Assessing the effects of resource extraction and climate-related disturbances on the growth of Picea mariana (Mill.) B.S.P. (Pinaceae) in boreal peatlands in the Hudson Bay Lowland, Canada
Bibliographic record
Abstract
The peatland-dominated Hudson Bay Lowland (HBL) is facing increasing pressures from climate change and resource extraction operations. Despite the potential for widespread changes in water availability to occur, information about hydrological and ecological feedbacks in the HBL remains limited. This study, located near the De Beers Victor diamond mine ~90 km west of Attawapiskat (Ontario, Canada), investigates the influence of mine dewatering activities (‘pumping’) and climatic variability on the radial growth of black spruce (Picea mariana (Mill.) B.S.P.) trees. Tree stem disks were collected from stunted black spruce trees in one reference (n=25) and three mine-affected bogs within the area of dewatering influence (n=41) along a transect of variable underlying aquitard (marine sediment) thickness. Pumping was not found to have influenced annual ring-width indices (RWIs) in mine-affected areas with either thick (6 to >18 m) or thin (< 5m) underlying marine sediment, as these sites showed similar growth patterns to the reference site during the period of mine operation. Analyses of the influence of climate on tree radial growth (1970–2018) using 20-year moving windows showed significant (p < 0.05) positive correlations (Pearson R) between residual RWI and mean monthly air temperature, including June (1979–2007 excluding the window of 1986–2006), August (1989–2018) and September (1984–2009). In addition, for the period during which ground temperature data were available (2011–2018), significant negative correlations were detected between residual RWI and mean monthly soil temperatures in late winter and early spring. The above relationships highlight the importance of both growing and shoulder season conditions for tree growth. As the HBL continues to respond to climate change, the growth response and potential proliferation of black spruce will undoubtedly influence the water balance and hydrological function of bog peatlands in the region.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".