Developing a New Model for Ecological Capability Evaluation of Forestry in Arid and Semi-Arid Regions

Abstract

Forest planning is a necessary requirement for long-term, economically efficient and environmentally responsible forest management and use. Iran has 12 million ha of forest cover, with 5 million ha in the mountainous Zagros area. Many of the improper uses in these forests, so far removed from the past, have resulted in significant degradation. The purpose of this paper is to check and compare the prepared methods, including the Iranian Ecological Model (with seven classes using Boolean logic), its revised method (with four classes using Boolean logic and four classes using geometric mean evaluation, as well) and a new model for ecological capability evaluation for better planning management for commercial and conservational forestry in Jahrom County located in Fars Province, Iran. In this study, we assessed the potential for conservational forestry in two ways: first, by adjusting the quantitative evaluation threshold of the model’s primary topographic criterion, and then, by removing this criterion altogether. It is worth noting that the necessary information, including climatic, topographic, soil and other types, was compiled by national and local organisations in Iran for the research. The improved Boolean technique (with [Formula: see text]) outperformed the Iranian Ecological Model (with [Formula: see text]), while the revised method using geometric mean assessment and calibration (with [Formula: see text]) outperformed the other methods tested. Furthermore, when all of the forestry capacity maps were compared, conservational forestry map demonstrated a higher capability after removing the topographic criterion in the region (with [Formula: see text] for calibration technique), indicating conservational forestry’s potential in Jahrom County. Overall, because of its simplicity and excellent precision, this study may be utilised as a fundamental framework to evaluate ecological capability for other locations with similar conditions, and this model can help users and administrations undertake executive initiatives.