Identifying Forests and Wetlands of Highest Value for Water Quality and Economic Benefits

1. Identifying Forests and Wetlands of Highest Value for Water Quality and Economic Benefits Chesapeake Bay Resource Lands Assessment Chesapeake Bay Program

2. Introduction • Valuable forests, farms, and wetlands are under pressure from land use change and other environmental stresses. • The Chesapeake 2000 Agreement charged the Chesapeake Bay Program with conducting an assessment of its resource lands in order to identify the most important lands to conserve. • Commitment # 4.1.3.3

3. Resource Lands Assessment(RLA) • Purpose: To identify the resource lands (i.e., forests, farms and wetlands) that have the highest water quality, habitat, cultural and economic value and are the most vulnerable to loss.

4. RLA Objectives • Habitat Value Assessment • Water Quality/Watershed Integrity Value Assessment • Cultural Value Assessment • IV. Economic Value (i.e., forest and farm production) • Assessment • V. Vulnerability Assessment

5. Water Quality and Watershed Integrity Value Assessment

6. The Role of Forests in Water Quality • Watershed integrity relates to physical and biological watershed functions that perform many functions to protect water quality. • Store precipitation • Retain and assimilate nutrients • Moderate runoff • Protect soils and critical riparian areas • Sustain aquatic ecosystems • In general, forests and wetlands are the best land cover for providing these watershed functions.

7. Goals of this Analysis • To identify the nexus between a forest or wetland and the parameters that affect its ability to provide these functions. • To place value on forests and wetlands that if lost would have significant potential to compromise or degrade watershed and water quality. Availability of specific and consistent data sets is a limiting factor in this analysis.

8. Assumptions • The characteristics of soil and vegetation at a particular site, and for the watershed within which they occur, have significant bearing on this assessment of value. • The GIS data layers used to represent the parameters are accurate enough for this coarse scale assessment.

9. Methods GIS data layers collected for parameters known to affect water quality and watershed integrity (total of 13 parameters) Data within every parameter classified into 4 ranges based on their influence on water quality (0 = no influence, 4 = highest influence) Every parameter given a weight from 0 to 5 to emphasize variables with a greater influence on water quality (0 = no influence, 5 = highest influence)

10. Data Types and Sources Local Parameters • Proximity to water USGS NED • Erodible Soils NRCS STATSGO • Net Primary Productivity USDA Forest Service • Slope USGS DEM • Wetland Function NWI • Forest Fragmentation CBP • 100 Year Floodplains FEMA • Hydrogeomorphic Regions USGS

11. Data Types and Sources Regional Parameters(summarized by HUC 11 watershed) • Stream Density (m/sq km) USGS NHD • Percent Forested MRLC 97 • Percent Impervious RESAC 2000 • Water Quality Rank USGS Sparrow/DU • Municipal Water Supplies USGS

12. Ranks and Weights

13. Preliminary Results – Unweighted

14. Preliminary Results - Weighted

15. Comparison Unweighted Weighted

16. New Data Layers to be Included • Forest Productivity – cu.ft/ac/yr -based on species, geography, elevation, climate, soils, and atmospheric deposition. (USFS-PNet Model) • Municipal Water Supplies – small-medium size systems, proximity to major river withdrawals (compile from USGS/State data)

17. Economic Value Assessment of Forest Land

18. Economic Value of Forests • Timber management activities contribute significantly to the economy of the region. • This assessment considers: • Economic returns of forest harvests; • Long-term economic sustainability of forest land; and • Local importance of the timber management and wood products industry. • It does not account for tourism, hunting, and other economic benefits. • A similar economic analysis for agricultural lands is being considered.

19. Goals of this Analysis • To identify the connection between forests and the parameters that effect their ability to produce economic benefits. • To place value on forests that if lost would have significant potential to negatively impact the region’s economy. Availability of specific and consistent data sets is a limiting factor in this analysis.

20. Assumptions • The physical, management, landscape, socioeconomic, and programmatic characteristics of forests have significant bearing on the economic value forests contribute. • The GIS data layers used to represent the parameters are accurate enough for this coarse scale assessment.

21. Methods GIS data layers collected for parameters known to affect the economic benefits produced by forests (total of 17 parameters) Data within every parameter classified and given a score based on its economic influence (0 = no influence, 10 = highest influence) Every parameter given a weight from 0 to 10 to emphasize variables with a greater influence on the economy (0 = no influence, 10 = highest influence)

22. Data Types and Sources Local Parameters • Species Composition GAP Vegetation (CBP) • Soil Productivity NRCS STATSGO • Precipitation Spatial Climate Analysis Service • Forest Density Landsat subpixel analysis • Riparian and Wetland Features MDP Streams (NHD) NWI Wetlands • Steep Slopes USGS DEM • Rare, Threatened, and Endangered SSPRA (BCD? & PNDI) Species

23. Data Types and Sources Regional Parameters • Forest Fragmentation/ Patch Size CBP • Probability of Sustainable Commercial Census 2000 Timber Management (Compatibility) • Contiguity of Ownership/ Parcel Size Parcelization MD (Census 2000) • Local Importance of Timber and IMPLAN (CBP) Primary Manufacturing Industry • Local Importance of Secondary IMPLAN (CBP) Manufacturing Industry

24. Data Types and Sources Regional Parameters (Continued) • Historic Timber Harvests USDA Forest Service • Sourcing Areas/ “Timbersheds” USDA Forest Service (Mill Locations) • Impacts of Growth PFA’s (Census 2000) • Private Land Protection Designations Forest Legacy and Rural Legacy (N/A) • Public Land Management Activities CBP

25. Ranks and Weights: Local Parameters

26. Ranks and Weights: Regional Parameters

27. Status of Economic Assessment • Maryland assessment completed • Model will be adapted for PA and VA • Have data for most parameters • Need to obtain data for rare, threatened, and endangered species information • Need to develop weighting system for public lands data • Population density will be substituted for Probability of Sustainable Timber Management, Parcel Size, and Impacts of Growth • No “Forest Legacy” land equivalent • Data sets for three states will be combined

28. When do we have enough data?

29. How will this information be used? • Combined with other analysis – especially vulnerability • Some ground proofing with local governments and land conservancies? • Identify priority landscapes and guide future protection efforts • Provide estimates of future program needs ($) • Provide information for “State of the Forests” Report

30. Questions?