A synthesis of thermokarst lake water balance in high-latitude regions of North America from isotope tracers
Why this work is in the frame
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Bibliographic record
Abstract
Numerous studies utilizing remote sensing imagery and other methods have documented that thermokarst lakes are undergoing varied hydrological transitions in response to recent climate changes, from surface area expansion to drainage and evaporative desiccation. Here, we provide a synthesis of hydrological conditions for 376 lakes of mainly thermokarst origin across high-latitude North America. We assemble surface water isotope compositions measured during the past decade at five lake-rich landscapes including Arctic Coastal Plain (Alaska), Yukon Flats (Alaska), Old Crow Flats (Yukon), northwestern Hudson Bay Lowlands (Manitoba), and Nunavik (Quebec). These landscapes represent the broad range of thermokarst environments by spanning gradients in meteorological, permafrost, and vegetation conditions. An isotope framework was established based on flux-weighted long-term averages of meteorological conditions for each lake to quantify water balance metrics. The isotope composition of source water and evaporation-to-inflow ratio for each lake were determined, and the results demonstrated a substantial array of regional and subregional diversity of lake hydrological conditions. Controls on lake water balance and how these vary among the five landscapes and with differing environmental drivers are assessed. Findings reveal that lakes in the Hudson Bay Lowlands are most vulnerable to evaporative desiccation, whereas those in Nunavik are most resilient. However, we also identify the complexity in predicting hydrological responses of these thermokarst landscapes to future climate change.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it