PHYTOPLANKTON BLOOM DYNAMICS IN COASTAL 

ECOSYSTEMS' A REVIEW WITH SOME GENERAL LESSONS 

FROM SUSTAINED INVESTIGATION OF SAN FRANCISCO 

BAY, CALIFORNIA 

James E. Cloern 

U.S. Geological Survey, Menlo Park, California 

Abstract. Phytoplankton blooms are prominent features of biological variability in shallow coastal ecosystems such as estuaries, lagoons, bays, and tidal rivers. 

Long-term observation and research in San Francisco 

Bay illustrates some patterns of phytoplankton spatial 

and temporal variability and the underlying mechanisms 

of this variability. Blooms are events of rapid production 

and accumulation of phytoplankton biomass that are 

usually responses to changing physical forcings originating in the coastal ocean (e.g., tides), the atmosphere 

(wind), or on the land surface (precipitation and river 

runoff). These physical forcings have different timescales 

of variability, so algal blooms can be short-term episodic 

events, recurrent seasonal phenomena, or rare events 

associated with exceptional climatic or hydrologic conditions. The biogeochemical role of phytoplankton primary production is to transform and incorporate reactive inorganic elements into organic forms, and these 

transformations are rapid and lead to measurable geochemical change during blooms. Examples include the 

depletion of inorganic nutrients (N, P, Si), supersaturation of oxygen and removal of carbon dioxide, shifts in 

the isotopic composition of reactive elements (C, N), 

production of climatically active trace gases (methyl 

bromide, dimethylsulfide), changes in the chemical form 

and toxicity of trace metals (As, Cd, Ni, Zn), changes in 

the biochemical composition and reactivity of the suspended particulate matter, and synthesis of organic matter required for the reproduction and growth of heterotrophs, including bacteria, zooplankton, and benthic 

consumer animals. Some classes of phytoplankton play 

special roles in the cycling of elements or synthesis of 

specific organic molecules, but we have only rudimentary 

understanding of the forces that select for and promote 

blooms of these species. Mounting evidence suggests 

that the natural cycles of bloom variability are being 

altered on a global scale by human activities including 

the input of toxic contaminants and nutrients, manipulation of river flows, and translocation of species. This 

hypothesis will be a key component of our effort to 

understand global change at the land-sea interface. Pursuit of this hypothesis will require creative approaches 

for distinguishing natural and anthropogenic sources of 

phytoplankton population variability, as well as recognition that the modes of human disturbance of coastal 

bloom cycles operate interactively and cannot be studied 

as isolated processes. 

INTRODUCTION 

Earth science of the 1980s and 1990s has been motivated partly by the challenge to understand global 

change, which in its broadest sense includes the myriad 

impacts of the human population on the Earth system. 

This problem persists as a difficult challenge because the 

component elements of global change, such as the climate system, hydrologic cycle, and biological populations, all have inherent large natural fluctuations. Superimposed onto these natural changes are those caused by 

human disturbance. This scientific challenge persists because human disturbance is often subtle, indirect, and 

sometimes confounded by natural changes that themselves are not well understood. This problem applies 

particularly to ecosystems at the continental margins, 

where natural change originates from processes in the 

coastal ocean, in the atmosphere, and on the land surface, and where human disturbance is highly focused. 

Seventy-five percent of the U.S. population will live 

within 75 km of a coast by the year 2010 [Williams et al., 

1991]. As a result of this dense human settlement along 

the continental margins, coastal ecosystems are influenced by diverse human activities, including agricultural 

practices [Fleischer et al., 1987; Nixon, 1995]; the damming of rivers and manipulation of their flows [Dynesius 

and Nilsson, 1994]; inputs of wastes, including nutrients 

[Justif et al., 1995] and toxic contaminants [Windom, 

1992]; changing land use [Cooper, 1995; Hopkinson and 

Vallino, 1995] and habitat loss [Nichols et al., 1986]; and 

disturbances of biological communities through harvest 

[Rothschild et al., 1994] or introductions of exotic species 

This paper is not subject to U.S. copyright. 

Published in 1996 by the American Geophysical Union. 

e127e 

Reviews of Geophysics, 34, 2 / May 1996 

pages 127-168 

Paper number 96RG00986 
128 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

Table 1. Examples of Recent Ecological Change in Global Coastal Waters 

Phenomenon Location (s) Reference (s) 

Episodes of anoxia and associated mortalities Baltic Sea 

of fish and shellfish Adriatic Sea 

Black Sea 

Harmful algal outbreaks global coastal waters 

Oyster population declines and disappearance Chesapeake Bay 

of vascular plants 

Changes in the community composition of 

phytoplankton 

Doubling of the biomass and shifts in the 

communities of invertebrates 

Invasion by exotic invertebrates and 

restructuring of biological communities 

Interannual fluctuations in abundance and 

species of macroalgae 

Mass mortalities of diverse marine biota 

Seabird mortality 

Episodes of thick foam accumulation on 

beaches 

Persistent closures of commercial shellfish 

harvest 

Increased frequency of red tides and associated 

fish kills 

Rosenberg et al. [1990] 

Justi• et al. [1987] 

Mee [1992] 

Smayda [1989], Hallegraeff [1993] 

Smith et al. [1992], Orth and Moore [1983] 

Bay of Aratu Salvador, 

Brazil 

Dutch Wadden Sea 

Cowgill [1987] 

Beukema [1991] 

north San Francisco Bay Alpine and Cloem [1992], Kimmerer et al. [1994] 

Peel-Harvey estuary, Australia Lavery et al. [1991] 

Scandinavian coastal waters 

Monterey Bay 

southern North Sea 

Underdal et al. [1989] 

Walz et al. [ 1994] 

Btitje and Michaelis [1986] 

New Zealand coastal waters Mackenziet al. [1995] 

Tolo Harbor, Hong Kong 

Seto Inland Sea, Japan 

Hodgkiss and Yim [1995] 

Prakash [1987] 

[Carlton, 1985; Carlton and Geller, 1993]. Nearly a fifth 

of the total marine fish catch comes from these zones of 

intense human activity [Pauly and Christensen, 1995]. 

In recent decades we have observed remarkable 

changes in coastal waters of all the continents; examples 

are listed in Table 1. Many of these changes are related 

either directly or indirectly to changes in the species 

composition, abundance, or production rate of the phytoplankton, so this one biological community is central 

to the problem of environmental change at the land-sea 

interface. This theme is prominent in the recent initiatives to understand mechanisms of change in coastal 

ecosystems (Table 2). One fundamental feature of phytoplankton dynamics is the episodic rapid population 

increase as events that we traditionally refer to as 

"blooms," presumably in reference to Sch•itt's [1892] 

description of the seasonal plankton cycles in Kiel Bight, 

(translation from Mills [1989, p. 125]): 

"and this play repeats itself year after year with the same 

regularity as every spring the trees turn green and in autumn 

lose their leaves; with just such absolute certainty as the cherries 

bloom before the sunflowers, so Skeletonema arrives at their 

yearly peak earlier than Ceratium." 

My purpose here is to review some principles of 

phytoplankton bloom dynamics in their context as features of change in estuarine and nearshore coastal waters. This review is organized to address basic questions: 

What are phytoplankton blooms? What are their underlying mechanisms? How are they related to changes in 

ecosystem processes and the geochemistry of estuarine 

and coastal waters? The review is based around observations, models, and insights that have come from the 

U.S. Geological Survey (USGS) program of research 

focused on San Francisco Bay. I begin with a general 

description and conceptual model of phytoplankton 

bloom dynamics in shallow coastal ecosystems. Next is a 

Table 2. Some Contemporary Research Initiatives to Describe and Explain Processes of Change in Coastal Ecosystems of 

North America and Europe 

Program Sponsor(s) * Reference (s) 

LMER (Land Margin Ecosystem Research) 

CoOP (Coastal Ocean Processes) 

GLOBEC (Global Ocean Ecosystems Dynamics) 

NECOP (Nutrient Enhanced Coastal Ocean Productivity) 

ECOHAB (Ecology and Oceanography of Harmful Algal 

Blooms) 

LOICZ (Land-Ocean Interactions in the Coastal Zone) 

EROS (European River Ocean System) 2000 

NSF 

NSF, NOAA, ONR 

NSF, NOAA 

NOAA 

NSF, NOAA 

ICSU 

CEC 

Boynton et al. [1992] 

Brink et al. [1992] 

U.S. GLOBEC [1995] 

Wenzel and Scavia [1993],Atwood et al. [1994] 

Anderson [1995] 

Holligan and de Boois [1993] 

Martin and Barth [1989] 

*Abbreviations are NSF, U.S. National Science Foundation; NOAA, U.S. National Oceanic and Atmospheric Administration; ONR, U.S. 

Office of Naval Research; ICSU, International Council for Scientific Unions; CEC, Commission of the European Communities. 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 129 

Shallow Coastal Ecosystem 

Local watershed 

ß .......... .. -..:..... ß 

Shallows "" 

-. 

Processes of phytoplankton 

population variability 

Lo n g itu d inal"• i7•'::. :. 

.tr.•._..::•a..nsport:•.:..• -' :-:?_:-_.- 

ß .. '•.... • Zoca?•?us 

Za/era/ •ran•?orZc '.i" ./ 

Primary.production 

'•:' -i)/:::: ' "'•';• -,- i"2i:'?•:i":' -::" ............ eel'2gic• "'"• ':":'" Turbulent '"::':: ' •nputs [ 

ß "... Resusp,e.i•Sion •i •' grazing mixing ... ß . : :'.•!•:..i,: Sedir•entation • ,&_ '....•.•"i•.'-'::.. -'-":I:'--')'" ":! -': '!i • -'-•-_d• Benthic grazing 

Plate 1. An idealized shallow coastal ecosystem (SCE) showing the key processes of phytoplankton 

population variability at the land-sea interface. Local processes include primary production (the source of new 

phytoplankton biomass), consumption by benthic and pelagic grazers, exchanges between the sediment 

surface and water column by sedimentation and resuspension, and turbulent mixing. Horizontal transport 

processes include exchanges with the coastal ocean, riverine inputs of phytoplankton, and longitudinal and 

lateral transports generated by density-, tide-, and wind-driven circulation and mixing. The color transition 

from green to blue represents the salinity gradient along the river-ocean continuum. Brightness represents the 

bathymetry, and white shadings indicate the lateral shallow domains common to coastal plain estuaries and lagoons. 

detailed review of the approaches used in our analysis of 

the long term observations in south San Francisco Bay, 

with emphasis on the search for patterns and mechanisms of phytoplankton population variability. Then I 

describe the significance of blooms in the coastal zone, 

emphasizing the role of phytoplankton production as a 

mechanism of geochemical and ecological change. I conclude with some thoughts on the compelling questions 

and hypotheses that will guide research at the land-sea 

interface into the next century. 

The USGS research program in San Francisco Bay 

began in 1968 and continues as one of the few long-term 

efforts of combined observation and research in the U.S. 

coastal zone. Other aspects of this program are described by Conomos [1979b], Kockelman et al. [1982], 

Cloern and Nichols [1985], Nichols et al. [1986], Nichols 

and Pamatmat [1988], Peterson [1989], Cheng [1990], 

Luoma et al. [1990], and Peterson et al. [1995]. 

THE GENERAL PROBLEM 

Domains of Interest 

San Francisco Bay has been the focus of sustained 

investigation because it has features common to many 

shallow coastal ecosystems (SCEs) that are influenced by 

natural and anthropogenic sources of variability. These 

SCEs include tidal rivers, estuaries, embayments, lagoons, and coastal river plumes, which are distinctly 

different ecosystems from the open ocean. The differences arise partly from the physical features illustrated 

in Plate 1, and they include the following. 

1. SCEs are transition zones at the land-sea interface, so they are influenced both by inputs from the land 

surface and exchanges with the coastal ocean. Connections to the land surface are made through rivers that 

carry runoff from large-scale catchments or from smaller 

tributaries that carry runoff from the local watershed 
130 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

(Plate 1). Riverine inputs are sources of fresh water, 

sediments, and nutrients that together create a unique 

habitat for phytoplankton population development. 

These habitats are characterized by large spatial gradients along the river-ocean continuum. 

2. The domains considered here are shallow. The 

mean depth of San Francisco Bay is less than 10 rn 

[Conomos et al., 1985], and maximum depth of the 

central channels is of the order of 20-30 m. Exchanges 

of materials between the pelagic domain (open water 

column) and the benthos (bottom sediments) are rapid, 

so strong benthic-pelagic coupling is a defining feature 

of SCEs. 

