐parametric rank sum two‐way analysis of variance with repeated measures was used to examine differences in mean climate match between climate scenarios. Results Mean climate match of ecoregions was projected to increase significantly with small effect sizes for freshwater ecoregions (recipients: 0.132; sources: 0.105), and moderate and small effect sizes for terrestrial ecoregions (recipients: 0.330; sources: 0.259). Climate change was predicted to increase mean climate match in North America and Eurasia, particularly in the Arctic by 2090 under each SSP. Ecoregions in central Africa and South America were predicted to have reduced mean climate match. Ecoregions within larger countries (e.g. Australia, Canada, USA) showed variation in mean climate match. Main Conclusion Climate change projections of bioclimatic predictors of species invasions were shown to increase in homogeneity under higher emissions scenarios. Furthermore, we demonstrate how climate change will provide opportunities for invasive species transported among ecoregions to survive under new conditions and identify where the climate filter of the invasion process will be most affected. Findings can be used to inform conservation actions for mitigating the impacts of introduced species by identifying potential risky source regions of future freshwater and terrestrial invasions under climate change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".