Influence of vertical and lateral heat transfer on permafrost thaw, peatland landscape transition, and groundwater flow
Bibliographic record
Abstract
Abstract Recent climate change has reduced the spatial extent and thickness of permafrost in many discontinuous permafrost regions. Rapid permafrost thaw is producing distinct landscape changes in the Taiga Plains of the Northwest Territories, Canada. As permafrost bodies underlying forested peat plateaus shrink, the landscape slowly transitions into unforested wetlands. The expansion of wetlands has enhanced the hydrologic connectivity of many watersheds via new surface and near‐surface flow paths, and increased streamflow has been observed. Furthermore, the decrease in forested peat plateaus results in a net loss of boreal forest and associated ecosystems. This study investigates fundamental processes that contribute to permafrost thaw by comparing observed and simulated thaw development and landscape transition of a peat plateau‐wetland complex in the Northwest Territories, Canada from 1970 to 2012. Measured climate data are first used to drive surface energy balance simulations for the wetland and peat plateau. Near‐surface soil temperatures simulated in the surface energy balance model are then applied as the upper boundary condition to a three‐dimensional model of subsurface water flow and coupled energy transport with freeze‐thaw. Simulation results demonstrate that lateral heat transfer, which is not considered in many permafrost models, can influence permafrost thaw rates. Furthermore, the simulations indicate that landscape evolution arising from permafrost thaw acts as a positive feedback mechanism that increases the energy absorbed at the land surface and produces additional permafrost thaw. The modeling results also demonstrate that flow rates in local groundwater flow systems may be enhanced by the degradation of isolated permafrost bodies.
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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) | 0.003 | 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 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".