Download Predicting the effects of sea level rise and salinity changes on west

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts
no text concepts found
Transcript
Predicting the effects of sea level rise and salinity changes on west coast tidal marsh plant and avian
communities
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
Lisa Schile, San Francisco State University
ABSTRACT
We propose to use new and existing data to examine the influence of salinity and inundation on
the distribution, productivity and diversity of tidal marsh plant and avian species. We will generate
spatially explicit models that predict the responses of tidal marsh extent and community processes 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, growth, productivity, and diversity 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 shift 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, primary productivity will be measured by total standing biomass, and
seed traps will be deployed to assess dispersal potential, abundance, and distance. Greenhouse
experiments will assess the effects of salinity and inundation treatments on relative growth rates,
mortality, and biomass of dominant tidal marsh plant species. Using field-based abundance and GISbased environmental data, we will develop distribution models for dominant, rare, and invasive plant
species, as well as spatial models for primary productivity and plant species diversity. Based on
relationships between habitat distributions and bird occurrences, we will model bird species distribution
and abundance and validate models using additional 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 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, and changes in patterns of precipitation 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 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), 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 representing 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, under various climate change scenarios using an extensive
set of new and existing field survey data. Because SDM predictions are based on current species’
distributions and do not explicitly consider community-level species interactions or dispersal abilities, we
propose to complement our modeling work with an experimental greenhouse study of plant tolerances of
salinity and inundation and a field-based study of plant dispersal. This will provide further insight into the
mechanisms for shifts in plant distributions, and the potential for future communities to remain intact.
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
hybrids 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 (i.e., increased in spring/summer, decreased in winter)
salinity regime (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 is projected to occur at a rate of
up to 89 cm over the next 100 years (IPCC 2001; Cayan et al. 2005), an acceleration of the recent rate of
23 cm/century (Flick and Cayan 1984). 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). 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 can not 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 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
2
Parker et al.
in response to SLR. Thus there is a high level of uncertainty about tidal marsh responses to SLR. SLR
contributes another significant stressor to the Bay-Delta system because most of the delta region is leveed
and under agriculture. Thus, 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
Salinity and tidal inundation are the two critical factors that drive vegetation community structure
in estuarine tidal wetlands (Atwater et al. 1979; Mitsch and Gosselink 2000; Cronk and Fennessy 2001,
Pennings et al. 2005). 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 do contain threatened and federally listed species, such as soft bird’s
beak (Cordylanthus mollis ssp. mollis). Brackish sites that are less saline are not markedly more diverse,
but 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 in the upper estuary 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. Atwater et al. (1979) also documented large-scale changes in brackish to near freshwater
wetland plant communities during a 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
1999; 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).
Plant zonation within estuarine wetlands is based primarily on inundation rates, largely as
determined by elevation across the wetland. Mahall and Park (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. At the low end of the marsh, plants typically are stressed by excessive
inundation and anaerobiosis, affecting both productivity and overall distributions (Chapman 1974;
Mendelssohn and Morris 2000). Wetland plants have many specific adaptations that allow them to
tolerate anaerobic conditions. Many species have well developed aerenchyma that allows oxygen to
diffuse to roots and rhizomes (Armstrong 1979), and some species (including Schoenoplectus, and Juncus
spp.) can transport oxygen to roots via pressurized ventilation and convective gas flow (Grosse et al.
1991). Spartina alterniflora and other species have physiological adaptations to deal with low oxygen
levels (Mendelssohn et al. 1981). Even with these adaptations, 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).
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
3
Parker et al.
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 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 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.
Tidal Marsh Avian Community Responses to Salinity and SLR
Due to the harsh environment created by high salinity and tidal inundation regimes, tidal marshes
are generally characterized by low vertebrate species diversity, as well as the low structural diversity of
these systems (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
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 high-tide refugia from predators, 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). 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 (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
4
Parker et al.
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 might expect avian species’ distributions to shift in
response to shifts in dominant or subdominant tidal marsh plant species. However, direct effects of
physical factors such as salinity, inundation, and channel density, as well as landscape context, may also
influence the distributions of these species and these need to be incorporated into predictive models.
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
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/analytical models, has greater precision than mechanistic or process-based
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 work has been done for upland terrestrial habitats. Very little species
distribution modeling work 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 model-averaged
CARTs (Lawler 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).
We have chosen to use a combination of MaxEnt, GLM, and GAM modeling methods.
OBJECTIVES AND HYPOTHESES
Using a combination of field sampling and data analysis, species distribution modeling, and
experimental manipulations, 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 will salinity and tidal inundation influence the distribution, growth, productivity, and diversity
of tidal marsh plant species, and how will these species respond to predicted climate change?
5
Parker et al.
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, diversity, and
productivity; (b) extensive sampling of vegetation distributions across the Bay-Delta, and spatial
modeling of estuary-wide patterns of distribution, diversity, and productivity; (c) experimental
evaluation of the differential impact of salinity and inundation on six dominant tidal marsh plant
species to determine threshold sensitivities to these factors; and (d) observational study of upstream
seed dispersal to evaluate species-specific dispersal limitations and order of colonization.
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.
3. How will the distributions of key freshwater, brackish and salt marsh plant species, including rare
species such as Cordylanthus mollis ssp. mollis and Cirsium hydrophilum var. hydrophilum and
invasive species such as Spartina alterniflora and Lepidium latifolium, 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 with results of greenhouse salinity and
inundation experiments, to describe an envelope of future change potential.
