Predicting tidal marsh bird and plant community response to climate change: A Pacific coast perspective using field experiments and spatial models PI: V. Thomas Parker, San Francisco State University Co-PI: Nadav Nur, PRBO Conservation Science John C. Callaway, University of San Francisco Mark Herzog, PRBO Conservation Science Diana Stralberg, PRBO Conservation Science ABSTRACT We propose to use new and existing data to examine the influence of salinity and inundation on the distribution, diversity, and establishment of tidal marsh plant and avian species. We will generate spatially explicit models that predict patterns of response of plant and avian distribution and abundance using a range of future climate change scenarios in a Mediterranean climate system. We will address the following questions: (1) How do salinity and tidal inundation influence the distribution, diversity, and establishment of tidal marsh plant species? (2) How do biotic and abiotic factors influence the distribution and abundance of tidal marsh bird species? (3) How will these plant and avian species respond to predicted climate change? Which species and what areas of their distributions are most likely to be affected by climate change? Research will be conducted within the tidal wetlands of the San Francisco Bay-Delta and adjacent uplands. Survey data of plant and bird occurrences will be collected for modeling purposes from sites throughout the Bay-Delta, while more intensive data collection will be conducted at six locations across the Bay-Delta to quantify factors affecting these distributions. At intensive study sites and in the greenhouse, we will complete a series of experiments to evaluate plant establishment from the seedbank across a range of salinity and inundation conditions. We also will measure seedling survival in the field across these same treatments and seed traps will be deployed to assess dispersal potential, abundance, and distance, especially in the upriver direction where recruitment is most likely to occur with changing climate. Using field-based abundance and GIS-based environmental data, we will develop distribution models for dominant, rare, and invasive plant species, as well as spatial models for plant species diversity. Model linkages will be based on path analysis among physical factors (salinity, inundation, channel density), plant characterisitcs, and avian population metrics. Based on relationships elucidated among physical factors, habitat distributions and bird occurrences, we will model bird species distribution and abundance and validate models using data not included in model development. Once models have been validated for existing conditions, Bay-Delta-specific predictions of sea-level rise and salinity will be used to predict changes in species distribution and abundance, and community composition. Models will be used to predict shifts in tidal marsh species distribution patterns for the Bay-Delta and identify species and geographic areas of conservation concern, as well as potential issues for rare or invasive species. Experimental data will identify underlying mechanisms for shifts in plant distributions and community composition. Predictive models and empirical results will be synthesized and testable predictions will be developed to further refine these models. -1- INTRODUCTION Mediterranean-climate tidal wetlands are particularly susceptible to the effects of climate change. As with other tidal wetlands, they share the threat of submersion if accretion rates are not in equilibrium with sea-level rise (SLR) (Morris et al. 2002, Turner et al. 2004) and differential impacts of CO2 fertilization on C3 and C4 plants (Rasse et al. 2005). However, Mediterranean-climate tidal systems are additionally threatened by salt accumulation during the lengthy dry summers that will accelerate with warmer temperatures. Changes in precipitation patterns and water management will exacerbate this impact, especially given the increased societal demands for water in a semi-arid climate. The composition, structure and dynamics of tidal wetland plant and bird communities will be significantly changed by these influences, but current predictions are merely speculative. Current understanding of how these tidal systems will respond and the resulting management or policy actions relies on a relatively limited history of basic research. In this study, we propose a focused research plan comprised of complementary observational studies, experimental and statistical analysis, and spatial modeling that will provide critical insight needed for management. Effective ecosystem management and species conservation require a thorough understanding of direct and indirect responses to environmental change (Burkett et al. 2005). Climate change combined with other anthropogenic influences is causing rapid, often non-linear, shifts in species’ distributions and life history characteristics (Parmesan 1996; Inouye et al. 2000; Ostander et al. 2000; Scheffer et al. 2001; Scheffer and Carpenter 2003; Folke et al. 2004; Hughes et al. 2005), and modifications at lower trophic levels can rapidly affect entire ecosystems (Porter et al. 2000; Dunne et al. 2002a, 2002b; Root et al. 2002; Lawrence and Soame 2004). One approach to assessing ecosystem-wide changes over large areas is the use of species distribution models (SDM), which use spatially-explicit empirical data to derive linear and non-linear relationships between species’ occurrence and environmental conditions. Many studies have modeled changes in species distribution due to climate change (Iverson and Prasad 1998; Bakkenes et al. 2002; Pearson et al. 2002; Thuiller 2004; Rehfeldt et al. 2006), but most have been based on global circulation model (GCM) predictions of temperature and precipitation at broad continental scales. Very few have explicitly modeled distribution shifts within tidal wetland ecosystems (but see Rehfisch et al. 2004), which are narrowly distributed and highly sensitive to fine-scale changes in elevation and salinity. Thus, we propose to apply the most recent developments in species distribution modeling to tidal marsh plants and vertebrates using fine-scale, California-specific spatial inputs that incorporate future tidal inundation and salinity patterns across the San Francisco Bay-Delta. We will investigate and model the distribution, diversity, and productivity of selected plant species, as well as the distribution and abundance of key tidal marsh endemic birds in relation to physical and biotic factors that may be altered as a result of current and future climate change. To improve our understanding of community-level species interactions and dispersal abilities, we propose to complement our modeling work with experimental field and greenhouse studies of plant recruitment and a field-based study of up-river plant dispersal. This will provide further insight into the mechanisms for shifts in plant distributions, and the consequences for bird species that depend on the plant community. Size and importance of San Francisco Bay-Delta The San Francisco Bay-Delta (hereafter referred to as the Bay-Delta) is the third largest estuary in the United States, covering approximately 4096 km2 of the central California coastal region and includes a broad mix of salt, brackish, and freshwater marsh ecosystems (Atwater et al. 1976, 1979; Josselyn 1983). The Bay-Delta is characterized by a Mediterranean climate, with precipitation limited to the winter and early spring seasons, and prolonged summer droughts. The wetland landscape is a complex mosaic of remaining historic wetlands, recently developed wetlands, restored wetlands, and potentially restorable diked bayland sites (farmland, former salt ponds, and seasonal and perennial wetlands), all situated within one of the country’s largest urban areas. Prior to 1850, tidal marshes in the Bay-Delta occupied 2200 