San Francisco Bay Margin Conservation Decision Support System (DSS)
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1 San Francisco Bay Margin Conservation Decision Support System (DSS) Presented by Brian Fulfrost1, MS David Thomson2, MS 1 Brian Fulfrost and Associates 2 San Francisco Bay Bird Observatory
2 Transitional Zone - Background What? A GIS based decision support system (DSS) to identify, map and prioritize marsh-upland transitional zone habitats (TZH) to assist land managers in restoring and protecting San Francisco Bay s tidal marsh ecosystem Why? (1) needs for obligate fauna (e.g. clapper rails, salt marsh harvest mouse) (2) the lack of existing transition zone habitats and their role in overall ecosystem function (3) as well as the perceived need for marsh accommodation space for climate change adaptation
3 Transitional Zone Goals and Objectives Goal Provide land managers tools to rank and prioritize sites for protection and restoration of transition zones that will best increase the long term resilience of tidal marsh ecosystem. Objective(s) 1. GIS models of the current distribution of transition zone habitats and marsh accommodation space 2. Indicators for ranking patch quality and for ranking and prioritizing transitional zones habitats for restoration or protection 3. GIS models of future distribution of transitional zone habitats under various SLR scenarios (2050 and 2100). 4. Maps that (a) highlight transitional zone vulnerabilities now and in the future; and (b) identify parcels with transition zone habitats that have the most potential to enhance overall estuarine function and are resilient to climatic pressures.
4 Project Area
5 Transitional Zone Project Steps Step 1. Definition and Characteristics Step 2. Elevation Relation to Tides Step 3. Shape Metrics Step 4. Adjacent Habitat Step 5. Ecological Index (existing) Step 6. Restoration and Protection Indices (existing) (a)protection Status and Land Use Step 7. Ground Truthing
6 Transitional Zone Project Steps Step 8. Sea Level Rise Scenarios (future) Step 9. Rank & Prioritize Transitional Zone Habitats (existing and future)
7 Step 1: Define and characterize transitional zone habitats Characterize the physical and biological properties with respect to the functions of the tidal marsh ecosystem and needs for obligate fauna. Habitat indicators were developed based on these functions used to map distribution and quality. 1. Elevation in relation to Tides high tide refugia for obligate fauna, SLR adaptation 2. Depth (width and slope of transitional zone) distance needed by tidal marsh fauna and flora, SLR adaptation 3. Size and Shape as needed by tidal marsh fauna and flora, overall estuarine function 4. Adjacent Habitats as needed by tidal marsh fauna and flora, overall estuarine function 5. Soils and Hydrology as needed by tidal marsh flora, overall estuarine function 6. Plant Community high tide refugia, overall estuarine function
8 Step 2: Map potential Transition Zone (Tide and Elevation) Map the potential transitional zone based on elevation and tidal constraints to create: elevation in relation to tides The range of potential transitional zone was identified as:.31 meters above Mean Higher High Water (MHHW) to Highest Observed Water Level (HOWL) +.27 meters
9 Step 2: Map potential Transition Zone (Tide and Elevation) Step 2.1 Mosaic Lidar (1 meter) from NOAA and USGS
10 Step 2: Map potential Transition Zone (Tide and Elevation) Step 2.2: Create Tidal Surfaces Two tidal rasters (converted to NAVD88) were generated from the tidal gauges data to assist with mapping the lower and upper limits of the transitional zone: (a) interpolated surface of MHHW (using ~ 40 tidal gauges) and (b) a trend surface of the difference between MHHW and HOWL (using around ~13 tidal gauges) to account for tidal variability throughout the estuary.
