A review and meta-analysis of the environmental biology of bleak Alburnus alburnus in its native and introduced ranges, with reflections on its invasiveness
Bibliographic record
Abstract
Abstract The bleak Alburnus alburnus is a medium body-size leuciscid fish that is naturally distributed across central European and western Asian fresh waters. However, during the last two decades A. alburnus has been widely introduced elsewhere in Europe and in northern Africa, mostly as a forage species for game fishes. Given its relatively recent history of invasion in non-native Eurasian waters, where it can become highly abundant, A. alburnus poses a serious risk to native communities where introduced. This study provides a review and meta-analysis of the biological traits of A. alburnus coupled with insights into its invasiveness. In its native range, A. alburnus has a moderate lifespan, inhabiting lakes or still waters in medium-to-large rivers, where it feeds mainly on zooplankton. However, non-native A. alburnus populations display high phenotypic plasticity in their biological attributes. Thus, growth, reproductive and/or dietary traits have adapted to local environmental conditions, with the species also invading lotic (stream) ecosystems. Feeding changes to benthic invertebrates, plant material and detritus when zooplankton is scarce. Such plasticity, including broad physiological tolerance, is likely to facilitate the species' adaptation and invasion of new habitats in the near future.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".