Proceedings of the Third International Conference on Invasive ...

Chapter 3: Ecosystem Effects <strong>of</strong> Invasive Spartina<strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> <strong>Third</strong> <strong>International</strong> <strong>Conference</strong> on Invasive SpartinaMETHODSMany studies have demonstrated that shorebird use <strong>of</strong>mudflat habitats is spatially and temporally variable, and thatthis variation is closely tied to cycles <strong>of</strong> tidal inundation, aswell as prey availability across <strong>the</strong> intertidal zone (Burger etal. 1977; Goss-Custard et al. 1977; Puttick 1977; Page et al.1979; Colwell and Landrum 1993; Yates et al. 1993). While wedid not have data on prey availability in San Francisco Bay,our quantification <strong>of</strong> shorebird habitat value did incorporatevariation within mudflats based on tidal inundation cycles, aswell as variation among mudflats based on shorebird use datafrom PRBO’s Pacific Flyway surveys (1988-1993, Page et al.1999). For <strong>the</strong> purpose <strong>of</strong> this exercise, we assumed that SouthBay mudflats were at carrying capacity (i.e., <strong>the</strong> maximumnumber <strong>of</strong> birds that can be supported by a finite food supply)at <strong>the</strong> time <strong>of</strong> <strong>the</strong> surveys. By extension, we assumed thatloss <strong>of</strong> habitat in one area would not be compensated for byincreased use <strong>of</strong> o<strong>the</strong>r areas.The spread potential <strong>of</strong> S. alterniflora and associatedhybrids was based on percentiles <strong>of</strong> cumulative monthly tidalinundation across <strong>the</strong> mudflats. The cumulative monthlyduration <strong>of</strong> inundation at a particular site is a function <strong>of</strong>mudflat elevation and tidal range, with a greater tidal rangeresulting in a longer duration <strong>of</strong> inundation. According toCollins’ (2002) analyses <strong>of</strong> non-native Spartina locationsin San Francisco Bay, <strong>the</strong> lower limit <strong>of</strong> Spartina growthappears to correspond with cumulative monthly inundation,and existing non-native Spartina locations suggest that <strong>the</strong>maximum cumulative duration <strong>of</strong> inundation tolerated during<strong>the</strong> month <strong>of</strong> June is approximately 70%, regardless <strong>of</strong> meantidal range. 1 This means that <strong>the</strong> smaller <strong>the</strong> tidal range, <strong>the</strong>lower <strong>the</strong> elevation at which non-native Spartina would bepredicted to grow. Due to uncertainty about <strong>the</strong> behavior <strong>of</strong>S. alterniflora hybrids, and because <strong>the</strong>se plants are known tochange <strong>the</strong>ir environment over time (Ranwell 1964; Daehlerand Strong 1996), accreting sediment at rates <strong>of</strong> 1-2 cm/yearin Willapa Bay (Sayce 1988) and up to 4 cm/year in Australia(Bascand 1970), we evaluated a range <strong>of</strong> inundation tolerancesbetween 60% and 80%. We assumed that mudflat areascovered by S. alterniflora and associated hybrids would beeffectively lost to shorebirds.Our GIS-based analysis was restricted to mudflatsmapped by <strong>the</strong> San Francisco Estuary Institute’s EcoAtlas(v. 1.50b, SFEI 1998) south <strong>of</strong> <strong>the</strong> San Francisco Bay Bridge.Using EcoAtlas map layers, PRBO shorebird surveys (Stenzelet al. 2002), and tide level data from <strong>the</strong> National Oceanicand Atmospheric Administration’s (NOAA) tide stations, wedeveloped a set <strong>of</strong> grid-based data layers (ArcInfo format)that were combined to generate predictions about <strong>the</strong> potentialloss <strong>of</strong> mudflat habitat and shorebird numbers.To generate <strong>the</strong> GIS grid layers for this analysis, wecompleted <strong>the</strong> following steps using <strong>the</strong> ArcInfo 8.3 GRIDmodule (ESRI 2002).1 Initial estimates <strong>of</strong> 40% presented in Collins (2002) have since been revised.Fig. 1. Tide station locations, station IDs, and allocation <strong>of</strong> tide stationswith continuous water level data to mudflat areas. Tide station informationwas obtained from NOAA/NOS (http://tidesandcurrents.noaa.gov/).Elevation/BathymetryWhen this analysis was performed, bathymetry datalayers <strong>of</strong> a fine enough resolution to capture mudflat topographywere not available for <strong>the</strong> South Bay. Thus, to createa spread model for S. alterniflora and associated hybrids,we elected to estimate mudflat elevation at a 3x3 m 2 (3-m)pixel resolution, creating a digital elevation model (DEM)based on mapped mudflat boundaries, tide level data, and anassumed linear mudflat slope.First, mean tide level (MTL) and mean lower low water(MLLW) contours were estimated from EcoAtlas (SFEI1998) and were defined based on <strong>the</strong> boundaries betweenmudflat and tidal marsh and between open water and mudflat,respectively. Actual elevations along <strong>the</strong> MTL contour werenot assumed to be constant, but were assigned based on MTLelevation at <strong>the</strong> closest tide station. MTL elevations wereobtained from NOAA’s National Oceanic Service (NOS)published benchmark sheets for seven South Bay locationsthat have been referenced to <strong>the</strong> new National Tidal DatumEpoch (NTDE; 1983-2001) (Fig. 1). For each mudflat area weassumed that local MTL was <strong>the</strong> same as that <strong>of</strong> <strong>the</strong> nearestNTDE-referenced tide station.Next we used MTL and MLLW contours to determine<strong>the</strong> width <strong>of</strong> <strong>the</strong> mudflat for each 3-m pixel. We calculated <strong>the</strong>distance from each pixel to <strong>the</strong> MTL line and to <strong>the</strong> MLLWline, to obtain two separate distance grids, which were <strong>the</strong>nadded to obtain a single grid representing mudflat width. For- 176 -