Emergence of Potential Anadromous Arctic Charr (<i>Salvelinus alpinus</i>) Habitats in the Svalbard Archipelago After the End of the Little Ice Age
Bibliographic record
Abstract
Abstract Glaciers in the Svalbard Archipelago are retreating rapidly in response to climate change. This retreat leads to the alteration of the hydrological and thermal regimes of freshwater ecosystems. In this delicate context, existing anadromous Arctic charr (Salvelinus alpinus) populations are at severe risk and might disappear from the archipelago. However, the retreat of glaciers also promotes the formation of new lake systems that might be suitable for colonization by anadromous Arctic charr. These systems may provide a substantial opportunity for the establishment of new populations of anadromous charr, potentially buffering the decline in existing systems. To date, there is a lack of information on the number of recently deglaciated lake systems that have emerged since the end of the Little Ice Age (ca. 1920) that might be suitable for charr colonization. Therefore, the goal of this paper is to provide an initial assessment of the number of these lakes. To this end, and in accordance with previously published research, this study assesses whether a recently deglaciated lake system is potentially open to colonization based on gradient, river length, and lake surface area. Depending on the applied threshold (four in total), up to 24 lake systems are classified as potentially open to colonization by anadromous Arctic charr, with Spitsbergen emerging as a potential hotspot for colonization. The findings of this paper might serve as basis for new studies and for implementing proactive management and conservation strategies to protect anadromous charr populations.
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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 | 0.001 | 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".