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). Values greater than MTL were redefined to be equal to local MTL.

B. Tidal Inundation i. Published verified six-minute water level data was available from NOS (http://www.co- ops.nos.noaa.gov/data_retrieve.shtml?input_code=100111111vwl) for only three of the seven benchmark locations: Alameda (station ID 9414750, year 2001), Dumbarton Bridge (station ID 9414509, year 1996), and Redwood City (station ID 9414523, year 2002). Assuming that the tidal inundation regime for each mudflat area was most similar to the nearest benchmark with available 6-minute water level data, we created a benchmark grid layer by allocating each 3m pixel to a benchmark (Fig. 1). ii. Because our shorebird data collection was centered around April and September, we generated monthly inundation curves for these months using cumulative water level data from the Alameda, Dumbarton Bridge, and Redwood City benchmarks using Visual FoxPro 3.0b (1995) and Stata 8.0 (2003) (Figs. 2, 3). Water level values were in meters above MLLW. iii. To predict the monthly tidal inundation percent of each 3-m mudflat pixel, we performed separate polynomial regression analyses (Stata 8.0, 2003) for each benchmark and each month (April and September) using the appropriate NOS 6-minute water level data. Resulting regression equations (Table 2) were used to calculate grids representing April and September inundation. Separate equations were developed for each benchmark so grids for each of the three benchmark areas (Fig. 1) could be calculated separately and then merged to create one seamless 3-m inundation grid for each season. iv. Finally, we generated grids representing April and September mudflat exposure (100 - monthly inundation percent).

C. Invertebrate Densities Based on preliminary analysis of Bolinas Lagoon invertebrate data from the fall of 1973 (PRBO, unpublished data) we estimated a 5:1 ratio between the lower mudflats (higher invertebrate densities) and upper mudflats (lower invertebrate densities). This ratio was used to develop 3m grids of relative invertebrate density for South Bay mudflats. Assuming that the distribution of invertebrates was strongly tied to tidal inundation regimes, we used a

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 4 of 61 reclassified version of our cumulative monthly inundation grids to develop April and September invertebrate density index grids.

D. Shorebird Habitat Value: Variation Within Mudflats Assuming that the value of mudflats for shorebirds is determined by a combination of temporal availability (i.e., mudflat exposure time) and food quality (i.e., invertebrate density), we combined the monthly exposure and invertebrate density grid layers to create an overall index of habitat value. Standardizing exposure time (both April and September) and invertebrate density on a scale of 1 to 100, we averaged the exposure time and invertebrate density grids to obtain 3m grids representing fall and spring indices of overall shorebird habitat value (Fig. 4)

E. Shorebird Habitat Value: Variation Among Mudflats We used PRBO’s shorebird survey data to estimate fall and spring shorebird numbers and overall biomass (kg) for each of six South Bay mudflat census tracts (Stenzel et al. 2002). This resulted in fall and spring shorebird density grids, with densities uniformly distributed over each census tract.

F. Potential Spartina Spread i. Cumulative water level data from the Alameda, Dumbarton Bridge and Redwood City benchmarks were used to generate monthly June inundation curves using Visual FoxPro 3.0b (1995) and Stata 8.0 (2003). Water level values were in meters above MLLW. ii. For each tidal benchmark, June duration of inundation curves were used to identify the elevations at which 60%, 70%, and 80% cumulative monthly inundation were achieved (Fig. 5). Each elevation was considered a potential threshold below which S. alterniflora would not grow (i.e., its inundation tolerance). We then calculated potential S. alterniflora spread for each inundation tolerance, selecting all mudflat pixels with modeled elevations above that particular elevation threshold.

G. Potential Effects of Spartina Spread on Shorebird Numbers Using the GIS grid layers described above, we estimate the potential effects of non-native Spartina spread on shorebird numbers, incorporating within- and among-marsh variation (items D and E above).

i. For each of the six South Bay census tracts we calculated the proportion of habitat value

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 5 of 61 that would be lost under each Spartina spread scenario (60%, 70%, and 80% inundation tolerance). As a quasi-sensitivity analysis we also compared four different approaches to calculating the shorebird habitat value of mudflats: a) All mudflat areas of equal value to shorebirds. b) 5:1 ratio between lower and upper mudflat value, based on invertebrate densities. c) Mudflat value inversely related to the percent of mudflat inundation time (i.e., upper mudflats have higher value). d) Mudflat value based on invertebrate density and inundation time (b and c combined, partially offsetting one another). ii. For the three Spartina spread scenarios and four mudflat value scenarios (12 combinations total) we calculated a predicted loss of spring and fall shorebird biomass by multiplying the proportion of mudflat value lost in each census tract with the total estimated shorebird biomass supported by that census tract. iii. To predict the potential loss of shorebird numbers (by species) we simply used the middle Spartina spread scenario (70% inundation tolerance) and the middle mudflat value scenario (index based on inundation and invertebrate density).

Results

PRBO’s shorebird surveys (1988-1993) found that shorebird density and biomass were highest along the southern and eastern shores of the South Bay during fall (2.32-6.62 kg/ha) and along the eastern shore during spring (4.33-6.37 kg/ha). Species that concentrated in the South Bay were Black-bellied Plover, Willet, Marbled Godwit, small sandpipers, and dowitchers (Stenzel et al. 2002). Overall shorebird numbers were higher in spring than in fall, driven primarily by the large number of Western Sandpipers that use San Francisco Bay as a staging area during spring migration (Table 4). Because Western Sandpipers are small-bodied shorebirds, the difference between fall and spring biomass was much smaller than the difference between fall and spring numbers (see Appendix 2 for shorebird use maps). Spartina spread models predicted that between 14% and 54% of the total South Bay mudflat area could be encroached upon by S. alterniflora and associated hybrids (Fig. 6, Table 3). Overall, the predicted loss of mudflat habitat value for shorebirds, based on all 12 potential scenario combinations, ranged from 9% (assuming 60% Spartina inundation tolerance and

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 6 of 61 mudflat habitat value driven only by lower invertebrate densities in the upper mudflats) to 80% (assuming 80% Spartina inundation tolerance and mudflat habitat value driven only by greater exposure of the upper mudflats) (Fig. 7, Table 3). Using the middle scenarios (70% Spartina inundation tolerance and mudflat habitat value driven by a combination of invertebrate density and inundation), we obtained estimates of 34% and 33% habitat loss in fall and spring, respectively. These estimates were remarkably close to the values obtained by assuming equal value across mudflats (33%), due to the nearly counteracting effects of invertebrate density and inundation, using our assumptions about invertebrate densities from Bolinas Lagoon. This highlights the need to study the spatial distribution of invertebrates over San Francisco Bay mudflats, especially given the dynamic nature of this largely non-native community (Nichols et al. 1986, Cohen and Carlton 1998). Our models did not incorporate any species-specific differences in shorebird foraging habits; thus the predicted proportional change in numbers was the same for all groups. Due to migration timing and overall numbers detected on shorebird surveys, Spartina spread would have the biggest numerical impact on small shorebirds, dowitchers, and Marbled Godwits (Fig. 8, Table 4). Willets and Black-bellied Plovers would be most affected during the fall, when their numbers are highest. In terms of total bird biomass (see Stenzel et al. 2002), the largest predicted losses were in the spring, due to higher overall biomass densities (Fig. 7). Combining our estimates of variation within and among mudflats, 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 (Figs. 8, 9). These areas also coincide with the areas of greatest Spartina invasion potential, based on elevation (upper mudflats), initial S. alterniflora introduction locations (mostly east shore), and planned tidal marsh restoration activities (mostly east and south shore salt ponds).

