Emerging dominance of summer rainfall in driving High Arctic terrestrial-aquatic connectivity
Bibliographic record
Abstract
Abstract Climate warming-related hydrological transformations are changing material mobilization, composition, and transport pathways along the terrestrial-aquatic continuum. Here, we integrate decade-long hydrometeorological and biogeochemical data from the High Arctic to show that annual fluvial energy is shifting from a skewed (snowmelt-dominated) to a multi-modal (snowmelt- and rainfall-dominated) distribution. This shift enhanced terrestrial-aquatic connectivity for dissolved and particulate material fluxes, but to overcome the watersheds’ buffering capacity for particulate material rainfall events had to increase by an order of magnitude. Permafrost disturbances (< 3 % of the watersheds’ areal extent) reduced watershed-scale DOC export enough to offset concurrent increased DOC export in undisturbed watersheds but play a weaker role in altering C export than the increased magnitude and frequency of late summer rainfall events. However, the disturbances have primed the landscape for accelerated geomorphic change when future rainfall magnitudes and consequent pluvial responses exceed the current buffering capacity of the terrestrial-aquatic continuum.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".