Tree squirrel abundance and demography in managed coniferous forests of British Columbia are within the range of natural fluctuations of old-growth stands
Bibliographic record
Abstract
The American red squirrel (Tamiasciurus hudsonicus Exrleben) and northern flying squirrel (Glaucomys sabrinus Shaw) are important mammal species in coniferous forests that are widely distributed across temperate and boreal ecological zones. Although T. hudsonicus and G. sabrinus apparently prefer late-successional forests, their population dynamics show no clear pattern in young second-growth and old-growth conifer forests. We used a compilation of study results that had standardized methodology and sampling effort to compare tree squirrel responses across a range of forest conditions. We tested the hypotheses (H) that abundance, reproduction, recruitment, and survival would be higher in (H 1 ) old-growth than second-growth stands, (H 2 ) unthinned than thinned second-growth stands, and (H 3 ) lightly than heavily thinned stands. Tree squirrel populations in old-growth stands were considered the “standard” treatment to which other treatments in second-growth stands (unthinned and variously thinned) were compared. Thinned stands were grouped into low, medium, and high densities of trees. Datasets from seven published studies included 2804 Tamiasciurus and 837 G. sabrinus individuals, 25 study years, and 158 trapping periods. Mean abundance of Tamiasciurus was similar among treatment stands, ranging from 0.62 to 1.29·ha −1 . Mean numbers of G. sabrinus were highest in old-growth stands at 0.65·ha −1 , followed by the low- and medium-density stands at 0.50·ha −1 , the high-density stands at 0.25·ha −1 , and finally the unthinned second-growth stands at a low of 0.12·ha −1 . In terms of effect size, mean proportional change in abundance, relative to that within old-growth stands, of both squirrel species in the three thinned stands were within the range of natural fluctuations in old-growth stands. Populations of Tamiasciurus in the unthinned stands were not within the range of fluctuations in the old-growth stands. Mean number of successful pregnancies and total recruits were similar among stands for Tamiasciurus, with variability in female breeding and winter survival. Mean number of recruits of G. sabrinus was highest in old-growth stands with no other differences in demographic attributes among stands. The biological significance of these differences in demographic variables was small in terms of effect sizes. Tamiasciurus and G. sabrinus seem to persist in a relatively broad range of young managed forest habitats, as well as in old-growth stands.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".