Recent trends in mountain lake primary production: evaluating the response to fish stocking relative to regional environmental stressors
Bibliographic record
Abstract
Sia ME, Doyle RM, Moser KA. 2020. Recent trends in mountain lake primary production: evaluating the response to fish stocking relative to regional environmental stressors. Lake Reserv Manage. XX:XXX–XXX.Although mountain lakes are often remote, they are impacted by a myriad of stressors, including species introductions, atmospheric fertilization, and climate change. These stressors have the potential to increase primary production, which can threaten mountain lakes by decreasing water quality, reducing species richness, and lowering dissolved oxygen concentrations. The relative importance of these stressors as drivers of production is not well understood. We therefore investigated the importance of fish stocking, relative to other stressors, as a driver of primary production in mountain lakes. Our research focused on Uinta Mountain lakes, which, like many lakes in the western United States, were stocked with salmonid fish in the 1950s. In 2 stocked lakes and one unstocked lake, we reconstructed a record of ∼300 yr of primary production from lake sediments using changes in percentage of organic matter and spectrally inferred concentrations of chlorophyll a and its derivatives. With long-term trends in primary production, we determined that all 3 study lakes, including the unstocked lake, show unprecedented increases in primary production beginning in the 1950s. We attribute recent increases in primary production mainly to atmospheric deposition of nitrogen and climate warming, but do not rule out future impacts of fish stocking. Our article demonstrates how breakpoint analysis can be used to identify the most serious threats to mountain lakes, even if those lakes are impacted by multiple stressors or stressors originating from distant places.
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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 | 0.001 | 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 | 0.001 |
| 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 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".