3. River-influenced SCEs are very different physical 

environments from the open ocean. For example, turbulent mixing is a key physical process that determines the 

vertical fluxes of heat, salt, nutrients, and plankton. 

Vertical mixing in the open ocean is regulated by the 

seasonal cycle of heat input and thermal stratification 

that retards mixing between surface and deep waters. 

However, in estuaries and other marine "regions of 

freshwater influence" [Simpson et al., 1991], vertical mixing is regulated by a larger and more variable source of 

buoyancy, the riverine input of fresh water that acts to 

stabilize the water column through salinity stratification. 

4. SCE's are particle-rich relative to the open ocean. 

In San Francisco Bay the near-surface concentrations of 

suspended particulate matter (SPM) range from <5 to 

>300 mg L -• [Conomos et al., 1979]; at highest concentrations the SPM is dominated by mineral particles delivered by river flow or resuspended off the bottom by 

tidal and wind wave currents. Suspended particles absorb and scatter light, so SCEs are turbid habitats in 

which phytoplankton growth can be limited by the availability of sunlight to sustain photosynthesis [Wofsy, 1983; 

Cloem, 1987]. 

5. Many SCEs are nutrient-rich because of inputs 

from the land surface [Malone et al., 1988; Nixon, 1995; 

Justif et al., 1995] and geochemical and biological processes that act as "filters" to retain nutrients within 

estuaries [Sharp et al., 1984]. In south San Francisco Bay, 

summer phosphate concentrations often exceed 10 gM 

compared with concentrations of <0.5 gM in the adjacent Pacific Ocean [Van Geen and Luoma, 1993]. Similar 

enrichment exists for other nutrients such as nitrogen 

(N) and silica (Si). Therefore the potential for phytoplankton production can be much higher in SCEs than in 

most regions of the ocean, and the phytoplankton population fluctuations in SCEs are highly amplified. 

General Overview and Conceptual Model 

of Phytoplankton Blooms in SCEs 

Shallow coastal ecosystems maintain plankton populations distinct from those beyond the freshwater and 

oceanic interfaces. Much of the biogeochemical variability within these SCEs originates with fluctuations in the 

phytoplankton population, and Riley [1967] provided the 

conceptual framework for understanding these fluctuations. The phytoplankton (Table 3) include 5000 marine 

species [Hallegraeff, 1993] of unicellular algae having a 

broad diversity of cell sizes (mostly in the range of 1 to 

100 txm), morphologies, physiologies, and biochemical 

compositions (Margalef [1978], Soumia [1982], and Fogg 

[1991] give excellent reviews of the form and function of 

the phytoplankton). All phytoplankton species are capable of photosynthesis, and many have the capacity for 

rapid cell division and population growth, up to four 

doublings per day [e.g., Fahnenstiel et al., 1995]. Population dynamics of the phytoplankton can be interpreted 

as responses to changes in individual processes that 

regulate the biomass (total quantity, in measures such as 

carbon, nitrogen, or chlorophyll concentration), species 

composition, and spatial distribution of the phytoplankton population. These processes include in situ (local) 

processes that cause population change within a water 

parcel, and horizontal transports that displace or mix 

water parcels and their phytoplankton (Plate 1). 

In situ processes of population change include (1) the 

production of new biomass, which is controlled by the 

availability of visible light energy required for photosynthesis and nutrient resources required for the biosynthesis of new algal cells, (2) mortality, including that caused 

by parasites or viruses, (3) grazing losses to pelagic and 

benthic consumer animals, (4) turbulent mixing by tideand wind-induced motions in the water column, (5) 

sinking and deposition of phytoplankton biomass on the 

bottom sediments, and (6) resuspension of bottom-deposited microalgae by tidal currents and wind waves. 

Horizontal transports follow water circulations that are 

driven by tidal currents, wind stresses on the water 

surface, and horizontal gradients of water density [Fischer et al., 1979]. These transports displace phytoplankton biomass longitudinally along the river-ocean continuum and laterally between shallow and deep domains, 

which are very different habitats for phytoplankton 

growth [Cloem and Cheng, 1981; Malone et al., 1986]. 

Although techniques exist to measure or estimate each 

process shown in Plate 1, comprehensive process-specific measurement programs are expensive, logistically 

challenging, and rarely done. Rather, phytoplankton dynamics in SCEs are often followed by measuring changes 

in biomass (usually as the concentration of chlorophyll 

a, the photosynthetic pigment contained in all phytoplankton cells), species composition, and photosynthesis 

as an index of population growth rate. These measurements are often done in conjunction with basic hydrographic measurements (salinity, temperature, tides) that 

can be used to infer patterns of water circulation and 

transports, and surveys of the pelagic and benthic herbivores that can used to estimate potential rates of 

grazing loss. 

Phytoplankton populations often exist in a static 

"quasi-equilibrium" [Evans and Parslow, 1985] in which 

the rate of biomass production (the primary productivity) is balanced by the phytoplankton losses and transports. Under this condition the net population growth 
34, 2 / REVIEWS OF GEOPHYSICS Cloern' COASTAL PHYTOPLANKTON BLOOMS ß 131 

Table 3. Characteristics of the Primary Classes of Algae That Form Phytoplankton Blooms in Tidal Rivers, Estuaries, and 

Shallow Coastal Waters 

Class Distinguishing Features Common Genera • Examples of Occurrence 

Chlorophyceae forms include unicells or multicelled Nannochloris 

(green algae) colonies or filaments; cell walls 

contain cellulose; zero, two or four 

equal flagella; storage product is Dunaliella 

starch; most species are freshwater 

Chrysophyceae mostly small unicells, motile or Pseudopedinella 

(chrysophytes) nonmotile; some species with Aureococcus 

silicified or calcareous scales in the 

cell wall; either one or two (unequal) 

flagella; storage products are lipid (fat) 

small, flattened, motile cells; cell 

coverings of minute proteinaceous 

plates; two equal flagella; ubiquitous 

but rarely dominate bloom biomass 

nonmotile cells shaped like discs, needles, Chaetoceros 

or multicelled colonies or chains; cell Thalassiosira 

walls composed of two organic shells 

(frustules) impregnated with 

amorphous silica; some species are 

capable of very rapid cell division; Skeletonema 

often the dominant components of 

spring blooms in temperate coastal 

waters 

Cryptophyceae Cryptomonas 

(cryptophytes) Chroomonas 

Diatomophyceae 

(diatoms) 

Dinophyceae 

(dinoflagellates) 

(mostly) large, motile unicells; 

multilayered cell covering, formed into 

distinct plates in the "armored" 

species; two unequal flagella (one 

transverse, one longitudinal); some 

species capable of rapid swimming and 

vertical migration; responsible for 

visible colored (red, green) blooms; 

Rhizosolenia 

Coscinodiscus 

Leptocylindricus 

Nitzschia 

Katodinium 

Gymnodinium 

Alexand•um 

Peridinium 

many species are mixotrophic (capable Dinophysis 

of both photosynthetic and heterotrophic nutrition) Prorocentrum 

Cyanophyceae (blue- very small, procaryotic (bacteria-like) Microcystis 

green algae, or cells with no defined internal structures Nodularia 

cyanobacteria) (e.g., no nucleus or chloroplasts); 

unicells or multicelled colonies or 

filaments; no flagella; gs vacuoles Aphanizomenon allow buoyancy regulation and dense 

accumulations at the water surface; Synechococcus 

some species fix N2 

Prasinophyceae small, motile cells; one, two, or four Pyramimonas 

flagella that are covered with minute Micromonas 

scales or hairs; most species have cell 

coverings with organic scales 

Prymnesiophyceae most species are small, motile cells, but Phaeocystis 

some form colonies of nonmotile cells; 

cell coverings include one or more 

layers of organic scales or calcite plates Emiliania 

(coccoliths); one or two flagella, with 

some species also having a short Chrysochromulina 

appendage (haptonema) for 

attachmento surfaces; complex life 

cycles of alternating cell forms and Prymnesium 

diverse modes of nutrition 

Calico Creek, North Carolina [Mallin, 

1994] 

lagoons of NE Spain [Comin, 1982] 

Pamlico River estuary [Mallin, 1994] 

Long Island embayments [Cosper et al., 

1989]; Narragansett Bay [Smayda and 

Villareal, 1989] 

Rhode River estuary [Gallegos, 1992] 

Neuse River estuary [Mallin, 1994]; San 

Francisco Bay [Cloern et al., 1985] 

Bedford Basin, Canada [Kepkay et al., 1993] 

Auke Bay, Alaska [Ziemann et al., 1991]; 

Gulf of St. Lawrence [Levasseur et al., 

1992]; Gulf of Naples, Italy [Zingone et al., 

1995] 

Kinu-ura Bay, Japan [Hama and Handa, 

1994]; Fraser River plume [Harrison et al., 

1991]; Dutch coastal waters [Brussaard et 

al., 1995]; Scottish sea lochs [Tett et al., 

1986]; Madras coast, India [Sivaswamy and 

Prasad, 1990]; Patos Lagoon, Brazil [Abreu 

et al., 1995] 

French coastal waters [Sournia et al., 1987] 

Otsuchi Bay, Japan [Nakaoka, 1992] 

German Bight [Colijn et al., 1990] 

Bay of Fundy, Canada [Martin et al., 1990] 

Patuxent River estuary [Sellner et al., 1991] 

Tomales Bay [Cole, 1989]; Ria de Viso, 

Spain [Fraga et al., 1992] 

Gulf of Maine [Franks and Anderson, 1992]; 

Chinhae Bay, Korea [Han et al., 1992] 

Baltic Sea [Heiskanen and Kononen, 1994] 

French Atlantic coast [Delmas et al., 1992] 

Chesapeake Bay [Tyler and Seliger, 1978] 

Neuse River estuary [Rudek et al., 1991] 

Baltic Sea [Wasmund, 1994]; Peel-Harvey 

estuary, Australia [Lukatelich and 

McComb, 1986] 

Baltic Sea [Gran•li et al., 1990] 

Changjiang (Yangtse River) plume, China 

[Ning et al., 1988] 

Tampa Bay [Gardiner and Dawes, 1987] 

Fraser River plume [Harrison et al., 1991]; 

Sundays River estuary, South Africa 

[Hilmer and Bate, 1991] 

Dutch coastal waters [Cad•e, 1990]; 

Narragansett Bay [Verity et al., 1988] 

Black Sea [Sur et al., 1994] 

Scandinavian coastal waters [Maestrini and 

Gran•li, 1991] 

Norwegian fjords [Kaartvedt et al., 1991] 
132 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

Table 3. (continued) 

Class Distinguishing Features Common Genera Examples of Occurrence 

Phototrophic chlorophyll-containing protozoans Mesodinium 

ciliates capable of rapid photosynthesis and 

population growth; swimming 

structures (cilia) allow rapid vertical 

migrations; form intense visible 

(nontoxic) red tides; a unique 

nonalgal component of the marine 

phytoplankton 

San Francisco Bay [Ctoern et at., 1994]; 

Patos Lagoon, Brazil [Abreu et at., 1994]; 

Sechelt Inlet, Canada [Haigh et al., 

1992]; Southampton Water, U.K. [Iriarte 

and Purdie, 1994]; Strait of Georgia 

[Harrison et al., 1983] 

Based on the algal taxonomy of Chr•tiennot-Dinet et al. [1993] and descriptions of Morals [1967] and Sournia [1982]. Algae are classified on 

the basis of their photosynthetic pigments, storage products (food reserves), cell walls (external coverings), and number and type of flagella 

(propulsive organs). 

rate is near zero and the biomass remains constant. 

Phytoplankton blooms are transient departures from 

quasi-equilibrium when the primary productivity temporarily exceeds the losses and transports and the population grows rapidly and reaches exceptionally high biomass [Paerl, 1988; Legendre, 1990]. Phytoplankton 

blooms usually are not single discrete events but rather 

are a series of fluctuations in which the biomass and the 

species composition (Table 3) of the phytoplankton population change rapidly. 

We can very generally classify blooms into three 

types: (1) recurrent seasonal events that usually persist 

over periods of weeks, (2) aperiodic events that often 

persist for periods of days [e.g., Takahashi et al., 1977], 

and (3) exceptional events that are typically dominated 

by few species (sometimes noxious or toxic forms) and 

persist for months [e.g., Nixon, 1989]. Seasonal blooms 

can occur in spring [Malone et al., 1988; Ziemann et al., 

1991; Lignell et al., 1993], summer [Sinclair, 1978; Cole, 

1989; Vant and Budd, 1993]; autumn [Zingone et al., 

1995], and winter [Hitchcock and Smayda, 1977; MacKenzie and Gillespie, 1986; Sellner et al., 1991]. These 

events are often dominated by different groups of species each season as the phytoplankton community adapts 

to changes in resources and the physical environment 

[Margalef, 1978; Smetacek and Pollehne, 1986]. A common annual cycle begins with large winter-spring diatom 

blooms followed by summer blooms of small flagellates, 

dinoflagellates, and diatoms and then autumn blooms 

dominated by dinoflagellates [Smetacek, 1986; Tett et al., 

1986; Mallin et al., 1991]. 

