Climate Change Vulnerability Assessments Based on Korean Freshwater Fish and Comparative Evaluations with three International Models
Bibliographic record
Abstract
Potential candidate fish species vulnerable to climate change were identified by the pre-screening process in streams and rivers of 4 major watersheds in Korea. Total 51 candidates from 252 fish species were selected by eliminating the species such as estuary-dwelling species, tolerant species to water pollution, omnivorous species (generalist), and widely distributed species. And then we preliminarily considered the restricted headwater species, cold-water affinity species, limited dispersal ability, and sensitive species to thermal and hydrological variations. The selected species were evaluated using three internationally recognized climate change vulnerability assessment tools (US Midwestern, US Environmental Protection Agency, and Canada models) to compare species-level vulnerability patterns. Spearman rank correlation analysis was used to quantitatively compare the consistency of assessment results across models. While three models identified species as relatively consistently vulnerable to climate change, differences in metric composition and weighting methods resulted in variations in relative vulnerability rankings for some species, highlighting the limitations of a single assessment model. A total of 92 metrics reported in global literature were reviewed, from which 20 metrics were selected by considering domestic data availability, ecological relevance, and sensitivity to climate drivers. The selected metrics were organized into three categories: temperature exposure, sensitivity, and adaptability. A standardized three-level scoring system (1, 3, and 5) was applied to assess the climate change vulnerability on the selected 51 species. Considering that freshwater fish were ectothermic organisms and exhibited high physiological sensitivity to water temperature changes, weighting of each metric was applied to metrics directly related to water temperature, thereby more clearly distinguishing the vulnerabilities of cold-water species. Overall, assessment and prioritization of climate change vulnerability are fundamental to identifying at-risk freshwater fish species and guiding effective conservation and management strategies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".