Modeling interventions to reduce deforestation in Zambia

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Agriculture faces tremendous pressure to supply both growing and wealthier populations with more food, fiber, and fuel, while recognizing the limits of agricultural ecosystems. But it remains unclear whether it is possible to increase agricultural and food production without increasing deforestation and associated greenhouse gas emissions. The objective of this study was to advance the understanding of landscape-level implications of sustainable intensification of agriculture on forest conservation in Zambia. Sustainable intensification aims to increase agricultural yields and reduce deforestation. Miombo woodlands, a dry forest ecosystem common throughout the region, are the dominant biome in much of Zambia, and they are suitable for the production of charcoal, a commonly used cooking fuel among urban households. We used participatory system dynamics modeling to examine the drivers of deforestation in two provinces in Zambia. We modeled four scenarios to examine their effects on reducing deforestation over a 50-year simulation period: (i) an increase in maize yield from adoption of SI practices, and (ii) occasional moderate and severe drought events, (iii) adoption of efficient charcoal cookstoves, and (iv) full electrification. We found no effects of adoption of sustainable intensification practices on agricultural encroachment into forested ecosystems. The clearing of forested land for agriculture was found to be largely driven by the rising demand for wood fuels for cooking and heating, particularly charcoal in urban areas. Charcoal was increasingly dominant as a driver of deforestation in both provinces such that changes in land practices and economic returns to farmers are unlikely to reveal measurable changes in land use. The findings have implications for the development of integrated approaches to address the challenges of food and energy insecurity, as well as for national-level policies aimed at climate change mitigation and reducing greenhouse gas emissions. This study provides a unique and innovative approach to integrating social and biophysical/ecological data through the application of system dynamics modeling. Furthermore, the study contributes to the literature on the environmental implications of agricultural land use and the drivers of deforestation.

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