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 plant species distributions, primary productivity, and plant species diversity, to models of
avian distribution and abundance, predicting future suitable habitat areas for bird species of interest.
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 Program (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
modeling of a single Delta restoration site, will commence in 2007. One of the PIs (Nur) has been
6
Parker et al.
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.
Data collected through BREACH and IRWM, supplemented by long-term avian monitoring data
collected by PRBO Conservation Science (PRBO), 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.
Petaluma Marsh represents the largest intact salt marsh in California, covering over 800 ha.
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.
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
7
Parker et al.
Field sampling
Plant Distribution and Diversity
Through IRWM vegetation surveys, we collected vegetation presence and cover data in over 300
randomly located plots at Coon and Browns Islands. We plan to continue this sampling at the remaining
four intensive sites to analyze within-marsh patterns of distribution, diversity, and productivity. At each
site, we will visit 100 randomly-selected points, recording species presence and percent cover in a 3mdiameter circular plot. Points will be stratified by distance from channel, as previous work has shown that
the majority of species diversity occurs within 40 m of a channel edge (Sanderson et al. 2000; Parker,
Callaway and Schile, unpublished data).
For distribution modeling purposes, we will use all available distribution and abundance data,
including PRBO relevé data 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). In addition
to the random plot sampling, we will document locations of threatened, endangered, and invasive species
across all sites, including invasive smooth cordgrass (Spartina alterniflora) and its hybrid and
pepperweed (Lepidium latifolium). 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 data on invasive plant species distributions within the Bay-Delta (e.g., existing
Spartina distributions are available from the Invasive Spartina Project, http:\\www.spartina.org).
Plant Productivity
Our productivity measurements will focus on six vascular plants that are widespread across the
Bay-Delta: Spartina foliosa, Sarcocornia pacifica (formerly Salicornia virginica), Bolboschoenus
maritimus (formerly Scirpus maritimus), Schoenoplectus americanus (formerly Scirpus americanus),
Schoenoplectus acutus (formerly Scirpus acutus), and Typha angustifolia. The first two species are
dominant in salt marshes, the second pair is dominant in brackish marshes, and the last pair is prevalent in
freshwater systems, although there is broad overlap in species distributions.
Over the past two years, we have collected annual net primary productivity (ANPP) data from a
suite of dominant species within the Bay-Delta. We will supplement these data with collections at more
sites throughout the Bay-Delta (Table 2). In August 2007, all standing biomass in five 0.25m2 plots will
be collected for each species at both high and low marsh locations at a subset of sites. In the lab, clipped
vegetation will be rinsed with freshwater, sorted by species and live/dead material, dried to a constant
weight, and scaled up to a 1m2 estimate of ANPP.
Using intensive plot data to analyze the relationship between primary productivity and variations
in salinity and species composition within and across sites, we will attempt to extrapolate these
relationships across the Bay-Delta system.
Seed dispersal
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 (Liberty Island) and San Joaquin River (Mandeville Tip). Seed traps made from multiple layers of
burlap will be anchored to the marsh surface near channel edges. 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 2007 and will be replaced every three months for an entire year. A shallow soil core 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
8
Parker et al.
Bay, CA (Diggory and Parker, unpublished data). These results will be used to modify model predictions
for species found to be dispersal-limited.
Avian Distribution and Abundance
At least 10 study sites have been annually surveyed since 1996; other 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 do not plan to conduct additional surveys beyond our current core sites, except if additional
freshwater delta sites are needed. However, upcoming BREACH III surveys are scheduled for a cluster of
delta sites, and we will utilize those data.
Greenhouse experiment
To assess the salinity and inundation tolerance of tidal marsh dominant plants, we will conduct a
common garden experiment with the same six plant species for which productivity measurements were
taken. In February 2008, we will collect rhizomes of B. maritimus, S. acutus, S. americanus, S. foliosa,
and T. angustifolia from a subset of sites and transport them to a greenhouse where they will be rinsed of
native sediment, weighed, planted in sandy soil, and watered with freshwater for 3 months in order to
minimize any negative effects of transplanting. S. pacifica will be started from seed since it is not as
easily propagated from roots. Fertilizer will be applied once at the beginning of the acclimation period to
aid in growth. After the plants have acclimated, ten pots of each species will placed into each of five 8 x 4
x 2 ft plywood containers lined with a double layer of plastic tarp. Two inundation regimes representing
high and low marsh conditions will be implemented. These regimes will be executed by placing five
replicates of each species on cinder blocks of equal height and the remaining replicates on the bottom of
the container. Plants placed on the bottom will be inundated for longer periods than the plants placed on
cinder blocks. Each container will be connected to its own reservoir via tubing and water will be pumped
in ever 12 hours to mimic diurnal tides. The cinder block height and the water level in the container will
be calibrated to result in designated tidal depths. The tidal amplitude will remain fixed throughout the
experiment. Each container will receive a salinity treatment with a target level of 0, 4, 8, 16, or 32 ppt
NaCl. Diluted sea water will be used and the concentration of salt will be increased by 4 ppt each week
from the beginning of the experiment until the target water salinity is obtained. Weekly soil salinity
measurements will be taken in a pot containing only soil and measured using a refractometer. A variety of
plant characters will be measured weekly, including height, number of leaves, ramets, and inflorescences,
among others, and the amount of senescence will be documented. The plants will be monitored for 6
months to evaluate effects of increased salinity and prolonged inundation on growth. At the end of the
experiment, all surviving plants will be rinsed of all sediment, weighed, and dried to a constant weight to
determine biomass.
