Potential Impacts of Non-Native Spartina Spread on Shorebird Populations in South San Francisco Bay Final Report to Coastal Conservancy Invasive Spartina Project Contract # 02-212 February 29, 2004 Diana Stralberg*, Viola Toniolo, Gary W. Page and Lynne E. Stenzel PRBO Conservation Science, 4990 Shoreline Highway, Stinson Beach, CA 94970 (http://www.prbo.org) * corresponding author ([email protected]) Potential Impacts of Non-Native Spartina Spread on Shorebird Populations in South San Francisco Bay This project was made possible by funding from the California Coastal Conservancy, the State Resources Agency, and the CALFED Program, through Coastal Conservancy contract #02-212. The analyses presented herein were requested by the Coastal Conservancy’s Invasive Spartina Project (ISP)—a coordinated regional effort among local, state and federal organizations dedicated to preserving California's extraordinary coastal biological resources through the elimination of introduced species of Spartina (cordgrass) (http://www.spartina.org/). Executive Summary San Francisco Bay holds 70% of California’s mudflats and provides habitat to more wintering and migratory shorebirds than any other wetland along the Pacific coast of the contiguous U.S. The bay’s mudflats are currently threatened by the spread of a non-native cordgrass, Spartina alterniflora, and associated hybrids, which grow at lower elevations than the native S. foliosa and can render large mudflat areas effectively unavailable to shorebirds for foraging. Using shorebird and benthic invertebrate survey data, tidal benchmark data, and GIS-based habitat data, we analyzed the potential effect of S. alterniflora on shorebird habitat in the South Bay by creating grid-based spatial models of shorebird habitat value and potential S. alterniflora spread. We developed 12 potential scenarios of habitat value loss for shorebirds based on assumptions about invertebrate density, inundation tolerance of S. alterniflora, and temporal availability of mudflat resources. Predictions of habitat value loss ranged from 9% to 80%. We identified the upper mudflats, due to their greater exposure time, and the east and south shore mudflats, due to the high numbers of birds detected there, as the areas of highest value to shorebirds in the South Bay. These areas also coincide with the areas of greatest Spartina invasion potential. Suggested citation: Stralberg, D., V. Toniolo, G.W. Page, and L.E. Stenzel. 2004. Potential Impacts of Non-Native Spartina Spread on Shorebird Populations in South San Francisco Bay. PRBO Report to California Coastal Conservancy (contract #02-212). PRBO Conservation Science, Stinson Beach, CA. i Introduction The San Francisco Bay estuary holds 70% of the mudflats in California (Ayres et al. 1999), providing habitat annually to over 350,000 migrating shorebirds (Charadrii) in the fall and over 900,000 in the spring (based on single-day counts, Stenzel et al. 2002). Along the Pacific coast of the contiguous United States alone (excluding Alaska), the bay holds more shorebirds than any other wetland in all seasons (Page et al. 1999). Although the current extent of S. alterniflora and associated hybrids is mostly limited to tidal marsh plains and channels, further spread poses a great threat to the mudflats upon which shorebirds depend. Shorebirds have difficulty landing in and utilizing areas of dense growth (Josselyn 1983, Evans 1986, White 1995), and studies have shown that Spartina growth effectively reduces the foraging area available to them (Goss-Custard and Moser 1988). In light of this, PRBO Conservation Science (PRBO) has completed a preliminary GIS- based analysis of the potential effects of non-native Spartina on shorebird habitat in South San Francisco Bay (the South Bay), creating grid-based spatial models of (a) shorebird habitat value and (b) potential S. alterniflora spread. This analysis was accompanied by a review of the scientific literature pertaining to shorebird use of mudflats and potential effects of non-native Spartina on shorebird numbers (see Appendix 1). Methods Many studies have demonstrated that shorebird use of mudflat habitats is spatially and temporally variable, and that this variation is closely tied to cycles of tidal inundation and the uneven distribution of sediments, prey densities, and prey availability across the intertidal zone (Burger et al. 1977, Goss-Custard et al. 1977, Puttick 1977, Goss-Custard 1979, Page et al. 1979, Quammen 1982, Evans 1986, Colwell and Landrum 1993, Yates et al. 1993, White 1995, Arcas et al. 2003). Our quantification of shorebird habitat value incorporated this variation within mudflats, which is based on tidal inundation cycles and presumed invertebrate distributions, as well as variation among mudflats, which is based on shorebird use data from PRBO’s Pacific Flyway surveys (1988-1993, Page et al. 1999). For the purpose of this exercise, we assumed that South Bay mudflats were at carrying capacity (i.e., the maximum number of birds that can be supported by a finite food supply) at the time of the surveys. By extension, we