A Functional Approach Reveals Zooplankton Responses to Environmental Change in Mountain Lakes
Bibliographic record
Abstract
Concern is increasing over the future cumulative impacts of multiple stressors on freshwater biodiversity and ecosystem function, especially in alpine environments where climatic warming increases with elevation. Here, consideration of individual species traits enables translation of changes in biodiversity into functional responses by communities to environmental change. I integrated data for 170 mountain lakes and ponds spanning large latitudinal (2276 km) and elevational (1959 m) gradients across the mountains of Western Canada to assess how climatic and other environmental factors affect the taxonomic composition and functional structure of zooplankton communities. Unconstrained ordination and RLQ analyses revealed that certain functional groups consisting of relatively small-bodied, shoreline-associated (littoral) species were significantly associated with several climatically dependent environmental changes, namely higher water temperatures, shallower water depths, and lower ionic concentrations. My findings highlight how species turnover (beta-diversity) in shrinking alpine lakes will depend on limited dispersal from nearby ponds or lower montane elevations as environmental conditions become more variable in a warmer and drier climate.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".