Global transpiration data from sap flow measurements: the SAPFLUXNET database

Abstract

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, https://sapfluxnet.creaf.cat/). 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 (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 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 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, 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 ( https://doi.org/10.5281/zenodo.3971689, Poyatos et al., 2020a). The sapfluxnetr R package, designed to access, visualise and process SAPFLUXNET data is available from CRAN.

Climate and functional traits jointly mediate tree water‐use strategies

“…Second, SAPFLUXNET may have an incomplete coverage of global forest ecosystems (Fig. 1; Poyatos et al, 2020). Third, highly nonlinear or threshold-based SWC responses may be difficult to capture, especially when using reanalysis data.…”

“…Data from 1929 trees belonging to 142 species on 126 plots without experimental treatments (Supporting Information Table S1) and meeting data quality criteria (see 'Data filtering' section) were obtained from the global SAPFLUXNET database (Poyatos et al, 2020) (Fig. 1; Table S2).…”

New Representation of Plant Hydraulics Improves the Estimates of Transpiration in Land Surface Model

“…A global database of plant sap flow measurement, SAPFLUXNET, has been widely used to understand ecological factors driving plant transpiration and evaluate land surface models [20]. Although the SAPFLUXNET dataset provides direct measurements on transpiration from over 120 sites worldwide, the modeled transpiration at the stand level cannot be directly compared with the sap flow measurement of individual plants.…”

“…Although the SAPFLUXNET dataset provides direct measurements on transpiration from over 120 sites worldwide, the modeled transpiration at the stand level cannot be directly compared with the sap flow measurement of individual plants. Upscaling from the individual to the stand level may introduce additional uncertainties [20]. The FLUXNET dataset is the most frequently used for the analysis of stand-level measurements, including land-atmosphere flux measurements from more than 900 sites [21].…”

Stressors Reveal Ecosystems' Hidden Characteristics

“…Large-scale, longterm and paired ecosystem studies produce datasets of such high temporal density to be statistically independent at sufficient time scales [Baldocchi and Ma, 2013] and allow the substitution of space with time [Panofsky and Dutton, 1984]. Notably, these results also reveal how crucial it is to thoroughly report metadata regarding the stand history along with present and past environmental context of measurements when reporting observations to global observational databases such as TRY [Kattge et al, 2011], SAPFLUXNET [Poyatos et al, 2020], the Ameriflux and other Fluxnet networks [Baldocchi et al, 2001;Novick et al, 2018], hydraulic traits databases [e.g. Chave et al, 2009;Choat et al, 2012], or GLOPNET [Reich et al, 2007;Wright et al, 2004], for example.…”