MAgPIE - An Open Source land-use modeling framework

4.6.3

created with goxygen 1.3.2

Forestry (32_forestry)

Description

The forestry module describes the constraints under which managed forest (age-class forest) exists. At the same time it calculates the corresponding carbon stocks and biodiversity value. The module provides carbon dioxide removal (CDR) from afforestation to the GHG policy module (56_ghg_policy) as well as afforestation related costs to the costs module (11_costs).

Interfaces

Interfaces to other modules

Input

module inputs (A: dynamic_feb21)
  Description Unit A
fm_bii_coeff
(bii_class44, potnatveg)
Biodiversity Intactness Index coefficients \(unitless\) x
fm_carbon_density
(t_all, j, land, c_pools)
LPJmL carbon density for land and carbon pools \(tC/ha\) x
fm_luh2_side_layers
(j, luh2_side_layers10)
luh2 side layers \(grid cell share\) x
im_plantedclass_ac
(j, ac)
Raw Distribution of ageclass in secondary forest as a proxy for planted forest \(10^6 ha\) x
pcm_land
(j, land)
Land area in previous time step including possible changes after optimization \(10^6 ha\) x
pm_carbon_density_ac
(t_all, j, ac, ag_pools)
Above ground natveg carbon density for age classes and carbon pools \(tC/ha\) x
pm_carbon_density_ac_forestry
(t_all, j, ac, ag_pools)
Above ground plantation carbon density for age classes and carbon pools \(tC/ha\) x
pm_demand_forestry_future
(i, kforestry)
Future forestry demand in current time step \(tDM/yr\) x
pm_interest
(t_all, i)
Interest rate in each region and timestep \(\%/yr\) x
pm_land_conservation
(t, j, land, consv_type)
Land protection and restoration for all land types \(10^6 ha\) x
pm_land_start
(j, land)
Land initialization area \(10^6 ha\) x
pm_selfsuff_ext
(t_ext, h, kforestry)
Self sufficiency for timber products in extended time frame \(1\) x
pm_timber_yield
(t, j, ac, forest_land)
Forest growing stock \(tDM/ha/yr\) x
pm_timber_yield_initial
(j, ac, forest_land)
Initial Forest yield \(tDM/ha/yr\) x
sm_fix_SSP2 year until which all parameters are fixed to SSP2 values \(year\) x
sm_wood_density Representative wood density based on IPCC \(tDM/m3\) x
vm_bv
(j, landcover44, potnatveg)
Biodiversity stock for all land cover classes \(Mha\) x
vm_carbon_stock
(j, land, c_pools, stockType)
Carbon stock in vegetation soil and litter for different land types \(10^6 tC\) x
vm_land
(j, land)
Land area of the different land types \(10^6 ha\) x

Output

module outputs
  Description Unit
pm_representative_rotation
(t_all, i)
Representative regional rotation \(1\)
vm_cdr_aff
(j, ac, aff_effect)
Expected bgc (CDR) and local bph effects of afforestation depending on planning horizon \(10^6 tC\)
vm_cost_fore
(i)
Forestry costs \(10^6 USD\)
vm_landdiff_forestry Aggregated difference in forestry land compared to previous timestep \(10^6 ha\)
vm_prod_forestry
(j, kforestry)
Production of woody biomass from commercial plantations \(10^6 tDM/yr\)

Realizations

(A) dynamic_feb21

The main feature of the this realization is afforestation for CDR and timber production. Afforestation can be modelled exogenously (prescribed by NPI/NDC policies) and/or endogenously (incentivized by a reward for CDR). National policies implemented (NPI) and nationally determined contributions to the Paris agreement (NDC) for afforestation are based on country reports. The interface vm_cdr_aff includes the expected CDR and local bph effects from afforestation depending on the planning horizon s32_planing_horizon. The reward for CDR and local bph effects from afforestation is calculated in the 56_ghg_policy module. In this realization, afforestation is modeled by default as regrowth of natural vegetation (see Humpenöder et al. (2014) for details on the implemenation). The regrowth of natural vegetation follows S-shaped growth curves, which are parametrized based on Braakhekke et al. (2019). Additionally this module handles the production of two timber products i.e., wood and woodfuel from plantation forests while still accounting for afforestation policies. New plantations are also established in the simulation step to account for future timber demand. This module also calculates the rotation lengths before the solve loop by maximizing current annual increment (CAI) based on Amacher, Ollikainen, and Koskela (2009). This rotation length calculation decision can also be changed to maximization of mean annual increment (MAI) or equating instantaneous growth rate (IGR) with interest rate. Rotation lengths calculated by maximization of CAI are empirically closer to economically optimal Faustmann rotation lengths (see Amacher, Ollikainen, and Koskela (2009)). For harvesting decisions we assume that land owners stick to their establishment decision, e.g. if a plantation has been established with a rotation length of 30 years it will be harvested after 30 years, even so the rotation length in the prevailing time step, used for establishment, is shorter or longer.