Results of the greenhouse experiment will be used in conjunction with plant distribution data to
identify salinity and inundation tolerances for each study species, and predict likely shifts in plant
distributions under shifts in salinity and inundation regimes associated with climate change. These data
will be used to fine tune model predictions under different climate change scenarios.
Spatial Modeling
Plant and avian survey data described above will be used to develop spatial models of species
distribution, abundance, diversity, and productivity. Data collected by this proposal’s collaborators and
institutions will be supplemented with publicly available species occurrence data (plants and birds) for the
distribution modeling component. Plant distribution, abundance, diversity, and productivity predictions
modeled from climate parameters will be used as inputs to vertebrate distribution and abundance models.
Other intermediate inputs such as channel density will also be modeled from climate parameters.
9
Parker et al.
Species Occurrence Inputs
Species distribution models will be constructed for tidal marsh plant and avian species, using two
primary data sources: (1) vegetation sampling plots and bird surveys conducted by the principal
investigators and their organizations (see Figure 2 for locations); and (2) 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/).
Species to be modeled include:
 Plants: tidal marsh dominant species, special status tidal marsh species, and invasive species
(Table 2)
 Vertebrates: tidal marsh specialist avian species (Table 3)
In addition to species distributions, we will develop models of abundance for common avian
species (see Table 3), and models for plant abundance (percent cover), productivity, and species diversity.
Environmental Inputs
The spatial resolution of our models will be tied to the resolution of available digital elevation
models (DEMs), which will be used as a basis for future SLR and tidal inundation scenarios: 10-m x 10m pixels from the national elevation dataset (NED). Other coarser data layers will be sampled down to
this resolution. Our SLR scenarios will encompass a range of predictions based on several emissions
scenarios from the upcoming Intergovernmental Panel on Climate Change (IPCC) Assessment 4 (AR4)
simulations, incorporating thermal expansion as well as melting of glaciers and ice caps, and adjusted for
California (Cayan et al. 2005) (Table 4).
Future marsh elevation 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 (Table 4; see the following for a range of
accretion estimates: Stevenson et al. 1986; Reed 1995; Callaway et al. 1996).
In addition to future 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, and adjusted for each SLR
scenario to estimate future inundation metrics.
For estimates of future salinity, we will rely on predictions being generated by the CalFed-funded
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 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.
Finally, 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.
10
Parker et al.
Species Modeling Approach
Depending on the type of data that are available for each species/metric, we will use variations on
two 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
 Abundance data: GLMs or GAMs with a Poisson or negative binomial distribution
 Species diversity / productivity data: GAMs with a Gaussian distribution.
Data will be combined across multiple years to produce a single set of points for each metric of
interest. Each data point will be weighted by sampling effort, the importance of which will be explicitly
evaluated in the modeling process. Relationships between species metrics and environmental inputs will
be used to develop models that predict current distributions (and abundance, etc.), as well as potential
future distributions under various climate change scenarios (Table 4). Model predictions will consist of
spatial data layers covering potentially tidal habitats and immediately adjacent uplands within the BayDelta 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 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.
Predicted distributions of dominant and invasive (but not special-status) tidal marsh plant species,
as well as predicted primary productivity and species diversity, will be used as inputs to the vertebrate
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 vertebrate models.
Shifts in distribution, abundance, productivity, and species diversity, will be assessed and
compared under each scenario, and the key environmental drivers will be identified For vertebrate
species, we will evaluate the contribution 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. Co-occurring species will also 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, accretion rate assumptions and dispersal assumptions,
providing insight for conservation and restoration priorities.
Research Schedule
We propose a three-year study incorporating 1.5 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
productivity, diversity, and seed dispersal and seed banks. 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 a greenhouse experiment investigating effects of increased salinity
and inundation on plant growth and survival. PRBO will also 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 and greenhouse 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
11
Parker et al.
research we will build on those findings. In addition, the plant PI and senior scientist (Parker, Callaway)
have a new proposal in review with CalFed that has been recommended for funding with final approval
due by January 2007. The proposed 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
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. Together, these two projects would
make tremendous contributions to the development of long-term management and policy initiatives for
Bay-Delta tidal marsh vegetation and the animals that are dependent on them.
TABLES AND FIGURES
Table 1. Sampling strategy for ANPP estimates of dominant plant species at sites in Bay-Delta tidal
marshes not previously sampled by USF and SFSU PIs.
Species
S. pacifica
S. foliosa
B. maritimus
S. americanus
S. acutus
T. angustifolia
China Camp
X
X
Petaluma Marsh
X
X
X
Site
Rush Ranch
X
X
X
Sand Mound Slough
X
X
X
Table 2. Plant species and metrics to be modeled (in addition to species diversity and ANPP).
Common Name
Scientific Name
Status
Bolboschoenus maritimus
common, native
alkali bulrush
Suisun thistle
Cirsium hydrophilum var. hydrophilum
Endangered; Federally listed
soft birds-beak
Cordylanthus mollis ssp. mollis
Endangered; Federally listed
gumplant
Grindelia stricta var. angustifolia
common, native
rose-mallow
Hibiscus lasiocarpus
CNPS List 2.2
Delta tule pea
Lathyrus jepsonii var. jepsonii
CNPS List 1B.2; CA-Endemic
pepperweed
Lepidium latifolium
invasive
Mason's lilaeopsis
Lilaeopsis masonii
CNPS List 1B.1; CA-Endemic
perennial pickleweed Sarcocornia pacifica
common, native
tule
Schoenoplectus acutus
common, native
common threesquare Schoenoplectus americanus
common, native
California bulrush
Schoenoplectus californicus
common, native
cordgrass
Spartina alterniflora
invasive
California cordgrass Spartina foliosa
common, native
cordgrass hybrid
Spartina hybrids
invasive
Suisun marsh aster
Symphyotrichum lentum
CNPS List 1B.2; CA-Endemic
12
Parker et al.
