Drivers of Holocene Carbon Uptake and Release in Peatlands of the Hudson Bay Lowlands, Canada
Bibliographic record
Abstract
Northern peatlands are a key component of the terrestrial carbon cycle, acting as both a source and sink of carbon. Therefore, to predict impacts from anthropogenic climate change and create effective land management policies, constraining how environmental factors impact peatland carbon fluxes is critical, especially in peatland-rich regions such as the Hudson Bay Lowlands (HBL), Canada. This thesis aims to understand how local-scale factors impacted Holocene carbon uptake and release in the HBL using paleoecological and geochemical analyses of radiocarbon-dated peat cores. Paleoecological analyses of a site on the southern HBL margin demonstrate that landscape position controls local hydrology and can subsequently limit Holocene carbon accumulation rates (CARs). This record also demonstrates a summer bias in temperature and validates pH reconstructions from lipid biomarker proxies. Paired treed fen and bog sites from the western HBL margin show markedly high carbon masses owing to deep peat accumulation with old initiation ages. Mean testate amoeba trait values reflect hydrology and food web structure and are also influenced by vegetation shifts and peatland type. Further, mixotrophic taxa are not related to higher millennial-scale CARs, suggesting a minor role for their primary production in long-term carbon storage. The above records were synthesized with other hydrological records derived from testate amoebae across the HBL to reconstruct paleo-methane fluxes via a linear regression model developed from modern relationships between methane fluxes and water table depths. Land availability controlled by glacial isostatic adjustment was an important control on Holocene emissions when fluxes were scaled to regional emissions. The combined hydrological reconstructions also suggest that peatlands were drier under warmer Middle Holocene conditions. A charcoal record collected from the western HBL margin supports drier conditions, as warmer Middle Holocene conditions were related to higher fire frequency. Although higher fire frequency did not have a significant impact on millennial-scale CARs, carbon loss from combustion was potentially doubled, which has implications for atmospheric carbon budgets. Overall, this thesis advances our understanding of the complex interplay between climate and local processes in long-term carbon dynamics that is of fundamental importance for conservation priorities and constraining future carbon emissions.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".