Evolving High Arctic Landscapes: A Fluvial Geomorphic Perspective
Bibliographic record
Abstract
Recent climate warming and changing precipitation patterns have both thermally and physically disturbed permafrost watersheds across much of the Arctic, increasing the mobility of dissolved and particulate material from terrestrial to aquatic environments. The overarching objective of this research was to determine the spatial and temporal scale of the impact permafrost disturbances, both thermal and physical, have on all of the major components of fluvial material fluxes. This research significantly expanded on long-term field observations (2003- 2017) at the Cape Bounty Arctic Watershed Observatory (CBAWO) in the Canadian High Arctic (~75 ºN). Thermal disturbance (deep active layer thaw) significantly alters the export of dissolved ions at all spatial scales observed and fluxes remain elevated after a decade of observation, post-disturbance. Localized physical disturbances (active layer detachments: ALDs) were shown to change fluvial systems from dissolved to particulate dominated export in small, headwater-slope streams. Particulate fluxes respond immediately to and recover rapidly from localized ALDs, but remain elevated ten-years post physical-disturbance. Despite increased particulate erosion from small, headwater-slope streams, localized ALDs have not increased the downstream, watershed-scale flux of particulate material beyond an immediate, short-lived pulse at the outlet of both watersheds. This indicates that the impact of localized ALDs on particulate material fluxes does not spatially scale-up to the larger watersheds at the CBAWO, which is largely explained by: (1) the propensity toward net in-channel and extra-channel sediment storage along the main drainage network, (2) changing hydrometeorological conditions, and (3) limited contemporary fluvial energy to mobilize additional sediment in this setting. This research has substantially advanced our understanding of how different types of permafrost disturbance alter the composition and magnitudes of fluvial fluxes in discernible ways that improve our understanding of changes to circum-Arctic environments. This thesis provides essential constraints on the temporal persistence of the impact of differing permafrost disturbances on fluvial systems. Results from this thesis will help inform coupled climate-terrestrial models and will help to spatially-scale the impact of permafrost changes on fluvial systems across the circum-Arctic.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".