11 Step 2.2a Interpolate MHHW surface using NOAA Tidal Gauges
12 Step 2.2b Interpolate Trend Surface of difference between MHHW and HOWL using NOAA Tidal Gauges
13 Step 2.3 Identify Potential Transitional Zone Habitat (existing) (a) Merge elevation data with MHHW surface to create elevation relative to MHHW (b) query the range of transitional zone habitat (c) convert to vector, simplify and merge adjacent polygons
14 Step 2: Initial Site Assessment (Tide and Elevation) LaRiviere Marsh is TZH poor Mayhew s Landing is TZH rich
15 Step 2.4: Divide into Tidal and Non-Tidal Tidal polygons represent potential existing transtional zone habitat
16 Step 2.4: Divide into Tidal and Non-Tidal Non-Tidal polygons represent potential marsh migration space
17 Step 3: Patch Metrics (Area, Width, Shape) (1) Area (2) Mean Width surface area / maximum length (diameter of smallest circumscribing circle) (3) Shape ratio of patch area to the area of the smallest circumscribing circle (linear to compact) Shape Metric at Bair Island red = linear (worst), orange = mixed, green = compact (best)
18 Step 4: Adjacent Habitat Transitional Zone Habitats were ranked based on a combination of : (a) type of adjacent land cover Highest Value: adjacent to both wetland and uplands Medium value: adjacent to wetland (or upland) Lowest Value: adjacent to urban (b) proportion of shared boundary for adjacent land cover (c) area of the adjacent land covers Indicator values for adjacent land cover were weighted based on: proportion (>= 50% of shared boundary given the highest weight) and area (50 cres of land cover given the highest value).
19 Adjacent Land Cover at Bair Island Data Used: (1) USDA's CalVeg dataset (all land cover types); and (2) SFEI BAARI dataset (for wetlands)
20 Step 5: Ecological Index Indicators values for Step 2 Step 4 (ecological indicators) were summed into a combined ecological index index value. Preliminary rankings for each transitional patch were determined as follows: Ecological Index (max = 100) Width Area (10 to 30) + Adjacent Wetland (10 to 30) + Adjacent Upland (10 to 30) + Adjacent Water (5 to 15) + Adjacent Urban (-10 to -30) + Adjacent Agriculture (TBD) + Shape (-10 to 10)
21 Step 5: Ecological Index (ranked)
22 Step 6: Restoration and Protection Indices Each transitional zone habitat was also assigned: (a) land use (at parcel level) Highest Protection Value: undeveloped (w/i parks, vacant, etc.) Lowest Protection Value: developed (w/i residential, commercial, industrial, etc.) (b) protection status Highest Restoration Value: within protected area Lowest Restoration Value: outside of protected area
23 Step 6: Land Use and Protection Status Data Used: Parcel based land use data from the Metropolitan Transit Commission (MTC); Protected open space from the California Protected Areas Database (ver 1.8) - GreenInfo.
24 Step 6: Restoration and Protection Indices (a) Protection Ranking not currently within protected area (1) ecological index + (2) land use value + (3) tidal (increase ranking ) or non-tidal (decrease ranking) (b) Restoration Ranking (1) protection status (protected = higher rank; not protected = lower rank) + (2) ecological index + (3) tidal (increase ranking ) or non-tidal (decrease ranking)
25 Step 8: Sea Level Rise Scenarios The Decision Support System will also account for Sea Level Rise (SLR) scenarios by mapping the distribution of tidal marsh habitats, including the transitional zones, using the following SLR scenarios from the National Research Council: 2050 (12-61 cm) 2100 ( cm)
26 Step 8: Sea Level Rise Scenarios 61 cm SLR existing
27 Step 8: Sea Level Rise Scenarios (South Bay)
28 Step 8: Sea Level Rise Scenarios (Bair Island)
29 Next Steps Step 7. Ground Truthung (underway) Step 9. Climate Change Scenarios (underway) Step 9. Rank & Prioritize Transitional Zone Habitats (existing and future) Future Enhancements Patch connectivity Improvement to Land (IL) ratio analysis (parcel) Landform categories (soil & topography) Site Specific Improvements Web Mapping Tool
30 Acknowledgments
31 San Francisco Bay Margin Conservation Decision Support System (DSS) Questions? Brian Fulfrost Brian Fulfrost and Associates
San Francisco Bay Ecotone Conservation and Management Decision Support System (DSS)
1 San Francisco Bay Ecotone Conservation and Management Decision Support System (DSS) Performance Report (June 2015) submitted by Brian Fulfrost (MS) Geospatial Lead Brian Fulfrost and Associates bfaconsult@gmail.com
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