The pasture module determines land used as pasture for livestock rearing. At the same time, it calculates geographically explicit production of pasture biomass and the carbon content of pasture land. Therefore, the module requires cellular information about the carbon density related to the different pasture carbon pools. Furthermore, it delivers regional production costs associated with pastures.
| Description | Unit | A | B | |
|---|---|---|---|---|
| fm_carbon_density (t_all, j, land, c_pools) |
LPJmL carbon density for land and carbon pools | \(tC/ha\) | x | x |
| pcm_land (j, land) |
Land area in previous time step | \(10^6 ha\) | x | |
| vm_carbon_stock (j, land, c_pools) |
Carbon stock in vegetation soil and litter for different land types | \(10^6 tC\) | x | x |
| vm_cost_prod (i, kall) |
Factor costs | \(10^6 USD_{05MER}/yr\) | x | x |
| vm_land (j, land) |
Land area of the different land types | \(10^6 ha\) | x | x |
| vm_prod (j, k) |
Production in each cell | \(10^6 tDM/yr\) | x | |
| vm_prod_reg (i, kall) |
Regional aggregated production | \(10^6 tDM/yr\) | x | |
| vm_yld (j, kve, w) |
Yields (variable because of technical change) | \(tDM/ha/yr\) | x |
In the endo_jun13 realization, pasture area and related carbon stocks are modelled endogenously. The initial spatially explicit patterns of pasture are defined in the module 10_land by the land use input data set. For future time steps, pasture area depends on the demand for biomass from pastures to feed livestock as calculated in the module 70_livestock and from the intensity of pasture utilization (“pasture yield”) as determined in the module 14_yields.
Production of pasture biomass is restricted to pasture area which is delivered as module output together with the resulting geographically explicit production of pasture biomass. Cellular production is calculated by multiplying pasture area vm_land with cellular rainfed pasture yields vm_yld which are delivered by the module 14_yields:
\[\begin{multline*} vm\_prod(j2,"pasture") \leq vm\_land(j2,"past") \cdot vm\_yld(j2,"pasture","rainfed") \end{multline*}\]
On the basis of the required pasture area, cellular above ground carbon stocks are calculated:
\[\begin{multline*} vm\_carbon\_stock(j2,"past",ag\_pools) = \sum_{ct}\left( vm\_land(j2,"past") \cdot fm\_carbon\_density(ct,j2,"past",ag\_pools)\right) \end{multline*}\]
In the initial calibration time step, where the pasture calibration factor is calculated that brings pasture biomass demand and pasture area in balance, small costs are attributed to the production of pasture biomass in order to avoid overproduction of pasture in the model:
\[\begin{multline*} vm\_cost\_prod(i2,"pasture") = vm\_prod\_reg(i2,"pasture") \cdot s31\_fac\_req\_past \end{multline*}\]
For all following time steps, factor requriements s31_fac_req_past are set to zero.
Limitations No consideration of generic differences between extensive and intensive grazing systems, of explicit pasture management options and of related degradation of pastures.
In the static realization, pasture areas are constant over time, independent from developments in the livestock sector and land competition.
Pasture areas are fixed to the initial spatially explicit patterns defined in the module 10_land by the land use input data set.
vm_land.fx(j,"past") = pcm_land(j,"past");Correspondingly, also the above ground carbon stocks related to pasture areas are fixed.
vm_carbon_stock.fx(j,"past",ag_pools) =
pcm_land(j,"past")*fm_carbon_density(t,j,"past",ag_pools);Regional costs associated with pasture management are set to zero.
vm_cost_prod.fx(i,"pasture") = 0;Limitations There are no computational limitations to this realization. Since pasture areas are static, they do not respond to demand trajectories and trends in the land use and agricultural sectors like intensification pathways, increasing production of animal products, bioenergy production or afforestation policies. This may lead to an inconsistent overall picture of future land use dynamics.
| Description | Unit | A | B | |
|---|---|---|---|---|
| q31_carbon (j, ag_pools) |
Above ground carbon content calculation for pasture | \(10^6 tC\) | x | |
| q31_cost_prod_past (i) |
Costs for putting animals on pastures | \(10^6 USD_{05MER}/yr\) | x | |
| q31_prod (j) |
Cellular pasture production constraint | \(10^6 tDM/yr\) | x | |
| s31_fac_req_past | Factor requirements | \(USD_{05MER}/tDM\) | x |
| description | |
|---|---|
| ag_pools(c_pools) | Above ground carbon pools |
| c_pools | Carbon pools |
| ct(t) | Current time period |
| i | all economic regions |
| i2(i) | World regions (dynamic set) |
| j | number of LPJ cells |
| j2(j) | Spatial Clusters (dynamic set) |
| k(kall) | Primary products |
| kall | All products in the sectoral version |
| kve(k) | Land-use activities |
| land | Land pools |
| t_all(t_ext) | 5-year time periods |
| t(t_all) | Simulated time periods |
| type | GAMS variable attribute used for the output |
| w | Water supply type |
Isabelle Weindl, Jan Philipp Dietrich
10_land, 14_yields, 17_production, 38_factor_costs, 52_carbon