Annual carbon fixation in terrestrial populations of <i>Nostoc commune</i> (Cyanobacteria) from an Antarctic dry valley is driven by temperature regime
Bibliographic record
Abstract
Abstract Nostoc commune Vaucher (a cyanobacterium) is a very conspicuous terrestrial primary producer in Victoria Land, continental Antarctica. Because polar ecosystems are considered to be especially sensitive to environmental changes, understanding the environmental constraints on net carbon (C) fixation by N. commune is necessary to determine the effects of environmental changes on the ecological functioning of ice‐free areas of the continent. A model describing net C fixation in terrestrial populations of N. commune in an Antarctic dry valley was constructed using field and laboratory measurements in which N. commune colonies were exposed to different combinations of incident irradiance (400–700 nm), temperature, and degree of desiccation. For desiccated N. commune mats with water content ≤ 30% saturation, net C fixation was highly variable between replicates and could not be modelled. However, for colonies at > 30% saturation, rates of net C fixation and dark respiration depended strongly on irradiance and temperature. Net C fixation reached a maximum rate of 21.6 μg C m − 2 s − 1 at irradiance of approximately 250 μmol m − 2 s − 1 and the optimum temperature of 20.5 °C. Agreement between predicted short‐term net C fixation and field and laboratory measurements allowed estimation of total seasonal fixation, using previously published environmental data. Annual net C fixation was estimated in the range 14.5–21.0 g C fixed m − 2 Nostoc mat, depending on year/season. Estimates for different seasons correlated with thermal time (accumulated hours above 0 °C during the year) rather than irradiance, in contrast to communities in local lacustrine environments, where irradiance is the main driver of primary productivity. In the terrestrial habitat, N. commune appears to compromise between an ability to capitalize on short periods of higher temperature and efficient utilization of lower irradiance at low temperature. The relationship between thermal time and net annual C fixation by N. commune is strongly linear.
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 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 | 0.000 | 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 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".