Microbial Substrate Utilization and Vegetation Shifts in Boreal Forest Floors of Western Canada
Bibliographic record
Abstract
Boreal forest soils are highly susceptible to global warming, and in the next few decades, are expected to face large increases in temperature and transformative vegetation shifts. The entire boreal biome will migrate northward, and within the main boreal forest of Western Canada, deciduous trees will replace conifers. The main objective of our research was to assess how these vegetation shifts will affect functioning of soil microbial communities and ultimately the overall persistence of boreal soil carbon. In this study, aspen and spruce forest floors from the boreal mixedwood forest of Alberta were incubated in the laboratory for 67 days without (control) and with the addition of three distinct 13C labeled substrates (glucose, aspen leaves, and aspen roots). Our first objective was to compare aspen and spruce substrate utilization efficiency (SUE) in the case of a labile C source (13C-glucose). For our second objective, addition of aspen litter to spruce forest floor mimicked future vegetation shifts, and we tested how this would alter substrate use efficiency in the spruce forest floor compared to the aspen. Tracking of carbon utilization by microbial communities was accomplished using 13C-PLFA analysis, and 13C-CO2 measurements allowed quantification of the relative contribution of each added substrate to microbial respiration. Following glucose addition, the aspen community showed a greater 13C-PLFA enrichment than the spruce throughout the 67-day incubation. The spruce community respired a greater amount of 13C glucose, and it also had a much lower glucose utilization efficiency compared to the aspen. Following addition of aspen litter, in particular aspen leaves, the aspen community originally showed greater total 13C-PLFA enrichment, although gram positive phospholipid fatty acids (PLFAs) were significantly more enriched in the spruce community. While the spruce community respired a greater amount of the added 13C-leaves, both forest floor types showed comparable substrate utilization efficiencies by Day 67. These results indicate that a shift from spruce to aspen may lead to a greater loss of the aspen litter through microbial respiration, but that incorporation into microbial biomass and eventually into the more persistent soil carbon pool may not be affected.
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 | 0.002 | 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) | 0.000 | 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".