USGS efforts to model sea-level rise impact to tidal marshes along the California coast.

Transcription

1 USGS efforts to model sea-level rise impact to tidal marshes along the California coast. Karen Thorne 1 J.Y Takekawa 1, K. Buffington 1, K. Swanson 2, J. Drexler 2, D.Schoellhamer 2, M. Casazza 3, and C. Overton 3 1 USGS Western Ecological Research Center, San Francisco Bay Estuary Field Station 2 USGS California Water Science Center, Sacramento 3 USGS Western Ecological Research Center, Dixon Field Station

2 Outline Brief introduction to sea-level rise & impacts to salt marsh wildlife Brief intro to modeling, why so different? Introduction to our program strategy San Pablo Bay NWR - sea-level rise modeling Tijuana Slough NWR establishment of baseline conditions

3 Overall Program Goals To establish baseline conditions at the local level, which can be used to understand and monitor changes from sea-level rise. To incorporate the tidal cycle into sea-level rise and storm impact models. Develop site specific sea-level rise models for land managers and decision makers. Use sea-level rise models to assess impacts on marsh plant communities and wildlife.

4 Sea-level rise scenarios Sea-level rise projections range from 9 to 88 cm by 2100 (IPCC 2007). Which includes thermal expansion of ocean waters and secondarily melting alpine glaciers. NO ice sheet dynamics included. 130 to 190 cm Grinsted et al. (2009) and Vermeer and Rahmstorf (2009) by to 110 cm (Jevrejeva et al. 2012) by CA Climate Adaptation Strategy report (2009)140 cm by 2100 (includes water trapping by dams), but does not include substantial ice melt from Greenland or west Antarctic ice sheet.

5 China Camp State Park/National Estuarine Research Reserve High tide and storm on January 22 nd, 2010 Video: J. Felis, USGS

6 Sea-level Rise Impacts on Marsh Wildlife Distribution When habitat is reduced wildlife emigrate or are lost Survival individual survival decreases when frequency of marsh flooding increases Reproduction productivity declines with nest flooding and young vulnerability

7 So many sea-level rise response models! Model Inputs: Starting elevation: LiDAR Ground (RTK GPS) Sea-level rise projection Accretion rate: sediment availability organic matter compaction Inundation time* Distance to sediment source* Efforts: Sea Level Affecting Marshes Model (SLAMM) Warren Pinnacle: users FWS SLAMM- View 2.0, National Wildlife Federation, among others. PRBO Conservation Science Sea-Level Rise Tool (Marsh98) NOAA Sea-level rise Digital Coast Sea level rise and coastal flooding impacts viewer

8 Objective: Investigate how sea-level rise could effect salt marsh communities at the local level Phase I Phase II Phase III Phase IV Baseline Conditions Sediment/Hydro Dynamics SLR Response Model Wildlife Risk Assessment Elevation Accretion/subsidence rate WARMER 1-D Habitat Use vs. Availability Vegetation THORNE 2-D Vertebrate Response Inundation Regime Population Change - PVA

9 Study sites along the Pacific Coast Tidal Range ft ( m), South-to-North Gradient 5.7 3

10 Phase I Phase II Phase III Phase IV Baseline Conditions Sediment/Hydro Dynamics SLR Response Model Wildlife Risk Assessment Elevation Vegetation Accretion/subsidence rate WARMER 1-D THORNE 2-D Habitat Use vs. Availability Vertebrate Response Inundation Population Change - PVA

11 Model Input Data: Elevation data Leica Real Time Kinematics GPS Network (RTK GPS) determines x,y,z position. ~2 cm elevation accuracy Synthesized to develop elevation models using ArcGIS.

12 Model Input Data: Water level monitoring Water level loggers are deployed in channels, 1-4 per site. Measures: depth, duration, conductivity, & temperature. Deployed up to 12 months. Used to develop local tidal datum relative to elevation.

13 Model Input Data: Vegetation Survey 0.25 m 2 quadrats are surveyed along transects. Data collected include: species, elevation, percent cover, max and average heights. Related to tidal datum.

14 Phase I Phase II Phase III Phase IV Baseline Conditions Sediment/Hydro Dynamics SLR Response Model Wildlife Risk Assessment Elevation Vegetation Accretion/subsidence rate WARMER 1-D THORNE 2-D Habitat Use vs. Availability Vertebrate Response Inundation Population Change - PVA

15 Model Input Data: Accretion rate Method depends on available data: Sediment cores 210Pb and 137Cs dating. Assess bulk density, % organic and inorganic matter. Surface Elevation Tables (SET) deployed longterm leveling device to measure precise elevation change Spatially explicit elevation change* - direct measurements of surface elevation change with RTK GPS.

16 Phase I Phase II Phase III Phase IV Baseline Conditions Sediment/Hydro Dynamics SLR Response Model Wildlife Risk Assessment Elevation Vegetation Accretion/subsidence rate WARMER 1-D THORNE 2-D Habitat Use vs. Availability Vertebrate Response Inundation Population Change - PVA

17 Sea-level rise modeling WARMER Can be done multiple ways depending on available data. WARMER: Wetland Accretion Rate Model for Ecosystem Resilience (modified from Calloway et al. 1996) done for 12 sites in San Francisco Bay. Uses core data (Swanson et al. in prep). A 1-D model of elevation that incorporates both biological and physical processes of vertical marsh accretion (Swanson et al. in prep). Thorne: relates observed accretion rates with inundation and distance from sediment source (Thorne et al. in prep) done for San Pablo Bay NWR (Thorne et al. in prep). A 2-D spatially explicit model for elevation change (Thorne et al. in prep)

18 Some results: San Pablo Bay NWR Extensive pickleweed areas San Pablo Bay National Wildlife Refuge

19 San Francisco Bay Fagan Over 8 million people 80% of historic tidal wetlands are gone. SFB marshes comprise 90% of California's remaining coastal wetlands. Tidal marsh species are impacted from: fragmentation, predation, invasive species, and pollution.