Table 3. Vertebrate species and metrics to be modeled.
Common name
California Clapper Rail
California Black Rail
Tidal Marsh Song
Sparrow (3 endemic
subspecies)
Salt Marsh
Yellowthroat
Great Egret
Snowy Egret
Great Blue Heron
Scientific Name
Rallus longirostris obsoletus
Laterallus jamaicensis
coturniculus
Melospiza melodia samuelis,
M.m. pusillula, M.m. maxillaris
Presence /
Absence
X
X
Abundance
(Density)
X
Geothlypis trichas sinuosa
X
Ardea alba
Egretta thula
Ardea herodias
X
X
X
Table 4. 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 (2001) 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
13
Parker et al.
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.
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.
14
Parker et al.
Figure 3. Potential effects of sea level rise (SLR) in the San Francisco-Bay Delta. Maps depict potential
extreme shifts in tidal marsh habitat with a 1m rise in sea level, under the assumption that accretion rates
do not keep up with SLR. Potential tidal marsh habitat is estimated between 0 and 1 meter above sea
level. Current marsh includes tidal and non-tidal (i.e., diked or leveed) marsh.
Figure 4. Preliminary distribution model predictions for Suisun marsh aster (Symphyotrichum lentum)
under current and potential future climate change scenarios, using the MaxEnt modeling approach
(Phillips et al. 2006). This model uses 1 m sea level rise and increased mean annual salinity projections (0.09 to +1.83 PSU; data provided by Noah Knowles, USGS).
15
Parker et al.
LITERATURE CITED
Araujo, M. B., R. G. Pearson, W. Thuiller, and M. Erhard. 2005. Validation of species-climate envelope
models under climate change. Global Change Biology 11:1504-1513.
Armstrong, W. 1979. Aeration in higher plants. Advances in Botanical Research 7:225-232. assessment:
Modeling the Sacramento Basin. Water Resources Research 23(6): 1049-1061.
Atwater B.F.S., G. Conard, J. N. Dowden, C. W. Hedel, R. L. MacDonald, and W. Savage. 1979. History,
landforms, and vegetation of the estuary’s tidal marshes. In: Conomos TJ (ed.) San Francisco
Bay: the urbanized estuary. Pacific Division AAAS, San Francisco, pp 347-385.
Atwater, B.F. and C.W. Hedel. 1976. Distribution of seed plants with respect to tide levels and water
salinity in the natural tidal marshes of the northern San Francisco Bay estuary. California
U.S.Geol. Surv. Open-File Rep. 76-389. 41 pp.
Austin, G. E., and M. M. Rehfisch. 2003. The likely impact of sea level rise on waders (Charadrii)
wintering on estuaries. Journal for Nature Conservation 11:43–58.
Ayres, D.R., D.L. Smith, K. Zaremba, S. Klohr, and D.R. Strong. 2004. Spread of exotic cordgrasses and
hybrids (Spartina sp.) in the tidal marshes of San Francisco Bay, California, USA. Biological
Invasions 6:221-231.
Bakkenes, M., J. R. M. Alkemade, F. Ihle, R. Leemans, and J. B. Latour. 2002. Assessing effects of
forecasted climate change on the diversity and distribution of European higher plants for 2050.
Global Change Biology 8:390-407.
Baldwin, A. H. and I. A. Mendelssohn. 1998. Effects of salinity and water level on coastal marshes: an
experimental test of disturbance as a catalyst for vegetation change. Aquatic Botany 61:255-268.
Baldwin, A. H., K. K. McKee, and I. A. Mendelssohn. 1996. The influence of vegetation, salinity, and
inundation on seed banks of oligohaline coastal marshes. American Journal of Botany 83(4):470479.
Basham, M. P., and L. R. Mewaldt. 1987. Salt water tolerance and the distribution of South San Francisco
Bay Song Sparrows. Condor 89:697-709.
Baumann, R.H., J.W. Day, Jr., and C.A. Miller. 1984. Mississippi deltaic wetland survival: Sedimentation
versus coastal submergence. Science 224:1093-1095.
Boesch, D.F., M.N. Josselyn, A.J. Mehta, J.T. Morris, W.K. Nuttle, C.A. Simenstad, and D.J.P. Swift.
1994. Scientific assessment of coastal wetland loss, restoration and management in Louisiana.
Journal of Coastal Research Special issue 20:1-103.
Breiman, L., J. H. Freidman, and R. A. Olshen. 1984. Classification and Regression Trees. Wadsworth
and Brooks/Cole, Monterey, CA.
Burkett, V.R., D. A. Wilcox, R. Stottlemyer, W. Barrow, D. Fagre, J. Baron, J. Price, J.L. Nielsen, C.D.
Allen, D.L. Peterson, G. Ruggerone and T. Doyle. 2005. Nonlinear dynamics in ecosystem
response to climatic change: case studies and policy implications. Ecological Complexity 2: 357394.
