Bibliographic record
Abstract
Abstract. The processes of tree water uptake in karst environments are poorly understood. One of the main challenges to improved understanding is the complex interaction between soil water and bedrock water, especially in systems characterized by rock fractures. While some studies have highlighted the potential importance of fractured bedrock as a water source for plants, few have quantitatively assessed the sources, residence times, and seasonal dynamics of tree water uptake from both soil and rock fracture compartments. Here, we combine stable isotope tracing, a Bayesian mixing model (MixSIAR), and hydrometric monitoring to quantify the contributions and mean residence times (MRT) of soil and rock water accessed by trees across seasons. We use a four-compartment sampling framework that distinguishes between soil water (mobile and bulk) and rock water (fracture and infilled fracture). Our results reveal clear seasonal shifts in plant water sourcing: during the peak rainy season, mobile soil water (mean MRT = 88 days) dominates uptake (mean contribution 41 %), whereas in late growing season, trees increasingly rely on bulk soil water (mean MRT = 95 days, mean contribution 55 %). Strikingly, in early spring, trees in fracture-rich areas exhibit the highest reliance on rock water (mean MRT = 113 days, mean contribution 69 %). During the subsequent early growing season, large trees derive up to 85 % of their water from rock, particularly from soil-filled fractures with apertures >10 mm, which act as transitional reservoirs capable of retaining precipitation for extended periods (MRT = 84–303 days). Trees preferentially access short-MRT sources under wet conditions and shift to longer-MRT pools during dry periods, reinforcing the concept of ecohydrological separation between tightly bound and dynamically recharged water pools. However, this separation is attenuated during periods of high precipitation due to increased hydraulic connectivity and water mixing. This work advances our understanding of vegetation resilience in structurally complex and hydrologically dynamic karst landscapes with important insights for sustainable water resource management under changing climatic 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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.025 | 0.012 |
| Insufficient payload (model declined to judge) | 0.352 | 0.279 |
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".