The underlying mechanisms of phytoplankton blooms 

are diverse and can be organized with a simple population budget that describes biomass fluctuations at a fixed 

geographic reference, 

AB/At = -+(ix - r) B - Gp - Gb -+ E -+ X (1) 

where AB is the change in phytoplankton biomass over 

time increment At and terms on the right-hand side 

represent the individual process illustrated in Plate 1: ix 

is the growth rate, a function of light and nutrient 

availability; ris loss rate to respiration (note that (ix - 

r) is the net growth rate and (ix - r)B is the net rate of 

biomass production); Gp is the loss rate to pelagic (zooplankton) grazing; G b is the loss rate to benthic grazing; 

E represents exchanges of biomass between the bottom 

sediments and overlying water column; and X represents 

all horizontal transports by advective and turbulent diffusive processes. Blooms are periods in which AB/At is 

large and positive, so [from Legendre, 1990] 

(ix - r)B > > (Gp + Gb + E + X) (2) 

Equation (2) can be satisfied under environmental 

conditions in which the net growth rate (ix - r) is large. 

When nutrients are abundant, the net growth rate is 

directly proportional to light availability. For example, in 

San Francisco Bay, (ix - r) is correlated with the mean 

daily irradiance I to which phytoplankton cells are exposed as they are moved within the water column by 

turbulent mixing [Alpine and Cloern, 1988]. The mean 

irradiance in a uniform mixed layer of thickness H is 

I • Io/(kH) (3) 

where I 0 is the daily quantity of photosynthetically active 

radiation penetrating just below the water surface and k 

is the light attenuation coefficienthat defines the exponential decay of light with depth. 

Equation (3) shows that the depth-averaged quantity 

of light available to sustain phytoplankton photosynthesis and growth is directly proportional to surface irradiance I0 and inversely proportional to turbidity k and the 

depth scale H. Blooms can be triggered by changes in 

each of these three quantities. The spring bloom in 

Swedish coastal waters begins when the daily surface 

irradiance I0 reaches a threshold value of about 30 E 

m -2 d -1 [Bt•mstedt, 1985]. In Dutch coastal waters the 

spring bloom begins first in offshore regions where k is 

small and i reaches the threshold value earlier than in 

the more turbid (high k) inshore regions [Gieskes and 

Kraay, 1975]. Short-term, aperiodic fluctuations of phytoplankton biomass can be caused by wind events that 

resuspend fine bottom sediments and increase k to the 

point where mean I and the net growth rate become very 

small [Tett and Grenz, 1994]. 

Blooms often develop when the effective mixing 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 133 

depth of the water column (depth scale H) is reduced by 

vertical stratification. If the water density is uniform over 

depth H, then wind and tidal stirring can move phytoplankton cells rapidly between the surface photic zone 

(where sufficient light exists to sustain photosynthesis 

and a positive net growth rate) and the deeper aphotic 

zone (where light is absent and the net growth rate is 

negative). Surface heating and freshwater inputs are 

sources of buoyancy that can establish vertical density 

gradients in the water column. Strong vertical stratification can effectively isolate phytoplankton in a shallow 

(small H) surface layer in which the mean irradiance Iis 

much higher than the irradiance averaged over the full 

water column height. As a result, the net growth rate of 

phytoplankton in the surface layer increases after the 

establishment of vertical stratification. Seasonal blooms 

can be triggered by seasonal fluctuations in river flow 

and the intensity of salinity stratification [Pennock, 

1985]. At shorter timescales the intensity of vertical 

stratification fluctuates with changes in the strength of 

tidal stirring. Regular weekly fluctuations of vertical 

stratification often coincide with the fortnightly neapspring tidal cycle, with alternations between well-mixed 

(spring tide) and stratified (neap tide) conditions. In 

many tidal SCEs the neap tide periods of enhanced 

stratification are periods of phytoplankton biomass 

growth, and the proximal agent of these weekly blooms 

is the increased growth rate of phytoplankton confined 

in a shallow surface layer [Winter et al., 1975; Sinclair, 

1978; Haas et al., 1981; Cloern, 1984; de Madariaga et al., 

1989; Roden, 1994; Ragueneau et al., 1996]. 

The second critical resource for phytoplankton 

growth is the pool of nutrients required for the biosynthesis of new cells. The potential magnitude of phytoplankton blooms is set by the supply rate of the least 

abundant nutrient elements. In addition, the growth 

efficiency of phytoplankton in low-light habitats increases with nutrient availability [Cloern et al., 1995]. 

Therefore phytoplankton blooms can be responses to 

seasonal fluctuations in the riverine inputs of nutrient 

elements such as N [Malone et al., 1988] and P [McComb 

and Humphties, 1992]. Episodic blooms can follow 

pulsed inputs of nutrients from runoff produced in the 

local watershed during storms [Gallegos et al., 1992; 

Hama and Handa, 1994], direct inputs of atmospheric 

nitrogen from rainfall [Paerl et al., 1990], or the input of 

nutrients from the coastal ocean during upwelling events 

[Lara-Lara et al., 1980]. 

The necessary condition for bloom initiation (equation (2)) is that the primary productivity must be large 

relative to all mechanisms of phytoplankton loss, including consumption (grazing) by pelagic and benthic animals. Therefore blooms can develop through mechanisms that lead to reduced grazing loss. The spring 

blooms in temperate and high-latitude coastal waters 

begin when the zooplankton biomass and grazing rate 

are near their annual minima [B•mstedt, 1985]. Diatom 

blooms can follow rapid declines in zooplankton abundance caused by episodes of intense predation on copepods (small pelagic crustaceans that feed on phytoplankton), so the timing and magnitude of blooms can be 

regulated by top down processes originating at higher 

trophic levels [Deason and Smayda, 1982]. 

In many SCEs the total biomass (and therefore potential grazing rate) of the benthic consumer animals is 

much higher than the biomass of the copepods and other 

zooplankton [Cloern, 1982; Knox, 1986; Colijn et al., 

1988]. Suspension-feeding benthic invertebrates, such as 

polychaete worms and bivalve mollusks (clams, mussels), 

actively remove phytoplankton biomass from just above 

the sediment-water interface; other benthic animals consume phytoplankton biomass deposited on the sediment 

surface. Therefore the rate of benthic grazing can be 

limited by the vertical flux of phytoplankton biomass 

from the water column to the sediment-water interface 

[Monismith et al., 1990]. In south San Francisco Bay, 

blooms are controlled by the seasonal and weekly fluctuations in salinity stratification because strong stratification retards the turbulent diffusive flux of phytoplankton from the productive surface layer to the bottom zone 

of active consumption by benthic animals. Stratification 

acts to decouple phytoplankton from the bottom grazers 

[Cloern, 1991b]. Therefore stratification promotes blooms 

by (1) establishing conditions of rapid phytoplankton 

growth in the surface layer and (2) slowing the delivery 

of phytoplankton biomass to the benthic consumers 

[Koseff et al., 1993]. In some SCEs the rate of benthic 

grazing continually overwhelms phytoplankton primary 

production. This is the current situation in upper 

reaches of northern San Francisco Bay, where summer 

blooms disappeared after an exotic clam (Potamocorbula 

amurensis) became so abundant that its grazing rate 

balances phytoplankton productivity [Alpine and Cloern, 

1992] (see Figure 3b below). Similar dramatic declines in 

phytoplankton biomass have been observed in other 

coastal systems after aquaculture activities increased the 

abundance of filter-feeding mollusks through cultivation 

[Motoda et al., 1987]. 

The last term in (2) represents the horizontal transports, which can also be mechanisms of bloom regulation. Plankton populations can be maintained in a 

coastal basin only when the net rate of biomass production, (ix - r)B, exceeds the net rate of transport losses, 

X [Malone, 1977; Kikuchi et al., 1992]. In SCEs coupled 

to large river systems, the hydraulic residence time can 

be short relative to the phytoplankton population growth 

rate during periods of high discharge. Blooms can develop only when the river discharge falls to a level at 

which the residence time within the SCE is longer than 

the phytoplankton population doubling time [Cloern et 

al., 1983; Relexans et al., 1988]. Horizontal transports can 

be sources of phytoplankton when coastal [Malone, 

1977] or riverine [de Madariaga et al., 1992] blooms are 

advected into coastal basins. Exceptional blooms can 

follow exceptional climate patterns that cause slow hor- 
1 34 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

izontal transports and long hydraulic residence time 

within coastal basins [Vieira and Chant, 1993]. 

Other mechanisms of water circulation and mixing 

influence plankton dynamics. The spring bloom in Chesapeake Bay develops when density-driven circulations 

cause a landward transport and accumulat, ion of phytoplankton biomass in the upper estuary [Malone et al., 

1988]. In south San Francisco Bay, localized blooms that 

develop over the lateral shallows are dissipated quickly 

by strong wind or river flow events that generate pulses 

of enhanced circulation and rapid horizontal transports 

[Huzzey et al., 1990]. Red tide blooms can be triggered by 

intrusions of coastal water that alter the vertical circulation pattern and carry dormant algal cells (cysts) from 

the sediments to the water column, where they seed the 

rapid population growth of dinoflagellates [Figueiras and 

Pazos, 1991]. Sharp discontinuities between different 

water masses (fronts) can be sites of phytoplankton 

accumulation. Tidal fronts at the interface between shallow mixed waters and deeper stratified waters promote 

the growth and physical accumulation of phytoplankton 

and can be zones of intense dinoflagellate blooms [Simpson and Hunter, 1974]. Buoyancy fronts between a lowsalinity (low density) and a high-salinity water mass can 

also be regions of active phytoplankton growth and 

accumulation [Franks, 1992]. 

The conceptual model outlined above places great 

emphasis on the changing physical and chemical environment as a mechanism of phytoplankton population 

change. However, it is important to remember also that 

the plankton species living in SCEs have evolved in these 

habitats and acquired behavioral, biochemical, and lifehistory adaptations to the physical and chemical variability characteristic of coastal waters. For example, the 

photosynthetic ciliate Mesodinium rubrum, which forms 

visible red tides in San Francisco Bay [Cloem et al., 1994] 

and other temperate estuaries, has a behavioral mechanism that acts to retain this species within tidal SCEs: 

active swimming toward the surface on incoming flood 

tides, and then downward migration to retard seaward 

transports by the ebb tides [Crawford and Purdie, 1992]. 

Some dinoflagellates [Horstmann, 1980] and other swimming species [Watanabe et al., 1995] have vertical migrations cued to the diurnal (daylight) cycle that allow for 

exploitation of sunlight at the surface during the day and 

nutrient resources in the bottom waters at night. Other 

species produce resting cells that sink to the sediments 

when growth resources become limited; these then seed 

blooms when environmental conditions become favorable for population growth [de Madariaga et al., 1989; 

Figueiras and Pazos, 1991]. Recent evidence suggests 

that overwintering dormant stages of some phytoplankton species begin their development into active cells 

when the daylength reaches about 13 hours in spring, so 

blooms of these species are life cycle responses cued to 

the annual photoperiod cycle [Eilertsen et al., 1995]. 

Therefore phytoplankton are not absolutely passive organisms subjected to the constraints imposed by their 

physical-chemical environment. They have diverse capabilities of adaptation. 

THE SAN FRANCISCO BAY EXAMPLE 

A Representative Shallow Coastal Ecosystem 

The sustained investigation of San Francisco Bay 

provides a case study to illustrate the patterns and mechanisms of phytoplankton blooms in one shallow coastal 

ecosystem. San Francisco Bay is a useful site for comparative estuarine science because it comprises two connected, but distinct, subsystems (Figure 1). The north 

bay is the estuary of the Sacramento and San Joaquin 

Rivers, which carry runoffrom a large (150,000 km 2) 

watershed between the Sierra Nevada mountains and 

the Pacific Ocean. The north bay has features characteristic of partially mixed estuaries, including large horizontal gradients of salinity, suspended sediments, nutrients, and biological communities. In contrast, the south 

bay is a semienclosed basin with salinity that is nearoceanic during the low-flow seasons and is diluted by 

freshwater inputs during the high-flow winter-spring. 

