Effects of experimental protocol on global vegetation model accuracy: A comparison of simulated and observed vegetation patterns for Asia

2009 ◽  
Vol 220 (12) ◽  
pp. 1481-1491 ◽  
Author(s):  
Guoping Tang ◽  
Sarah L. Shafer ◽  
Patrick J. Bartlein ◽  
Justin O. Holman
Keyword(s):  
Vegetation Patterns ◽  
Experimental Protocol ◽  
Vegetation Model ◽  
Model Accuracy ◽  
Global Vegetation

Soil depth affects simulated carbon and water in the MC2 dynamic global vegetation model

2014 ◽  
Vol 294 ◽  
pp. 84-93 ◽  
Author(s):  
Wendy Peterman ◽  
Dominique Bachelet ◽  
Ken Ferschweiler ◽  
Timothy Sheehan
Keyword(s):  
Soil Depth ◽  
Vegetation Model ◽  
Dynamic Global Vegetation Model ◽  
Global Vegetation

scholarly journals The Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM): a diverse approach to representing terrestrial biogeography and biogeochemistry based on plant functional trade-offs

2013 ◽  
Vol 10 (6) ◽  
pp. 4137-4177 ◽  
Author(s):  
R. Pavlick ◽  
D. T. Drewry ◽  
K. Bohn ◽  
B. Reu ◽  
A. Kleidon
Keyword(s):  
Functional Diversity ◽  
Land Surface ◽  
Grid Cell ◽  
Surface Fluxes ◽  
Growth Strategies ◽  
Vegetation Model ◽  
Terrestrial Biosphere ◽  
Dynamic Global Vegetation Model ◽  
Trade Offs ◽  
Global Vegetation

Abstract. Terrestrial biosphere models typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semi-empirical plant functional types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM) as a new approach to terrestrial biosphere modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly generated plant growth strategies, each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional trade-offs. These trade-offs ultimately determine whether a strategy is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other strategies. The biogeochemical fluxes and land surface properties of the individual strategies are aggregated to the grid-cell scale using a mass-based weighting scheme. We evaluate the simulated global biogeochemical patterns against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favourably with other state-of-the-art global vegetation models. We also evaluate the simulated patterns of functional diversity and the sensitivity of the JeDi-DGVM modelling approach to the number of sampled strategies. Altogether, the results demonstrate the parsimonious and flexible nature of a functional trade-off approach to global vegetation modelling, i.e. it can provide more types of testable outputs than standard PFT-based approaches and with fewer inputs. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere.

Using a Dynamic Global Vegetation Model to Help Inform Management Decisions

2015 ◽  
pp. 151-170
Author(s):  
Joshua S. Halofsky ◽  
Jessica E. Halofsky ◽  
David R. Conklin ◽  
Dominique Bachelet ◽  
Miles A. Hemstrom ◽  
...  
Keyword(s):  
Vegetation Model ◽  
Management Decisions ◽  
Dynamic Global Vegetation Model ◽  
Global Vegetation

scholarly journals ORCHIDEE-MICT-BIOENERGY: an attempt to represent the production of lignocellulosic crops for bioenergy in a global vegetation model

2018 ◽  
Vol 11 (6) ◽  
pp. 2249-2272 ◽  
Author(s):  
Wei Li ◽  
Chao Yue ◽  
Philippe Ciais ◽  
Jinfeng Chang ◽  
Daniel Goll ◽  
...  
Keyword(s):  
Lignocellulosic Biomass ◽  
Management Practices ◽  
Carbon Allocation ◽  
Field Measurements ◽  
Bioenergy Crops ◽  
Climate Mitigation ◽  
Bioenergy Crop ◽  
Vegetation Model ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Bioenergy crop cultivation for lignocellulosic biomass is increasingly important for future climate mitigation, and it is assumed on large scales in integrated assessment models (IAMs) that develop future land use change scenarios consistent with the dual constraint of sufficient food production and deep decarbonization for low climate-warming targets. In most global vegetation models, there is no specific representation of crops producing lignocellulosic biomass, resulting in simulation biases of biomass yields and other carbon outputs, and in turn of future bioenergy production. Here, we introduced four new plant functional types (PFTs) to represent four major lignocellulosic bioenergy crops, eucalypt, poplar and willow, Miscanthus, and switchgrass, in the global process-based vegetation model ORCHIDEE. New parameterizations of photosynthesis, carbon allocation, and phenology are proposed based on a compilation of field measurements. A specific harvest module is further added to the model to simulate the rotation of bioenergy tree PFTs based on their age dynamics. The resulting ORCHIDEE-MICT-BIOENERGY model is applied at 296 locations where field measurements of harvested biomass are available for different bioenergy crops. The new model can generally reproduce the global bioenergy crop yield observations. Biases in the model results related to grid-based simulations versus the point-scale measurements and the lack of fertilization and fertilization management practices in the model are discussed. This study sheds light on the importance of properly representing bioenergy crops for simulating their yields. The parameterizations of bioenergy crops presented here are generic enough to be applicable in other global vegetation models.

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