Content uploaded by James E. Cloern
Author content
All content in this area was uploaded by James E. Cloern on Apr 18, 2020
Content may be subject to copyright.
Available via license: CC BY 4.0
Content may be subject to copyright.
MANAGEMENT APPLICATIONS
Nutrient Status of San Francisco Bay and Its Management
Implications
James E. Cloern
1
&Tara S. Schraga
1
&Erica Nejad
1
&Charles Martin
1
Received: 4 June 2019 /Revised: 19 March 2020 /Accepted: 20 March 2020
#The Author(s) 2020
Abstract
Nutrient enrichment has degraded many of the world’s estuaries by amplifying algal production, leading to hypoxia/anoxia, loss
of vascular plants and fish/shellfish habitat, and expansion of harmful blooms (HABs). Policies to protect coastal waters from the
effects of nutrient enrichment require information to determine if a water body is impaired by nutrients and if regulatory actions
are required. We compiled information to inform these decisions for San Francisco Bay (SFB), an urban estuary where the best
path toward nutrient management is not yet clear. Our results show that SFB has high nutrient loadings, primarily from municipal
wastewater; there is potential for high algal production, but that production is not fully realized; and SFB is not impaired by
hypoxia or recurrent HABs. However, our assessment includes reasons for concern: nitrogen and phosphorus concentrations
higher than those in other estuaries impaired by nutrient pollution, chronic presences of multiple algal toxins, a recent increase of
primary production, and projected future hydroclimatic conditions that could increase the magnitude and frequency of algal
blooms. Policymakers thus face the challenge of determining the appropriate protective policy for SFB. We identify three crucial
next steps for meeting this challenge: (1) new research to determine if algal toxins can be reduced through nutrient management,
(2) establish management goals as numeric targets, and (3) determine the magnitude of nutrient load reduction required to meet
those targets. Our case study illustrates how scientific information can be acquired and communicated to inform policymakers
about the status of nutrient pollution, its risks, and strategies for minimizing those risks.
Keywords Estuary .Nutrients .Pollution .Eutrophication .Policy .Management .San Francisco Bay
Introduction
The world’s estuaries, bays, and lagoons, and in particular
those set in urban landscapes or agricultural watersheds, have
been enriched in nitrogen and phosphorus by human activi-
ties. Nutrient pollution has been judged the largest pollution
problem in US coastal rivers and bays (Howarth et al. 2002),
and it is a growing problem of global scale. Nutrient enrich-
ment alters coastal ecosystems through a suite of changes that
begin with increased algal production and biomass, leading to
increased ecosystem metabolism, turbidity, and occurrences
of harmful algal blooms, and decreases of oxygen, vascular
plants, biological diversity, and ecosystem goods and services
upon which we depend (Ferreira et al. 2011). Manifestations
of this eutrophication syndrome have been expressed along
many of the world’s coastlines, from the Baltic, Black, and
Seto Inland Seas to Tokyo, Chesapeake, and Moreton Bays,
and coastal waters of the Gulf of Mexico, North Sea, and
South China Sea (Boesch 2019).
Protection of estuarine-coastal ecosystems from the eutro-
phication syndrome has proven to be a difficult policy chal-
lenge, partly because of the diverse sources of nutrients deliv-
ered to coastal waters from urban and agricultural runoff, at-
mospheric deposition, and point sources such as municipal
wastewater treatment plants. A second challenge, learned
from many experiences of nutrient management, is that re-
sponses to enrichment vary across ecosystems and they
change over time. Thus, protective policies must be place-
based and adaptive. This requires that strategies of nutrient
management be grounded in information contained in obser-
vational data from long-term research and monitoring pro-
grams. In particular, policymakers ask of the scientific
Communicated by Mark J. Brush
*James E. Cloern
jecloern@usgs.gov
1
US Geological Survey, 345 Middlefield Rd, Menlo Park, CA 94025,
USA
Estuaries and Coasts
https://doi.org/10.1007/s12237-020-00737-w
community two essential questions: what is the nutrient status
of this estuary, and what does that status mean for developing
protective policies? Here we address these questions for San
Francisco Bay, a highly enriched estuary where the best path
toward nutrient management is not yet clear.
In “Part 1: Nutrient Status of San Francisco Bay,”we syn-
thesize different kinds of observational data to assess nutrient
status. There is no standard definition of “nutrient status,”and
we took a comprehensive view of the problem following cli-
mate scientists in their assessments of climate change and
policy responses to it. The Global Climate Observing
System was built around the concept of Essential Climate
Variables, defined as a set of variables “that critically contrib-
utes to the characterization of Earth’s climate”(Bojinski et al.
2014). We assessed the nutrient status of San Francisco Bay
by compiling a set of essential variables that critically contrib-
ute to the characterization of nutrient pollution in estuaries.
These include (1) the environmental setting, including indica-
tors of current water quality condition and factors thatregulate
conversion of nutrients into algal biomass, (2) identification of
nutrient sources and their input rates to the estuary, (3) nutrient
concentrations and forms in the estuary, (4) nutrient-based
indicators of the potential for algal biomass production and
the degree to which that potential is realized, and (5) budgets
to estimate the fates of externally derived nitrogen and phos-
phorus. These variables show that San Francisco Bay has high
nutrient loadings and concentrations, the primary source is
municipal wastewater, the primary forms are dissolved inor-
ganic N and P, there is potential for high algal production, that
production is not fully realized in today’s hydroclimatic set-
ting, but production has increased in recent decades.
In “Part 2: Management Implications and Actions,”we
discuss implications of this status assessment for resource
managers who face challenging decisions of when and how
to implement policies of nutrient control. First, we discuss
three reasons for concern about the nutrient status of San
Francisco Bay: (1) its nitrogen and phosphorus concentrations
exceed those in other estuaries impaired by the eutrophication
syndrome; (2) warning signs including presence of multiple
algal toxins, the trend of increased primary production, and
occurrences of large algal blooms during climate anomalies;
and (3) model-based projections of future hydroclimatic con-
ditions that could increase the magnitude and frequency of
phytoplankton blooms. These concerns have motivated next
steps toward a regulatory policy, including development of
water quality targets as numerical indicators of nutrient im-
pairment, and determination of the magnitude of nutrient load
reduction required to meet those targets.
Our purpose here is to use the San Francisco Bay case study
as an example of how scientific information can be acquired and
communicated to inform policymakers about the changing state
of nutrient pollution, the risks it poses, and scientifically ground-
ed strategies for minimizing those risks.
Study Design and Methods
The San Francisco Bay System
San Francisco Bay has been a focus of research by the US
Geological Survey (USGS) since 1969 to learn how estuaries
respond to hydroclimatic variability and human disturbances such
as nutrient enrichment. San Francisco Bay includes two connect-
ed, but very different, estuary types. North Bay, which includes
Suisun and San Pablo Bays (Fig. 1), is the estuary of California’s
two largest rivers, the Sacramento and San Joaquin. South Bay is
a marine lagoon situated in an urban landscape. Both of these
estuaries are connected to the seaward Central Bay, a deep basin
strongly influenced by water exchange with the coastal Pacific
Ocean (Raimonet and Cloern 2016). The North Bay salinity gra-
dient spans the range from fresh water to nearly full-strength sea
water, is displaced seaward ~ 40 km by large winter floods
(Cloern et al. 2017), and its freshwater source is runoff from
California’s agricultural Central Valley. The South Bay salinity
gradient is weaker, and its freshwater source is urban runoff and
effluent from municipal wastewater treatment plants. Water resi-
dence time varies seasonally from days to months in North Bay,
and from weeks to > 3 months in South Bay (Walters et al. 1985).
In analyses presented here, we consider the San Francisco Bay
system as a whole, without consideration of its large spatial var-
iability, to develop an overall assessment of its nutrient status.
Water Samples
Our sampling in recent years was designed to capture seasonal
and spatial variability of nitrogen and phosphorus concentra-
tions and to measure their partitioning into particulate, dis-
solved, inorganic, and organic components. We collected
512 near-surface water samples by pump on 100 dates be-
tween 18 November 2014 and 24 July 2019. Sampling was
monthly in North Bay and biweekly-monthly in South Bay
and Central Bay. Aliquots for analyses of dissolved inorganic
nitrogen (DIN), dissolved inorganic phosphorus (DIP), total
dissolved nitrogen (TDN), and total dissolved phosphorus
(TDP) were filtered with a syringe using 0.45-μmmembrane
filters. Particulate nitrogen (PN) was measured in particles
collected onto precombusted glass fiber (GF/F) filters.
Whole water samples were collected for Total Phosphorus
(TP) measurements and immediately acidified. All samples
were stored at −20 °C until analyzed by the USGS National
Water Quality Laboratory.
DIN and DIP were measured with an Aquakem 600 auto-
mated discrete analyzer using methods of Fishman and
Friedman (1989) for nitrite and phosphate, the method of
Patton and Kryskalla (2003) for nitrate, and the method of
Solorzano (1969) for ammonium with a salt correction factor
applied (Stewart and Elliott 1996). TDN was measured in
sample filtrates using an alkaline persulfate digestion method
Estuaries and Coasts
(Patton and Kryskalla 2003). TP was measured in acidified
whole-water samples and TDP was measured in filtrates, both
using US Environmental Protection Agency (USEPA) method
365.1 (O'Dell 1993). PN was measured using USEPA method
440.0 (Zimmermann et al. 1997).
Aliquots of each sample were also analyzed to measure
chlorophyll-a (in cells retained on GF/F filters) and suspended
particulate matter SPM (collected onto polycarbonate filters
having 0.4-μm pore size). Chlorophyll-a concentration (chl-a)
was measured fluorometrically using the acidification method
on a Turner 10AU or Turner Designs Trilogy fluorometer
calibrated with chlorophyll-a standard (Jeffrey et al. 1997;
Arar and Collins 1997). SPM concentration was measured
as dry-weight mass, with a correction for mass of salt retained
Fig. 1 Map of USGS sampling stations in San Francisco Bay. All
components of N and P (dissolved, particulate, organic, inorganic) were
measured in Lower South Bay (station 36), South Bay (stations 32, 27,
22), Central Bay (station 18), and North Bay (stations 13, 6). Dissolved
inorganic N and P were also measured at stations 30, 24, 15, 9, 3.
Chlorophyll-a, salinity, dissolved oxygen, and suspended particulate
matter were measured at all stations
Estuaries and Coasts
in filters (Hager 1993). Salinity and temperature were mea-
sured using a Sea-Bird Electronics SBE-9plus CTD with an
SBE-4C conductivity sensor and SBE-3plus temperature sen-
sor. Dissolved oxygen (DO) was measured with a Sea-Bird
Electronics SBE-43 oxygen sensor. Detailed methods for each
analysis are described by Schraga and Cloern (2017). Data are
accessible from the USGS Science Base repository (Cloern
and Schraga 2016; Schraga et al. 2020).
Computed Quantities
Nutrient analyses included direct measurements of ammoni-
um (NH
4
), nitrate+nitrite (NO
32
), TDN, PN, DIP, TDP, and
TP. From these, we computed: DIN as NO
32
+NH
4
,totalN
(TN) as PN + TDN, dissolved organic N (DON) as TDN −
DIN, particulate P (PP) as TP −TDP, and dissolved organic P
(DOP) as TDP −DIP.
