A northward range shift of sugar maple (Acer saccharum) in Eastern Canada should reduce soil carbon storage, with no effect on carbon stability
Bibliographic record
Abstract
Climate change is shifting the home range of sugar maple (Acer saccharum Marsh.) northward, onto the southern range of balsam fir (Abies balsamea (L.) Mill.). Such a shift from coniferous to deciduous forests will result in more labile tree litter, potentially decreasing soil organic carbon (SOC) storage in the forest floor. However, microbial processing of deciduous litter may be more efficient, leading to more stable SOC as mineral-associated organic matter (C-MAOM) in the mineral soil. To test these hypotheses, we surveyed 15 stands of each tree species along the sugar maple–balsam fir ecotone in Eastern Canada. In each of the 30 stands, we dug three soil pits and measured SOC stocks in the forest floor and across five mineral soil depths. Mineral soil samples were incubated 51 weeks and monitored for CO2 emission rates, to quantify the bioreactive SOC pool. We also derived two indices of microbial SOC processing based on δ13C signatures and assessed the proportion of C-MAOM at each soil depth. SOC stocks were 21% lower in sugar maple than in balsam fir stands, mainly because of thicker forest floors in the latter. Soil CO2 emissions were higher in samples from sugar maple stands during the first 10 weeks of the incubation, but higher in samples from balsam fir stands thereafter. Consequently, the bioreactive SOC pool did not differ between tree species. Microbial SOC processing was higher under sugar maple than under balsam fir in only a subset of stands occurring in one region. Likewise, the effect of tree species on C-MAOM was significant in only one region, but contrary to expectations (i.e. balsam fir > sugar maple). We conclude that a northward shift of sugar maple will reduce SOC storage but will not increase SOC stability in the mineral soil, potentially creating positive feedback on global warming.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".