Lumber recovery, a leaf area model, and water use in response to commercial thinning, for plantation grown black spruce (Picea mariana [Mills] B.S.P.) / by Steven M. Young.
Bibliographic record
Abstract
Three black spruce (Picea mariana [Mills] B.S.P.) plantations (Airstrip, Boom Lake and Tyrol Lake), in northwestern Ontario, with varied stand densities (2806 stems ha[superscript -1], 2285 stems ha[superscript -1], and 3578 stems ha[superscript -1], respectively) and site indices (11.8 m, 13.3 m, 10.9 m, respectively) were studied to determine lumber properties and yield and to develop a model to predict leaf area. The Boom Lake site was also studied to assess the impacts of site disturbance and residual tree damage from commercial thinning on tree water use. \nWith respect to lumber recovery, all three sites produced over 87% No. 2 and Better grades lumber. Wane and skip were the two most prominent defects causing lumber downgrades. The lowest quality site with the highest stand density produced significantly stronger (modulus of rupture, MOR) and stiffer (modulus of elasticity, MOB) lumber than either the best quality site with a lower stand density or the medium quality site with a similar stand density. The best site with the lowest stand density also produced significantly stronger and stiffer lumber than the medium site with higher stand density. Lumber sawn from log sections taken from below the live crown were significantly stronger but not significantly stiffer than lumber sawn from logs from within the live crown. There were no significant differences in bending MOB and MOR between visual grades. Economy grade lumber was denser than the other grades and had a smaller average ring width than the Grades No. 1 and No. 2. There were weak negative relationships between average ring width and basic wood density. There were weak positive relationships between basic wood density and MOB or MOR. Three scenarios were examined for relative economic return. Regardless of economic scenario, the Boom site (best site quality) produced the highest value per hectare followed by Tyrol (poorest site \nquality) and then Airstrip. Generally, MSR grading produced the highest value per hectare (maximum $28,000/ha at the Boom site). \nThe model to predict whole tree leaf area was developed from 37 plantation grown black spruce trees collected from all 3 sites. Allometric equations to describe needle weight (W[subscript n]), leaf area (A,) and A[subscript 1]: breast height sapwood area (A[subscript s]) relationships are described. \nSpecific leaf area (SLA, m[superscript 2]/g ) was measured on needles from 4 needle age classes on 4 subsampled branches taken from 3 crown sections of equal length on each of the 37 trees. SLA varied by site, needle age and crown section. SLA of needles from the Airstrip was \nsignificantly larger than those from the Tyrol site, while needle SLA from the Boom site was not significantly different from either. Linear and nonlinear allometric models were built to appropriately scale up to whole tree leaf area based on live branch diameters measured in the field, and compared against trees (9 total, 3 from each site) where the entire crown was collected. Nonlinear models for crown sections 1 (top section) and 2 (middle section) revealed an unbiased predictive ability whereas both linear and nonlinear models showed a general tendency to over predict the needle weight of crown section 3 (bottom section). Nevertheless, a linear model to predict A[subscript 1] from A[subscript s] was developed that showed to no evidence of bias. \nSapflow was measured from May 2007 to August 2008 to assess the impacts of site disturbance and residual tree damage from commercial thinning on tree water use. Twelve black spruce trees were instrumented with thermal dissipation sap flow sensors in the spring following a fall season harvest. Soil resistance to penetration was measured with an Eijkelkamp 06.15.SA model Penetrologger Set. The twelve trees were classified based on damage and adjacency to trails resulting in 4 treatment groups; TD (adjacent to the trail with apparent damage), TN (adjacent to the trail with no damage), ID (away from the trail with apparent damage) \nand IN (away from the trail with no damage). There was no significant difference between the soil resistance to penetration on or between harvest trails. Daily water use (Q[subscript d]) was as high as 20.711 day[superscript -1] and as little as 0.06 1 day[superscript-1]. There were no significant differences detected between treatment groups for diameter at breast height (DBH), height (H), length of live crown (EC), sapwood area (A[subscript s]) or leaf area (A[subscript1]). The TD trees appeared to have the lowest Qd, while the TN trees appeared to have lowest mean sap velocity ( v[subscript s]) and low Qd. Transpiration (Qi) and stomatal conductance (G c) levels appeared to generally be lower for the TN group when compared to other treatment groups. The data suggests that Q, and Gc may not be affected by adjacency to trails and/or mechanical damage in the first year following thinning treatment.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".