Neutral Biogeography and the Evolution of Climatic Niches
Bibliographic record
Abstract
Recent debate on whether climatic niches are conserved through time has focused on how phylogenetic niche conservatism can be measured by deviations from a Brownian motion model of evolutionary change. However, there has been no evaluation of this methodological approach. In particular, the fact that climatic niches are usually obtained from distribution data and are thus heavily influenced by biogeographic factors has largely been overlooked. Our main objective here was to test whether patterns of climatic niche evolution that are frequently observed might arise from neutral dynamics rather than from adaptive scenarios. We developed a model inspired by neutral biodiversity theory, where individuals disperse, compete, and undergo speciation independently of climate. We then sampled the climatic niches of species according to their geographic position and showed that even when species evolve independently of climate, their niches can nonetheless exhibit evolutionary patterns strongly differing from Brownian motion. Indeed, climatic niche evolution is better captured by a model of punctuated evolution with constraints due to landscape boundaries, two features that are traditionally interpreted as evidence for selective processes acting on the niche. We therefore suggest that deviation from Brownian motion alone should not be used as evidence for phylogenetic niche conservatism but that information on phenotypic traits directly linked to physiology is required to demonstrate that climatic niches have been conserved through time.
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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 | 0.002 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".