Acceleration of coastal-retreat rates for high-Arctic rock cliffs on Brøggerhalvøya, Svalbard, over the past decade
Bibliographic record
Abstract
Abstract. In many Arctic regions, marine coastlines change rapidly in our currently warming climate. In contrast, coastal rock cliffs on Svalbard are considered to be relatively stable. Long-term trends of coastal-retreat rates for rock cliffs on Svalbard remain unknown, but quantifying them could improve our understanding of coastal dynamics in the Canadian Arctic Archipelago. This study presents coastal-retreat rates for rock cliffs along several kilometres of Brøggerhalvøya, Svalbard. The analysis relies on high-resolution orthoimages from 1970, 1990, 2010, and 2021. The data are corroborated by high-precision dGNSS (differential Global Navigation Satellite System) measurements obtained along selected segments of the coastline. Our analysis reveals statistically significant acceleration in coastal-retreat rates across Brøggerhalvøya between 2010 and 2021. The northeast-facing coastline features fairly stable conditions, with retreat rates of 0.04 ± 0.06 m a−1 (1970–1990; calculated retreat rate ± the corresponding measurement uncertainty), 0.04 ± 0.04 m a−1 (1990–2010), and 0.06 ± 0.08 m a−1 (2010–2021). Along the southwest-facing coastline, higher retreat rates of 0.26 ± 0.06 m a−1 (1970–1990), 0.24 ± 0.04 m a−1 (1990–2010), and 0.30 ± 0.08 m a−1 (2010–2021) were calculated. For the most recent decade, this corresponds to an increase of 50 % for the northeast-facing coastline and an increase of 25 % for the southwest-facing coastline. Furthermore, for the northeast-facing coastline, the proportion of the coastline affected by erosion increased from 47 % (1970–1990) to 65 % (2010–2021), while it stayed consistently above 90 % for the southwest-facing coastline. The recent acceleration in retreat rates coincides with increasing storminess and retreating sea ice, factors that can enhance coastal erosion.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".