From November 2014 to May 2016, TN was measured
directly using the method of Patton and Kryskalla (2003)
and PN was computed as the difference between measured
TN and TDN. However, some computed PN values were neg-
ative. After May 2016, PN was measured directly and TN
computed as the sum of PN + TDN as above. We only report
PN and TN based on this approach.
We estimated the components of particulate N and P asso-
ciated with suspended sediments and phytoplankton biomass
using multiple linear regressions of PN (μM N) and PP (μM
P) as functions of SPM (mg l
−1
) and chl-a (μgl
−1
):
PN ¼2:70 þ0:101 SPM þ0:677 chl−a
PN ¼0:32 þ0:025 SPM þ0:031 chl−a
adjusted R2¼0:85
adjusted R2¼0:69
From these regressions, we estimated the concentrations of
nitrogen (N
sed
,N
phyt
) and phosphorus (P
sed
,P
phyt
)boundto
sediments and in phytoplankton biomass:
Nsed ¼0:101 SPM
Nphyt ¼0:677 chl−a
Psed ¼0:025 SPM
Pphyt ¼0:031 chl−a
Regression coefficients show that a gram of sediment in
surface waters of San Francisco Bay contains, on average,
1.4 mg N and 0.78 mg P. Intercepts of the regression equations
represent mean concentrations of particulate nitrogen
(PN
other
=2.70 μM) and phosphorus (PP
other
=0.32 μM) as-
sociated with other particles such as free-living bacteria and
microzooplankton.
Cross-Ecosystem Comparisons
As a frame of reference for interpreting nutrient concentra-
tions and chemical forms in San Francisco Bay, we compared
our measurements against similar measurements made in
Chesapeake Bay. Data were accessed 9 July 2018 from
websites of the Chesapeake Bay Program (http://data.
chesapeakebay.net/WaterQuality). We aggregated
Chesapeake Bay data collected January 2013 through
December 2017 in surface waters at 6 sites (2.1, 3.3C, 4.3C,
5.2, 6.1, 7.4) distributed along the estuarine salinity gradient.
Part 1: Nutrient Status of San Francisco Bay
There is no standard method for assessing the nutrient status of
estuaries. We took a comprehensive view and built an assess-
ment of nutrient status that has five components. Each com-
ponent was grounded in data, and each provides a different
perspective for understanding the degree of nutrient enrich-
ment in this estuary and its meaning for regulatory protection
of water and habitat quality. Our assessment begins with a
description of the estuarine setting of San Francisco Bay as
summaries of water quality metrics that define the ecosystem
as habitat for phytoplankton production. Second, we describe
the sources and rates of externally supplied N and P to San
Francisco Bay and place those loadings in a global perspec-
tive. Third, we synthesize measurements of nutrient concen-
trations and chemical forms in the estuary and give meaning to
those measurements by comparing them with measurements
in Chesapeake Bay as an example of an estuary degraded by
nutrient enrichment. Fourth, we develop indicators of N and P
availability in San Francisco Bay relative to phytoplankton
growth requirements and their potential for biomass accumu-
lation. Finally, we construct a nutrient budget for San
Francisco Bay as a foundation for understanding the fate of
nutrients delivered externally, and for developing policies to
protect its water quality from the harmful consequences of
nutrient enrichment.
The Estuarine Setting
Water samples were collected along the salinity gradients of
North and South Bay. Hydrologic conditions varied seasonal-
ly between high-flow winters and low-flow summers and in-
cluded extremes of low inflow during 2014 and 2015 (during
thedriestperiodonrecord)andhighinflowduring2016and
2017 (the wettest period on record). Surface salinity in those
samples ranged from 0.1 to 33.5, and the median was 25.9
(Fig. 2). Therefore, most samples were collected in estuarine
waters having a larger fraction of seawater than fresh water.
This reflects the saline character of South, Central, and San
Pablo Bays that contain 94% of the water volume in this
estuarine system (Jassby et al. 1993). Most of the 134 salinity
measurements less than 20 (Fig. 2) represented sampling
along the landward reaches of the North Bay salinity gradient.
Others represented events of high runoff from storms during
winter and spring of 2016 and 2017.
Estuaries and Coasts
San Francisco Bay is a turbid estuary, and that turbidity is
derived primarily from large sediment inputs from its urban
watershed and the Sacramento-San Joaquin Rivers
(Schoellhamer 2011). The fine-grained sediments are
suspended by bottom stresses from wind waves and tidal cur-
rents (Schoellhamer 1996), and their concentrations are highly
variable seasonally and along the salinity gradients (Cloern
et al. 2017). In this study, surface SPM concentrations ranged
from 2 to 703 mg l
−1
(Fig. 2). The median SPM was 19 and the
mean 39 mg l
−1
. This difference between median and mean
reflects events of extremely high surface SPM, exceeding
400 mg l
−1
in Lower South Bay and 100 mg l
−1
in South
Bay, during storms and high-energy spring tides.
We measured surface chl-a as an index of phytoplankton
biomass in the photic zone. Chl-a concentration ranged be-
tween 1 and 52 μgl
−1
; the median was 4.0 and the mean
was 5.2 μgl
−1
(Fig. 2). This difference was primarily attrib-
uted to spring blooms (chl-a > 10 μgl
−1
) in South Bay and
larger spring blooms (chl-a > 25 μgl
−1
) in Lower South Bay.
Blooms in this estuary are events of biomass production by
large cells, particularly diatoms (Cloern 2017).
Dissolved oxygen concentrations in bottom waters ranged
from 3.6 to 10.6 mg l
−1
; the mean and median were 7.5 and
7.4 mg l
−1
, respectively (Fig. 2). Twenty-two samples had
bottom DO < 6 mg l
−1
. Eighteen of these occurred in the
Lower South Bay during warm months, and the other 4 in
Central Bay. The Lower South Bay is enriched in organic matter,
including phytoplankton biomass produced in its shallow
sloughs and ponds (Thebault et al. 2008), so lowest oxygen
concentrations in this region are attributed partly to its high me-
tabolism (MacVean et al. 2018). Low-DO events in Central Bay
are associated with intrusions of recently upwelled deep ocean
water (Cloern et al. 2017) and therefore are unrelated to anthro-
pogenic nutrient enrichment.
These results show that the environmental setting of San
Francisco Bay includes a wide range of estuarine environ-
ments along its two salinity gradients. Phytoplankton bio-
mass (chl-a) is low relative to some other estuaries (Cloern
and Jassby 2008). Exceptions occur as (usually short-
lived) blooms. The estuary has high SPM concentrations,
and light limitation of growth by sediment-derived turbid-
ity constrains phytoplankton production (Cole and Cloern
1987). Bottom waters are usually well oxygenated (Fig.
2)−only 1 of 507 measured concentrations was less than
the state’sWaterQualityDOCriterionof5mgl
−1
(Sutula
et al. 2017). Therefore, deep waters of San Francisco Bay
do not have the seasonal anoxia or hypoxia characteristic
of many nutrient-enriched estuaries. Tidal sloughs draining
Fig. 2 Distributions of surface salinity, SPM, and chl-a and bottom DO measured along the salinity gradients of San Francisco Bay fromNovember 2014
through July 2019. Note log scales in distributions of SPM and chl-a
Estuaries and Coasts
into Lower South Bay do experience DO < 5 mg l
−1
,par-
ticularly in summer, and this may create localized zones of
reduced habitat quality for some fish species (MacVean
et al. 2018).
External Sources of N and P
San Francisco Bay receives nutrient inputs from three key
anthropogenic sources: effluent discharge from 42 publicly
owned treatment works (POTWs) and 6 refineries; storm wa-
ter runoff from the surrounding urban watershed; and outflow
from the Sacramento-San Joaquin Delta that includes nutri-
ents from agricultural runoff and from the Sacramento
Regional Wastewater Treatment Facility (SRWTF).
Historical data are not available to quantify inputs of total N
or P, but Novick and Senn (2014) compiled inputs of dis-
solved inorganic N and P. Mean daily loadings, based primar-
ily on measurements from 2006 to 2014, were 73.8 (metric)
tons of DIN and 6.3 tons of DIP (Table 1). The largest source
is POTWs, contributing 62% of both DIN and DIP input from
cumulativedischarge of 500 million gallons of treated effluent
per day. Storm water contributes 15% of DIN and 21% of DIP
input (Table 1), and nutrient input from Delta outflow includes
large fractions of DIN and DIP from the SRWTF (Hager and
Schemel 1992). Therefore, San Francisco Bay is enriched in N
and P because of its urban setting.
The inputs listed in Table 1are incomplete measures of
total nutrient loadings because they do not include particulate
or organic forms of N or P. We can estimate these components
of wastewater because DIN and DIP account for 89% of TN
and 78% of TP, respectively (Novick and Senn 2014). This
implies daily loadings of 82.9 t of N and 8.1 t of P from all
measured sources (Table 1). No information is available for
assessing organic or particulate inputs from refineries or urban
runoff, or for assessing nutrient inputs from atmospheric de-
position or groundwater. However, we can conclude from the
available measurements that daily inputs to San Francisco Bay
exceed 82.9 t of nitrogen and 8.1 t of phosphorus.
We place these loadings in a global context by comparing
them against N and P inputs to other estuaries. The area of San
Francisco Bay at mean tide level is 4.4 × 10
8
m
2
(Jassby et al.
1993), so areal loadings from Table 1are >
69 g TN m
−2
year
−1
and > 6.7 g TP m
−2
year
−1
. These values
place San Francisco Bay in the 87th percentile of N loadings
compiled from 163 estuaries, and in the 91st percentile of P
loading across a range of estuarine-coastal ecosystem types.
By global standards, then, San Francisco Bay has very high
external inputs of both nitrogen and phosphorus. Its areal
loading rates exceed those in many estuaries and bays where
water and habitat quality have been degraded by nutrient en-
richment, such as the Neuse River Estuary, Long Island
Sound, Chesapeake Bay, Venice Lagoon, and the Odense
fjord (Fig. 3).
Nutrient Concentrations and Chemical Forms
The third component of our assessment includes measure-
ments of total nitrogen and phosphorus concentrations, and
their partitioning into organic, inorganic, particulate, and dis-
solved forms. The long history of nutrient measurements in
San Francisco Bay has focused almost exclusively on the dis-
solved inorganic components. Here, we include recent mea-
surements of the other components to give a more complete
assessment of the sizes and biological availability of the N and
P stocks in surface waters. We also estimated the fractions of
those stocks assimilated into phytoplankton biomass and the
remaining fractions available to support additional biomass
production.
Frequency distributions (Fig. 4) show the variability of
total N and P and their individual components captured in
seasonal and spatial sampling from November 2014 through
July 2019. Total nutrient concentrations ranged from 18.1 to
218 μM TN and from 1.4 to 35.5 μM TP. The dissolved
inorganic forms ranged from 1.3 to 151 μM DIN (most as
nitrate) and from 1.0 to 28.8 μM DIP. The distribution of
TN was skewed toward very high values, with 49 measure-
ments exceeding 100 μM(Fig.4). These were all from sam-
ples collected in Lower South Bay. The distributions of TP
and DIP were bimodal (Fig. 4), reflecting higher phosphorus
concentrations in South Bay than in North Bay (Conomos
et al. 1979).
We used the means of these measurements as indicators of
the nutrient status of the entire San Francisco Bay system.
