Investigating competitive interactions from spatial patterns of trees in multispecies boreal forests: the random mortality hypothesis revisited
Bibliographic record
Abstract
Plant competition is expected to produce an overdispersed spatial pattern relative to the initial pattern of individuals. The spatial patterns of two boreal forest tree species, Populus tremuloides Michx. (trembling aspen) and Pinus banksiana Lamb. (jack pine), were examined for evidence of intraspecific and interspecific competition. Data consisting of species, position, and age of tree stems were obtained from a 21-year-old, 40 m × 30 m postfire area of boreal forest in northern Alberta, Canada. Tree stems were mapped and classified according to size (greater or less than 5 cm in diameter at ground height) and species. A variation on the random mortality hypothesis was used to detect overdispersed patterns indicative of competitive interactions. This was done by comparing the size of neighbouring stems with those expected when the size or "success" of a stem occurred randomly. The results showed roughly two scales of pattern. First, large seed-regenerating jack pine neighboured each other more often than expected, but jack pine and trembling aspen neighboured each other less than expected. Second, although the large jack pine appeared to be clustered as neighbours, they tended to associate at distances farther than expected. These results show little evidence of density-dependence patterns in the species at the site, and the interspecific association between jack pine and trembling aspen could be indicative of a heterogeneous habitat.Key words: triangulation, size variability, Pinus banksiana, Populus tremuloides, jack pine, trembling aspen.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".