Busby, J. R. 1991. BIOCLIM – a bioclimate analysis and prediction system. – In: Margules, C. R. and
Austin, M. P. (eds), Nature conservation: cost effective biological surveys and data analysis.
CSIRO, pp. 64–68.
Callaway, J. C. and M. N. Josselyn. 1992. The introduction and spread of smooth cordgrass (Spartina
alterniflora) in south San Francisco Bay. Estuaries. 15(2):218-226.
Callaway, J.C., J.A. Nyman, and R.D. DeLaune. 1996. Sediment accretion in coastal wetlands: A review
and a simulation model of processes. Current Topics in Wetland Biogeochemistry 2:2-23.
Carpenter, G., A. N. Gillson, and J. Winter. 1993. DOMAIN: a flexible modeling procedure for mapping
potential distributions of plants and animals. Biodiversity and Conservation:667-680.
Casanova, M. T. and M. A. Brock. 2000. How do depth, duration and frequency of flooding influence the
establishment of wetland plant communities? Plant Ecology 147:237-250.
Cayan, D., P. Bromirski, K. Hayhoe, M. Tyree, M. Dettinger, and R. Flick. 2005. Projecting Future Sea
Level. California Climate Change Center Report (CEC-500-2005-202-SD), December 2005.
16
Parker et al.
http://www.energy.ca.gov/2005publications/2005_pubs_alpha_order.html.
Chapman, V.J. 1974. Salt marshes and salt deserts of the world, 2nd Ed. J. Cramer, Berlin.
Cohen, A. N. and J. T. Carlton. 1998. Accelerating invasion rate in a highly invaded estuary. Science
279:555-558.
Colorado and Sacramento-San Joaquin River Basins. Journal of the American Water
Cronk, J. K. and M. S. Fennessy. 2001. Wetland Plants: biology and ecology. Lewis Publishers, Boca
Raton, FL.
Dettinger, M. D. 2005. From climate change spaghetti to climate-change distributions for 21st Century
California. San Francisco Estuary and Watershed Science 3(1) Article 4.
http://repositories.cdlib.org/jmie/sfews/vol3.iss1.art4
Dettinger, M. D., D. R. Cayan, M. K. Meyer and A. E. Jeton. 2004. Simulated hydrologic responses to
climate variations and change n the Merced, Carson, and American River basins, Sierra Nevada,
California, 1900-2099. Climatic Change 62:283-317.
Donnelly, J.P. and M.D. Bertness. 2001. Rapid shoreward encroachment of salt marsh cordgrass in
response to accelerated sea-level rise. Proc. Nat. Acad. Sci. (USA) 98: 14218-14223.
Dunne, J.A., R.J. Williams, and N.D. Martinez. 2002a. Network structure and biodiversity loss in food
webs: robustness increases with connectance. Ecology Letters 5:558-567.
Dunne, J.A., R.J. Williams, and N.D. Martinez. 2002b. Food-web structure and network theory: the role
of connectance and size. Proceedings of the National Academy of Sciences USA 99:1291712922.
Elith, J., C. H. Graham, R. P. Anderson, M. Dudik, S. Ferrier, A. Guisan, R. J. Hijmans, F. Huettmann, J.
R. Leathwick, A. Lehmann, J. Li, L. G. Lohmann, B. A. Loiselle, G. Manion, C. Moritz, M.
Nakamura, Y. Nakazawa, J. McC. M. Overton, A. Townsend Peterson, S. J. Phillips, K.
Richardson, R. Scachetti-Pereira, R. E. Schapire, J. Soberon, S. Williams, M. S. Wisz, and N. E.
Zimmermann. 2006. Novel methods improve prediction of species' distributions from occurrence
data. Ecography 29:129-151.
estuary. Science 231:567-573.
Evens, J., and G. W. Page. 1986. Predation on black rails during high tides in salt marshes. Condor
88:107-109.Flick, R. E. and D. R. Cayan. 1984. Extreme seas levels on the coast of California.
ASCE 19th Coastal Engineering Conference Proceedings. Houston, TX, pp. 886-897.
Flick, R.E. and D.R. Cayan. 1984. Extreme sea levels in San Diego, California: winter 1982-1983.
Coastal Engineering, pp 886-898.
Flynn, K. M., K. L. McKee, and I. A. Mendelssohn. 1995. Recovery of fresh-water marsh vegetation after
a saltwater intrusion event. Oecologia 103:63-72.
Folke, C. S. Carpenter, B. Walker, M. Scheffer, T. Elmqvist, L. Gunderson, and C.S. Holling. 2004.
Regime shifts, resilience and biodiversity in ecosystem management. Annual Review of Ecology
and Systematics 35:557-581.
Foxgrover, A. C., S. A. Higgins, M. K. Ingraca, B. E. Jaffe, and R. E. Smith. 2004. Deposition, erosion,
and bathymetric change in South San Francisco Bay: 1858-1983: U.S. Geological Survey OpenFile Report 2004-1192.25 p.
functioning. Conservation Biology 19:1019-1024.
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.
Gleick, P.H. 1987a. The development and testing of a water-balance model for climate impact
assessment: Modeling the Sacramento Basin. Water Resources Research 23:1049-1061.
Gleick, P.H. 1987b. Regional hydrologic consequences of increases in atmospheric carbon dioxide and
other trace gases. Climatic Change 10(2): 137-161.
Gleick, P.H. and E.L. Chalecki. 1999. The impacts of climatic changes for water recourses of the
Colorado and Sacramento-San Joaquin river basins. Journal of the American Water Resources
Association 35(6):1429-1441.
