A Functional Approach to Zooplankton Communities in Mountain Lakes Stocked With Non‐Native Sportfish Under a Changing Climate
Bibliographic record
Abstract
Abstract Cumulative impacts of multiple stressors on freshwater biodiversity and ecosystem function likely increase with elevation, thereby possibly placing alpine communities at greatest risk. Here, consideration of species traits enables stressor effects on taxonomic composition to be translated into potential functional impacts. We analyzed data for 47 taxa across 137 mountain lakes and ponds spanning large latitudinal (491 km) and elevational (1,399 m) gradients in western Canada, to assess regional and local factors of the taxonomic composition and functional structure of zooplankton communities. Multivariate community analyses revealed that small body size, clonal reproduction via parthenogenesis, and lack of pigmentation were species traits associated with both introduced non‐native sportfish and also environmental conditions reflecting a warmer and drier climate—namely higher water temperatures, shallower water depths, and more chemically concentrated water. Thus, historical introductions of sportfish appear to have potentially induced greater tolerance in zooplankton communities of future climatic warming, especially in previously fishless alpine lakes. Although alpine lake communities occupied a relatively small functional space (i.e., low functional diversity), they were contained within the broader regional functional structure. Therefore, our findings point to the importance of dispersal by lower montane species to the future functional stability of alpine communities.
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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 | 0.001 | 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".