km2, of which a substantial majority– 1400 km2 –consisted of freshwater tidal marshes in the Delta region (Nichols et al. 1986; SFEP -1- Parker et al. 1991). These extensive tidal marshes have now been reduced by more than 80% (95% in the Delta). Despite impacts from surrounding development, these remaining ecosystems are of critical regional importance for biodiversity, harboring a number of rare plant and animal species, including almost 50 special status species (Goals Project 1999; Olofson 2000). In addition to the ecological value of the BayDelta, the Delta’s freshwater storage and transport system is vital to California’s economy, providing water to meet agricultural, municipal, industrial, and environmental demands. The Bay-Delta is one of the most invaded aquatic ecosystems in the world (Cohen and Carlton 1998). Over 234 exotic species, including algae, plants, 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. Within tidal marshes, non-native cordgrass (Spartina alterniflora and recombinants with the native Spartina foliosa) (Callaway and Josselyn 1992; Ayres et al. 2004), as well as pepperweed (Lepidium latifolium) (Young et al. 1995), have been particularly effective at changing plant community composition and structure. Spartina alterniflora has invaded only the more saline portions of the San Francisco Bay, where native S. foliosa is also found, suggesting that an increase in salinity could increase invasibility in other areas of the Bay-Delta. Climate change impacts on San Francisco Bay-Delta Many studies have shown that the effects of a warmer global climate in this system would include reduced snowpack storage in the mountains, higher flood peaks during the winter rainy season, and reduced warm-season river flows after April (Gleick 1987a, 1987b; Roos 1989; Lettenmaier and Gan 1990; Gleick and Chalecki 1999; Knowles and Cayan 2002, 2004; Dettinger et al. 2004; Knowles et al. 2006). Even with some contention about which model might be the best and which direction certain parameters may shift, most models are in coarse agreement for California (Dettinger 2005). Dettinger (2005) compared multiple models and contingencies and determined that the most likely result of climate shift is a total precipitation regime similar to present, combined with warmer springs, reduced snowpack, and higher winter floods and lower summer flows. These hydrologic changes would propagate downstream to the estuary, resulting in an altered salinity regime (i.e., increased in spring/summer, decreased in winter) (Knowles and Cayan 2002). During the late spring and summer, the lower stream flows and increased salinities would affect many species that depend on the estuary and rivers. While several studies have examined current ecological conditions along the salinity gradient (Atwater et al. 1979, Pearcy and Ustin 1984), few have investigated how ecological systems in the estuary would respond to these changing conditions (Josselyn and Callaway 1988, Williams 1989). Another critical influence on estuarine conditions is SLR, which by conservative calculations is projected to occur at a global rate of up to 59 cm over the next 100 years (IPCC 2007). Predictions for the California coast range from 10-90 cm by 2100, an acceleration of the recent rate of approximately 20 cm during the last century (Cayan et al. 2005). Some recent predictions posit that future rates could be much greater due to more rapid melting of terrestrial ice sheets, primarily in Greenland and the Antarctic (Overpeck et al. 2006; Rignot and Kanagaratnam 2006). Winter storm surges may also increase sea levels by up to an additional 0.30 m (Flick 1998), 0.20 m within the San Francisco Bay (Cayan et al. 2005). In response to increased rates of SLR, tidal marshes must either accumulate more sediment to keep pace with SLR, migrate inland to adjacent terrestrial areas, or face increased inundation (Donnelly and Bertness 2001, Morris et al. 2002). Most tidal marshes accumulate 2-8 mm of sediment per year (Stevenson et al. 1986; Reed 1995; Callaway et al. 1996), and this compensates for SLR and other processes. However, substantial data from Louisiana, Chesapeake Bay and modeling studies have shown that as increases in relative sea level get close to 10 to 12 mm/yr, most marshes cannot keep pace and vegetation eventually may be inundated and converted to open water/mudflats (Baumann et al. 1984; Kearney and Stevenson 1991; Boesch et al. 1994; Morris et al. 2002, Rasse et al. 2005). Historic data from other systems has shown that slower increases in relative sea level (or loss in elevation) can lead to shifts in vegetation communities over time (Warren and Niering 1993). Although it may be possible for marsh accretion in the San Francisco Bay to keep up with SLR (Orr et al. 2003), bathymetric mapping 2 Parker et al. studies have shown a decline in bay sediments over time (Foxgrover et al. 2004), and future large-scale tidal marsh restoration projects will further deplete existing bay sediments. Furthermore, in the heavily impacted Bay-Delta system, filled, diked, and developed baylands tidal systems are severely restricted in terms of adjacent terrestrial habitats for upslope migration in response to SLR, creating a high level of uncertainty about tidal marsh responses to SLR. Most of the delta region is leveed and under agriculture, and SLR further increases the pressure on these levees, adding to the probability of their failure (Ingebritsen et al. 2000; Mount and Twiss 2005). The increased possibility of levee failure that would result from higher wet-season flows, and SLR could have additional impacts on the region’s ecosystems, particularly by drawing more saline water farther into the estuary. Tidal marsh vegetation responses to salinity and SLR Within the Bay-Delta, Atwater et al. (1979) first reported that freshwater wetlands of the Delta are characterized by greater plant species diversity than the salt marshes of the lower estuary. There is a dramatic, non-linear increase in plant species diversity and productivity in the fresh region of the BayDelta (Figure 1). Sites that are most saline have relatively low species diversity (Hopkins and Parker 1984, Sanderson et al. 2000) but contain threatened and federally listed species, such as soft bird’s beak (Cordylanthus mollis ssp. mollis). Brackish sites are not markedly more diverse; however, wetlands located further up the estuary are substantially more diverse and have greater numbers of locally uncommon and rare species than lower estuary sites (Vasey, Parker, Callaway, and Schile, unpublished data). The greater diversity at freshwater sites underscores the potential ecological importance of freshwater tidal wetlands and their potential vulnerability to salt water intrusion. Within California, a high proportion of imperiled and endemic species can be found within coastal ecosystems, including tidal marshes (Seabloom et al. 2006). Given the large number of locally uncommon and rare species in the brackish and freshwater tidal wetland ecosystem, as suggested by Lyons et al. (2005), the loss of these wetlands could have severe consequences for ecosystem functions in this region. On a regional scale, vegetation community structure of estuarine tidal wetlands is affected by salinity and inundation regimes, with clear differences in plant communities across fresh, brackish, and salt marshes (Atwater et al. 1979; Mitsch and Gosselink 2000; Cronk and Fennessy 2001, Pennings et al. 2005). Interspecific interactions are critical for within marsh vegetation patterns (Bertness 1991, Pennings et al. 2003), and large-scale distribution patterns of estuarine plants along a salinity gradients are driven by competition at low salinities, but freshwater plants are limited by physical factors at higher salinities (Crain et al. 2004). Mahall and Park (change to 1976a, 1976b?1976b, 1976c) showed that both