Mosnier - Impacts of improved transportation infrastructure on agricultural sector in the Congo Basin

Impacts of improved transportationinfrastructure on agricultural sector in the Congo Basin A. Mosnier , P. Havlik, M. Obersteiner, K. Aoki, E. Schmid International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria University of Natural Resources and Applied Life Sciences (BOKU), Vienna, AustriaInternational CIALCA Conference, Kigali, Rwanda, October 24-27

Introduction Congo BasinCameroonCongo RepublicDemocratic Republic of Congo (DRC)Central African Republic (CAR)GabonEquatorial Guinea

Introduction• Mainly subsistence agriculture • 80% of the territory is• Food production per capita has covered by forests => decreased over the last decade agriculture main driver and net imports have increased of deforestation

Introduction • 1/3 of increase in cereal production worldwide has been attributed to fertilizer related factors • Average fertilizer use in SSA ~8 kg/ha vs. 54 kg/ha in Latin America and 80 kg/ha in South Asia. • In the Congo Basin, only Cameroon is a significant user of fertilizer • Problem of poor transportation infrastructures in the Congo Basin Fertilizer use per arable land in 2008 (kg nutrients/ha) Cameroon Congo DRC GabonNitrogen 3.37 0.06 0.20 0.07Phosphate 0.79 0.00 0.04 0.03Potash 1.30 0.02 0.05 1.35Total 5.45 0.09 0.29 1.45 Source: State of the forest 2008 and FAOSTAT

IntroductionLiterature highlights:  Positive impact of transportation infrastructure on agriculture  Negative impact of transportation infrastructure on forest cover• What will be the effect of transportation infrastructure development on agricultural sector in the Congo Basin?

METHODOLOGY

GLOBIOM: a global, partial equilibrium modelObjective function = Maximization of producer and consumer surplus DEMAND Exogenous drivers Population growth, economic growth 28 regions Wood products Food Bioenergy Process PROCESSPrimary wood products Crops SUPPLY HRU = Altitude & Slope & Soil Aggregation in larger units Altitude class, Slope class, Soil Class (max 200*200 LUC PX5 km) PX5 Altitude class (m): 0 – 300, 300 – 600, 600 – 1200, 1200 – 2500 and > 2500; Slope class (deg): 0 – 3, 3 – 6, 6 – 10, 10 – 15, 15 – 30, 30 – 50 and > 50; Soil texture class: coarse, medium, fine, stony and peat; Biophysical Between 10*10 models EPIC G4M km and 50*50 km

GLOBIOM: Cropland - EPICProcesses  Hydrology EPIC  Weather Evaporation and  Erosion Rain, Snow, Transpiration Chemicals  Carbon sequestration  Crop growth Subsurface Flow  Crop rotations Surface Flow  Fertilization  Tillage Below Root Zone  Irrigation etc… 9

Productivity changeEPIC Major outputs:• Crop yields, Input Requirements, Environmental effects (e.g. soil carbon, )• For 18 crops (>75% of harvested area)• And 4 management systems: High input, Low input, Irrigated, SubsistenceIn GLOBIOM, endogenous yield change through:• Production increase in more (or less) fertile areas• Change in management practices

Internal transportation costsCompute time from a methodology developed by Nelson (2006) using several GIS datasetsClosest market:for food crops = city above 300 000 inhabitantsfor cash crops, timber and fertilizers= portTransportation cost per simulation unit (between 10x10 and 50x50km) :Tc = constant + wage.hours + fuel price. fuel consumption.distance + other costs. distanceParameters from literature review (Teravaninthorn and Raballand, 2009; ILO; GTZ)

SCENARIOS & RESULTS

Baseline• Period 2000-2030, 10 year-steps (recursive dynamics)• Demand exogenously driven: – By GDP for processed wood – By population for fuel wood – By both for food = minimum calorie intake p.c. differentiated between vegetable and animal calories (FAO, 2006a) – Bioenergy use from POLES model (Russ et al., 2007) and World Energy Outlook estimates (IEA-2006)• Fixed crop mix per simulation unit• No exogenous agricultural productivity growth

Scenario• Realization of the planned infrastructures after 2010

Scenarios• The reduction of transportation costs affect:1) Farm output prices2) Fertilizer cost• Scenarios to distinguish these different effects:INFRA1 = channel 1) onlyINFRA2 = channels 1) and 2)DIFHI = increase of the productivity in the high input system by 5% between 2020-2030)

Results

Results Baseline INFRA1 INFRA2 DIFHI High Input and Irrigated 12.7% 12.7% 19.9% 57.1% DRC Subsistence- Low input 87.3% 87.3% 80.1% 42.9% High Input and Irrigated 8.7% 9.2% 12.7% 48.3%Congo Basin Subsistence- Low input 91.3% 90.8% 87.3% 51.7%

ResultsRelative land use change compared to the baseline level by 2030 INFRA1 INFRA2 DIFHI Cropland 12.9% 17.4% 15.1% DRC Forests -4.2% -4.4% -3.9% Congo Cropland 3.2% 4.7% 2.2% Basin Forests -0.4% -0.4% 0.0%Average annual C02 emissions from deforestation over 2020-2030 (inMtCO2) Baseline INFRA1 INFRA2 DIFHI DRC 36 50 51 47 Congo Basin 68 76 76 68

ConclusionTransportation infrastructure improvement provides incentives: to increase agricultural production to switch to more intensive systems even if it remains limited to 13% of the cropped area in the Congo Basin and 20% in the DRC by 2030=> support to further increase efficiency of fertilizer use could lead to significant intensification in the region• However, it is most probably than intensification will not impede deforestation increase, especially in dense forests area of DRC=> land tenure definition and implementation with delineation of protected area/permanent forests area

Concluding remarks• Transportation infrastructure could not necessarily lead to transportation cost reduction• Need for continuous efforts to maintain infrastructures in good shape• There are other non-cost factors that play an important role for new technology adoption• Other problems related to increase fertilizer use: higher costs in the future, environmental sustainability,…

Thank you ! For more information : www.globiom.orgContact: mosnier@iiasa.ac.at

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Mosnier - Impacts of improved transportation infrastructure on agricultural sector in the Congo Basin

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