20 San Pablo Bay National Wildlife Refuge Second largest refuge in San Francisco Bay 13,190 acres Includes: open bay waters, salt marsh, intertidal mudflats, restored wetlands Managed for listed species

21 Elevation Goal: Develop Data high resolution elevation model Data: Elevation Data 1700 elevation points were collected. 68% of the elevation points fell within m. Field data collected in summer 2008 and 2009.

22 Elevation Model for San Pablo Bay NWR Snapshot for

23 Goal: Downscale tidal cycles to assess inundation patterns Data: Water level logging San Pablo Bay NWR Water level data is used to understand seasonal patterns of inundation and to develop local tidal datum.

24 Goal: Quantify plant species distribution relative to elevation and tidal datum Data: Vegetation Survey vegetation was surveyed at 800+ elevation points.

25 Plant species distribution: San Pablo Bay NWR

26 Accretion: Spatially explicit Sea-level rise modeling We used historic elevation data ( ) to determine Annual Accretion Rate (30 m x 30 m gridcells). Used this Annual Accretion Rate with: Starting elevation Inundation frequency Distance to sediment source Local sea-level rise rate to model the salt marsh response to sea-level rise to 2100 (Thorne et al. in prep).

27 San Pablo Bay NWR: sea-level rise results

28 San Pablo Bay NWR: elevation results

29 San Pablo Bay NWR Plant community Relative to MSL Scientific name Species Common name Community Mean SD Low High Spartina foliosa SPFO California cordgrass low Scirpus americanus SCAM bulrush mid Jaumea carnosa JACA jaumea mid Sarcocornia pacifica SAPA pickleweed mid-high Distichlis spicata DISP salt grass mid-high Frankenia salina FRSA alkali heath high Baccharis pilularis BAPI coyote brush high-upland We can use this information to define the plant community to interpret change with sea-level rise.

30 San Pablo Bay NWR plant community results

31 San Pablo Bay NWR results Salt marsh plant communities Endangered salt marsh harvest mouse

32 Expansion for San Pablo Bay NWR Bathymetric surveys for Tolay Creek (2012)

33 Other modeling results: SLAMM 6 Initial condition 1 m SLR scenario to 2100 Why?

34 Modeling: LiDAR/Bathymetry Corte Madera Marsh USGS 2010 Bathymetric Survey and Digital Elevation Model of Corte Madera Bay, California By Amy C. Foxgrover, David P. Finlayson, Bruce E. Jaffe, John Y. Takekawa, Karen M. Thorne, and Kyle A. Spragens

35 Modeling: RTK GPS vs. LiDAR elevation LiDAR Works well in low vegetation cover or bare ground. high spatial resolution (1x1 m) Dense vegetation increases elevation error. Corte Madera Marsh: average elevation error = 23 cm USGS Open-File Report OF

36 Some results: Tijuana Slough National Wildlife Refuge Tijuana Slough National Wildlife Refuge

37 Tijuana Slough National Wildlife Refuge One of southern CA largest remaining salt marshes Surrounded by San Diego County and Tijuana Mexico ~ 4.3 million people. Marshes are habitat for the endangered light-footed clapper rail and salt marsh bird s-beak. We have collected elevation, vegetation, and inundation information to establish baseline conditions for This can be used to model sea-level rise responses.

38 Frequency Tijuana Slough National Wildlife Refuge: Elevation Elevation (NAVD88, m) 5,913 elevation points taken in the salt marsh and adjacent uplands

39 Tijuana Slough National Wildlife Refuge: Vegetation Distribution 1,483 Vegetation points

40 Tijuana Slough National Wildlife Refuge: Water Level Monitoring

41 Using baseline data for restoration: San Diego Refuge Complex Otay River Estuary Restoration Project San Diego used our elevation, inundation and vegetation baseline relationships to establish restoration targets. Bolsa Cell Seal Beach National Wildlife Refuge elevation and inundation data was used to assist in the development of a hydrologic model. Which was used for a muted marsh culvert replacement.

42 Conclusions Sea-level rise modeling efforts vary due to input datasets. Investment in intensive site-specific data collection results in quality baseline characterization that is used to develop sea-level response models at a scale relevant to management decisions. Establishing baseline conditions can allow the monitoring of a salt marsh for change with sea-level rise and can be used for other management activities such as restoration.

43 Acknowledgments USGS Climate Change Program USGS National Climate Change and Wildlife Science Center California LCC North Pacific LCC U.S. Fish & Wildlife Service I & M Program U.S. Fish & Wildlife Service Recovery Branch U.S. Fish & Wildlife Service Refuges: SFBNWR, SDNWR NOAA NERR China Camp SP, Tijuana Estuary USGS Western Ecological Research Center USGS California Water Science Center USGS Native American Internship Program California Department of Fish & Game East Bay Regional Parks University of California, Davis