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Dendroclimatic reconstructions, which are a well-known tool for extending records of climatic variability, have recently been expanded by using wood anatomical parameters. However, the relationships between wood cellular structures and large-scale climatic patterns, such as El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), are still not completely understood, hindering the potential for wood anatomy as a paleoclimatic proxy. To better understand the teleconnection between regional and local climate processes in the western United States, our main objective was to assess the value of these emerging tree-ring parameters for reconstructing climate dynamics. Using Confocal Laser Scanning Microscopy, we measured cell lumen diameter and cell wall thickness (CWT) for the period 1966 to 2015 in five Douglas-firs [ Pseudotsuga menziesii (Mirb.) Franco] from two sites in eastern Arizona (United States). Dendroclimatic analysis was performed using chronologies developed for 10 equally distributed sectors of the ring and daily climatic records to identify the strongest climatic signal for each sector. We found that lumen diameter in the first ring sector was sensitive to previous fall–winter temperature (September 25 th to January 23 rd ), while a precipitation signal (October 27 th to February 13 th ) persisted for the entire first half of the ring. The lack of synchronous patterns between trees for CWT prevented conducting meaningful climate-response analysis for that anatomical parameter. Time series of lumen diameter showed an anti-phase relationship with the Southern Oscillation Index (a proxy for ENSO) at 10 to 14year periodicity and particularly in 1980–2005, suggesting that chronologies of wood anatomical parameters respond to multidecadal variability of regional climatic modes. Our findings demonstrate the potential of cell structural characteristics of southwestern United States conifers for reconstructing past climatic variability, while also improving our understanding of how large-scale ocean–atmosphere interactions impact local hydroclimatic patterns. 

Abstract. Plant transpiration links physiological responses ofvegetation to water supply and demand with hydrological, energy, and carbonbudgets at the land–atmosphere interface. However, despite being the mainland evaporative flux at the global scale, transpiration and its response toenvironmental drivers are currently not well constrained by observations.Here we introduce the first global compilation of whole-plant transpirationdata from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021).We harmonized and quality-controlled individual datasets supplied bycontributors worldwide in a semi-automatic data workflow implemented in theR programming language. Datasets include sub-daily time series of sap flowand hydrometeorological drivers for one or more growing seasons, as well asmetadata on the stand characteristics, plant attributes, and technicaldetails of the measurements. SAPFLUXNET contains 202 globally distributeddatasets with sap flow time series for 2714 plants, mostly trees, of 174species. SAPFLUXNET has a broad bioclimatic coverage, withwoodland/shrubland and temperate forest biomes especially well represented(80 % of the datasets). The measurements cover a wide variety of standstructural characteristics and plant sizes. The datasets encompass theperiod between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data areavailable for most of the datasets, while on-site soil water content isavailable for 56 % of the datasets. Many datasets contain data for speciesthat make up 90 % or more of the total stand basal area, allowing theestimation of stand transpiration in diverse ecological settings. SAPFLUXNETadds to existing plant trait datasets, ecosystem flux networks, and remotesensing products to help increase our understanding of plant water use,plant responses to drought, and ecohydrological processes. SAPFLUXNET version0.1.5 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, visualize, and processSAPFLUXNET data – is available from CRAN.