Evolutionary ecology at the extremes of species’ ranges
Bibliographic record
Abstract
The nature of species at the extremes of their ranges impinges fundamentally on diverse biological issues, including species’ range dynamics, population variability, speciation and conservation biology. We review the literature concerning genetic and ecological variation at species’ range edges, and discuss historical and contemporary forces that may generate observed trends, as well as their current and future implications. We discuss literature which shows how environmental, ecological and evolutionary factors act to limit species’ ranges, and how these factors impose selection for adaptation or dispersal in peripheral populations exposed to extreme and stochastic biotic and abiotic stressors. When conditions are sufficiently harsh such that local extinction is certain, peripheral populations may represent temporary offshoots from stable core populations. However, in cases where peripheral populations persist at the range edge under divergent or extreme conditions, biologically significant differences can arise from historical and contemporary ecological and evolutionary forces. In many such cases reviewed herein, peripheral populations tended to diverge from the species’ core, and to display lower genetic diversity or greater stress-adaptation. We conclude that while such populations may be of particular conservation value as significant components of intraspecific biodiversity or sources of evolutionary innovation and persistence during environmental change, small and greatly variable population size, especially combined with low genetic variability, can result in elevated extinction risk in harsh and stochastic peripheral environments. As a result, while peripheral populations should not be dismissed as evolutionary dead-ends destined for local extinction, neither should they be uncritically granted inherently superior significance based only on their peripheral position alone.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".