Future Directions

The results presented herein are based on several basic assumptions, all of which should be examined in further detail in order to restrict the wide range of predicted shorebird losses. The following represents a summary of assumptions that we made, follow-up research questions, and suggestions for testing or improving those assumptions.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 7 of 61 1. Carrying Capacity Our most basic assumption was that the mudflat habitats were at carrying capacity during the fall and spring survey periods. However, it is possible that only preferred areas are functioning at carrying capacity (Goss-Custard 1979). If individuals could switch to lower- quality mudflat areas without significantly affecting their overall fitness, then the potential loss of birds may have been overestimated (Goss-Custard 2003). Anecdotal evidence suggests that San Francisco Bay mudflats may reach carrying capacity during the winter, when storm-related flooding may prompt some species to move inland to the Central Valley (Warnock et al. 1995, Takekawa et al. 2002) but we do not know if mudflats and neighboring tidal and salt pond habitats are at carrying capacity during migration. Currently, we lack the data on mudflat food resources, shorebird energetics, and individual foraging behavior (especially prey preference) that would be necessary to obtain an estimate of carrying capacity. Research questions: • When and where are mudflats at carrying capacity, if at all? What potential, if any, exists for shorebirds to switch to other nearby habitats (e.g., salt ponds)? • How does shorebird use of mudflats in winter compare with fall and spring use? • What mudflat invertebrate species are preferred by different shorebird species? • Is prey availability a limiting factor for shorebirds during migration? • Is prey availability more limiting for wintering birds? • Do winter storms exacerbate the effective mudflat habitat loss caused by Spartina invasion? Would San Francisco Bay birds be more likely to go inland to the Central Valley during the winter under a high Spartina invasion scenario? Suggested next steps: • Compare mudflat shorebird numbers and densities with South Bay salt pond and tidal marsh numbers and densities, based on existing PRBO survey data. Incorporate mudflat habitats and change predictions into future iterations of PRBO’s habitat conversion model (see http://www.prbo.org/cms/index.php?mid=131&module=browse). • Conduct new mudflat surveys across seasons (fall, winter, spring; at least two per season) at a subset of South Bay mudflats. Identify periods of peak shorebird use and compare with previous surveys.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 8 of 61 • Conduct shorebird use surveys concurrently with benthic invertebrate samples across a subset of South Bay mudflats. Analyze relationships between densities of specific shorebird and invertebrate species. • Obtain South Bay water level data for winter storm periods and model available mudflat areas during these periods. • Collect and analyze diet data for shorebirds feeding on mudflats across tides and seasons.

2. Mudflat topography and tidal inundation In order to estimate mudflat elevations, we interpolated between MTL and MLLW contours by assuming a linear mudflat slope. In reality, South Bay mudflat slopes may be significantly different from linear (B. Jaffe, USGS, pers. comm., Dec 2003). While high-resolution topographic/bathymetric data are not currently available for the entire South Bay mudflat region, we hope that future Light Detection and Ranging (LiDAR) flights planned by USGS will result in a fine-scale DEM that may be used to improve our models. With respect to tidal inundation regimes, we used water level data from three benchmarks to represent the entire South Bay. In reality, the tidal range varies greatly in the South Bay, and small local differences could have a large influence on our model predictions. In order to interpret our predictions at the local scale, a refinement of tidal inundation maps, based on local water level data, would be necessary. Research questions: • What are actual mudflat slopes and microtopographic characteristics? • Could detailed bathymetry data (e.g., LiDAR) improve our ability to predict Spartina spread? • How do predictions of shorebird habitat loss vary with local tidal inundation regimes? • How important is tidal range in determining potential Spartina spread? Suggested next steps: • Work with Janie Civille of UC Davis to analyze existing LiDAR-derived Willapa Bay mudflat topography, its relationship to Spartina spread characteristics, and potential relevance to San Francisco Bay.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 9 of 61 • Work with Bruce Jaffe of USGS and/or other coastal geomorphologists to develop more detailed digital elevation models more accurately representing mudflat slopes. Rerun model predictions with refined mudflat slopes. • Obtain continuous water level data from additional (non-NOS) tide gauges and create more locally appropriate tidal inundation graphs for each major mudflat section. Rerun model predictions with refined inundation data.

3. Mudflat heterogeneity To refine our predictions about potential shorebird habitat loss under various Spartina spread scenarios, we attempted to incorporate mudflat heterogeneity into our models by considering tidal inundation cycles and potential variation in invertebrate densities. In doing this, we made some additional simplifying assumptions related to the temporal and spatial use of mudflat habitats by shorebirds. For example, we assumed that exposed mudflat areas are used evenly by shorebirds, although we know that individuals of many species tend to forage along the rising or receding tide line (Colwell and Landrum 1993, Durell et al. 1997). Furthermore, we used a crude linear estimate of the invertebrate density gradient that was based on Bolinas Lagoon data from the 1970s. Given that San Francisco Bay has a different invertebrate community than Bolinas Lagoon, estimates should eventually be recalculated using San Francisco Bay data (T. Grosholz, UC Davis, pers. comm., Nov 2003). Research questions: • Is the value of the upper mudflats derived from their longer exposure time offset by higher invertebrate densities in the lower mudflats? • How do benthic invertebrate densities vary over the elevation/inundation gradient of mudflats? How do they vary over mudflats of different substrates and salinities? • How does prey availability and energetic value relate to prey density, both spatially and temporally? • How do shorebird species differences in prey selection affect their exploitation of mudflat prey resources? • How does the species composition and abundance of foraging shorebirds vary across the mudflat elevation/inundation gradient by season? Suggested next steps:

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 10 of 61 • Enter and analyze additional PRBO invertebrate data from Bolinas Lagoon collected in the 1970s, as well as data from upcoming 2004 surveys, in order to describe more comprehensively the spatial distribution patterns of benthic invertebrates. • Work with Ted Grosholz at UC Davis and researchers at Bodega Bay Marine Lab to analyze existing benthic invertebrate distribution data from San Francisco and Bodega Bays, respectively. Compare distribution patterns with Bolinas Lagoon and rerun model predictions under different assumptions about invertebrate distribution patterns. • Work with Ted Grosholz and other aquatic entomologists to collect new benthic invertebrate data, concurrent with shorebird use data, across seasons, tides, substrates, and salinities in the South Bay. Refine model predictions based on new results pertaining to foraging shorebird and benthic invertebrate distributions (temporal and spatial).

4. Upper vs. lower limits of non-native Spartina spread Our models examined only the lower limits of Spartina spread and the subsequent impacts on shorebird habitat value. In reality, the upward spread of S. alterniflora and hybrids may pose an equally serious threat to shorebirds as mudflats along tidal channels and open areas within the marsh plain are colonized by invasive Spartina and become unavailable to foraging shorebirds. Tidal marsh breeding birds such as the Alameda Song Sparrow (Melospiza melodia pusillula) and California Clapper Rail (Rallus longirostris obsoletus) are also likely to be affected by invasive Spartina spread, as nesting substrates and foraging opportunities change. Research questions: • What is the magnitude and relative importance for shorebirds of invasive Spartina spread along channel mudflats, compared to its predicted spread across open mudflats? • How will tidal marsh birds be affected by invasive Spartina spread? Which species will be adversely affected and which will benefit? Suggested next steps: • Using shorebird data collected by PRBO, combined with South Bay tidal marsh area surveys used to develop PRBO’s habitat conversion model, calculate relative shorebird densities along major and minor tidal channels, and compare these densities with open mudflat densities.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 11 of 61 • Identify the potential upper limits of invasive Spartina spread, in terms of elevation and monthly tidal inundation, using Spartina location data and site-specific water level data. • Establish a new study to monitor nest site selection and reproductive success in South Bay tidal marsh breeding birds, comparing Spartina-invaded and non-invaded marsh areas.