salinity and soil aeration changed with elevation and that both were critical in determining the relative abundance of S. foliosa and Sarcocornia pacifica (formerly Salicornia virginica) in San Francisco Bay. Detailed surveys at San Quintín Bay, Baja California found that salt marsh plants respond to elevation differences as small as 8 cm (Zedler et al. 1999). Sanderson et al. (2000) found similar sensitivity of salt marsh plant distributions to elevation in San Francisco Bay and also identified the importance of tidal channels in influencing plant distributions. Increased inundation rates associated with increases in global SLR will stress marsh plants, reduce productivity, and potentially shift plant distributions (Scavia et al. 2002; Schile, Callaway, Parker, and Vasey, unpublished data). Lower estuarine salinities in the winter and spring could increase seed germination rates, but higher salinities during the summer differentially will stress plants during the growing season, potentially shifting competitive ranking. Increases in SLR will further affect vegetation, particularly at the low end of the marsh where plants typically are stressed by excessive inundation and anaerobiosis (Chapman 1974; Mendelssohn and Morris 2000). Wetland plants have many specific adaptations that allow them to tolerate anaerobic conditions, including well developed aerenchyma (Armstrong 1979), pressurized ventilation and convective gas flow (Grosse et al. 1991), and physiological adaptations (Mendelssohn et al. 1981); however, increased inundation rates will shift tolerances of species across the marsh as areas are flooded to a greater extent. A recent model by Morris (2006) predicts that 3 Parker et al. shifts in SLR will have significant effects on competitive interactions among species, as well as the geomorphological development of intertidal marshes. Beyond impacts to existing, well-developed vegetation, climate change impacts will also affect recruitment patterns within estuarine wetlands. Plant recruitment is a multi-staged, temporally and spatially structured process central to the dynamics of plant communities. Current community or population theories (like plant metapopulation, source-sink, and metacommunity dynamics) require dispersal, seed bank dynamics, and seedling establishment to structure populations and communities (Hubbell 2001, Leibold et al. 2004). Our understanding of plant dispersal (Howe and Smallwood 1982, Nathan and Muller-Landau 2000, Levine and Murrell 2003), seed germination ecology (Baskin and Baskin 1998, Fenner and Thompson 2005), and seed bank dynamics (Leck et al. 1989), as well as the structure and dynamics of adult plants and communities, emphasize the need to focus on the seedling stage. This is particularly important to assess recruitment limitation (Hurtt and Pacala 1995). Given SF Bay-Delta climate change predictions, earlier climatic fluxes suggest the rapidity of potential recruitment changes. For example, Atwater et al. (1979) documented large-scale changes in brackish to near freshwater wetland plant communities during a severe drought year, indicating the potential importance of dispersal effects on future distribution changes. That result parallels more recent studies from other wetland systems that have suffered temporary shifts toward more saline conditions, for example, along the Gulf Coast (Wang 1988; Flynn et al. 1995; Howard and Mendelssohn 1999, 2000; Thomson et al. 2001; Visser et al. 2002). Freshwater and oligohaline plant species will be the most sensitive to any increases in salinity (e.g., Baldwin et al. 1996). Knowledge of the relationships among seed dispersal, seed banks, plant recruitment and physical processes is crucial to predicting potential effects of climate change on tidal wetland (Baldwin et al. 1996); both salinity and inundation regimes are significant drivers of wetland plant germination and establishment. Prolonged inundation reduces species diversity and biomass (Casanova and Brock 2000) and can have differential effects along an inundation gradient (Keddy and Ellis 1985). Research conducted in coastal marshes of Louisiana suggests that higher salinity and prolonged inundation reduces germination (Baldwin et al. 1996), and these effects are amplified with disturbance (Baldwin and Mendelssohn 1998); however, comparable research in the western coast of North America has not been conducted to adequately address concerns of SLR and increased salinity on marsh plant recruitment. In addition to shifts in plant distributions, there are likely to be shifts in productivity due to gradual changes in salinity, with lower productivity in saline marshes (Pearcy and Ustin 1984, Rasse et al. 2005). Productivity studies from the Bay-Delta are limited (Mahall and Park 1976c?1976a); however, data from across the Bay-Delta demonstrate a trend of decreased productivity with increasing salinity (Figure 1). Atwater et al. (1979) measured high annual biomass of fresh and brackish marsh dominant Schoenoplectus californicus (formerly Scirpus californicus; approximately 2500 g/m2) in comparison to salt marsh biomass for Spartina foliosa (300 to1700 g/m2, with only one site near the high end of this range) or Sarcocornia pacifica (500-1200 g/m2). Similarly, in other estuarine ecosystems, production rates are consistently lower in salt marshes (Odum 1988), likely due to the added stress of high salinities in salt marsh soils. While the proposed research will not evaluate plant productivity directly, two recently funded companion studies supported by CALFED will research productivity rates along the estuarine gradient, including an evaluation of plant interspecific interactions from fresh, brackish and salt marshes, with both greenhouse and transplant studies of dominant plant species (see section below on synergistic research) Tidal marsh avian community responses to salinity and SLR Due to the harsh environment created by high salinity and tidal inundation regimes, as well as the low structural diversity of these systems, tidal marshes are generally characterized by low vertebrate species diversity (Greenberg et al. 2006). However, they are also characterized by a high proportion of endemic vertebrate subspecies, specially adapted to tolerate those harsh environments (Basham and Mewaldt 1987; Greenberg and Droege 1990). Brackish and fresh marshes support more vertebrate species 4 Parker et al. than salt marshes (PRBO unpublished data), but the additional species are generally more common and generalist in their habitat preferences. In the Bay-Delta, salt marshes support six avian subspecies of conservation concern—California Clapper Rail (Rallus longirostris obsoletus), California Black Rail (Laterallus jamaicensis coturniculus), Tidal Marsh Song Sparrow (Melospiza melodia samuelis, M.m. pusillula, M.m. maxillaris), and Salt Marsh Yellowthroat (Geothlypis trichas sinuosa). These same species are also found in brackish, but usually not in fresh marshes. Thus, while an increase in salinity may lead to declines in tidal marsh plant diversity, and perhaps the loss of several rare and endemic plant species, we do not expect the same pattern in avian communities, in which many species may benefit from an increase in high salinity tidal marshes. Rather, SLR may pose a larger threat to tidal marsh vertebrates. Several taxa, including California Black Rail, are known to depend on the presence of refugia from predators at high tide, which may be reduced or eliminated with SLR (Evens 1986). Others, including Tidal Marsh Song Sparrow and Salt Marsh Yellowthroat have been observed to have lower densities in smaller, more fragmented marshes (Spautz et al. 2006). For the Song Sparrow, which generally nests in low-lying Sarcocornia pacifica or Grindelia stricta, high tide and storm-related flooding has been demonstrated to be a major source (up to 25%) of nestling mortality (Johnston 