1. FrESCOES: Framework Earth Surface Characteristics Ontology for Ecosystem Services Austin Troy, Ken Bagstad, Shuang Liu, and Matthew Wilson Submitted to: Frontiers in Ecology and the Environment

2. Key Points Ecosystem service values are increasingly being used in decision making Ecosystem service values are increasingly being used in decision making Information from ecosystem services Information from ecosystem services research is often transferred from a study site to another site where the necessary information for decision making is unavailable; the basis of this transfer is generally the similarity of conventional land cover classes, which were not designed for this purpose. We outline a new system for characterizing land and aquatic features that is designed to simplify and standardize knowledge transfer in ecosystem service- based management.

3. Overview Ontology (or classification) Ontology (or classification)   For ecosystem services   For earth surface characteristics   In order to share common understanding of the structure of information Looking to the future Looking to the future

4. ES ontology history Up until recently, ES are intuitively categorized by “ecosystem functions” Up until recently, ES are intuitively categorized by “ecosystem functions” 1 st list in 1970, 9 services including pest control, insect pollination, fisheries, climate regulation, soil retention, flood control, soil formation, cycling of matter, and composition of the atmosphere (Mooney and Ehrlich 1997) 1 st list in 1970, 9 services including pest control, insect pollination, fisheries, climate regulation, soil retention, flood control, soil formation, cycling of matter, and composition of the atmosphere (Mooney and Ehrlich 1997) 1997, Daily’s book 13 services 1997, Daily’s book 13 services Costanza et al. 17 services Costanza et al. 17 services Recently Millennium Assessment 21 services: four groups. Recently Millennium Assessment 21 services: four groups.

5. ES framework in MA Separated supporting service

6. An operational ontology should Build bridges between our current knowledge and ecosystem services Build bridges between our current knowledge and ecosystem services Take into consideration of the transdisiplinary nature of ecosystem service research Take into consideration of the transdisiplinary nature of ecosystem service research Facilitate benefit transfer and predictive modeling of ecosystem services Facilitate benefit transfer and predictive modeling of ecosystem services

7. Lack of common language: Earth surface characteristics “Traditional” LU/LC: Anderson (1976) Land Use Classification System Anderson (1976) Land Use Classification System Hierarchical systems (e.g., urban >> urban residential >> urban low density residential) Hierarchical systems (e.g., urban >> urban residential >> urban low density residential) Poorly suited for ecosystem service valuation Poorly suited for ecosystem service valuation Similar problems in FAO LCCS, other USGS/USEPA classification schemes Similar problems in FAO LCCS, other USGS/USEPA classification schemes Past global valuation studies: Costanza et al. 1997 – 11 cover types, nested for coastal, forests, wetlands Boumans et al. 2002 – 11 cover types

8. Limitations of value transfer Problems with past global/regional studies relying on value transfer Forest  forest  forest Forest  forest  forest

9. Variation in studies Land cover Service # studies # datapoints Mean ($) SD ($) BeachAesthetic4414,84718,067 EstuaryAesthetic49303448 ForestRefugia589231,211 ForestAesthetic914130204 Fresh wetland Water supply 561,1611,183 Fresh wetland Aesthetic581,5711,600 Open water Water supply 55409235 Open water Aesthetic914356310 Riparian buffer Water supply 891,9213,704 Riparian buffer Aesthetic781,3702,150 Salt wetland Aesthetic44230274

10. Growth of ESV studies

11. Base classes Goals: 1. Based on “top down” characteristics 2. Exhaustive, mutually exclusive, parsimonious 3. Definitions modified from National Land Cover Database (NLCD)

12. Modifiers

13. Proposed solution: Base classes & modifiers 1.Agriculture 2.Forest 3.Grassland/herbaceous 4.Woody perennial/shrubland 5.Permanent open water 6.Ice and glaciers 7.Exposed substrate 8.Impervious/impacted Superclasses Old-growth Early/mid-successional Old-growth Level 2 modifier Predicted differences in C sequestration, C storage, N cycling, recreation, aesthetics, watershed services, biodiversity Non-spotted owl habitat Spotted owl habitat Level 3 modifier Predicted existence value Subsistence economy Non-subsistence economy Predicted differences in value for fuelwood, medicinal plants, food, other NTFPs, etc.

14. Our vision Provide a Realistic basis for value transfer Provide more realistic framework for surface cover in modeling efforts Identify research gaps Contribution and consensus- building from the ESV research community

15. Future work For our collaborators: For our collaborators: Collaborative effort using SourceForge Collaborative effort using SourceForge Identify important modifiers for your geographic area of interest Identify important modifiers for your geographic area of interest Use ontology for modeling Use ontology for modeling Use in future primary valuation studies - will facilitate future value transfer and meta analysis Use in future primary valuation studies - will facilitate future value transfer and meta analysis UVM group UVM group Move ESC ontology from Excel to Web Ontology Language Move ESC ontology from Excel to Web Ontology Language Develop standard language for other model parameters Develop standard language for other model parameters

16. Class Hierarchy