Pond hydrology and dissolved carbon dynamics at Polar Bear Pass wetland, Bathurst Island, Nunavut, Canada
Bibliographic record
Abstract
ABSTRACT A large number of wetlands, lakes and ponds exist in northern Canada, Alaska and Siberia, and the hydrologic and ecological processes in these water bodies are now responding to a changing climate. A large wetland, Polar Bear Pass (PBP), situated in the middle of Bathurst Island is considered to be one of the most important ecological sites in the region. Numerous ponds exist at PBP and are connected to their surrounding watersheds by streams and groundwater inflow, receiving varying amounts of water and nutrients. In 2008 and 2009, the representative hydrology of typical ponds at PBP along with their quantity of dissolved organic and inorganic carbon (DOC and DIC, respectively) was evaluated. Pond DOC and DIC loads and composition differ depending on the presence or absence of one or more hydrologic linkages that a pond has with its catchment. Elevated DOC loads were mostly of terrestrial origin and occurred in ponds receiving meltwater from snowbeds and discharge from hillslope creeks. The seasonal shift in connectivity of a pond to its catchment was critical in controlling DOC loads and concentrations. The frequency and duration of summer precipitation had a strong control on pond hydrologic connectivity and elevated the contribution of terrestrial DOC from wetland to ponds, especially ones that were hydrologically connected. The estimated DOC yields from wet meadow catchments highlight their importance as a source of carbon to pond ecosystems downstream. These wetland areas and ponds are potentially significant pools of carbon and are sensitive to future climate changes in permafrost‐dominated environments. Copyright © 2012 John Wiley & Sons, Ltd.
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 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) | 0.005 | 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".