The direct costs of Timber production and afforestation vm_cost_fore include maintenance and monitoring costs for newly established plantations as well as standing plantations ’(Sathaye et al. 2005). In addition, this type of forest management (including afforestation) may cause costs in other parts of the model such as costs for technological change 13_tc or land expansion 39_landconversion. Also included are additional costs for producing timber from extremely highly managed plantations which are analogous to intensification using technological change from 13_tc but in a parametrized form.

\[\begin{multline*} vm\_cost\_fore(i2) = v32\_cost\_recur(i2) + v32\_cost\_establishment(i2) + v32\_cost\_hvarea(i2) + \sum_{cell(i2,j2)} v32\_land\_missing(j2) \cdot s32\_free\_land\_cost \end{multline*}\]

The interface vm_cdr_aff provides the projected biogeochemical (bgc) carbon sequestration and the local biophysical (bph) warming/cooling effects of an afforestation activity for a planning horizon of 50 years s32_planing_horizon to the 56_ghg_policy module.

\[\begin{multline*} vm\_cdr\_aff(j2,ac,"bgc") = \sum_{ac\_est} v32\_land(j2,"aff",ac\_est) \cdot \sum_{ct} p32\_cdr\_ac(ct,j2,ac) \end{multline*}\]

\[\begin{multline*} vm\_cdr\_aff(j2,ac,"bph") = \sum_{ac\_est} v32\_land(j2,"aff",ac\_est) \cdot p32\_aff\_bgp(j2,ac) \end{multline*}\]

ac_est can only increase if total afforested land increases

\[\begin{multline*} \sum_{ac\_est} v32\_land(j2,"aff",ac\_est) \leq \sum_{ac} v32\_land(j2,"aff",ac) - \sum_{ct,ac} p32\_land(ct,j2,"aff",ac) \end{multline*}\]

The interface vm_land provides aggregated forestry land pools (type32) to other modules.

\[\begin{multline*} vm\_land(j2,"forestry") = \sum_{type32,ac} v32\_land(j2,type32,ac) \end{multline*}\]

The constraint q32_aff_pol accounts for the exogenous afforestation prescribed by NPI/NDC policies.

\[\begin{multline*} \sum_{ac\_est} v32\_land(j2,"ndc",ac\_est) = \sum_{ct} p32\_aff\_pol\_timestep(ct,j2) \end{multline*}\]

The constraint q32_max_aff accounts for the allowed maximum global endogenous afforestation defined in i32_max_aff_area_glo. The constraint q32_max_aff_reg accounts for the allowed maximum regional endogenous afforestation defined in i32_max_aff_area_reg. Only one of the two constraints is active, depending on s32_max_aff_area_glo.

\[\begin{multline*} \sum_{j2,ac} v32\_land(j2,"aff",ac) \leq \sum_{ct} i32\_max\_aff\_area\_glo(ct) \end{multline*}\]

\[\begin{multline*} \sum_{cell(i2,j2),ac} v32\_land(j2,"aff",ac) \leq \sum_{ct} i32\_max\_aff\_area\_reg(ct,i2) \end{multline*}\]

Forestry above ground carbon stocks are calculated as the product of forestry land (v32_land) and the area weighted mean of carbon density for carbon pools (p32_carbon_density_ac).

\[\begin{multline*} vm\_carbon\_stock(j2,"forestry",ag\_pools,stockType) = m\_carbon\_stock\_ac(v32\_land,p32\_carbon\_density\_ac,"type32,ac","type32,ac\_sub") \end{multline*}\]

