Adjacency arrangement effects on plant diversity and composition in woodland patches
Bibliographic record
Abstract
To understand “adjacency arrangement” (configuration of a patch and its adjoining elements) as a basic unit of landscape pattern, we studied 30 woodland patches ( Populus tremuloides) in Alberta, Canada, with adjacent vegetation varying from 0% shrubland (100% grassland) to 100% shrubland (0% grassland). We evaluated (1) how important adjacency effects are relative to resource availability and disturbance in affecting plant species richness and composition in the woodland understory, and (2) which species and species groups change in abundance and presence with increasing percent shrubland in the adjacency arrangement. We found that, in addition to topography and previous grazing, adjacency arrangement is a major significant variable affecting the vegetation composition of woodland patches. Along a gradient from 0% to 100% adjacent shrubland, the species composition in woodland patches changed from an abundance of weedy and introduced plants to an abundance of moist‐environment plants, the proportion of native species and perennials increased linearly, the number of “shrubland species” increased linearly, “grassland species” decreased linearly, and total species richness remained constant. Woodland vegetation did not differ significantly where adjacent shrubland was to the east or to the west of the wooded patch, nor between patches which did or did not experience a change in the adjacent shrubland in the recent past. We conclude that adjacency arrangement is an easily measured, highly promising concept for ecological understanding, as well as for land planning, design, conservation and management.
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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".