The San Francisco Bay system has complex bottom 

topography with broad shallow embayments that are 

incised by a deeper channel, channel constrictions between the embayments, and connection to the Pacific 

Ocean through a deep (100 m), narrow entrance at the 

Golden Gate (Figure 1). The estuary is nutrient-rich, 

with nutrient sources dominated by agricultural inputs 

carried by river flow and sewage inputs from the local 

population of 8 million. 

Much of the phytoplankton population variability 

within San Francisco Bay originates with fluctuations in 

physical forcings at the oceanic, atmospheric, and watershed interfaces. A primary forcing at the estuary-watershed interface is the input of fresh water, which has 

strong seasonal and interannual variability. Figure 2a 

shows fluctuations of the freshwater inflow to north San 

Francisco Bay during four of the years in which phytoplankton population variability has been measured. 

These records show that annual fluctuations in river flow 

are dominated by a wet season (from winter storms and 

spring snowmelt) and a dry summer-autumn season 

when precipitation stops. These records also show pronounced year-to-year fluctuation of river flow to San 

Francisco Bay: 1983 was the wettest year of this century, 

1986 was dominated by an extreme flood event (the 

highest recorded flow of this century), and the 1989 and 

1993 hydrographs show seasonal patterns of river flow 

during representative dry and wet years, respectively. 

Freshwater inputs from the smaller local streams are 

more immediately responsive to winter storms, and local 

streamflows to the south bay stop entirely during summer-autumn (Figure 2b). These seasonal and interannual fluctuations in river flow are driven by large-scale 

atmospheric circulations that control the strength and 

position of the Pacific high-pressure system, which de- 
34 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 135 

122030 ' 122ø15;" 122000 ' 121"45' 

37045 ' 

0 5 10 mi 

0 5 10kin 

Figure 1. Map of San Francisco Bay, a shallow coastal ecosystem influenced by tides at the oceanic boundary 

(the Golden Gate) and freshwater inflows at the watershed boundaries. Arrows show sources and flows of 

fresh water during periods of high runoff. SFA is San Francisco International Airport. The inset shows the 

drainage basin and major tributaries of the Sacramento-San Joaquin River system. 

flects moisture-bearing storms to the north of California 

[Peterson et al., 1995]. 

Physical forcings at the estuary-atmosphere interface 

include wind stress at the water surface that stirs the 

upper water column, resuspends bottom sediments, and 

drives horizontal circulations. In the San Francisco Bay 

region, winds have maximum speeds in summer (Figure 

2c) associated with the westerly sea breeze [Conomos et 

al., 1985]. Episodic fluctuations in wind stress are associated with storms, particularly winter storms that typically come from the southwest. Irradiance has regular 

seasonal periodicity and daily fluctuations associated 

with storms and intrusions of coastal fog during summer 

(Figure 2d). 

A primary physical forcing at the estuary-ocean interface is the tide, which propagates into San Francisco Bay 

through the Golden Gate. In this region of the northeast 

Pacific, the tides have a strong semidiurnal component 

with two unequal flood and ebb cycles every 24.84 hours. 

A second important component of the tide is the fortnightly neap-spring cycle (Figure 2e) of two unequal 

spring and neap tides each lunar month (27.5 days). In 

the south bay the tidal amplitude (difference between 

water elevation at high and low tide) is about 2 m, the 

tidal excursion (horizontal displacement of a water parcel during a tidal cycle) ranges between 7 km at neap 

tide and 13 km at spring tide, and maximum tidal current 

speed U is about 0.75 m s -• [Conomos, 1979a; Walters et 

al., 1985]. Therefore San Francisco Bay is a mesotidal 

SCE with tidal influence smaller than that in macrotidal 

systems such as the English Channel and Bay of Fundy 

(tidal amplitude > 10 m), but larger than in the microtidal Gulf of Mexico, Baltic Sea, and Mediterranean 

Sea (tidal amplitude < 0.5 m). 
1 36 ß Cloern' COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

150OO 

• 10000 5000 

z 

o 

300 

200 

lOO 

-• o "*•i '•

15 

• 10 

-o 5 

a 

•, 6o 

• 40 

c: 20 

0.7 

0.5 

0.4 

1983 1986 1989 1993 

Figure 2. Daily fluctuations of five physical forcings that 

influence population dynamics of phytoplankton in San Francisco Bay. Series are for four contrasting hydrologic years 

(1983, 1986, 1989, and 1993), showing (a) net freshwater inflow 

from the Sacramento and San Joaquin Rivers (a calculated 

quantity, the Delta Outflow Index, from the California Department of Water Resources), (b) daily discharge of a local stream 

(Patterson Creek) that discharges into south San Francisco 

R•,x, (from 11 R •oc•lc•glcml Suv:ey (L•, ni•_ 

trict), (c) mean daily wind speed at the San Francisco airport 

(from the National Climatic Data Center, National Oceanic 

and Atmospheric Administration), (d) daily irradiance, measured as quantum flux of photosynthetically active radiation, 

and (e) m•imum daily tidal current speed in the channel of 

south San Francisco Bay, calculated with harmonic constants 

from long-term current measurements [Cheng and Ganner, 

1985]. 

The Issue of Scale 

Each of the physical forcings illustrated in Figure 2 

contributes to phytoplankton population variability by 

influencing the rates of vertical mixing, horizontal transport, production, or grazing. Each forcing has characteristic timescales of variability, such as the 12.42-hour and 

•-14-day tidal periods; the diel (24 hours) light cycle; 2- 

to 5-day storm events of enhanced streamflow and wind 

stress; seasonal cycles of irradiance and temperature; 

and the pronounced interannual variability of river flow. 

Therefore phytoplankton populations in SCEs are exposed to physical forcings that have timescales of variability ranging from hours to years: "a hierarchy of 

forcing functions which drive the various biological response mechanisms at different time and length scales" 

[Mackas et al., 1985, p. 653]. Each of these timescales can 

be identified in the population fluctuations of the phytoplankton. 

Biomass fluctuations at the short timescales can be 

measured with moored fluorometers that detect and 

record chlorophyll fluorescence at a fixed location. A 

sample record in Figure 3a shows a 2-week series of 

hourly measurements in south San Francisco Bay. The 

first week of the record shows periodic fluctuations in 

chlorophyll fluorescence over the semidiurnal tidal period, with chlorophyll peaks at the two low slack tides 

each day. This high-frequency variability is caused by 

tidal advection as chlorophyll spatial gradients oscillate 

over the sensor with the tide [Cloem et al., 1989]. Spectral analyses of such chlorophyll series confirm a high 

variance at the tidal frequencies [Litaker et al., 1993]. 

Short-term fluctuations can result from other processes 

such as diel cycles of chlorophyll synthesis and zooplankton grazing [Litaker et al., 1993] and wind-wave resuspension of algal cells off the bottom [Demers et al., 1987; 

de Jonge and van Beusekom, 1995]. The second half of 

the record in Figure 3a shows a 6-day period of exponential chlorophyll increase. Here the semidiurnal tidal 

variability is overwhelmed by the rapid growth of phytoplankton biomass along the entire channel; this period 

of the record illustrates daily-scale variability during a 

bloom event. Day-to-day fluctuations in phytoplankton 

biomass or physiological condition are commonly associated with hydrologic-meteorologic events, such as rainfall pulses, wind events, or periods of abrupt warming 

[C6t• and Platt, 1983], and with fluctuations in tidal 

mixing over the neap-spring period [Sinclair et al., 1981; 

Cloem, 199 lb ]. 

Longer-term fluctuations of phytoplankton biomass 

are illustrated in Figure 3b, a series of monthly chlorophyll a measurements in north San Francisco Bay from 

1974 to 1995. Three scales of variability are evident in 

this record: a seasonal cycle with peak biomass during 

the low-flow summers, interannual variability with a 

damped summer bloom during years of extremely high 

river flow and short residence time (e.g., 1983), and an 

apparent permanent change in the nature of the record, 

with the virtual disappearance of summer blooms after 
34, 2 / REVIEWS OF GEOPHYSICS Cloern' COASTAL PHYTOPLANKTON BLOOMS ß 137 

40 

•ø• 30 

o (D 

oo 20 

'• 10 

0 

Semi-diurnal 

_ variability ' Y 

1 2 4 5 7 8 

i i i i i i 

•--"•----'-----':•;% daily variability F 

• ' - ofa ,bo•t •,)• - 

9 10 11 12 13 14 15 

March, 1995 

b 

'• 4o,-- Seasonal Interannual , ""'"':•:•:•• •"•'....'••:• 

• / variabili• variabili I 

• 30 - 

o 20 

• persistent . - 

e 10 

o 

1976 1978 198o 1982 1984 1986 1988 199o 1992 1994 1996 

Figure 3. Some timescales of phytoplankton biomass variability in San Francisco Bay. (a) A 14-day record 

of hourly measurements with an in situ fluorometer placed 2 m above the bottom near station 28 in south San 

Francisco Bay (Figure 5); the fluorometer was calibrated with discrete chlorophyll a measurements made at 

the beginning and end of the record (fluorometer data from D. A. Cacchione, personal communication, 1995). 

(b) A 21-year record of monthly (or semimonthly) measurements of surface chlorophyll a concentrationear 

station 5 in north San Francisco Bay (Figure 1); this record includes data from the California Department of 

Water Resources (1974-1986) and USGS (1986-1995). 

the North Bay was colonized in large numbers by the 

clam Potamocorbula amurensis in 1987. Jassby and Powell [1994] examined a period of this chlorophyll record 

and concluded that most of the interannual variability is 

driven by two hydrodynamic processes, one associated 

with fluctuations in river flow (a natural source of variability), and one associated with managed diversions of 

fresh water from the upper estuary (an anthropogenic 

source of variability). 

Spatial variability (patchiness) is also observed across 

a spectrum of scales [Mackas et al., 1985]. Phytoplankton 

patchiness can be measured with continuous profiles of 

chlorophyll fluorescence along horizontal transects [Wilson and Okubo, 1980; Childers et al., 1994; A.D. Jassby 

et al., Towards the design of sampling networks for 

characterizing water quality changes in estuaries, submitted to Estuadne, Coastal, and Shelf Science, 1996]. 

Horizontal variability in south San Francisco Bay is 

illustrated in Figure 4, which shows the spatial structure 

of chlorophyll fluorescence along a longitudinal channel 

transect (Figure 4a) and along a transverse transect 

between the channel and adjacent shallows (Figure 4b). 

The longitudinal profiles show measurements spaced 

every 25 m, and variability is evident even at this small 

spatial scale. This small-scale variability is superimposed 

onto larger-scale patterns (mesoscale variability) that 

often show trends of decreasing chlorophyll fluorescence 

in the seaward direction (February 28, 1995; Figure 4a) 

and increasing chlorophyll across the shallows (March 

21, 1985; Figure 4b). Both small-scale and mesoscale 

patchiness are influenced by hydrodynamic processes 

because the plankton are transported by their fluid environment [Mackas et al., 1985]. Therefore the spatial 

variability patterns, both of chlorophyll biomass and of 

individual species [e.g., Kononen et al., 1992; Zingone et 

al., 1995], are shaped by the turbulent advective transports of phytoplankton within a spatially variable growth 

environment. These features of spatial structure are not 

stable or persistent. The mesoscale trends change from 

season to season [Glibert et al., 1995] and day to day 

[Wilson and Okubo, 1980], while the small-scale variability changes over the tidal period [Dustan and Pinckney, 

1989]. 

Figures 3 and 4 show that phytoplankton biomass in 

shallow coastal ecosystems varies at timescales from 

hours to decades and at spatial scales from tens of 

meters to tens of kilometers. Levin [1992] suggests that 

the central problem in ecology is the problem of pattern 

and scale, where pattern is the description of spatial or 

temporal variability and the mechanisms of pattern formation are scale-dependent. Therefore studies of population fluctuations such as phytoplankton blooms require 
138 ß Cloern' COASTAL PHYTOPLANKTON BLOOMS 34 2 / REVIEWS OF GEOPHYSICS 

• 50 A • "•B•-:•:•.•__• • • • ] 

,T 40 

'• 30 

Fa 20 

• •0 

05 10 15 20 25 30 35 40 

b 

50 • • • • D 

40 

30 

20- - 

10 

c 

o • • • i • 

o 2 4 6 8 lO 12 

Distance (kin) 

Figure 4. Horizontal variability of phytoplankton biomass from continuous measures of chlorophyll fuorescence along (a) longitudinal transects and (b) a lateral transect of south San Francisco Bay. Near-surface 

water was pumped to a shipboard fluorometer that was calibrated with 6-10 discrete measurements of

chlorophyll a concentration taken along each transect. Inset maps show locations of the transects. 

explicit choices about the scales at which population 

variability can be observed and explained. The long-term 

observational program in San Francisco Bay was designed to characterize mesoscale spatial variability along 

the longitudinal axis, at timescales of weeks to years. 

