Susceptibility of European freshwater fish to climate change: Species profiling based on life‐history and environmental characteristics
Bibliographic record
Abstract
Climate change is expected to strongly affect freshwater fish communities. Combined with other anthropogenic drivers, the impacts may alter species spatio-temporal distributions and contribute to population declines and local extinctions. To provide timely management and conservation of fishes, it is relevant to identify species that will be most impacted by climate change and those that will be resilient. Species traits are considered a promising source of information on characteristics that influence resilience to various environmental conditions and impacts. To this end, we collated life-history traits and climatic niches of 443 European freshwater fish species and compared those identified as susceptible to climate change to those that are considered to be resilient. Significant differences were observed between the two groups in their distribution, life history, and climatic niche, with climate-change-susceptible species being distributed within the Mediterranean region, and being characterized by greater threat levels, lesser commercial relevance, lower vulnerability to fishing, smaller body and range size, and warmer thermal envelopes. Based on our results, we establish a list of species of highest priority for further research and monitoring regarding climate-change susceptibility within Europe. The presented approach represents a promising tool to efficiently assess large groups of species regarding their susceptibility to climate change and other threats, and to identify research and management priorities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".