Climate Effects on High Latitude Daphnia via Food Quality and Thresholds
Bibliographic record
Abstract
Climate change is proceeding rapidly at high northern latitudes and may have a variety of direct and indirect effects on aquatic food webs. One predicted effect is the potential shift in phytoplankton community structure towards increased cyanobacterial abundance. Given that cyanobacteria are known to be a nutritionally poor food source, we hypothesized that such a shift would reduce the efficiency of feeding and growth of northern zooplankton. To test this hypothesis, we first isolated a clone of Daphnia pulex from a permafrost thaw pond in subarctic Québec, and confirmed that it was triploid but otherwise genetically similar to a diploid, reference clone of the same species isolated from a freshwater pond in southern Québec. We used a controlled flow-through system to investigate the direct effect of temperature and indirect effect of subarctic picocyanobacteria (Synechococcus) on threshold food concentrations and growth rate of the high latitude clone. We also compared the direct effect of temperature on both Daphnia clones feeding on eukaryotic picoplankton (Nannochloropsis). The high latitude clone had a significantly lower food threshold for growth than the temperate clone at both 18 and 26°C, implying adaptation to lower food availability even under warmer conditions. Polyunsaturated fatty acids were present in the picoeukaryote but not the cyanobacterium, confirming the large difference in food quality. The food threshold for growth of the high latitude Daphnia was 3.7 (18°C) to 4.2 (26°C) times higher when fed Synechococcus versus Nannochloropsis, and there was also a significant negative effect of increased temperature and cyanobacterial food on zooplankton fatty acid content and composition. The combined effect of temperature and food quality on the performance of the high latitude Daphnia was greater than their effects added separately, further indicating the potentially strong indirect effects of climate warming on aquatic food web processes.
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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".