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A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

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Abstract

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households’ income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

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Acknowledgments

The authors are thankful to Professor Bruce M. Campbell and Dr. Neil Collier for their helpful professional support and Neil Cory editing the paper. We would like to thank the farmers and field-guides for their valuable participation and time. Special thanks go to Wondo Genet College of Forestry and Natural Resources and the Swedish International Development Agency (Sida) for financing the study.

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Correspondence to Efrem Garedew.

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Garedew, E., Sandewall, M. & Soderberg, U. A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia. Environmental Management 49, 151–162 (2012). https://doi.org/10.1007/s00267-011-9783-4

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