The USGS Sustaining Environmental Capital Initiative (SECI) is an ongoing effort to coordinate federal agency ecosystem services research and knowledge development, develop interagency partnerships to address policy and scientific issues and build a web portal to provide support to the research and practitioner communities. The initial effort is engaged in a series of pilot studies, conducted throughout the US. The SECI team and its collaborators are using this opportunity to understand the current state of the science related to methods and tools for modeling and valuing ecosystem services, as well as incorporating ecosystem services analysis in federal land management and decision-making processes, and eventually extending their utility to support a national-scale natural capital accounting framework. This talk will present two alternative approaches for modeling and valuing ecosystem services. The first approach focuses on econometric models for valuing clean water in Lake Champlain (Vermont) at multiple spatial scales. The second approach integrates hydrologic models with statistical and agent-based models to assess water supply benefits derived from Wilderness Areas (North Carolina and Arizona), and conduct a multi-service assessment in the Upper Rio Grande watershed (northern New Mexico and southern Colorado) evaluating landscape-level responses to managed and naturally occurring fire events.
Lake Champlain plays a vital role in Vermont’s economy, and declining water quality is threatening both the ecological and economic underpinnings of the region. A hedonic analysis revealed that a one-meter reduction in water clarity yields 3% and 37% decreases in transaction values for single family and seasonal dwellings, respectively, and reduces hotel occupancy rates in lake-dependent communities by 10%. At the regional scale, $300 million in lake-related expenditures results in an additional $72.75 million in spending and 1,070 jobs, and a one-meter reduction in water clarity would result in 195 lost full-time summer jobs and a corresponding $16.8 million reduction in economic activity.
The Artificial Intelligence for Ecosystem Services (ARIES) modeling platform was used to develop spatially-explicit process- and agent-based models of freshwater ecosystem service generation, flow and benefits delivery for three case study areas, demonstrating the machine learning, machine reasoning, and artificial intelligence functionality of ARIES. Ongoing research seeks to link the econometric modeling with participatory modeling efforts geared towards the development of demand-side profiles for multiple beneficiary groups (e.g. household, commercial and industrial water supply) for water provision (supply and quality), sediment regulation and recreation-based ecosystem services (among others) under alternative fire management and climate scenarios.