Density‐dependent effects on tree survival in an old‐growth Douglas fir forest
Bibliographic record
Abstract
Summary 1 We mapped the locations of live and dead trees in a large forest plot dominated by pioneer Douglas fir (Pseudotsuga menziesii) with an understorey of the invading late‐successional species western hemlock (Tsuga heterophylla) and western red cedar (Thuja plicata) on Vancouver Island, British Columbia, Canada, to test for intra‐ and interspecific density‐dependent effects on tree survival. 2 We analysed both the spatial patterning of trees in the plot and the relationships between neighbourhood density and tree survival. We also examined the effects of additional variables (principally elevation) as covariates in our neighbourhood analyses. 3 Both the spatial and initial neighbourhood analyses suggested strong intra‐ and interspecific density‐dependent effects on tree survival. Douglas fir survival was significantly higher in less dense patches of conspecifics and non‐random tree death led to regularly spaced survivors, as expected from intraspecific competition. The significantly lower survival of western hemlock in denser patches of Douglas fir and the resulting negative spatial association between surviving trees of these two species were consistent with interspecific competition. 4 However, having controlled for the influence of elevation on tree survival (probably mediated by variation in soil moisture) in neighbourhood analyses, although the survival of the pioneer Douglas fir trees was still subject to strong density‐dependent effects, variation in its density in the overstorey no longer appeared to influence the survival of the invading late‐successional species. There was, however, evidence for asymmetric interspecific density dependence between the two late‐successional species since western hemlock mortality tended to be higher in denser patches of western red cedar. 5 Our results emphasize the importance of considering confounding factors in studies that seek evidence for density dependence.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".