Site preparation severity influences lodgepole pine plant community composition, diversity, and succession over 25 years
Bibliographic record
Abstract
Lodgepole pine (Pinus contorta var. latifolia Engelm.) ecosystems of central British Columbia face cumulative stresses, and management practices are increasingly scrutinized. We addressed trade-offs between “light-on-the-land” versus more aggressive silvicultural approaches by examining plant communities and indicator species (non-natives, berry producers, epiphytes, mycotrophs, pine rust alternate hosts) across a gradient of five or six site preparation treatments at the Bednesti trial (established 1987). We tested whether more severe site preparation (i) caused plant community composition to diverge from a 35- to 46-year-old reference forest, (ii) accelerated succession by hastening crown closure, or (iii) delayed succession by promoting seral species. Nonmetric multidimensional scaling (NMDS) ordination showed all treatments converging toward the reference forest composition. At 10 years, succession was incrementally delayed by more severe treatments; at 25 years, only burned windrows were still delayed. Mixed-effects models based on site preparation severity were better than crown closure models for 11 of 13 variables tested, suggesting that mostly belowground processes drive succession in these infertile ecosystems. Invasive hawkweeds persisted on all treatments at 25 years. Limited, contradictory data did not support using mechanical or fire treatments to reduce alternate hosts of pine stem rusts. Long-term trials such as Bednesti highlight the need for ecosystem-specific strategies and diverse approaches to accommodate conflicting benefits and risks of disturbance in forests.
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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 | 0.001 |
| 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 | 0.001 | 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".