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Record W4220942420 · doi:10.5194/egusphere-egu22-1196

Evidence that a northward range shift of sugar maple (Acer saccharum Marsh.) causes a net release of CO2 from soil

2022· preprint· en· W4220942420 on OpenAlexaffabout
Gabriel Boilard, Robert L. Bradley, Daniel Houle

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsEnvironment and Climate Change CanadaUniversité de Sherbrooke
Fundersnot available
KeywordsMapleBalsamDeciduousSoil carbonAbies balsameaPlant litterUdic moisture regimeEnvironmental scienceEdaphicAgronomyChemistryBotanyEcologySoil waterEcosystemBiologySoil science

Abstract

fetched live from OpenAlex

Climate change is expected to shift the home range of sugar maple (Acer saccharum Marsh.) northward, thereby encroaching onto the southern range of present-day balsam fir (Abies balsamea (L.) Mill.) forests. Such a shift from coniferous to deciduous forest stands will affect several edaphic properties and potentially modify soil organic carbon (SOC) storage and stability. For example, the more labile deciduous litter should decompose faster than coniferous litter, potentially resulting in lower SOC storage in forest floors. On the other hand, labile deciduous litter may result in a greater microbial turnover of SOC, leading to more stable SOC in mineral-associated organic matter (C-MAOM) in the subsoil. To test these hypotheses, we surveyed 30 mature forest stands in three regions along the sugar maple–balsam fir ecotone in southern Quebec, Canada. We dug three soil pits in each stand and measured SOC stocks in the organic forest floor as well as across five depth increments (0-5, 5-10, 10-20, 20-30 and 30-40 cm) in the mineral soil. We incubated mineral soil samples from each depth for 51 weeks and monitored CO2 emissions rates, from which we quantified the bioreactive SOC pool. We derived two indices of microbial turnover of SOC at different soil depths based on δ13C signatures. Finally, we used a wet sieving procedure to assess the proportion of C-MAOM at each soil depth. Results revealed that SOC stocks were 27% greater in balsam fir than in sugar maple forests. Most of this difference was attributable to the thicker forest floors under balsam fir, in accordance with slower litter decomposition rates. CO2 emission rates in the first 10 weeks of incubation were higher in soil samples collected under sugar maple; thereafter, CO2 emission rates were higher in soil samples collected under balsam fir. As a result, the bioreactive SOC pool over the course of 51 weeks did not differ significantly between stand types. We found significant region × stand type interactions on both indices of microbial turnover as well as on the proportion of C-MAOM in the mineral soil. More specifically, only in one region was microbial turnover higher under sugar maple than under balsam fir. Likewise, the effect of stand type on the proportion of C-MAOM was significant in only one region, and this effect was contrary to expectations (i.e. balsam fir > sugar maple). We ascribe this unexpected result to the presence of earthworms, which we only found in sugar maple stands in this region. Although we did not find generalizable effects of stand type on SOC turnover and stability, we did find significant generalizable patterns of decreasing SOC bioreactivity, increasing microbial turnover and increasing C-MAOM with increasing soil depth. Taken collectively, our results suggest that a northward shift of sugar maple will cause a net release of CO2 to the atmosphere and potentially create a positive feedback on global warming.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.697

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.052
GPT teacher head0.244
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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