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Impact model: 4C

The model 4C (‘FORESEE’-Forest Ecosystems in a Changing Environment) has been developed to describe long-term forest behaviour under changing environmental conditions. It describes processes on tree and stand level based on findings from eco-physiological experiments, long term observations and physiological modelling. The model includes descriptions of tree species composition, forest structure, total ecosystem carbon content as well as leaf area index. The model shares a number of features with gap models, which have often been used for the simulation of long-term forest development. Establishment, growth and mortality of tree cohorts are explicitly modelled on a patch on which horizontal homogeneity is assumed. Currently the model is parameterised for the five most abundant tree species of Central Europe (beech (Fagus sylvatica L.), Norway spruce (Picea abies L. Karst.), Scots pine (Pinus sylvestris L.), oaks ( Quercus robur L., and Quercus petraea Liebl.), and birch (Betula pendula Roth)) as well as other tree species, namely aspen (Populus tremula (L.), P. tremuloides (Michx.)), Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), black locust (Robinia pseudoacacia L.), Aleppo pine (Pinus halepensis Mill.), Ponderosa pine (Pinus ponderosa Dougl.), and Lodgepole pine (Pinus contorta Dougl.).

Sector
Forests
Region
regional
Contact Person

Information for the model 4C is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Basic information
Model Version: 4C 2.1
Reference Paper: Other References:
Person Responsible For Model Simulations In This Simulation Round: Petra Lasch, lasch@pik-potsdam.de
Resolution
Spatial Aggregation: forest stand
Temporal Resolution Of Input Data: Climate Variables: daily
Temporal Resolution Of Input Data: Co2: annual
Temporal Resolution Of Input Data: Land Use/Land Cover: annual
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Simulated Atmospheric Climate Data Sets Used: IPSL-CM5A-LR, HadGEM2-ES, GFDL-ESM2M, MIROC5
Emissions Data Sets Used: CO2 concentration
Other Human Influences Data Sets Used: Nitrogen deposition
Climate Variables: ta, tas, tasmin, sfcWind, rhs, rsds, ps, pr
Spin-up
Was A Spin-Up Performed?: No
Management & Adaptation Measures
Management: thinning from below or from above according to targets of stem biomass or stem number or relative targets of stem biomass planting, natural regeneration short-rotation coppice
Extreme Events & Disturbances
Key Challenges: drought stress
Key model processes
dynamic vegetation: yes: Forest dynamics are described by forest growth, regeneration/planting, management.
nitrogen limitation: yes Different approaches are used to estimate the nitrogen depending reduction of NPP. Nitrogen supply is calculated by a soil model (water, temperature, C/N module) from the soil conditions, the litter input and nitrogen uptake and leaching.
CO2 effects: The annual course of net photosynthesis is simulated with a mechanistic formulation of net photosynthesis as a function of environmental influences (temperature, water and nitrogen availability, radiation, and CO2) where the physiological capacity (maximal carboxylation rate) is calculated based on optimisation theory (modified after Haxeltine and Prentice, 1996) plus calculation of total tree respiration following the concept of constant annual respiration fraction as proposed by Landsberg and Waring (1997).
light interception: yes: The share of any tree cohort in the total stand’s net photosynthetic assimilation of carbon is proportional to its share of the absorbed photosynthetically active radiation. The total fraction of photosynthetically active radiation absorbed by each tree cohort is calculated each time stand phenology changes, based on the Lambert-Beer law. Four models exist to calculate light transmission and absorption through the canopy.
light utilization: Light use efficiency is calculated according to Haxeltine and Prentice (1996).
phenology: yes: The phenological approach in 4C is based on the interaction of inhibitory and promotory agents that are assumed to control the developmental status of a plant. The agents are driven by temperature and photoperiod, which play the most prominent role in phenology. Using these simple but basic principles a model for the abundance or concentration of an inhibitory and a promotory compound made of a system of two difference equations is used (Schaber and Badeck, 2003).
water stress: yes: After calculating water demand by forest stand and water supply from the soil for each tree cohort photosynthesis is being reduced if demand is greater than supply. Allocation is also affected.
Evapo-transpiration approach: yes: Different approaches are used: Turc/Ivanov, Priestley/Taylor, Penman/ Monteith.
Differences in rooting depth: yes: The model uses a fixed site-specific rooting depth as input parameter depending on soil characteristics.
Root distribution over depth: yes 4C uses an approach according to Jackson (1996), which assumes an exponential decrease of fine root biomass with soil depth. Additionally, a site and species specific root distribution can be used as input.
closed energy balance: It is not considered.
Coupling/feedback between soil moisture and surface temperature: yes: 4C includes a coupled soil moisture and temperature model.
latent heat: Latent heat is not calculated.
sensible heat: Sensible heat is not calculated.
Causes of mortality in vegetation models
Age/Senescence: yes: The so called ‘age related’ mortality basing on life span corresponds to the intrinsic mortality developed by (Botkin, 1993).
Drought: yes: The response of trees to growth suppression by drought is described by a carbon-based stress mortality .