Forestry land expansion and reduction is calculated as follows:

\[\begin{multline*} vm\_landdiff\_forestry = \sum_{j2,type32,ac}\left( v32\_land\_expansion(j2,type32,ac) + v32\_land\_reduction(j2,type32,ac)\right) \end{multline*}\]

\[\begin{multline*} v32\_land\_expansion(j2,type32,ac\_est) = v32\_land(j2,type32,ac\_est) - pc32\_land(j2,type32,ac\_est) \end{multline*}\]

\[\begin{multline*} v32\_land\_reduction(j2,type32,ac\_sub) = pc32\_land(j2,type32,ac\_sub) - v32\_land(j2,type32,ac\_sub) \end{multline*}\]

\[\begin{multline*} vm\_bv(j2,"aff\_co2p",potnatveg) = \sum_{bii\_class\_secd}\left( \sum\left(ac\_to\_bii\_class\_secd(ac,bii\_class\_secd), v32\_land(j2,"aff",ac)\right) \cdot p32\_bii\_coeff("aff",bii\_class\_secd,potnatveg)\right) \cdot fm\_luh2\_side\_layers(j2,potnatveg) \end{multline*}\]

\[\begin{multline*} vm\_bv(j2,"aff\_ndc",potnatveg) = \sum_{bii\_class\_secd}\left( \sum\left(ac\_to\_bii\_class\_secd(ac,bii\_class\_secd), v32\_land(j2,"ndc",ac)\right) \cdot p32\_bii\_coeff("ndc",bii\_class\_secd,potnatveg)\right) \cdot fm\_luh2\_side\_layers(j2,potnatveg) \end{multline*}\]

\[\begin{multline*} vm\_bv(j2,"plant",potnatveg) = \sum_{bii\_class\_secd}\left( \sum\left(ac\_to\_bii\_class\_secd(ac,bii\_class\_secd), v32\_land(j2,"plant",ac)\right) \cdot p32\_bii\_coeff("plant",bii\_class\_secd,potnatveg)\right) \cdot fm\_luh2\_side\_layers(j2,potnatveg) \end{multline*}\]

Cost of new plantations establishment v32_cost_establishment is the investment made in setting up new plantations but also accounts for the expected value of future harvesting costs. This makes sure that the model sticks to reasonable plantation patterns over time. Present value of harvesting costs is (1+pm_interest)^p32_rotation_regional and annuity factor of pm_interest/(1+pm_interest) averages the cost of this investment over time.

\[\begin{multline*} v32\_cost\_establishment(i2) = \left(\sum_{cell(i2,j2),type32,ac\_est}\left( v32\_land(j2,type32,ac\_est) \cdot s32\_reESTBcost\right) \right) \cdot \sum_{ct}\left(\frac{pm\_interest(ct,i2)}{\left(1+pm\_interest(ct,i2)\right)}\right) \end{multline*}\]

Recurring costs are paid for plantations where the trees have to be regularly monitored and maintained. These costs are only calculated becuase we see active human intervention in commercial plantations. These costs are paid for trees used for timber production or trees established for afforestation purposes.

\[\begin{multline*} v32\_cost\_recur(i2) = \sum_{cell(i2,j2),type32,ac\_sub} v32\_land(j2,type32,ac\_sub) \cdot s32\_recurring\_cost \end{multline*}\]

New plantations are already established in the optimization step based on a certain percentage (p32_plantation_contribution) of current demand (pm_demand_forestry_future). Its called pm_demand_forestry_future because the model also has a foresight switch which give the model an ability to account for future changes in demand. By default pm_demand_forestry_future is set to existing roundwood demand. As plantation establishment decisions should also know some indication of expected future yields, we calculate how much yield newly established plantation can realize based on rotation lengths. This is defined as the expected future yield (pc32_yield_forestry_future) at harvest (year in time step are accounted for). Area constraint for plantation establishment based on expected average regional timber yield at rotation age (pc32_yield_forestry_future_reg) to ovoid overspecialization of plantation establishment towards highly productive cells.

