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Ecosystem Services Research Program: LTG 2: Monitor, map, and model ecosystem services at multiple scales
Impact/Purpose:
ECO MYP
Description:
Mapping ecosystem services is a high priority and an area of significant ORD expertise. Monitoring will be confined to designing a monitoring system for accounting for ecosystem service changes. This will move EMAP condition monitoring to ecosystem services monitoring, building in the need for multiple scale design options. Modeling research will be refocused to acquire, evaluate, improve and make available ecosystem models that are applicable at multiple scales. We will develop monitoring designs and indicators that will allow current ecosystem services (ES) for aquatic ecosystems to be estimated on a national and regional basis. This approach will yield unbiased and representative regional/national inventories, and through time, allow for assessment of ES trends associated with management decisions. We also envision the use of these data for the empirical parameterization of models to allow scaling to more local levels and/or for developing associations with regional/national remote sensing data. Monitored ES data will also allow model hindcasting to assess predictive accuracy of these models. Within the next five years we will determine whether ES produced by aquatic ecosystems can be estimated from current condition monitoring programs. For existing monitoring programs to be useful for ES, they must provide high quality, consistent, representative, and spatially distributed data of sufficient record length to assess status, changes, and trends in ES with time. This requires examination of both the monitoring designs and indicators to determine if they will allow for ES estimates at local to national levels. If they do not, we will determine what additional information is needed or whether entirely new ES indicators and designs are needed. Further, we will examine the response of ES to anthropogenic stressors and determine whether ES response thresholds exist for selected ES. We will also develop approaches to combine data from different spatial units, monitoring designs/, and ecosystem types.