Biodiversity-Based Empirical Critical Loads of Nitrogen Deposition in the Athabasca Oil Sands Region
Bibliographic record
Abstract
Anthropogenic nitrogen (N) emissions can have considerable effects on terrestrial ecosystems, with chronic N deposition leading to changes in plant species composition. The Athabasca Oil Sands Region (AOSR) represents a large point source of N emissions, which has prompted concern for surrounding habitats. The objective of this study was to determine the relative importance of N deposition as a driver of plant species community composition against bioclimatic and soil chemical variables. Further, we sought to identify community thresholds in plant species composition across a N deposition gradient. This assessment was performed for 46 Jack pine (Pinus banksiana Lamb.)-dominant forest sites surrounding the AOSR spanning Alberta and Saskatchewan. In total, 35 environmental variables were evaluated using redundancy analysis (RDA), followed by gradient forest analysis applied to plant species abundance data. Soil chemical variables accounted for just over 26% of the total explainable variation in the dataset, followed by bioclimatic variables (19%) and deposition variables (5%), but joint effects between variables also explained a significant portion of the total variation (p < 0.001). Total deposited nitrogen (TDN), and sulphur (TDS) along with bioclimatic and soil chemical variables, were identified as important variables in gradient forest analysis. A single, definitive threshold across TDN was identified at approximately 5.6 kg N ha−1 yr−1 (while a TDS threshold was found at 14.4 kg S ha−1 yr−1). The TDN threshold range was associated primarily with changepoints for several vascular species (Pyrola asarifolia, Pyrola chlorantha, Cornus canadensis, and Arctostaphylos uva-ursi) and bryophyte and lichen species (Pleurozium schreberi, Vulpicida pinastri, and Dicranum polysetum). These results suggest that across Jack pine-dominant forests surrounding the AOSR, the biodiversity-based empirical critical load of nutrient N is 5.6 kg N ha−1 yr−1.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".