Even though (large) population variance exists at other 

scales, the data set described below is not appropriate 

for analysis of the small-scale fluctuations illustrated in 

Figures 3 and 4. 

The South San Francisco Bay Data Set 

Patterns of Variability. South San Francisco Bay 

has been the site of focused research on phytoplankton 

122030 ' 

.:.:.-......:• 

Central 

Bay...._ 

37045 ' 

37o30 ' 

122ø15; ' 122000 ' 

Figure 5. Map of south San Francisco Bay showing locations of fixed sampling stations along the 

longitudinal channel. 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 139 

Table 4. Phytoplankton Species Commonly Observed 

During Spring Blooms in South San Francisco Bay 

Class Species 

Diatomophyceae 

Chlorophyceae 

Chrysophyceae 

Cryptophyceae 

Dinophyceae 

Prasinophyceae 

Photosynthetic 

ciliates 

Diatoms 

Chaetoceros debile 

Chaetoceros decipiens 

Chaetoceros didymus 

Chaetoceros gracilis 

Chaetoceros socialis 

Chaetoceros vistulae 

Chaetoceros wighami 

Coscinodiscus curvatulus (Actinocyclus 

curvatulus) 

Coscinodiscus lineatus (Thalassiosira 

leptopus) 

Coscinodiscus radiatus 

Cyclotella meneghiniana 

Cyclotella sp. 

Cyclotella striata 

Ditylum brightwelii 

Eucampia zoodiacus 

Leptocylindrus minimus 

Nitzschia seriata (Pseudo-nitzschia seriata) 

Paralia sulcata 

Rhizosolenia setigera 

Skeletonema costatum 

Thalassiosira decipiens (Thalassiosira 

angulata) 

Thalassiosira rotula 

Nondiatoms 

Chlorella marina 

Chlorella salina 

Monoraphidium convolutum 

Nannochloris atomus 

Chromulina sp. 

Kephyrion sp. 

Ochromonas sp. 

Chroomonas acuta ( Teleaulax acuta )

Chroomonas amphioxeia (Teleaulax 

amphioxeia ) 

Chroomonasalina (Rhodomonasalina) 

Gonyaulax tamarensis (Alexandrium 

ostenfeldii) 

Heterocapsa triquetra 

Katodinium rotundatum 

Prorocentrum minimum 

Protoperidinium claudicans 

Pyramimonas micron (or P. orientalis) 

Tetraselmis gracilis 

Mesodinium rubrum 

From samples taken during 1992-1995 and microscopic enumerations/identifications of R. G. Dufford (personal communications, 

1992-1995). Names in parentheses are revisions based on the taxonomy of Tomas [1993, 1996]. 

bloom dynamics because it has a recurrent, somewhat 

predictable period of rapid biomass increase during the 

spring months. This lagoon-like basin has an irregular 

bottom topography with sharp bathymetric transitions 

between the 10- to 25-m-deep axial channel and the 

lateral shallows (Figure 5), and a large transverse shoal 

(San Bruno) that slows horizontal exchanges between 

the seaward and landward estuary. Local streams carry 

runoff to the lower (landward) estuary. The open connection to the central bay allows fresh water from the 

Sacramento and San Joaquin Rivers to intrude into the 

south bay during periods of high river flow (Figure 1) 

and allows tidal exchange between the South Bay and 

coastal ocean. The basin's residual (tidally averaged) 

circulation is slow, with mean seaward flow along the 

eastern shallows and landward flow along the channel 

[Cheng and Gartner, 1985] and a hydraulic residence 

time of several months [Walters et al., 1985]. This weak 

mean circulation can be disrupted by strong wind events 

or freshwater inputs that alter the strength and direction 

of the residual flows [Huzzey et al., 1990]. Water density 

is often vertically uniform, indicating rapid vertical mixing of the water column. The channel can become salinity stratified after periods of runoff that deliver lowdensity fresh water as a source of buoyancy, but 

stratification occurs only during neap tides when the 

tidal stirring is weak [Cloern, 1984]. Phytoplankton primary production is the largest source of organic carbon 

to south San Francisco Bay [Jassby et al., 1993], and 

much of the total annual primary production occurs 

during the spring [Cole et al., 1986]. 

The south San Francisco Bay spring bloom has been 

followed every year since 1978, and the patterns of 

variability within this series can be used to illustrate 

some general lessons of phytoplankton bloom dynamics 

in SCEs. The core measurement program.in south San 

Francisco Bay includes vertical profiles of salinity, temperature, chlorophyll (by calibrated fluorometry), and 

turbidity at sampling stations (Figure 5) spaced about 

every 3-4 km along the channel (detailed methods are 

given in annual data reports [e.g., Edmunds et al., 1995]). 

Water samples are also taken for microscopic examination to determine the abundance of phytoplankton species present during the spring blooms (Table 4). The 

sampling frequency in 1978-1979 was once monthly; 

after 1979 the sampling frequency was increased to once 

or twice weekly during the period of the spring blooms. 

Bloom dynamics are characterized here with the chlorophyll measurements made along the channel transect 

(Figure 5). Near-surface chlorophyll is used as a measure of biomass in the photic zone (i.e., the quantity that 

contributes to primary production), and vertical variability is not considered here. Lateral variability is also not 

considered, although there is coherence between the 

seasonal dynamics of phytoplankton biomass in the 

channel and adjacent shallows [Cloern and Cheng, 1981; 

Cloern et al., 1985; Vidergar et al., 1993]. Plate 2 depicts 

the chlorophyll fluctuations in south San Francisco Bay 

with color, and several prominent patterns of variability 

stand out. First, the solid background shows that biomass is usually less than 5 Ixg L- 1 chlorophyll a. Second, 

a period of rapid biomass growth (a bloom) occurs 

during the spring of every year. Third, bloom intensity is 

often greatest in the landward estuary, consistent with 

the trends in the high-resolution chlorophyll transects. 
140 ß Cloern' COASTAL PHYTOPLANKTON BLOOMS 34 2 / REVIEWS OF GEOPHYSICS 

Ba/• Bridge 

78 

San Mateo Bri%ge Dumbarton Bridge

8O 

82 

84 

• 86 

88 

9o 

92 

94 

0 5 10 15 20 25 30 35 

Distance along channel transect, in kilometers 

....... I.. I I I I I 

5 10 15 20 25 30 35 40 

Chlorophyll a 

Plate 2. Color representation of spatial-temporal variability of phytoplankton biomass (chlorophyll a 

concentration) in south San Francisco Bay. Blooms are shown as departures from the low background biomass 

(green), with bloom intensity proportional to color brightness. The vertical axis represents time from January 

1978 to July 1995, and the horizontal axis represents spatial variability along the channel transect from the 

seaward estuary (station 21) to the landward estuary (station 32). Color contours were produced from a matrix 

of interpolated values based on 4449 measurements of surface chlorophyll a concentration on 417 dates. 
34, 2 / REVIEWS OF GEOPHYSICS Cloern' COASTAL PHYTOPLANKTON BLOOMS ß 141 

1.0 

0.8 

0.6 

0.4 

0.2 

1.0 

0.8 

0.6 

0.4 

0.2 

PC1 = 52% of Variance 

21 22 23 24 25 26 27 

Station 

PC2 = 35% of Variance 

28 29 30 31 32 

Figure 6. Coefficients (loadings) of the first 

two principal components, which account for 

87% of the chlorophyll variance along the 

south San Francisco Bay transect, for the 

period January 1978 to July 1995. Principal 

component analysis was done on •he correlation matrix, and results are varimax-rotated 

solutions [Jassby and Powell, 1990]. This analysis suggests two independent spatial modes 

of phytoplankton biomass variability: one 

(PC1) in the landward estuarine basin south 

of station 25, and a second (PC2) in the 

seaward estuary north of station 25. 

Finally, the nature of the spring bloom changes from 

year to year. For example, the 1986 spring bloom was a 

monthlong event of very high chlorophyll concentration 

(maximum >70 !xg L -•) along the entire transect. The 

1991 spring bloom was a short-lived event confined to 

the landward estuary, where maximum chlorophyll concentration was only 12 !xg L -•. The patterns revealed in 

this image illustrate two lessons that apply generally to 

shallow coastal ecosystems: (1)phytoplankfon blooms 

are spatially heterogeneous, and (2) the timing and 

magnitude of the seasonal blooms change from year to 

year. 

The patterns of population variability in time and 

space can be formalized with multivariate techniques 

such as principal components analysis (PCA). If we 

consider measurements at sampling stations as variables, 

and sampling dates as individual cases, then PCA can 

reveal patterns of spatial coherence in the temporal 

fluctuations of biomass along a transect. This PCA of the 

south San Francisco Bay data set identifies two principal 

components that together account for 87% of the total 

chlorophyll variance. The first principal component 

(PC1), which accounts for 52% of the chlorophyll variance, has small coefficients (or loadings) at the seaward 

stations and progressively larger coefficients at the landward stations (Figure 6). The second component (PC2), 

accounting for an additional 35% of the variance, has 

largest coefficients at the seaward stations. This PCA 

shows that most of the phytoplankton biomass variability 

in south San Francisco Bay can be explained with only 

two spatial modes (patterns): the first is expressed 

strongly in that region of the estuary landward of station 

25, and the second is expressed strongly in the region of 

the estuary seaward of station 25 (Figure 6). This separation of the two spatial modes at station 25 corresponds 

to the location of the San Bruno Shoal (Figure 5), a 

topographic control of horizontal mixing. The tidally 

averaged circulation of south San Francisco Bay is characterized by a slowly rotating gyre that acts to retain fluid 

within the central basin of the estuary, below the San 

Bruno Shoal [Cheng and Casulli, 1982]. The PCA result 

is consistent with this mean circulation that maintains 

two spatial domains separated by a topographic control 

of mixing [Powell et al., 1986]. This lesson applies to 

other coastal ecosystems where the mesoscale spatial 

variability of plankton reflects the water circulation patten [Jouffre et al., 1991] and where distinct spatial domains can have different temporal patterns of bloom 

evolution [Therriault and Levasseur, 1986; Kahru and 

Nbmmann, 1990; Glibert et al., 1995]. 

A second result of PCA is the series of scalar amplitudes (or scores) that express the relative importance of 

each principal component over time [Jassby and Powell, 

1990]. Figure 7 shows the time series of amplitudes for 

PC1. This series is a representation of pattern in the 

temporal variability of phytoplankton biomass in the 

landward basin. This temporal pattern is dominated by 

episodic spikes that occur in the spring of each year, with 
142 ß C!oern' COASTAL PHYTOPLANKTON BLOOMS 34, 2/REVIEWS OF GEOPHYSICS 

'•' 30 

o•.•, :20 

lO 

I I I I I I I I I I I I 

6 

m 

m 

E 1-- 

0 m 

_1 m 

_2 / 

78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 

Year 

Figure 7. (bottom) Time series of amplitudes 

(scores) for the first principal component of 

chlorophyll variability in south San Francisco 

Bay. Large amplitudes correspond to events of 

high phytoplankton biomass (blooms) in the 

landward estuary. (top) Parallel series of nearsurface salinity in the landward estuary (mean 

of measurements at stations 26-32), illustrating that blooms occur during the wet season of 

high river flow and annual salinity minima. 

prominent year-to-year fluctuation in the timing, duration, and magnitude of these spikes. 

Mechanisms of variability. The series of principal 

component amplitudes in Figure 7 is consistent with the 

notion of phytoplankton blooms as departures from 

population quasi-equilibrium. Blooms are population 

outbursts that can appear and dissipate within a period 

of weeks. What determines the timing of these outbursts, 

their duration, and their magnitude, and why do these 

features change from year to year? The two series in 

Figure 7 show that blooms occur in south San Francisco 

Bay during the wet season, when surface salinity is 

diluted by fresh water. This seasonal coherence between 

bloom development and low salinity results, in part, 

from the stabilization of the water column by the salinity 

stratification induced by freshwater inflows [Cloern, 

1991a, hi. The absence of blooms in summer-autumn is 

also a response to the seasonal cYCles of the benthic 

suspensiOn-feeding animals, whose biomass and grazing 

rate are highest in summer. Therefore the seasonal 

distribution of blooms in this particular estuary appears 

........ 1 • _• _ •._ .... 

to be a response to seasonat nuctuatlons in nyurmogy 

(river flow and its influence on density stratification) and 

trophic interactions (grazing losses to benthic consumers). 

