Higher temperatures enhance the effects of invasive sportfish on mountain zooplankton communities
Bibliographic record
Abstract
Summary 1. Decades of introductions of exotic sportfish to mountain lakes around the world have impoverished them biologically, and this may be exacerbated by global warming. We assessed the current status of invasive salmonids and native zooplankton communities in 34 naturally fishless lakes along an elevational gradient, which served as an environmental proxy for the expected effects of climate change. 2. Our main goal was to explore how climate‐related variables influence the effects of stocked salmonids on the total biomass, species richness and taxonomic composition of zooplankton. We predicted that warmer conditions would dampen the negative predatory effects of exotic brook trout (Salvelinus fontinalis) on zooplankton communities because more temperate lakes contain a greater diversity of potentially tolerant species. 3. Instead, we discovered that the persistence of stocked brook trout in the warmer lakes significantly amplified total zooplankton biomass and species richness. In colder and deeper lakes, zooplankton were relatively unaffected by S. fontinalis, which however persisted better in alpine lakes than at lower elevations after stocking practices were halted over two decades ago. Warmer lake conditions and higher concentrations of dissolved organic carbon (DOC) were significant primary drivers of zooplankton species turnover, both favouring greater species diversity. 4. Our findings of an ecological surprise involving potential synergistic positive effects of climate warming and exotic trout on native zooplankton communities presents a conundrum for managers of certain national mountain parks. Present mandates to eradicate non‐native trout and return the mountain lakes to their naturally fishless state may conflict with efforts to conserve biodiversity under a rapidly changing 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 | 0.000 | 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) | 0.002 | 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".