5. Future change Finally, our model predictions were based on a static picture of mudflat spatial extent and elevation. In reality, there are several factors in addition to S. alterniflora spread that may affect mudflat extent and quality, including sea level rise (Galbraith et al. 2002), tidal marsh restoration, and natural geomorphologic processes. Thus it would be useful to apply our models to future mudflat predictions developed by coastal geomorphologists. Research questions: • What will San Francisco Bay mudflats look like in the future? Will a baywide sediment deficit combined with sea level rise cause existing mudflats to shrink? How will tidal marsh restoration affect mudflats? • Will Spartina spread cause enough sediment accretion to raise mudflat elevations? • Will Spartina spread affect invertebrate populations on outboard mudflats? • How will shorebirds respond to invasive Spartina removal/treatment areas? Will treatment areas support similar bird densities as non-invaded areas? Suggested next steps: • As predictions for mudflat change are developed by coastal geomorphologists, generate new predictions for Spartina spread and shorebird habitat value. • Survey multiple treatment and control areas for birds prior to, during, and after the treatment of invasive Spartina. Analyze the effects of Spartina removal on bird communities, controlling for local site variation.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 12 of 61 Acknowledgments

This project was requested by the Invasive Spartina Project (ISP), a project of the California Coastal Conservancy, and funded by the California Coastal Conservancy, the State Resources Agency, and the CALFED Program, under contract #02-212. We would like to thank Katy Zaremba and Peggy Olofson of the ISP, Don Strong, Debra Ayres, Janie Civille and Ted Grosholz of UC Davis, and Bruce Jaffe of USGS for their valuable input and support. We are also grateful to Josh Collins and Stuart Siegel for advice on methods, and to Hildie Spautz for assistance with the literature review. Finally, we are very grateful for the assistance of the 100+ people who volunteered their time and expertise to make the shorebird surveys possible. This is PRBO contribution number 1078.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 13 of 61 Literature Cited

Arcas, J., F. Benitez, and M. Paramos. 2003. Diet and habitat use of Sanderling Calidris alba, wintering in a southern European estuary. Alauda 71:69-77. Ayres, D. R., D. Garcia-Rossi, H. G. Davis, and D. R. Strong. 1999. Extent and degree of hybridization between exotic (Spartina alterniflora) and native (S. foliosa) cordgrass (Poaceae) in California, USA determined by random amplified polymorphic DNA (RAPDs). Molecular Ecology 8:1179-1186. Bascand, L. D. 1970. The roles of Spartina species in New Zealand. Proc. N.Z. Ecol. Soc. 17:33- 40. Burger, J., M. A. Howe, D. C. Hahn, and J. Chase. 1977. Effects of tide cycles on habitat selection and habitat partitioning by migrating shorebirds. Auk 9:743-758. Cohen, A. N. and J. T. Carlton. 1998. Accelerating invasion rate in a highly invaded estuary. Science 279:555-558. Collins, J. N. 2002. Invasion of San Francisco Bay by smooth cordgrass, Spartina alterniflora: a forecast of geomorphic effects on the intertidal zone. Unpublished report of San Francisco Estuary Institute, Oakland, CA. Colwell, M. A. and S. L. Landrum. 1993. Nonrandom shorebird distribution and fine-scale variation in prey abundance. Condor 95:94-103. Daehler, C. C. and D. R. Strong. 1996. Status, prediction and prevention of introduced cordgrass Spartina spp. invasions in Pacific estuaries, USA. Biological Conservation 78:51-58. Durell, S. E., A. LeDit, J. D. Goss-Custard, and R. T. Clarke. 1997. Differential response of migratory subpopulations to winter habitat loss. Journal of Applied Ecology 34:1155- 1164. ESRI. 1999. Spatial Analyst 1 Extension for ArcView 3.x. Environmental Systems Research Institute, Redlands, CA. ESRI. 2002. ArcInfo 8.3. Environmental Systems Research Institute, Redlands, CA. Evans, P. R. 1986. Use of the herbicide 'Dalapon' for control of Spartina encroaching on intertidal mudflats: beneficial effects on shorebirds. Colonial Waterbirds 9:171-175. Galbraith, H., R. Jones, R. Park, J. Clough, S. Herrod-Julius, B. Harrington, and G. Page. 2002. Global climate change and sea level rise: potential losses of intertidal habitat for shorebirds. Waterbirds 25:173-183.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 14 of 61 Goss-Custard, J. D. 1979. Effect of habitat loss on the numbers of overwintering shorebirds. Studies in Avian Biology 2:167-177. Goss-Custard, J. D. 2003. Fitness, demographic rates and managing the coast for wader populations. Wader Study Group Bulletin 100:183-191. Goss-Custard, J. D., R. E. Jones, and P. E. Newbery. 1977. The ecology of the Wash. I. Distribution and diet of wading birds (Charadrii). Journal of Applied Ecology. 14:681- 700. Goss-Custard, J. D. and M. E. Moser. 1988. Rates of change in the numbers of Dunlin, Calidris alpina, wintering in British estuaries in relation to the spread of Spartina Anglica. Journal of Applied Ecology. 25:95-109. Josselyn, M. 1983. The ecology of San Francisco Bay tidal marshes: a community profile. U.S. Fish and Wildlife Service, Division of Biological Services, FWS/OBS-83/23. Washington D.C. Microsoft. 1995. Visual FoxPro 3.0b. Microsoft Corporation, Seattle, WA. Nichols, F. H., J. E. Cloern, S. N. Luoma, and D. H. Peterson. 1986. The modification of an estuary. Science 231:567-573. Page, G. W., L. E. Stenzel, and J. E. Kjelmyr. 1999. Overview of shorebird abundance and distribution in wetlands of the Pacific Coast of the contiguous United States. Condor 101:461-471. Page, G. W., L. E. Stenzel, and C. M. Wolfe. 1979. Aspects of the occurrence of shorebirds on a central California estuary. Studies in Avian Biology 2:15-32. Puttick, G. M. 1977. Spatial and temporal variations in intertidal animal distribution at Langebaan Lagoon, South Africa. Royal Society of South Africa. Transactions 42:403- 440. Quammen, M. L. 1982. Influence of subtle substrate differences on feeding by shorebirds on intertidal mudflats. Marine Biology 71:339-343. Ranwell, D. S. 1964. Spartina salt marshes in southern England: II. rate and seasonal pattern of sediment accretion. Journal of Ecology 52:79-94. Sayce, K. 1988. Introduced cordgrass, Spartina alterniflora Loisel in saltmarshes and tidelands of Willapa Bay, Washington. Report to US Fish and Wildlife Service, Willapa National Wildlife Refuge.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 15 of 61 SFEI. 1998. EcoAtlas beta release, version 1.5b4. San Francisco Estuary Institute, Oakland, CA. Stata. 2003. Intercooled Stata 8.0 for Windows. Stata Corporation, College Station, TX. Stenzel, L. E., C. M. Hickey, J. E. Kjelmyr, and G. W. Page. 2002. Abundance and distribution of shorebirds in the San Francisco Bay area. Western Birds 33:69-98. Takekawa, J. Y., N. Warnock, G. M. Martinelli, A. K. Miles, and D. C. Tsao. 2002. Waterbird use of bayland wetlands in the San Francisco Bay Estuary: movements of Long-billed Dowitchers during winter. Waterbirds 25 (Special Publication 2):93-105. Warnock, N., G. W. Page, and L. E. Stenzel. 1995. Non-migratory movements of Dunlin on their California wintering grounds. Wilson Bulletin 107:131-139. White, B. C. 1995. The shorebird foraging response to the eradication of the introduced cordgrass, Spartina alterniflora. M.A. Thesis. San Francisco State University, San Francisco, CA. Yates, M. G., J. D. Goss-Custard, S. McGrorty, K. H. Lakhani, S. Durell, R. T. Clarke, W. E. Rispin, I. Moy, T. Yates, R. A. Plant, and J. Frost. 1993. Sediment characteristics, invertebrate densities and shorebird densities on the inner banks of the Wash. Journal of Applied Ecology 30:599-614.

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 16 of 61 FIGURES

FIGURE 1. Benchmark locations, station IDs, and allocation of benchmarks with continuous water level data to mudflat areas. Benchmark information was obtained from NOAA/NOS (http://www.co- ops.nos.noaa.gov/bench_mark.shtml?region=ca).

