Intra‐specific and inter‐specific variation in specific leaf area reveal the importance of abiotic and biotic drivers of species diversity across elevation and latitude
Bibliographic record
Abstract
Abstract Questions Are patterns of intra‐ and inter‐specific functional trait variation consistent with greater abiotic filtering on community assembly at high latitudes and elevations, and greater biotic filtering at low latitudes and elevations? Locations Area de Conservación Guanacaste, Costa Rica; Santa Catalina Mountains, Arizona; Siskiyou Mountains, Oregon. Methods We measured woody plant species abundance and a key functional trait associated with competition for resources and environmental tolerance (specific leaf area, SLA) along elevational gradients in low‐latitude tropical (Costa Rica), mid‐latitude desert (Arizona) and high latitude mediterranean (southern Oregon) biomes. We explored patterns of abiotic and biotic filtering by comparing observed patterns of community‐weighted means and variances along elevational and latitudinal gradients to those expected under random assembly. In addition, we related trait variability to niches and explored how total trait space and breadth vary across broad spatial gradients by quantifying the ratio of intra‐ to inter‐specific variation. Results Both the community‐wide mean and variance of SLA decreased with increasing latitude, consistent with greater abiotic filtering at higher latitudes. Further, low‐elevation communities had higher trait variation than expected by chance, consistent with greater biotic filtering at low elevations. Finally, in the tropics and across latitude the ratio of intra‐ to inter‐specific variation was negatively correlated to species richness, which further suggests that biotic interactions influence plant assembly at low latitudes. Conclusions Intra‐ and inter‐specific patterns of SLA variation appeared broadly consistent with the idea that the relative strength of biotic and abiotic drivers on community assembly changes along elevational and latitudinal gradients; evidence for biotic drivers appeared more prominent at low latitudes and elevations and evidence for abiotic drivers appeared more prominent at high latitudes and elevations.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".