Insects: yes: Modelling of impacts of mistletoe, phloem feeder, defoliator, stem disturber, xylem disturber, root disturber is under construction.
Other: Self-thinning mortality due to light availability is implemented (stress mortality).
NBP components
Harvest: The model includes harvests and all fluxes caused by thinning and harvesting (litter fall, harvest pool). Harvested biomass is pooled into different carbon pools and later on released to the atmosphere e.g. by decomposition.
Other processes: Dead biomass which is not harvested is an input to the litter pool, where it is decomposed.
Species / Plant Functional Types (PFTs)
Comments: 4C uses tree species and parameters for 13 tree species.
Model output specifications
Output format: per forest stand/ per simulated forest unit
Additional Forest Information
Forest sites simulated: Soroe, Hyytiälä, KROOF, Solling beech, Solling spruce, Peitz, Colllelongo
Basic information
Model Version: 4C 2.1
Reference Paper: Other References:
Person Responsible For Model Simulations In This Simulation Round: Petra Lasch, lasch@pik-potsdam.de
Resolution
Temporal Resolution Of Input Data: Climate Variables: daily
Temporal Resolution Of Input Data: Co2: annual
Temporal Resolution Of Input Data: Land Use/Land Cover: annual
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Observed Atmospheric Climate Data Sets Used: GSWP3, Historical observed climate data, PGMFD v.2 (Princeton), WATCH (WFD), WATCH+WFDEI
Emissions Data Sets Used: CO2 concentration
Climate Variables: tasmax, tas, tasmin, rhs, rsds, ps, pr
Additional Input Data Sets: N deposition (EMEP)
Spin-up
Was A Spin-Up Performed?: No
Management & Adaptation Measures
Management: thinning from below or from above according to targets of stem biomass or stem number or relative targets of stem biomass planting, natural regeneration short-rotation coppice
Extreme Events & Disturbances
Key Challenges: drought stress
Key model processes
dynamic vegetation: yes: Forest dynamics are described by forest growth, regeneration/planting, management.
nitrogen limitation: yes Different approaches are used to estimate the nitrogen depending reduction of NPP. Nitrogen supply is calculated by a soil model (water, temperature, C/N module) from the soil conditions, the litter input and nitrogen uptake and leaching.
CO2 effects: The annual course of net photosynthesis is simulated with a mechanistic formulation of net photosynthesis as a function of environmental influences (temperature, water and nitrogen availability, radiation, and CO2) where the physiological capacity (maximal carboxylation rate) is calculated based on optimisation theory (modified after Haxeltine and Prentice, 1996) plus calculation of total tree respiration following the concept of constant annual respiration fraction as proposed by Landsberg and Waring (1997).
light interception: yes: The share of any tree cohort in the total stand’s net photosynthetic assimilation of carbon is proportional to its share of the absorbed photosynthetically active radiation. The total fraction of photosynthetically active radiation absorbed by each tree cohort is calculated each time stand phenology changes, based on the Lambert-Beer law. Four models exist to calculate light transmission and absorption through the canopy.
light utilization: Light use efficiency is calculated according to Haxeltine and Prentice (1996).
phenology: yes: The phenological approach in 4C is based on the interaction of inhibitory and promotory agents that are assumed to control the developmental status of a plant. The agents are driven by temperature and photoperiod, which play the most prominent role in phenology. Using these simple but basic principles a model for the abundance or concentration of an inhibitory and a promotory compound made of a system of two difference equations is used (Schaber and Badeck, 2003).
water stress: yes: After calculating water demand by forest stand and water supply from the soil for each tree cohort photosynthesis is being reduced if demand is greater than supply. Allocation is also affected.
Evapo-transpiration approach: yes: Different approaches are used: Turc/Ivanov, Priestley/Taylor, Penman/ Monteith.
Differences in rooting depth: yes: The model uses a fixed site-specific rooting depth as input parameter depending on soil characteristics.
Root distribution over depth: yes 4C uses an approach according to Jackson (1996), which assumes an exponential decrease of fine root biomass with soil depth. Additionally, a site and species specific root distribution can be used as input.
closed energy balance: It is not considered.
Coupling/feedback between soil moisture and surface temperature: yes: 4C includes a coupled soil moisture and temperature model.
latent heat: Latent heat is not calculated.
sensible heat: Sensible heat is not calculated.
Causes of mortality in vegetation models
Age/Senescence: yes: The so called ‘age related’ mortality basing on life span corresponds to the intrinsic mortality developed by (Botkin, 1993).
Drought: yes: The response of trees to growth suppression by drought is described by a carbon-based stress mortality .
Insects: yes: Modelling of impacts of mistletoe, phloem feeder, defoliator, stem disturber, xylem disturber, root disturber is under construction.
Other: Self-thinning mortality due to light availability is implemented (stress mortality).
NBP components
Harvest: The model includes harvests and all fluxes caused by thinning and harvesting (litter fall, harvest pool). Harvested biomass is pooled into different carbon pools and later on released to the atmosphere e.g. by decomposition.
