Impacts of Sulfur Dioxide Emissions on Lodgepole Pine Growth in Alberta, Canada
Bibliographic record
Abstract
Stressors to trees could alter the relationships between climate and tree growth or affect tree growth directly. Anthropogenic emissions of sulfur dioxide (SO2) are one such stressor that may complicate predictions of future tree growth. Sulfur dioxide may affect tree growth and climate-growth relationships directly by entering through stomata and altering photosynthetic rate, or indirectly by causing soil acidification. I assessed how the growth and climate-growth relationships of lodgepole pine (Pinus contorta) changed with varying SO2 emissions intensity and distance from the source in two areas of Alberta, Canada with sour gas facilities. To assess whether SO2 altered tree response to climate, I determined the monthly climate variables (temperature and precipitation) that were important to growth and then assessed how the growth response of trees to these variables changed between periods of differing emissions and proximity to the source of emissions. Overall, climate had a stronger effect on tree growth in the high SO2 emissions period compared to the periods of no emissions and reduced emissions, and farther from the source of emissions compared to near. Liming in stands near the source of emissions likely reduced the effects of SO2 on tree growth and climate-growth relationships in one area. In the case of previous year late summer precipitation, the commonly observed positive effect on tree growth was reversed only during the high emissions period, near the source of emissions. This could indicate that under heavy acidic deposition, increased precipitation may lead to soil nutrient leaching. After accounting for climate, I found that the effect of SO2 emissions on tree growth was complex. In one study area, tree growth near the source of emissions was more strongly negatively affected by 6-year and 10-year cumulative emissions than by annual emissions, indicating that soil acidification may be more important to tree growth than direct effects of SO2 on photosynthesis. SO2 and other stressors to trees should be considered to develop sustainable forestry management practices in the context of a changing climate and in the development of natural climate change mitigation strategies.
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 | 0.000 |
| 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 | 0.001 | 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".