At shorter timescales, too, the timing of blooms is 

regulated by physical processes that influence the balance between phytoplankton production and losses. 

Simulation experiments with numerical models show 

that this balance is sensitive to the rate of vertical mixing 

in the water column [Cloern, 1991b]. Vertical mixing is 

brought about by tidal stresses applied at the bottom and 

wind stresses on the water surface [Simpson et al., 1991], 

and in mesotidal SCEs the tidal stresses often dominate. 

Weak tidal stirring promotes blooms by (1) slowing the 

turbulent diffusive loss of phytoplankton biomass from 

the photic zone [Koseff et al., 1993], (2) deepening the 

photic zone (growth habitat) as tidal resuspension of 

bottom sediments weakens [Schoellhamer, 1996], and (3) 

reducing the vertical flux of phytoplankton to benthic 

consumer animals [Cloern, 1991b]. Blooms develop during periods of weak tidal energy, and they dissipate 

during periods of strong tidal energy. This lesson is 

illustrated in Figure 8, which shows the evolution of the 

1985 spring bloom and the simultaneous changes in the 

daily tidal current amplitude U. Rapid biomass (chlorophyll) growth occurred during the neap tide in late 

March; this bloom dissipated soon after the subsequent 

spring tide in early April. 

The association between weekly-scale chlorophyll 

vanatomy and the uuax re -me •s a prominent ........ of 

phytoplankton population dynamics in south San Francisco Bay. This association is illustrated in Figure 9, 

which shows a linear relationship between the rate of 

biomass change and the antecedent tidal current speeds 

for all the large spring blooms observed between 1978 

and 1995. The rate of biomass change, R, was calculated 

as 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 143 

0.7 

0.6 

0.5 

0.4 

I I I I I I I 

30 / 

20• 

10 / 

.e' 

I ' I 

79-,%b 10-/l•a r 

I 

20-1•ar 

' I 

30-graf 

1985 

I I 

19-4,0 r 

Figure 8. The 1985 spring bloom in south 

San Francisco Bay: (bottom) weekly fluctuations of phytoplankton biomass in the landward estuary (mean chlorophyll a concentration at stations 26-32) and (top) daily 

fluctuations in the tidal current amplitude U. 

Current amplitudes were computed from 

tidal harmonic constants derived from longterm current measurements in the central 

south bay channel [Cheng and Gartner, 1985] 

(predicted U from J. W. Gartner (personal 

communication, 1995)). Biomass increased 

rapidly after March 20, when U was less than 

0.5 ms -•. 

0.2 • 

0.1 / 

0.4 

ß 'e89 4 

95 

0.5 0.6 

Mean Current Amplitude U 7 (m/s) 

0.7 

Figure 9. Tidal forcing and phytoplankton 

blooms in south San Francisco Bay. The net 

rate of biomass change, R, was calculated 

from the week-to-week changes in mean 

chlorophyll a concentration in the landward 

estuary (stations 26-32). The tidal regime is 

represented by the 7-day mean current amplitude, U7. Points represent all the weeklyscale events of 1978-1995 in which the 

mean chlorophyll a concentration fell below 

or increased above 10 Ixg L- • (updated and 

revised from Figure 4 of Cloern [1991b]). 

The dashed line is the least squares regression of R against U7 (r = 0.66). Deviations 

around this regression in 1983, 1989, 1990, 

and 1995 are examined in Figures 10-13 to 

illustrate other mechanisms of bloom variability. 
144 ß Cloern' COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

Distance (km) 

0 10 20 30 40 

10 "•:•' .......... .•i?.'ii•!,?,•i,•. .... 

15 -.:: ........... :?.-:- 

20- 

>26 

5 - 

24 22 20 18 16 14 <13 

.. ::: !::!::•::-'::•!::•!:[i::!i!i::!!::i!:: ............ •i•...•....•.•.•i[•[i[•:....•:....•...i!•!!•...•..•i•i•i;..•.•!i;..•i i•ii!•:-:i --• 

Salinity •i!',!!!?.'!:!:i!..: ........ ?'""•:'"'"•1 

>28 27 25 

i ...' ".'.:..:.::...::..:..::....:::•:. ß •...... -: "- ..:--.......-•ii ::.- .......•::-:: .;•-. :•:•: ::::d: :•::::-::. .:. . . 

. 

ß 

10- ;. i•i•!•:?•!•ii•i•i•:ii?•!•i•; ..... '... 10 

15 - 15 

20 - 20 

Distance (km) 

O0 10 20 30 40 

g'-.2j:•-•i!::iii•:'"----:-'---•::-.... "-'•il;-":g•i:•iiii?::::1111iii'#.. .";':'::!iii!::i::iii::i::i::::::i:" ".:i...:'•i•;;--':.-i•.. :ii!::i•i::i:;::i•!• ':• 

!•;•i•.g•.:•i•:;..i.•.....•.•`..i•;•`..•.•.....?.`:.:..•i•i•':":•1⁄2i•i•.' •:"•-"•:•i[?-::.-'i-'•.'.'• :':!•i•i![!•i•i!::i•i.:-::!..:-•:i•::::: !:•.• ....... - ........... 

20 

432<1 

Mar-May River Flow (m3/s) 

5000 3000 1000 0 

i i i i 1978 

1980 

1982 

1984 

1986 

1988 

1990 

1992 

Figure 10. Sectional (vertical-longitudinal) contour plots of the (left) salinity and (right) chlorophyll a 

distributions along the south San Francisco Bay channel, going from the seaward (station 21) to landward 

(station 32) estuary. Top panels show strong vertical gradients in May 1983 following a period of exceptionally 

high river discharge. Bottom panels show vertical homogeneity in May 1989 that is representative of the 

estuarine condition after periods of lower river flow. The mean freshwater inflow to north San Francisco Bay 

(Delta Outflow Index, from the California Department of Water Resources) for the months March-May is 

shown at far right. The spring of 1983 was the wettest in this century. 

R = In [Bt+/,t/B t]/At (4) 

where n t+At is biomass (mean chlorophyll a in the 

landward estuary) at time t + At; B t is biomass at 

previous time t; and R(1/d) is the specific rate of biomass change over time increment At. The rate R represents the net result of all the processes of biomass 

change. This net rate is inversely related to the tidal 

current amplitude averaged over the previous week, U7 

(Figure 9). The distribution of points in Figure 9 shows 

that the biomass change R was always positive (i.e., a 

bloom developed) when U7 was less than 0.5 m s-•: 

phytoplankton biomass increased during extremely weak 

neap tides. Conversely, R was always negative when U7 

exceeded 0.6 m s-•: blooms dissipated during the highly 

energetic spring tides. For tidal regimes between these 

extremes, R was either positive or negative: blooms can 

either grow or dissipate at intermediate tidal energies. 

The linear relation between R and U 7 suggests that 

the timing of bloom inception is set by the astronomical 

tides. However, deviations around this linear relation 

are large, especially at the intermediate tidal regimes 

(Figure 9), so other processes must come into play. The 

individual deviations around the linear relation between 

R and U7 can reveal some of these other mechanisms of 

population variability. As an example, the rate of biomass growth during May 1983 was much larger than that 

predicted from the tidal regime alone (see Figure 9). 

This positive deviation (+R) from the linear model can 

be explained by the unusual hydrography of 1983: exceptionally high river flow and strong salinity stratification that persisted into May (Figure 10). The intense 

stratification observed in May of 1983 (but not other 

years) stimulated rapid biomass increases in the surface 

layer. The combined effects of large buoyancy input plus 

weak tidal stirring created an unusually stable water 

column and unusually large blooms during 1983 (Figure 

7). Therefore the year-to-year fluctuations in spring 

bloom magnitude are determined partly by annual fluctuations in precipitation and river flow, with exceptionally large blooms (1982, 1983, 1986, 1995) during years 

of exceptionally high river flow [Cloern and Jassby, 1995]. 

Climate can modulate the development of blooms in 

other ways. The positive growth rate deviation (+R) in 

1990 occurred during a period of unusually calm winds 

in late March and early April (Figure 11), when the 

bloom magnitude was amplified by the small inputs of 

mixing energy at the surface [Koseff et al., 1993]. On the 

other hand, the negative growth-rate deviation (-R) in 

1989 followed an event of strong westerly winds that 

--1 persisted for several days. Westerly winds of 10 rn s 

generate a seaward flow along the channel at speeds up 

to 10 km d -1 [Walters, 1982; Cheng and Casulli, 1982]. 
34, 2 / REVIEWS OF GEOPHYSICS Cloern' COASTAL PHYTOPLANKTON BLOOMS ß 145 

0.7 

0.6 

0.5 

0.4 I I I I I 

30 

20 / 

10• 

o 

2o-•ar •o-•ar 9',q•r 

1990 

Figure 11. The 1990 spring bloom 

in south San Francisco Bay. (bottom) 

Weekly changes in chlorophyll a concentration in the landward estuary 

(dashed line) and daily fluctuations in 

mean wind speed (solid line). The 

horizontal line shows the long-term 

mean wind speed for March-April 

(5.6 m s-•). (top) The 7-day running 

mean tidal current amplitude U?. A 

period of unusually rapid biomass increase (+R) occurred in early April, 

following 2 weeks of unusually calm 

winds. 

Therefore the negative deviation in early March 1989 

(Figure 12) was probably the result of wind-driven 

pulsed flows that carried phytoplankton biomass away 

from the landward estuary, coupled with the negative 

effects of rapid vertical mixing by the surface wind stress. 

The negative growth rate deviation (-R) in 1995 

illustrates another mechanism of bloom regulation. The 

1995 spring bloom began in late February, and high 

biomass persisted for over a month. This period of 

sustained high biomass led to a steady depletion of 

dissolved inorganic nitrogen (Figure 13) as the phytoplankton assimilated nutrients faster than they were 

replaced by inputs and regeneration. By late March the 

initial high stock of dissolved inorganic nitrogen was 

exhausted, and the potential rate of further biomass 

production became limited by the availability of N. As a 

result, the phytoplankton biomass declined rapidly in 

early April. This example illustrates that phytoplankton 

biomass production can be episodically nutrient limited, 

even in SCEs that receive large inputs of nutrients. 

A Synthetic Picture of Bloom Mechanisms 

This detailed analysis of chlorophyll variability in 

south San Francisco Bay leads to a general picture of 

how the timing and magnitude of the spring bloom 

change from year to year. The proximal agents of blooms 

are changes in the physical state of the estuary as determined by inputs of energy at the interfaces with the 

coastal ocean, rivers, and the atmosphere (Figure 14). 

Tides originate in the ocean, propagate into the estuary, 

and influence turbidity and light availability for photosynthesis (through tidal resuspension of bottom sediments), the intensity of turbulent mixing, and the patterns of horizontal circulation. The strength of the tidal 

forcing fluctuates, and episodes of minimal tidal energy 

occur within each neap-spring and lunar monthly period. 

The monthly minimum tides create a physical condition 

that promotes bloom developmenthrough several different mechanisms, and these periods of weak tides 

provide windows of opportunity for the phytoplankton 

population to grow. The timing of potential bloom development is set by the astronomical tides and is therefore 

predictable in estuariesuch as south San Francisco Bay. 

The degree to which phytoplankton populations can 

respond to the tidal windows is determined by hydrology, weather, nutrient availability, and the activity of 

consumer organisms. River flow delivers fresh water that 

establishes density-driven circulations, and it is a source 

of buoyancy to stratify the water column and inhibit 

vertical mixing. If freshwater buoyancy inputs are large 

enough to offset the effects of tidal and wind stirring, 

then the water column remains stratified for a sufficiently long period that phytoplankton biomass can grow 

and reach high levels. Other sources of buoyancy, such 

as rapid heating of the surface layer during periods of 

calm, stable weather, can have the same effect. Winds 
146 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

0.7 

0.6 

0.5 

0.4 

3o 

2o 

lO 

9"c'eb 19.F.eb •9.F.eb 10.•ar •O'•a r 30'•ar 

1989 

12 

lO• 

8 _m. 

6 • 

4• 

Figure 12. The 1989 spring bloom 

in south San Francisco Bay. (bottom) 

Weekly changes in chlorophyll a concentration in the landward estuary 

(dashed line) and daily fluctuations in 

mean wind speed (solid line). The 

horizontal line shows the long-term 

mean wind speed for March-April 

(5.6 m s-•). (top) The 7-day running 

mean tidal current amplitude U7. 

The rapid biomass decline (-R) in 

early March followed a storm when 

daily wind speeds exceeded 12 m s-•. 

further influence the development of blooms by altering 

the circulation patterns and transport of phytoplankton, 

turbidity and the light climate (through wind-wave resuspension of bottom sediments), and the breakdown of stratification and enhancement of vertical mixing (Figure 14). 

