8 research outputs found
Comparing Inductive and Deductive Modeling of Land Use Decisions: Principles, a Model and an Illustration from the Philippines
REDD policy impacts on the agri-food sector and food security
The REDD policy which preserves, enables substantial emission reductions. Since agricultural production and area expansion is a primary driver of tropical deforestation, REDD policies might limit the expansion possibilities of agricultural land use and therefore influence competitiveness, agricultural prices, trade, production and food security the world. This paper studies the impact of REDD policies on the agri-food sector and food security with a global CGE model called MAGNET. It focuses on the restrictions on agricultural land expansion within the REDD policy package. Simulation results show that REDD policies start to affect the agri-food sector in some lower developed countries if more than 15% of potentially available agricultural areas are protected from deforestation. A stringent REDD policy that protects 90% of land reserves that could potentially be used for agriculture production results in a global real agricultural price increase of almost 6%, and a worldwide agricultural production decrease of 1.5%
REDD policy impacts on the agri-food sector and food security
Recent research shows that the combined contributions of deforestation, forest degradation and peat land emissions account for about 15% of greenhouse gas emissions. The REDD policy which preserves forests and values standing forests, enables substantial emission reductions. Since agricultural production and area expansion is a primary driver of tropical deforestation, REDD policies might limit the expansion possibilities of agricultural land use and therefore influence competitiveness of the agricultural sector, agricultural prices, trade patterns, agricultural production and therefore food security in the world. This paper studies the impact of REDD policies on the agri-food sector and food security with a global CGE model called MAGNET using a scenario approach. It focuses on the restrictions on agricultural land expansion within the REDD policy package. Simulation results show that REDD policies start to affect the agri-food sector in some lower developed countries if more than 15% of potentially available agricultural areas are protected from deforestation. A stringent REDD policy that protects 90% of land reserves that could potentially be used for agriculture production results in a global real agricultural price increase of almost 7.6%, and a worldwide agricultural production decrease of 1.7%. Regional differences are large, with real agricultural price changes ranging from 4% in North America to about 24% in Sub-Saharan Africa and South-East Asia. Food access rapidly deteriorates for low-income population in these regions in the case of high forest protection levels. Compensatory payments are necessary from a food security point of view if the level of forest protection increases. Our results indicate that from a food security perspective REDD policy should stop short of trying to protect more than 40% of global carbon if the compensation mechanism is not effectively implemented within REDD
REDD policy impacts on agri-food sector and food security : scenario analysis with a CGE model
Estimating the costs of reducing CO2 emission via avoided deforestation with integrated assessment modeling
Estimates for deforestation and forest degradation were shown to account for about 17% of greenhouse gas emissions. The implementation of REDD is suggested to provide substantial emission reductions at low costs. Proper calculation of such a costs requires integrated modeling approach involving biophysical impact calculations and estimation economic effects of these. However, only few global modeling studies concerning this issue exist, and the actual implementation can take many forms. This study uses the approach of assuming that non Annex-I countries protect carbon rich areas from deforestation, and therefore loose the opportunity to use it as agricultural area. The opportunity costs of reducing deforestation within the framework of REDD are assessed with the global economic model LEITAP and the biophysical model IMAGE. A key methodological challenge is the representation of land use and the possibility to convert forestry land into agricultural land as REDD policies might prevent the use of forest for agriculture. We endogenize availability of agricultural land by introducing a flexible land supply curve and proxy the implementation of the REDD policies as a shift in the asymptote of this curve representing maximal agricultural land availability in various regions in the world. In a series of experiments, increasingly more carbon rich areas are protected from deforestation, the associated costs in terms of GDP reduction are calculated with the economic model. The associated reduction in CO2 emissions from land use change are calculated by the IMAGE model. From this series of experiments, abatement cost curves, relating CO2 emission reduction to costs of this reduction, are constructed. The results show that globally a maximum CO2 reduction of around 2.5 Gt could be achieved. However, regional differences are large, ranging from about 0 to 3.2 USD per ton CO2 in Africa, 2 to 9 USD in South and Central America, and 20 to 60 USD in Southeast Asia
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Estimating the costs of reducing CO2 emission via avoided deforestation with integrated assessment modeling
Estimates for deforestation and forest degradation were shown to account for about 17% of greenhouse gas emissions. The implementation of REDD is suggested to provide substantial emission reductions at low costs. Proper calculation of such a costs requires integrated modeling approach involving biophysical impact calculations and estimation economic effects of these. However, only few global modeling studies concerning this issue exist, and the actual implementation can take many forms. This study uses the approach of assuming that non Annex-I countries protect carbon rich areas from deforestation, and therefore loose the opportunity to use it as agricultural area. The opportunity costs of reducing deforestation within the framework of REDD are assessed with the global economic model LEITAP and the biophysical model IMAGE. A key methodological challenge is the representation of land use and the possibility to convert forestry land into agricultural land as REDD policies might prevent the use of forest for agriculture. We endogenize availability of agricultural land by introducing a flexible land supply curve and proxy the implementation of the REDD policies as a shift in the asymptote of this curve representing maximal agricultural land availability in various regions in the world. In a series of experiments, increasingly more carbon rich areas are protected from deforestation, the associated costs in terms of GDP reduction are calculated with the economic model. The associated reduction in CO2 emissions from land use change are calculated by the IMAGE model. From this series of experiments, abatement cost curves, relating CO2 emission reduction to costs of this reduction, are constructed. The results show that globally a maximum CO2 reduction of around 2.5 Gt could be achieved. However, regional differences are large, ranging from about 0 to 3.2 USD per ton CO2 in Africa, 2 to 9 USD in South and Central America, and 20 to 60 USD in Southeast Asia
REDD policy impacts on the agri-food sector and food security
Recent research shows that the combined contributions of deforestation, forest degradation and peat land emissions account for about 15% of greenhouse gas emissions. The REDD policy which preserves forests and values standing forests, enables substantial emission reductions. Since agricultural production and area expansion is a primary driver of tropical deforestation, REDD policies might limit the expansion possibilities of agricultural land use and therefore influence competitiveness of the agricultural sector, agricultural prices, trade patterns, agricultural production and therefore food security in the world. This paper studies the impact of REDD policies on the agri-food sector and food security with a global CGE model called MAGNET using a scenario approach. It focuses on the restrictions on agricultural land expansion within the REDD policy package. Simulation results show that REDD policies start to affect the agri-food sector in some lower developed countries if more than 15% of potentially available agricultural areas are protected from deforestation. A stringent REDD policy that protects 90% of land reserves that could potentially be used for agriculture production results in a global real agricultural price increase of almost 7.6%, and a worldwide agricultural production decrease of 1.7%. Regional differences are large, with real agricultural price changes ranging from 4% in North America to about 24% in Sub-Saharan Africa and South-East Asia. Food access rapidly deteriorates for low-income population in these regions in the case of high forest protection levels. Compensatory payments are necessary from a food security point of view if the level of forest protection increases. Our results indicate that from a food security perspective REDD policy should stop short of trying to protect more than 40% of global carbon if the compensation mechanism is not effectively implemented within REDD