Other processes: Dead biomass which is not harvested is an input to the litter pool, where it is decomposed.
Species / Plant Functional Types (PFTs)
Comments: 4C uses tree species and parameters for 13 tree species.
Model output specifications
Output format: per forest stand/ per simulated forest unit
Additional Forest Information
Forest sites simulated: Soroe, Hyytiälä, KROOF, Solling beech, Solling spruce, Peitz, Colllelongo
Basic information
Model Version: 4C 2.1
Reference Paper: Other References:
Person Responsible For Model Simulations In This Simulation Round: Petra Lasch, lasch@pik-potsdam.de
Resolution
Spatial Aggregation: forest stand
Temporal Resolution Of Input Data: Climate Variables: daily
Temporal Resolution Of Input Data: Co2: annual
Temporal Resolution Of Input Data: Land Use/Land Cover: annual
Temporal Resolution Of Input Data: Soil: constant
Input data sets used
Simulated Atmospheric Climate Data Sets Used: GCM atmospheric climate data (Fast Track)
Emissions Data Sets Used: CO2 concentration
Climate Variables: tasmax, tasmin, rhs, rsds, pr
Additional Input Data Sets: N deposition (EMEP)
Spin-up
Was A Spin-Up Performed?: No
Management & Adaptation Measures
Management: thinning from below or from above according to targets of stem biomass or stem number or relative targets of stem biomass planting, natural regeneration short-rotation coppice
Extreme Events & Disturbances
Key Challenges: drought stress
Key model processes
dynamic vegetation: yes: Forest dynamics are described by forest growth, regeneration/planting, management.
nitrogen limitation: yes Different approaches are used to estimate the nitrogen depending reduction of NPP. Nitrogen supply is calculated by a soil model (water, temperature, C/N module) from the soil conditions, the litter input and nitrogen uptake and leaching.
CO2 effects: The annual course of net photosynthesis is simulated with a mechanistic formulation of net photosynthesis as a function of environmental influences (temperature, water and nitrogen availability, radiation, and CO2) where the physiological capacity (maximal carboxylation rate) is calculated based on optimisation theory (modified after Haxeltine and Prentice, 1996) plus calculation of total tree respiration following the concept of constant annual respiration fraction as proposed by Landsberg and Waring (1997).
light interception: yes: The share of any tree cohort in the total stand’s net photosynthetic assimilation of carbon is proportional to its share of the absorbed photosynthetically active radiation. The total fraction of photosynthetically active radiation absorbed by each tree cohort is calculated each time stand phenology changes, based on the Lambert-Beer law. Four models exist to calculate light transmission and absorption through the canopy.
light utilization: Light use efficiency is calculated according to Haxeltine and Prentice (1996).
phenology: yes: The phenological approach in 4C is based on the interaction of inhibitory and promotory agents that are assumed to control the developmental status of a plant. The agents are driven by temperature and photoperiod, which play the most prominent role in phenology. Using these simple but basic principles a model for the abundance or concentration of an inhibitory and a promotory compound made of a system of two difference equations is used (Schaber and Badeck, 2003).
water stress: yes: After calculating water demand by forest stand and water supply from the soil for each tree cohort photosynthesis is being reduced if demand is greater than supply. Allocation is also affected.
Evapo-transpiration approach: yes: Different approaches are used: Turc/Ivanov, Priestley/Taylor, Penman/ Monteith.
Differences in rooting depth: yes: The model uses a fixed site-specific rooting depth as input parameter depending on soil characteristics.
Root distribution over depth: yes 4C uses an approach according to Jackson (1996), which assumes an exponential decrease of fine root biomass with soil depth. Additionally, a site and species specific root distribution can be used as input.
closed energy balance: It is not considered.
Coupling/feedback between soil moisture and surface temperature: yes: 4C includes a coupled soil moisture and temperature model.
latent heat: Latent heat is not calculated.
sensible heat: Sensible heat is not calculated.
Causes of mortality in vegetation models
Age/Senescence: yes: The so called ‘age related’ mortality basing on life span corresponds to the intrinsic mortality developed by (Botkin, 1993).
Drought: yes: The response of trees to growth suppression by drought is described by a carbon-based stress mortality .
Insects: yes: Modelling of impacts of mistletoe, phloem feeder, defoliator, stem disturber, xylem disturber, root disturber is under construction.
Other: Self-thinning mortality due to light availability is implemented (stress mortality).
NBP components
Harvest: The model includes harvests and all fluxes caused by thinning and harvesting (litter fall, harvest pool). Harvested biomass is pooled into different carbon pools and later on released to the atmosphere e.g. by decomposition.
Other processes: Dead biomass which is not harvested is an input to the litter pool, where it is decomposed.
Species / Plant Functional Types (PFTs)
Comments: 4C uses tree species and parameters for 13 tree species.
Model output specifications
Output format: per forest stand/ per simulated forest unit
Additional Forest Information
Forest sites simulated: Soroe, Hyytiälä, KROOF, Solling beech, Solling spruce, Peitz, Colllelongo




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