Widespread 20th-century increases in Canadian lake primary production and the roles of climate warming, solar irradiance and human impacts
Bibliographic record
Abstract
Lakes provide many vital ecosystem services but are highly sensitive to human impacts and climate change. While data needed to assess their long-term trajectories are generally unavailable, lake responses to such perturbations can be inferred from sediment archives, including records of chlorophyll, a proxy for primary production. However, few if any datasets exist to test hypotheses at large spatial scales about the drivers of long-term change. Here, we apply rapid hyperspectral imaging to produce high-resolution records of sediment chlorophyll (defined as the sum of chlorophyll a and b and their degradation products) in dated cores from 80 lakes across Canada and identify an overall increase since the mid-19th-century. Breakpoint analysis detected a shift whereby the average rate of chlorophyll increase was seven times greater after 1966 than before. We then compared spatiotemporal chlorophyll trends to climate variables, solar irradiance, and land-use data to assess their relationships to past changes in primary production. We identified robust correlations between chlorophyll and climate variables (temperature and ice cover) that were especially strong after 1966, suggesting continental-scale alterations to lake primary production in response to recent accelerated warming. We also detected significant associations with incident solar radiation and catchment human impacts, and show that both had the potential to influence past primary production at the continental scale. Strong correlation between increased chlorophyll and climate variables after 1966 suggests continental-scale alterations to lake primary production due to accelerated warming, solar irradiance, and human impacts, according to high-resolution imaging of dated cores from 80 lakes across Canada.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".