Dataset: The SPIKE II experiment - Tracing the water balance
Bibliographic record
Abstract
This repository holds data collected during the “SPIKE II” tracer experiment. The experiment was carried out on a large vegetated lysimeter (2.5 m3) planted with two willow trees (clones) (Salix viminalis) within the EPFL campus (CH), in Switzerland. SPIKE II took place from May 10 to June 29 in 2018. This composite dataset contain stable isotopic composition (δ2H and δ18O) of more than 900 water samples of precipitation, soil water, bulk soil collected at different depths in the soil profile, xylem from willow, and leakage flow in the bottom of the lysimeter. The dataset comprises environmental conditions and water fluxes recorded during the experiment. This includes: meteorological conditions, soil moisture and tension, evapotranspiration in the lysimeters, and tree transpiration recorded at high resolution. Finally, the repository holds tree hydraulic and growth measurements and root traits. Specifically, this dataset contains six files: “METADATA_spikeII.txt” contains specific information about each recorded variable and data point collected throughout the experiment. “spike.hydrometric.II.csv” contains information about meteorological and soil conditions, evapotranspiration fluxes, and tree stem radius, including growth and tree water deficit. "spike.isotopes.II.csv” contains stable isotope data. “fineroots_spike.II.csv” contains root traits information. “events_chronology.csv” summarizes the main events that occurred during SPIKE II. “Figure1_SpikeII_Aerial_Image.PNG” illustrates the location and spatial display of the experiment at the EPFL campus. This data repository was used in the following SPIKE II publications: Nehemy, M. F., Benettin, P., Asadollahi, M., Pratt, D., Rinaldo, A., & McDonnell, J. J. (2021). Tree water deficit and dynamic source water partitioning. Hydrological Processes, 35(1), e14004. doi:10.1002/hyp.14004 Benettin, P., Nehemy, M. F., Cernusak, L. A., Kahmen, A., & McDonnell, J. J. (2021). On the use of leaf water to determine plant water source: A proof of concept. Hydrological Processes, 35(3), e14073. doi:10.1002/hyp.14073 Benettin, P., Nehemy, M. F., Asadollahi, M., Pratt, D., Bensimon, M., McDonnell, J. J., & Rinaldo, A. (2021). Tracing and closing the water balance in a vegetated lysimeter. Water Resources Research, 57, e2020WR029049. doi:org/10.1029/2020WR029049 For any further inquiry, please contact Magali Nehemy or Paolo Benettin. We thank Kim Janzen for assistance with laser and mass spec analysis. We thank the Laboratory of Ecohydrology at EPFL (ECHO/IIE/ENAC/EPFL) for assistance throughout the experiment. We also thank Pierre Queloz and Scott Allen for precious help, Gabriel Cotte and Torsten Vennemann from University of Lausanne (CH) for the collection and analysis of atmospheric vapor samples. This research was supported by the American Geophysical – Horton Research Grant 2019 awarded to MFN, an NSERC CREATE in Water Security and an NSERC Discovery Grant to JJM, AR and PB thank ENAC school at EPFL for financial support and acknowledge the Swiss National Science Foundation grant number CRSII5\_186422.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.031 |
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".