Quantifying the importance of regional and local filters for community trait structure in tropical and temperate zones
Bibliographic record
Abstract
The influence of regional and local processes on community structure is a major focus of ecology. Classically, ecologists have used local-regional richness regressions to evaluate the role of local and regional processes in determining community structure, an approach that has numerous flaws. Here, we implemented a novel trait-based approach that treats local and regional influences as a continuum, rather than a dichotomy. Using hylid frogs (Hylidae), we compared trait dispersion among members of local species assemblages to the trait dispersion in the regional assemblage from which they were drawn. Similarly, we compared trait dispersion in the regional assemblages to dispersion in the continental species pool. We estimated the contributions of local and regional filters, and we compared their strength in temperate and tropical zones. We found that regional and local filters explained 80% of the total variation among local assemblages in community body size dispersion. Overall, regional filters reduced trait dispersion, and local filters increased it, a pattern driven by particularly strong antagonistic effects in temperate zones that reduced the realized total variation by more than 40%. In contrast, local and regional filters acted in concert in tropical regions. Patterns within the tropics did not differ from the random expectation based on a null model, but within the temperate zone, local community filtering was stronger than expected by chance. Furthermore, in temperate regions, antagonistic regional and local filtering masked from 76% to 90% of the total variation in trait dispersion. Together, these results suggest that there are fundamental differences in the scale and identity of the processes determining community structure in temperate and tropical regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".