17
Parker et al.
Goals Project. 1999. Baylands ecosystem habitat goals: A report of habitat recommendations. U.S.
Environmental Protection Agency, San Francisco, CA.
Greenberg, R., and S. Droege. 1990. Adaptations to tidal marshes in breeding populations of the swamp
sparrow. Condor 92:393-404.
Greenberg, R.J. Maldonado, S. Droege, and M.V. McDonald. 2006. Tidal marshes: a global perspective
on the evolution and conservation of their terrestrial vertebrates. BioScience 56:675-685.
Grosse, W., H.B. Buchel, and H. Tiebel. 1991. Pressurized ventilation in wetland plants. Aquatic Botany
39:89-98.
Guisan, A., and N. E. Zimmermann. 2000. Predictive habitat distribution models in ecology. Ecological
Modelling 135:147-186.
Hastie, T. J., and R. J. Tibshirani. 1990. Generalized Additive Models. Chapman & Hall, London.
Hopkins, D. R. and V. T. Parker. 1984. A study of the seed bank of a salt marsh in northern San
Francisco Bay. Amer. J. Bot. 71:348-355.
Howard, R.J., and I.A. Mendelssohn. 1999. Salinity as a constraint on growth of oligohaline marsh
macrophytes. II. Salt pulses and recovery potential. American Journal of Botany 86:795-806.
Howard, R.J., and I.A. Mendelssohn. 2000. Structure and composition of oligohaline marsh plant
communities exposed to salinity pulses. Aquatic Botany 68:143-164.
Hughes, T. P., D. R. Bellwood, C. Folke, R. S. Steneck and J. Wilson. 2005. New paradigms for
supporting the resilience of marine ecosystems. Trends Ecol. Evol. 20:380-386.
immersion. Journal of Ecology 64:811-819.
Ingebritsen, S.E., M.E. Ikehara, D.L. Galloway, D.R. Jones. 2000. Delta subsidence in California: the
sinking heartof the state. U.S. Geological Survey FS-005-00. 4 p.
Inouye, D. W., B. Barr, K. B. Armitage, and B. D. Inouye. 2000. Climate change is affecting altitudinal
migrants and hibernating species. Proceedings of the National Academy of Sciences 97:16301633.
IPCC. 2001. Cimate Change 2001: Impacts, Adaptation and Vulnerability.
Iverson, L. R., and A. M. Prasad. 1998. Predicting abundance of 80 tree species following climate change
in the eastern United States. Ecological Monographs 68.
James, F. C., and N. O. Wamer. 1982. Relationships between temperate forest bird communities and
vegetation structure. Ecology 63:159-171.
Josselyn M. 1983. The ecology of San Francisco Bay tidal marshes: a community profile. Biological
Report FWS/OBS-83/23. U.S. Fish and Wildlife Service, Division of Biological Services,
Washington, DC.
Josselyn, M., and J. Callaway. 1988. Ecological Effects of Global Climate Change: Wetland Resources
of San Francisco Bay. Prepared for the Environmental Research Laboratory, U.S. Environmental
Protection Agency. Romberg Tiburon Center for Environmental Studies, Tiburon, CA. 39 p.
Journal of Ecology 64:793-809.
Kearney, M.S., and J.C. Stevenson. 1991. Island land loss and marsh vertical accretion rate evidence for
historical sea-level changes in Chesapeake Bay. Journal of Coastal Research 7:403-415.
Keddy, P. A. and T. H. Ellis. 19985. Seedling recruitment of 11 wetland plant species along a water level
gradient: Shared or distinct responses? Canadian Journal of Botany 63: 1876-1879.
Knowles, K., M. D. Dettinger, and D. R. Cayan. 2006. Trends in Snowfall versus Rainfall in the Western
United States. Journal of Climate 19:4545-4559.
Knowles, N. and D. Cayan. 2004. Elevational dependence of projected hydrologic changes in the San
Francisco Estuary and watershed: Climatic Change 62:319-336.
Knowles, N. and D.R. Cayan. 2002. Potential effects of global warming on the Sacramento/San Joaquin
watershed and the San Francisco estuary: Geophysical Research Letters 29:1-5.
Lawler, J. J., D. White, R. P. Neilson, and A. R. Blaustein. 2006. Predicting climate-induced range shifts:
model differences and model reliability. Global Change Biology 12:1568-1584.
Lawrence, A. J., and J. M. Soame. 2004. The effects of climate change on the reproduction of coastal
invertebrates. Ibis 146:29-39.
18
Parker et al.
Lettenmaier D.P. and T. Y. Gan. 1990. Hydrologic sensitivities of the Sacramento-San Joaquin
Lyons, K.G., C.A. Brigham, B.H. Traut, and M.W. Schwartz. 2005. Rare species and ecosystem
Mahall, B. E., and R. B. Park. 1976a. The ecotone between Spartina foliosa Trin. and Salicornia virginica
L. in salt marshes of northern San Francisco Bay: I. Biomass and production. Journal of Ecology
64:421-433.
Mahall, B.E., and R.B. Park. 1976b. The ecotone between Spartina foliosa Trin. and Salicornia
Mahall, B.E., and R.B. Park. 1976c. The ecotone between Spartina foliosa Trin. and Salicornia
McCullagh, P. and J. A. Neder. 1989. Generalized Liner Models. Chapman and Hall, London.
