The Resilience of Polar Collembola (Springtails) in a Changing Climate
Bibliographic record
Abstract
Assessing the resilience of polar biota to climate change is essential for predicting the effects of changing environmental conditions for ecosystems. Collembola are abundant in terrestrial polar ecosystems and are integral to food-webs and soil nutrient cycling. Using available literature, we consider resistance (genetic diversity; behavioural avoidance and physiological tolerances; biotic interactions) and recovery potential for polar Collembola. Polar Collembola have high levels of genetic diversity, considerable capacity for behavioural avoidance, wide thermal tolerance ranges, physiological plasticity, generalist-opportunistic feeding habits and broad ecological niches. The biggest threats to the ongoing resistance of polar Collembola are increasing levels of dispersal (gene flow), increased mean and extreme temperatures, drought, changing biotic interactions, and the arrival and spread of invasive species. If resistance capacities are insufficient, numerous studies have highlighted that while some species can recover from disturbances quickly, complete community-level recovery is exceedingly slow. Species dwelling deeper in the soil profile may be less able to resist climate change and may not recover in ecologically realistic timescales given the current rate of climate change. Ultimately, diverse communities are more likely to have species or populations that are able to resist or recover from disturbances. While much of the Arctic has comparatively high levels of diversity and phenotypic plasticity; areas of Antarctica have extremely low levels of diversity and are potentially much more vulnerable to climate change.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".