{"title":"What trees are more suitable for agroforestry implementation? A case study in Northwestern Iran","authors":"Mohammad Kheiri, Jafar Kambouzia, Saeid Soufizadeh, Abdolmajid Mahdavi Damghani, Romina Sayahnia, Hossein Azadi","doi":"10.1007/s10457-024-00955-2","DOIUrl":null,"url":null,"abstract":"<p>Agroforestry is an integrative farm management approach in which trees are deliberately integrated with other crops. Agroforestry systems can be effective if appropriate trees are chosen based on particular environmental and economic factors. However, it is crucial to identify suitable trees for agroforestry implementation (AI). The objective of the current study was to recognize the most suitable trees for AI in the agricultural lands of Nazar Kahrizi (NK) rural district of Hashtroud city, located in the northwest of Iran using a multi-dimensional approach. The study area was environmentally evaluated using ArcGIS, which led to the creation of 16 classes with different features. Then, based on the preference of 126 local farmers (from 26 villages of NK), 19 native trees were selected for AI assessment. These trees were evaluated and compared considering seven criteria (i.e., frostbite resistance, salinity resistance, sensitivity to drainage, storm resistance, drought resistance, preventing soil erosion, and economic benefits). Finally, a flexible multi-criteria decision analysis (MCDA) tool (PROMETHEE II) was applied to provide a complete ranking of preferred trees from the best to the worst for each class. The findings showed that the agricultural lands should be allocated for planting elaeagnus (about 79.6%, 27,446 ha), almond (13.5%, 4619 ha), quince (4.6%, 1573 ha), apple (1.8%, 635 ha), and walnuts (0.5%, 176 ha). Measurements showed that AI with the recommended trees in the study area will lead to CO<sub>2</sub> sequestration of about 12.96 Mg yr<sup>−1</sup>. The approach used in this study provides a valuable resource for decision-making in AI evaluations and, therefore, contributes to preserving the lands from degradation and ensures sustainable AI.</p>","PeriodicalId":7610,"journal":{"name":"Agroforestry Systems","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agroforestry Systems","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1007/s10457-024-00955-2","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
Agroforestry is an integrative farm management approach in which trees are deliberately integrated with other crops. Agroforestry systems can be effective if appropriate trees are chosen based on particular environmental and economic factors. However, it is crucial to identify suitable trees for agroforestry implementation (AI). The objective of the current study was to recognize the most suitable trees for AI in the agricultural lands of Nazar Kahrizi (NK) rural district of Hashtroud city, located in the northwest of Iran using a multi-dimensional approach. The study area was environmentally evaluated using ArcGIS, which led to the creation of 16 classes with different features. Then, based on the preference of 126 local farmers (from 26 villages of NK), 19 native trees were selected for AI assessment. These trees were evaluated and compared considering seven criteria (i.e., frostbite resistance, salinity resistance, sensitivity to drainage, storm resistance, drought resistance, preventing soil erosion, and economic benefits). Finally, a flexible multi-criteria decision analysis (MCDA) tool (PROMETHEE II) was applied to provide a complete ranking of preferred trees from the best to the worst for each class. The findings showed that the agricultural lands should be allocated for planting elaeagnus (about 79.6%, 27,446 ha), almond (13.5%, 4619 ha), quince (4.6%, 1573 ha), apple (1.8%, 635 ha), and walnuts (0.5%, 176 ha). Measurements showed that AI with the recommended trees in the study area will lead to CO2 sequestration of about 12.96 Mg yr−1. The approach used in this study provides a valuable resource for decision-making in AI evaluations and, therefore, contributes to preserving the lands from degradation and ensures sustainable AI.
期刊介绍:
Agroforestry Systems is an international scientific journal that publishes results of novel, high impact original research, critical reviews and short communications on any aspect of agroforestry. The journal particularly encourages contributions that demonstrate the role of agroforestry in providing commodity as well non-commodity benefits such as ecosystem services. Papers dealing with both biophysical and socioeconomic aspects are welcome. These include results of investigations of a fundamental or applied nature dealing with integrated systems involving trees and crops and/or livestock. Manuscripts that are purely descriptive in nature or confirmatory in nature of well-established findings, and with limited international scope are discouraged. To be acceptable for publication, the information presented must be relevant to a context wider than the specific location where the study was undertaken, and provide new insight or make a significant contribution to the agroforestry knowledge base