Carbon Stocks and Fluxes From a Boreal Conifer Swamp: Filling a Knowledge Gap for Understanding the Boreal C Cycle
Bibliographic record
Abstract
The carbon (C) dynamics of boreal coniferous swamps are a largely understudied component of wetland carbon cycling. We investigated the above- and below-ground carbon stocks and growing season carbon dioxide (CO2) and methane (CH4) fluxes from a representative boreal coniferous swamp in northern Alberta, Canada in 2022. Tree inventories, understory vegetation biomass and peat cores were collected across three sub-sites within the broader swamp, with gas flux collars placed in the dominant plant communities present. Alongside the C flux measurements, environmental variables such as water table depth, soil temperature and growing season understory green leaf phenology were measured. Our results show that these boreal coniferous swamps store large volumes of organic C in their biomass and soil (134 kg C m-2), comparable with other wetland and forest types, although 95% of the total C stock at our site was within the soil organic carbon. We also found that understory CO2 and CH4 fluxes indicated that the ground layer of the site is a source of greenhouse gases (GHGs) to the atmosphere across the growing season. However, we did not measure litterfall input, tree GHG fluxes or net primary productivity of the overstory, therefore we are not able to say whether the site is an overall source of C to the atmosphere. This study provides a much-needed insight into the C dynamics of these under-valued wetland ecosystems, and we highlight the need for a coordinated effort across boreal regions to try to improve inventories of C stocks and fluxes.Compared to other wetland types across Canada, boreal conifer swamps do not receive the same level of scientific attention and therefore our understanding of how much carbon they potentially store and release is limited. To fill this knowledge gap, our study measured how much carbon was stored both in the trees and within the soil itself, alongside measurements of carbon uptake and release within a representative conifer swamp wetland in Western Canada. We found that although these wetlands may function similarly to other wetland types, by ignoring them, we are missing out on large amounts of carbon being stored in these systems. We also found that at the ground layer, these sites are a source of carbon, that is, releasing more carbon than is being taken up by the understory moss and plant layer. However, we cannot say if the site overall is a source of carbon to the atmosphere as we were unable to measure other key components of a wetland carbon cycle including litterfall input and the productivity of the trees themselves. Our findings indicate that by not including these wetlands in modeling of carbon dynamics, we are missing a substantial component of boreal carbon cycling processes.Boreal conifer swamp wetlands are an underrepresented wetland class within wetland C cycling measurements and modeling These swamps store large volumes of organic C in their aboveground biomass but most importantly, in their soil organic carbon stock We also found that the ground-layer of this site is a net source of greenhouse gases during the growing season
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".