1956, N. Nur, unpubl. data). Furthermore, not all tidal marsh-associated vertebrate species are likely to respond in the same manner to the effects of climate change, given the variation in salinity tolerance, vegetation associations, vulnerability to edge-associated predation, impacts of tidal inundation and flooding, and response to tidal channels. The disparate shifts in ranges of plant, as well as avian species, may therefore result in a “tearing apart” of ecological communities (Parmesan 1996), which could cascade up and down the food chain, creating other disruptions in ecosystem functions. In conjunction with habitat fragmentation, the disruption could provide new opportunities for introduced exotic species to invade. Furthermore, the spread of exotic invasive plant species such as S. alterniflora has great potential to change tidal marsh plant community structure, and exclude some species, such as Song Sparrow, that have low densities and low reproductive success in this vegetation type (Gutenspergen and Nordby 2006). In addition to improving or reducing nesting habitat opportunities for certain avian species, changes in plant community composition may also facilitate new or different species interactions by altering their spatial distributions. For example, Marsh Wrens may exclude Song Sparrows via aggressive territorial behavior, as well as nest depredation, in Spartina-invaded marshes (J.C. Nordby unpublished data). For avian species, high diversity has been associated with high structural vegetation diversity, more than plant species diversity (Rotenberry and Wiens 1980; James and Warner 1982). However, San Francisco Bay studies have demonstrated that individual marsh plant species are important predictors of individual avian species’ abundance (Spautz et al. 2006), as has been found in other systems (Wiens and Rotenberry 1981). Statistically controlling for landscape context, geomorphic characteristics, and vegetation structure, Song Sparrow density has been shown to increase with percent cover of Grindelia stricta (saline-brackish) and Baccharis pilularis (upland), while Common Yellowthroat density has been shown to increase with percent cover of Schoenoplectus acutus (brackish-fresh), Bolboschoenus maritimus (saline-brackish), and Lepidium latifolium (invasive), as well as overall vegetation diversity (Spautz et al. 2006). Thus, to a certain extent, we would also expect avian species’ distributions to shift in response to shifts in dominant or subdominant tidal marsh plant species that may occur with climate change. Thus for avian communities, the potential pathways of climate change effects are numerous and complex. Changes in salinity, elevation, and inundation may effect some bird species directly, while the indirect effects of changes in marsh composition and structure (including plant species and channel characteristics), as well as resulting changes in avian species interactions (e.g., competition) may be equally or more important to consider. Modeling species distributions Species distribution models (SDM), also known as niche models or bioclimatic models, have seen increasing popularity in recent years as tools for predicting potential shifts in species’ distributions as a 5 Parker et al. result of climate change (Pearson and Dawson 2003; Thuiller 2004; Araujo et al. 2005). This empirical approach has distinct practical advantages in that it tends to provide more realistic (data-driven) predictions than theoretical models and can also provide a high level of generality given proper inputs and informed ecological assumptions (Guisan and Zimmerman 2000). However, most SDM work has been done at a broad, continental or regional scale, often at spatial resolutions of grid cells 1 km2 or greater. Furthermore, the great majority of such modeling has been done for upland terrestrial habitats. Very little species distribution modeling has been conducted explicitly for coastal systems, which necessitate a relatively fine-scale approach, due to their limited narrow extent. Although several researchers have conducted spatial evaluations of SLR on the availability and quality of shorebird habitat (Galbraith et al. 2002; Austin and Rehfisch 2003), we know of only one example of an SDM used to predict climate change-induced shifts in coastal or estuarine species (Rehfisch et al. 2004). There are several common approaches to SDMs, which can be categorized as simple bioclimatic envelope models such as BIOCLIM (Busby 1991) and DOMAIN (Carpenter et al. 1993); statistical models such as generalized linear models (GLM; McCullagh and Neder 1989), generalized additive models (GAM; Hastie and Tibshirani 1990), and classification and regression trees (CART; Breiman et al. 1984); or machine learning approaches, such as genetic algorithms for rule-set prediction (GARP; Peterson 2001), artificial neural networks (ANN; Ripley 1996), and maximum entropy (MaxEnt; Phillips et al. 2006). In general, statistical approaches are considered the most rigorous and are usually used with species occurrence datasets that contain both presence and absence data, while envelope models and some machine learning approaches are most suitable for presence-only occurrence data, such as museum specimens or natural heritage databases. However, there is wide variation in the performance of these models, and this depends on a large number of factors that are difficult to control. Recent comparative studies have suggested that novel methods such as MaxEnt (Elith et al. 2006) and “boosted” or modelaveraged CARTs (Lawler et al. 2006, Leathwick et al. 2006) have the highest rates of prediction success in some contexts. However, standard GLMs and GAMs are widely used, have strong statistical foundations, identify functional relationships, are relatively easy to interpret, and perform well in comparison tests (Wintle et al. 2005). Although community-based multivariate approaches to SDMs have been developed (Ferrier et al. 2002, Hirzel et al. 2002, Leathwick et al. 2006), SDMs are still based on current species distributions in relation to environmental conditions, and do not explicitly incorporate interactions among species or dispersal abilities. Thus SDMs alone may not be sufficient to accurately predict future shifts in species occurrence. In this study we will statistically estimate the effects of one species on other species through path analysis (Wooton 1994) and thus characterize important direct and indirect pathways linking physical factors, plant species, and bird species. In addition, competitive interactions will be addressed through field experiments. In this way we will be able to evaluate the assumptions of standard SDMs that outcomes for one species can be predicted independently of its competitors. OBJECTIVES AND HYPOTHESES Using a combination of field sampling and data analysis, experimental manipulations, and species distribution modeling we propose to address the following overall question: How will tidal marsh extent and community processes respond to a range of future SLR and salinity scenarios? In our study we will focus on the following specific questions: 1. How do salinity and tidal inundation influence the distribution, diversity, and establishment of tidal marsh plant species in the San Francisco Bay-Delta? We will address this question through (a) intensive vegetation sampling at six mature marsh sites across the salinity gradient, and analysis of within-marsh patterns of distribution and diversity; (b) extensive sampling of vegetation distributions across the Bay-Delta, and spatial modeling of estuarywide patterns of distribution, diversity, and establishment; (c) experimental evaluation of the differential impact of salinity and inundation on the establishment of tidal marsh plant species to 6 Parker et al. determine threshold sensitivities for establishment; (d) sampling study of upstream seed dispersal to evaluate species-specific dispersal limitations and order of colonization, and (e) coordination with an on-going CALFED-funded project to evaluate plant productivity and community interactions, including competition, across these same gradients. Our combined efforts will identify the influence of biotic and abiotic factors on overall plant distributions under current conditions and with projected climate change. 