Nutrient dynamics of the southern and northern BOREAS boreal forests
Bibliographic record
Abstract
The objective of this study was to compare nutrient concentration, distribution, and select components of nutrient budgets for aspen (Populus tremuloides), jack pine (Pinus banksiana), and black spruce (Picea mariana) forest ecosystems at the BOReal Ecosystem Atmosphere Study (BOREAS), southern and northern study areas near Candle Lake, Saskatchewan and Thompson, Manitoba, Canada, respectively. The vegetation (excluding fine roots and understory) in the aspen, black spruce, and jack pine stands contained 70-79%, 53-54%, and 58-67% of total ecosystem carbon content, respectively. Soil (forest floor and mineral soil) nitrogen (N), calcium (Ca), and magnesium (Mg) content comprised over 90% of the total ecosystem nutrient content, except for Ca and Mg content of the southern black spruce stand and Ca content of the southern aspen stand which were less than 90%. Annual litterfall N content was significantly greater (p < 0.05) for trembling aspen (30-41 kg N ha-1 yr-1) than for jack pine (5-10 kg N ha-1 yr-1) or black spruce (6-7 kg N ha-1 yr-1), and was generally greater, but not significantly, for the southern than for the northern study area. Aboveground net primary production was positively correlated (R2 = 0.91) to annual litterfall N content for the BOREAS forests, and for all boreal forests (R2 = 0.57). Annual aboveground nutrient (N, Ca, Mg, and K) requirements (sum of the annual increment of nutrient in foliage, branches, and stems) were significantly greater (p < 0.05) for trembling aspen than for jack pine or black spruce forests. Annual aboveground N requirements ranged from 37-53, 6-14, and 6-7 kg N ha-1 yr-1 for trembling aspen, jack pine, and black spruce forests, respectively. The greater nutrient requirements of deciduous than evergreen boreal forests was explained by a greater annual production of biomass and lower use efficiency of nutrients. Nutrient cycling characteristics of boreal forests were influenced by climate and forest type, with the latter having a greater influence on litterfall N, annual nutrient requirements, nutrient mean residence time, and nutrient distribution.
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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 | 0.000 |
| 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) | 0.000 | 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 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".