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?

IF 1.7 3区 农林科学 Q2 FORESTRY
Hadi Beygi Heidarlou, Abbas Banj Shafiei, Amin Tayyebi, Stelian Alexandru Borz
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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.
基于土地转型模型评估伊朗扎格罗斯森林持续保护政策和森林覆盖变化的效果:向森林过渡还是毁林?
近几十年来,伊朗西部的扎格罗斯森林在覆盖和结构上经历了巨大的变化。另一方面,自2002年以来,这些森林已经存在或正在实施保护政策,以防止森林砍伐。然而,有一个问题是,保护政策在防止森林损失方面的效果如何。本研究的目的是分析保护政策在防止森林损失方面的效果,并预测其未来的有效性。由于森林覆盖、土地利用及其格局的时空变化呈非线性变化,本研究基于土地转化模型(LTM)。利用地理信息系统(GIS)和人工神经网络(ann),该模型预测了未来30年的森林变化。为此使用了三种情景,其中输入模式包括2002-2012年、2002-2022年和2012-2022年。在此基础上,利用14个变量预测了未来30年的森林砍伐情况。假设在扎格罗斯森林中执行的保护政策没有变化,该模型的特点是具有一贯的准确性,并显示出该地区未来几年森林砍伐增加的预测模式。换句话说,由于现行的保护政策,净森林砍伐超过净再造林。看来,要阻止森林进一步退化,伊朗林业局的决策者必须实施改进的森林保护政策。
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来源期刊
CiteScore
2.20
自引率
11.10%
发文量
11
审稿时长
12 weeks
期刊介绍: Annals of Forest Research is a semestrial open access journal, which publishes research articles, research notes and critical review papers, exclusively in English, on topics dealing with forestry and environmental sciences. The journal promotes high scientific level articles, by following international editorial conventions and by applying a peer-review selection process.
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