PRBO Spartina-Shorebird Final Report, Feb 2004 Page 17 of 61 co m C FIG PRBO co m C FIGURE i i , , t t rr rr respect respect y y U esp esp , and , and Percent Inundati on Percent Inundati on R Sp ond ond

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FIGURE 4. Fall (September) and spring (April) indices of mudflat habitat value used to model shorebird distributions. The invertebrate index assumes a 5:1 ratio between lower and upper mudflat value, based on invertebrate densities (Scenario B). The exposure index assumes that mudflat value is positively related to the percent of time that the mudflat is exposed during that month (Scenario C). The combined index is an average of the exposure index and the invertebrate index (Scenario D). Color shadings represent mudflat habitat quantiles, where 25% of the total area is contained in each shading category and darker colors have higher value.

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June Inundation 0 10 80 on i t a d 60 nun I t n e c 40 r e P 20 0

-1 0 1 2 3 Ele vat ion (m )

Alam eda Dumbarton Bridge Redwood City

FIGURE 5. Cumulative duration of inundation curves for June based on water level data from Alameda, Redwood City, and Dumbarton Bridge benchmarks. Elevations corresponding to 60% inundation were 0.864 m, 1.101 m, and 1.113 m, respectively. Elevations corresponding to 70% inundation were 0.674 m, 0.882 m, and 0.874 m, respectively. Elevations corresponding to 80% inundation were 0.413 m, 0.575 m, and 0.646 m, respectively.

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FIGURE 6. Predicted extent of Spartina alterniflora spread based on monthly inundation tolerances ranging from 60% to 80% (from Collins 2002). Sharp breaks in predictions are due to breaks in nearest benchmark locations.

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FIGURE 7. Predicted fall and spring shorebird biomass (kg) lost, based on a range of shorebird habitat value and Spartina spread scenarios for South San Francisco Bay, compared with baseline biomass values calculated from 1988-1993 PRBO surveys. Scenario A assumes that all mudflat areas are of equal value to shorebirds. Scenario B assumes a 5:1 ratio between lower and upper mudflat value, based on invertebrate densities. Scenario C assumes that mudflat value is positively related to the percent of time that the mudflat is exposed during that month. Scenario D is based on an average of scenarios B and C. Scenario 1 assumes that Spartina alterniflora and its hybrids can tolerate being inundated 60% of the time during month of June; scenario 2 assumes 70% inundation; and scenario 3 assumes 80% inundation. All predictions assume that mudflats are currently at carrying capacity during fall and spring migration.

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Fall Fall

Spring Spring

FIGURE 8. Current fall (orange) and spring (green) numbers of individual shorebird species from PRBO survey data (1988-1993) and predicted shorebird numbers under three different Spartina spread scenarios, assuming mudflats are currently at carrying capacity. Scenario 1 assumes that Spartina alterniflora and its hybrids can tolerate being inundated 60% of the time during month of June; scenario 2 assumes 70% inundation; and scenario 3 assumes 80% inundation. AMAV = American Avocet, REKN = Red Knot, SEPL = Semipalmated Plover, LBCU = Long-billed Curlew, Small Shorebirds = Least and Western Sandpipers and Dunlin, BBPL = Black-bellied Plover, DOWI = Long- and Short-billed Dowitchers, MAGO = Marbled Godwit, WILL = Willet.

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FIGURE 9. Predicted extent of Spartina alterniflora spread based on a 70% inundation tolerance and overlap with tidal mudflats, classified according to their potential fall season value for shorebirds. Shorebird habitat value was based on: (a) PRBO Pacific Flyway shorebird survey data (1988-1993); (b) length of mudflat inundation during September; and (c) presumed invertebrate densities (Scenario D as described in text, adjusted for actual shorebird survey numbers).

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FIGURE 10. Predicted extent of Spartina alterniflora spread based on a 70% inundation tolerance and overlap with tidal mudflats, classified according to their potential spring season value for shorebirds. Shorebird habitat value was based on: (a) PRBO Pacific Flyway shorebird survey data (1988-1993); (b) length of mudflat inundation during April; and (c) presumed invertebrate densities (Scenario D as described in text, adjusted for actual shorebird survey numbers).

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TABLES

TABLE 1. Tidal benchmark locations used to obtain mean tide level elevations, based on the National Tidal Datum Epoch (NTDE; 1983-2001). From NOAA’s NOS website (http://www.co- ops.nos.noaa.gov/bench_mark.shtml?region=ca).

Station ID Name Period Lat Lon 9414750 ALAMEDA, SAN FRANCISCO BAY January 1983 - December 2001 37ø 46.3' N 122ø 17.9' W 9414575 COYOTE CREEK, ALVISO SLOUGH April 1984 - March 1985 37ø 27.9' N 122ø 1.4' W 9414509 DUMBARTON BRIDGE, SF BAY April 1996 - March 1997 37ø 30.4' N 122ø 6.9' W 9414746 OAKLAND/ALAMEDA PARK ST. BRIDGE April 1980 - March 1981 37ø 46.3' N 122ø 14.1' W 9414525 PALO ALTO YACHT HARBOR, S. F. BAY June 1984 - December 1984 37ø 27.5' N 122ø 6.3' W 9414523 REDWOOD CITY, WHARF 5, S. F. BAY November 1997 - October 2002 37ø 30.4' N 122ø 12.6' W 9414458 SAN MATEO BRIDGE, WEST SIDE January 1981 - December 1987 37ø 34.8' N 122ø 15.2' W

TABLE 2. Coefficients for regression equations used to predict inundation from elevation. Equations were based on inundation curves obtained from 6-minute water level data from NOS benchmarks and took the form y = ax + bx2 + cx3 + d, where Y = inundation percent and X = elevation / water level above MLLW.

2 Benchmark Month a b c d R

Alameda April -27.9 -24.9 7.85 91.3 0.9974

Alameda Sept -21.6 -28.4 7.92 96.4 0.9997

Dumbarton Bridge April -19.7 -13.7 2.93 94.6 0.9990

Dumbarton Bridge Sept -20.4 -12.1 2.36 98.2 0.9984

Redwood City April -20.4 -16.8 4.01 93.9 0.9974

Redwood City Sept -15.7 -18.2 3.79 97.9 0.9994

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TABLE 3. Predicted percent of effective mudflat habitat lost based on a range of shorebird habitat value and Spartina spread scenarios. Scenario A assumes that all mudflat areas are of equal value to shorebirds. Scenario B assumes a 5:1 ratio between lower and upper mudflat value based on invertebrate densities. Scenario C assumes that mudflat value is inversely related to the percent of time that the mudflat is inundated during that month. Scenario D is based on an average of scenarios B and C. Scenarios 1, 2, and 3 assume that Spartina can tolerate being inundated 60%, 70%, and 80% of the time during June, respectively. All predictions assume that mudflats are currently at carrying capacity during fall and spring migration.

Shorebird Habitat Value Scenario C (Inundation D (Invertebrates & Spartina Spread Scenario A (All Areas Equal) B (Invertebrates) Time) Inundation) Fall 1 (60% Inundation Tolerance) 0.14 0.09 0.29 0.15 2 (70% Inundation Tolerance) 0.33 0.23 0.57 0.34 3 (80% Inundation Tolerance) 0.54 0.44 0.80 0.55 Spring 1 (60% Inundation Tolerance) 0.14 0.09 0.27 0.15 2 (70% Inundation Tolerance) 0.33 0.23 0.54 0.33 3 (80% Inundation Tolerance) 0.54 0.44 0.76 0.55

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TABLE 4. Predicted loss of shorebird numbers by species, based on a range of Spartina spread scenarios. Scenario B assumes a 5:1 inundation-based ratio between lower and upper mudflat value, based on invertebrate densities. Scenario 1 assumes that invasive Spartina can tolerate being inundated 60% of the time during month of June; scenario 2 assumes 70% inundation; and scenario 3 assumes 80% inundation. All predictions assume that mudflats are currently at carrying capacity during fall and spring migration.

