Isotopic evidence of increasing water abundance and lake hydrological change in Old Crow Flats, Yukon, Canada
Bibliographic record
Abstract
Abstract Lake-rich northern permafrost landscapes are sensitive to changing climate conditions, but ability to track real-time and potentially multiple hydrological responses (e.g. lake expansion, drawdown, drainage) is challenging due to absence of long-term, sustainable monitoring programs in these remote locations. Old Crow Flats (OCF), Yukon, is a Ramsar Wetland of International Importance where concerns about low water levels and their consequences for wildlife habitat and traditional ways of life prompted multidisciplinary studies during the International Polar Year (2007–2008) and led to the establishment of an aquatic ecosystem monitoring program. Here, we report water isotope data from 14 representative thermokarst lakes in OCF, the foundation of the monitoring program, and time-series of derived metrics including the isotope composition of input waters and evaporation-to-inflow ratios for a 13 year period (2007–2019). Although the lakes spanned multiple hydrological categories (i.e. rainfall-, snowmelt- and evaporation-dominated) based on initial surveys, well-defined trends from application of generalized additive models and meteorological records reveal that lakes have become increasingly influenced by rainfall, and potentially waters from thawing permafrost. These sources of input have led to more positive lake water balances. Given the documented role of rainfall in causing thermokarst lake drainage events in OCF and elsewhere, we anticipate increased vulnerability of lateral water export from OCF. This study demonstrates the value of long-term isotope-based monitoring programs for identifying hydrological consequences of climate change in lake-rich permafrost landscapes.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".