Mendelssohn, I.A., and J.T. Morris. 2000. Ecophysiological controls on the productivity of Spartina
alterniflora Loisel. In: Concepts and Controversies in Tidal Marsh Ecology. Eds. M.P. Weinstein
and D.A. Kreeger. pp 59-80.
Mendelssohn, I.A., K.L. McKee, and W.H. Patrick, Jr. 1981. Oxygen deficiency in Spartina alterniflora
roots: Metabolic adaptation to anoxia. Science 214:439-441.
Mitsch, W.J., and J.G. Gosselink. 2000. Wetlands, 3rd ed edition. John Wiley, New York, NY.
Morris, J.T., P.V. Sundareshwar, C.T. Nietch, B. Kjerfve, and D.R. Cahoon. 2002. Responses of coastal
wetlands to rising sea level. Ecology 83: 2869-2877.
Mount, J. and R. Twiss. 2005. Subsidence, sea level rise, and seismicity in the Sacramento-San Joaquin
Delta. San Francisco Estuary and Watershed Science 3(1):Article 5,
http://repositories.cdlib.org/jmie/sfews/vol3/iss1/art5.
Nichols, F. H., J. E. Cloern, S. N. Luoma, and D. H. Peterson. 1986. The modification of an
Odum, W. E. 1988. Comparative ecology of tidal fresh-water and salt marshes. Annual Review of
Ecology and Systematics 19:147-176.
Olofson, P. R., editor. 2000. Bayland ecosystem species and community profiles: Life histories and
environmental requirements of key plants, fish, and wildlife. San Francisco Bay Regional Water
Quality Control Board, Oakland, CA.
Orr, M., S. Crooks, and P. B. Williams. 2003. Will Restored Tidal Marshes Be Sustainable? San
Francisco Estuary and Watershed Science. 1:Article 5.
http://repositories.cdlib.org/jmie/sfews/vol1/iss1/art5.
Ostander, G. K., K. M. Armstrong, E.T. Knobbe, D. Gerace and E. P. Scully. 2000. Rapid transition in the
structure of a coral reef community: The effects of coral bleaching and physical disturbance.
Proc. Nat. Acad. Sci. (USA) 97: 5297-5302.
Overpeck, J.T., B.L. Otto-Bliesner, G.H. Miller, D.R. Muhs, R.B. Alley, and J.T. Kiehl. 2006.
Paleoclimatic evidence for future ice-sheet instability and rapid sea-level rise. Science 311:17471750.
Parmesan, C. 1996. Climate and species' range. Nature 382:765-766.
Patrick, W. H., Jr., and R. D. DeLaune. 1990. Subsidence, accretion, and sea level rise in south San
Francisco Bay marshes. Limnology and Oceanography 35:1389-1395.
Pearcy, R.W. and S.L. Ustin. 1984. Effects of salinity on growth and photosynthesis of three California
tidal marsh species. Oecologia 62: 68-73.
Pearson, R. G., and T. P. Dawson. 2003. Predicting the impacts of climate change on the distribution of
species: are bioclimate envelope models useful? Global Ecology and Biogeography 12:361-371.
Pearson, R. G., T. P. Dawson, P. M. Berry, and P. A. Harrison. 2002. SPECIES: A spatial evaluation of
climate impact on the envelope of species. Ecological Modelling 154:289-300.
Pennings, S.C., M-B Grant and M.D. Bertness. 2005. Plant zonation in low-latitude salt marshes:
disentangling the roles of flooding, salinity and competition. J. Ecol. 93: 159-167.
Peterson, A. T. 2001. Predicting species' geographic distributions based on ecological niche modeling.
Condor:599-605.
Phillips, S. J., R. P. Anderson, and R. E. Schapire. 2006. Maximum entropy modeling of species
geographic distributions. Ecological Applications 190:231-259.
19
Parker et al.
Porter, W. P., S. Budaraju, W. E. Stewart, and N. Ramankutty. 2000. Calculating climate effects on birds
and mammals: impacts on biodiversity, conservation, population parameters, and global
community structure. American Zoologist 40:597-630.
Ralph, C. J., G. R. Geupel, P. Pyle, T. E. Martin, and D. F. DeSante. 1993. Handbook of field methods for
monitoring landbirds. Gen. Tech. Rep., USDA Forest Service, Pacific Southwest Research
Station 144.
Rasse, D.P., G. Peresta and B. G. Drake. 2005. Seventeen years of elevated CO2 exposure in a
Chesapeake Bay wetland: sustained by contrasting responses of plant growth and CO2 uptake.
Global Change Biology 11: 369-377.
Reed, D.J. 1995. The response of coastal marshes to sea-level rise: Survival or submergence. Earth
Surface Processes and Landforms 20:39-48.
Rehfisch, M. M., G. E. Austin, S. N. Freeman, M. J. S. Armitage, and N. H. K. Burton. 2004. The
possible impact of climate change on the future distributions and numbers of waders on Britain's
non-estuarine coast. Ibis 146:70-81.
Resources Association 35(6): 1429-1441.
Rignot, E., and P. Kanagaratnam. 2006. Changes in the velocity structure of the Greenland ice sheet.
Science 311:986-990.
Ripley, B. D. 1996. Pattern recognition and neural networks. Cambridge University Press, Cambridge.
River basin, California, to global warming. Water Resour Res 26:69-86.
Roos, M. 1989. Possible climate change and its impact on water supply in California. Oceans ’89
Conference, Inst. Of Electr. And Electron. Eng., Seattle, WA.