These indicators show that, on average, 82% of the nitrogen
in surface waters was in a dissolved form, 59% as DIN and
23% as DON (Fig. 5). Most (77%) of the phosphorus was also
Table 1 Mean daily inputs of DIN and DIP to San Francisco Bay, based
on compilations of measured (POTWs, refineries, Delta outflow) and
modeled (storm water) loadings from measurements between 2006 and
2014 (Novick and Senn 2014). The bottom row compares DIN/DIP ratios
of the four sources and their loading-weighted mean. The last column
adds estimates of wastewater inputs of organic and particulate N and P
42 POTWs 6 Refineries Storm water Delta Total DIN, DIP Total TN, TP
N Input (t day
−1
) 45.8 1 10.8 16.2 73.8 > 82.9
P Input (t day
−1
) 3.9 0.1 1.3 1 6.3 > 8.1
DIN:DIP (mol/mol) 26 22 18 36 26
Estuaries and Coasts
in dissolved form, primarily as DIP (70%). On average, the
fractions of total N and P contained in phytoplankton biomass
were small, only 7% and 3%, respectively. The fractions of
total N and P associated with suspended sediments averaged
5% and 13%, respectively. A few samples deviated substan-
tially from these means during phytoplankton blooms or
events of sediment resuspension. The phytoplankton compo-
nents reached maximum values of N
phyt
= 35.3 μM N and
P
phyt
=1.6 μM P during the largest bloom (chl-a =
52.2 μgl
−1
). The sediment component reached a maximum
N
sed
=71.0μMNandP
sed
=17.6μM P in the sample having
highest SPM concentration (703 mg l
−1
).
These results support three conclusions about the nutrient
status of San Francisco Bay. First, N and P concentrations in
surface waters are high and mostly in dissolved forms that
could be converted into phytoplankton biomass but are not,
except during short-lived bloom events. Second, historical
measurements of only dissolved inorganic forms have
under-estimated total N and P by 41% and 30%, respectively.
Some of the other components, in particular DON (mean
16.2 μM) and PP (mean 1.5 μM), are accessible to phyto-
plankton (e.g., Bronk et al. 2007; Ellison and Brett 2006)
and therefore can support biomass growth to levels beyond
those set by the availability of DIN or DIP alone. Finally, the
extreme values of chl-a (highest), bottom DO (lowest), SPM
(highest), TN and TP (highest) all occurred in Lower South
Bay. This small region receives discharge from one of the
largest wastewater treatment plants, is connected to shallow
high-productivity ponds, and its water exchange with larger
South Bay is restricted by a topographic constriction (Fig. 1).
Therefore, the nutrient status of Lower South Bay is distinct
from that of the entire Bay system that we assess here.
By themselves, the numbers presented here may convey
little information to policymakers responsible for managing
nutrient pollution and its effects. As one context for under-
standing the nutrient status of San Francisco Bay, we com-
pared its meanconcentrations and forms of N and P with mean
measurements made in surface waters along the salinity
Fig. 3 Log 10 of annual areal
loadings of N and P to estuaries
and bays around the world,
ranked from lowest to highest. N
loadings are inputs of either DIN,
TDN, or TN. P loadings are TP.
Loadings to San Francisco Bay
are underestimates of TN and TP
inputs because they do not
include organic or particulate
inputs from refineries, urban
runoff, or atmospheric deposition.
Loadings to other estuaries were
obtained from previously
published compilations
(Dettmann 2001; McGlathery
et al. 2007;Josefsonand
Rasmussen 2000; Boynton et al.
1996; Moorman et al. 2014)
Estuaries and Coasts
gradient of Chesapeake Bay. Total and total dissolved N and P
all have higher mean concentrations in San Francisco Bay
than in Chesapeake Bay (Table 2). Mean NO
32
is about dou-
ble, NH
4
is more than five times higher, TP is more than six
times higher, and DIP is 26 times higher than in Chesapeake
Bay (Table 2). The nutrient status of Chesapeake Bay provides
a useful context because it is a high-profile example of an
estuary impaired by nutrient enrichment through its elevation
of primary productivity and chl-a, leading to decreased water
transparency, loss of seagrasses, increased system metabolism
and areal extent of hypoxia (Kemp et al. 2005). San Francisco
Bay has higher N and especially higher P concentrations, so
its potential for these kinds of water-quality impairments ex-
ceeds that of Chesapeake Bay.
Indicators of Nutrient Enrichment
Nutrient enrichment has important implications for phytoplank-
ton production and biomass accumulation. We used three indi-
cators based on nutrient measurements to assess (1) the potential
for biomass production in San Francisco Bay, (2) the degree to
which that potential is currently realized, and (3) the availability
of N and P relative to phytoplankton requirements.
Nutrient Limitation Index The rates of phytoplankton nutrient
uptake and growth follow the hyperbolic Michaelis-Menten
function that is shaped by the half-saturation constant K,the
nutrient concentration where uptake or growth rate is half
maximal. Characteristic values for marine diatoms are K
N
=
1.6 μM for DIN uptake and K
P
= 0.24 μM for DIP uptake
(Sarthou et al. 2005). From these, we computed indices of
nutrient limitation as the percentage of maximal uptake rate
supported by measured DIN and DIP concentrations:
Nlimit ¼100 DIN=DIN þ1:6ðÞ
Plimit ¼100 DIP=DIP þ0:24ðÞ
These are conservative estimates of maximum growth rate
because they do not include dissolved organic or sediment-
associated components as additional sources of N and P to
support phytoplankton growth. The mean values from 2014
to 2019 measurements were N
limit
=95% and P
limit
=94%
(Table 2). For comparison, mean indices in Chesapeake Bay
were N
limit
= 60% and P
limit
= 33% (Table 2). Thus, phyto-
plankton growth in Chesapeake Bay is more frequently limit-
ed by low DIN, and especially low DIP, than in San Francisco
Bay. Therefore, one consequence of large DIN and DIP inputs
to San Francisco Bay is that N and P concentrations are usu-
ally high enough to support near-maximal uptake and growth
rates. Thus, enrichment at this level creates a potential for high
biomass production and accumulation.
Fig. 4 Distributions offour different components of the nitrogen and phosphorus stocks measured along the salinity gradients of San Francisco Bay from
November 2014 through July 2019. Note log scales of all x-axes
Estuaries and Coasts
Nutrient Utilization Efficiency We computed a second index to
measure the degree to which this potential for high biomass
production is realized in San Francisco Bay. The index follows
Monbet (1992), who compared chl-a and DIN relationships as an
index of nutrient utilization efficiency across 40 estuarine-coastal
ecosystems. We used chl-a/DIN as an index of the ratio of phy-
toplankton biomass to the stock of DIN available to produce
additional biomass. Similarly, we used chl-a/DIP as an index of
P utilization efficiency. Large values indicate high ecosystem
efficiency at converting dissolved inorganic nutrients into phyto-
plankton biomass. Mean ratios chl-a/DIN and chl-a/DIP were 0.1
and 1.0, respectively, in San Francisco Bay compared to 0.6 and
53.4 in Chesapeake Bay (Table 2).Basedonthisindex,the
Chesapeake Bay system is 6 and 53 times more efficient at
transforming inorganic N and P stocks into phytoplankton bio-
mass. The lower mean efficiencies of N and P utilization in San
Francisco Bay show that its nutrient-based potential for high
biomass production is usually not realized. Exceptions occur
during the largest spring blooms when most or all of the DIN
pool is converted into biomass (Cloern 1996).
Nutrient Stoichiometry Lastly, we used N/P ratios in San
Francisco Bay to identify the nutrient element that could limit
phytoplankton growth if utilization efficiency increased. A
common approach (e.g., Boynton et al. 2008)istocompare
N/P ratios against the Redfield ratio (16 mol N per mole of P),
an index of the relative N and P requirements of phytoplank-
ton. There is no standard approach for the nutrient forms used
to compare against the Redfield ratio, so we used three: DIN/
DIP, TDN/TDP, and TN/TP. There also is not universal agree-
ment that 16 is the best representation of phytoplankton nutri-
ent stoichiometry because N/P ratios of phytoplankton in cul-
ture are highly variable and have a mean of 10 (Geider and La
Roche 2002). None of the three N/P ratios measured in San
Francisco Bay had mean values exceeding 16 (Table 2). Based
on the Redfield benchmark, this indicates that N is less avail-
able than P relative to phytoplankton requirements. However,
the mean DIN/DIP in San Francisco Bay was 8.7 (Table 2),
close to the mean N/P ratio of marine phytoplankton in cul-
ture. Therefore, our conclusions about the most-limiting nu-
trient vary depending on the threshold N/P ratio assumed.
Additional uncertainty arises in the interpretation of N/P ratios
in San Francisco Bay because the range across all 3 indices
(0.7 to 64.9) spans far below and far above the threshold N:P
ratios of either 10 or 16 (Table 2). This large seasonal and
spatial variability of N/P ratios is one reason why estuarine
scientists recommend reduction of both N and P loadings to
remediate nutrient-impaired coastal waters (Paerl et al. 2016;
Conley et al. 2009).
Where Does All This N and P Go?
Nutrients delivered to estuaries can have three fates: accumu-
lation, export, or loss to internal processes. Few of these pro-
cesses have been measured directly, but we synthesized the
available information to construct budgets and estimate the
fate of the > 80 t of N and > 8 t of P delivered daily to San
Francisco Bay.
Accumulation in Bay Waters We first consider accumulation
because annual nutrient budgets are often built from an
assumption that inputs and losses are balanced—i.e., there
is no accumulation over an annual cycle (e.g., Dettmann
2001). We used bay-wide mean concentrations of DIN
and DIP over the period 2009–2018 (the most recent com-
plete decade of measurements) to determine if dissolved
inorganic N or P are accumulating in San Francisco Bay.
For each year, we computed mean DIN and DIP in each
region, then calculated bay-wide means from regional
mean concentrations weighted by the volume of each re-
gion (from Table 1; Smith and Hollibaugh (2006)). The
Mann Kendall trend test (Rpackage wql; Jassby and
Cloern (2016)) on these annualized series showed that
trends were small, −0.20 μMDINyear
−1
and 0.03 μM
Fig. 5 Pie charts showing the overall mean partitioning of N and P into
five components, based on surface samples collected along the salinity
gradients of San Francisco Bay from November 2014 through July 2019.
DIN and DIP = dissolved inorganic N and P; DON and DOP = dissolved
organic N and P; N
phyt
and P
phyt
= the mean phytoplankton component
estimated from regression slopes of PN and PP on chl-a; N
sed
and P
sed
=
the mean sediment-bound component estimated from regression slopes of
PN and PP on SPM; N
resid
and P
resid
are residual components of TN and
TP not associated with the other four components
Estuaries and Coasts
DIP year
−1
, and not significantly different from zero (P=
0.60 and 0.86, respectively). Therefore, stocks of dis-
solved inorganic nutrients have not accumulated in the
estuary over the past decade. This test also showed no
significant trends of annualized bay-wide mean chl-a
(−0.08 μgl
−1
year
−1
,P= 0.11) or SPM concentration
(0.27mgl
−1
year
−1
,P= 0.48). These results imply no
accumulation of nutrients associated with phytoplankton
(N
phyt
) or suspended sediments (N
sed
) over the past de-
cade. The observational record is too short to determine
if dissolved organic N or P have changed over the past
decade, but the available data indicate that N and P are
not accumulating in San Francisco Bay waters (Table 3).
