Evaluating the effect of ongoing conservation policies and forest cover changes in Iranian Zagros forests based on a Land Transformation Model: transition to forest or deforestation?
DOI:
https://doi.org/10.15287/afr.2023.2628Keywords:
Conservation, Deforestation, Forecasting model, Land use/cover change, ANNs.Abstract
In recent decades, Zagros forests from western Iran have experienced dramatic changes in cover and structure. Conservation policies, on the other hand, have existed or are being implemented in these forests since 2002 to prevent deforestation. There is, however, the question on how effective were the conservation policies in preventing forest loss. The goal of this study was to analyze the effect of conservation policies in preventing forest loss, as well as to forecast their future effectiveness. Since the spatio-temporal changes in forest cover, land-use and its patterns occur in a non-linear way, this study was based on the use of Land Transformation Model (LTM). Using geographic information systems (GIS) and artificial neural networks (ANNs), this model forecasts future forest changes for the next 30 years. Three scenarios were used for this purpose, in which the input patterns included the years 2002-2012, 2002-2022, and 2012-2022. Based on these, deforestation was predicted for the next three decades using 14 variables. Assuming no changes in the implementation of conservation policies in the Zagros forests, the model was characterized by a consistent accuracy and indicated a projected pattern of increased deforestation over the next years in the region. In other words, by the ongoing conservation policies, the net deforestation overtakes net reforestation. It appears that to stop further forest degradation, Iran's Forestry Service decision-makers must implement improved forest conservation policies.References
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