A review on the progress of modeling techniques in ecosystem services

The number, diversity and application of ecosystem service models has greatly increased over the past decade. To integrate ecosystem service assessment into decision-making processes, systematically comparing and examining the different tools to identify the corresponding approaches that apply to decision requirements are especially essential and important. In this context, we summarized the existing modeling techniques for ecosystem service assessments nationally and internationally, including correlative models, process-based models, and expert-based models. We analyzed their principles, differences, advantages, and disadvantages in detail. Each of these modeling approaches had strengths and weaknesses that made them a better fit to different decision contexts: (1) the correlative models focused on existing statistical relationships, which were easy to use, to create and to revise, making these types of models useful in initial or rapid assessments. However, the weakness was that they could dramatically fail in data-poor situations. (2) Process-based models, which represented a scientific understanding of key dynamics for ecosystem services, were difficult to produce and to access but allowed the exploration of interactions and long-term dynamics in human-earth systems. (3) Expert-based models could facilitate to achieve the incorporation of diverse types of expert knowledge into ecosystem service assessments, which was particularly useful for bridging multiple knowledge systems as well as focusing on the interactions among people and nature systems. However, the expert-based models were often only partial and were difficult to verify from place to place. Furthermore, the applications of typical ecosystem service assessments models based on the three techniques were systematically reviewed and discussed. Our study highlighted that these modeling approaches had to compromise between usability and scientific accuracy, which meant that practitioners need to weigh their requirements for specific projects carefully before deciding on the appropriate tools. The analysis and integration of different modeling techniques would enhance the capabilities of decision support for ecosystem services assessments, and help to provide information and reference for domestically relevant research.