Therefore, nutrient inputs to the Bay appear to be bal-
anced by internal losses and export.
Internal Losses Particle sinking and burial can be an important
loss of N and P in depositional regions of estuaries (e.g., Boynton
et al. 1995;Eyreetal.2016).SanFranciscoBayhashadan
exceptional history of alternating eras of sediment accretion and
erosion, but it is now in an era of sediment loss. This has been
learned from comparisons of bathymetric surveys to measure
changes in morphometry and, thus, sediment gain or loss between
different eras (e.g., Jaffe et al. 1998). These studies show that San
Table 2 Summary statistics of the different forms of N and P measured
in surface waters of San Francisco Bay from November 2014 through
July 2019. Included for comparison are means of comparable
measurements made along the salinity gradient of Chesapeake Bay
(CB) from 2013 through 2017. Also shown are indicators of nutrient
limitation, utilization efficiency, and stoichiometry
Nutrient form Method Number of
measurements
Minimum
(μM)
Maximum
(μM)
Mean
(μM)
Mean
CB
TN = total N Computed: PN + TDN 369 18.1 217.8 63.3 47.0
PN =particulate N USEPA Method 440.0 (Zimmermann
et al. 1997)
369 1.7 97.1 10.6 12.4
TDN = total dissolved N Patton and Kryskalla (2003) 510 8.6 196 53.8 34.8
DON = dissolved organic N Computed: TDN −NO
32
−NH
4
498 0.1 85.7 16.2 18.2
NO
32
= nitrate+nitrite Fishman and Friedman (1989) 511 0.8 136 31.5 15.6
NH
4
= ammonium Solorzano (1969); Stewart and Elliott
(1996)
510 0.3 22.8 6.9 1.3
N
phyt
= N in phytoplankton Computed: 0.677 × chl-a 511 0.7 35.3 3.5 6.7
N
spm
= N on suspended
sediments
Computed: 0.101 × SPM 511 0.2 71.0 3.9 0.5
TP =total P USEPA Method 365.1 (O'Dell 1993) 511 1.4 35.5 6.6 1.0
PP = particulate P Computed: TP −TDP 480 0.0 22.4 1.5 0.4
TDP = total dissolved P Patton and Kryskalla (2003) 511 0.9 29.3 5.3 0.4
DOP = dissolved organic P Computed: TDP −DIP 330 0.0 6.6 0.4 0.2
DIP = dissolved inorganic P Fishman and Friedman (1989) 511 1.0 28.8 5.2 0.2
P
phyt
= P in phytoplankton Computed: 0.031 × chl-a 511 0.0 1.6 0.2 0.2
P
spm
= P on suspended
sediments
Computed: 0.025 × SPM 511 0.1 17.6 1.0 0.3
Nutrient limitation index (% maximum uptake rate)
N
limit
Computed: DIN/(DIN + 1.6) 511 45% 99% 95% 60%
P
limit
Computed: DIP/(DIP + 0.24) 511 81% 99% 94% 33%
Nutrient utilization efficiency
Nitrogen Computed: mean chlorophyll-a /mean
DIN
510 0.1 0.6
Phosphorus Computed: mean chlorophyll-a /mean DIP 510 1.0 53.4
Nutrient stoichiometry
Inorganic Computed: DIN/DIP 511 0.7 25.8 8.7
Dissolved Computed: TDN/TDP 509 2.2 64.9 12.5
Total Computed: TN/TP 369 2.0 36.8 11.6
Estuarine environment
Salinity 507 0.1 33.5 23.2 13.6
Chlorophyll-a (μgl
−1
) 510 1.0 52.2 5.2 9.8
SPM (mg l
−1
) 511 2.0 703 39.0 7.8
Estuaries and Coasts
Francisco Bay system has lost 7 × 10
6
m
3
year
−1
of sediment in
recent decades as a consequence of reduced sediment supply and
increased dredging and export to the ocean and wetlands. On this
basis, we infer that N and P are not currently being lost to burial in
San Francisco Bay, although nutrients must have accumulated in
sediments during earlier periods of deposition.
Denitrification is a second important loss of N from estu-
aries, but rates have not been measured in San Francisco Bay.
However, Smith and Hollibaugh (2006) used measurements
of flow, salinity, and nutrients to infer rates of biogeochemical
transformations in North and South Bay. Differences between
modeled and measured changes in DIN were interpreted as
rates of net denitrification, i.e. the difference between N fixa-
tion and denitrification. The median calculated rate of net
denitrification was 1757 × 10
3
mol N day
−1
(Table 9 in
Smith and Hollibaugh (2006)). If this areal rate applies also
to Central Bay, then net denitrification across the entire San
Francisco Bay system is estimated as 38.7 t N day
−1
(Table 3).
Loss to Export Lastly, we consider nutrient losses to the Pacific
Ocean using a range of measurement types. Martin et al.
(2007) directly measured Bay-ocean fluxes of phytoplankton
biomass during three seasons using cross-sectional profiling
of currents and chl-a concentrations at the Golden Gate. Net
export over complete tidal cycles ranged from 7718 mg chl-a
s
−1
(out of San Francisco Bay) during spring to −1285 mg
chl-a s
−1
(into San Francisco Bay) during the summer upwell-
ing season. From these, and our measured PN/chl-a and PP/
chl-a ratios (Table 2), we computed N
phyt
and P
phyt
exports
ranging from −6.3 to + 1.1 t N day
−1
,and−0.6to+
0.1 t P day
−1
,respectively(Table3). Although the measure-
ments are limited in number, they provide evidence that bay-
ocean water exchange can be an important process of both
exporting and importing N and P contained in phytoplankton
biomass. We estimated export of sediment-associated N and P
from a sediment budget (Schoellhamer et al. 2005) built from
measured inputs to San Francisco Bay and changes in storage
from the bathymetric surveys cited above. The sediment bud-
get for a normal water year indicated loss of 2.4 × 10
6
tof
sediment per year. We multiplied this sediment loss by the
ratios of PN/SPM and PP/SPM derived from our data
(Table 2) to compute daily export losses of 9.3 t N
sed
and
5.1 t P
sed
(Table 3).
Another process of nutrient export could be loss of biomass
to harvest or emigration of fish or shellfish. Large-scale com-
mercial fishing and aquaculture in San Francisco Bay ended
decades ago, so we presume this process of nutrient export is
unimportant now. However, San Francisco Bay is a spawning
habitat for marine fishes and rearing habitat for early-stage
fish and crustaceans that mature in the Bay and then
emigrate to the Pacific Ocean. Export of nutrients by fish
migration is rarely measured in estuaries, but Deegan (1993)
demonstrated that this process can be of comparable magni-
tude to nutrient export by water exchange. Her study focused
on Gulf menhaden (Brevoortia patronus) that immigrates into
estuaries as larvae and emigrates to coastal waters as juveniles.
Emigration of menhaden from Fourleague Bay LA exported
3.1 g N m
−2
year
−1
and0.9gPm
−2
year
−1
. These areal rates,
applied to San Francisco Bay, would export 3.7 t of N and
1.1 t of P per day. We included these values in Table 3simply
as placeholders to recognize that biotic transport could be an
important, but unmeasured, process of nutrient export from
San Francisco Bay. The actual losses could be larger, given
the high abundances and multiple species of marine fish and
crustaceans that grow in San Francisco Bay and emigrate to
the coastal ocean, such as Crangon shrimp, Dungeness crab
(Cancer magister),andEnglishsole(Parophrys vetulus)
(Raimonet and Cloern 2016).
Nutrient Budgets The process rates compiled here provide the
first estimates of nitrogen and phosphorus budgets for San
Francisco Bay. Most terms were derived indirectly and all
have large uncertainty, but one important conclusion is
grounded in a rigorous data set: DIN and DIP have not accu-
mulated over the past decade, so their inputs must be balanced
by internal losses and exports. The current era of sediment loss
sets San Francisco Bay apart from many other estuaries, such
as Chesapeake Bay and its tributary estuaries where sediment
deposition of PN buries 28–53% of total nitrogen inputs and
PP deposition buries over 100% of total phosphorus inputs
(Boynton et al. 1995). The well-documented net erosion of
Table 3 Estimated daily N and P budget terms for San Francisco Bay.
Values in italics are from direct measurements. Negative exports are
transport into San Francisco Bay
Nitrogen Tons N day
−1
Phosphorus Tons P day
−1
Input
1
>82.9 Input
1
>8.1
DIN accumulation
2
0.0 DIP accumulation
2
0.0
N
phyt
accumulation
2
0.0 P
phyt
accumulation
2
0.0
N
sed
accumulation
2
0.0 P
sed
accumulation
2
0.0
Denitrification
3
38.7
N
phyt
export
4
−6.3 to 1.1 P
phyt
export
4
−0.6 to 0.1
N
sed
export
5
9.3 P
sed
export
5
5.1
N
fish
emigration
6
>3.7 P
fish
emigration
6
>1.1
Export DIN+DON
7
> 30.1 Export DIP+DOP
7
>1.8
1
Estimated from Novick and Senn (2014): 89% of TN input is DIN; 78%
of TP input is DIP
2
Based on Baywide trends of DIN, DIP, chl-a and SPM over the decade
2009–2018
3
From Smith and Hollibaugh (2006)
4
From Martin et al. (2007); positive fluxes are exports to the ocean
5
From the sediment budget of a normal water year (Schoellhamer et al.
2005)
6
From Deegan (1993)
7
Residual = input minus maximum value of summed loss terms
Estuaries and Coasts
sediments in San Francisco Bay implies that nutrient burial is
not an important internal loss process from this estuary now.
However, losses of sediment to the coastal ocean and dredging
imply that export of sediment-bound nutrients is an important
component of the N, and particularly the P, budget (Table 3).
The P budget has no internal losses, so phosphorus inputs and
exports are balanced. Phosphorus exports include, in descend-
ing order, P
sed
and DIP+DOP export by bay-ocean mixing,
and export of P in biota. The two important loss terms in the N
budget are denitrification and DIN+DON export. The large
uncertainties of these two processes preclude assessment of
their relative importance. Export of sediment-bound N ac-
counts for a loss of about 10% of N input, and losses to biotic
emigration could be of similar magnitude.
Recycling The budget above is a static accounting of in-
puts and outputs, but it provides little information about
the cycling of nutrients once they enter San Francisco
Bay. Nitrogen and phosphorus are reactive, essential ele-
ments of life, and their dissolved inorganic forms are
rapidly assimilated into microbial biomass. We estimated
the mass of N and P assimilated by microalgae from their
bay-wide net primary productivity of 1.75 ×
10
8
t C year
−1
(Jassby et al. 1993). The molar ratios
C/N/P in microalgae are variable, but mean ratios of phy-
toplankton grown in nutrient-rich cultures are C/N = 7.7
and C/P = 75 (Geider and La Roche 2002). Therefore,
this bay-wide carbon fixation rate implies that microalgae
assimilate 73 t of N and 16.5 t of P per day, equal to
100% of the daily DIN input and 260% of DIP input
(Table 1). About 70% of microalgal production is con-
tributed by phytoplankton (Jassby et al. 1993), so this
community plays a central role in nutrient cycling by
transforming DIN and DIP into algal biomass. That bio-
mass does not accumulate in the estuary (Table 3)be-
cause it is rapidly consumed and metabolized, releasing
organic forms of N and P. While phytoplankton assimila-
tion has no net effect on the annual N or P budgets of
San Francisco Bay, it is a key entry point into a biotic
recycling system in which nutrients are assimilated and
metabolized multiple times (Boynton et al. 2008). This
recycling system, which also includes potentially large
uptake by heterotrophic bacteria (Kirchman 1994), does
have a net effect on the composition of nitrogen com-
pounds by transforming DIN into particulate and organic
forms. This is evidenced by the smaller ratio of DIN:TN
in San Francisco Bay (mean 61%, Table 2) compared to
that in wastewater inputs to San Francisco Bay of 89%
(Novick and Senn 2014).
