Stan D. Wullschleger


2022

DOI bib
Range shifts in a foundation sedge potentially induce large Arctic ecosystem carbon losses and gains
Salvatore R. Curasi, Ned Fetcher, Rebecca E. Hewitt, Peter M. Lafleur, M. M. Loranty, Michelle C. Mack, Jeremy L. May, Isla H. Myers‐Smith, Susan M. Natali, Steven F. Oberbauer, Thomas C. Parker, Oliver Sonnentag, S. A. Vargas Zesati, Stan D. Wullschleger, A. V. Rocha
Environmental Research Letters, Volume 17, Issue 4

Abstract Foundation species have disproportionately large impacts on ecosystem structure and function. As a result, future changes to their distribution may be important determinants of ecosystem carbon (C) cycling in a warmer world. We assessed the role of a foundation tussock sedge ( Eriophorum vaginatum ) as a climatically vulnerable C stock using field data, a machine learning ecological niche model, and an ensemble of terrestrial biosphere models (TBMs). Field data indicated that tussock density has decreased by ~0.97 tussocks per m2 over the past ~38 years on Alaska’s North Slope from ~1981 to 2019. This declining trend is concerning because tussocks are a large Arctic C stock, which enhances soil organic layer C stocks by 6.9% on average and represents 745 Tg C across our study area. By 2100, we project that changes in tussock density may decrease the tussock C stock by 41% in regions where tussocks are currently abundant (e.g. -0.8 tussocks per m2 and -85 Tg C on the North Slope) and may increase the tussock C stock by 46% in regions where tussocks are currently scarce (e.g. +0.9 tussocks per m2 and +81 Tg C on Victoria Island). These climate-induced changes to the tussock C stock were comparable to, but sometimes opposite in sign, to vegetation C stock changes predicted by an ensemble of TBMs. Our results illustrate the important role of tussocks as a foundation species in determining future Arctic C stocks and highlights the need for better representation of this species in TBMs.

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
Missing pieces to modeling the Arctic-Boreal puzzle
Joshua B. Fisher, D. J. Hayes, Christopher R. Schwalm, D. N. Huntzinger, Eric Stofferahn, Kevin Schaefer, Yiqi Luo, Stan D. Wullschleger, Scott J. Goetz, Charles E. Miller, P. C. Griffith, Sarah Chadburn, Abhishek Chatterjee, Philippe Ciais, Thomas A. Douglas, Hélène Genet, Akihiko Ito, C. S. R. Neigh, Benjamin Poulter, Brendan M. Rogers, Oliver Sonnentag, Hanqin Tian, Weile Wang, Yongkang Xue, Zong‐Liang Yang, Ning Zeng, Zhen Zhang
Environmental Research Letters, Volume 13, Issue 2

Author(s): Fisher, JB; Hayes, DJ; Schwalm, CR; Huntzinger, DN; Stofferahn, E; Schaefer, K; Luo, Y; Wullschleger, SD; Goetz, S; Miller, CE; Griffith, P; Chadburn, S; Chatterjee, A; Ciais, P; Douglas, TA; Genet, H; Ito, A; Neigh, CSR; Poulter, B; Rogers, BM; Sonnentag, O; Tian, H; Wang, W; Xue, Y; Yang, ZL; Zeng, N; Zhang, Z | Abstract: NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.
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