\[\begin{multline*} \sum_{cell(i2,j2)}\left( \left(\frac{\left(\sum\left(ac\_est, v32\_land(j2,"plant",ac\_est)\right) + v32\_land\_missing(j2)\right) }{ m\_timestep\_length\_forestry}\right) \cdot pc32\_yield\_forestry\_future\_reg(i2)\right) = \sum_{ct,kforestry}\left( pm\_demand\_forestry\_future(i2,kforestry) \cdot min\left(s32\_max\_self\_suff, \sum_{supreg(h2,i2)}pm\_selfsuff\_ext(ct,h2,kforestry)\right) \cdot p32\_plantation\_contribution(ct,i2) \cdot f32\_estb\_calib(i2)\right) \end{multline*}\]

Constraint to maintain the average regional timber yield at rotation age, accounting for the cellular timber yield (pc32_yield_forestry_future).

\[\begin{multline*} \sum_{cell(i2,j2)}\left( \left(\sum\left(ac\_est, v32\_land(j2,"plant",ac\_est)\right)+v32\_land\_missing(j2)\right) \cdot pc32\_yield\_forestry\_future(j2)\right) = pc32\_yield\_forestry\_future\_reg(i2) \cdot \left(\sum_{cell(i2,j2)}\left( \sum\left(ac\_est, v32\_land(j2,"plant",ac\_est)\right)+v32\_land\_missing(j2)\right)\right) \end{multline*}\]

If plantations have to be static (defined by s32_establishment_static) then the model simply establishes the amount of plantations which are harvested. this keeps the plantation area static but accounts for age-class changes and regrowth during every time step.

\[\begin{multline*} \sum_{ac} v32\_land(j2,"plant",ac) = \sum_{ac} pc32\_land(j2,"plant",ac) \end{multline*}\]

This constraint distributes additions to forestry land over ac_est, which depends on the time step length (e.g. ac0 and ac5 for a 10 year time step).

\[\begin{multline*} v32\_land(j2,type32,ac\_est) = \frac{ \sum_{ac\_est2} v32\_land(j2,type32,ac\_est2)}{card(ac\_est2)} \end{multline*}\]

Change in forestry area is the difference between plantation area from previous time step (‘pc32_land’) and optimized plantation area from current time step (‘v32_land’)

\[\begin{multline*} v32\_hvarea\_forestry(j2,ac\_sub) \leq v32\_land\_reduction(j2,"plant",ac\_sub) \end{multline*}\]

Woody biomass production from timber plantations is calculated by multiplying the area under production with corresponding yields of plantation forests, divided by the timestep length.

\[\begin{multline*} \sum_{kforestry} vm\_prod\_forestry(j2,kforestry) = \frac{ \sum_{ac\_sub}\left( v32\_hvarea\_forestry(j2,ac\_sub) \cdot \sum\left(ct, pm\_timber\_yield(ct,j2,ac\_sub,"forestry")\right)\right) }{ m\_timestep\_length\_forestry} \end{multline*}\]

Harvesting cost in plantations is defined as the cost incurred while removing biomass from such forests.

\[\begin{multline*} v32\_cost\_hvarea(i2) = \sum_{ct,cell(i2,j2),ac\_sub} v32\_hvarea\_forestry(j2,ac\_sub) \cdot s32\_harvesting\_cost \end{multline*}\]

Afforestation switch: 0 = Use natveg growth curve towards LPJmL natural vegetation 1 = Use plantation growth curve (faster than natveg) towards LPJmL natural vegetation

if(s32_aff_plantation = 0,
 p32_carbon_density_ac(t,j,"aff",ac,ag_pools) = pm_carbon_density_ac(t,j,ac,ag_pools);
elseif s32_aff_plantation = 1,
 p32_carbon_density_ac(t,j,"aff",ac,ag_pools) = p32_c_density_ac_fast_forestry(t,j,ac);
);

Timber plantations carbon densities:

p32_carbon_density_ac(t,j,"plant",ac,ag_pools) = pm_carbon_density_ac_forestry(t,j,ac,ag_pools);

NDC carbon densities are natveg carbon densities.

p32_carbon_density_ac(t,j,"ndc",ac,ag_pools) = pm_carbon_density_ac(t,j,ac,ag_pools);

CDR from afforestation for each age-class, depending on planning horizon.

