Conifer density increases in semi-desert habitats of British Columbia in the absence of fire
Bibliographic record
Abstract
We determined whether or not conifer density has changed over time in the hottest and driest areas of the south Okanagan and lower Similkameen valleys in British Columbia, Canada. These grassland and savannah habitats are important for biodiversity and species at risk in Canada, and there is some discussion as to whether conifer establishment is occurring. Densities of ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) were compared between airphotos from 1938 to 1985, and from 1985 to 1996 in study sites 10- to 183-ha in size. Air photos were scanned and georeferenced to ensure spatial congruency between years. The location and area of wildfires in the intervening periods were also recorded. A three-way ANCOVA, with site area as the covariable, tested the effects of fire, latitudinal category (north versus south), and biogeoclimatic (ecological) zone (ponderosa pine versus Bunchgrass) on changes in conifer density between years. The results showed an overall significant increase in density in unburned sites from 1938 to 1985, and from 1985 to 1996. Despite some inconsistent sites, fire resulted in an overall decrease in density. Neither biogeoclimatic zone nor latitude affected conifer density change over time. Stem densities in 1938, 1985 and 1996 were similar between latitudinal category and biogeoclimatic zone, except for the hottest and driest combination, in the south, in the lower elevation Bunchgrass biogeoclimatic zone, which had less than half the stem density of the other areas. However, the rate of change in stem density of conifers in unburned sites did not differ because of latitude or biogeoclimatic zone. Our results show that coniferous trees are capable of establishing in even these dry semi-desert sites, and prescribed burns might be considered for restoring grassland and savannah habitat.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".