FALL SPRING Current 1 (60%) 2 (70%) 3 (80%) Current 1 (60%) 2 (70%) 3 (80%) Hectares 6,062 -904 -1,988 -3,269 6,062 -904 -1,988 -3,269 Species American Avocet 5,023 -628 -1,561 -2,617 844 -113 -268 -445 Black-bellied Plover 8,138 -1,258 -2,781 -4,496 4,595 -642 -1,485 -2,456 Short/Long-billed Dowitcher 13,377 -2,099 -4,577 -7,376 33,008 -5,206 -11,277 -18,244 Long-billed Curlew 371 -61 -130 -209 218 -34 -75 -121 Marbled Godwit 14,251 -2,210 -4,884 -7,884 13,437 -2,088 -4,569 -7,406 Red Knot 1,678 -353 -691 -1,037 503 -97 -193 -299 Semipalmated Plover 1,501 -244 -521 -839 725 -125 -256 -411 Willet 15,612 -2,444 -5,370 -8,671 2,112 -366 -759 -1,206 Western/Least Sandpipers and Dunlin 160,374 -24,224 -54,299 -88,119 450,817 -66,817 -149,731 -245,213 TOTAL 220,325 -48,615 -70,055 -94,175 506,259 -104,793 -156,097 -212,813

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APPENDIX 1, Literature Review By Viola Toniolo ([email protected])

Importance And Status Of San Francisco Bay

San Francisco Bay is one of the largest and most important estuaries in the Western Hemisphere. The bay comprises 1500 km2 of aquatic habitat and carries runoff from a 163,000 km2 watershed, which equals approximately 40% of California’s surface area (Nichols et al. 1986, Cohen and Carlton 1998). It also includes 70% of the mudflats in California (see Ayres et al. 1999), which provide habitat to over 350,000 migrating shorebirds (Charadrii) at a time in the fall and over 900,000 in the spring (based on single-day counts, Stenzel et al. 2002). Its importance to shorebirds has earned the San Francisco Bay estuary status among the top five nationally and internationally important sites for shorebirds (Galbraith et al. 2002), and as a Western Hemisphere Shorebird Reserve Network site of hemispheric importance (Page et al. 1999, 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). Nonetheless the bay is also one of the most altered estuaries in the United States (Nichols et al. 1986, Stenzel et al. 2002). Following the 1850s gold rush and the resulting influx of hydraulic mining sediments, years of agricultural, urban, and industrial development throughout bay watersheds have led to the widespread loss and alteration of historic intertidal habitats throughout the bay (Nichols et al. 1986, Cohen and Carlton 1998). According to the Goals Project (1999), more than 80% of pre-settlement tidal marsh and 40% of mudflat areas have been lost to dredging, filling, diking and development. Furthermore, San Francisco Bay may be one of the most invaded aquatic ecosystems in the world (Cohen and Carlton 1998). Over 234 exotic species, including algae, plants, protozoans, invertebrates, and vertebrates were introduced via a number of anthropogenic activities between 1850 and 1990, with most introductions having taken place in the latter part of the 20th century. Many of these species now dominate much of the bay’s ecosystem both in terms of numbers and biomass, and the bay’s benthic community consists of a constantly changing mosaic of non-native invertebrate and plant species along with what remains of the native communities. Ballast water from ships has been identified as one of the most important factors contributing to these invasions (see Ruiz et al. 1997).

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Spartina Invasion

Smooth cordgrass, Spartina alterniflora (Loisel) was originally introduced in the mid- 1970s as part of a marsh restoration and erosion control project in the Coyote Hills Slough in the South Bay. By 1992 it had spread to many mudflats and channels throughout the bay (Callaway and Josselyn 1992, Daehler and Strong 1994). S. alterniflora readily hybridizes where it coexists with the native S. foliosa (Daehler and Strong 1997, Ayres et al. 1999). Both pure S. alterniflora and hybrids are now found primarily in the South Bay from Alameda Island to Fremont on the eastern side and from San Bruno to Hunter’s Point on the western side (Ayres et al. 1999). As compared with its native congener, S. alterniflora and associated hybrids exhibit higher tolerance to tidal submersion and salinity (Callaway and Josselyn 1992, Donnelly and Bertness 2001, Collins 2002), earlier growth initiation, higher vegetative and lateral growth rates, copious pollen (“pollen swamping”) and seed production, high germination rates, and greater seed viability (Callaway and Josselyn 1992, Daehler and Strong 1996, Anttila et al. 1998, Ayres et al. 1999). Its tendency to grow at lower elevations and establish new patches at relatively high rates makes this non-native species an “ideal invader” (Callaway and Josselyn 1992) that severely affects the relatively common native S. foliosa (Anttila et al. 1998). Hybrids, which can be difficult to tell apart from the parental species, have greater reproductive and ecological vigor than the parent plants and are thus thought to pose an additional and perhaps more serious threat to S. foliosa (Daehler and Strong 1997, Anttila et al. 1998, Ayres et al 1999). The native cordgrass is now absent from areas where S. alterniflora was purposefully introduced, whereas areas colonized by dispersal of seed contain a full range of levels of hybridization (Ayres et al. 1999). Although the current extent of non-native Spartina is mostly limited to tidal marsh plains and channels, further spread of S. alterniflora and associated hybrids poses a great threat to the continued existence of bordering mudflats. Due to the gentle gradient of mudflat surfaces, a small change in the inundation tolerance of non-native Spartina would translate into a fairly extensive horizontal expansion across the mudflat (Callaway and Josselyn 1992, Daehler and Strong 1996) and the formation of the typical monospecific, circular patches in formerly open habitat (Daehler and Strong 1994). These patches can then slow tidal flow and cause the precipitation and accretion of fine sediments that are suspended in the water column, thus raising

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the overall elevation of the mudflat over time (Ranwell 1964, Daehler and Strong 1996) and effectively acting as an ecosystem engineer (see definition in Jones et al. 1994, 1997), potentially resulting in the eventual conversion of tidal flats to non-native cordgrass meadows.

Spartina effects on invertebrates

Studies on the effects of non-native cordgrass on invertebrate fauna are inconclusive and difficult to compare because they range geographically and by species. Studies in France (Triplet et al. 2002), England (Evans 1986), and Tasmania (Hedge and Kriwoken 2000) looked at the effects of removal of S. anglica, a recent hybrid of S. alterniflora and the European native S. maritima, and suggested that cleared areas held higher densities of invertebrates than nearby vegetated areas, especially if the removal had taken place within three years (Evans 1986). Similarly, Capehart and Hackney (1989) found that the density of a burrowing clam, Polymesoda caroliniana, was lower in S. alterniflora stands due to the higher densities of roots and rhizomes. In contrast, both White (1995) and Rader (1984) reported that invertebrate densities were higher in S. alterniflora swards than in mudflats or areas where Spartina has been removed. This might be due to the greater structural complexity present in vegetative stands of Spartina (Daehler and Strong 1996, Josselyn et al. 1993). Whatever the relationship between Spartina and invertebrate populations, it is unlikely that shorebirds would be able to utilize dense or even patchy Spartina habitats to nearly the same degree as mudflats, if at all (White 1995), because shorebirds are unable to move through and forage in areas with high stem density.

Shorebirds

Pacific Flyway Project

Between April 1988 and April 1993 PRBO Conservation Science, with the help of hundreds of volunteers, conducted three fall and six spring shorebird censuses in the intertidal portion of San Francisco and San Pablo Bay and associated wetlands (Stenzel et al. 2002). This was part of a larger project whose primary goal was to obtain an overview of shorebird abundance and distribution in wetlands of the Pacific Coast of the contiguous United States (Page et al. 1999). The surveys were designed to minimize the double counting of flocks and keep track of all flock movements between plots, and involved hundreds of observers simultaneously conducting surveys at multiple locations during moderately high rising tides

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(Stenzel et al. 2002). This is the most comprehensive survey of shorebirds in the San Francisco Bay to date.

