North American Swamps: What Lies Beneath
Bibliographic record
Abstract
Terrestrial wetlands are a highly significant carbon reservoir in North America. Forested wetlands, or swamps, are an important category of North American wetland and include boreal forested peatlands, swamps dominated by needle-leaved trees including Thuja (cedar), Picea (Spruce), Larix (Tamarack) or Taxodium (bald cypress), swamps dominated by broad-leaved trees or shrubs including Fraxinus (Ash), Ulmus (Elm), or Acer (Maple), as well as mangroves. The Second State of the Carbon Cycle Report estimates that forested wetlands may make up ~55% of the total terrestrial wetland area for North America, although estimates vary considerably due to different mapping conventions and classification systems across national and provincial borders, and also due to the ongoing impacts of land use change. Additionally, that report suggests that forested wetlands contain larger total carbon pools than non-forested wetlands, and that forested wetlands effect 53% of the estimated 123 Tg total wetland annual carbon sink for North America. Uncertainties in the sizes of the forested wetland soil carbon pools continue to be significant due in part to insufficient data on variabilities in carbon densities across diverse swamp types. Further, there are limited data on the rates of vertical accretion of swamp soils and the associated long-term rates of carbon accumulation, needed for better predicting impacts of climate warming on carbon sequestration in swamp soils. We present here a comparative synthesis of swamp soil carbon properties including bulk densities, organic carbon contents, soil thicknesses, rates of vertical accretion and rates of long-term carbon accumulation, from >200 swamp sites. We compare these properties for broad-leaf swamps (including mangroves), needle-leaf swamps, mixed swamps, and shrub-dominated swamps, and also compare across North American Ecoregions. The results show significant variability across peat-forming and mineral swamps, and indicate rates of carbon accumulation in some swamp types similar to those of northern bogs and fens.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".