2. How do biotic (vegetation-based) and abiotic factors (channel density, inundation patterns) influence the distribution and abundance of tidal marsh bird species? We will address this question by using an extensive dataset of avian occurrence and abundance across the Bay-Delta, in conjunction with plant distribution, diversity, and productivity data, as well spatial environmental data layers, to develop and compare various empirical models of avian distribution and abundance. A complementary path analysis will provide a potent means to identify linkages among physical (salinity, inundation, geomorphology) and biotic (plants and other bird species) on tidal marsh bird species. 3. How will the distributions of key freshwater, brackish and salt marsh plant species, including rare and invasive species, respond to various climate change scenarios, as indicated by SLR and estuarine salinity patterns? Which species will migrate together or separately? We will address this question by applying future predictions of SLR and salinity shifts to spatial models developed using current plant distribution data. A range of climate change scenarios will be used to assess conservative to more extreme predictions of future conditions. Model-predicted future distributions will be compared with current distributions, and will consider results of field-based salinity and inundation experiments, as well as seed dispersal observations, to describe an envelope of future change potential. The importance of interactions among plant species will be assessed based on statistical and experiment studies described above. 4. How will the distributions of tidal marsh bird species shift under various climate change scenarios? Which species and what parts of their distributions are most likely to be threatened by climate change? We will address this question by applying future predictions of SLR and salinity shifts, as well as predicted changes in plant species distributions, primary productivity, and plant species diversity, to models of avian distribution and abundance. METHODS This proposed research will incorporate a broad suite of plant and bird data collected throughout the Bay-Delta. Much of these data have been collected as part of two regional, multi-disciplinary research efforts, partly overlapping in research objectives and spatial extent. The Integrated Regional Wetlands Monitoring Pilot Project (IRWM; www.irwm.org) is an interdisciplinary research effort examining wetland restoration in the North Bay and Delta, with primary goals of (1) understanding how ecosystem restoration efforts affect ecosystem processes at different scales and (2) identifying useful monitoring indicators and protocols. IRWM activities have involved the intensive collection of nutrient, elevation, salinity, vegetation, invertebrate, fish, and avian data at six sites over two years throughout the northern bay and into the Delta. The PIs and senior personnel involved in this proposal have collaborated together under the IRWM project, which will be completed in 2007, with several publications in progress. BREACH is another interdisciplinary research effort, seeking to gain a conceptual and empirical understanding of the important mechanisms and thresholds of restoration processes in Bay-Delta tidal marshes. Two BREACH phases focusing on the Delta (fresh) and North Bay (saline to brackish) marshes have been completed (Simenstad et al. 2000), and a third phase, focusing on intensive monitoring and 7 Parker et al. modeling of a single Delta restoration site, will commence in late 2007. One of the PIs (Nur) has been involved in all three phases, and two senior personnel (Stralberg, Herzog) will play a role in the avian and landscape ecology components of the upcoming third phase. In addition, Parker and Callaway recently received a grant from CALFED to build on IRWM results and evaluate the effects of climate change on marsh productivity, decomposition, and fish food webs (see below). Data collected through BREACH and IRWM, supplemented by long-term avian monitoring data collected by PRBO Conservation Science (PRBO; see Spautz et al. 2006), provide the basis for a comprehensive investigation into the effects of climate change on tidal wetland vegetation and vertebrate distribution and diversity in the Bay-Delta. Additional field sampling will be conducted to fill in any gaps along the salinity gradient, and public databases will be used to improve sample sizes for rare and special status species. Sampling sites Intensive sampling sites We have selected six natural marsh systems as the focus of intensive research in this investigation (Figure 2). These six sites span the full salinity gradient of the estuary and represent some of best representatives of historic tidal wetland landscapes in the region. They also have a rich legacy of scientific investigation and baseline data. We chose relatively undisturbed remnants of the Bay-Delta’s historic wetland ecosystem, rather than restoration sites, because the former should provide greater insight into how different salinity regimes affect existing wetland conditions. The first two sites represent the saline end of the spectrum (25-45 ppt summer salinity). China Camp State Park is part of the San Francisco Bay National Estuarine Research Reserve and consists of about 125 ha with an uncharacteristically intact upland transition and large expanse of tidal mudflats. It has been studied by PRBO since 1996. Petaluma Marsh represents the largest intact salt marsh in California, covering over 800 ha and was part of the BREACH 2 project. Two sites have been chosen that represent brackish tidal wetlands (15 ppt average summer salinity). Coon Island is one of the last undiked, large tidal wetland landscapes in the upper San Pablo Bay area, covers about 175 ha, and has received intensive investigation as part of the IRWM project. Rush Ranch Open Space Preserve is also part of the SF Bay NERR and contains the largest remnant brackish tidal wetland in the Bay-Delta, covering over 400 ha. It has been studied by PRBO since 1996. The last two sites represent freshwater or near freshwater tidal marshes. Browns Island is in the western end of the freshwater delta created by the confluence of the Sacramento and San Joaquin rivers. It covers about 200 ha and has also received intensive investigation as part of the IRWM project. Sand Mound Slough is farther up the estuary and is comprised of a number of small, intra-channel remnants of historic Delta wetlands, covering a total of approximately 25 ha. Extensive sampling sites PRBO (Nur, Stralberg, Herzog) has been conducting breeding season point count surveys according to standardized protocols (Ralph et al. 1993) in Bay-Delta marshes since 1996, and has accumulated an extensive long-term database of avian occurrence and abundance, as well as data on plant species composition, structure, and cover proportions collected at each point location using a modified relevé protocol (Figure 2; Spautz et al. 2006). Currently, we have bird and vegetation data from over 450 survey points at over 55 marshes, including BREACH and IRWM sites (Figure 2). We will also select additional freshwater sites throughout the Delta (i.e., Lindsey Slough marsh and Upper Mandeville Tip) to conduct plant and avian surveys for modeling purposes. These sites will be used to fill in the gaps in our existing dataset, which may not adequately represent the fresh end of the salinity spectrum for some organisms (Figure 2). Vegetation surveys will be conducted on many remnant freshwater marshes throughout the Delta in order to supplement species distribution and abundance data collected at the intensive sampling sites. 