Stan D Wullschleger1, Howard E Epstein2, Elgene O Box3, Eugénie S Euskirchen4, Santonu Goswami5, Colleen M Iversen5, Jens Kattge6, Richard J Norby5, Peter M van Bodegom7, Xiaofeng Xu5. 1. Environmental Sciences Division, Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6301, USA wullschlegsd@ornl.gov. 2. Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904-4123, USA. 3. Department of Geography, University of Georgia, Athens, GA 30602, USA. 4. Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK 99775, USA. 5. Environmental Sciences Division, Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6301, USA. 6. Max Planck Institute for Biogeochemistry, Jena, Germany. 7. Department of Ecological Sciences, VU University Amsterdam, Amsterdam, The Netherlands.
Abstract
BACKGROUND: Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. SCOPE: Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. CONCLUSIONS: Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings. Published by Oxford University Press on behalf of the Annals of Botany Company 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
BACKGROUND: Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. SCOPE: Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. CONCLUSIONS: Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings. Published by Oxford University Press on behalf of the Annals of Botany Company 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Authors: D A Stainforth; T Aina; C Christensen; M Collins; N Faull; D J Frame; J A Kettleborough; S Knight; A Martin; J M Murphy; C Piani; D Sexton; L A Smith; R A Spicer; A J Thorpe; M R Allen Journal: Nature Date: 2005-01-27 Impact factor: 49.962
Authors: Johannes H C Cornelissen; Peter M van Bodegom; Rien Aerts; Terry V Callaghan; Richard S P van Logtestijn; Juha Alatalo; F Stuart Chapin; Renato Gerdol; Jon Gudmundsson; Dylan Gwynn-Jones; Anne E Hartley; David S Hik; Annika Hofgaard; Ingibjörg S Jónsdóttir; Staffan Karlsson; Julia A Klein; Jim Laundre; Borgthor Magnusson; Anders Michelsen; Ulf Molau; Vladimir G Onipchenko; Helen M Quested; Sylvi M Sandvik; Inger K Schmidt; Gus R Shaver; Bjørn Solheim; Nadejda A Soudzilovskaia; Anna Stenström; Anne Tolvanen; Ørjan Totland; Naoya Wada; Jeffrey M Welker; Xinquan Zhao Journal: Ecol Lett Date: 2007-07 Impact factor: 9.492
Authors: S F Oberbauer; S C Elmendorf; T G Troxler; R D Hollister; A V Rocha; M S Bret-Harte; M A Dawes; A M Fosaa; G H R Henry; T T Høye; F C Jarrad; I S Jónsdóttir; K Klanderud; J A Klein; U Molau; C Rixen; N M Schmidt; G R Shaver; R T Slider; Ø Totland; C-H Wahren; J M Welker Journal: Philos Trans R Soc Lond B Biol Sci Date: 2013-07-08 Impact factor: 6.237
Authors: Jenny C Ordoñez; Peter M van Bodegom; Jan-Philip M Witte; Ruud P Bartholomeus; Jurgen R van Hal; Rien Aerts Journal: Am Nat Date: 2010-02 Impact factor: 3.926
Authors: M R Turetsky; B Bond-Lamberty; E Euskirchen; J Talbot; S Frolking; A D McGuire; E-S Tuittila Journal: New Phytol Date: 2012-10 Impact factor: 10.151
