Peat swamp hydrological connectivity and runoff vary by hydrogeomorphic setting: Implications for carbon storage
Bibliographic record
Abstract
Abstract Despite their importance in carbon cycling and catchment runoff dynamics, the hydrology of temperate peat swamps in response to changing hydrometeorological conditions is largely understudied. We examined the importance of hydrogeomorphic settings in controlling hydrological connectivity and runoff in a temperate peat swamp in southern Ontario, Canada over two consecutive growing seasons with contrasting conditions (dry and wet years). We chose two different small‐scale hydrogeomorphic settings to investigate: (i) a site with strong wetland‐stream interactions (i.e., an unconfined stream channel; unconfined) and (ii) a site with limited wetland‐stream interactions (confined). During the wet year, the confined site exhibited a consistently gaining stream, maintaining lateral hydrological connectivity and yielding high runoff ratios, while during the dry year, the confined site lost water and experienced low runoff ratios during storm events. Overland flow at the unconfined site maintained a longitudinal hydrological connectivity delivering water to its sub‐catchment outflow, as reinforced by hydrochemical observations. This connectivity was maintained in the wet year but ceased in the dry year despite consistent upstream sub‐catchment water inflow due to high depression storage. Runoff ratios were reduced because of this hydrological disconnection. We highlight the importance of small‐scale hydrogeomorphic setting on peat swamp carbon storage as facilitated by the variation of within‐site hydrological connectivity and runoff, which also has important implications for downstream water quality. The unconfined site maintained a higher water table position in both years and has much greater peat carbon stocks. We suggest peat swamp channelization either naturally or through drainage decreases carbon stocks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".