Prediction of coastal barren plant species richness and functional diversity by environmental variability across scales
Bibliographic record
Abstract
Abstract Questions The relationships between environmental heterogeneity and plant diversity may be negative or neutral at fine spatial scales but positive across broader areas. How do the relationships between spatial environmental variability and mean environmental conditions, plant species richness and functional diversity change across spatial scales? Location Coastal barrens landscape in Nova Scotia, eastern Canada. Methods We sampled plant species composition and environmental variables in nested areas at three scales: 0.25 m 2 , 1 m 2 and 50 m 2 . At each scale, subsamples of environmental variables (including elevation, soil moisture and depth) were used to calculate average and standard deviation; plant species richness was also determined for each sample. Plant traits at the species level were used to calculate functional dispersion for each of five traits (specific leaf area, leaf dry matter content, leaf thickness, plant height and canopy width) and a combined index of total functional dispersion. Functional dispersion and species richness were predicted at each scale by environmental variables using linear mixed models. Results Environmental heterogeneity had low predictive power for plant diversity at the 0.25‐m 2 scale but was unimodally related to species richness and functional‐diversity variables at the 1‐m 2 scale. The shape of the unimodal relationships suggested a leveling off of diversity at higher levels of environmental variability rather than a decline in diversity (monotonic or asymptotic). There was a strong positive relationship between elevation (topographic) variability and species richness at the 50‐m 2 scale. Functional dispersion was most strongly related to environmental variables at the 1‐m 2 scale. Conclusions Positive or non‐linear asymptotic relationships between environmental heterogeneity, richness and functional diversity at the 1‐m 2 scale provide some support for niche‐based explanations of species coexistence in plant neighborhoods. At broader sampling extents, greater topographic heterogeneity may allow distinct plant communities to co‐occur within a sample, increasing richness but not functional diversity because functional diversity in leaf and canopy traits are already high within each plant community.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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".