p32_cdr_ac(t,j,ac)$(ord(ac) > 1 AND (ord(ac)-1) <= s32_planing_horizon/5)
= p32_carbon_density_ac(t,j,"aff",ac,"vegc") - p32_carbon_density_ac(t,j,"aff",ac-1,"vegc");
if((ord(t) = 1),
 pc32_land(j,type32,ac) = p32_land_start_ac(j,type32,ac);
else
 pc32_land(j,type32,ac) = p32_land(t-1,j,type32,ac);
);
p32_disturbance_loss_ftype32(t,j,"aff",ac_sub) = pc32_land(j,"aff",ac_sub) * f32_forest_shock(t,"%c32_shock_scenario%") * m_timestep_length;
pc32_land(j,"aff",ac_est) = pc32_land(j,"aff",ac_est) + sum(ac_sub,p32_disturbance_loss_ftype32(t,j,"aff",ac_sub))/card(ac_est);
pc32_land(j,"aff",ac_sub) = pc32_land(j,"aff",ac_sub) - p32_disturbance_loss_ftype32(t,j,"aff",ac_sub);

Regrowth of natural vegetation (natural succession) is modelled by shifting age-classes according to time step length. For first year of simulation, the shift is just 1. Division by 5 happends because the age-classes exist in 5 year steps

s32_shift = m_yeardiff_forestry(t)/5;

Exchange land information after optimization

p32_land(t,j,type32,ac) = v32_land.l(j,type32,ac);

Limitations Rotation lengths for timber plantations are not endogenous.

