Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information
Dynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land...
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Copernicus Publications
2016-07-01
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Series: | Geoscientific Model Development |
Online Access: | http://www.geosci-model-dev.net/9/2415/2016/gmd-9-2415-2016.pdf |
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Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. B. Harper P. M. Cox P. Friedlingstein A. J. Wiltshire C. D. Jones S. Sitch L. M. Mercado M. Groenendijk E. Robertson J. Kattge G. Bönisch O. K. Atkin M. Bahn J. Cornelissen Ü. Niinemets V. Onipchenko J. Peñuelas L. Poorter P. B. Reich N. A. Soudzilovskaia P. V. Bodegom |
spellingShingle |
A. B. Harper P. M. Cox P. Friedlingstein A. J. Wiltshire C. D. Jones S. Sitch L. M. Mercado M. Groenendijk E. Robertson J. Kattge G. Bönisch O. K. Atkin M. Bahn J. Cornelissen Ü. Niinemets V. Onipchenko J. Peñuelas L. Poorter P. B. Reich N. A. Soudzilovskaia P. V. Bodegom Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait information Geoscientific Model Development |
author_facet |
A. B. Harper P. M. Cox P. Friedlingstein A. J. Wiltshire C. D. Jones S. Sitch L. M. Mercado M. Groenendijk E. Robertson J. Kattge G. Bönisch O. K. Atkin M. Bahn J. Cornelissen Ü. Niinemets V. Onipchenko J. Peñuelas L. Poorter P. B. Reich N. A. Soudzilovskaia P. V. Bodegom |
author_sort |
A. B. Harper |
title |
Improved representation of plant functional types and physiology in the
Joint UK Land Environment Simulator (JULES v4.2) using plant trait
information |
title_short |
Improved representation of plant functional types and physiology in the
Joint UK Land Environment Simulator (JULES v4.2) using plant trait
information |
title_full |
Improved representation of plant functional types and physiology in the
Joint UK Land Environment Simulator (JULES v4.2) using plant trait
information |
title_fullStr |
Improved representation of plant functional types and physiology in the
Joint UK Land Environment Simulator (JULES v4.2) using plant trait
information |
title_full_unstemmed |
Improved representation of plant functional types and physiology in the
Joint UK Land Environment Simulator (JULES v4.2) using plant trait
information |
title_sort |
improved representation of plant functional types and physiology in the
joint uk land environment simulator (jules v4.2) using plant trait
information |
publisher |
Copernicus Publications |
series |
Geoscientific Model Development |
issn |
1991-959X 1991-9603 |
publishDate |
2016-07-01 |
description |
Dynamic global vegetation models are used to predict the response of
vegetation to climate change. They are essential for planning ecosystem
management, understanding carbon cycle–climate feedbacks, and evaluating the
potential impacts of climate change on global ecosystems. JULES (the Joint
UK Land Environment Simulator) represents terrestrial processes in the UK
Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs):
broadleaf trees, needle-leaf trees, C<sub>3</sub> and C<sub>4</sub> grasses, and shrubs.
This study addresses three developments in JULES. First, trees and shrubs
were split into deciduous and evergreen PFTs to better represent the range
of leaf life spans and metabolic capacities that exists in nature. Second, we
distinguished between temperate and tropical broadleaf evergreen trees.