assumed that loss PRBO Spartina-Shorebird Final Report, Feb 2004 Page 1 of 61 of habitat in one area would not be compensated for by increased use of other areas. (See Appendix 1 for a discussion of carrying capacity issues.) The spread potential of S. alterniflora and associated hybrids was based on percentiles of cumulative monthly tidal inundation across the mudflats. The cumulative monthly duration of inundation at a particular site is a function of mudflat elevation and tidal range, with a greater tidal range resulting in a longer duration of inundation. According to Collins’ (2002) analyses of non-native Spartina locations in San Francisco Bay, the lower limit of Spartina growth appears to correspond with cumulative monthly inundation, and existing S. alterniflora locations suggest that the maximum cumulative duration of inundation tolerated during the month of June is approximately 70%, regardless of mean tidal range1. This means that the smaller the tidal range, the lower the elevation at which non-native Spartina would be predicted to grow. Due to uncertainty about the behavior of S. alterniflora hybrids, and because these plants are known to change their environment over time (Ranwell 1964, Daehler and Strong 1996), accreting sediment at rates of 1-2 cm/year in Willapa Bay (Sayce 1988) and up to 4 cm/year in Australia (Bascand 1970), we evaluated a range of inundation tolerances between 60% and 80%. Thus, the model based on a 60% inundation tolerance was intended to reflect what early stages of spread may look like, while that based on a 80% inundation tolerance would represent a hypothetical example of how much farther non-native Spartina could spread beyond its assumed maximum if it caused substantial sediment accretion to occur, or if hybrid individuals were able to tolerate greater inundation rates. We assumed that mudflat areas covered by S. alterniflora and associated hybrids would be effectively lost to shorebirds. Our GIS-based analysis was restricted to mudflats mapped by the San Francisco Estuary Institute’s EcoAtlas (v. 1.50b, SFEI 1998) south of the San Francisco Bay Bridge. Using EcoAtlas map layers, PRBO shorebird surveys (Stenzel et al. 2002), PRBO invertebrate data from Bolinas Lagoon, and tide level data from the National Oceanic and Atmospheric Administration’s (NOAA) tidal benchmarks, we developed a set of grid-based data layers (ArcInfo format) that were combined to generate predictions about the potential loss of mudflat habitat and shorebird numbers. 1 Initial estimates of 40% presented in Collins (2002) have since been revised. PRBO Spartina-Shorebird Final Report, Feb 2004 Page 2 of 61 To generate the GIS grid layers for this analysis, we completed the following steps using Spatial Analyst for ArcView 3.2 (ESRI 1999) and the ArcInfo 8.3 GRID module (ESRI 2002). A. Elevation/Bathymetry We were not aware of any available elevation or bathymetry data layers for the South Bay of a fine enough resolution to capture mudflat topography adequately. To enable the creation of a spread model for S. alterniflora and associated hybrids, we elected to model mudflat elevation at a 3x3 m2 (3-m) pixel resolution, creating a digital elevation model (DEM) based on mapped mudflat boundaries, tide level data, and an assumed linear mudflat slope. i. Mean tide level (MTL) and mean lower low water (MLLW) contours were estimated from EcoAtlas (SFEI 1998) and were defined based on the boundaries between mudflat and tidal marsh and between open water and mudflat, respectively. Actual elevations along the MTL contour were not assumed to be constant, but were assigned based on MTL elevation at the closest tidal benchmark location. MTL elevations were obtained from NOAA’s National Oceanic Service (NOS) published benchmark sheets (http://www.co-ops.nos.noaa.gov/bench_mark.shtml?region=ca) for seven South Bay locations that have been referenced to the new National Tidal Datum Epoch (NTDE; 1983-2001) (Table 1). ii. For each mudflat area we assumed that local MTL was the same as that of the nearest NTDE-referenced benchmark and created a 3-m MTL grid covering the South Bay mudflats. iii. We used MTL and MLLW contours to determine the width of the mudflat for each 3-m pixel. We calculated the distance from each pixel to the MTL line and to the MLLW line, to obtain two separate distance grids, which were then added to obtain a single grid representing mudflat width. iv. For each mudflat section we estimated the slope (assumed linear) by dividing the total change in elevation across the mudflat (MTL grid) by the mudflat width grid (slope = rise/run). We removed values that exceeded a slope of 0.1 (10%), assuming that the low gradient of mudflats would be well below this value. v. Next we created two 3-m elevation grids based on the following equations, where each 3- m pixel value was equal to the elevation at that point: elevation 1 = slope * distance to MLLW PRBO Spartina-Shorebird Final Report, Feb 2004 Page 3 of 61 elevation 2 = MTL – (slope * distance to MTL) We averaged these two grids to obtain the final 3-m mudflat elevation grid (DEM).