Lipid‐rich zooplankton subsidise the winter diet of benthivorous Arctic charr (<i>Salvelinus alpinus</i>) in a subarctic lake
Bibliographic record
Abstract
Summary Generalist fish species commonly act as important links between littoral and pelagic habitats and food‐web compartments in lakes. However, diet and habitat links may depend significantly on seasonal availability of, and qualitative differences between, littoral and pelagic prey and on fish size. Despite increasing interest in food‐web dynamics, little is known about the seasonal changes in, or qualitative differences between, littoral and pelagic trophic pathways supporting generalist fish species in high‐latitude lakes. We used stomach contents together with analyses of stable carbon and nitrogen isotopes and fatty acids to study the winter and summer diet of generalistArctic charr and determine the qualitative differences between littoral and pelagic prey items. We were particularly interested to determine whetherArctic charr are able to utilise abundant and lipid‐rich winter zooplankton resources in subarcticLakeSaanajärvi, northernFinland. Arctic charr fed actively on cladoceran zooplankton in both seasons, despite the higher abundance and higher lipid content of calanoid copepods. Although the stomach contents consisted mainly of zooplankton in summer, the isotopic compositions of muscle and liver suggestArctic charr relied more on littoral carbon sources throughout the year. Fatty acid analysis indicated thatArctic charr had lower amounts of body fat and total and essential fatty acids in winter compared with summer. Observed seasonal feeding activity and dietary shifts were partly related toArctic charr size. Small (<200 mm)Arctic charr had more empty stomachs in winter, but higher amounts of zooplankton in stomachs and of essential fatty acids in muscle tissue in summer compared with larger (>200 mm) conspecifics that had more seasonally stable feeding activity and diet. Fatty acid analysis indicated that both littoral and pelagic food sources provided similar fatty acids toArctic charr, but in general, zooplankton had higher percentages of essential fatty acids compared with zoobenthos. PelagicEudiaptomus graciloidescalanoids and littoralGammarus lacustrisamphipods had the highest concentrations of total and essential fatty acids, but only the latter prey item was found in Arctic charr stomach contents. Our study demonstrates that lipid‐rich zooplankton can subsidise the predominantly benthivorous diet of top consumers (hereArctic charr) in subarctic lakes. The results also demonstrate that littoral and pelagic trophic pathways can be highly integrated in high‐latitude lakes, as a result of the flexible foraging behaviour of top consumers such as Arctic charr.
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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".