Selection of the Most Suitable Tree and Shrub Species for the Afforestation of Iranian Northern Zagros Forests Using AHP and TOPSIS Techniques (Case Study: Perdanan Piranshahr)

Extended Abstract Background: Because human and non-human factors are present in most part of the Iranian northern Zagros Forests, an extensive portion of the forests in these areas have been lost or are at risk of destruction, making forestry initiatives increasingly important for the environment. Even enriching the existing forests is a particular approach to dealing with the quantitative and qualitative degradation processes. Furthermore, afforestation is a strategy for recovering degraded areas and is recognized as a method of protecting soil and water, combating desertification, providing wood, and increasing carbon and nitrogen stores. The selection of suitable tree/shrub species based on expert opinion and decision-making model criteria is one of the most effective factors in the success of afforestation and reforestation projects. The current study aimed to enhance the Iranian northern Zagros Forests in the Perdanan area of Piranshahr and to restore its destroyed regions (empty spots) by finding the most appropriate forest tree/shrub species. Methods: In this research, all destroyed spots, clearings, and empty spots of tree and shrub species were first identified and extracted as destroyed spots using the satellite images of 2022 from ESRI and the Google Company. To prepare the homogeneous units of the investigated area in the Pardanan forest lands of Piranshahr (northwest of Iran, the starting point of the Zagros forests), the topographical layers of the area, including slope, direction, height above sea level, geological maps, land ecology, and the map of micro-ecosystems, were combined to prepare the map of the ecological unit (homogeneous units) of the studied area. Because of the existence of destroyed spots, gaps, and empty spots of tree plant species, three one-kg soil samples from a depth of 0-30 cm were prepared from each of the environmental units. The soil samples passed through a two-mm sieve and thensubjected to measurements of soil physicochemical properties, including pH, electrical conductivity, texture, moisture, lime, nitrogen, organic carbon, phosphorus, potassium, calcium, magnesium, bulk density, and particle density factors. The findings of the soil samples were then analyzed with SPSS software to categorize the region based on soil properties by generating a dendrogram of the retrieved parameters using the K-Means Cluster technique. The acquired parameters were split into three good, medium, and poor stands after being separated into distinct groups and identifying the limiting characteristics of the studied region. The best species were selected through an extensive literature review of studies conducted in the area of Zagros forests. A list of 29 species of the most important and best species as final options was prepared and delivered to the questioners, which included university members and forestry experts in Iran. The most suitable species were selected based on the examined criteria and the soil properties of the region. Finally, the introduced species (options) were prioritized independently for each habitat by the TOPSIS method utilizing the opinions of the respondents (university members and forestry specialists in the forest areas of Iran), the AHP approach, and the decision-making criteria (viz. power of adaptation, the cost of keeping seedlings and seeds in afforested regions, water and soil protection, drought and natural element resistance (e.g., wind, pests, fire, etc.), growth rate, and seedling or seed purchase price). Results: The findings of extracting damaged spots, clearings, and vacant spots of tree and shrub species using remote sensing data revealed the presence of 141 places covering a total area of 685 ha. Decomposing the decision-making problem into smaller elements created a hierarchy on three levels. The first level contained the purpose of decision-making, and the second level comprised six criteria (maintenance cost, purchase price, growth rate, resistance, compatibility, and soil and water protection). In the third level, options with 29 native species were examined through a questionnaire among five experts, and finally, the most suitable species (option) was selected for each habitat (good, medium, and poor habitats) determined by examining the results of the sample dendrogram. The soil patches were separated and selected using the TOPSIS method. The results of the TOPSIS ranking technique showed that  Arjan and Ars species were the most preferred species, with closeness indexes of 0.63, 0.65, and 0.64, respectively, in good/medium and poor habitats, respectively. Walnut, sand, and hackberry species (with closeness indices of 0.489, 0.487, and 0.484, respectively) were selected as the most unfavorable species for afforestation and forest restoration in these areas. Conclusion: The adaptability of the selected species for afforestation and forest enrichment projects to the region's current environmental conditions, as well as its low demands in comparison to other tree species, are the primary success factors for these programs. Plants, on the other hand, prefer certain conditions over others based on their biology and ecological demands, such as the quantity of light in different life stages, humidity, bedrock, and soil depth. Knowing these requirements will undoubtedly improve the accuracy of species selection and planting site selection and increase the chances of achieving a satisfactory result. According to the findings of this study, the studied region may be divided into good, medium, and poor stands based on its soil properties, and each of these areas has the necessary potential for afforestation. Nevertheless, given that each species has unique ecological demands, the relatedness of the species' ecological needs to the current ecological circumstances in the region is a prerequisite for the success of afforestation and reforestation projects. According to our findings, native species are the best alternative for recovering destroyed forest areas, and nursing species are more important than climax species in restoring degraded forest areas. The findings of this study can help forest managers plan effective forestry operations, particularly in Zagros ravaged areas (particularly in Iranian Northern Zagros forests).