MAgPIE - An Open Source land-use modeling framework

4.14.0

created with goxygen 1.5.0

Timber (73_timber)

Description

This module provides demand for forestry products via the interface pm_demand_forestry to the modules 32_forestry and 62_material, and merges production of timber from different sources into the interface vm_prod, which is used in the 17_production and 21_trade modules.

Interfaces

Interface plot missing!

Input

module inputs (A: default)
  Description Unit A
im_gdp_pc_ppp_iso
(t_all, iso)
Per capita income in purchasing power parity \(USD_{17PPP}/cap/yr\) x
im_pop_iso
(t_all, iso)
Population \(10^6/yr\) x
im_vol_conv
(i)
Regional basic wood density \(tDM/m3\) x
sm_fix_SSP2 year until which all parameters are fixed to SSP2 values \(year\) x
vm_prod_forestry
(j, kforestry)
Production of woody biomass from commercial plantations \(10^6 tDM/yr\) x
vm_prod
(j, k)
Production in each cell \(10^6 tDM/yr\) x
vm_prod_natveg
(j, land_natveg, kforestry)
Production of woody biomass from natural vegetation \(10^6 tDM/yr\) x

Output

module outputs
  Description Unit
im_timber_prod_cost
(i, kforestry)
Regional base cost for timber production based on UNECE market prices \(USD_{17MER}/tDM\)
pm_demand_forestry
(t_ext, i, kforestry)
Extended demand for timber beyond simulation \(10^6 tDM/yr\)
vm_cost_timber
(i)
Actual cost of harvesting timber from forests \(10^6 USD_{17MER}/yr\)

Realizations

(A) default

In this realization, aggregated timber demand for wood and woodfuel pm_demand_forestry is calculated based on demand equation from Lauri et al. (2019) and income elasticities from Morland et al. (2018). See Mishra et al. (2021) for more details. This realization can also account for construction wood demand based on Churkina et al. (2020) which is added on top of industrial roundwood demand (see Mishra et al. (2022)). FAO demand volumes (m3) are converted to dry matter (tDM) using IPCC climate-zone-specific basic wood density (im_vol_conv). For woodfuel, a stacking factor (0.65) is applied before density conversion to correct for FAO reporting in stacked m3 rather than solid m3. Timber can be produced from both timber plantations vm_prod_forestry provided by 32_forestry and natural vegetation vm_prod_natveg provided by 35_natveg. Production costs differentiate between plantation and natural vegetation sources, with natveg paying a per-tDM premium reflecting higher extraction costs. Logging residues from both roundwood and woodfuel harvest can contribute to woodfuel supply.

Timber production cost has four components: 1. Base production cost: all timber (plantation + natveg) pays im_timber_prod_cost(i) per tDM, regionalized via wood density (source: 89/44 USD17MER/m3 for wood/woodfuel). 2. Natveg cost premium: natveg timber pays an additional s73_natveg_cost_premium (15%) on top of the base cost. This reflects higher processing costs for heterogeneous natural forest timber. When premium is zero, the term vanishes. 3. Residue removal cost: s73_residue_removal_cost (2.7 USD17MER/tDM) for collecting logging residues (branches, tops) from the harvest site. 4. Slack variable cost: s73_free_prod_cost (1e6 USD17MER/tDM) — prohibitively high cost for the slack variable v73_prod_heaven_timber, used only as a last resort to ensure technical feasibility when timber demand cannot be met from available forest resources.

\[\begin{multline*} vm\_cost\_timber(i2) = \sum_{cell(i2,j2),kforestry}\left( vm\_prod(j2,kforestry) \cdot im\_timber\_prod\_cost(i2,kforestry)\right) + \sum_{cell(i2,j2),land\_natveg,kforestry}\left( vm\_prod\_natveg(j2,land\_natveg,kforestry) \cdot \left(i73\_timber\_prod\_cost\_natveg(i2,kforestry) - im\_timber\_prod\_cost(i2,kforestry)\right)\right) + \sum_{cell(i2,j2)} v73\_prod\_residues(j2) \cdot s73\_residue\_removal\_cost + \sum_{cell(i2,j2),kforestry}\left( v73\_prod\_heaven\_timber(j2,kforestry) \cdot s73\_free\_prod\_cost\right) \end{multline*}\]

The following equations describes cellular level production (in dry matter) of woody biomass vm_prod as the sum of the cluster level production of timber coming from ‘vm_prod_forestry’ and ‘vm_prod_natveg’. When production capabilities are exhausted, the model can produce roundwood without using any land resources but by paying a very high cost (‘s73_free_prod_cost’). Timber production equation is split in two parts, one each for industrial roundwood and wood fuel production. Woodfuel production, in addition to usual production channels, can also use residues left from industrial roundwood harvest for meeting overall wood fuel production targets.

