Estimates of critical loads and exceedances of acidity and nutrient nitrogen for mineral soils in Canada for 2014–2016 average annual sulfur and nitrogen atmospheric deposition
Bibliographic record
Abstract
The steady-state simple mass balance model was applied to natural and semi-natural terrestrial ecosystems across Canada to produce nation-wide critical loads of acidity (maximum sulfur, CL max S; maximum nitrogen, CL max N; minimum nitrogen, CL min N) and nutrient nitrogen (CL nut N) at 250 m resolution. Parameterisation of the model for Canadian ecosystems was considered with attention to the selection of the chemical criterion for damage at a site-specific resolution, with comparison between protection levels of 5 % and 20 % growth reduction (approximating commonly chosen base-cation-to-aluminum ratios of 1 and 10, respectively). Other parameters explored include modelled base cation deposition and site-specific nutrient and base cation uptake estimates based on North American tree chemistry data and tree species and biomass maps. Critical loads of acidity were estimated to be low (e.g., below 500 eq. ha −1 yr −1 ) for much of the country, particularly above 60° N latitude, where base cation weathering rates are low due to cold annual average temperature. Exceedances were mapped relative to annual sulfur and nitrogen deposition averaged over 2014–2016. Results show that under a conservative estimate (5 % protection level), 10 % of Canada's protected and conserved areas in the study area experienced exceedance of some level of the soil critical load of acidity, while 70 % experienced exceedance of the soil critical load of nutrient nitrogen.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".