Assessment of interspecific competition using relative height and distance indices in an age sequence of seral interior cedarhemlock forests in British Columbia
Bibliographic record
Abstract
Treatments that reduce neighbour density are widely applied in the belief they will improve conifer growth in mixed forests. However, our understanding of stand composition and age effects on competition is poor. We used neighbourhood analysis for 748 target conifer trees to examine interspecific competition within 11-, 25-, and 50-year-old mixed, even-aged stands of paper birch (Betula papyrifera Marsh.), Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn.) Franco), western redcedar (Thuja plicata Donn ex D. Don), and western larch (Larix occidentalis Nutt.) in southern interior British Columbia. Critical neighbourhood height and distance were identified where competition accounted for the greatest variation in target conifer diameter. Competition processes were emperically examined using relative height indices. We found that critical neighbourhood distance increased with stand age and was greater for larch than for cedar. Critical neighbourhood height was higher for cedar than for Douglas-fir or larch in the 11-year-old stands but lower in the older stands. The most important competitors in the 11-year-old stands were tall neighbours, whereas those in the older stands were short neighbours. We found asymmetrical relationships between target conifers and neighbours for all species and age-classes, indicating a resource preemption mode of competition. To be useful in developing prescriptions for competition management in mixed species stands, competition indices should consider neighbour identity and critical height for each target species. Assessment radius must also be sufficiently large to adequately characterize competition.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".