\[\begin{multline*} vm\_prod(j2,"wood") = vm\_prod\_forestry(j2,"wood") + \sum_{land\_natveg}vm\_prod\_natveg(j2,land\_natveg,"wood") + v73\_prod\_heaven\_timber(j2,"wood") \end{multline*}\]

\[\begin{multline*} vm\_prod(j2,"woodfuel") = vm\_prod\_forestry(j2,"woodfuel") + \sum_{land\_natveg}vm\_prod\_natveg(j2,land\_natveg,"woodfuel") + v73\_prod\_residues(j2) + v73\_prod\_heaven\_timber(j2,"woodfuel") \end{multline*}\]

Production of residues is calculated based on s73_residue_ratio. This fraction of total timber harvest is assumed to be recoverable as harvest residues (branches, tops, bark). The theoretical potential of logging residues is 27% of stem harvest (Oswalt et al. 2019). The average technical recovery rate is 52% (Thiffault et al. 2015), giving 0.27 * 0.52 = 0.14 ~ 0.15. Independently, (Di Fulvio et al. 2016) report technically recoverable logging residues at 13.5% of roundwood volume for the EU28. Residues are generated from all real harvest sources (forestry plantations and natural vegetation) for both products. The slack variable v73_prod_heaven_timber is excluded (no real harvest = no residues). v73_prod_residues itself is also excluded to avoid circularity.

\[\begin{multline*} v73\_prod\_residues(j2) \leq \left(\sum_{kforestry} vm\_prod\_forestry(j2,kforestry) + \sum_{land\_natveg,kforestry} vm\_prod\_natveg(j2,land\_natveg,kforestry)\right) \cdot s73\_residue\_ratio \end{multline*}\]

Limitations Timber demand cannot be determined endogenously

Definitions

Objects

module-internal objects (A: default)
  Description Unit A
f73_construction_wood_demand
(t_all, i, pop_gdp_scen09, build_scen)
Construction wood demand \(10^6 tDM\) x
f73_demand_modifier
(t_ext, scen_73)
Factor diminishing paper use \(1\) x
f73_income_elasticity
(total_wood_products)
Income elasticities of wood products \(1\) x
f73_prod_specific_timber
(t_all, iso, total_wood_products)
End use timber product demand \(10^6 m3/yr\) x
f73_regional_timber_demand
(t_all, i, total_wood_products)
End use timber product demand \(10^6 m3/yr\) x
i73_timber_prod_cost_natveg
(i, kforestry)
Regional cost for timber production from natural vegetation incl natveg premium \(USD_{17MER}/tDM\) x
p73_demand_constr_wood
(t_all, i)
Demand for construction wood \(10^6 tDM/yr\) x
p73_demand_modifier
(t_all)
Simple demand modifier for construction wood \(10^6 tDM/yr\) x
p73_forestry_demand_prod_specific
(t_all, iso, total_wood_products)
End product specific timber demand \(10^6 m3/yr\) x
p73_fraction_sm_fix Modifier fraction at sm_fix_SSP2 time step \(1\) x
p73_fraction
(t_all)
Fraction over which construction wood demand is spread out \(1\) x
p73_glo_wood
(t_all, kforestry)
Global wood demand \(10^6 tDM/yr\) x
p73_income_elasticity
(t_all, iso, total_wood_products)
Income elasticities of wood products \(1\) x
p73_timber_demand_gdp_pop
(t_all, i, kforestry)
Timber demand based on lauri et al 2019 \(10^6 m3/yr\) x
q73_cost_timber
(i)
Actual cost of harvesting timber from forests \(10^6 USD_{17MER}/yr\) x
q73_prod_residues
(j)
Production of residues from industrial roundwood harvest \(10^6 tDM/yr\) x
q73_prod_woodfuel
(j)
Production of wood fuel \(10^6 tDM/yr\) x
q73_prod_wood
(j)
Production of industrial roundwood \(10^6 tDM/yr\) x
s73_expansion Construction wood demand expansion factor by end of century based on industrial roundwood demand as base \(1=100 percent increase\) x
s73_free_prod_cost Very high cost for settling demand without production \(USD_{17MER}/tDM\) x
s73_income_threshold Threshold for income-elastic industrial roundwood demand \(USD_{17PPP}/cap/yr\) x
s73_natveg_cost_premium Cost premium for natveg timber production relative to plantation \(1\) x
s73_residue_ratio Proportion of timber harvest recoverable as logging residues such as branches and tops \(1\) x
s73_residue_removal_cost Cost of removing residues left after industrial roundwood harvest \(USD_{17MER}/tDM\) x
s73_timber_demand_switch Logical switch to turn on or off timber demand 1=on 0=off \(1\) x
s73_timber_prod_cost_wood Cost for producing one unit of wood \(USD_{17MER}/m3\) x
s73_timber_prod_cost_woodfuel Cost for producing one unit of woodfuel \(USD_{17MER}/m3\) x
s73_woodfuel_stacking_factor Stacking factor to convert stere to solid m3 \(1\) x
v73_prod_heaven_timber
(j, kforestry)
Production of woody biomass from heaven \(10^6 tDM/yr\) x
v73_prod_residues
(j)
Production of residues from industrial roundwood harvest \(10^6 tDM/yr\) x

