Biomass and Carbon Allocation in Chronosequence of White Pine (Pinus strobus L.) plantations in Southern Ontario, Canada
Bibliographic record
Abstract
This study assessed biomass and carbon (C) allocation in a chronosequence of four White pine (Pinus strobus L.) plantation forests planted in 2002 (WPP02), 1989 (WPP89), 1974 (WPP74), and in 1939 (WPP39), in southern Ontario, Canada. A plotbased inventory and destructive tree sampling were conducted in 2004 to assess allocation of oiomass and C in ecosystem components, as well as allometry of tree biomass. Seasonal and annual patterns of litter and branch fall were also determined. Individual tree biomass components as well as sapwood area have strong site specific allometric relationships with tree diameter. Except for foliage biomass, strong single allometric equations could also be obtained across all sites and stand ages. Whereas allometry of individual tree components may be affected by site conditions and stand age, total tree biomass solely depended on tree diameter. This suggests that total biomass of White pine may be predicted from single allometric equations with DBH as input variable across sites and even across regions. Relative partitioning of tree biomass components was strongly related to tree age. Stem biomass gains major importance with increasing tree age at the cost of all other components comprising 69% of total tree biomass after 65 years. Whereas site conditions influenced the absolute amount of biomass and allometry of individual tree components, they did not affect their relative partitioning Only biomass of trees, woody debris, and small roots (2-5mm) showed agerelated patterns by increasing with greater stand age. Increase in tree biomass was highest during the early decades after establishment and after thinning practices. C storage in forest floor was 0.8, 7.5, 5.4, and 12.1 t C ha⁻¹ and C content in mineral soil was 37.2, 33.9, 39.1, and 36.7 t C ha⁻¹ at WPP02, WPP89, WPP74, and WPP39, respectively. Biomass of roots < 5mm was 0.3, 6.0, 8.9, and 7.5 t ha⁻¹ at WPP02, WPP89, WPP74 and WPP39, respectively. Annual litter fall was age independent with 5, 3 and 4 t ha⁻¹ y⁻¹ at WPP89, WPP74, and WPP39, whereas branch fall increased with age and basal area to 0.007, 0.17, and 1.38 t ha⁻¹ y⁻¹ at WPP89, WPP74, and WPP39, respectively. Average total tree biomass was 0.4, 67, 122, and 547 kg per tree with an uncertainty of less than 1, 5, 3, and 1 % at WPP02, WPP89, WPP74 and WPP39, respectively. Belowground to aboveground tree biomass ratio was 0.35, 0.19, 0.14, and 0.17 forWPP02, WPP89, WPP74, and WPP39, respectively, which suggests a considerable amount of C stored in root biomass. Above and below ecosystem C increased with an average rate of 1.9 and 0.5 t C ha⁻¹ y⁻¹ across the chronosequence, reaching 122 and 66 t C ha⁻¹ y⁻¹ respectively at age 65. Total net ecosystem C accumulation between age 2 and 65 was 147 t C ha⁻¹. Inventories limited to stem biomass may underestimate total tree biomass by up to 3 5% and total ecosystem C by up to 62%. Thus, estimations of C storage in forest ecosystems should include all above and belowground C pools, and its accuracy may be improved by predicting total treebiomass with allometric equations related to stand age and tree diameter.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".