Interannual variations of evapotranspiration and its response to different drought types in a boreal larch forest in China
Bibliographic record
Abstract
Assessing evapotranspiration (ET) responses to droughts is of great significance for understanding the exchanges of water, carbon, and energy in a changing environment. However, the interannual variation (IAV) of ET and its environmental controls under different drought types in China’s boreal forests remain poorly understood. In this study, we integrated eight years of eddy covariance measurements and environmental observations during growing seasons to evaluate the IAV of ET and the control mechanisms of ET under no drought, atmospheric drought, soil drought, and combined drought conditions. Over the study period, the IAV of ET was relatively small with a coefficient of variation (CV) of 8.6%, whereas the evapotranspiration/precipitation (ET/P) ratio exhibited a great fluctuation with a CV of 24.6%, corresponding to the higher variability in P (CV of 31.2%). Atmospheric drought significantly increased ET by 18.05% than no drought condition, whereas soil drought significantly reduced ET by 19.02%. However, ET showed no significant difference between no drought and combined drought due to the constraint role of low soil water content (SWC) in high atmospheric demand during the combined drought. The indirect and direct driving effects of atmospheric conditions, such as net radiation (Rn), air temperature (Ta), and vapor pressure deficit (VPD) were the key to ET responses to different drought types. Furthermore, precipitation rather than energy demand or canopy greenness had a greater impact on the IAV of ET. Interestingly, the precipitation regime with larger rainfall events (> 15 mm/day) was mostly related to the IAV of ET. These findings enhance our understanding of the responses of ET to multiple drought types and the intricate relationship between ET and P, highlighting that precipitation patterns due to climate change could potentially increase the complexity of environmental control on ET variations in boreal forests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".