Heat tracer-based sap flow methods for tree transpiration measurements: a mini review and bibliometric analysis
Bibliographic record
Abstract
Accurate measurement of plant transpiration is critical to gaining a better understanding of plant water use and exploration of the influence of plants on regional and even global climate. Heat tracer-based sap flow (HTSF) techniques are currently the dominant method to estimate plant transpiration at the individual plant level. However, the majority of current research focuses on specific applications or the evaluation of the method itself, and there is a lack of an overall analysis of HTSF methods. The objectives of this study were: (i) to briefly review the theories and categories of the various HTSF methods, and (ii) to undertake a bibliometric analysis of the use of HTSF methods in measuring plant transpiration. Each HTSF method is described mathematically and their application and pros and cons are briefly discussed. A bibliometric analysis was conducted using 3964 papers published between 1992 and 2020 archived in the Web of Science core collection. The analysis identified publication trends, the most productive authors, organizations, and countries, as well as the most utilized HTSF method (i.e., thermal dissipation) and journals in which these papers were published. In addition, world distribution maps of the use of HTSF methods and tree species measured were drawn based on 741 selected publications with in situ measurements.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.025 |
| 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) | 0.002 | 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".