Sets

sets in use
  description
build_scen Building wood scenario
cell(i, j) number of LPJ cells per region i
construction_wood(total_wood_products) Wood products used for building construction
i all economic regions
i2(i) World regions (dynamic set)
iso list of iso countries
i_to_iso(i, iso) mapping regions to iso countries
j number of LPJ cells
j2(j) Spatial Clusters (dynamic set)
kforestry(k) forestry products
kforestry_to_woodprod(kforestry, total_wood_products) Mapping between intermediate and end use wood products
k(kall) Primary products
land_natveg(land_timber) Natural vegetation land pools
pop_gdp_scen09 Population and GDP scenario
scen_73 Forestry future scenario
t_all(t_ext) 5-year time periods
t_ext 5-year time periods
total_wood_products End use wood product category from FAO
t_past_forestry(t_all) Forestry Timesteps with observed data
t(t_all) Simulated time periods
type GAMS variable attribute used for the output
wood_panels(wood_products) Wood products used for panels construction
wood_products(total_wood_products) Major 2nd level products from wood processing

Authors

Abhijeet Mishra, Florian Humpenöder

See Also

09_drivers, 11_costs, 17_production, 32_forestry, 35_natveg, 52_carbon, 62_material

References

Churkina, Galina, Alan Organschi, Christopher PO Reyer, Andrew Ruff, Kira Vinke, Zhu Liu, Barbara K Reck, TE Graedel, and Hans Joachim Schellnhuber. 2020. “Buildings as a Global Carbon Sink.” Nature Sustainability 3 (4): 269–76.
Di Fulvio, Fulvio, Nicklas Forsell, Ola Lindroos, Anu Korosuo, and Mykola Gusti. 2016. “Spatially Explicit Assessment of Roundwood and Logging Residues Availability and Costs for the EU 28.” Scandinavian Journal of Forest Research 31 (7): 691–707. https://doi.org/10.1080/02827581.2016.1221128.
Lauri, Pekka, Nicklas Forsell, Mykola Gusti, Anu Korosuo, Petr Havlík, and Michael Obersteiner. 2019. “Global Woody Biomass Harvest Volumes and Forest Area Use Under Different SSP-RCP Scenarios.” Journal of Forest Economics 34 (3-4): 285–309. https://doi.org/10.1561/112.00000504.
Mishra, Abhijeet, Florian Humpenöder, Galina Churkina, Christopher P. O. Reyer, Felicitas Beier, Benjamin Leon Bodirsky, Hans Joachim Schellnhuber, Hermann Lotze-Campen, and Alexander Popp. 2022. “Land Use Change and Carbon Emissions of a Transformation to Timber Cities.” Nature Communications 13 (1): 4889. https://doi.org/10.1038/s41467-022-32244-w.
Mishra, Abhijeet, Florian Humpenöder, Jan Philipp Dietrich, Benjamin Leon Bodirsky, Brent Sohngen, Christopher P. O. Reyer, Hermann Lotze-Campen, and Alexander Popp. 2021. “Estimating Global Land System Impacts of Timber Plantations Using MAgPIE 4.3.5.” Geoscientific Model Development 14 (10): 6467–94. https://doi.org/10.5194/gmd-14-6467-2021.
Morland, Christian, Franziska Schier, Niels Janzen, and Holger Weimar. 2018. “Supply and Demand Functions for Global Wood Markets: Specification and Plausibility Testing of Econometric Models Within the Global Forest Sector.” Forest Policy and Economics 92: 92–105.
Oswalt, Sonja N, W Brad Smith, Patrick D Miles, and Scott A Pugh. 2019. “Forest Resources of the United States, 2017: A Technical Document Supporting the Forest Service 2020 RPA Assessment.” Gen. Tech. Rep. WO-97. Washington, DC: US Department of Agriculture, Forest Service, Washington Office. 97.
Thiffault, Evelyne, Annie Bechard, Daniel Pare, and Doug Allen. 2015. “Recovery Rate of Harvest Residues for Bioenergy in Boreal and Temperate Forests: A Review.” WIREs Energy and Environment 4 (5): 429–51. https://doi.org/10.1002/wene.157.