Assessing Differences in Competitive Effects Among Tree Species in Central British Columbia, Canada
Bibliographic record
Abstract
Research Highlights: We investigated the competitive interactions among three tree species (interior Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn.) Franco), interior spruce (Picea glauca [Moench] Voss × Picea engelmannii Engelm.), and lodgepole pine (Pinus contorta Dougl. Ex Loud. var. latifolia Englem.)) in multi-aged stands in central British Columbia, Canada. Background and Objectives: Understanding competitive interactions among tree species in mixed-species stands is fundamental to supporting silvicultural decision-making in such stands. Using the periodic annual basal area increment for single trees as our dependent variable, we investigated whether neighboring trees competed with subject trees independently of species identity. We also examined the differences in single-tree basal area growth among the three conifer species over time under different levels of competition. Materials and Methods: We developed several spatially explicit, single-tree basal area growth models for interior Douglas-fir, interior spruce, and lodgepole pine using data from 16 plots in two blocks of a long-term study (five measurements over a 21-year period) on the response to pre-commercial thinning. We compared these equations to assess whether intraspecific or interspecific competition predominated. We also examined the differences in basal area growth among the three conifer species over time under different levels of competition. Results: We found asymmetrical relationships between the conifer trees and their neighbors for all species, indicating that the main driver limiting growth in these stands is aboveground competition for light. There was evidence of higher intraspecific competition for small (<10.0 cm DBH) interior Douglas-fir in one block. However, there was no general pattern among larger subject trees with respect to the identity of neighborhood competitive effects and the equivalence of neighbors. We observed a higher level of basal area growth over time for interior Douglas-fir than for lodgepole pine and interior spruce, irrespective of the competition intensity and, not surprisingly, the growth rate declined with increasing competition levels for the three species. Conclusions: Our results provide an understanding of how interior Douglas-fir stands will develop over time and information on species interactions that could help forest managers explore different silvicultural options and their effects on individual tree growth in these complex stands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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 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".