Utilising conservative tracers and spatial surveys to identify controls on pathways and DOC exports in an Arctic catchment
Bibliographic record
Abstract
Dissolved organic carbon (DOC) is typically the predominant form of carbon exported from headwater streams, it therefore represents a major carbon export from Arctic catchments. The projected deepening of thaw depth in permafrost regions, due to an increase in air temperature, may have a significant effect on the amount of DOC exported from these systems. However, quantification of the impacts of climate driven changes on DOC export are still highly uncertain. Understanding the processes controlling DOC export is therefore crucial in predicting the potential impact of projected environmental changes. The controls of DOC production and transport are heavily influenced by soil and vegetation, which are highly variable across the landscape. To completely understand these systems information regarding spatial variability of plants, soils and thaw depths must be taken into account. In this study sub-weekly sampling of DOC was undertaken throughout 2014 in a headwater (<1 km2) catchment in the Northwest Territories, Canada. Spatial surveys of soil properties, active thaw depth and normalised difference vegetation index (NDVI) were collected and used in conjunction with conservative stable water isotopes tracers and major ions to understand sources, flow pathways and timing of DOC exports from the catchment. Stable isotope tracers act as fingerprints of water allowing sources and pathways to be assessed. Observations reveal changing DOC concentrations throughout the season as the active layer deepens and the connectivity of the soils to the stream network throughout the catchment increases. Linking the DOC data with the conservative tracer response improves the identification of carbon pathways and fluxes from the soils; preliminary analysis indicates DOC is being delivered via deeper more mineral soils later in the season. The results indicate that the active layer depth has a strong influence on the amount of DOC exported from the system, independent of the amount of carbon stored in these deeper soils.
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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 | 0.002 | 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".