The magnitude of the spring bloom in south San 

Francisco Bay is set by the initial stocks of nutrients 

required for biomass production, the water circulation 

pattern as it determines phytoplankton residence time 

within the estuarine basin, the potential losses to pelagic 

and benthic grazers, and the particular combination of 

climatic-hydrologiconditions during the tidal windows 

30-- 

20-- 

_ 

lO-- 

9-F'eb 19.F.eb '•9.F.eb 

6-6 

10-•a r •O-•a r 30-•a r 9-•i1• r 

1995 

-- 5O 

40 ---• 

Z 

o 

•30• 

o 

20:3 

• 10 

Figure 13. The 1995 spring bloom 

in south San Francisco Bay. The 

dashed line shows the weekly fluctuations in mean chlorophyll a concentration in the landward estuary (stations 26-32); the solid line shows 

parallel changes in the concentration 

of dissolved inorganic nitrogen (DIN 

= nitrate + nitrite + ammonium). 

The event of unusually rapid biomass 

decline (-R) in_ earl_y April occurred 

after the large initial stock of inorganic nitrogen became depleted. Nutrient data from S. W. Hager (personal communication, 1995). 
34, 2 / REVIEWS OF GEOPHYSICS Cloern' COASTAL PHYTOPLANKTON BLOOMS ß 147 

River Inflows 

... 

Figure 14. Cartoon diagrams of three physical forcings that operate at the interface between SCEs and the 

coastal ocean (tides), watershed (river inflow), and atmosphere (wind). Each physical forcing influences the 

growth rate of the resident phytoplankton population through, for example, its influence on the distribution 

of suspended sediments and turbidity. Each forcing also influences the rate of vertical mixing, with riverine 

inputs of fresh water as a source of buoyancy to stratify the water column and the tide and wind as sources 

of kinetic energy to mix the water column. Each forcing is also a mechanism of water circulation that 

transports phytoplankton horizontally. Much of the variability of phytoplankton biomass during blooms can be 

understood as responses to fluctuations in these interfacial forcings. 
148 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 

OCEAN RIVER 

ß 

Small pelagic 

Reactive heterotrophs 

inorganic ..... Inver/ebrate Metazoan 

substances ,.,,.•a,•c•..,. Consumpt,o_•=,• larvae. copepods. food

"'• ............. rotifers etc CO 2,NH 3, I Uptake , .... ••""•"•' ,' ' chan 

uo.Po.. I ; I I•hytøp 'anktøn r•:cretio, Si04, S04, [ Regenemt•oon ] [ •,LVsis . . ,. I Bacieria 

Fe, Cd, etc I '•'"- I I nl--• Upt_akel •, I .......... 

' ' I I I ..... •'--•1 Fla•ellateslfood 

• Consumption Sedimentation I 

34, 2 / REVIEWS OF GEOPHYSICS 

Figure 15. Schematic illustrating the 

central role of phytoplankton as agents 

of biogeochemicalhange in shallow 

coastal ecosystems. Phytoplankton assimilate reactive inorganic substances 

and incorporate these into particulate 

(POM) and dissolved organic matter 

(DOM) which supi•ort the production of 

pelagic and benthic heterotrophs. Arrows indicate some of the material fluxes 

between these different compartments. 

of potential population growth. Blooms are biological 

responses to physical variability [Paerl, 1988], where the 

timescales of bloom variability are set by the timescales 

of the prominent physical forcings [Legendre and Demers, 1984]: semidiurnal, daily, and weekly tidal fluctuations; seasonal, episodic, and interannual fluctuations in 

river flow; and seasonal and event-scale fluctuations in 

wind stress. 

LINKAGES OF PHYTOPLANKTON TO THE 

BIOGEOCHEMICAL SYSTEM 

The preceding section presented the patterns and 

mechanisms of phytoplankton bloom variability in San 

Fi'ancisco Bay to illustrate the strong linkages between 

the climate System, hydrologic cycle, and biological populations in the coastal zone. Here we explore the geochemical and ecological implications of these phytoplankton population fluctuations. Geochemists and 

ecologists use mass balances to describe the dynamical 

nature of the systems they study. Figure 15 is an example 

showing some of the linkages between the phytoplankton and other components of estuarine-coastal ecosystems. This diagram shows exchanges between five pools 

of matter: reactive inorganic substances (RIS; see Table 

5) that are transformed by biogeochemicai processes; 

particulate organic matter (POM), which includes phytoplankton, detritus, and organic matter sorbed onto 

suspended sediments; dissolved organic matter (DOM) 

including metabolites produced by phytoplankton and 

released into the water; and populations of the pelagic 

and benthic consumer organisms (heterotrophs) that u•e 

phytoplankton-derived organic matter for their nutrition. 

Phytoplankton are linked to the pool of reactive inorganic substances through their uptake and assimilation of C02 and the other raw materials required for 

photosynthesis and the biosynthesis of new phytoplankton biomass. Heterotrophs are linked to the phytoplankton either through their direct consumption of live algal 

biomass or their consumption/assimilation of algal-derived detritus or DOM. Phytoplankton consumption occurs in the water column, by pelagic heterotrophs, and in 

the sediments, by benthic heterotrophs (Figure 15). The 

heterotrophs are not perfectly efficient at transforming 

food into new biomass, so their feeding and metabolic 

activities return a portion of the ingested organic matter 

back to the RIS or DOM pools (the process of regeneration or remineralization). 

Although the pools of reactive materials and their 

Table 5. Frequently Used Acronyms and Abbreviations 

Abbreviation Definition 

DIC 

DIN 

DOC 

DOM 

DRP 

DSi 

•13 C 

813C POM 

•15 N 

PCA 

P'C1, PC2 

PC. 

PC:PN 

PN 

POM 

PP 

PUFA 

RIS 

SCE 

SPM 

U 

dissolved inorganic carbon (all species of 

CO2), mM 

dissolved inorganic nitrogen (total of NO•-, 

NO•-, NH•-), • 

dissolved organic carbon 

dissolved organic matter 

dissolved reactive phosphorus, IdF/ 

dissolved silicate, I•M 

measure of the ratio •3C: •2C relative to a 

Standard, %o 

measure of the ratio 13C: 12C in the 

particulate organic matter, %0 

measure of the ratio 15N: •4N relative to a 

standard, %o 

principal Component analysis 

first and second principal components 

particulate carbon, pog L-• 

ratio of particulate carbon to particulate 

nitrogen, mol mol- • 

particulate nitrogen, •g L -• 

particulate organic matter 

particulate phosphorus 

polyunsaturated fatty acids 

reactive inorganic substances 

shallow coastal ecosystem 

suspended particulate matter, mg L- • 

tidal current speed amplitude, m s -• 
34, 2 / REVIEWS OF GEOPHYSICS Cloern' COASTAL PHYTOPLANKTON BLOOMS ß 149 

linkages are more complex than is suggested in Figure 

15, this diagram illustrates how phytoplankton primary 

production acts to transform inorganic substances into 

organic matter. This newly produced organic matter 

exists in forms that are readily available to consumer 

organisms. Thus phytoplankton primary production is a 

key process in both the cycling of reactive elements and 

in trophic dynamics (the transfers of matter and chemical energy between organisms). These transformation 

processes operate continuously, but they are not easily 

observed when the rates of RIS uptake and regeneration, or the rates of phytoplankton production and consumption, are balanced. These balances are disrupted 

during phytoplankton blooms, when the rate of primary 

production temporarily exceeds the rate of consumption. Blooms ar• biological events that cause large geochemical changes (transformations of RIS into POM or 

DOM), followed by accelerated consumption and metabolism of organic matter by the heterotrophs. Therefore all the roles played by phytoplankton in element 

cycling and trophic dynamics are amplified during 

blooms. This central role of the phytoplankton can be 

illustrated with some geochemical and biological responses to the spring blooms observed in south San 

Francisco Bay. 

Phytoplankton biomass in south San Francisco Bay is 

low except during the spring blooms, when chlorophyll 

concentrations exceed 10 Ixg L -• and reach peaks in the 

range of 50-70 Ixg L -• (Figure 16a). Phytoplankton 

primary productivity istypically <0.5 g C m -2 d -1, 

except during the spring blooms when the rate of production can exceed 1g C m -2 d- 1 and reach peaks of the 

order of 2-3 g C m -2 d -• (Figure 16b). Primary productivity is a measure of the rate at which new organic 

matter is produced and made available to the heterotrophs, and rates of other biological processes (in composite, the system metabolism) accelerate as a response 

to these new inputs of food. This response is seen, for 

example, in the production rate of pelagic bacteria, 

which peaks during March-April (Figure 16c). Pelagic 

respiration (measured as oxygen consumption), an index 

of total microbial metabolism in the oxygenated water 

column, also peaks in spring (Figure 16d). These accelerated rates of biological activity are general responses 

to phytoplankton blooms: pelagic respiration is correlated with phytoplankton biomass and primary productivity [L. M. Jensen et al., 1990; Iriarte et al., 1991], and 

bacterial and primary productivity are tightly coupled in 

coastal ecosystems where phytoplankton are the dominant source of labile organic matter [Lancelot and Billen, 

1984; Billen and Fontigny, 1987; Cole et al., 1988; Lignell 

et al., 1993]. 

One consequence of the shallow water depth of SCEs 

is a close linkage between the pelagic and benthic domains. Food delivery to the benthos is enhanced during 

blooms, either by the active particle capture of suspensionfeeding macrofauna (e.g., bivalve mollusks, polychaete 

60 

'• 30 

,- 20 o 

lO 

a. Chlorophyll Biomass 

oO • 3 

:. • 2 

ß 

•11 FMAMJ J ASOND _ 0j 

b. Daily Primary Productivity ,, 

, ,-,* • .... • ,**, ',. 

FMAM J J A$OND 

Years 1990-1994 Years 1980,1991 and 1993 

c. Bacterial Productivity 

400 ' '

-q,, ~ 1990 bloom 

--- 300 

• 200Iß 

I •'1 ee ß . .., ..,,•. 

0j i•M A M ,• j A S (•1• D 

800 

600 

•400 

200 

0j 

d. Pelagic Respiration 

, , • 

1993 bloom 

ß 

Years 1988-1991 Year 1993 

Figure 16. Seasonal distributions of phytoplankton biomass 

(as chlorophyll a) and three indices of system metabolism in 

south San Francisco Bay: (a) near-surface chlorophyll a concentrations (measurements between USGS stations 29 and 33 

for the years 1990-1994; data from Wienke et al. [1991, 1992, 

1993], Caffrey et al. [1994], and Edmunds et al. [1995]), (b) 

primary productivity (between USGS stations 27 and 32 for the 

years 1980, 1991, and 1993; data from Cole and Cloern [1984, 

1987] and B. E. Cole (personal communication, 1993)), (c) 

pelagic bacterial productivity (between USGS stations 21 and 

36 for the years 1988-1991; data from Hollibaugh and Wong 

[1996]), and (d) pelagic respiration measured as oxygen consumption during 24-hour incubations of sample water in dark 

bottles (USGS stations 27 and 32 during 1993; data from 

Rudek and Cloern [1996]). 

worms, and crustaceans) or through the deposition of 

phytoplankton-derived POM onto the sediment surface. 

Blooms can terminate as mass sedimentation events 

triggered by resource depletion [Bienfang et al., 1982; 

Smetacek, 1985; Waite et al., 1992] or by the formation of 

dense algal aggregates [Riebesell 1991a, b; Jackson and 

Lochmann, 1992], leading to pulsed inputs of POM to 

the sediments [Riebesell, 1989; Lignell et al., 1993]. 

Benthic microbial and animal communities respond 

quickly to these events of enhanced food supply, leading 

to rapid acceleration of oxygen consumption and CO2 

and NH•- release from the sediments [Kelly and Nixon, 

1984; Hansen and Blackburn, 1992; Conley and Johnstone, 1995]. This direct coupling between benthic metabolism and phytoplankton dynamics gives rise to a 

general correlation between phytoplankton productivity 

and the rate of oxygen consumption in coastal marine 

sediments [Nixon, 1981; Dollar et al., 1991]. 

