Climatic commonness and rarity shape phylogenetic structure and suitability in tetrapod communities
Bibliographic record
Abstract
Climate shapes ecological communities across space and time, with significant implications for biodiversity conservation. It sets physiological limits for organisms, influencing population dynamics, species distributions, community assembly and, ultimately, biodiversity patterns. Among its various components, an underexplored aspect of climate is its frequency distribution—or commonness and rarity—across space. We investigated three questions to elucidate the mechanisms underlying community-level responses to climatic frequency: Does climatic frequency influence the phylogenetic structure of ecological communities across geographical scales? Are rare climates less suitable for supporting diversity of closely related species than common climates? Do species sharing relatively recent common ancestors share similar climatic frequencies? We analyzed global data on climate, geographical distributions, and phylogenetic relationships of extant terrestrial four-limbed vertebrates (Tetrapoda)—amphibians, birds, mammals, and reptilian squamates. Globally, we found that ecological communities are less phylogenetically clustered in rare climates. Communities in rare climates exhibit less phylogenetic clustering, and in both exceedingly rare and common climates, co-occurring species frequently depart from their climatic optima. Combined, these findings suggest that recent ecological dynamics and evolutionary adaptations play a stronger role than deep ancestral constraints in shaping these communities.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".