Sap flow measurements are fundamental to understanding water use in trees and could aid in predicting climate change effects on forest function. Deriving knowledge from such measurements requires empirical calibrations and upscaling methods to translate thermometric recordings to tree water use. Here, we developed a user\uffe2\uff80\uff90friendly open\uffe2\uff80\uff90source application, the Sap Flow Analyzer (SFA), which estimates sap flow rates and tree water use from the heat field deformation (HFD) instruments.
The SFA incorporates four key features to ensure maximum accuracy and reproducibility of sap flow estimates: diagnosis diagrams to assess data patterns visually, regression models implemented to increase accuracy when estimating K (the main HFD parameter), three approaches to upscale sap flow rates to whole\uffe2\uff80\uff90tree water use and visualization of the input parameters' uncertainty. Thirteen participants were given three raw datasets and assigned data processing tasks using the SFA user guide, from estimating sapwood depth to scaling sap flow rates to whole\uffe2\uff80\uff90tree water use to assess the reproducibility and applicability of the SFA.
Participants' results were reasonably consistent and independent of their background in using the SFA, R, or HFD method. The results showed lower variability for high flow rates (SD: mean 1% vs. 10%). K estimates and sapwood depth differentiation were the primary sources of variability, which in turn was mainly caused by the user's chosen scaling method.
The SFA provides an easy way to visualize and process sap flow and tree water use data from HFD measurements. It is the first free and open software tool for HFD users. The ability to trace analysis steps ensures reproducibility, increasing transparency and consistency in data processing. Developing tools such as the SFA and masked trials are essential for more precise workflows and improved quality and comparability of HFD sap flow datasets.
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Exposing a tool to access physical sample and digital data", "description": "The Archive''s soil specimens are invaluable time capsules for assessing temporal changes in soil properties. Physical samples are a basic element for reference, study, and experimentation in research. There is an urgent need for better integrating these physical objects into the digital research data ecosystem, both in a global and in an interdisciplinary context to support scientific reuse. The CREA collection, located at the Experimental Farm of Fagna, Scarperia (FI), stores specimens and associated metadata. It covers all major agricultural and forestry soil landscapes in Italy for organic and mineral horizons. Parameters include water impedance, rooting depth, stoniness, Coarse fraction, particle size, pH, organic carbon, and total carbonates, World Reference Base classification. Part of collected samples was recently received and is temporarily stored unordered. With the present work, a tool was developed to expose both metadata, digital research data, displacement to support FAIR principles. The tool was developed by means of Ms Power BI. The original local Ms Access database was stored on the cloud and connected to the tool to allow automatic updates. Geographic and semantic queries are graphically implemented through drop-down menus and pie charts on administrative units- Soil districts- European Environments- Land use- WRB- and Project. The tool expose data collected by 13 different projects from 1986 to 2017. Contains 13,231 analyzed observations (pedological profiles, minipits, or augerings) for a total of 33,523 samples. Soil properties resulted in ranging for Clay 0.1-93.5 (29,9 average)- Sand 0.0-99.4 (17.9), pH (water) 3.9-9.7 (7.5) - Organic carbon 0.0-53.4 (7.8) - Total carbonates 0.0-91.4 (5.5) for the whole dataset. Textural composition of every Reference Soil Group (24 out of 32) is presented as Bar Histogram. A navigation panel allows to preview the site location and storing collocation. \\nAlthough samples access is restricted, data and storing displacement are exposed to support use of the data and specimen''s reuse. 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