Part 2: Management Implications and Actions
The information contained in our assessment of nutrient status
has raised concern about nutrient enrichment of San Francisco
Bay to a level that did not exist a decade ago. Here, we present
the rationale for this growing concern, and then describe re-
sponses to it by the management and scientific communities.
Three Reasons for Concern
Risks of Nutrient Enrichment In the early 1980s, Scott Nixon
and his colleagues used mesocosm experiments to learn how
Narragansett Bay might respond to elevated rates of nitrogen
loading. Results showed that a 32-fold increase in N loading
led to increases of mean chl-a from 2 to 18 μgl
−1
and annual
primary production from 80 to 320 g C m
−2
(Nixon et al.
2001). This now-classic experiment was among the first to
measure estuarine phytoplankton responses to nutrient enrich-
ment. Comparisons across many estuarine-coastal ecosystems
have since established strong associations between phyto-
plankton biomass (chl-a) and TN and TP concentrations
(Smith 2006). At some levels, the increased phytoplankton
production from nutrient enrichment generates responses we
would judge as positive, including amplified production of
species we harvest for food (Nixon and Buckley 2002).
However, production of harvestable species begins to de-
crease after nutrient supplies reach a critical loading rate
(e.g., Josefson and Rasmussen 2000). Once that threshold is
exceeded, a syndrome of responses follows that we judge as
negative. The syndrome includes elevated rates of ecosystem
metabolism and oxygen consumption (Caffrey 2004).
The link between nutrient enrichment and ecosystem me-
tabolism underlies the expansion of hypoxia and anoxic dead
zones across the world’s coastal zones (Diaz and Rosenberg
2008). Hypoxia is a physiological stress to fish and shellfish
and constricts their habitat; anoxia leads to fish kills (Paerl
et al. 1998), and loss of oxygen has feedback effects on the
eutrophication syndrome by suppressing nitrification-
denitrification and releasing sediment-bound phosphate
(Kemp et al. 2009). Elevated metabolism leads to increased
CO
2
production and acidification as another threat to shellfish
and finfish (Wallace et al. 2014). Other manifestations of nu-
trient enrichment include loss of eelgrasses (Hauxwell et al.
2003) and saltmarshes (Deegan et al. 2012), and promotion of
harmful algal blooms with growing economic costs and risks
to health of humans, fish, and sea birds (Anderson 2009). As a
consequence of these broad-ranging disturbances by nutrient
enrichment, coastal eutrophication is an environmental prob-
lem of global significance.
By world standards, San Francisco Bay has high nutri-
ent loadings (Fig. 3) and high concentrations of nitrogen
and phosphorus (Table 2), primarily from municipal
wastewater. Nutrient enrichment at this level sets the
Estuaries and Coasts
potential for degradation of water and habitat quality that
has occurred in other US estuaries and coastal waters such
as Chesapeake Bay (Kemp et al. 2005), Long Island
Sound (O'Shea and Brosnan 2000), Neuse River Estuary
(Paerl et al. 1998), Elkhorn Slough (Hughes et al. 2011),
Tampa Bay in the 1970s (Greening et al. 2014), and the
Mississippi River plume in the Gulf of Mexico (Rabalais
et al. 2002).
Potential Warning Signs Although San Francisco Bay has not
been degraded by the hypoxia/anoxia that develops in these
other enriched estuaries, signals of nutrient-enrichment effects
are present in our observational records. Although the open
waters of San Francisco Bay are well oxygenated (Table 2),
tidal sloughs and ponds connected to the Lower South Bay
produce high phytoplankton biomass (chl-a > 50 μgl
−1
)and
have diel cycles of dissolved oxygen that oscillate between
near-anoxia and supersaturation (Thebault et al. 2008).
Second, although San Francisco Bay does not have recurrent
high-biomass algal blooms, events of extremely high biomass
accumulation have developed over large regions of the bay.
Spring blooms in 1998 reached chl-a concentrations exceed-
ing 100 μgl
−1
from Lower South Bay to San Pablo Bay. This
was a strong El Niño year of high runoff and unusually per-
sistent salinity stratification, illustrating one mechanism
through which hydroclimatic variability regulates the efficien-
cy of biomass production. Our sampling also captured a large-
scale red tide event in 2004 when surface chl-a concentrations
in South and Central Bay exceeded 100 μgl
−1
(Cloern et al.
2005). That bloom occurred when thermal stratification was
set up by a heat wave when an anomalous high-pressure sys-
tem developed along the US west coast. That bloom was
dominated by species that develop harmful algal blooms
(HABs) in other estuaries—Akashiwo sanguinea,
Heterocapsa rotundata, and Prorocentrum micans (Cloern
et al. 2005) These examples illustrate that the high potential
for biomass production in San Francisco Bay can be fully
realized under some hydroclimatic conditions.
More recent observations provide further evidence of water
quality changes that might be tied to nutrient enrichment.
Visible HABs are not regular occurrences in San Francisco
Bay, but its phytoplankton community includes three toxin-
producing taxa: the domoic-acid producing diatom Pseudo-
nitzschia, saxitoxin-producing dinoflagellate Alexandrium
sp., and okadaic-acid producing dinoflagellate Dinophysis
sp. (Sutula et al. 2017). These three toxins co-occur in
San Francisco Bay along with microcystins produced by
the freshwater cyanobacteria Microcystis (Peacock et al.
2018). All four toxins have been found in water and in
California mussels (Mytilus californianus)growninSan
Francisco Bay, with microcystins detected in 56%,
domoic acid in 98%, paralytic shellfish toxins (including
saxitoxin) in 59%, and Dinophysis shellfish toxins in 71%
of samples. The unexpected co-occurrence of four classes
of toxins produced by both marine and freshwater taxa
leaves an open question about their cumulative effects as
risks to the health of San Francisco Bay biota and human
consumers.
Nutrient Management in a Changing World Over the past
three decades, several regional and national programs
have been implemented to reverse the effects of nutrient
pollution by reducing N and P inputs to estuarine-coastal
ecosystems. Some have been successful, and perhaps the
most notable US example is recovery of Tampa Bay from
the severe ecosystem disturbances manifested in the
1970s (Greening et al. 2014). More commonly, however,
outcomes of nutrient reductions have differed from the
expectation that estuaries will re-trace their trajectories
of impairment and return to a pre-enrichment state.
Duarte et al. (2009) examined chl-a records in four
estuarine-coastal ecosystems that had early (1970s–
1980s) trends of significant nutrient increase followed
by trends of significant nutrient decrease after regulatory
controls were enacted. In each case, annual mean chl-a
was higher at the end of the record than at the beginning,
and the chl-a trajectories during the era of nutrient reduc-
tion were complex, convoluted departures from expecta-
tions. The authors attributed these unexpected responses
to “shifting baselines”—i.e., concurrent changes in envi-
ronmental factors that regulate conversion of nutrients in-
to biomass, such as changes in food web structures and
climate. A subsequent study (Carstensen et al. 2011)
found highly variable phytoplankton-nutrient relation-
ships across 28 coastal ecosystems, and that the produc-
tion of phytoplankton biomass per unit nitrogen nearly
doubled over the past 3–4 decades across all regions.
This is compelling evidence that the efficiency of phyto-
plankton nutrient utilization can change over periods of
decades in synchrony with global changes such as in-
creasing temperature and CO
2
concentrations, overfishing,
and harvest of filter feeders (Carstensen et al. 2011).
Our observations captured a baseline shift in San Francisco
Bay after 2000, when summer (June–September) chl-a con-
centrations began to increase in South Bay (Fig. 6). This chl-a
increase was attributed to loss of bivalves and their filter-
feeding control of phytoplankton biomass when biological
communities were restructured following a 1999 shift in cli-
mate forcing of the Northeast Pacific (Cloern et al. 2010). The
Pettit change-point test (wql function pett) identified a signif-
icant (P<10
−5
) change in the summer chl-a series after 2000.
The size effect of this change (median of all differences be-
tween 1978–2000 and 2001–2018 measurements) was
3.2 μgl
−1
. A chl-a shift of this magnitude implies two impor-
tant changes: (1) increased efficiency of N and P utilization
(Fig. 6); and (2) increased primary production that, since
Estuaries and Coasts
2000, has twice exceed 300 g C m
−2
year
−1
,signalingapos-
sible transition from a mesotrophic to a eutrophic estuary
(Nixon 1995). This example of a baseline shift illustrates the
dynamic nature of estuarine ecosystems where processes reg-
ulating algal production can change, sometimes abruptly and
unexpectedly.
Responses to Concern about Nutrient Enrichment
Regulatory Responses The development of hypoxia in periph-
eral habitats, increase of summer chl-a after 2000, presence of
HAB-forming phytoplankton taxa, and multiple algal toxins
in biota, have generated concern that San Francisco Bay has
reached a tipping point of nutrient impairment. If this is the
case, advanced wastewater treatment may now be required to
remove N and P from POTW effluents, as it has in other
estuaries. As a response to this concern, the San Francisco
Bay Regional Water Quality Control Board issued an interim,
5-year discharge permit to 37 POTWs. This permit “sets forth
a regional framework to facilitate collaboration on studies that
will inform future management decisions and regulatory strat-
egies”(BACWA 2018). The permit includes provisions to: (1)
evaluate the processes required and their costs to reduce nu-
trient discharges through upgrades of wastewater treatment;
and (2) support targeted studies to better understand potential
and realized effects of nutrient enrichment so that water qual-
ity objectives can be established for San Francisco Bay.
The first task has been completed by the Bay Area Clean
Water Agencies (BACWA), a joint powers agency
representing the dischargers. Its evaluation compared the costs
of treatment upgrades at two levels: one based on optimization
of conventional treatments that would remove 57% of TN and
59% of TP in effluents, and a second that would include new
processes (e.g., denitrification, coagulation) to remove 82%
and 88% of effluent TN and TP, respectively. The current cost
estimates of these upgrades are US $9.4 billion for the first
level, and US $12.4 billion for the higher level of nutrient
removal (BACWA 2018). These costs are substantial, and
Fig. 6 Changes from 1978 to
2018 in the median values of
summer (June–September)
surface chl-a, N utilization
efficiency, and P utilization
efficiency measured from stations
21 to 32 (Fig. 1)
Estuaries and Coasts
they motivated the second provision of targeted studies that
was realized through creation of a Nutrient Management
Strategy (NMS)—a multi-stakeholder collaboration charged
with developing a “coherent nutrient science and management
strategy for the Bay”(https://sfbaynutrients.sfei.org/).
