Land Cover Changes in Northern Zagros Forests (Nw Iran) Before and During Implementation of Energy Policies

ABSTRACT

Our ability to forecast future Land use/cover changes (LUCC) is extremely limited due to lack of understanding of how rapid and drastic changes like socio-economic shocks and disturbances (e.g., policy changes and economic crises) affect land use/cover. Energy policies changing in Iran have been implemented since 2010. In this study, we explored whether changes in energy policies affect the sustainability of forest cover and LUCC. Results showed that in the time periods of before and after implementation of the policies, 2,841 and 3,155 ha of forests converted to other land covers, respectively. It was also revealed that forest and rangelands degradation and their conversion to croplands and built-up areas have had the most contribution to increasing area of these land covers. Calculation annual rate of deforestation showed an increase in deforestation activities after the plan (−0.40% versus −0.53%). On the other hand, the population growth in the first period was 10,074 people, which was higher than the population increase in the second period (9,803 people). Therefore, it can be argued that the effect of the energy policies is likely to be greater than the increase in population and it appears to be able to cause a transition of land systems.

KEYWORDS:

• Deforestation
• economic crisis
• energy carriers
• forest cover change
• land Change Modeler
• socio-economic disturbances
• targeted subsidies plan

Acknowledgments

This paper has been extracted from a Ph.D. thesis which financially supported by Urmia University, Iran. We gratefully acknowledge of very beneficial technical assistance and advice received from Professor Dr. Tobias Kümmerle and Dr. Matthias Baumann, Humboldt University of Berlin.

Declaration of interest statement

We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

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