Timothy A. Martin


2021

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, https://sapfluxnet.creaf.cat/, 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 (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The “sapfluxnetr” R package – designed to access, visualize, and process SAPFLUXNET data – is available from CRAN.

2018

DOI bib
Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks
Housen Chu, Dennis Baldocchi, C. Poindexter, Michael Abraha, Ankur R. Desai, Gil Bohrer, M. Altaf Arain, Timothy J. Griffis, Peter D. Blanken, Thomas L. O’Halloran, R. Quinn Thomas, Quan Zhang, Sean P. Burns, J. M. Frank, Christian Dold, Shannon Brown, T. Andrew Black, Christopher M. Gough, B. E. Law, Xuhui Lee, Jiquan Chen, David E. Reed, W. J. Massman, Kenneth L. Clark, Jerry L. Hatfield, John H. Prueger, Rosvel Bracho, John M. Baker, Timothy A. Martin
Geophysical Research Letters, Volume 45, Issue 17

Author(s): Chu, H; Baldocchi, DD; Poindexter, C; Abraha, M; Desai, AR; Bohrer, G; Arain, MA; Griffis, T; Blanken, PD; O'Halloran, TL; Thomas, RQ; Zhang, Q; Burns, SP; Frank, JM; Christian, D; Brown, S; Black, TA; Gough, CM; Law, BE; Lee, X; Chen, J; Reed, DE; Massman, WJ; Clark, K; Hatfield, J; Prueger, J; Bracho, R; Baker, JM; Martin, TA | Abstract: Aerodynamic canopy height (ha) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate ha from data are limited. This synthesis evaluates the applicability and robustness of the calculation of ha from eddy covariance momentum-flux data. At 69 forest sites, annual ha robustly predicted site-to-site and year-to-year differences in canopy heights (R2n=n0.88, 111nsite-years). At 23 cropland/grassland sites, weekly ha successfully captured the dynamics of vegetation canopies over growing seasons (R2ngn0.70 in 74nsite-years). Our results demonstrate the potential of flux-derived ha determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying ha derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure.
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