Atmospheric aridity and soil moisture fluctuations regulate GPP in a temperate peat bog
Bibliographic record
Abstract
Despite only covering ~3% of the land area, peatlands store more carbon (650 gigatons (Gt) of C) than global terrestrial vegetation (409 GtC). However, this C is vulnerable to climate warming and drainage. Plants mediate land-atmosphere C exchange and its coupling with water by regulating stomatal opening and root water intake during droughts. Stomatal regulation and photosynthesis are dependent on soil water content (SWC), air temperature (Tair), and vapour pressure deficit (VPD). However, the role of SWC on gross primary productivity (GPP) is still not straightforward, as evidenced by several contradictory literature. Considering this, we asked whether there is a threshold at which SWC drawback starts to regulate GPP in a peat bog in Vancouver, Canada. We used weekly time step eddy covariance data spanning five years (2016-2020). Our analysis suggests that stomatal regulation in response to increased VPD caused a reduction in GPP during the 2016 drought (~2.5gC m-2 day-1). On the other hand, an absence of stomatal regulation in 2017 and 2018 (to maximise C assimilation) following the initial drought caused the peat surface to dry out in 2019. This resulted in SWC regulating GPP more than VPD by 2019. We report a SWC threshold of 82.5% (-8 cm water table depth), below which it starts to regulate GPP at this site. The interaction between energy and water limitations on GPP is expected to intensify with the projected increase in the frequency of drought events across the northern hemisphere.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".