نوع مقاله : مقاله پژوهشی
1 دانشجوی دکترای آمایش محیطزیست، گروه محیط زیست، دانشکده منابع طبیعی و محیطزیست، دانشگاه ملایر، ملایر، ایران
2 - استادیار، گروه محیط زیست، دانشکدة منابع طبیعی و محیط زیست ، دانشگاه ملایر، ملایر، ایران
3 استادیار،پژوهشکدة محیطزیست وتوسعةپایدارسازمان حفاظت محیطزیست، تهران، ایران
عنوان مقاله [English]
Valuing ecosystem services requires consideration of spatial patterns. Therefore, we used new spatial statistics methods, such as Moran's spatial correlation and GIS capability, to identify and determine spatial patterns of ecosystem services after quantifying habitat ecosystem services in the Qarah Qeshlaq wetland, a 22,000 ha wetland between the eastern and western Azerbaijan provinces. Studies show that there are 13 types of land uses in the area of Qarah Gheshlagh wetland, which in the area of about 22,000 hectares shows the diversity of land use and in fact the active presence of human factors, about 46% of the area has agricultural land and about 28% of saline land. In this regard, residential centers as a threat center and access road as a threat development have been the largest share in land use change. According to the Moran index of 0.62 and the expected index of -0.000017 and the z-score of 1505869, the probability of random distribution is low and the distribution is clustered. The optimized analysis of the sensitive points in the area of Qarah Qeshlaq wetland reveals that the correlation is highest on the western side of the wetland where there is no human activity, while it is lowest on the eastern side where there is a great deal of human activity.
In general, any type of wetland is composed of a large number of physical, biological or chemical factors, and water, soil and nutrients represent these components that, in conjunction with each other in an integrated system, form the wetland and the processes between the components, the functions of the components. Creates. Wetlands are defined based on their biological, chemical, and physical properties, regardless of their specific function, production, or process (Ganagey, 2018). In order to identify wetlands, first the type of wetlands must be determined from a hydrological point of view, and each of the different classes of wetlands provides different ecosystem services. In other words, many benefits that ecosystems provide to individuals are called ecosystem services.
Introduction of the study area
The study area of Qaraghshlagh wetland with an area of 22,000 hectares is located between East Azerbaijan and West Azerbaijan provinces and on the outskirts of Bonab and Miandoab cities in a geographical position of 37 degrees 13 minutes and 25 seconds north latitude and 45 degrees and 51 minutes and 38 seconds east longitude. It is located on the south shore of Lake Urmia at an altitude of 1270 meters above sea level.
InVEST habitat quality model, by combining land use / vegetation patterns and biodiversity threats, leads to the production of habitat quality maps. This model is implemented using raster data or maps divided into square cells (pixels). Each pixel in the image is assigned to a type of land use / vegetation, which can be a natural cover or a man-made cover. This approach provides two basic types of information necessary for the initial assessment of conservation needs: which includes the relative extent and extent of degradation of different types of habitats in an area and its various changes over time.
Understanding patterns and discovering trends in spatial data is important. Because before any analysis, it must be determined how the data are distributed in space and their spatial patterns. In this study, Moran correlation statistic was used to analyze the spatial correlation of ecosystem services. There are two types of Moran indices to determine the spatial correlation between variables whose efficiency is different from each other. Global Moran Index and Local Moran Index. One of the most basic global indicators of solidarity is the Moran index. This index gives a number (as a standard score) that can be used to measure the dispersion or concentration of phenomena or spatial data.
Land use related to the current time
There are 13 types of land uses in the area of Ghareh Gheshlagh wetland, which in the area of about 22,000 hectares shows the diversity of land use and in fact the active presence of human factors, about 46% of the area has agricultural land and about 28% is saline land. If this area was not saline, it could be added to the area of agricultural land. Of the remaining 24%, about 7% is used as a fish farm and 7% is a rangeland. In other words, 35% of the lands in this area are national lands (rangeland and saline). Only 10% of the area as an aquatic habitat belongs to Qarah Gheshlagh wetland, river, flood area and water supply canal. Qarah Gheshlagh wetland in the current situation with an area of about 140 hectares and covers less than one percent of the area (Figure 2). In evaluating ecosystem services, there is a wider range of goals, including ecological sustainability and social welfare, along with the traditional economic goal of efficiency. In fact, by determining the value of ecosystem services in socio-economic and ecological dimensions, we can understand the contribution of each of these services in achieving the above goals. Therefore, due to the heterogeneity of units of measurement in three dimensions of economic, social and ecological, it is necessary to develop criteria for measuring each and in some cases to determine the degree of importance of these criteria in the specific service of the ecosystem by qualitative weighting. On the other hand, the implementation of the development plan can have different socio-economic and ecological effects; Effects that can change the value of ecosystem services and reduce and in some cases increase the value of these services.
In the present study, in order to investigate the spatial structure of ecosystem services in the area of Gharaghshlagh wetland, spatial statistics (value2 column of land use) have been evaluated. The statistics used, based on the conceptualization of the dispersion index, examine the ratio of variance to the average based on the distance of services. 0.62 does not follow a random distribution, but the p-value is zero, which indicates a high correlation and cluster distribution and is significant.
According to Table 4, the Moran index is 0.62 and the expected index is negative 0.000017 and the z-score is 1505869. The probability of random distribution is low and is in the form of clusters. Examination of Map 5 Analysis of hotspots in Qarah Gheshlagh area shows the southwest side of the area which includes wetland, fish breeding place, Zarrineh river and flood spreading place in this area has the highest value and in the eastern side of the area which is agricultural use has the lowest value or points. It is hot or correlated, and there is no correlation with pale pink in the center of the range and paths of rivers and water supply canals.
Qarah Gheshlagh wetland is located on the shores of Lake Urmia and at the mouth of large rivers such as Zarrineh and Simaneh rivers, as well as Mordagh Chai, Leylan Chai and Sufi Chai, and has been a habitat and water source in the region. These wetlands have provided food, drinking water, pastures and transportation routes for indigenous communities and have emerged as part of their culture. In this study, the spatial correlation pattern for habitat ecosystem service was investigated. Gharaghshlagh wetland is the first station for waterfowl in the country due to its migration route from north to south, especially birds living in Siberia, and therefore, it carries a rich source of animal diversity and serves as a link between the north and The south is home to rare species of birds. Studies show that 14 ecosystem services are affected by each other in the area of Ghareh Gheshlagh wetland and these uses are interdependent, so that without the river and canal, neither the wetland is important nor agricultural activity is possible in that area. As the studies show that the standard standardization row has been done, the distance threshold is 10813163 m and the studied data do not follow the random distribution according to Moran index of 0.62, and the p-value is zero, which indicates high correlation and clustering of the distribution. And is significant and according to z-score 150.586901454, there is less than 1% probability that this clustering pattern can be the result of a random chance that positive value values in this statistic indicate cluster data and negative value values indicate unsatisfactory data. is. However, each of the farms and ecosystem service centers of the wetland have scalable conditions and are suitable for a variety of ecosystem service traits, and on the other hand, the level and capacity of services and outgoing data in each user is easily identifiable and on the other hand sensitive to they do not prioritize ecosystem services and each has a specific application and role in the ecosystem.