Biomass and nutrient distribution in two old growth forest ecosystems in south coastal British Columbia
Bibliographic record
Abstract
The distribution of the above-ground biomass and macronutrient content of the trees were studied on two sample plots in south coastal British Columbia, near Vancouver. The plots differed in elevation (4,600 and 2,200 feet; 1,500 and 700 m), in soil type and depth. Tree age was similar in both plots, ranging from 150 to 530 years. The tree cover on the high elevation plot consisted of Tsuga mertensiana (Bong.) Carr. (mountain hemlock) and Abies amabilis (Dougl.) Forbes (Pacific silver fir) while the lower elevation plot was occupied by Tsuga heterophylla (Raf.) Sarg. (western hemlock), Thuja plicata D. Don (western red cedar) and Chamaecy- paris nootkatensis (D. Don) Spach (yellow cedar). Twenty-four trees were sampled to determine the biomass and nutrient content of wood, bark, branches, twigs, foliage and cones. Another nine trees were sampled for the biomass and nutrient content of wood and bark only. Multiple regression analysis was used to establish the relationship between d.b.h., tree length, crown length and biomass of the various tree components. The regression equations obtained were used to estimate the total biomass of wood, bark, branches, twigs and foliage contained in the trees on each of the sample plots. The data thus obtained were combined with data on chemical concentration and used to estimate the distribution of macronutrient elements in different above-ground biomass components of the stands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".