Linking biodiversity and geodiversity: Arctic-nesting birds select refuges generated by permafrost degradation
Bibliographic record
Abstract
Abstract. To gain better insight into the cascading impact of warming-induced changes in the physical landscape on biodiversity, it is crucial to establish stronger links between abiotic and ecological processes governing species distribution. Abiotic processes shaping the physical characteristics of the environment could significantly influence predator movements in the landscape and ultimately affect biodiversity through interspecific interactions. In the Arctic tundra, the main terrestrial predator (Arctic fox) avoids patches of wetlands composed of ponds with islets that can act as refuges for prey. Little is known about the geomorphological processes generating islets selected by prey species. Our study aimed to identify i) the physical characteristics of islets selected by Arctic-nesting birds and ii) the geomorphological processes generating islets available in the landscape. Over two breeding seasons, we determined the occurrence of nesting birds (Glaucous gull, Cackling goose, Red-throated loon) on islets (N=396) found over a 150 km2 area on Bylot Island (Nunavut, Canada). Occupied islets were located further away from the shore (10.6 m ± 7.3 vs 7.4 m ± 6.8) and surrounded by deeper water (33.6 cm ± 10.6 vs 28.1 cm ± 11.5). As expected, all three bird species selected islets less accessible to Arctic foxes, with nesting occurrence increasing (linearly or nonlinearly) with distance to shore and/or water depth around islets. Based on high-resolution satellite image and field observations, we found that ice-wedge polygon degradation generated the majority of islets (71 %) found in the landscape. Those islets were on average farther from the shore and surrounded by deeper water than those generated by other processes. As polygon degradation is projected to accelerate in response to warming, new refuges will likely emerge in the Arctic landscape, but current refuges could also disappear. Changes in the rate of polygon degradation may thus affect Arctic tundra biodiversity by altering predator-prey interactions.
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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 | 0.000 |
| 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".