Counting Carbon: Quantifying Biomass in the McMurdo Dry Valleys through Orbital & Field Observations
Bibliographic record
Abstract
We use correlative field studies and high-resolution multispectral remote sensing data from the WorldView-2 instrument to estimate the abundance of photosynthetically active biomass (photoautotrophs consisting primarily of microbial mats and mosses) in Canada Stream in Taylor Valley, McMurdo Dry Valleys (MDV), Antarctica. In situ field investigations were performed to (1) acquire ground validation targets for atmospherically correcting satellite imagery, (2) derive spectra of “pure” geologic and biological endmembers, (3) estimate photoautotroph cover from remote sensing data, and (4) convert these coverage estimates to biomass using data collected in the field. Our results suggest that, on the morning of 12 December 2018, the Canada Stream system contained more than 3,800 kg of photosynthetically active carbon. Extrapolating our unmixing results to the entirety of the Fryxell basin of Taylor Valley, Antarctica, we model the presence of more than 750,000 kg of photosynthetically active carbon across the landscape and carbon fixation rates roughly equivalent to five hectares of tropical rainforest. The ability to spatially and temporally quantify the amount of photosynthetically active biomass using remote sensing data in the MDV of Antarctica is a revolutionary development that will help elucidate the ecological drivers and environmental responses in this cold desert landscape.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".