8 Parker et al. At extensive sampling sites, we will do field surveys of each location to develop presence/absence data for plant occurrences. These data will be used in conjunction with the existing and new bird data to further evaluate bird habitat relationships and to expand data for modeling on plant species distributions. Field and greenhouse studies Plant distribution and diversity To accurately determine different dimensions of plant diversity, we plan to utilize randomly placed 0.1 ha plots to survey for plant composition (Stohlgren et al. 1995, Peet et al. 1998, Stohlgren 2007). Smaller subplots within these larger plots will be randomly placed to assess relative cover and frequency. We will use species-area/species-accumulation curves to assess sampling intensity (EstimateS version 8; Colwell 2006). During IRWM vegetation surveys, we collected vegetation presence and cover data in over 300 randomly located plots at Coon and Browns Islands. We plan to compare the sampling techniques to analyze within-marsh patterns of distribution, diversity, and productivity. For distribution modeling purposes, we will use all available distribution and abundance data, including PRBO relevé data on plants and intensive plot samples, and also conduct new surveys at a variety of remnant freshwater wetlands in the Delta to increase data coverage (approximately 15 sites). These data will be used to develop spatial models of individual species’ distribution and abundance (percent cover), as well as plant species diversity. We will also make use of extensive existing datasets on invasive and special status plant species distributions within the Bay-Delta. We intentionally have chosen additional sites farther upstream in the Delta so that we will be able to evaluate the migration of more salinity tolerant species up the estuary. Seed dispersal and plant establishment To estimate seed dispersal abilities of salt marsh plant species into the tidal freshwater zones of the Bay-Delta, we will establish 0.25m2 seed traps at two sites representing the transition from oligohaline to freshwater tidal, Browns Island and Sand Mound Slough, and two sites farther up the Sacramento River (Lindsey Slough) and San Joaquin River (Upper Mandeville Tip). Seed traps made from multiple layers of burlap will be anchored to the marsh surface near channel edges (Hicks and Hartman 2004`, Neff and Baldwin 2005). All existing vegetation will be clipped from around the traps, and a 3-m diameter vegetation survey will be conducted to determine presence and abundance of local species. Depending on the size of the site, 10-20 traps will be deployed at each site in September 2008 and will be replaced every three months for an entire year. Shallow soil cores will be removed near seed trap locations to document the local seed bank. In a lab, traps and soil cores will be placed in cold storage for 2 weeks and then germinated in a greenhouse with freshwater in flats filled with sand. All seedlings will be identified to species and counted. This method has been used successfully to document seed dispersal and seed bank characteristics at tidal marshes along the Napa River, San Pablo Bay, CA (Diggory and Parker, manuscript in prep.). These results will be used to modify model predictions for species found to be dispersal-limited. In order to evaluate potential rates of plant establishment under changing salinity and inundation regimes, we will conduct companion field and greenhouse experiments. First we will collect seed bank material during midwinter (prior to germination) from each of the four freshwater marshes above (Browns Island, Sand Mound Slough, Lindsey Slough, and Upper Mandeville Tip), as well as the targeted brackish and salt marsh sites (Rush Ranch, Coon Island, Petaluma Marsh, and China Camp). Sampling locations will be randomly selected, but stratified into two groups at each marsh, in low marsh and in high marsh, and samples taken in clusters. Individual seed bank samples will be collected from 25 x 25 cm surface area, taken to a 5 cm depth. Locations of samples will be marked and GPS coordinates taken. Samples will be divided into 3 groups. One group will assess natural seed bank composition and relative dominance for each site using emergence technique (Hopkins and Parker 1984). For the other two groups, samples from all sites will be bulked together and mixed thoroughly. Subsamples of half of the bulked material will be germinated in the greenhouse under several treatment conditions. Treatments will include 9 Parker et al. watering with a range of salinity concentrations (0 ppt, 4 ppt, 8 ppt, 16 ppt) and two flooding treatments (well-drained, flooded to 2 cm) in a random block design. The other half of the bulked seed banks also will be split into smaller subsamples, and placed into the field at 6 sites (2 freshwater tidal, 2 brackish tidal and 2 salt marshes) under both high and low marsh conditions. We will use 25 x 25 cm quarter flats, with bottoms replaced by fine mesh weed cloth, buried to the surface, to place the seed banks in the field. Locations within marshes will use the previous seed bank sample sites. Soil samples lacking seeds (blanks) will be placed at every site to account for new dispersal. Sites will be monitored throughout the season for changes in soil salinity using refractometers. Data from these experiments will be used to assess the potential influence of SLR and increases in salinity on future differential recruitment patterns, including the influences of seedlings from other species. Because establishment rates from seed could be quite low, we also will evaluate establishment rates from small seedlings (approximately 4 to 6 weeks old) in the field. Seedlings of each species will be raised in the greenhouse and transplanted into the field using the same sampling locations as the transplanted seedbank experiment (stratified high and low marsh locations at all eight sites). Combinations of experiments such as those proposed have provided direction into possible shifts in seed bank and recruitment dynamics (Hopkins and Parker 1984, Parker and Leck 1985, Leck and Simpson 1995, Baldwin et al. 1996, 2001). The seed trap data will allow assessment of potential upriver dispersal limitation (Neff and Baldwin 2005, Diggory and Parker, manuscript in prep.). The seed bank and seedling out-planting data will permit assessment of recruitment limitations, either by environmental constraint (flooding or salinity) (Noe and Zedler 2001, Seabloom et al. 2001, Peterson and Baldwin 2004) or by differential exclusion (competitive displacement or lack of facilitation) (Bertness and Ellison 1987, Pennings and Callaway 1992, Callaway and Pennings 2000). Avian distribution and abundance At least 20 study sites have been annually surveyed in at least 10 breeding seasons during the period 1996 to 2007. The other 35+ sites vary in the number of years in which avian surveys were conducted, but points at all sites have at least one associated vegetation survey. We will revisit a subset of our core sites and also identify and survey approximately 10 new freshwater sites in the delta region. Standardized avian point count surveys (Ralph et al. 1993) accompanied by modified relevé surveys (Spautz et al. 2006) will be used to collect additional bird and plant species distribution and abundance data. Statistical analysis and spatial modeling Before developing predictive spatial models, we will carry out statistical analyses of plant and avian survey data, so as to identify linkages between drivers (especially SLR and salinity) and proximate factors (geomorphic features such as channel density; plant