Shorebird use patterns in San Francisco Bay

Thirty-eight species of shorebirds comprising 18 species groups were detected on Pacific Flyway Project surveys. On a seasonal basis the bay held 340,000-360,000 individuals during fall and 589,000-932,000 individuals during spring. The most abundant species on each survey was Western Sandpiper, followed by Dunlin, Marbled Godwit, Least Sandpiper, and dowitchers (Stenzel et al. 2002). Areas with the highest overall density and biomass were along the east side of central San Francisco Bay, the east and south shores of South San Francisco Bay, and the Napa River flats in the north bay (Stenzel et al. 2002). Most areas held high densities of at least some species groups. High overall density seemed to be related to the presence of nearby active salt ponds, which provide roosting and feeding habitat during high tides and may cause mudflats to hold more birds than they would otherwise (Stenzel et al. 2002). Peak abundance of temperate breeders occurred in fall and late winter, and peak abundance for arctic breeders occurred in fall or spring (Page et al. 1999). In the South Bay (south of the Richmond Bridge), density and biomass were highest along the southern and eastern shores during fall (2.32-6.62 kg/ha) and eastern shore during spring (4.33-6.37 kg/ha). Species that concentrated in the South Bay were Black-bellied Plover, Willet, Marbled Godwit, small sandpipers and dowitchers (Stenzel et al. 2002).

Shorebird use of mudflats

Although the Pacific Flyway Project accomplished its goal of estimating the overall abundance and distribution of shorebirds throughout San Francisco Bay, the scope and geographic scale of the surveys did not allow for the fine spatial resolution necessary to capture the variation of shorebird distributions across individual mudflats, though much can be gleaned from the literature. Many studies have demonstrated that shorebird utilization of mudflat habitats is spatially and temporally variable on both the inter- and intra-specific level (Burger et al. 1977, Goss- Custard 1979, Quammen 1982, Colwell and Landrum 1993). This variation is closely tied to cycles of tidal inundation and the uneven distribution of sediments, prey densities, and prey

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availability across the intertidal zone (Burger et al. 1977, Goss-Custard et al. 1977, Puttick 1977, Page et al. 1979, Evans 1986, Colwell and Landrum 1993, Yates et al. 1993, White 1995, Arcas 2003). Burger et al. (1977), for example, compared shorebird use of three intertidal habitats in coastal New Jersey and found that dowitchers, knots, Black-bellied Plovers, and oystercatchers preferred the algal zones of the mudflat, while Semipalmated and Western Sandpipers utilized more sandy areas. The authors noted that spatial segregation was less marked when the mudflat was more exposed, and suggest that when foraging habitat is limited, species exhibit spatial and temporal segregation in order to reduce competition. They also observed temporal patterns and found that the number of species present on the mudflat increased faster than the mudflat area during first 1 ½ hrs after high tide, then remained constant, with the maximum number of birds occurring 1 hr after low tide. Colwell and Landrum (1993) examined shorebird distribution and abundance in the Mad River estuary in northern California and found that Least and Western Sandpipers foraged closer to the tide edge, whereas Semipalmated Plovers foraged at an average of 10 m from the tide edge. In San Francisco Bay Semipalmated Plover, Least Sandpiper, and Black-bellied Plover tend to forage higher along the tidal gradient, whereas American Avocet, dowitchers, Marbled Godwit, and other species forage closer to the tide line (G. Page, pers. obs.). Spatial and seasonal patterns in prey density are also strongly correlated with bird density, provided of course that the habitat is accessible to birds (Puttick 1977, Evans 1986, Yates et al. 1993). Colwell and Landrum (1993) found that the spatial distribution of invertebrates was substrate-dependent, with a significant relationship between the density of an amphipod, Corophium spp., and bird abundance, especially for Least and Western Sandpipers. In addition to invertebrate density and distribution, the availability of invertebrates plays an equal if not more important role in predicting shorebird density (White 1995). Invertebrates are more abundant and more accessible in wet substrates and tend to burrow deeper as the tide recedes and the mud dries out (Goss-Custard 1984, White 1995; reviewed in Durell 2000). Drier mud is also more difficult to penetrate by bird bills (Quammen 1982). Prey also become less available in cold weather and are harder to obtain during winter (Goss-Custard 1979).

Effects Of Habitat Loss On Shorebirds

The further spread of S. alterniflora and associated hybrids has the potential to greatly reduce the size of mudflats throughout San Francisco Bay. While there is little doubt that such

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habitat loss would have a negative impact on shorebird fitness, possibly reducing fat reserves needed for migration (Stillman 2003), it is difficult to estimate the magnitude of decline in shorebird populations in the Bay. The relationship between habitat availability and bird populations is generally thought to be non-linear, such that a 50% reduction in habitat would not necessarily translate into a 50% loss in the numbers of birds. This is due to patchiness in habitat quality, the propensity of certain species or individuals to move to other areas, and the degree of responses and general trends among other aspects of a given ecosystem (e.g., invertebrate prey, rates of predation) that are likely to influence shorebirds. Habitat loss, for example, can lead to emigration to alternative wintering sites (Stillman 2003, Goss-Custard 1979), which is very difficult to measure, and/or an increase in density in the present habitat, which in turn can result in birds moving to less preferred areas (e.g., areas with lower foraging quality), greater impacts on the prey populations, an increase in interactions among birds, and a reduction in fitness (Goss-Custard 1979). Even if one could figure out the degree of emigration and changes in density, it is still very difficult to predict what effects these will have on fitness and survival at a larger scale, for birds may respond to habitat loss with compensatory density-dependent reproduction on their breeding grounds that offset greater mortality on their wintering grounds (Stillman 2003, Goss-Custard 2003). At the same time, even a small increase in mortality can significantly reduce the population over the long term, especially in species with low annual mortality rates. A 2% increase in mortality in the Eurasian Oystercatcher, Haematopus ostralegus, can reduce the population by as much as 30-60% (see Goss-Custard 2003). The importance of adult survival was also found for the Pacific Coast population of the Western Snowy Plover, Charadrius alexandrinus nivosus. Based on a population viability analysis, the population was shown to be sensitive to small changes in adult survival (Nur et al. 2001). In general, adult survival has been shown to be the most important limiting factor across shorebird taxa (Sandercock 2003). Survival and fitness can also vary depending on whether the habitat is functioning at carrying capacity, which is defined as either the maximum bird-days a given habitat can support or the maximum number of birds that can survive the non-breeding season (Goss-Custard et al. 2002). Because of the disproportionate responses of individuals (e.g., juveniles v. adults) to depleted resources, many birds may emigrate or starve before carrying capacity has been reached (Durell 2000, Goss-Custard et al 2002, Goss-Custard 2003, Stillman 2003). Once the system is

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functioning at or beyond carrying capacity, density-dependent mortality can then cause a population to decrease at an increasing rate. Changes in invertebrate productivity can either offset this loss if positive or exacerbate it if negative. The latter is especially true during winter when food is less abundant and less available (West et al. 2002, Goss-Custard 1979, 2003). Individual variation can play an even more important role in determining the fate of populations undergoing losses in wintering and migratory habitat. This issue is reviewed thoroughly in Durell (2000). Many species exhibit significant differences in morphology, social status, and skill (e.g., experience) among individuals, sexes, and across different ages, such that any changes that affect one sector of the population more than another are likely to have greater effects on population size than if all individuals were affected equally (Durell 2000, Goss- Custard 2003). Examples of individual variation in shorebirds include differential migration (i.e., males and adults overwinter closer to the breeding grounds, females and juveniles are found in high proportions at the same sites) and dimorphism (e.g., differences in bill size and morphology between ages and sexes). Young animals are also less efficient at foraging than older, more experienced animals. What this means is that different portions of the population will have differences in energetic and habitat requirements, foraging strategies (e.g., prey size), and behavior, and individuals that specialize in less profitable strategies will have an increased vulnerability to factors that decrease fitness such as parasite loading, bill damage, and predation; if mortality varies between males and females then the sex ratio of a population can change and the numbers of breeding pairs would be less than if males and females were affected equally; if mortality is higher among juveniles then population size will decrease at a faster rate over the long term than if all ages were affected equally (Durell 2000, Goss-Custard 1979, 2003). Unfortunately, individual variation can be difficult to estimate because differences in plumage between males and females and juveniles and adults are not easily discernible in wintering populations (Durell 2000). Stillman (2003) suggests that in order to increase the level of accuracy in estimating the effects of habitat loss on shorebird populations, we need to develop behavior-based models that take into account mortality rate, feeding rate, changes in distribution, and the tendency of individual birds to maximize their own fitness in response to change. West et al. (2002), for example, developed a behavior-based model in order to assess the impacts of disturbance on foraging birds and found that many small disturbances cause greater damage than fewer, larger

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disturbances and that disturbance can be more damaging (i.e., lead to increased mortality) than permanent habitat loss.

