Impacts of elevated temperature and CO<sub>2</sub> with varying groundwater levels on seasonality of height and biomass growth of a boreal bioenergy crop (<i>Phalaris arundinacea</i>) — a modeling study
Bibliographic record
Abstract
The boreal aquatic crop reed canary grass (Phalaris arundinacea L., hereafter RCG) is widely cultivated for bioenergy production in northern Europe, where climate change is likely to modify the growing conditions for this species substantially. In this context, we analyzed and modeled the effects of elevated temperature and CO2 together with variable groundwater levels on the seasonal development of height and the accumulation of the aboveground biomass in RCG. For this purpose, RCG plants were grown in autocontrolled environmental chambers over two growing seasons applying a factorial design, including two temperature regimes (ambient and ambient + approximately 3 °C), two carbon dioxide concentrations (ambient and approximately 700 μmol·mol−1), and three groundwater levels (0, 20, and 40 cm below the soil surface). The results showed that elevated temperature was the dominant variable controlling the seasonal course of height development and biomass accumulation, and soil water levels could accelerate or delay these processes. Compared with ambient conditions, elevated temperatures did not accelerate the onset of RCG but made growth cessation occur earlier. This made the growing period shorter and reduced final height and biomass accumulation than other climatic treatments. Elevated CO2 significantly increased height development and biomass accumulation throughout the growing period relative to ambient conditions, whereas no differences occurred regarding the onset, cessation, and duration of growing season. A higher groundwater level increased RCG growth, mainly because of the delay in the timing of the peak growth rate and of the cessation with prolonged duration of growing season compared with low groundwater level. However, the enhanced growth of RCG caused by elevated CO2 may be partly lost due to increasing temperature, which may reduce the availability of soil water and make senescence occur earlier. This will potentially inhibit the growth of RCG under drought conditions. Our results suggested that management of soil water and maintenance of high groundwater levels are key problems with respect to optimizing RCG biomass production under climate change in the boreal conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".