Hamidreza Keshtkar; Hassan Yeganeh; Omid Kavoosi
Abstract
Ferula gummosa is one of the rare and valuable species in Iran's rangelands, which is exploited by local stakeholders due to its high economic value. Protecting this species can help maintain the biodiversity and stability of mountainous areas. This study was conducted to compare the performance of six ...
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Ferula gummosa is one of the rare and valuable species in Iran's rangelands, which is exploited by local stakeholders due to its high economic value. Protecting this species can help maintain the biodiversity and stability of mountainous areas. This study was conducted to compare the performance of six predictive models: Artificial Neural Networks, Random Forest, Classification Tree Analysis, Surface Range Envelope, Generalized Boosting Machines, and Generalized Linear Models. To evaluate the interactions between topographic factors and other variables, two environmental datasets were quantified and used for model calibration. The first dataset includes eleven factors covering topographic, climatic, edaphic, and remote sensing variables. Meanwhile, the second dataset contains six factors, focusing on climatic, edaphic, and remote-sensing variables. Model accuracy was evaluated using the True Skill Statistic (TSS), the area under the curve of the Receiver Operating Characteristics (ROC), and the Accuracy Index. The evaluation indices indicate that the Generalized Boosting Machine (GBM) model predicted the ecological niche of F. gummosa more accurately than the other methods. Additionally, the results showed that removing topographical variables reduced the model accuracy by 11 to 25%. The slope, NDVI, wetness, and soil groups were found to be the most important factors in mapping potentially suitable habitats for the target plant. According to the results obtained from the GBM model, approximately 45% of the Ghorkhoud area is in excellent condition. This knowledge can aid in the selection of predictors for practical Species Distribution Model (SDM) applications and provide information on which modeling techniques are most useful for a group of species.
Emad Zakeri; Mahdi Ghorbani; Ali Bozorgmehr; Hojatollah Rabani Nasab
Abstract
Current nomad settlement programs seek improving the quality of nomads’ life as their ultimate goal. However, it seems some of these programs failed due to some problems such as socio- economic problems that appear after settlement or due to the lack of proper preliminary studies before the implementation. ...
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Current nomad settlement programs seek improving the quality of nomads’ life as their ultimate goal. However, it seems some of these programs failed due to some problems such as socio- economic problems that appear after settlement or due to the lack of proper preliminary studies before the implementation. Nomad settlement program in Northern Khorasan is not an exception; therefore, identification and prioritization of problems before implementation of the program in Northern Khorasan is essential for better planning. The required data to identify and prioritize nomad settlement problems and to plan for their proper settlement were gathered through a questionnaire including the criteria and sub-criteria as well as options to solve extant challenges. The questionaire then was completed by experts and analyzed by using the analytic hierarchy process in Expert Choice2000. The results showed that cultural and social management and planning factors with coefficients of (0.433) and (0.314), respectively left the greatest influence on the failure of relevant projects in North Khorasan province. Therefore; the reform of the administrative and planning system as an important solution to problems related to the management and planning criteria and increasing the nomads’ participation in planning and management as an important solution to problems related to social and cultural criteria were assessed in present study.