Effect Of Spartina Spread On Shorebirds

Several studies have looked at the effects of habitat loss as a result of the spread of Spartina. In Britain, where S. alterniflora hybridized with the native S. maritima to form S. anglica, numbers of wintering Dunlins (Calidris alpina) have decreased by almost half since the winter of 1973-1974, and these declines were greatest in estuaries where S. anglica has spread over most of the available tidal flat (Goss-Custard and Moser 1988). Numbers did not increase in estuaries where Spartina experienced a natural dieback, suggesting that Dunlins have not been able to emigrate from areas where they were experiencing habitat loss to these newly available habitats and perhaps to other areas in their wintering range. The authors suggest that this species might have been more affected by invasive Spartina due to its small size, higher need for constant foraging, and more extensive use of higher elevations during the tidal cycle. Evans (1986) investigated the effects of herbicide removal and found that shorebirds feed more in areas recently cleared of Spartina than areas cleared 3-4 years prior, and that bird densities in the recently cleared plots were higher than in areas of nearby mud that were never colonized by Spartina. This pattern is also true for amphipod (Corophium spp.) density and overall invertebrate activity due to the presence of more standing water (less dried out) in the recently cleared patches. Triplet et al. (2002) also found that cordgrass removal in northern France had a positive effect on some species, especially the Ringed Plover, Charadrius hiaticula, and Dunlin. White (1995) compared bird use of plots with different Spartina removal treatments and found that bird density decreased from open mudflats to herbicide-treated mudflats, plastic- treated mudflats, and plots vegetated by cordgrass, in that order. The main difference between all the plots was the degree of vegetative cover, and birds generally avoided areas with even minimal amounts of vegetation. When birds did enter patches with some cordgrass they usually did so by landing in nearby open mud and then wandering in on foot. In Willapa Bay, Washington, where S. alterniflora increased from 800 ha in 1994 to over 2500 ha in 2002 (Buchanan 2003), aerial surveys conducted in 2000-2001 suggest a reduction in shorebird numbers by as much as 67% and foraging time by as much as 50% in the southern

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portions of the bay as compared with data from the 1991-1995 surveys (Jaques 2002). Unfortunately, bird data are missing prior to 1991, making it difficult to estimate how much of this reduction is attributable to the invasion of Spartina (Buchanan 2003). Many of these studies indicate that birds have difficulty landing in and utilizing areas of dense growth (Evans 1986, Josselyn et al. 1993, White 1995), and that Spartina effectively reduces the foraging area available to shorebirds and diminishes their feeding time (Goss- Custard and Moser 1988).

Future

Unchecked Spartina growth has the potential of converting open mudflats into dense stands of S. alterniflora and alterniflora x foliosa hybrids, not just in south San Francisco Bay but in other important shorebird migratory routes and wintering areas throughout the Pacific Flyway. Daehler and Strong (1996) used physical characteristics to identify 31 estuaries along the pacific coast as vulnerable to future Spartina invasions and found that all of them are specifically vulnerable to S. alterniflora. Cordgrass poses additional threats to many habitats that are already under extreme pressure from development and increased human use of coastal areas (Zedler 1996). Sea level rise associated with climate change can further reduce the seaward extent of mudflats and cause the shoreward migration of S. alterniflora, which, due to its higher tolerance for inundation, can outcompete and eventually dominate the tidal marsh vegetation (Donnelly and Bertness 2001). Under normal conditions sea level rise is gradual enough that wetlands can adapt to these changes and shift inland, but the presence of coastal development will hinder this process (Orr et al. 2003). Galbraith et al. (2002) examined current and projected trends in sea level rise and, using conservative estimates, predict a conversion of 39% of the intertidal habitat in San Francisco Bay to subtidal habitat. In South San Francisco Bay, that conversion is expected to be as high as 70% by 2100. This is because the South Bay is subsiding faster and is experiencing greater aquifer depletion and compaction than other areas in the greater bay. Other geomorphologic (e.g., tectonic activity) and anthropogenic factors (e.g., construction of seawalls) can play unforeseen and unpredictable role in the future of wetlands and intertidal areas. Habitat loss and future sea level rise can have deleterious effects on the size of shorebird populations, many of which are already in severe decline. As many as 19 of 35 shorebird species

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that breed in Arctic and temperate regions throughout North America show negative population trends (Morrison et al. 2001). In general, large population sizes, long migrations, high concentrations of individuals in restricted areas during migration, and high demand for development along coastal areas make shorebirds particularly vulnerable to environmental degradation (Morrison et al. 2001). While it is unclear whether these populations are limited most by changes in their breeding, migration, or wintering habitats (Page and Gill 1994, Morrison et al. 2001), temperate breeders seem to be among the most vulnerable shorebird species (Page and Gill 1994). Restoration that involves the use of chemicals seems to be effective only as a short-term measure (Evans 1986, White 1995), while other restoration methods appear to be only marginally effective in restoring the same numbers of birds found in mudflats that have never been colonized by cordgrass (White 1995). Furthermore, sea level rise, increased development, and other anthropogenic factors need to be taken into consideration when managing coastal areas for shorebirds. Finally, given the uncertainty about the future spread of invasive Spartina and hybrids, as well as shorebird responses, it is only with the use of regular, systematic survey data (Buchanan 2003) over large areas (Goss-Custard 2003) that we can fully assess the impact of habitat loss to shorebirds by Spartina and devise restoration methods that will reclaim habitat and prevent further losses.

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Literature Cited

Anttila, C. K., C. C. Daehler, N. E. Rank, and D. R. Strong. 1998. Greater male fitness of a rare invader (Spartina alterniflora, Poaceae) threatens a common native (Spartina foliosa) with hybridization. American Journal of Botany 85:1597–1601. Arcas, J., F. Benitez and M. Paramos. 2003. Diet and habitat use of Sanderling, Calidris alba, wintering in a southern European estuary. Alauda 71:69-77. Ayres, D. R., D. Garcia-Rossi, H. G. Davis and D. R. Strong. 1999. Extent and degree of hybridization between exotic (Spartina alterniflora) and native (S. foliosa) cordgrass (Poaceae) in California, USA determined by random amplified polymorphic DNA (RAPDs). Molecular Ecology 8:1179-1186. Buchanan, J. B. 2003. Spartina invasion of Pacific coast estuaries in the United States: implications for shorebird conservation. Wader Study Group Bulletin 100:47-49. Burger, J., M. A. Howe, D. C. Hahn and J. Chase. 1977. Effects of tide cycles on habitat selection and habitat partitioning by migrating shorebirds. Auk 94:743-758. Callaway, J. C. and M. N. Josselyn. 1992. The introduction and spread of smooth cordgrass (Spartina alterniflora) in South San Francisco Bay. Estuaries 15:218-226. Capehart, A. A. And C. T. Hackney. 1989. The potential role of roots and rhizomes in structuring salt-marsh benthic communities. Estuaries 12:119-122. Cohen, A. N. and J. T. Carlton. 1998. Accelerating invasion rate in a highly invaded estuary. Science 279:555-558. Collins, J. N. 2002. Invasion of San Francisco Bay by smooth cordgrass, Spartina alterniflora: a forecast of geomorphic effects on the intertidal zone. Unpublished report of San Francisco Estuary Institute, Oakland, CA. Colwell, M. A. and S. L. Landrum. 1993. Nonrandom shorebird distribution and fine-scale variation in prey abundance. Condor 95:94-103. Daehler, C. C. and D. R. Strong. 1994. Variable reproductive output among clones of Spartina alterniflora (Poaceae) invading San Francisco Bay, California: the influence of herbivory, pollination, and establishment site. American Journal of Botany 81:307-313. Daehler, C. C. and D. R. Strong. 1996. Status, prediction and prevention of introduced cordgrass Spartina spp. invasions in Pacific estuaries, USA. Biological Conservation 78:51-58.

