Patterns of frequency in species-rich vegetation in pine savannas: Effects of soil moisture and scale
Bibliographic record
Abstract
Our principal objective was to document dominant plant composition and the species frequency pattern in a plant community type, longleaf pine savanna, known for its extraordinary number of vascular plant species. We also tested whether an important habitat factor, soil moisture, affected the resulting patterns, and whether the patterns were scale-dependent. We began with a collection of 120 sample plots (1- × 1-m) in a wet coastal plain savanna. These plots contained 126 plant species. The 3 dominant species by cover were Rhynchospora gracilenta (15.37%), Schizachyrium tenerum (13.36%), and Scleria pauciflora (10.07%). The species frequency distribution was a skewed unimodal pattern with most species occurring infrequently, in less than 10% of the plots. There was no evidence for bimodality. To test whether soil moisture affected species frequency patterns, we sorted the plots into 2 groups: 60 representing wetter conditions and 60 representing drier conditions. Measured by percent cover, the dominants in the wetter plots were R. gracilenta, Dichanthelium scabriusculum, and S. pauciflora, whereas in the drier area they were S. tenerum, Ilex glabra, and D. dichotomum. The species frequency pattern was similar for both wet and dry plots (χ2 = 8.97, P > 0.05). To explore possible effects of sample area on this pattern, we sampled a further 75 plots in a larger tract of similar habitat in De Soto National Forest, using 4 sample areas 0.1, 1, 10, and 100 m2 Again, the species frequency distributions all had a skewed unimodal pattern. These patterns are consistent with other studies of savannas but do not appear consistent with the bimodal patterns reported from some grasslands. Further studies of frequency will determine the degree of generality of such patterns and their relationship to mechanistic processes in plant communities.
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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 | 0.000 |
| 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) | 0.001 | 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".