Unraveling the Interplay of Community Assembly Processes Acting on Multiple Niche Axes across Spatial Scales
Bibliographic record
Abstract
How the relative importance of community assembly processes varies with spatial scale is the focus of intensive debate, in part because inferring the scales at which specific niche-based processes act is difficult. One obstacle is that standard phylogenetic and functional diversity metrics may integrate the signals of multiple processes when combining separate niche axes into one variable (multiple-niche-axis metrics), potentially obscuring overlapping niche-based processes. We use simulations to evaluate the power of these metrics to detect competition and habitat filtering when these processes operate across multiple niche axes and vary in their relative importance. We then test for both processes at a range of spatial scales in a Neotropical bird assemblage. Simulations revealed that multiple-niche-axis metrics had low power to detect competition and habitat filtering when a mix of both processes acts across niche axes, whereas metrics focused on single-niche axes were better able to deal with this complexity. We found the same contrast in bird communities, where both competition and habitat filtering were detected at the scale of individual territories, but only by single-niche-axis metrics focused on specific niche axes (e.g., foraging traits). Our results suggest that multiple-niche-axis metrics may produce misleading evidence that niche-based processes are partitioned, particularly across scales, and highlight the importance of analyzing functional diversity patterns on individual niche axes when testing assembly models.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".