Definitions

Objects

module-internal objects (A: dynamic_feb21)
  Description Unit A
f32_ac_dist
(ac)
Age class distribution share \(1\) x
f32_aff_bgp
(j, bgp32)
Biogeophysical temperature change of afforestation \(degree C\) x
f32_aff_mask
(j)
afforestation mask \(binary\) x
f32_aff_pol
(t_all, j, pol32)
npi+ndc afforestation policy \(Mha new forest wrt to 2010\) x
f32_estb_calib
(i)
Calibration factor for plantation forest establishment \(1\) x
f32_forest_shock
(t_all, shock_scen32)
Forest carbon shock scenarios \(area share affected/year\) x
f32_gs_relativetarget
(i)
Relative growing stock target in each region \(m3/ha\) x
f32_max_aff_area
(i)
Maximum regional afforestation area \(10^6 ha\) x
f32_plant_prod_share
(t_all)
Share of overall production coming from plantations \(1\) x
f32_plantation_contribution
(t_ext, i, inter32, scen32)
Share of roundwood production coming from timber plantations \(percent\) x
f32_plantedforest
(i)
Share of plantation forest in planted forest \(1\) x
f32_tcre
(j, tcre32)
Transient surface temperature response to CO2 emission \(degree C/tC/ha\) x
i32_max_aff_area_glo
(t)
Maximum global endogenous afforestation area \(10^6 ha\) x
i32_max_aff_area_reg
(t, i)
Maximum regional endogenous afforestation area \(10^6 ha\) x
p32_ac_dist
(j, ac)
Actual share of age-class distribution \(1\) x
p32_ac_dist_flag
(j, ac)
Distribution flag with inverse weights according to age-classes \(1\) x
p32_aff_bgp
(j, ac)
Biophysical impact of afforestation \(tCeq/ha\) x
p32_aff_pol
(t, j)
NDC forest stock \(10^6 ha\) x
p32_aff_pol_timestep
(t, j)
NDC afforestation per time step \(10^6 ha\) x
p32_aff_pot
(t, j)
Potential afforestation area \(10^6 ha\) x
p32_aff_togo
(t, i)
Remaining exogenous afforestation wrt to the maximum exogenous target over time \(10^6 ha\) x
p32_avg_increment
(t_all, j, ac)
Mean annual increment \(tC/ha/year\) x
p32_bii_coeff
(type32, bii_class_secd, potnatveg)
bii coeff \(1\) x
p32_c_density_ac_fast_forestry
(t_all, j, ac)
Carbon densities in plantations based on Braakhekke et al \(tC/ha\) x
p32_carbon_density_ac
(t, j, type32, ac, ag_pools)
Carbon density for ac and ag_pools \(tC/ha\) x
p32_carbon_density_ac_forestry
(t_all, j, ac)
Above ground carbon density for age classes and carbon pools \(tC/ha\) x
p32_carbon_density_ac_marg
(t_all, j, ac)
Marginal above ground carbon density for age classes and carbon pools \(tC/ha\) x
p32_cdr_ac
(t, j, ac)
Non-cumulative CDR from afforestation plantations for each age-class depending on planning horizon \(tC/ha\) x
p32_discount_factor
(t_all, j, ac)
Discount factor for each age class \(1\) x
p32_disturbance_loss_ftype32
(t, j, type32, ac)
Loss due to disturbances in all plantation type forests \(10^6 ha\) x
p32_gs_scaling_reg
(i)
Calibration factor for scaling up the relative growing stock \(1\) x
p32_IGR
(t_all, j, ac)
Instantaneous growth rate or periodic annual increment of forest growth \(1\) x
p32_investment_returns_lost
(t_all, j, ac)
Present value of investment returns lost by not harvesting now and beginning a new series of rotations on the land \(10^6 USD\) x
p32_land
(t, j, type32, ac)
Forestry land for each cell wood type and age class before and after optimization \(10^6 ha\) x
p32_land_before
(t, j, type32, ac)
Saving time value of starting land \(10^6 ha\) x
p32_land_rent_weighted
(t_all, j, ac)
Land rent weighted by the value of the trees at harvest age-class \(10^6 USD\) x
p32_land_start_ac
(j, type32, ac)
Saving first value of starting land \(10^6 ha\) x
p32_ncells
(i)
Number of cells in each region \(1\) x
p32_net_present_value
(t_all, j, ac)
Net present value for a representative 1ha land of plantations \(10^6 USD\) x
p32_observed_gs_reg
(i)
Observed growing stock \(tDM/ha\) x
p32_plant_ini_ac
(j)
Initialization of plantation area \(10^6 ha\) x
p32_plantation_contribution
(t_ext, i)
Share of roundwood production coming from timber plantations \(percent\) x
p32_rot_flg
(t_all, j, ac)
Identifier flag when calculating rotation length \(1\) x
p32_rot_flg_faustmann
(t_all, j, ac)
Identifier flag when calculating faustmann rotation length \(1\) x
p32_rot_length_ac_eqivalent
(t_all, j)
Cellular rotation length of plantations translated to age class equivalent for future \(1\) x
p32_rot_length_faustmann
(t_all, j)
Cellular Faustmann rotation length of plantations translated to age class equivalent \(1\) x
p32_rotation_cellular_estb
(t_all, j)
Establishment rotation length translated to age classes on cellular level \(1\) x
p32_rotation_cellular_harvesting
(t_all, j)
Harvesting rotation length of plantations translated to age class equivalent for future \(1\) x
p32_rotation_dist
(j, ac)
Poulter distribution within celular rotation lengths \(1\) x
p32_rotation_offset Offset calc in age class equivalents \(1\) x
p32_rotation_regional
(t_all, i)
Regional average rotation length of plantations translated to age class equivalent for future \(1\) x
p32_stand_value
