Osmoregulatory Capacity and Non-Specific Food Preferences as Strengths Contributing to the Invasive Success of the Signal Crayfish Pacifastacus leniusculus: Management Implications
Bibliographic record
Abstract
Various biological traits support the invasive success of different organisms. The osmoregulatory capacity and food preferences of the signal crayfish Pacifastacus leniusculus were experimentally tested to determine if they contribute to its invasive success. The osmotic concentrations of haemolymph were determined after acclimation of the crustaceans to seven salinities from 0 to 20 PSU. Food preferences were tested using Canadian pondweed Elodea canadensis, and rainbow trout Oncorhynchus mykiss. The results showed that the signal crayfish exhibits a hyper-hypoosmotic regulation pattern in the salinity range from 0 to 20 PSU, enabling them to inhabit both freshwater and brackish environments. Furthermore, the study found signal crayfish to have non-specific food preferences, although fish muscle tissue is more beneficial as a source of energy. Both features, osmoregulatory ability and food preferences, can increase the invasive success of this species as it expands into new areas. The ability to survive in higher salinities compared to the coastal waters of the Baltic Sea along the Polish coastline should be considered in targeted management strategies to control the spread of this invasive species.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".