Responses of the Scientific Community Based on our assess-
ment of the nutrient status of San Francisco Bay, policymakers
now ask for guidance as they face the essential question: What
is the appropriate protective policy for this estuary? Targeted
research, funded by the dischargers and directed by the NMS,
is in process or planned to address three challenges common
to all nutrient management programs:
1. Numeric targets: Regulatory policies to protect coastal
waters from the eutrophication syndrome are implemented
using targets expressed as numerical indicators of the direct
effects of nutrient enrichment such as increased algal produc-
tion or biomass, and indirect effects such as loss of oxygen or
biological diversity (e.g., Ferreira et al. 2011). Establishment
of numeric targets was a key to success for the Tampa Bay
Estuary Program in reversing the effects of nutrient enrich-
ment (Greening et al. 2014). Numeric targets have not yet
been established to guide nutrient management of San
Francisco Bay. As a first step, Sutula et al. (2017) analyzed
two decades of observational data to determine if chl-a can be
used as one indicator of adverse effects of nutrient enrichment
in San Francisco Bay, as it has in many other estuaries.
Regression analyses showed positive relationships between
chl-a concentration and: (1) abundances of toxigenic phyto-
plankton taxa (Alexandrium,Dinophysis,Karlodinium,
Pseudo-nitzschia), and (2) concentrations of algal toxins.
Conditional probability analysis identified a chl-a limit of
13 μgl
−1
as a “protective”threshold below which probabili-
ties are small for exceeding alert levels of algal abundances or
toxins. They also found lowest summer DO concentrations in
years of highest seasonal-mean (February–September) chl-a,
and identified a seasonal-mean chl-a concentration of 13–
16 μgl
−1
as a limit beyond which the state’s Water Quality
Criterion for DO might not be met. These targets were devel-
oped to identify chl-a levels that “constitute tipping points of
phytoplankton biomass beyond which water quality will be-
come degraded, requiring significant nutrient reductions”
(Sutula et al. 2017).
In today’s hydroclimatic setting, seasonal-mean chl-a con-
centrations in San Francisco Bay are usually less than the
proposed target of 13 μgl
−1
, even though the nutrient-based
potential for biomass accumulation is much higher. However,
as we have learned from studies of other estuaries, phyto-
plankton production efficiency can change over time. A crit-
ical uncertainty is long-term persistence of the physical attri-
butes of San Francisco Bay that constrain production
efficiency—turbulent mixing that breaks down stratification,
and high turbidity that limits light availability. Intermittent
stratification is a key feature that sets San Francisco Bay apart
from Chesapeake Bay where stratification and hypoxia persist
during summer (Kemp et al. 2005). Therefore, policymakers
ask if there are plausible scenarios of altered freshwater inputs,
warming of the surface layer, and rising water level such that
regions of San Francisco Bay could become stratified long
enough to promote large blooms and for bottom waters to lose
their oxygen content. These scenarios can be developed from
California’s Fourth Climate Change Assessment (Ackerly
et al. 2018) and its projections of: regional warming of up to
2.4 °C by mid-century; more frequent, larger magnitude and
longer duration heat waves (up to 40 more extreme heat days
per year by 2050); increased magnitude of high precipitation
events; and sea level rise potentially reaching 3 m by 2100.
Equally important is the future trajectory of water clarity that
has increased over recent decades because of altered wind
patterns and reduced sediment supplies to the estuary (Bever
et al. 2018). Several 3D models of hydrodynamics and sedi-
ment transport have been calibrated and validated for San
Francisco Bay (e.g., Elmilady et al. 2018; Bever and
MacWilliams 2013).These kinds of physical models can be
coupled with nutrient-phytoplankton models to assess the
likelihood that chl-a levels will regularly exceed numeric tar-
gets in a future climate. These scenarios can also provide
policymakers a basis for deciding if regulatory policies should
be adapted to current or to future hydroclimatic conditions.
2. Nutrients and algal toxins: A second key uncertainty is
the strength of coupling between nutrient enrichment and algal
toxins in San Francisco Bay. We know with certainty that the
phytoplankton community includes species that form HABs
elsewhere, and that multiple algal toxins are measured at
levels that pose health risks to estuarine biota and humans
(Peacock et al. 2018). However, there is uncertainty about
the extent to which nutrient reductions can reduce these
HAB risks in San Francisco Bay. This uncertainty arises in
part from the connections of San Francisco Bay to (1) an
inland delta and urban reservoirs that have recurrent
Microcystis blooms and high concentrations of microcystin
(Lehman et al. 2013), and (2) a coastal upwelling system that
develops Pseudo-nitzschia blooms that have led to fisheries
closures and mortalities of seabirds and marine mammals in
the coastal Pacific (McCabe et al. 2016).
Deeper understanding of the nutrient-HAB linkage and
its potential for management will require investments in
new research directions to answer fundamental questions.
Are HAB-forming diatoms and dinoflagellates and their
toxins produced primarily in San Francisco Bay, or in the
coastal ocean and transported into San Francisco Bay? Is
the export of N and P from San Francisco Bay an important
source of nutrients supporting HABs in the adjacent coastal
Pacific, as it is in the nearshore Southern California Bight
(Howard et al. 2014)? What roles do nutrients play in reg-
ulating toxin production? What environmental factors
Estuaries and Coasts
trigger population growth and toxin synthesis of HAB
taxa? What is the source of microcystin and its pathway
for movement into the Bay? Will reductions of microcystin
require active nutrient management of surrounding inland
waters, while reductions of marine algal toxins require re-
duction of wastewater nutrient inputs to the Bay? The glob-
al HAB community has recently provided guidance about
research approaches for answering these kinds of questions
(Wells et al. 2019). The stakes are high because if the
chronic presence of algal toxins in San Francisco Bay is a
consequence of nutrient enrichment, then this would be
compelling evidence of current impairment and a need for
regulatory actions to reduce nutrient loadings.
3. Toward a nutrient management plan: A third common
challenge of nutrient management is to determine the magni-
tude of nutrient load reduction required to meet numeric tar-
gets, such as chl-a thresholds. Loading goals are usually de-
veloped using models that range from simple to complex. The
management target for Chesapeake Bay is a 43% reduction of
both N and P loading from 1985 levels (Boesch 2019), and
these targets were set using simulations with a coupled
airshed-watershed-estuarine model (Linker et al. 2013).
Nutrient management of San Francisco Bay will require a
similar model to project water-quality and ecological re-
sponses to different levels of N and P load reduction. These
projections are best viewed as a starting place because re-
sponses to nutrient load reduction often deviate, sometimes
substantially, from the model projections used to set loading
targets. Realized responses to nutrient reduction have “vari-
ously been effective, ineffective, recalcitrant and sometimes
surprising”(Boesch 2019). Ineffective, recalcitrant and sur-
prising responses to action plans imply that strategies of nu-
trient management require adaptability (e.g., changing tar-
gets), patience (over decades), and ongoing monitoring to
capture and understand surprises as they unfold.
The intergovernmental commitments to reduce nutrient
inputs to Chesapeake Bay have been sustained for over
35 years, with measured progress toward nutrient reduc-
tions but slower progress toward the rehabilitation goals.
The slow pace of progress, relative to expectations, reflects
the complexity of the coastal eutrophication problem. One
example of complexity arises from the large stocks of ni-
trogen and phosphorus that have accumulated over decades
in bottom sediments. This “internal source”of nutrients can
continue to fuel phytoplankton production as external nu-
trient loadings are reduced, leading to lagged (recalcitrant)
responses to regulatory actions. Our measurements of the N
and P content of sediments in San Francisco Bay (1.4 mg N
and0.78mgPg
−1
sediment) allow us to estimate the size of
those stocks. Assuming that the active sediment layer is 15-
cm deep (Davis 2004) and sediment density is 2.7 g cm
−3
(Fuller et al. 1999), these nutrient/sediment ratios imply
stocks of 2.5 × 10
5
tofNand1.4×10
5
t P in the bottom
sediments of San Francisco Bay. These are equivalent to
8.4 years of today’s external N loading and 4.7 years of P
loading. Additional stocks of N and P are contained in the
sediment pore waters. Coupled water-column sediment
models that account for these internal sources can project
rates of DIN and DIP decrease after nutrient reductions
begin. For example, model simulations by Soetaert and
Middelburg (2009) indicate that a 50% reduction of exter-
nal N loading can ultimately reduce DIN concentrations by
more than 50%, but the process develops over a period of
1–2 decades as the internal source is gradually depleted.
Models can be useful for setting targets, but also for judg-
ing the time scale over which those targets can be met.
The learning experiences from successes and failures at
managing nutrient pollution along world’s coastlines provide
a collective wisdom about how to solve this complex and
challenging problem. In his review of those experiences,
Boesch (2019) encapsulates that wisdom as guidance for re-
source managers of San Francisco Bay and other coastal eco-
systems: “Outcomes must be measured and strategies appro-
priately adjusted through: sustained monitoring of essential
indicators and processes, the use of multiple models, truly
adaptive management, and cautious interventions within the
coastal ecosystem. The changing climate must be taken into
account by reassessing achievable future conditions and seek-
ing alternatives for mitigating and adapting to climate change
that also reduce nutrient loads.”
Acknowledgments Any use of trade, firm, or product names in this pub-
lication is for descriptive purposes only and does not imply endorsement
by the US Government. This research was supported by the USGS Water
Mission Area, USGS Ecosystems Mission Area, and the Regional
Monitoring Program of the San Francisco Estuary Institute. We appreci-
ate the thoughtful comments and suggestions from reviewers that
strengthened this paper.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing, adap-
tation, distribution and reproduction in any medium or format, as long as
you give appropriate credit to the original author(s) and the source, pro-
vide a link to the Creative Commons licence, and indicate if changes were
made. The images or other third party material in this article are included
in the article's Creative Commons licence, unless indicated otherwise in a
credit line to the material. If material is not included in the article's
Creative Commons licence and your intended use is not permitted by
statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this
licence, visit http://creativecommons.org/licenses/by/4.0/.
References
Ackerly, D., A. Jones, M. Stacey, and B. Riordan. 2018. Francisco Bay
Area summary report. California’s Fourth Climate Change
Assessment. Publication number: CCCA4-SUM-2018-005.
Available at https://www.energy.ca.gov/sites/default/files/2019-07/
Estuaries and Coasts
Reg%20Report-%20SUM-CCCA4-2018-005%
20SanFranciscoBayArea.pdf. Accessed 26 March 2020.
Anderson, D.M. 2009. Approaches to monitoring, control and manage-
ment of harmful algal blooms (HABs). Ocean & Coastal
Management 52 (7): 342. https://doi.org/10.1016/j.ocecoaman.
2009.04.006.
Arar, E.,and G. Collins. 1997. In-vitro determination of chlorophyll a and
pheophytin a in marine and freshwater algae by fluorescence. US
Environmental Protection Agency, Method EPA 445: 1–23.
BACWA. 2018. Potential nutrient reduction by treatment optimization,
sidestream treatment, treatment upgrades, and other means. Bay
Area Clean Water Agencies Final Report June 22, 2018. Available
at https://bacwa.org/wp-content/uploads/2018/06/BACWA_Final_
Nutrient_Reduction_Report.pdf. Accessed 26 March 2020.
Bever, AJ., and M.L. MacWilliams. 2013. Simulating sediment transport
processes in San Pablo Bay using coupled hydrodynamic, wave, and
sediment transport models. Marine Geology 345: 235–253. https://
doi.org/10.1016/j.margeo.2013.06.012.
