ارزیابی الگوهای مکانی خدمات اکوسیستمی بر مبنای رویکرد تطبیقی مبتنی بر آمار فضایی در قسمت مرکزی استان اصفهان

بررسی پراکنش مکانی خدمات اکوسیستمی در ارزیابی ظرفیت سرزمین برای فراهم سازی این سودمندی ها نقش مهمّی ایفا می کند. بر این اساس، تغییرات مکانی سه خدمت اکوسیستمی ارزش زیبایی شناسی، ارزش تفرّجی و کاهش آلودگی صوتی در قسمت مرکزی استان اصفهان با به کارگیری رویکردهای آماری موران محلّی و گیتسارد جی بررسی شد، سپس صحّت مکانی رویکردهای مورد بررسی با استفاده از نمودار مشخّصه عملکرد، ارزیابی و مقایسه شد. با توجّه به نتایج، تغییرات مکانی خدمات اکوسیستمی مورد بررسی، الگوی خوشه ای بالا دارد. براساس هر دو رویکرد مورد استفاده، بخش مرکزی منطقه مطالعاتی برای هر سه خدمت اکوسیستمی دارای الگوی همبستگی مکانی مثبت و بخش جنوبی منطقه، دارای الگوی همبستگی مکانی منفی است. بخش های دارای الگوی خوشه ای بالا دارای بیشترین میزان عرضه خدمات اکوسیستمی در منطقه مورد مطالعه است در حالی که در مناطق دارای الگوی خوشه ای پایین، میزان فراهم سازی خدمات اکوسیستمی بسیار ناچیز است. ارزیابی صحّت مکانی الگوهای همبستگی مکانی خدمات اکوسیستمی نشان داد که بیشترین سطح زیر منحنی مربوط به خدمت اکوسیستمی ارزش تفرّجی و رویکرد گیتسجی ارد (972/0) و کمترین میزان آن مربوط به خدمت کاهش آلودگی صوتی و روش موران محلّی (833/0) است. به طور کلّی، با توجّه به نتایج، روش گیتس ارد جی نسبت به روش موران محلّی برای هر سه خدمت اکوسیتمی صحّت مکانی بیشتری دارد و نمودار مشخّصه عملکرد، معیار مناسبی برای ارزیابی دقّت و صحّت رویکردهای تحلیلی مورد استفاده در این مطالعه است. نتایج نوشتار پیش رو می تواند به منظور شناسایی و مدیریت الگوهای همبستگی مکانی خدمات اکوسیستمی مورد استفاده تصمیم گیران و برنامه ریزان سرزمین قرار گیرد.

Evaluating Spatial Patterns of Ecosystem Services based on a Comparative Approach on Spatial Statistics in the Central Part of Isfahan Province

