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 the currently warming climate. In contrast, coastal rock cliffs on Svalbard are considered to be comparably stable, based on previous studies that considered only a few years and limited coastal reaches. Long-term trends of coastal retreat rates in rock cliffs on Svalbard are unknown so far, but their quantification could improve the understanding of coastal dynamics on the Arctic archipelago. This study presents coastal retreat rates in rock cliffs along several kilometers of the Brøgger peninsula, Svalbard. The work is based on high-resolution orthoimages from 1970, 1990, 2010, and 2021, corroborated by high-precision dGNSS measurements along selected segments of the coastline and by rock surface temperature measurements during the period 2020–2021. Our analysis shows that coastal retreat rates accelerate statistically significant along the Brøgger peninsula in the time period of 2010 to 2021. This is true for both the northeast facing coastline, with retreat rates increasing from 0.04 ± 0.06 m/a (1970–1990) and 0.04 ± 0.04 m/a (1990–2010) to 0.07 ± 0.08 m/a (2010–2021) and the southwest facing coastline, where retreat rates of 0.26 ± 0.06 m/a (1970–1990), 0.24 ± 0.04 m/a (1990–2010) and 0.30 ± 0.08 m/a (2010–2021) are measured. Furthermore, the parts of the coastline affected by erosion increase along the northeast facing coastline from 47 % (1970–1990) to 65 % (2010–2021), while they stay consistently above 90 % along the southwest facing coastline. Measurements of rock surface temperature show mean annual values close to the thaw threshold with −0.49 °C at the southwest facing coastline, while records at the northeast facing coastline are lower with −1.64 °C. The recently accelerated retreat rates coincide with increasing storminess and retreating sea ice, together with increasing ground temperatures, all 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".