Mapping of soil organic carbon and nitrogen in two small adjacent Arctic watersheds on Herschel Island, Yukon \nTerritory
Bibliographic record
Abstract
Permafrost soils are particularly vulnerable to global climate change, and warming air \ntemperatures could turn them from carbon sinks into carbon sources. Estimates of Arctic \ncarbon stocks are still highly uncertain, despite their importance to predict the magnitude of \nCO2 and CH4 release to the atmosphere, a process termed the Permafrost Carbon Feedback. \nBecause most of the Arctic is difficult to access and survey, remote sensing techniques bear the \ncapacity to fill spatial gaps and map the changing landscape at wider scales. Recent studies have \nattempted to use multispectral images, such as Landsat, to estimate soil total organic carbon \n(TOC) and total nitrogen (TN) storage. Yet, most studies worked on a regional to global scale \nand used relatively coarse landscape classes. Since TOC and TN storage is known to be highly \nspatially variable in the landscape, high resolution estimates of TOC and TN storage are \nnecessary to estimate the potential impact of thawing permafrost (and the subsequent release \nof CO2 and CH4) to the atmosphere. This project is one of the first to use high resolution images \n(1.65m GeoEye (4 spectral bands: blue‐infrared), 2m DEM) to predict SOC and TN storage \nwithin different Tundra vegetation classes in a small (3 km²) twin watershed (Ice Creek) on \nHerschel Island, Yukon, Canada. Vegetation classes were based on indicator species and \ngeomorphic disturbance levels. Remote sensing detection accuracy varied strongly between \nclasses. Field based moisture measurements were most strongly correlated with the carbon to \nnitrogen (CN) ratio, TOC and TN (ρ =0.84, ρ =0.74 ρ =0.65, p<0.05). However, slope and the \nnormalized difference vegetation index (NDVI) also had a statistically significant relationship to \nCN and TOC. This suggests that fine scale estimates of carbon and nitrogen stocks are possible \nusing few spectral bands from high resolution images. The active layer of Ice Creek watershed \ncontains 33391 tonnes of TOC and 3635 tonnes of TN, which is lower than the average value \nreported for Herschel Island by the Northern Circumpolar Soil Carbon Database. Carbon and \nnitrogen are not evenly distributed within the watershed. Flat upland terrain and tall erect bush \nareas contained the largest amount TOC and TN. Lowest contents could be found in the steep \nand frequently eroded zones. High carbon accumulation along the stream banks suggests that \nfluvial processes do not remove all the eroded sediments from the watershed. An intensification \nof summer rainfall and warmer temperatures could alter the hydrological patterns of the \nwatershed and current accumulation sites may release more carbon from the catchments to the \nBeaufort Sea. High correlation between soil moisture and TOC and TN contents found in this \nthesis shows that moisture information retrieved from satellite radar data could provide \nadditional information on soil properties. This thesis also shows that detailed studies on \nremobilization of carbon in the catchments and atmospheric losses of carbon are crucial to \nunderstand the role small watersheds play in the face of a changing climate.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".