(t_all, j, ac)
Stand value based on given prices \(10^6 USD\) x
p32_tcre_glo
(j)
Global mean Transient Climate Response to cumulative Emissions \(degree C/tC/ha\) x
p32_time
(ac)
Time as a function of age-classes \(yr\) x
p32_updated_gs_reg
(t, i)
Updated growing stock information after calibration \(m3/ha\) x
pc32_area_rotation
(j)
Forestry area at rotation length end used as weight for regional aggregation \(10^6 ha\) x
pc32_land
(j, type32, ac)
Forestry land per forestry land type initialization of the optimization \(10^6 ha\) x
pc32_yield_forestry_future
(j)
Cellular timber yield expected in the future \(m3/ha/year\) x
pc32_yield_forestry_future_reg
(i)
Regional timber yield expected in the future \(m3/ha/year\) x
q32_aff_est
(j)
Afforestation constraint for establishment age classes \(10^6 ha\) x
q32_aff_pol
(j)
Afforestation policy constraint \(10^6 ha\) x
q32_bgp_aff
(j, ac)
Biophysical afforestation calculation \(10^6 tCeq\) x
q32_bv_aff
(j, potnatveg)
Biodiversity value for aff forestry land \(Mha\) x
q32_bv_ndc
(j, potnatveg)
Biodiversity value for ndc forestry land \(Mha\) x
q32_bv_plant
(j, potnatveg)
Biodiversity value for plantations \(Mha\) x
q32_carbon
(j, ag_pools, stockType)
Forestry carbon stock calculation \(10^6 tC\) x
q32_cdr_aff
(j, ac)
Calculation of CDR from afforestation \(10^6 tC\) x
q32_cost_establishment
(i)
Present value of cost of establishment \(10^6 USD\) x
q32_cost_hvarea
(i)
Cost of harvesting timber from forests \(10^6 USD/yr\) x
q32_cost_recur
(i)
Recurruing costs \(10^6 USD\) x
q32_cost_total
(i)
Total forestry costs constraint \(10^6 USD\) x
q32_establishment_dynamic
(i)
Establishment in current time step for future demand \(10^6 ha\) x
q32_establishment_dynamic_yield
(i)
Regional timber yield \(tDM/ha\) x
q32_establishment_fixed
(j)
Establishment in current time step for future demand \(10^6 ha\) x
q32_forestry_est
(j, type32, ac)
Distribution of forestry establishment over ac_est \(10^6 ha\) x
q32_hvarea_forestry
(j, ac)
Plantations area harvest \(10^6 ha\) x
q32_land
(j)
Land constraint \(10^6 ha\) x
q32_land_diff Aggregated difference in forestry land compared to previous timestep \(10^6 ha\) x
q32_land_expansion
(j, type32, ac)
Land expansion \(10^6 ha\) x
q32_land_reduction
(j, type32, ac)
Land contraction \(10^6 ha\) x
q32_max_aff Maximum total global afforestation \(10^6 ha\) x
q32_max_aff_reg
(i)
Maximum total regional afforestation \(10^6 ha\) x
q32_prod_forestry
(j)
Production of woody biomass from commercial plantations \(10^6 tDM/yr\) x
s32_aff_bii_coeff BII coefficent to be used for CO2 price driven afforestation 0=natural vegetation 1=plantation \(1\) x
s32_aff_plantation Switch for using growth curves for afforestation 0=natveg 1=plantations \(1\) x
s32_establishment_dynamic If plantations should be dynamic \(including establishment and harvest decsions\) x
s32_establishment_static Static plantations with no establishmnet no harvest no regrowth x
s32_faustmann_rotation Switch to activate faustmann rotations \(1=on 0=off\) x
s32_forestry_int_rate Global interest rate for plantations \(percent\) x
s32_free_land_cost Very high cost for using non existing land for plantation establishment \(USD/ha\) x
s32_harvesting_cost Harvesting cost \(USD/ha\) x
s32_hvarea Flag for harvested area and establishemt \(0=zero 1=exognous 2=endogneous\) x
s32_initial_distribution Switch to Activate ageclass distribution in plantations 0=off 1=equal distribution 2=FAO distribution 3=Poulter distribution 4=Manual distribution \(1\) x
s32_max_aff_area Maximum total global afforestation \(10^6 ha\) x
s32_max_aff_area_glo Switch for global or regional afforestation constraint \(1\) x
s32_max_self_suff Upper ceiling for the self sufficiency used in calculation for establishment decision \(1\) x
s32_planing_horizon Afforestation planing horizon \(years\) x
s32_price Price for timber \(USD\) x
s32_recurring_cost Recurring costs \(USD/ha\) x
s32_reESTBcost Re establishment cost \(USD/ha\) x
s32_rotation_extension Rotation extension factor 1=original rotations 2=100 percent increase in rotations etc \(1\) x
s32_shift Number of 5-year age-classes corresponding to current time step length \(1\) x
s32_tcre_local Switch for local (1) or global (0) TRCE factors \(1\) x
v32_cost_establishment
(i)
Cost of establishment calculated at the current time step \(10^6 USD\) x
v32_cost_hvarea
(i)
Cost of harvesting timber from forests \(10^6 USD/yr\) x
v32_cost_recur
(i)
Recurring forest management costs \(USD/ha\) x
v32_hvarea_forestry
(j, ac)
Harvested area from timber plantations \(10^6 ha\) x
v32_land
(j, type32, ac)
Forestry land pools \(10^6 ha\) x
v32_land_expansion
(j, type32, ac)
Forestry land expansion \(10^6 ha\) x
v32_land_missing
(j)
Forestry land which can be used at extrmemly high costs in case not enough area is available for new establishment \(10^6 ha\) x
v32_land_reduction
(j, type32, ac)
Forestry land reduction \(10^6 ha\) x

