Spring photosynthesis in a cool temperate bog
Bibliographic record
Abstract
Abstract In northern ecosystems, the onset and growth of spring photosynthesis may have an important influence on the annual carbon (C) budget, yet the controls have not been clearly identified, especially for peatlands. We used a 5‐year set of daily carbon dioxide (CO2) exchange measurements derived from an eddy covariance tower located at Mer Bleue, an ombrotrophic bog near Ottawa, Canada, from March to May [day‐of‐year (DOY) 60–150], 1999–2003. We used half‐hourly measured net ecosystem exchange minus modelled ecosystem respiration to estimate daily photosynthesis, as gross ecosystem production (GEP). The onset of GEP in each year was closely related to the thinning and disappearance of the snow cover, occurring between DOY 86 and 101. GEP increased during the spring, reaching 10‐day average values of between 5 and 9 g CO2 m−2 day−1 by the end of May. This increase was initially associated with moss activity (Sphagnum and Polytrichum), followed by the evergreen shrubs. Peat temperatures in the rooting zone (10–20 cm depth) and increases in shrub leaf nitrogen and chlorophyll a concentrations contributed to this rapid increase in GEP. Examination of moderate‐resolution imaging spectroradiometer (MODIS) images over several years revealed that the temporal resolution (16‐day composites) was inadequate to capture the onset of GEP but estimates of gross primary productivity and photosynthesis from MODIS 8‐day composites for the most part followed the pattern and magnitude of CO2 exchange observed at the tower.
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 | 0.001 | 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) | 0.000 | 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".