Authors: Anne D Bjorkman; Isla H Myers-Smith; Sarah C Elmendorf; Signe Normand; Nadja Rüger; Pieter S A Beck; Anne Blach-Overgaard; Daan Blok; J Hans C Cornelissen; Bruce C Forbes; Damien Georges; Scott J Goetz; Kevin C Guay; Gregory H R Henry; Janneke HilleRisLambers; Robert D Hollister; Dirk N Karger; Jens Kattge; Peter Manning; Janet S Prevéy; Christian Rixen; Gabriela Schaepman-Strub; Haydn J D Thomas; Mark Vellend; Martin Wilmking; Sonja Wipf; Michele Carbognani; Luise Hermanutz; Esther Lévesque; Ulf Molau; Alessandro Petraglia; Nadejda A Soudzilovskaia; Marko J Spasojevic; Marcello Tomaselli; Tage Vowles; Juha M Alatalo; Heather D Alexander; Alba Anadon-Rosell; Sandra Angers-Blondin; Mariska Te Beest; Logan Berner; Robert G Björk; Agata Buchwal; Allan Buras; Katherine Christie; Elisabeth J Cooper; Stefan Dullinger; Bo Elberling; Anu Eskelinen; Esther R Frei; Oriol Grau; Paul Grogan; Martin Hallinger; Karen A Harper; Monique M P D Heijmans; James Hudson; Karl Hülber; Maitane Iturrate-Garcia; Colleen M Iversen; Francesca Jaroszynska; Jill F Johnstone; Rasmus Halfdan Jørgensen; Elina Kaarlejärvi; Rebecca Klady; Sara Kuleza; Aino Kulonen; Laurent J Lamarque; Trevor Lantz; Chelsea J Little; James D M Speed; Anders Michelsen; Ann Milbau; Jacob Nabe-Nielsen; Sigrid Schøler Nielsen; Josep M Ninot; Steven F Oberbauer; Johan Olofsson; Vladimir G Onipchenko; Sabine B Rumpf; Philipp Semenchuk; Rohan Shetti; Laura Siegwart Collier; Lorna E Street; Katharine N Suding; Ken D Tape; Andrew Trant; Urs A Treier; Jean-Pierre Tremblay; Maxime Tremblay; Susanna Venn; Stef Weijers; Tara Zamin; Noémie Boulanger-Lapointe; William A Gould; David S Hik; Annika Hofgaard; Ingibjörg S Jónsdóttir; Janet Jorgenson; Julia Klein; Borgthor Magnusson; Craig Tweedie; Philip A Wookey; Michael Bahn; Benjamin Blonder; Peter M van Bodegom; Benjamin Bond-Lamberty; Giandiego Campetella; Bruno E L Cerabolini; F Stuart Chapin; William K Cornwell; Joseph Craine; Matteo Dainese; Franciska T de Vries; Sandra Díaz; Brian J Enquist; Walton Green; Ruben Milla; Ülo Niinemets; Yusuke Onoda; Jenny C Ordoñez; Wim A Ozinga; Josep Penuelas; Hendrik Poorter; Peter Poschlod; Peter B Reich; Brody Sandel; Brandon Schamp; Serge Sheremetev; Evan Weiher Journal: Nature Date: 2018-09-26 Impact factor: 49.962
Authors: Daniel J Wieczynski; Brad Boyle; Vanessa Buzzard; Sandra M Duran; Amanda N Henderson; Catherine M Hulshof; Andrew J Kerkhoff; Megan C McCarthy; Sean T Michaletz; Nathan G Swenson; Gregory P Asner; Lisa Patrick Bentley; Brian J Enquist; Van M Savage Journal: Proc Natl Acad Sci U S A Date: 2018-12-24 Impact factor: 11.205
Authors: Cyrille Violle; Peter B Reich; Stephen W Pacala; Brian J Enquist; Jens Kattge Journal: Proc Natl Acad Sci U S A Date: 2014-09-15 Impact factor: 11.205
Authors: Julia Kemppinen; Pekka Niittynen; Peter C le Roux; Mia Momberg; Konsta Happonen; Juha Aalto; Helena Rautakoski; Brian J Enquist; Vigdis Vandvik; Aud H Halbritter; Brian Maitner; Miska Luoto Journal: Nat Ecol Evol Date: 2021-02-25 Impact factor: 15.460
Authors: Risto Virtanen; Lauri Oksanen; Tarja Oksanen; Juval Cohen; Bruce C Forbes; Bernt Johansen; Jukka Käyhkö; Johan Olofsson; Jouni Pulliainen; Hans Tømmervik Journal: Ecol Evol Date: 2015-12-15 Impact factor: 2.912