Landscape-level dynamics of grassland-forest transitions in British Columbia
Bibliographic record
Abstract
Grasslands in the interior British Columbia of Canada are adjacent to forests and are susceptible to tree encroachment. Grazing, fire suppression, and climate variability are among factors affecting vegetation dynamics in the ecotone between grassland and forest, but topographic factors such as slope aspect, slope degree and elevation may interact with these factors and result in uneven changes in vegetation among landscape elements. Nine sites with a total of approximately 50,000 ha of grasslands and forests in the Cariboo/Chilcotin forest region of British Columbia were selected to study the effect of slope aspect, slope degree and elevation on vegetation distribution, dynamics and forest expansion from the 1960's to 1990's. Vegetation maps of the 1960's and 1990's were generated using aerial photos and overlaid with GIS layers including aspect, slope and elevation. The classification of open grassland, treed grassland, open forest and closed forest was based on the percent coverage of coniferous species, ranging from 0-5%, 5-15%, 15-35%, and ≥ 35%, respectively. A probability index (P-value) was developed to test the effect of aspect, slope, and elevation on vegetation distribution, dynamics, and forest expansion based on the distribution and changed areas. Results show that open grasslands occurred on southerly aspects and the shift to treed grassland occurred mostly on these aspects. The probability of vegetation shift from open to treed grasslands decreased with increasing slope degree, probably due to the less favorable moisture regime on steep slopes. Treed grassland also shifted to open forest on south facing slopes and more level sites. In contrast, closed forest most often occurred on northerly facing slopes and the shift from open to closed forests was most likely to occur there. The greatest changes in vegetation cover types occurred at mid-elevations between 700 and 1,000 m. Management plans aimed at the control of tree encroachment and forest ingrowth should take these topographic factors into consideration.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".