Climate and productivity shape fish and invertebrate community structure in subarctic lakes
Bibliographic record
Abstract
Summary Climate change and land‐use intensification are increasing productivity in subarctic lakes. Simultaneously, fish and invertebrate species adapted to temperate conditions are expanding their range northwards into subarctic habitats. Community level studies are required to predict long‐term effects of these dual stressors on subarctic freshwater ecosystems. We conducted a space‐for‐time study examining the fish, benthic invertebrate and pelagic zooplankton communities in littoral, profundal and pelagic habitats in 19 subarctic lakes situated on a temperature, land‐use and productivity gradient in northern Europe. Fish density (ranging between 0.5 and 150.5 fish per net series h −1 ) and biomass (range between 92 and 5,147 g per net series h −1 ) increased significantly with increasing lake temperature and productivity. This was associated with significantly decreasing body size (26 to 12 cm total length; 174 to 19 g body mass) and a shift in fish community structure from salmonid (Arctic charr Salvelinus alpinus , whitefish Coregonus lavaretus ), to percid (ruffe Gymnocephalus cernua , perch Perca fluviatilis) and ultimately cyprinid (roach Rutilus rutilus , bleak Alburnus alburnus ) dominance. Changes in fish community composition were most apparent in littoral and pelagic zones. Benthic macroinvertebrate density peaked in mesotrophic lakes, zooplankton density was highest at either end of the gradient, indicating habitat specific differences in predation pressure and top‐down control. Body size of zooplankton and benthic macroinvertebrates was negatively related to temperature and productivity. These results suggest that climate change and intensification of land‐use practices are gradually turning subarctic lakes into warmer, less transparent and more productive systems harbouring abundant, small‐sized and warmer adapted communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".