The carbon balance and water use efficiency of an intensively managed forage crop in the Lower Fraser Valley in British Columbia, Canada
Bibliographic record
Abstract
• We report eddy-covariance measured carbon fluxes and the water use efficiency of an intensively managed forage field. • More carbon was removed as harvest than returned as manure, resulting in a net carbon import/export deficit. • Changes in precipitation and soil temperature impacted annual carbon uptake and the effect was modified by harvesting frequency. • Separating ecosystem respiration into heterotrophic and autotrophic components suggested that the individual components of ecosystem respiration may have been affected by harvest. • Crop harvest suppressed gross primary productivity more than evapotranspiration which decreased water use efficiency. Intensively managed grasslands have been found to be either carbon (C) sources or sinks depending on management and climate. This study reports the net ecosystem production (NEP) and latent heat fluxes ( λE ) from a managed forage field at a dairy farm in Agassiz, British Columbia, Canada. The forage crop (ryegrass and tall fescue) was harvested up to 6 times a year. The field received multiple applications of dairy manure slurry and was also fertilized with inorganic nitrogen. Eddy-covariance measurements of NEP were combined with C imports (manure additions) and exports (harvested biomass) to determine the net ecosystem C balance (NECB), and values of gross primary production (GPP) and λE were used to determine water use efficiency (WUE). In terms of environmental controls on NEP, variability of daytime NEP was well described by fitting measured incoming photosynthetically active radiation with a rectangular hyperbolic light-response curve, but variability in nighttime NEP was less effectively described by soil temperature and soil moisture. After accounting for C imports and exports, the NECB of the field was -315 ± 141 and -51 ± 148 g C m -2 y -1 (± indicates the uncertainty range) during the 2020 and 2021 study years, respectively, indicating C was lost from the field and was strongly influenced by C imports and exports relative to NEP. Higher than normal soil moisture and precipitation as well as higher than normal air temperature were both found to suppress GPP and ecosystem respiration ( R e ), but annual NEP was more impacted by soil moisture in the first year (2020) due to its effect of lowering GPP compared to high air temperature (including the 2021 Pacific Northwest heat dome) and low soil moisture in the second year due to their greater impact on R e relative to GPP. Crop harvests were found to substantially reduce both GPP and WUE which suggests that the intensity of management in terms of harvest frequency could be modified to improve long-term C sequestration.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".