characteristics) as well as influences of both physical and biotic factors on birds. Thus plant characteristics will be used as both outcome variables and as independent variables. We will use insights gathered to develop and validate spatial models suitable for predicting current distribution and abundance of plants and birds (SDMs) and then use these models to make predictions of plant and bird response to future changes in salinity and SLR. Statistical Analysis Using path analysis (Wooton 1994), or more generally, structural equation modeling (Grace and Pugesek 1997), we will characterize causal and correlational relationships among the physical and biotic factors and the outcomes of interest. This process will guide the development of spatially predictive models described below. Structural equation modeling (SEM) is a very general, yet powerful multivariate analysis technique that will allow us to consider multiple outcome variables and how they are linked, directly and indirectly. The models we will develop will have salinity and inundation as driver variables, which then have both direct and indirect pathways of influence. Thus tidal inundation could influence channel density which influences plant productivity or structure which then influences bird species 10 Parker et al. abundance, but there may also be direct influences of tidal inundation on bird abundance. These pathways will be elucidated and evaluated using SEM. In addition, we will use this approach to evaluate influences of one plant species on other species, as well as influences of one bird species on others (all ecologically relevant species to be considered). These analyses will not only assist in predictive model development, but results from these statistical analyses can be used to examine (confirm or question) assumptions of the single species predictive modeling described below. Modeling current species distribution and abundance SDMs will be constructed for tidal marsh plant and avian species, using three primary data sources for species occurrence data: (1) vegetation sampling plots and bird surveys conducted by the principal investigators and their organizations (see Figure 2 for locations); (2) statewide public database records for special status species occurrence, including the California Natural Diversity Database (CNDDB; http://www.dfg.ca.gov/whdab/html/cnddb.html) and Jepson Herbarium on-line database (http://ucjeps.berkeley.edu/db/smasch/); and (3) other data on the distribution of Bay-Delta plant and animal species collected by research colleagues and public agencies, including the Invasive Spartina Project (http://www.spartina.org). Species to be modeled include dominant plant species, special status tidal marsh plant species, invasive plant species, and tidal marsh specialist avian species. In addition to species distributions, we will develop models of abundance for common avian species, and models for plant abundance (percent cover), productivity, and species diversity. Environmental inputs will include spatial data layers representing salinity, elevation, tidal inundation, and land use. Predicted plant and bird distributions will also be used as inputs to other species’ models. The spatial resolution of our models will be tied to the resolution of available digital elevation models (DEMs), which will also be used as a basis for future SLR and tidal inundation scenarios: 10-m x 10-m pixels from the national elevation dataset (NED, http://ned.usgs.gov/). From elevation, we will model tidal inundation, using continuous water level data from NOAA, various municipalities, and restoration projects, including IRWM sites. We will develop tidal inundation graphs for each tide gauge location and calculate total monthly and maximum daily tidal inundation during the growing season (June/July), as well as tidal range. Inundation metrics will be interpolated across the subtidal and intertidal portions of the Bay-Delta. Coarser salinity data layers (approximately 3-km resolution) will be obtained from the CALFEDfunded CASCaDE project (http://sfbay.wr.usgs.gov/cascade/, see next section), and sampled down to the 10-m resolution. Current land use from NOAA’s 2000 C-CAP dataset, will be included in models for vertebrate species, whose distributions and abundances are known to be limited by the composition and configuration of surrounding uplands (Shriver et al. 2004; Spautz et al. 2006). From this and other land use data, we will identify barriers to shoreward migration and use them as a mask for future distributions. Depending on the type of data that are available for each species/metric, we will use and compare variations on several different distribution modeling approaches: Presence-only data: Maximum entropy (MaxEnt) models Presence/absence data: Generalized linear models (GLM) or Generalized additive models (GAM) with a binary distribution; and/or boosted regression trees Abundance data: GLMs or GAMs with a negative binomial distribution; and/or boosted regression trees Species diversity / productivity data: GLMs with a Gaussian distribution; and/or boosted regression trees. Relationships between species metrics and environmental inputs (including the presence of other similar species) will have been determined through the path analysis/SEM described above. Spatially predictive models (“spatial models”) will be developed that predict current distributions (and abundance, etc.), as well as potential future distributions under various climate change scenarios (Table 1). The use of interaction terms in our models will allow better incorporation of interspecific competition effects, which may limit or enhance the effects of physical drivers on plant communities. Predicted distributions of 11 Parker et al. dominant and invasive (but not special-status) tidal marsh plant species, as well as predicted primary productivity and species diversity, will also be used as inputs to the bird models (with non-tidal areas masked out for model development). Tidal marsh channel density will also be modeled based on environmental inputs and used as an input to bird models. Model predictions will consist of spatial data layers covering potentially tidal habitats and immediately adjacent uplands within the Bay-Delta system (see Figure 3). Each model will be built using 75% of the dataset, and evaluated using the other 25%, to obtain indicators of model predictive ability; this will be repeated three more times so that all data are included in one test dataset. Functional relationships will be evaluated, during the initial statistical analysis phase and as part of the field experiments and in the model building phase, and used to further evaluate the performance of each model. Examples of preliminary current and future predictions for a special status tidal marsh plant species, based on coarse environmental inputs, are shown in Figure 4. Modeling future distribution and abundance Once models have been developed that adequately account for present distribution and abundance of plants and birds, consistent with the SEM analysis and results of field experiments, we will turn to applying these models to future changes in salinity and SLR. Our SLR scenarios will encompass a range of predictions based on several emissions scenarios from the recent Intergovernmental Panel on Climate Change (IPCC) Assessment 4 (AR4) simulations (IPCC 2007), incorporating thermal expansion as well as melting of glaciers and ice caps, and adjusted for California (Cayan et al. 2005) (Table 1). Future marsh elevation and tidal inundation predictions will be based on current topography and will not include geomorphic change, unless such predictions become available for San Francisco Bay. Future values for marsh relative elevation will be based on current elevation values, predicted SLR, and rates of marsh accretion (Figure 4). Because there is uncertainty as to how much