Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

2010 ◽  
Vol 221 (20) ◽  
pp. 2458-2474 ◽  
Author(s):  
V. Bellassen ◽  
G. Le Maire ◽  
J.F. Dhôte ◽  
P. Ciais ◽  
N. Viovy
Keyword(s):  
Forest Management ◽  
Model Structure ◽  
Vegetation Model ◽  
General Behaviour ◽  
Global Vegetation

scholarly journals Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

2011 ◽  
Vol 222 (1) ◽  
pp. 57-75 ◽  
Author(s):  
V. Bellassen ◽  
G. le Maire ◽  
O. Guin ◽  
J.F. Dhôte ◽  
P. Ciais ◽  
...  
Keyword(s):  
Forest Management ◽  
Model Validation ◽  
Vegetation Model ◽  
Continental Scale ◽  
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.

scholarly journals Uncertainties in modeling CH<sub>4</sub> emissions from northern wetlands in glacial climates: effect of hydrological model and CH<sub>4</sub> model structure

2009 ◽  
Vol 5 (2) ◽  
pp. 817-851 ◽  
Author(s):  
C. Berrittella ◽  
J. van Huissteden
Keyword(s):  
Ice Cover ◽  
Atmospheric Composition ◽  
Model Structure ◽  
Vegetation Model ◽  
Ch4 Flux ◽  
Tuning Parameters ◽  
Ch4 Production ◽  
Highly Sensitive ◽  
Flux Model ◽  
Earth System Models

Abstract. Methane (CH4) fluxes from northern wetlands may have influenced atmospheric CH4 concentrations at climate warming phases during the 800 000 years and at present global warming. Including these CH4 fluxes in earth system models is essential to understand feedbacks between climate and atmospheric composition. Attempts to model CH4 fluxes from wetlands have been undertaken previously using various approaches. Here, we test a process-based wetland CH4 flux model (PEATLAND-VU) which includes details of soil-atmosphere CH4 transport. The model has been used to simulate CH4 emissions from continental Europe in different glacial climates and the present climate. This paper displays results on the sensitivity of modeling glacial terrestrial CH4 fluxes to basic tuning parameters of the model, to different approaches in modeling of the water table, and to model structure. For testing the model structure, PEATLAND-VU has been compared to a simpler modeling approach based on wetland primary production estimated from a vegetation model (BIOME). The tuning parameters are the CH4 production rate from labile organic carbon and its temperature sensitivity. The modelled fluxes prove comparatively insensitive to hydrology representation, and sensitive to microbial parameters and model structure. Glacial climate emissions are also highly sensitive to assumptions on the extent of ice cover and exposed seafloors. Wetland expansion on low relief exposed seafloor areas, may have compensated for a decrease of wetland area due to continental ice cover.

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
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