Evolutionary and ecological causes of species richness patterns in North American angiosperm trees
Bibliographic record
Abstract
Climate and evolutionary factors (e.g. diversification, time‐for‐speciation, niche conservatism) are both thought to be major drivers of species richness in regional assemblages. However, few studies have simultaneously investigated the relative effects of climate and evolutionary factors on species richness across a broad geographical extent. Here, we assess their relative effects on species richness of angiosperm trees across North America. Species richness of angiosperm trees in 1175 regional assemblages were related to climate and phylogenetic structure using a structural equation modeling (SEM) approach. Climate was quantified based on the mean temperature of the coldest month and mean annual precipitation. Evolutionary factors (time‐for‐speciation vs diversification) were inferred from phylogeny‐based measures of mean root distance, phylogenetic species variability, and net relatedness index. We found that at the continental scale, species richness is correlated with temperature and precipitation with approximately similar strength. In the SEM with net relatedness index and phylogenetic species variability and with all the 1175 quadrats, the total direct effect size of phylogenetic structure on species richness is greater than the total direct effect size of climate on species richness by a factor of 3.7. The specific patterns of phylogenetic structure (i.e. greater phylogenetic distances in more species rich regions) are consistent with the idea that time and niche conservatism drive richness patterns in North American angiosperm trees. We conclude that angiosperm tree species richness in regional assemblages in North America is more strongly related to patterns of phylogenetic relatedness than to climatic variation. The results of the present study support the idea that climatic and evolutionary explanations for richness patterns are not in conflict, and that evolutionary processes explain both the relationship between climate and richness and substantial variation in richness that is independent of climate.
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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 | 0.001 |
| Scholarly communication | 0.000 | 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".