An investigation into the contrasting growth response of lodgepole pine and white spruce to harvest-related soil disturbance
Bibliographic record
Abstract
Losses in forest productivity through poor soil management are typically evaluated by changes in crop production, but conflicting growth responses among co-occurring species can challenge criteria for sustainability. In this study, we evaluate species response to compaction and organic matter removal by contrasting the growth and foliar attributes at age 20 of lodgepole pine (Pinus contorta Dougl. ex Loud.) and hybrid white spruce (Picea glauca × engelmannii (Moench) Voss) in sub-boreal forests of central British Columbia. Bole volume increment was stable for lodgepole pine, averaging a 6 % difference across treatments. White spruce, in contrast, often had large growth increases on forest floor retained – compacted plots (average of 63 % gain) but reductions in productivity on the forest floor removed – compacted plots (40 % decline). Foliar nitrogen concentrations converged across treatments for both species, despite the removal of over 50 % of the site N capital. Some key differences in species traits were suggested by foliar δ15N, attributed to deeper rooting of pine, and foliar δ13C, indicating possibly higher CO2 assimilation potential for spruce. The implication is that standard metrics of sustainable forestry are contingent upon tree autecology and that comprehensive assessments of land management require a measure of collective species response.
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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 | 0.000 |
| 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 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".