A Paleolimnological Assessment of the Response of Trout-bearing Lakes to Climate and Watershed Disturbance in Semi-arid South-Central British Columbia, Canada
Bibliographic record
Abstract
Water quality and quantity in trout-bearing lakes in the southern Interior Plateau (SIP) of British Columbia is threatened by lake and watershed disturbances of anthropogenic origin, and regional factors including climate change. This was exemplified in Roche Lake, the highest-use recreational fishing lake in B.C., when it experienced its first-recorded winterkill in 2015. However, given the absence of monitoring data, this event raised numerous questions about lake-sensitivity to these multiple stressors. The research presented here utilizes paleolimnological records that span a single century to several millennia to investigate human impacts on lake structure, and to inform possible lake ecosystem trajectories that may occur under a future warm and dry climate. An investigation of trophodynamics in four stocked lakes (including Roche) from the SIP spanning the past ~100 years showed that pronounced early-to-mid 20th century eutrophication, possibly due to the construction of outlet dams, altered foodweb structure in these systems by providing the large and effective grazer Daphnia with increased food availability, and possibly enhanced deep-water refugium. By extending the paleolimnological record to ~11,000 cal yr BP, we showed that water quality and quantity in Roche Lake is sensitive to enhanced aridity; during the Holocene Thermal Maximum (HTM, which was ~2-3°C warmer than present), lake levels were low, and thermal stratification and deep-water anoxia were pronounced. An additional, high-resolution investigation from Roche Lake over the past ~1800 years revealed that the driest period within this time frame was associated with an increase in primary production, and that changes in diatom species composition and deep-water oxygen were driven primarily by lake-atmosphere energy exchange, as opposed to altered lake-landscape interaction. Finally, by synthesizing additional proxy data from the Pacific Northwest, we demonstrated that external climate forcings (i.e., insolation, solar irradiance) and ocean-atmosphere processes, including the Pacific Decadal Oscillation (PDO) and the El Niño Southern Oscillation (ENSO), can generate changes in water quality and quantity in the SIP on millennial to centennial time scales. Overall, these findings highlight the negative consequences that certain lake-management strategies have on water quality and provides evidence for the importance of developing climate-adaptation strategies to protect economically important fisheries in the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".