An evidence base of ecosystems services provided by diadromous fish in the European Atlantic Area
Bibliographic record
Abstract
Historical and existing environmental and human induced pressures have negatively impacted diadromous species, as well as benefits to humans, derived from the ecosystem services these species contribute to. As species move across national boundaries, successful management is rendered a complex process. Future climate change scenarios are likely to change species distributions, further impacting management and the benefits available to people across each species range. To provide an evidence base on the contribution of eleven diadromous fish populations to ecosystem services, and so gains and losses of ecosystem service benefits in the European Atlantic Area, we completed an evidence review of available literature identified within the search strategy. We also gathered expert opinion of diadromous species contributions to ecosystem services for individual catchments across Europe, to gather the full extent of contributions. Evidence was arranged in a matrix, documenting each species ecosystem service contribution to aid communication of results and application to policy and decision makers. The evidence base provided by the literature review identified that each diadromous species contributed to provision of multiple ecosystem services. Volume of evidence available to compile the matrix was far greater for Atlantic salmon Salmo salar and brown trout Salmo trutta. All species had historically contributed to provisioning ecosystem services. However, in recent decades, declines in certain species populations has reduced opportunity for commercial fisheries, leading to contributions to cultural services such as recreational activities and cultural heritage becoming comparatively greater. Evidence of contribution to regulating ecosystem services is growing in recent years, especially transfer of nutrients from marine to freshwater environments. Inclusion of local expert knowledge enabled verification of evidence from literature, in addition to identification of important contributions of lesser studied species, to culturally important commercial fisheries and cultural heritage in European regions. Collecting expert knowledge also aided communication of ecosystem service approaches.
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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 | 0.012 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".