DOI: 10.5281/zenodo.2530797
title: SAPFLUXNET: A global database of sap flow measurements

description: <strong>General description</strong> SAPFLUXNET contains a global database of sap flow and environmental data, together with metadata at different levels.<br> SAPFLUXNET is a harmonised database, compiled from contributions from researchers worldwide. The SAPFLUXNET version 0.1.5 database harbours 202 globally distributed datasets, from 121 geographical locations. SAPFLUXNET contains sap flow data for 2714 individual plants (1584 angiosperms and 1130 gymnosperms), belonging to 174 species (141 angiosperms and 33 gymnosperms), 95 different genera and 45 different families. More information on the database coverage can be found here: http://sapfluxnet.creaf.cat/shiny/sfn_progress_dashboard/. <br> The SAPFLUXNET project has been developed by researchers at CREAF and other institutions (http://sapfluxnet.creaf.cat/#team), coordinated by Rafael Poyatos (CREAF, http://www.creaf.cat/staff/rafael-poyatos-lopez), and funded by two Spanish Young Researcher's Grants (SAPFLUXNET, CGL2014-55883-JIN; DATAFORUSE, RTI2018-095297-J-I00 ) and an Alexander von Humboldt Research Fellowship for Experienced Researchers). <strong>Changelog </strong> Compared to version 0.1.4, this version includes some changes in the metadata, but all time series data (sap flow, environmental) remain the same. For all datasets, climate metadata (temperature and precipitation, ‘si_mat’ and ‘si_map’) have been extracted from CHELSA (https://chelsa-climate.org/), replacing the previous climate data obtained with Wordclim. This change has modified the biome classification of the datasets in ‘si_biome’. In ‘species’ metadata, the percentage of basal area with sap flow measurements for each species (‘sp_basal_area_perc’) is now assigned a value of 0 if species are in the understorey. This affects two datasets: AUS_MAR_UBD and AUS_MAR_UBW, where, previously, the sum of species basal area percentages could add up to more than 100%. In ‘species’ metadata, the percentage of basal area with sap flow measurements for each species (‘sp_basal_area_perc’) has been corrected for datasets USA_SIL_OAK_POS, USA_SIL_OAK_1PR, USA_SIL_OAK_2PR. In ‘site’ metadata, the vegetation type (‘si_igbp’) has been changed to SAV for datasets CHN_ARG_GWD and CHN_ARG_GWS. <strong>Variables and units</strong> SAPFLUXNET contains whole-plant sap flow and environmental variables at sub-daily temporal resolution. Both sap flow and environmental time series have accompanying flags in a data frame, one for sap flow and another for environmental<br> variables. These flags store quality issues detected during the quality control process and can be used to add further quality flags. Metadata contain relevant variables informing about site conditions, stand characteristics, tree and species attributes, sap flow methodology and details on environmental measurements. The description and units of all data and metadata variables can be found here: Metadata and data units. To learn more about variables, units and data flags please use the functionalities implemented in the sapfluxnetr package (https://github.com/sapfluxnet/sapfluxnetr). In particular, have a look at the package vignettes using R: <pre><code># remotes::install_github( # 'sapfluxnet/sapfluxnetr', # build_opts = c("--no-resave-data", "--no-manual", "--build-vignettes") # ) library(sapfluxnetr) # to list all vignettes vignette(package='sapfluxnetr') # variables and units vignette('metadata-and-data-units', package='sapfluxnetr') # data flags vignette('data-flags', package='sapfluxnetr')</code></pre> <strong>Data formats</strong> SAPFLUXNET data can be found in two formats: 1) RData files belonging to the custom-built 'sfn_data' class and 2) Text files in .csv format. We recommend using the sfn_data objects together with the sapfluxnetr package, although we also provide the text files for convenience. For each dataset, text files are structured in the same way as the slots of sfn_data objects; if working with text files, we recommend that you check the data structure of 'sfn_data' objects in the corresponding vignette. <strong>Working with sfn_data files</strong> To work with SAPFLUXNET data, first they have to be downloaded from Zenodo, maintaining the folder structure. A first level in the folder hierarchy corresponds to file format, either RData files or csv's. A second level corresponds to how sap flow is expressed: per plant, per sapwood area or per leaf area. Please note that interconversions among the magnitudes have been performed whenever possible. Below this level, data have been organised per dataset. In the case of RData files, each dataset is contained in a sfn_data object, which stores all data and metadata in different slots (see the vignette 'sfn-data-classes'). In the case of csv files, each dataset has 9 individual files, corresponding to metadata (5), sap flow and environmental data (2) and their corresponding data flags (2). After downloading the entire database, the sapfluxnetr package can be used to:<br> - Work with data from a single site: data access, plotting and time aggregation.<br> - Select the subset datasets to work with.<br> - Work with data from multiple sites: data access, plotting and time aggregation. Please check the following package vignettes to learn more about how to work with sfn_data files: Quick guide Metadata and data units sfn_data classes Custom aggregation Memory and parallelization <strong>Working with text files</strong> We recommend to work with sfn_data objects using R and the sapfluxnetr package and we do not currently provide code to work with text files. <strong>Data issues and reporting</strong> Please report any issue you may find in the database by sending us an email: sapfluxnet@creaf.uab.cat. Temporary data fixes, detected but not yet included in released versions will be published in SAPFLUXNET main web page ('Known data errors'). <strong>Data access, use and citation</strong> This version of the SAPFLUXNET database is open access and corresponds to the data paper submitted to Earth System Science Data in August 2020. When using SAPFLUXNET data in an academic work, please cite the data paper, when available, or alternatively, the Zenodo dataset (see the ‘Cite as’ section on the right panels of this web page).