Impacts of reduced Lepidurus arcticus availability on brown trout life history traits in a mountain reservoir
Bibliographic record
Abstract
Abstract Lepidurus arcticus(the Arctic tadpole shrimp) is a vulnerable keystone species in Arctic and alpine water bodies where its occurrence and population size may influence the viability and life history traits of resident salmonids. Using data from a Norwegian mountain hydropower reservoir, Aursjoen, we illustrate how reduced availability ofL. arcticusas prey resulted in the reduced condition, growth and delayed maturation of resident brown trout (Salmo trutta). We further link changes in the relative abundance ofL. arcticusas prey to changing reservoir conditions, e.g. water level changes in the spring period, thereby establishing an indirect link between reservoir operation regimes and brown trout population traits. While no evidence for decreased brown trout survival was found, the results indicate that alternative brown trout prey resources, i.e. the small chydorid cladoceranEurycercus lamellatus, do not appear to have successfully offset the caloric loss from reduced consumption of large-sizedL. arcticus. Although the fundamental explanation for the observedL. arcticuscollapse remains largely unknown, the present findings provide strong evidence that this vulnerable crustacean species can affect the abundance, viability and life history traits of valued resident salmonid populations in oligotrophic alpine lakes and reservoirs exposed to climate- and hydropower-driven changes in water levels and temperature.
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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 | 0.001 |
| 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".