A wide variety of mathematical and empirical models have been implemented as practical tools for land-use planning, and multilayer perceptron (MLP), logistic regression or LR (mathematical model) and multi-criteria evaluation or MCE (empirical) are among widely applied models. One of the main drawbacks of the mathematical models is that they require dependent data and the process of data collection can be so costly and time-consuming for large areas. As such, we investigated the possibility of providing dependent data set through the MCE method for tourism planning in Golestan Province, Iran. The accuracy of MCE-based algorithms was investigated using ground truth data collected during field observations from early spring up to late summer 2016. The MCE-based and ground-based outputs were investigated and compared for spatial accuracy and connectivity and compactness of the results using receiving operator characteristic (ROC) and landscape configuration metrics. ROC statistics were scored at 0.886, 0.834, 0.82 and 0.814 for ground-based MLP, ground-based LR, MCE-based MLP and MCE-based LR, respectively, showing no meaningful differences between MCE-based and ground-based methods in terms of spatial accuracy. Landscape metrics also indicated that MCE-based methods have resulted in a more connected and manageable pattern for tourism planning. According to the results of this study, MCE can serve as a preliminary approach to define field sampling spots or even as an alternative to field observation efforts in case of limited time and financial resources.
Wind erosion is one of the main drivers of soil loss in the world, which affects 20 million hectare land of Iran. Besides the soil loss, wind erosion contributes to carbon dioxide emission from the soil into the atmosphere. The objective of this study is to evaluate monthly and seasonal changes in carbon dioxide emission in four classes i.e., low, moderate, severe and very severe soil erosion and the interactions between air temperature and wind erosion in relation to carbon dioxide emission in the Bordekhun region, Boushehr Province, southwestern Iran. Wind erosion intensities were evaluated using IRIFR (Iran Research Institute of Forests and Ranges) model, in which four classes of soil erosion were identified. Afterward, we measured carbon dioxide emission on a monthly basis and for a period of one year using alkali traps in each class of soil erosion. Data on emission levels and erosion classes were analyzed as a factorial experiment in a completely randomized design with twelve replications in each treatment. The highest rate of emission occurred in July (4.490 g CO 2 /(m 2 •d)) in severely eroded lands and the least in January (0.086 g CO 2 /(m 2 •d)) in low eroded lands. Therefore, it is resulted that increasing erosion intensity causes an increase in soil carbon dioxide emission rate at severe erosion intensity. Moreover, the maximum amount of carbon dioxide emission happened in summer and the minimum in winter. Soil carbon dioxide emission was just related to air temperature without any relationship with soil moisture content; since changes of soil moisture in the wet and dry seasons were not high enough to affect soil microorganisms and respiration in dry areas. In general, there are complex and multiple relationships between various factors associated with soil erosion and carbon dioxide emission. Global warming causes events that lead to more erosion, which in turn increases greenhouse gas emission, and rising greenhouse gases will cause more global warming. The result of this study demonstrated the synergistic effect of wind erosion and global climate warming towards carbon dioxide emission into the atmosphere.
Ecosystem function is affected by management activities in rangeland ecosystems. Hence, it is necessary to consider management effects on rangeland ecosystem to reduce its degradation. In order to determine the effects of management activities on rangeland ecosystem, four management treatments were chosen in Taleghan, Iran. Functionality characteristics including: stability, infiltration and nutrient cycling were calculated using Landscape Function Analysis (LFA). LFA calculates these parameters using 11 soil surface indicators. Results showed that stability, infiltration and nutrient cycle were higher in Karkaboud than the other locations because of low grazing pressure and non-accessibility conditions. As grazing pressure increased we witnessed less stability, infiltration and nutrient cycling in Karkaboud cascade, Kouin and Kouin-Marjan. Main causes of decline in stability, infiltration and nutrient cycling are perennial vegetation removal, soil trampling and decrease in soil organic matter and subsequent increase in erosion and soil instability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.