Ge Sun


DOI bib
Global transpiration data from sap flow measurements: the SAPFLUXNET database
Rafael Poyatos, Víctor Granda, Víctor Flo, Mark A. Adams, Balázs Adorján, David Aguadé, Marcos Pereira Marinho Aidar, Scott T. Allen, M. Susana Alvarado-Barrientos, Kristina J. Anderson‐Teixeira, L. M. T. Aparecido, M. Altaf Arain, Ismael Aranda, Heidi Asbjornsen, Robert C. Baxter, Eric Beamesderfer, Z. Carter Berry, Daniel Berveiller, B. Blakely, Johnny L. Boggs, Gil Bohrer, Paul V. Bolstad, Damien Bonal, Rosvel Bracho, Patricia Brito, Jason Brodeur, Fernando Casanoves, Jérôme Chave, Hui Chen, César Cisneros Vaca, Kenneth L. Clark, Edoardo Cremonese, Jorge S. David, Teresa S. David, Nicolas Delpierre, Ankur R. Desai, Frédéric Chauvaud, Michal Dohnal, Jean‐Christophe Domec, Sebinasi Dzikiti, C. Edgar, Rebekka Eichstaedt, Tarek S. El‐Madany, J.A. Elbers, Cleiton B. Eller, Eugénie Euskirchen, B. E. Ewers, Patrick Fonti, Alicia Forner, David I. Forrester, Helber C. Freitas, Marta Galvagno, Omar García-Tejera, Chandra Prasad Ghimire, Teresa E. Gimeno, J. P. Grace, André Granier, Anne Griebel, Guangyu Yang, Mark B Gush, P. J. Hanson, Niles J. Hasselquist, Ingo Heinrich, Virginia Hernández‐Santana, Valentine Herrmann, Teemu Hölttä, F. Holwerda, Hongzhong Dang, J. E. Irvine, Supat Isarangkool Na Ayutthaya, P. G. Jarvis, Hubert Jochheim, Carlos A. Joly, Julia Kaplick, Hyun‐Seok Kim, Leif Klemedtsson, Heather Kropp, Fredrik Lagergren, Patrick Lane, Petra Lang, Andrei Lapenas, Víctor Lechuga, Minsu Lee, Christoph Leuschner, Jean‐Marc Limousin, Juan Carlos Linares, Maj-Lena Linderson, A. Lindroth, Pilar Llorens, Álvaro López-Bernal, M. M. Loranty, Dietmar Lüttschwager, Cate Macinnis‐Ng, Isabelle Maréchaux, Timothy A. Martin, Ashley M. Matheny, Nate G. McDowell, Sean M. McMahon, Patrick Meir, Ilona Mészáros, Mirco Migliavacca, Patrick J. Mitchell, Meelis Mölder, Leonardo Montagnani, Georgianne W. Moore, Ryogo Nakada, Furong Niu, Rachael H. Nolan, R. J. Norby, Kimberly A. Novick, Walter Oberhuber, Nikolaus Obojes, Christopher A. Oishi, Rafael S. Oliveira, Ram Oren, Jean‐Marc Ourcival, Teemu Paljakka, Óscar Pérez-Priego, Pablo Luís Peri, Richard L. Peters, Sebastian Pfautsch, William T. Pockman, Yakir Preisler, Katherine G. Rascher, George R. Robinson, Humberto Ribeiro da Rocha, Alain Rocheteau, Alexander Röll, Bruno H. P. Rosado, Lucy Rowland, Alexey V. Rubtsov, Santiago Sabaté, Yann Salmon, Roberto L. Salomón, Elisenda Sánchez-Costa, Karina V. R. Schäfer, Bernhard Schuldt, A. V. Shashkin, Clément Stahl, Marko Stojanović, Juan Carlos Suárez, Ge Sun, Justyna Szatniewska, Fyodor Tatarinov, Miroslav Tesař, Frank M. Thomas, Pantana Tor‐ngern, Josef Urban, Fernando Valladares, Christiaan van der Tol, Ilja van Meerveld, Andrej Varlagin, Holm Voigt, Jeffrey M. Warren, Christiane Werner, Willy Werner, Gerhard Wieser, Lisa Wingate, Stan D. Wullschleger, K. Yi, Roman Zweifel, Kathy Steppe, Maurizio Mencuccini, Jordi Martínez‐Vilalta
Earth System Science Data, Volume 13, Issue 6

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,, last access: 8 June 2021). We harmonized 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 (; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.


DOI bib
Wildland fire impacts on water yield across the contiguous United States
Dennis W. Hallema, Ge Sun, Peter Caldwell, François Robinne, Kevin D. Bladon, Steve Norman, Yongqiang Liu, Erika Cohen, Steven G. McNulty

Wildland fires in the contiguous United States (CONUS) have increased in size and severity, but much remains unclear about the impact of fire size and burn severity on water supplies used for drinking, irrigation, industry, and hydropower. While some have investigated large-scale fire patterns, long-term effects on runoff, and the simultaneous effect of fire and climate trends on surface water yield, no studies account for all these factors and their interactions at the same time. In this report, we present critical new information for the National Cohesive Wildland Fire Management Strategy—a first-time CONUS-wide assessment of observed and potential wildland fire impacts on surface water yield. First, we analyzed data from 168 fire-affected locations, collected between 1984 and 2013, with machine learning and used climate elasticity models to correct for the local climate baseline impact. Stream gage data show that annual river flow increased most in the Lower Mississippi and Lower and Upper Colorado water resource regions, however they do not show which portion of this increase is caused by fire and which portion results from local climate trends. Our machine learning model identified local climate trends as the main driver of water yield change and determined wildland fires must affect at least 19 percent of a watershed >10 km2 to change its annual water yield. A closer look at 32 locations with fires covering at least 19 percent of a watershed >10 km2 revealed that wildfire generally enhanced annual river flow. Fires increased river flow relatively the most in the Lower Colorado, Pacific Northwest, and California regions. In the Lower Colorado and Pacific Northwest regions, flow increased despite post-fire drought conditions. In southern California, post-fire drought effects masked the flow enhancement attributed to wildfire, meaning that annual water yield declined but not as much as expected based on the decline in precipitation. Prescribed burns in the Southeastern United States did not produce a widespread effect on river flow, because the area affected was typically too small and characterized by only low burn severity. In the second stage of the assessment, we performed full-coverage simulations of the CONUS with the Water Supply Stress Index (WaSSI) hydrologic model (88,000 HUC-12-level watersheds) for the period between 2001 and 2010. This enables us to fill in the gaps of areas with scarce data and to identify regions with large potential increases in post-fire annual water yield (+10 to +50 percent): midto high-elevation forests in northeastern Washington, northwestern Montana, central Minnesota, southern Utah, Colorado, and South Dakota, and coastal forests in Georgia and northern Florida. A hypothetical 20-percent forest burn impact scenario for the CONUS suggests that surface yield can increase up to +10 percent in most watersheds, and even more in some watersheds depending on climate, soils, and vegetation. The insights gained from this quantitative analysis have major implications for flood mitigation and watershed restoration, and are vital to forest management policies aimed at reducing fire impact risk and improving water supply under a changing climate.