Quantifying and mapping ecosystem services (ES) that reach beneficiaries provide a key to distinguishing between the potential for benefit provision and the benefits actually accrued by society. Such a spatially explicit information framework can improve the accuracy of ES valuation and expand the value of ES assessments to decision makers. Beneficiary-based maps of ES provision are crucial in resource management scenarios for influencing management decisions that appropriately address distributional equities among ‘‘winners’’ and ‘‘losers’’. Modeling approaches that map and quantify service-specific sources (ecosystem capacity to provide a service), sinks (biophysical or anthropogenic features that deplete or alter service flows), beneficiaries (user locations and level of demand), and spatial flows only can provide a more complete understanding of ecosystem services leading to decision making at different scales. Researchers have long recognized that the ecosystems that provide benefits to people and the beneficiaries of these services are not always located in the same region. ARIES (Artificial Intelligence for Ecosystem Services) is the first modeling tool that explicitly accounts for this spatial disconnect. ARIES accomplishes this by first using deterministic or probabilistic models to map provision, use, and sinks of ecosystem services. It then uses agent based models to move a carrier for each service across the landscape according to service specific flow paths. While most ecosystem services mapping tools and projects have simply mapped the potential provision of ecosystem services in the past, ARIES maps actual provision, use, and flows of services by accounting for flow paths and rival use or “sink” regions that deplete or transform the carrier of a service as it moves across the landscape.
At ICIMOD, under transboundary landscapes regional program various initiatives are working on assessment and quantification of ecosystem services, thus it will be crucial to monitor the status of these services under changing climatic and anthropogenic scenarios. For example, a framework on assessment and valuation of non-monitory cultural ecosystem services is already been prepared for Kailash Sacred Landscape, which defines methods and formats for collection of data on cultural services. Geospatial Solutions theme and KSLCDI are currently utilizing ARIES modelling platform to assess the sacredness potential of the Kailash landscape based on the data on cultural sites from India, China, and Nepal, which could prove to be an important input while nominating the landscape as an UNESCO world heritage site. Similarly, quantification and assessment based on the geospatial framework in ARIES could help in understanding the current source-sink-beneficiaries scenario in other ecosystem services from other transboundary landscapes as well.
In this regard, we are organizing a regional workshop at ICIMOD, Kathmandu during 8 to 10 November 2016 for professionals in-house as well as from partner organizations to participate, learn, and implement the ARIES platform in assessment and quantification of ecosystem services. The objective of the workshop is to bring professionals working on ecosystem services in different transboundary landscape initiatives and SERVIR HKH in different RMCs to get their inputs on assessments of ecosystem services that are currently being performed using ARIES platform at ICIMOD, to build their capacity on using ARIES platform for assessment of ecosystem services in their country, and to discuss the strategies for mainstreaming the framework for assessment and valuation of ecosystem services for upscaling to HKH level.