These first two changes result in a new set of nine PFTs: tropical and
temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf
evergreen and deciduous trees, C<sub>3</sub> and C<sub>4</sub> grasses, and evergreen
and deciduous shrubs. Third, using data from the TRY database, we updated
the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (<i>V</i><sub>cmax</sub>), and updated the leaf turnover and growth rates to
include a trade-off between leaf life span and leaf mass per unit area.<br><br>Overall, the simulation of gross and net primary productivity (GPP and NPP,
respectively) is improved with the nine PFTs when compared to FLUXNET sites, a
global GPP data set based on FLUXNET, and MODIS NPP. Compared to the
standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the
exception of C<sub>3</sub> grasses in cold environments and C<sub>4</sub> grasses that
were previously over-productive. On a biome scale, GPP is improved for all
eight biomes evaluated and NPP is improved for most biomes – the exceptions
being the tropical forests, savannahs, and extratropical mixed forests where
simulated NPP is too high. With the new PFTs, the global present-day GPP and
NPP are 128 and 62 Pg C year<sup>−1</sup>, respectively. We conclude
that the inclusion of trait-based data and the evergreen/deciduous
distinction has substantially improved productivity fluxes in JULES, in
particular the representation of GPP. These developments increase the
realism of JULES, enabling higher confidence in simulations of vegetation
dynamics and carbon storage. |
url |
http://www.geosci-model-dev.net/9/2415/2016/gmd-9-2415-2016.pdf |
work_keys_str_mv |
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spelling |
doaj-677ec38dcd5f4fa5a1364eee5465ea4d2020-11-24T23:12:13ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032016-07-01972415244010.5194/gmd-9-2415-2016Improved representation of plant functional types and physiology in the Joint UK Land Environment Simulator (JULES v4.2) using plant trait informationA. B. Harper0P. M. Cox1P. Friedlingstein2A. J. Wiltshire3C. D. Jones4S. Sitch5L. M. Mercado6M. Groenendijk7E. Robertson8J. Kattge9G. Bönisch10O. K. Atkin11M. Bahn12J. Cornelissen13Ü. Niinemets14V. Onipchenko15J. Peñuelas16L. Poorter17P. B. Reich18N. A. Soudzilovskaia19P. V. Bodegom20College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UKCollege of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UKCollege of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UKMet Office Hadley Centre, Exeter, UKMet Office Hadley Centre, Exeter, UKCollege of Life and Environmental Sciences, University of Exeter, Exeter, UKCollege of Life and Environmental Sciences, University of Exeter, Exeter, UKCollege of Life and Environmental Sciences, University of Exeter, Exeter, UKMet Office Hadley Centre, Exeter, UKMax Planck Institute for Biogeochemistry, Jena, GermanyMax Planck Institute for Biogeochemistry, Jena, GermanyARC Centre of Excellence in Plant Energy Biology, Research School of Biology, Australian National University, Canberra, AustraliaInstitute of Ecology, University of Innsbruck, AustriaSystems Ecology, Department of Ecological Science, Vrije Universiteit, Amsterdam, the NetherlandsInstitute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Tartu, Estonia Department of Geobotany, Moscow State University, Moscow 119234, RussiaCSIC, Global Ecology Unit CREAF-CSIC-UAB, Cerdanyola del Vallès, 08193 Barcelona, Catalonia, SpainForest Ecology and Forest Management Group, Wageningen University, P.O. Box 6700 AA, Wageningen, the NetherlandsDepartment of Forest Resources, University of Minnesota, Saint Paul, Minnesota, USAInstitute of Environmental Sciences, Leiden University, Leiden, the NetherlandsInstitute of Environmental Sciences, Leiden University, Leiden, the NetherlandsDynamic global vegetation models are used to predict the response of vegetation to climate change. They are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential impacts of climate change on global ecosystems. JULES (the Joint UK Land Environment Simulator) represents terrestrial processes in the UK Hadley Centre family of models and in the first generation UK Earth System Model. Previously, JULES represented five plant functional types (PFTs): broadleaf trees, needle-leaf trees, C<sub>3</sub> and C<sub>4</sub> grasses, and shrubs. This study addresses three developments in JULES. First, trees and shrubs were split into deciduous and evergreen PFTs to better represent the range of leaf life spans and metabolic capacities that exists in nature. Second, we distinguished between temperate and tropical broadleaf evergreen trees. These first two changes result in a new set of nine PFTs: tropical and temperate broadleaf evergreen trees, broadleaf deciduous trees, needle-leaf evergreen and deciduous trees, C<sub>3</sub> and C<sub>4</sub> grasses, and evergreen and deciduous shrubs. Third, using data from the TRY database, we updated the relationship between leaf nitrogen and the maximum rate of carboxylation of Rubisco (<i>V</i><sub>cmax</sub>), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area.<br><br>Overall, the simulation of gross and net primary productivity (GPP and NPP, respectively) is improved with the nine PFTs when compared to FLUXNET sites, a global GPP data set based on FLUXNET, and MODIS NPP. Compared to the standard five PFTs, the new nine PFTs simulate a higher GPP and NPP, with the exception of C<sub>3</sub> grasses in cold environments and C<sub>4</sub> grasses that were previously over-productive. On a biome scale, GPP is improved for all eight biomes evaluated and NPP is improved for most biomes – the exceptions being the tropical forests, savannahs, and extratropical mixed forests where simulated NPP is too high. With the new PFTs, the global present-day GPP and NPP are 128 and 62 Pg C year<sup>−1</sup>, respectively. We conclude that the inclusion of trait-based data and the evergreen/deciduous distinction has substantially improved productivity fluxes in JULES, in particular the representation of GPP. These developments increase the realism of JULES, enabling higher confidence in simulations of vegetation dynamics and carbon storage.http://www.geosci-model-dev.net/9/2415/2016/gmd-9-2415-2016.pdf |