Sets

sets in use
  description
ac Age classes
ac_bph(ac) fade-in of bph effect over age-classes
ac_est(ac) Dynamic subset of age classes for establishment
ac_sub(ac) Dynamic subset of age classes excluding establishment
ac_to_bii_class_secd(ac, bii_class_secd) Mapping between forest ageclasses and bii coefficent land cover classes
aff_effect biochemical and local biophysical effect of afforestation on climate
ag_pools(c_pools) Above ground carbon pools
age Population age groups
bgp32 biogeophysical effect (degree C) of afforestation on local surface temperature
bii_class_secd(bii_class44) bii coefficent land cover classes secondary vegetation
bii_class44 bii coefficent land cover classes
c_pools Carbon pools
cell(i, j) number of LPJ cells per region i
consv_type Type of land conservation
ct(t) Current time period
factors factors included in factor requirements
fcosts32(fcostsALL) forestry factor cost per annum
fcostsALL forestry factor cost types
forest_land(land) land from which timber can be taken away
h all superregional economic regions
h2(h) Superregional (dynamic set)
i all economic regions
i2(i) World regions (dynamic set)
ini32(j, ac) subset for initialization of timber plantations
inter32 Interpolation of scenario from FAO study on proportion of roundwood production coming from plantations
j number of LPJ cells
j2(j) Spatial Clusters (dynamic set)
kforestry(k) forestry products
land Land pools
landcover44 land cover classes used in bii calculation
luh2_side_layers10 side layers from LUH2
pol32 afforestation policy type
potnatveg(luh2_side_layers10) potentially forested biomes
rotation_type Rotation type
scen32 Scenario for development of roundwood production share from plantations
shock_scen32 Scenario name of forest carbon shock
stockType Carbon stock types
supreg(h, i) mapping of superregions to its regions
t_all(t_ext) 5-year time periods
t_ext 5-year time periods
t_future(t_all) 5-year time periods
t_historical(t_all) Historical period
t(t_all) Simulated time periods
tcre32 transient surface temperature response to CO2 emission (degree C per tC)
type GAMS variable attribute used for the output
type32 plantation type

Authors

Florian Humpenöder, Abhijeet Mishra

See Also

09_drivers, 10_land, 11_costs, 12_interest_rate, 14_yields, 21_trade, 22_land_conservation, 29_ageclass, 44_biodiversity, 52_carbon, 56_ghg_policy, 73_timber

References

Amacher, Gregory S, Markku Ollikainen, and Erkki Koskela. 2009. Economics of Forest Resources. Mit Press Cambridge.
Braakhekke, Maarten C., Jonathan C. Doelman, Peter Baas, Christoph Müller, Sibyll Schaphoff, Elke Stehfest, and Detlef P. van Vuuren. 2019. “Modelling Forest Plantations for Carbon Uptake with the LPJmL Dynamic Global Vegetation Model.” Earth System Dynamics Discussions, April, 1–24. https://doi.org/https://doi.org/10.5194/esd-2019-13.
Humpenöder, Florian, Alexander Popp, Jan Philip Dietrich, David Klein, Hermann Lotze-Campen, Markus Bonsch, Benjamin Leon Bodirsky, Isabelle Weindl, Miodrag Stevanovic, and Christoph Müller. 2014. “Investigating Afforestation and Bioenergy CCS as Climate Change Mitigation Strategies.” Environmental Research Letters 9 (6): 064029. https://doi.org/10.1088/1748-9326/9/6/064029.
Sathaye, Jayant, Willy Makundi, Larry Dale, Peter Chan, and Kenneth Andrasko. 2005. GHG Mitigation Potential, Costs and Benefits in Global Forests: A Dynamic Partial Equilibrium Approach.” Lawrence Berkeley National Laboratory, March. http://escholarship.org/uc/item/92d5m16v.