Considering the spatial patterns of ecosystem services plays an important role in evaluating land capacity to provide some benefits. Accordingly, the spatial variation of three ecosystem services, aesthetics value, recreation value and noise pollution reduction in the central part of Isfahan province was investigated applying statistical approaches of Local Moran’s I, and GetisOrd Gi analysis. Then, spatial accuracy of the investigated algorithms was evaluated and compared using the Receiving Operator Characteristic method. The findings reveal that the spatial variation of the ecosystem services under study have Highcluster pattern. Based on both used approaches and for all three ecosystem services, the central part of the study area has a positive spatial correlation pattern, whereas the southern part of the study area has a negative spatial correlation pattern. Areas representing the high cluster pattern involved have the highest supply of ecosystem services in the study area, while in areas with low cluster pattern, the provision of ecosystem services is very low. Spatial accuracy evaluating of ecosystem services spatial correlation patterns indicate that returned the largest area under ROC curve of recreational value and GetisOrd Gi analysis (0.972), whereas the lowest rate is found for the noise pollution reduction service and Local Moran’s I, (0.833). Overall, according to the results, the GetisOrd Gi indicates higher spatial accuracy than Local Moran’s I method for three ecosystem services, and the Receiving Operator Characteristic is an appropriate index to evaluate the accuracy of the analytical approaches used in This research. The findings of this study can be applied by decision makers and land planner to identify and management spatial correlation patterns of ecosystem services.Extended Abstract1IntroductionEcological components of the ecosystem affects the total ecosystem structure through an interaction with other socioenvironmental parameters form its spatial structure and instability in these components. Accordingly, the concept of ecosystem services is a tool to assess the ecosystems conditions and relates the ecosystems structure and function to human wellbeing. Ecosystem services are used as an appropriate tool to link knowledge, policymaking and land planning which can be identified in four categories: provisioning services, regulating services, supporting services and cultural services. For sustainable development, it is necessary to identify and investigate ecosystem services at different scales. Spatial presentation of ecosystem services supply in landscape is necessary to integrate ecosystem services in the urban and regional planning process. Therefore, mapping and quantifying the spatial distribution of ecosystem services is an important tool so that decisionmakers and urban planners manage and monitor the levels of ecosystem services provision and provides a framework to identify regions including conversation value (due to the high supply of services). In recent years, spatial information systems (GIS) have been widely used to identify supply areas and assess the spatial distribution of ecosystem services. Using the capabilities of the spatial information system, we can map the spatial and temporal distribution of ecosystem services and assess the potential effects of environmental and managerial changes on the ecosystem services provision. The application of spatial statisticsbased methods such as local Moran and GetisOrd Gi analysis to evaluate spatial patterns of ecosystem services has recently been considered. However, in most studies, only one method based on spatial statistics has been used. Thus, the systematic comparison of these methods provides valuable information on how they are applied to evaluate spatial patterns of ecosystem services and provides a basis for integrating these variables into land planning.2Materials and MethodsThe current study was conducted in the central part of Esfahan province, Iran. The area is located at 51°12′to 51°59′eastern longitudes and 32°19′to 32°56′ northern latitudes covering an area about 1181 Km2. The area includes Isfahan, ShahinShahr, KhomeiniShahr, Najafabad and Falavarjan townships. The annual average precipitation and temperature are 116.9 mm and 16.7 ° C, respectively.The data used in this research are ecosystem service maps of aesthetic value, recreational value, and noise pollution reduction service, which were prepared in a GIS environment based on both effective criteria and indicators on each ecosystem service and according to the study of Abdollahi et al. (2020). In the next step, two methods of local Moran and GetisOrd Gi analysis, the subbranch of spatial statistics were used in the GIS environment, in order to evaluate the spatial patterns of ecosystem services. One of the basic concepts to analyze spatial statistics is the spatial contiguity of the phenomena. Various methods are applied to detect spatial contiguity and develop a weight matrix, among which, two methods of inverse distance and Contiguity edges only are used more. Finally, spatial accuracy of these approaches was calculated using Receiving Operator Characteristic (ROC).3Results and DiscussionThe findings reveal that for both methods, the pattern of distribution of ecosystem services is the same and the central, eastern and western parts of the study area include patches with a high supply of ecosystem services, while the south part of the study area shows spots with low supply of ecosystem services. According to findings from local Moran, very high cluster patterns cover the minimum area and large part of the study area does not follow a specific spatial pattern which is not statistically significant. Based on the findings from Receiving Operator Characteristic the GetisOrd Gi analysis has more spatial accuracy than the local Moran method for all three ecosystem services. Among ecosystem services, recreational value has the highest value under the curve for both approaches. On the other hand, regarding the fact that the values under the curve are close to one for ecosystem services in both approaches, both approaches have high spatial accuracy in order to evaluate the spatial patterns of ecosystem services.4ConclusionIdentifying the patterns of ecosystem services is an effective step to improve the management of the benefits obtained from nature. Overall, the Receiving Operator Characteristic (ROC) is an appropriate index to evaluate the accuracy of the analytical approaches used in this research. Along with this study, Saeidi et al (2017) reported that the ROC method is an appropriate approach to consider the different algorithms of aesthetic mapping. The results of this study can be used by decisionmakers and land planners to identify and manage spatial correlation patterns of ecosystem services.