Root, T. L., J. T. Price, K. R. Hall, S. H. Schneider, C. Rosenzweig, and A. Pounds. 2002. 'Fingerprints'
of global warming on wild animals and plants. Nature 421:57-59.
Rotenberry, J. T., and J. A. Wiens. 1980. Habitat structure, patchiness, and avian communities in North
American steppe vegetation: a multivariate analysis. Ecology 61:1228-1250.
San Francisco Estuary Project. 1991. Status and trends report on wetlands and related habitats in
Sanderson, E.W., S.L. Ustin, T.C. Foin. 2000. The influence of tidal channels on the distribution of salt
marsh plant species in Petaluma Marsh, CA, USA. Plant Ecology 146: 29-41.
Scavia, D., J.C. Field, D.F. Boesch, R.W. Buddemeier, V. Burkett, D.R. Cayan, M. Fogarty, M.A.
Harwell, R.W. Howarth, C. Mason, D.J. Reed, T.C. Royer, A.H. Sallenger, and J.G. Titus. 2002.
Climate Change Impacts on U.S. Coastal and Marine Ecosystems. Estuaries 25: 149-164.
Scheffer, M. and S.R. Carpenter. 2003. Catastrophic regime shifts in ecosystems: linking theory to
observation. Trends Ecol. Evol. 18: 648-656.
Scheffer, M., S. Carpenter, J.A. Foley, C. Folkes, and B. Walker. 2001. Catastrophic shifts in ecosystems.
Nature 413:591-596.
Seabloom, E. W., J. W. Williams, D. Slayback, D. M. Stoms, J. H. Viers, and A. P. Dobson. 2006.
Human impacts, plant invasion, and imperiled plant species in California. Ecological
Applications 16:1338–1350.
Shriver, W. G., T. P. Hodgman, J. P. Gibbs, and P. D. Vickery. 2004. Landscape context influences salt
marsh bird diversity and area requirements in New England. Biological Conservation 119:545553.
Simenstad, C., J. Toft, H. Higgins, J. Cordell, M. Orr, P. Williams, L. Grimaldo, Z. Hymanson, and D.
Reed. 2000. Sacramento/San Joaquin Delta Breached Levee Wetland Study (BREACH).
Unpulished report to CALFED. [URL: http://depts.washington.edu/calfed/breachii.htm]
Spautz, H., N. Nur, D. Stralberg, and Y. Chan. 2006. Multiple-scale habitat relationships of tidal marsh
breeding birds in the San Francisco Bay estuary. Environmental threats to tidal marsh vertebrates
of the San Francisco Estuary. Proceedings of the Vertebrates of Tidal Marshes Symposium,
October 24-26, 2002, Patuxent, MD. Studies in Avian Biology No. 32.
Stevenson, J.C., L.G. Ward, and M.S. Kearney. 1986. Vertical accretion in marshes with varying rates of
sea level rise. Pages 241-259 in D.A. Wolfe, editor. Estuarine variability. Academic Press, San
Diego, CA.
20
Parker et al.
the San Francisco Estuary : Public report. San Francisco Estuary Project, Oakland, Calif.
Thomson, D.M., G.P. Shaffer, and J.A. McCorquodale. 2001. A potential interaction between sea-level
rise and global warming: implications for coastal stability on the Mississippi River Deltaic Plain.
Global and Planetary Change 32:49-59.
Thuiller, W. 2004. Patterns and uncertainties of species' range shifts under climate change. Global
Change Biology 10:2020-2027.
Turner, R.E., E.M. Swenson, C.S. Milan, J.M. Lee and T.A. Oswald. 2004. Below-ground biomass in
healthy and impaired salt marshes. Ecological Research 19:29-35.
virginica L. in salt marshes of northern San Francisco Bay: II. Soil water and salinity.
virginica L. in salt marshes of northern San Francisco Bay: III. Soil aeration and tidal
Visser, JM., C.E. Sasser, R.H. Chabreck, and R.G. Linscombe. 2002. The impact of a severe drought on
the vegetation of a subtropical estuary. Estuaries 25:1184-1195.
Wang, F. C. 1988. Dynamics of saltwater intrusion in coastal channels. Journal of Geophysical Research
93:6937-6946.
Warren, R.W., and W.A. Niering. 1993. Vegetation change on a northeast tidal marsh: Interaction of sealevel rise and marsh accretion. Ecology 74:96-13.
Wiens, J. A., and J. T. Rotenberry. 1981. Habitat associations and community structure of birds in
shrubsteppe environments. Ecological Monographs 51:21-41.
Williams, P.B. 1989. The impacts of climate change on the salinity of San Francisco Bay. In: SmithJB,
Tirpak DA, editors. The potential effect of global climate change on the United States. Appendix
A, Water Resources. Prepared for the United States Environmental Protection Agency, Office of
Policy Planning and Evaluation. EPA-230-05-89-051. Washington DC: US EPA. p 3-1 to p 3-29.
Wintle, B., J. Elith, and J.M. Potts. 2005. Fauna habitat modelling and mapping: A review and case study
in the Lower Hunter Central Coast region of NSW. Austral Ecology 30:719-738.
Young, J.A., C.E. Turner, and L.F. James. 1995. Perennial pepperweed. Rangelands 17:121-123.
Zedler, J. B., J. C. Callaway, J. S. Desmond, G. Vivian-Smith, G. D. Williams, G. Sullivan, A. E.
Brewster, and B. K. Bradshaw. 1999. Californian salt marsh vegetation: An improved model of
spatial pattern. Ecosystems 2:19-35.
21