Global transpiration data from sap flow measurements: the SAPFLUXNET database

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Abstract

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, textlessa href="https://sapfluxnet.creaf.cat/" target="blank"textgreaterhttps://sapfluxnet.creaf.cat/textless/atextgreater). We harmonised and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well-represented (80thinsp;. The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50thinsp; years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56thinsp;0thinsp; allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks and remote sensing products to help increase our understanding of plant water use, plant responses to drought and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (textlessa href="https://doi.org/10.5281/zenodo.3971689" target="blank"textgreater https://doi.org/10.5281/zenodo.3971689textless/atextgreater, Poyatos et al., 2020a). The textlessqtextgreatersapfluxnetrtextless/qtextgreater R package, designed to access, visualise and process SAPFLUXNET data is available from CRAN.textless/ptextgreater
Original languageEnglish
Pages (from-to)1-57
Number of pages57
JournalEarth System Science Data
DOIs
Publication statusPublished - 1 Oct 2020

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