Mechanisms by Which Pre-Commercial Thinning Increases Black Spruce Growth in Different Climates and Soil Types
Bibliographic record
Abstract
In the province of Québec (Canada), pre-commercial thinning (PCT) is a common silvicultural practice applied to young black spruce (Picea mariana (Mill.) BSP) stands. PCT removes some of the competing vegetation and smaller black spruce stems, in order to improve growth rates and reduce forest rotation intervals. It is uncertain whether this positive response in black spruce growth is primarily due to lower competition for resources or to other mechanisms, which may vary according to climate or edaphic conditions. We sampled soils and black spruce needles in PCT-treated and non-treated control plots occurring in two climate regimes, as well as on two contrasting soil parent materials within one of these two climate regimes (i.e., three “site types”). We performed our sampling approximately 20 years after treatment. Paired treatment plots (i.e., PCT vs. control) were replicated at four independent sites in each of the three site types, for a total of 24 plots. Over two consecutive years, we measured stand structural characteristics, indices of soil N fertility, soil microbial activity, indices of soil moisture availability, canopy openness, and foliar characteristics in each plot. In each site type, PCT decreased total basal area but increased radial growth of individual trees. Across all plots, soil N mineralization rates measured in 2016 were positively related to foliar N concentrations of one-year-old needles collected in 2017. Annual precipitation, drainage class, potential evapotranspiration, and climate moisture index all indicated that plots occurring in the drier climate and on glacial till deposits were more prone to summer moisture deficits. Accordingly, PCT increased forest floor moisture only in this site type, which may benefit tree growth. In the wetter climate and on poorly drained soils, however, we found evidence that PCT reduces soil N fertility, presumably by increasing the spread of ericaceous shrubs in the understory. In the dry fertile site type, the range in canopy openness was substantially higher (12–37%) and correlated negatively with tree diameter, suggesting that greater light availability did not improve tree growth. Taken collectively, our data suggest that PCT increases black spruce growth across a broad range of site conditions found in Québec, presumably by lowering intraspecific competition for resources. However, on drier sites, PCT may also benefit trees by increasing soil moisture availability, whereas wetter climates may mitigate the beneficial effect of PCT due to a loss of soil N fertility.
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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) | 0.000 | 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".