Edge influence on herbaceous plant species, diversity and soil properties in sparse oak forest fragments in Iran
Bibliographic record
Abstract
Abstract Forest edges have been well studied in temperate and tropical forests, but less so in open canopy forests. We investigated edge influence on plant species diversity and soil properties in sparse oak forest fragments. Data were collected along three transects from the edge to the interior of three small (under 10 ha) and three large (over 10 ha) oak forest fragments in Kermanshah Province, Iran. We measured herbaceous plants (<0.5 m in height) and soil attributes at 0 (forest edge), 25, 50, 100 and 150 m. We quantified species diversity using the Shannon index, used rarefaction to compare species richness between two different sizes of fragments and applied non-metric multidimensional scaling ordination to investigate the variation in species composition. We estimated the distance of edge influence using randomization tests. Generalized linear mixed models with post-hoc Tukey’s HSD tests were used to assess the effects of distance from edge and fragment size on diversity and soil properties. We found greater species richness, diversity and evenness at the edge of both small and large fragments and lower nitrogen and organic carbon at the edge compared to the interior of large fragments, with most changes within 50 m of the edge. Species composition, organic carbon and total nitrogen were significantly different between small and large fragments. Our findings of significant edge influence on herbaceous plants and soil properties in these sparse forests provide a significant contribution to the literature on edges, especially in relation to herbaceous plants.
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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".