Identifying wetland types of ice-free intervals prior to the Last Glacial Maximum: first insights into pre-LGM carbon dynamics from the Hudson Bay Lowlands, Canada
Bibliographic record
Abstract
The Hudson Bay Lowlands (HBL) of central Canada are characterized by expansive complexes of patterned forested and open bog, rich and poor fen, swamp, and marsh ecosystems. These systems have accumulated thick Holocene peat deposits, making them globally significant carbon (C) stocks. However, the magnitude of peatland C sinks, and their potential to be C sources through methane release, are sensitive to variability in temperature and moisture balance, creating uncertainties around responses to projected climate change. Periods of significant ice retreat pre-dating the Last Glacial Maximum (LGM), including interglacials and interstadials, provide opportunities to investigate wetland C dynamics under different boundary conditions including warmer and/or drier climatic conditions. Despite palynological and paleontological evidence that wetlands existed in the HBL region during Late Pleistocene periods of ice retreat, their C dynamics are poorly understood. This is in part because the available non-glacial records are mainly preserved in fluvial contexts, are often overlain by massive glacial deposits, contain both organic and mineral fractions, and are thus not readily comparable to in situ peatland records of Holocene age that are used to measure and model apparent rates of net C accumulation. Nevertheless, these non-glacial intervals preserve fossil pollen and macrofossil assemblages, and thus, have potential to contribute new insights into peatland C dynamics during ice-free intervals pre-dating the LGM. In this study, we compare fossil pollen assemblages and quantitative paleoclimate reconstructions from pre-LGM sections in the HBL, situated in the heart of glaciated North America to reconstruct paleoenvironments. We then present an approach to extract peatland C information from these deposits by identifying the presence of specific peatland types using combined modern and fossil pollen assemblages and a random forest algorithm. Using the modern analogs, assigned peatland types can then be linked to C accumulation and methane flux regimes. Ordinations of available samples indicate the presence of several distinct wetland types including Sphagnum-dominated bogs, wet fen environments in both open and forested contexts, riparian or stream bank environments with relatively better drainage, thicket swamps and marshes with Typha. These wetland types can then be used to make initial inferences on potential peat C dynamics during ice-free intervals pre-dating the LGM.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".