Carbon cycle and natural vegetation/Description: Difference between revisions
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|Description===Vegetation types== | |Description====Vegetation types=== | ||
The Natural vegetation and carbon cycle model is implemented by using [[LPJmL model]]. This is a Dynamic Global Vegetation Model ([[hasAcronym::DGVM]]), initially developed to assess the role of the terrestrial biosphere in the global carbon cycle (Prentice et al., 2007). DGVMs simulate vegetation distribution and dynamics, using the concept of multiple plant functional types ([[hasAcronym::PFT]]s) that are differentiated according to their bioclimatic (e.g. temperature requirement), physiological, morphological, and phenological (e.g. growing season) attributes, and that compete for resources (i.e. light and water). In order to aggregate the vast diversity of plant species in the world, with respect to the most important differences for the carbon cycle, Natural vegetation and carbon cycle model distinguishes [[Plant functional types|nine PFTs]]. Plant dynamics are computed for each PFT present in a grid cell. Since IMAGE uses the concept of biomes (see the [[Land cover types|Natural vegetation types]]), combinations of PFTs in an area/grid cell are translated into a certain biome type (see figure on the right: Biome classification). In the IMAGE framework there is one modification to LPJml, namely the biome ‘ice’, for biomes initially defined as ‘arctic tundra’, and with an average annual temperature of < -2 oC and an annual net primary production (NPP) of < 1 Pg.yr-1. All carbon pools and fluxes in this biome are set to zero. | The Natural vegetation and carbon cycle model is implemented by using [[LPJmL model]]. This is a Dynamic Global Vegetation Model ([[hasAcronym::DGVM]]), initially developed to assess the role of the terrestrial biosphere in the global carbon cycle (Prentice et al., 2007). DGVMs simulate vegetation distribution and dynamics, using the concept of multiple plant functional types ([[hasAcronym::PFT]]s) that are differentiated according to their bioclimatic (e.g. temperature requirement), physiological, morphological, and phenological (e.g. growing season) attributes, and that compete for resources (i.e. light and water). In order to aggregate the vast diversity of plant species in the world, with respect to the most important differences for the carbon cycle, Natural vegetation and carbon cycle model distinguishes [[Plant functional types|nine PFTs]]. Plant dynamics are computed for each PFT present in a grid cell. Since IMAGE uses the concept of biomes (see the [[Land cover types|Natural vegetation types]]), combinations of PFTs in an area/grid cell are translated into a certain biome type (see figure on the right: Biome classification). In the IMAGE framework there is one modification to LPJml, namely the biome ‘ice’, for biomes initially defined as ‘arctic tundra’, and with an average annual temperature of < -2 oC and an annual net primary production (NPP) of < 1 Pg.yr-1. All carbon pools and fluxes in this biome are set to zero. | ||
{{FigureRightTemplate|Biome classification flowchart NVCC}} | {{FigureRightTemplate|Biome classification flowchart NVCC}} | ||
==Carbon dynamics== | ===Carbon dynamics=== | ||
IMAGE-LPJmL covers the carbon cycle processes, described in the | IMAGE-LPJmL covers the carbon cycle processes, described in the [[Natural_vegetation_and_carbon_cycle|introduction]], and tracks all carbon fluxes between the atmosphere and the biosphere. Carbon-cycle dynamics of the terrestrial biosphere are computed as the carbon uptake and release in plants (photosynthesis, autotrophic respiration), transfer of plant carbon to the soil (shedding of leaves, turnover, mortality of plants) and the mineralisation of soil organic matter (heterotrophic respiration; see Figure 6.1.1). Because the photosynthesis, autotrophic respiration and mineralisation of soil organic matter strongly depend on weather conditions, these processes are computed in time steps of one day. The composition of natural vegetation is dependent on slower processes, such as the interannual and interseasonal variability of weather conditions and disturbance incidences, such as natural fires. Therefore, vegetation dynamics, including competition between plant functional types, mortality, turnover, and fire disturbances are computed in time steps of one year. Allocation of newly established biomass is computed in time steps of one year for perennial plants (natural grasses, trees) and in time steps of one day for annual plants (crops). Allocation to plant organs (represented by a carbon pool for each) distinguishes up to four living plant carbon pools, depending on plant type. For grasses, the model distinguishes carbon pools of leaves and roots only, and for trees, there are two additional woody carbon pools (hardwood and sapwood), whereas for agricultural crops, the pools are categorised as leaves, roots, storage organs, stems, and a mobile reserve pool. For the simulation of the different mineralisation rates of soil organic carbon, three soil carbon pools are distinguished in the model: one for litter and two for soil organic matter of fast (10 years) and slow (100 years) mineralisation rates. Harvested agricultural products (crops, grass, biofuels) are assumed to be consumed or combusted with the related CO2 emitted to the atmosphere within the same year. Residues are either left on the fields to enter the litter pool or are removed to subsequently decompose (scenario setting). During wood harvesting, certain fraction of the plant pools are cut-down and harvested, as determined in the forest management model (Section 4.2.2), the waste is left behind to enter the soil litter pool as dead biomass. Wood products are distinguished into three classes, in order to account for their various lifespans: pulp and paper have fast turnover rates; timber products, such as furniture, have longer turnover rates (Lauk et al., 2012); and traditional biomass that is used as an energy source and emitted within the same year. All land-use dynamics, including the expansion or abandonment of pastures, cropland and bio-energy plantations, as well as wood harvested from natural vegetation are determined annually by the IMAGE land-use module (Section 4.2). | ||
==Model linkage and simulation procedure== | ===Model linkage and simulation procedure=== | ||
The technical link between LPJmL and IMAGE is established via an interface and starts in the simulation year of 1970. Before the coupled simulation is started, vegetation and soil carbon pools need to be initialised. This is achieved by using LPJmL first in a 1000-year spin-up in order to initialise the natural ecosystems and their carbon pools and fluxes. This is followed by a 390-year spin-up, in which the agricultural land is gradually expanded based on historical HYDE land-use data (Klein Goldewijk et al., 2011). Timber product pool sizes of 1970 are based on literature estimates (Lauk et al., 2012). The coupled IMAGE-LPJmL simulations start in 1970 with observed climate, followed by simulated climate for the years from 2000 onwards (Section 6.5). As the interannual variability of weather conditions is needed for the simulation of vegetation dynamics in IMAGE-LPJmL, smooth annual climate trends from IMAGE are superimposed by interannual variability fields, extracted from observed climate over the 1971–2000 period. To avoid repeating climate trends within these 30-year periods, annual anomalies are ordered at random before superimposition. | The technical link between LPJmL and IMAGE is established via an interface and starts in the simulation year of 1970. Before the coupled simulation is started, vegetation and soil carbon pools need to be initialised. This is achieved by using LPJmL first in a 1000-year spin-up in order to initialise the natural ecosystems and their carbon pools and fluxes. This is followed by a 390-year spin-up, in which the agricultural land is gradually expanded based on historical HYDE land-use data (Klein Goldewijk et al., 2011). Timber product pool sizes of 1970 are based on literature estimates (Lauk et al., 2012). The coupled IMAGE-LPJmL simulations start in 1970 with observed climate, followed by simulated climate for the years from 2000 onwards (Section 6.5). As the interannual variability of weather conditions is needed for the simulation of vegetation dynamics in IMAGE-LPJmL, smooth annual climate trends from IMAGE are superimposed by interannual variability fields, extracted from observed climate over the 1971–2000 period. To avoid repeating climate trends within these 30-year periods, annual anomalies are ordered at random before superimposition. | ||
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Revision as of 10:58, 7 January 2014
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