Abstract
Abstract. 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, C3 and C4 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, C3 and C4 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 (Vcmax), and updated the leaf turnover and growth rates to include a trade-off between leaf life span and leaf mass per unit area.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 C3 grasses in cold environments and C4 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−1, 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.
Highlights
The net exchange of carbon dioxide between the vegetated land and the atmosphere is predominantly the result of two large and opposing fluxes: uptake by photosynthesis and efflux by respiration from soils and vegetation
We provide a set of recommended parameters and guidance for users who wish to run JULES with the original five plant functional types (PFTs) (Table A2)
Full results are shown in the Supplement, but for the main text we focus the discussion on JULES with five PFTs (JULES5); JULES with nine PFTs and updated Nm, leaf mass per unit area (LMA), Vcmax,25, and leaf life span from the TRY database (JULES9TRY); and JULES with nine PFTs and all updated parameters described in Sect. 2.3 (JULES9ALL)
Summary
The net exchange of carbon dioxide between the vegetated land and the atmosphere is predominantly the result of two large and opposing fluxes: uptake by photosynthesis and efflux by respiration from soils and vegetation. CO2 can be released by land ecosystems due to vegetation mortality resulting from human and natural disturbances, such as changes in land use practices, insect outbreaks, and fires. A subset of vegetation models predicts both compositional and biogeochemical responses of vegetation to climate change (dynamic global vegetation models, DGVMs), one of these being the Joint UK Land Environment Simulator (JULES). Within JULES, the TRIFFID model (Top-down Representation of Foliage and Flora Including Dynamics; Cox, 2001) predicts changes in biomass and the fractional coverage of five plant functional types (PFTs; broadleaf trees, needle-leaf trees, C3 grass, C4 grass, and shrubs) based on cumulative carbon fluxes and a predetermined dominance hierarchy. DGVMs such as JULES are essential for planning ecosystem management, understanding carbon cycle–climate feedbacks, and evaluating the potential
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