future marsh accretion may occur, we will use two different estimates of marsh accretion: one which is indicative of current conditions (based on sampling by the BREACH team in north San Francisco Bay and Callaway in other Bay locations, as well as published values in Patrick and DeLaune 1990 and other sources) and the potential for maximum marsh accretion based on a survey of other marsh systems (Stevenson et al. 1986; Reed 1995; Callaway et al. 1996) (Table 1). For estimates of future salinity, we will rely on predictions being generated by the CALFEDfunded CASCaDE project (http://sfbay.wr.usgs.gov/cascade/), an extension of previous California climate modeling work conducted by the principal investigators (Knowles and Cayan 2002; Dettinger et al. 2004; Knowles et al. 2006). Using GCMs scaled-down for California, temperature and precipitation predictions were converted to monthly estimates of snowmelt runoff and stream flow, which were used to generate salinity predictions (approximately 3-km resolution across bay salinity gradient) under various scenarios. These predictions will be available from the CASCaDE team and will be used in conjunction with tidal marsh salinity measurements collected by the IRWM project and the South Bay Salt Pond Restoration Project, to extend salinity predictions into the tidal marsh zone. Shifts in distribution, abundance, productivity, and species diversity will be assessed and compared under each scenario, and the key environmental drivers will be identified in each model. For plant species, we will assess the relative importance of physical factors compared with species competition, for those species where competitive interactions were implicated (see Statistical Analysis section, above). For avian species, we will evaluate the direct and indirect contributions of physical (salinity, elevation, inundation, channel density) factors compared with biotic factors (plant species composition and diversity) to better understand the mechanisms influencing their distribution and abundance. Species currently co-occurring will be evaluated in terms of the similarity of future distributions, providing an indication of maintenance or disruption of future community integrity. Finally, for each species/metric, we will evaluate areas of highest potential loss and gain, across emissions scenarios and accretion rate assumptions, providing insight for conservation and restoration priorities. Results of field experiments will be used to modify or augment the predictions from the spatial 12 Parker et al. models developed. For example, plant establishment studies may indicate broader ranges of environmental tolerance (i.e., inundation and salinity ranges) than indicated by models for some plant species, due to competitive exclusion. Conversely, dispersal experiments may indicate limits on modelpredicted distribution shifts. Incorporating these factors explicitly into models is beyond the scope of the current proposed work, but this study will lay the foundation for future modeling by identifying and quantifying the relevant constraints and interactions. Research Schedule We propose a three-year study incorporating 2 years of data collection that will supplement previously-collected data throughout the Bay-Delta. In Year 1, personnel from San Francisco State University (SFSU) and University of San Francisco (USF) will begin field sampling for plant diversity, seed dispersal ,seed banks, and establishment. PRBO, SFSU, and USF will also summarize and prepare existing species occurrence data, and prepare elevation and inundation inputs to SDMs. In Year 2, SFSU and USF will conduct experiments investigating effects of increased salinity and inundation on plant establishment. PRBO will conduct statistical analyses (SEM) as well as obtain spatial salinity projections, develop, and validate SDMs, and generate predictions for SLR and salinity scenarios. In Year 3, USF and SFSU will complete all analysis of field-collected observational and experimental data, and together with PRBO, will finalize models, synthesize results, and write findings for publication. Significance and Synergism of Collaborative Research Team The collaborators in this project have worked together during the IRWM project, which was previously mentioned. We combine extensive field experience with plants and birds, as well as modeling and spatial analysis expertise. Through the IRWM project, we began developing a variety of metrics as a predictive tool for plant and animal distributions and abundances in marshes, and in this proposed research we will build on those findings. In addition, the plant PI and senior scientist (Parker, Callaway) recently received funding from CALFED. The CALFED research would be synergistic with this one (http://science.calwater.ca.gov/pdf/psp/PSP_TSP_results_summary_112206.pdf), focusing on overlapping research sites along the same salinity gradient but targeting questions related to plant productivity, decomposition rates, sedimentation dynamics, plant elevational distributions, and the linkage to estuarine fish food webs. The CALFED research includes a different modeling approach, focusing on potential climate change impacts for fish food webs in Bay-Delta marshes. In addition a CALFED Ph.D. fellowship recently awarded to Lisa Schile (former Research Technician with Parker and Callaway) will provide detailed data on plant interspecific interactions through field transplant experiments and greenhouse experiments under a range of different salinity and inundation regimes. This companion research supported by CALFED will provide data on well-established marsh plants; the proposed plant research for this grant will fill a major gap in understanding potential plant community shifts by evaluating climate change impacts on plant establishment. Together, these projects will make tremendous contributions to the development of long-term management and policy initiatives for BayDelta tidal marsh vegetation and the animals that are dependent on them. 13 Parker et al. TABLES AND FIGURES Table 1. Climate change scenarios to be evaluated using SDM techniques (combinations with gray shading). GCM outputs will be based on IPCC Assessment Report 4 (AR4) simulations. GFDL = Geophysical Fluid Dynamics Laboratory; PCM = Parallel Climate Model. See IPCC (2007) for description of emissions scenarios. Salinity Emissions Scenarios / GCMs (from CASCADE project SLR Emissions output, based on IPCC 2007 AR4 simulations) Scenarios (Cayan et al. 2005) B1 / GFDL B1 / PCM A2 / GFDL A2 / PCM current current accretion rates accretion rates B1 / GFDL (13-62 cm) max. max. accretion accretion current current accretion rates accretion rates A2 / GFDL (18-76 cm) max. max. accretion accretion current current accretion rates accretion rates A1fi / GFDL (21-89 cm) max. max. accretion accretion 2000 species diversity ANPP 6 4 1000 2 ANPP (g/m2) species diversity 1500 500 0 0 0 2 4 6 8 10 12 average spring water salinity (psu) 14 16 B Figure 1. Average plant species diversity per 3m-diameter plot and ANPP decrease with increasing salinity in the San Francisco Bay-Delta (error bars = ±1 SE; number of random plots per site range from 151 to 447). Salinity data represent measurements averaged across spring months in 2004 (Wetlands and Water Resources, unpublished data). ANPP values were derived from site-specific averages of total standing biomass of individual dominant species that were scaled up to site-level estimates using vegetation maps, and then adjusted by site area to obtain ANPP estimates at the g/m2 level. 14 Parker et al. Figure 2. Locations of existing extensive and intensive sampling locations in the San Francisco-Bay Delta. Additional sites will be selected in the Delta region if possible. Figure 3. Potential effects of sea-level rise (SLR) in the San Francisco-Bay Delta. 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