Bever, A.J., M.L. MacWilliams, and D.K. Fullerton. 2018. Influence of
an observed decadal decline in wind speed on turbidity in the San
Francisco Estuary. Estuaries and Coasts 41 (7):1943-1967. https://
doi.org/10.1007/s12237-018-0403-x
Boesch, D.F. 2019. Barriers and bridges in abating coastal eutrophication.
Frontiers in Marine Science 6. https://doi.org/10.3389/fmars.2019.
00123.
Bojinski, S., M.Verstraete, T.C. Peterson, C. Richter, A. Simmons, and M.
Zemp. 2014. The concept of essential climate variables in support of
climate research, applications, and policy. Bulletin of the American
Meteorological Society 95 (9): 1431–1443. https://doi.org/10.1175/
bams-d-13-00047.1.
Boynton, W.R., J.H. Garber, R. Summers, and W.M. Kemp. 1995. Inputs,
transformations, and transport of nitrogen and phosphorus in
Chesapeake Bay and selected tributaries. Estuaries 18 (1B): 285–
314.
Boynton, W.R., L. Murray, J.D. Hagy, C. Stokes, and W.M. Kemp.1996.
A comparative analysis of eutrophication patterns in a temperate
coastal lagoon. Estuaries 19 (2): 408–421.
Boynton, W.R., J.D. Hagy, J.C. Cornwell, W.M. Kemp, S.M. Greene,
M.S. Owens, J.E. Baker, and R.K. Larsen. 2008. Nutrient budgets
and management actions in the Patuxent River Estuary, Maryland.
Estuaries and Coasts 31 (4): 623–651. https://doi.org/10.1007/
s12237-008-9052-9.
Bronk, D.A., J.H. See, P. Bradley, and L. Killberg. 2007. DON as a source
of bioavailable nitrogen for phytoplankton. Biogeosciences 4(3):
283–296.
Caffrey, J.M. 2004. Factors controlling net ecosystem metabolism in US
estuaries. Estuaries 27 (1): 90–101.
Carstensen, J., M. Sanchez-Camacho, C.M. Duarte, D. Krause-Jensen,
and N. Marba. 2011. Connecting the dots: Responses of coastal
ecosystems to changing nutrient concentrations. Environmental
Science & Technology 45 (21): 9122–9132. https://doi.org/10.
1021/es202351y.
Cloern, J.E. 1996. Phytoplankton bloom dynamics in coastal ecosystems:
A review with some general lessons from sustained investigation of
San Francisco Bay, California. Reviews of Geophysics 34 (2): 127–
168.
Cloern, James E. 2017. Why large cells dominate estuarine phytoplank-
ton. Limnology and Oceanography 62 (S1): S392–S409. https://doi.
org/10.1002/lno.10749.
Cloern, J.E., and A.D. Jassby. 2008. Complex seasonal patterns of pri-
mary producers at the land-sea interface. Ecology Letters 11 (12):
1294–1303. https://doi.org/10.1111/j.1461-0248.2008.01244.x.
Cloern, J.E., and T.S. Schraga. 2016. USGS measurements of water qual-
ity in San Francisco Bay (CA), 1969-2015: U. S. Geological Survey
data release, https://doi.org/10.5066/F7TQ5ZPR.
Cloern, J.E., T.S. Schraga, C.B. Lopez, N. Knowles, R.G. Labiosa, and R.
Dugdale. 2005. Climate anomalies generate an exceptional dinofla-
gellate bloom in San Francisco Bay. Geophysical Research Letters
32 (14). https://doi.org/10.1029/2005GL023321.
Cloern, J.E., K.A. Hieb, T. Jacobson, B. Sanso, E. Di Lorenzo, M.T.
Stacey, J.L. Largier, et al. 2010. Biological communities in San
Francisco Bay track large-scale climate forcing over the North
Pacific. Geophysical Research Letters 37: L21602. https://doi.org/
10.1029/2010GL044774.
Cloern, James E., Alan D. Jassby, Tara S. Schraga, Erica Nejad, and
Charles Martin. 2017. Ecosystem variability along the estuarine sa-
linity gradient: Examples from long-term study of San Francisco
Bay. Limnology and Oceanography 62: S272–S291. https://doi.
org/10.1002/lno.10537.
Cole, B.E., and J.E. Cloern. 1987. An empirical model for estimating
phytoplankton productivity in estuaries. Marine Ecology-Progress
Series 36 (3): 299–305.
Conley, D.J., H.W. Paerl, R.W. Howarth, D.F. Boesch, S.P. Seitzinger,
K.E. Havens, C. Lancelot, and G.E. Likens. 2009. Controlling eu-
trophication: Nitrogen and phosphorus. Science 323 (5917): 1014–
1015. https://doi.org/10.1126/science.1167755.
Conomos, T.J., R.E. Smith, D.H. Peterson, S.W. Hager, and L.E.
Schemel. 1979. Processes affecting seasonal distributions of water
properties in the San Francisco Bay estuarine system. In San
Francisco Bay: The urbanized estuary, ed. T.J. Conomos, 115–
142. San Francisco: Pacific Division of the American Association
for the Advancement of Science.
Davis, J.A. 2004. The long-term fate of polychlorinated biphenyls in San
Francisco Bay (USA). Environmental Toxicology and Chemistry 23
(10): 2396–2409. https://doi.org/10.1897/03-373.
Deegan, L.A. 1993. Nutrient and energy transport between estuaries and
coastal marine ecosystems by fish migration. Canadian Journal of
Fisheries and Aquatic Sciences 50 (1): 74–79.
Deegan, L.A., D.S. Johnson, R.S. Warren, B.J. Peterson, J.W. Fleeger, S.
Fagherazzi, and W.M. Wollheim. 2012. Coastal eutrophication as a
driver of salt marsh loss. Nature 490 (7420): 388–392. https://doi.
org/10.1038/nature11533.
Dettmann, E.H. 2001. Effect of water residence time on annual export and
denitrification of nitrogen in estuaries: A model analysis. Estuaries
24: 481–490.
Diaz, R.J., and R. Rosenberg. 2008. Spreading dead zones and conse-
quences for marine ecosystems. Science 321 (5891): 926–929.
Duarte, Carlos M., Daniel J. Conley, Jacob Carstensen, and María
Sánchez-Camacho. 2009. Return to Neverland: Shifting baselines
affect eutrophication restoration targets. Estuaries and Coasts 32
(1): 29–36. https://doi.org/10.1007/s12237-008-9111-2.
Ellison, M.E., and M.T. Brett. 2006. Particulate phosphorus bioavailabil-
ity as a function of stream flow and land cover. Water Research 40
(6): 1258–1268. https://doi.org/10.1016/j.watres.2006.01.016.
Elmilady, H., M. Wegen, D. Roelvink, and B.E. Jaffe. 2018. Intertidal
area disappears under sea level rise: 250 years of morphodynamic
modeling in San Pablo Bay, California. Journal of Geophysical
Research: Earth Surface.https://doi.org/10.1029/2018jf004857.
Eyre, Bradley D., Damien T. Maher, and Christian Sanders. 2016. The
contribution of denitrification and burial to the nitrogen budgets of
three geomorphically distinct Australian estuaries: Importance of
seagrass habitats. Limnology and Oceanography 61 (3): 1144–
1156. https://doi.org/10.1002/lno.10280.
Ferreira, João G., Jesper H. Andersen, Angel Borja, Suzanne B. Bricker,
Jordi Camp, Margarida Cardoso da Silva, Esther Garcés, et al. 2011.
Overview of eutrophication indicators to assess environmental sta-
tus within the European Marine Strategy Framework Directive.
Estuarine, Coastal and Shelf Science 93 (2): 117–131. https://doi.
org/10.1016/j.ecss.2011.03.014.
Fishman, M. J., and L.C. Friedman. 1989. Methods for Determination of
Inorganic Substances in Water and Fluvial Sediment: U.S.
Estuaries and Coasts
Geological Survey, Techniques of Water-Resources Investigations,
Book 5, Chapter A1. 545p. https://doi.org/10.3133/twri05A1.
Fuller, C.C., A. van Geen, M. Baskaran, and R. Anima. 1999. Sediment
chronology in San Francisco Bay, California, defined by
210
Pb,
234
Th,
137
Cs, and
239,240
Pu. Marine Chemistry 64: 7–27.
Geider, Richard, and Julie La Roche. 2002. Redfield revisited: Variability
of C:N:P in marine microalgae and its biochemical basis. European
Journal of Phycology 37 (1): 1–17. https://doi.org/10.1017/
s0967026201003456.
Greening, H., A. Janicki, E.T. Sherwood, R. Pribble, and J.O.R.
Johansson. 2014. Ecosystem responses to long-term nutrient man-
agement in an urban estuary: Tampa Bay, Florida, USA. Estuarine,
Coastal and Shelf Science 151: A1–A16. https://doi.org/10.1016/j.
ecss.2014.10.003.
Hager, S.W. 1993. Dissolved nutrient and suspended particulate matter
data for the San Francisco Bay Estuary, California, October1988
through September 1991. U.S. Geological Survey Open-File
Report 93–57.
Hager, S.W., and L.E. Schemel. 1992. Sources of nitrogen and phospho-
rus to Northern San Francisco Bay. Estuaries 15 (1): 40–52.
Hauxwell, J., J. Cebrián, and I. Valiela. 2003. Eelgrass Zostera marina
loss in temperate estuaries: Relationship to land-derived nitrogen
loads and effect of light limitation imposed by algae. Marine
Ecology Progress Series 247: 59–73.
Howard, Meredith D.A., Martha Sutula, David A. Caron, Yi Chao, John
D. Farrara, Hartmut Frenzel, Burton Jones, George Robertson,
Karen McLaughlin, and Ashmita Sengupta. 2014. Anthropogenic
nutrient sources rival natural sources on small scales in the coastal
waters of the Southern California Bight. Limnology and
Oceanography 59 (1): 285–297. https://doi.org/10.4319/lo.2014.
59.1.0285.
Howarth, R.W., A. Sharpley, and D. Walker. 2002. Sources of nutrient
pollution to coastal waters in the United States: Implications for
achieving coastal water quality goals. Estuaries 25: 656–676.
Hughes, Brent B., John C. Haskins, Kerstin Wasson, and Elizabeth
Watson. 2011. Identifying factors that influence expression of eutro-
phication in a central California estuary. Marine Ecology Progress
Series 439: 31–43.
Jaffe, B.E., R.E. Smith, and L.Z. Torresan. 1998. Sedimentation and
bathymetric change in San Pablo Bay, 1856–1983. US Geological
Survey Open-File Report 98–759. doi: https://doi.org/10.3133/
ofr98759.
Jassby, A. D., and J. E. Cloern. 2016. wq: Some tools for exploring water
quality monitoring data. R package version 0.4.8. Available at:
http://cran.r-project.org/package=wq. Accessed 26 March 2020.
Jassby, A.D., J.E. Cloern, and T.M. Powell. 1993. Organic-carbon
sources and sinks in San Francisco Bay - variability induced by river
flow. Marine Ecology-Progress Series 95 (1–2): 39–54.
Jeffrey, S.W., R.F.C. Mantoura, and S.W. Wright. 1997. Phytoplankton
pigments in oceanography: Guidelines to modern methods.
UNESCO Publications. Paris: UNESCO.
Josefson, A.B., and B. Rasmussen. 2000. Nutrient retention by benthic
macrofaunal biomass of Danish estuaries: Importance of nutrient
load and residence time. Estuarine, Coastal and Shelf Science 50
(2): 205–216. https://doi.org/10.1006/ecss.1999.0562.
