Zooplankton in northern lakes show taxon‐specific responses in fatty acids across climate‐productivity and ecosystem size gradients
Bibliographic record
Abstract
Abstract Northern lakes are facing rapid environmental alterations—including warming, browning, and/or changes in nutrient concentrations—driven by climate change. These environmental changes can have profound impacts on the synthesis and trophic transfer of polyunsaturated fatty acids (PUFA), which are important biochemical molecules for consumer growth and reproduction. Zooplankton are a key trophic link between phytoplankton and fish, but their biochemical responses to environmental change are not well understood. In this study, we assess the trends in fatty acid (FA) composition of zooplankton taxa among 32 subarctic and temperate lakes across broad climate‐productivity and ecosystem size gradients. We found that genus‐level taxonomy explained most FA variability in zooplankton (54%), suggesting that environmental changes that alter the taxonomic composition also affect the FA composition of zooplankton communities. Furthermore, the FA responses and their underlying environmental drivers differed between cladocerans and copepods. Cladocerans, including widespread Bosmina spp. and Daphnia spp., showed pronounced responses across the climate‐productivity gradient, with abrupt declines in PUFA, particularly eicosapentaenoic acid and arachidonic acid in warmer, browner, and more eutrophic lakes. Conversely, calanoid copepods had high and relatively stable PUFA levels across the gradient. In addition, all zooplankton taxa increased in stearidonic acid levels in larger lakes where PUFA‐rich cryptophytes were more abundant. Overall, our results suggest that climate‐driven environmental alterations pose heterogeneous impacts on PUFA levels among zooplankton taxa, and that the negative impacts of climate warming are stronger for cladocerans, especially so in small lakes.
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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 | 0.001 | 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".