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Daehler, C. C. and D. R. Strong. 1997. Hybridization between introduced Smooth Cordgrass (Spartina alterniflora) and native California cordgrass (S. foliosa) in San Francisco Bay, California, USA. American Journal of Botany 84:607-611. Donnelly, J. P. and M. D. Bertness. 2001. Rapid shoreward encroachment of salt marsh cordgrass in response to accelerated sea-level rise. Proceedings of the National Academy of Sciences of the U.S.A. 98:14218-14223. Durell, S. E., A. le Dit, J. D. Goss-Custard and R. T. Clarke. 1997. Differential response of migratory subpopulations to winter habitat loss. Journal of Applied Ecology 34:1155- 1164. Evans, P. R. 1986. Use of the herbicide 'Dalapon' for control of Spartina encroaching on intertidal mudflats: beneficial effects on shorebirds. Colonial Waterbirds 9:171-175. Galbraith, H., R. Jones, R. Park, J. Clough, S. Herrod-Julius, B. Harrington and G. Page. 2002. Global climate change and sea level rise: potential losses of intertidal habitat for shorebirds. Waterbirds 25:173-183. Goals Project. 1999. Baylands ecosystem habitat goals. A report of habitat recommendations prepared by the San Francisco Bay Area Wetlands Ecosystems Goals Project. Joint publication of the U. S. Environmental Protection Agency, San Francisco, California, and San Francisco Bay Regional Water Quality Control Board, Oakland, CA. Goss-Custard, J. D. 1979. Effect of habitat loss on the numbers of overwintering shorebirds. Studies in Avian Biology 2: 167-177. Goss-Custard, J. D. 1984. Intake rates and food supply in migrating and wintering shorebirds. Pp. 233-270 in J. Burger & B. L. Olla (editors). Shorebirds: Migration and Foraging Behaviour. Plenum Press, London and New York. Goss-Custard, J. D. 2003. Fitness, demographic rates and managing the coast for wader populations. Wader Study Group Bulletin 100:183-191. Goss-Custard, J. D., R. E. Jones, and P. E. Newbery. 1977. The ecology of the Wash. I. Distribution and diet of wading birds (Charadrii). Journal of Applied Ecology 14:681- 700. Goss-Custard, J. D. and M. E. Moser. 1988. Rates of change in the numbers of Dunlin, Calidris alpina, wintering in British estuaries in relation to the spread of Spartina anglica. Journal of Applied Ecology 25:95-109.

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Goss-Custard, J. D., R. A. Stillman, A. D. West, R. W. G. Caldow, and S. Mcgrorty. 2002. Carrying capacity in overwintering migratory birds. Biological Conservation 105:27-41. Hedge, P. and L. K. Kriwoken. 2000. Evidence for effects of Spartina anglica invasion on benthic macrofauna in Little Swanport estuary, Tasmania. Austral Ecology 25:150-159. Jaques, D. 2002. Shorebird status and effects of Spartina alterniflora at Willapa NWR. Jones, C. G., J. H. Lawton, and M. Shachak. 1994. Organisms as ecosystem engineers. Oikos 69:373-386.. Jones, C. G., J. H. Lawton, and M. Shachak. 1997. Positive and negative effects of organisms as physical ecosystem engineers. Ecology 78:1946-1957. Josselyn, M., B. Larsson, and A. Fiorillo. 1993. An ecological comparison of an introduced marsh plant, Spartina alterniflora, with its native congener, Spartina foliosa, in San Francisco Bay. San Francisco Bay Estuary Project Report, Romberg Tiburon Center, Tiburon, CA. Morrison, R. I. G., Y. Aubry, R. W. Butler, G. W. Beyersbergen, G. M. Donaldson, C. L. Gratto- Trevor, P. W. Hicklin, V. H. Johnston, and R. K. Ross. 2001. Declines in North American shorebird populations. Wader Study Group Bull 94:34-38. Nichols, F. H., J. E. Cloern, S. N. Luoma, and D. H. Peterson. 1986. The modification of an estuary. Science 231:567-573. Nur, N., G. W. Page, and L. E. Stenzel. 2001. Appendix D: Population viability analysis for Pacific coast Snowy Plovers in Western Snowy Plover (Charadrius alexandrinus nivosus) Pacific coast population draft recovery plan. U.S. Fish and Wildlife Service, Portland, OR. Orr, M., S. Crooks, and P.B. Williams. 2003. Will restored tidal marshes be sustainable? In L. R. Brown (editor). Issues in San Francisco Estuary Tidal Wetlands Restoration. San Francisco Estuary and Watershed Science. Vol. 1, Issue 1 (October 2003), Article 5. http://repositories.cdlib.org/jmie/sfews/vol1/iss1/art5. Page, G. W., and R. E. Gill, Jr. 1994. Shorebirds in western North America: late 1800s to late 1900s. Studies in Avian Biology 15:147-160. Page, G. W., L. E. Stenzel, and J. E. Kjelmyr. 1999. Overview of shorebird abundance and distribution in wetlands of the Pacific coast of the contiguous United States. Condor 101: 461-471.

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Page, G. W., L. E. Stenzel, and C. M. Wolfe. 1979. Aspects of the occurrence of shorebirds on a central California estuary. Studies in Avian Biology 2:15-32. Puttick, G. M. 1977. Spatial and temporal variations in intertidal animal distribution at Langebaan Lagoon, South Africa. Royal Society of South Africa. Transactions 42:403- 440. Quammen, M. L. 1982. Influence of subtle substrate differences on feeding by shorebirds on intertidal mudflats. Marine Biology 71:339-343. Rader, D. N. 1984. Salt-marsh benthic invertebrates: small-scale patterns of distribution and abundance. Estuaries 7:413-420. Ranwell, D. S. 1964. Spartina salt marshes in southern England: II. rate and seasonal pattern of sediment accretion. Journal of Ecology 52:79-94. Ruiz, G. M., J. T. Carlton, E. D. Grosholz, and A. H. Hines. 1997. Global invasions of marine and estuarine habitats by non-indigenous species: mechanisms, extent, and consequences. American Zoology 37:621-632. Sandercock, B. K. 2003. Estimation of survival rates for wader populations: a review of mark- recapture methods. Wader Study Group Bulletin 100:163-174. Stenzel, L. E., C. M. Hickey, J. E. Kjelmyr, and G. W. Page. 2002. Abundance and distribution of shorebirds in the San Francisco Bay area. Western Birds 33:69-98. Stillman, R. A. 2003. Predicting wader mortality and body condition from optimal foraging behaviour. Wader Study Group Bulletin 100:192-196. Triplet, P., C. Fagot, S. Van Imbeck, A. Sournia and F. Sueur. 2002. Role de la vegetation dans l'utilisation de l'estran par les limicoles. [The importance of vegetation in the use of mud flats by waders.]. Alauda 70:445-449. West, A. D., J. D. Goss-Custard, R. A. Stillman, R. W. G. Caldow, A. le Dit, S. E. Durell, and S. McGrorty. 2002. Predicting the impacts of disturbance on shorebird mortality using a behaviour-based model. Biological Conservation 106:319-328. White, B. C. 1995. The shorebird foraging response to the eradication of the introduced cordgrass, Spartina alterniflora. M.A. Thesis. San Francisco State University, San Francisco, CA. Yates, M. G., J. D. Goss-Custard, S. McGrorty, K. H. Lakhani, S. Durell, R. T. Clarke, W. E. Rispin, I. Moy, T. Yates, R. A. Plant, and J. Frost. 1993. Sediment characteristics,

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invertebrate densities and shorebird densities on the inner banks of the Wash. Journal of Applied Ecology 30:599-614. Zedler, J. B. 1996. Ecological issues in wetland mitigation: an introduction to the forum. Ecological Applications 6:33-37.

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APPENDIX 2, Shorebird Use Maps

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