Kemp, W.M., W.R. Boynton, J.E. Adolf, D.F. Boesch, W.C. Boicourt, G.
Brush, J.C. Cornwell, et al. 2005. Eutrophication of Chesapeake
Bay: Historical trends and ecological interactions. Marine
Ecology-Progress Series 303: 1–29. https://doi.org/10.3354/
meps303001.
Kemp, W.M., J.M. Testa, D.J. Conley, D. Gilbert, and J.D. Hagy. 2009.
Temporal responses of coastal hypoxia to nutrient loading and phys-
ical controls. Biogeosciences 6 (2985–3008): 2009.
Kirchman, D.L. 1994. The uptake of inorganic nutrients by heterotrophic
bacteria. Microbial Ecology 28: 255–271. https://doi.org/10.1007/
BF00166816.
Lehman, P.W., K. Marr, G.L. Boyer, S. Acuna, and S.J. Teh. 2013. Long-
term trends and causal factors associated with Microcystis abun-
dance and toxicity in San Francisco Estuary and implications for
climate change impacts. Hydrobiologia 718 (1): 141–158.
Linker, L.C., R.A. Batiuk, G.W. Shenk, and C.F. Cerco. 2013.
Development of the Chesapeake Bay watershed total maximum
daily load allocation. Journal of the American Water Resources
Association 49: 986–1006. https://doi.org/10.1111/jawr.12105.
MacVean, L.J., L.S. Lewis, P. Trowbridge, J.A. Hobbs, and D.B. Senn.
2018. Dissolved oxygen in South San Francisco Bay: Variability,
important processes, and implications for understanding fish
habitat. Richmond: Technical Report. San Francisco Estuary
Institute. Available at https://www.sfei.org/documents/dissolved-
oxygen-south-san-francisco-bay-variability-important-processes-
and-implications. Accessed 26 March 2020.
Martin, M.A., J.P. Fram, and M.T. Stacey. 2007. Seasonal chlorophyll a
fluxes between the coastal Pacific Ocean and San Francisco Bay.
Marine Ecology Progress Series 357: 51–61.
McCabe, R.M., B.M. Hickey, R. Kudela, K. Lefebvre, N.G. Adams, B.
Bill, F. Gulland, R.E. Thomson, W. Cochlan, and V.L. Trainer. 2016.
An unprecedented coastwide toxic algal bloom linked to anomalous
ocean conditions: The 2015 US west coast toxic algal bloom.
Geophysical Research Letters 43 (19): 10366–10376. https://doi.
org/10.1002/2016GL070023.
McGlathery, K.J., K. Sundbäck, and I.C. Anderson. 2007. Eutrophication
in shallow coastal bays and lagoons: The role ofplants in the coastal
filter. Marine Ecology Progress Series 348: 1–18.
Monbet, Yves. 1992. Control of phytoplankton biomass in estuaries: A
comparative analysis of microtidal and macrotidal estuaries.
Estuaries 15: 563–571. https://doi.org/10.2307/1352398.
Moorman, M.C., A.B. Hoos, S.B. Bricker, R.B. Moore, A.M. García, and
S.W. Ator. 2014. Nutrient load summaries for major lakes and estu-
aries of the Eastern United States, 2002: U.S. Geological Survey
Data Series 820, 94 p. https://doi.org/10.3133/ds820.
Nixon, S.W. 1995. Coastal marine eutrophication - a definition, social
causes, and future concerns. Ophelia 41: 199–219.
Nixon, S.W., and B.A. Buckley. 2002. “A strikingly rich zone”- Nutrient
enrichment and secondary production in coastal marine ecosystems.
Estuaries 25 (4B): 782–796.
Nixon, S., B. Buckley, S. Granger, and J. Bintz. 2001. Responses of very
shallow marine ecosystems to nutrient enrichment. Human and
Ecological Risk Assessment 7 (5): 1457–1481.
Novick, E., and D. Senn. 2014. External nutrient loads to San Francisco
Bay. Available at: https://sfbaynutrients.sfei.org/sites/default/files/
NutrientLoadsFINAL_FINAL_Jan232014.pdf San Francisco
estuary institute.
O'Dell, J.W. 1993. Method 365.1. Determination of phosphorus by semi-
automated colorimetry, ed. Inorganic Chemistry Branch Chemistry
Research Division. Cincinnati: USEPA.
O'Shea, M.L., and T.M. Brosnan. 2000. Trends in indicators of eutrophi-
cation in Western Long Island sound and the Hudson-Raritan
Estuary. Estuaries 23 (6): 877–901. https://doi.org/10.2307/
1353004.
Paerl, H.W., J.L. Pinckney, J.M. Fear, and B.L. Peierls. 1998. Ecosystem
responses to internal and watershed organic matter loading:
Consequences for hypoxia in the eutrophying Neuse river estuary,
North Carolina, USA. Marine Ecology Progress Series 166: 17–25.
https://doi.org/10.3354/meps166017.
Paerl, H.W., J.T. Scott, M.J. McCarthy, S.E. Newell, W.S. Gardner, K.E.
Havens, D.K. Hoffman, S.W. Wilhelm, and W.A. Wurtsbaugh.
2016. It takes two to tango: When and where dual nutrient (N &
P) reductions are needed to protect lakes and downstream ecosys-
tems. Environmental Science &Technology 50 (20): 10805–10813.
https://doi.org/10.1021/acs.est.6b02575.
Patton, Charles J. , and Jennifer R. Kryskalla. 2003. Methods of analysis
by the U.S. Geological Survey National Water Quality Laboratory
Estuaries and Coasts
―Evaluation of alkaline persulfate digestion as an alternative to
Kjeldahl digestion for determination of total and dissolved nitrogen
and phosphorus in water: U.S. Geological Survey, Water-Resources
Investigations Report 03–4174.
Peacock, M.B., C.M. Gibble, D.B. Senn, J.E. Cloern, and R.M. Kudela.
2018. Blurred lines: Multiple freshwater and marine algal toxins at
the land-sea interface of San Francisco Bay, California. Harmful
Algae 73: 138–147. https://doi.org/10.1016/j.hal.2018.02.005.
Rabalais, N.N., R.E. Turner, and W.J. Wiseman. 2002. Gulf of Mexico
hypoxia, aka “The dead zone”.Annual Review of Ecology and
Systematics 33: 235–263. https://doi.org/10.1146/annurev.ecolsys.
33.010802.150513.
Raimonet, Mélanie, and James E. Cloern. 2016. Estuary-ocean connec-
tivity: Fast physics and slow biology. Global Change Biology.
https://doi.org/10.1111/gcb.13546.
Sarthou, Géraldine, Klaas R. Timmermans, Stéphane Blain, and Paul
Tréguer. 2005. Growth physiology and fate of diatoms in the ocean:
Areview.Journal of Sea Research 53 (1–2): 25–42. https://doi.org/
10.1016/j.seares.2004.01.007.
Schoellhamer, David H. 1996. Factors affecting suspended-solids con-
centrations in South San Francisco Bay, California. Journal of
Geophysical Research: Oceans 101: 12087–12095. https://doi.org/
10.1029/96JC00747.
Schoellhamer, David H. 2011. Sudden clearing of estuarine waters upon
crossing the threshold from transport to supply regulation of sedi-
ment transport as an erodible sediment pool is depleted: San
Francisco Bay, 1999. Estuaries and Coasts 34: 885–899. https://
doi.org/10.1007/s12237-011-9382-x.
Schoellhamer, D.H., M.A. Lionberger, B.E. Jaffe, N.K. Ganju, S.W.
Wright, and G.G Schellenbarger. 2005. Bay sediment budget:
Sediment accounting 101. In 2005 Pulse of the Estuary:
Monitoring and Managing Water Quality in the San Francisco
Estuary. Available at https://www.sfei.org/documents/pulse-
estuary-2005-monitoring-and-managing-water-quality-san-
francisco-estuary. Richmond, CA: San Francisco Estuary Institute.
Schraga, Tara S., and James E. Cloern. 2017. Water quality measurements
in San Francisco Bay by the U.S. Geological Survey, 1969–2015.
Scientific Data 4(1):4–14. https://doi.org/10.1038/sdata.2017.98.
Schraga, T.S., Nejad, E.S., Martin, C.A., and Cloern, J.E., 2020, USGS
measurements of water quality in San Francisco Bay (CA), begin-
ning in 2016 (ver. 3.0, March 2020): U.S. Geological Survey data
release, https://doi.org/10.5066/F7D21WGF.
Smith, V.H. 2006. Responses of estuarine and coastal marine phytoplank-
ton to nitrogen and phosphorus enrichment. Limnology and
Oceanography 51: 377–384.
Smith, S.V., and J.T. Hollibaugh. 2006. Water, salt, and nutrient ex-
changes in San Francisco Bay. Limnology and Oceanography 51
(1, part 2): 504–517.
Soetaert, K., and J.J. Middelburg. 2009. Modeling eutrophication and
oligotrophication of shallow-water marine systems: The importance
of sediments under stratified and well-mixed conditions.
Hydrobiologia 629: 239–254.
Solorzano, L. 1969. Determination of ammonia in natural waters by the
phenolhypochlorite method. Limnology and Oceanography 14:
799–801.
Stewart, B.M., and P.A.W. Elliott. 1996. Systematic salt effects in the
automated determination of nutrients in seawater. Wat er R es earc h
30 (4): 869–874.
Sutula, M., R. Kudela, J.D. Hagy III, L.W. Harding Jr., D. Senn, J.E.
Cloern, S. Bricker, and G.M. Berg. 2017. Novel analyses of long-
term data provide a scientific basis for chlorophyll-a thresholds in
San Francisco Bay. Estuarine, Coastal and Shelf Science 197: 107–
118. https://doi.org/10.1016/j.ecss.2017.07.009.
Thebault,J., T.S. Schraga, J.E. Cloern, and E.G. Dunlavey. 2008. Primary
production and carrying capacity of former salt ponds after recon-
nection to San Francisco Bay. Wetlands 28 (3): 841–851.
Wallace, Ryan B., Hannes Baumann, Jason S. Grear,Robert C. Aller, and
Christopher J. Gobler. 2014. Coastal ocean acidification: The other
eutrophication problem. Estuarine, Coastal and Shelf Science 148:
1–13. https://doi.org/10.1016/j.ecss.2014.05.027.
Walters, R. A., R. T. Cheng, and T. J. Conomos. 1985. Time scales of
circulation and mixing processes of San Francisco Bay waters. In
Temporal dynamics of an estuary: San Francisco Bay, eds. James E.
Cloern, and Frederic H. Nichols, 13-36. Developments in
Hydrobiology, vol. 30: Springer Netherlands.
Wells, Mark L., Bengt Karlson, Angela Wulff, Raphael Kudela, Charles
Trick, Valentina Asnaghi, Elisa Berdalet, et al. 2019. Future HAB
science: Directions and challenges in a changing climate. Harmful
Algae 91. https://doi.org/10.1016/j.hal.2019.101632.
Zimmermann, C.F., C.W. Keefe, and J. Bashe. 1997. Determination of
carbon and nitrogen in sediments and particulates of estuarine/
coastal waters using elemental analysis, ed. Office of Research and
Development National Exposure Research Laboratory. Cincinnati,
Ohio 45268: U.S. Environmental Protection Agency.
Estuaries and Coasts