Much of the POM delivered to sediments is consumed through anaerobic pathways of metabolism, including those coupled to the bacterial respiration of 
150 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

a. Dissolved Oxygen 

i i I •i i i i i i i i i 

.-. 14 I •;ø - 

-- • 10 

•" • 

/ I I I I I I I 

J F M A M J J A S O N D 

b. Dissolved Inorganic Carbon, DIC 

i i i i i i i i i i 

- • 

øi 

990 bloom 

c. Nitrate 

Years 1993-1994 Years 1990-1992 Years 1990-1994 

d. Ammonium 

i i i i i i i i i i i 

I ß 

"i ' 

; : . :, 

ß .j.:l" !, t 'j ! i!1 I i 

D 

Years 1990-1994 

e. Silicate f. Phosphate 

•0 i ß ß 

: ß :.:.* ß ß i:- * , 

ß ß ß , '- I * :*;,:** 

ß • I : , : I0 :o •* • _1 • 10 * 

I I I I I I 

J J A S ON D Oj FM A M J J A S ON D 

Years 1990-1994 Years 1990-1994 

Figure 17. Seasonal distributions of some reactive inorganic substances in south San Francisco Bay: 

near-surfaceoncentrations of (a) dissolved oxygen (between USGS stations 29 and 33 for the years 1993 and 

1994; data from Caffrey et al. [1994] and Edmunds etal. [1995]), (b) dissolved inorganic carbon (between USGS 

stations 29 and 33 for the years 1990-1992; data from M. Huebner (personal communication, 1992)), and (c) 

NO•-, (d) NH•-, (e) DSi, and (f) DRP (between USGS stations 27 and 33 for the years 1990-1994; data from 

Hager [1993, 1994, also S. W. Hager, personal communication, 1995]). 

sulfate (the process of sulfate reduction, producing S-- 

from SO•--) or nitrate (denitrification, which produces 

gaseous N20 and N 2 from NO•-). Total benthic metabolism (combined anaerobic plus aerobic processes) can 

be measured as biogenic heat production in the sediments, and this index also accelerates in response to 

inputs of POM from phytoplankton blooms [Graf, 1992]. 

The geochemical implications of this benthic-pelagic 

coupling are that rates and pathways of element cycling 

in shallow coastal environments are strongly influenced 

by seasonal phytoplankton blooms. The rate of sulfate 

reduction in coastal sediments increases with phytoplankton primary productivity [IndrebO et al., 1979]. Sedimentation of diatom-derived POM leads to rapid increases in the flux of NH•- from sediments to the 

overlying water and a shift from net release to net 

consumption of NO•- in the sediments, because nitriffk,;i::l, U,,,XIU•tLIUII tlUJl [,Hllf,.;I UUli::tl of tO U 3 minD]lea iN INI-14 is 

while denitrification is stimulated by oxygen reductions 

that follow inputs of labile organic substrates [M. H. 

Jensen et al., 1990]. Similar linkages between N cycling 

and blooms have been established in south San Francisco Bay, where the production of NH•- in sediment 

porewaters increases more than tenfold during spring 

[Caffrey, 1995]. 

Dissolved Substances 

Even before Redfield's [1958] seminal paper, oceanographers recognized the importance of biological processes in changing the chemical composition of seawater. A key biological process of geochemical change is 

phytoplankton primary production (Figure 15), and the 

impact of this process is evident during blooms, when 

primary productivity exceeds the rates of remineralization processes. In south San Francisco Bay the concentration of dissolved oxygen is usually below 8 mg L- • and 

it is undersaturated with respect to atmospheric oxygen 

(Figure 17a). Exceptions occur in the spring, when the 

rate of photosynthetic oxygen production by phytoplankton exceeds losses from respiration and atmospheric 

exchange. During the spring blooms, dissolved oxygen 

becomes supersaturated in the water and reaches concentrations 50-60% higher than those at equilibrium 

with atmospheric 02. The CO 2 content of seawater Is 

large relative to the photosynthetic demand of phytoplankton, but sustained bloom events can lead to measurable decreases of dissolved inorganicarbon (DIC) 

[Nakatsuka et al., 1992]. In south San Francisco Bay the 

DIC concentration is usually in the range 2-2.2 mM, 

except during blooms, when photosynthetic uptake depresses DIC to about 1.85 mM (Figure 17b). This re- 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 151 

moval of CO2 leads to pH increases in the water, and 

seasonal fluctuations of pH are common responses to 

seasonal fluctuations in phytoplankton productivity 

[Hinga, 1992]. 

These large fluctuations in the inorganic carbon and 

oxygen content of the water are indications that the net 

ecosystem metabolism (balance between total photosynthesis by all primary producers and total community 

respiration) changes during phytoplankton blooms. Depletion of DIC and supersaturation of 02 indicate that 

community photosynthesis exceeds community respiration (the ecosystem is net autotrophic). Conversely, undersaturation of 02 and excess CO2 indicate that respiration exceeds photosynthesis (the ecosystem is net 

heterotrophic). The net metabolism is used as an integrative descriptor of coastal ecosystems as tranformers 

of reactive materials as they are carried from the land 

surface to the coastal ocean [Smith et al., 1991]. Although most assessments of system metabolism have 

been made as annual averages [Smith and Hollibaugh, 

1993], phytoplankton blooms can lead to large, episodic 

shifts from net system heterotrophy to net autotrophy 

[Relexans et al., 1988]. These episodic shifts in trophic 

state must be considered in the calculation of annual 

budgets of reactive elements such as C and 02. 

Phytoplankton blooms also give rise to large changes 

in the concentrations of dissolved inorganic nutrients. 

South San Francisco Bay receives continual inputs of 

nitrogen, phosphorus, and silica from treated sewage 

[Hager and Schemel, 1996], so the concentrations of 

dissolved inorganic nitrogen (DIN), dissolved reactive 

phosphorus (DRP), and dissolved silicate (DSi) are very 

high. In the landward estuary, nutrient concentrations 

during winter months usually fall in the following ranges: 

NO•- = 40-80 gM, NH•- = 10-15 gM, DSi = 70-130 

gM, and DRP = 5-10 gM. These concentrations are 

much higher than those typically seen in the open ocean, 

but they are representative of nutrient concentrations 

observed in estuaries and bays influenced by agricultural, riverine, and municipal inputs. The variability of 

inorganic nutrient concentrations in south San Francisco 

Bay is highest in spring (Figures 17c to 17f), and this 

nutrient variability is a result of the fluctuating uptake 

and assimilation of reactive inorganic substances around 

the timing of the spring blooms. As phytoplankton biomass increases, the winter stock of DIN can be almost 

completely depleted. Phytoplankton blooms also change 

the isotopic composition of the DIN because algal uptake of the light nitrogen isotope (14N) is faster than 15N 

uptake. As nitrate assimilation accelerates during a 

bloom, the residual pool of nitrate becomes enriched in 

lSN by this biological fractionation, especially inestuaries where phytoplankton uptake is the dominant NO•- 

sink [Horrigan et al., 1990]. Seasonal depletions of DSi 

reflect the spring bloom dominance by silica-requiring 

diatoms (Figure 17e), and although DRP is not completely depleted, minimum concentrations (• 1 g3//) occur during peaks of phytoplankton biomass. Nutrient 

concentrations (DIN, DRP, DSi) progressively increase 

during summer months, when phytoplankton productivity decreases and nutrient uptake rates become smaller 

than the nutrient sources (Figures 17c to 17f). These 

seasonal-scale connections between phytoplankton photosynthesis and the distributions of 02, CO2, and nutrients are well-characterized features of estuarine variability that include oxygen supersaturation [Gr•eti• et al., 

1991; Ragueneau et al., 1994] and depletions of DIN, 

DRP, and DSi during blooms [Peterson et al., 1985; 

Froelich et al., 1985; Robert et al., 1987; Meybeck et al., 

1988; Jordan et al., 1991a, b; Conley and Malone, 1992; 

Wetsteyn and Kromkamp, 1994; Pennock and Sharp, 

1994]. 

Recent improvements in analytical precision have 

given us new tools to explore phytoplankton-mediated 

transformations of trace substances such as dissolved 

metals. The traditional conceptual model of metal dynamics in estuaries placed emphasis on geochemical 

processesuch as exchange reactions on particle surfaces 

or complexation reactions. However, phytoplankton uptake and biochemical transformations can also play important roles in the cycling of some trace elements 

[Froelich et al., 1985; Sanders and Riedel, 1993], perhaps 

through pathways analogous to those of nutrient cycling. 

In south San Francisco Bay the concentrations of dissolved cadmium, zinc, and nickel decreased from 0.8 to 

0.4 nM, 20 to 3 nM, and 40 to 30 nM, respectively, 

during the 1994 spring bloom (A. Van Geen and $. N. 

Luoma, manuscript in preparation, 1996). Similar depletions of dissolved zinc [Reynolds and Hamilton-Taylor, 

1992], aluminum [Moran and Moore, 1988], and cadmium [Gonzalez et al., 1991] have been observed during 

blooms, when phytoplankton remove these metals from 

solution and transform them into particulate forms. 

High concentrations of reduced iron Fe(II) occur in 

surface waters during blooms, when algal metabolites 

(hydroxycarboxylic acids) facilitate the photoreduction 

of the low-solubility form Fe(III) [Kuma et al., 1992]. 

The biological availability of some metals, such as copper, fluctuates in response to the extracellular production of organic ligands (complexing agents) by phytoplankton [Zhou and Wangersky, 1989; Shine and Wallace, 

1995]. Phytoplankton can reduce and methylate arsenic, 

increasing its toxicity to animals [Sanders and Riedel, 

1993]; rates of these biotransformations are proportional to primary productivity [Sanders, 1983]. Because 

of these observations, the contemporary conceptual 

model of metal cycling includes algal uptake and biotransformation among the key processes that influence 

the chemical form, toxicity, and incorporation of some 

trace metals into estuarine food webs, with the recognition that these aspects of metal geochemistry can change 

rapidly during blooms. 

Parallel revisions are occurring in the conceptual 

models of estuarine organic geochemistry. The largest 

pool of organic matter is the dissolved pool, and distributions of dissolved organic carbon (DOC) within estu- 
152 ß Cloern' COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

5000 

• 4000 

.o 3000 

• 2000 

o 1000 

0 

b. Ratiof Chlorophyll 

a. Particulate Carbon to Particulate Carbon 

i i I el i I , i i i i i i i , {• i i i i , i I i 

ß 

[,.i.", 1⁄2 

J FMAMJ J ASOND 

Years 1980,1990 and 1991 

• 0.03 

• 0.02 

.. 

o 

• O.Ol 

o 

Years 1980,1990 and 1991 

c, Particulate Carbon: 

Particulate Nitrogen 

ii 

J FMAMJ J ASOND 

Years1990-1992 

d. 13C: 12C Ratiof POM 

= /1990 bloom 

! - 

ß 

ß - 

ß 

. : .- 

ß 

, , , , i i i i i i i 

J FMAMJ JASOND 

Years 1976-1977and 1990-1992 

Figure 18. Seasonal distributions of four characteristics of 

the suspended particulate matter in near-surface waters of 

south San Francisco Bay: (a) concentration of particulate carbon and (b) ratio of chlorophyll a to particulate carbon (between USGS stations 21 and 32 for the years 1980 and 1990- 

1991; data from Wienke and Cloern [1987] and Cloern et al. 

[1993]), (c) ratio of particulate carbon to particulate nitrogen 

(between USGS stations 21 and 34 for the years 1990-1992; 

data from Cloern et al. [1993]), and (d) •3C:•2C ratio, expressed as g•3C (between USGS stations 27 and 32 for the 

years 1976-1977 [Spiker and Schemel, 1979] and 1990-1992 

[Cloern et al., 1993]). 

aries often follow conservative patterns of mixing between high-DOC fresh water and low-DOC seawater. 

These distributions are consistent with the traditional 

view that estuarine DOC is refractory (resistanto rapid 

microbial degradation) and originates primarily from 

riverine inputs of terrestrial material. However, recent 

observations indicate that the estuarine DOC pool is 

reactive and altered by internal sinks and sources, including the synthesis and release of algal metabolites 

[Peterson et al., 1994]. The mechanisms of DOC release 

by phytoplankton are not well understood, but algal cells 

excrete low-molecular-weight compounds such as amino 

acids [Poulet et al., 1985; Fuhrman, 1990], and when 

blooms are terminated by nutrient limitation [l/an 

Boekel et al., 1992] or viral infection [Suttle et al., 1990; 

Bratbak et al., 1993], algal cells can rupture and release 

their dissolved contents into the water. Changes in the 

DOC pool during blooms include rapid increases in the 

extracellular release of organic carbon [Baines and Pace, 

1991]; the bulk DOC concentration [e.g., Norrman et al., 

1995]; the low-molecular-weight components [Kepkay et 

al., 1993], including volatile hydrocarbons [Milne et al., 

1995]; the turnover rate of labile compounds [Kirchman 

et al., 1991]; aliphatic hydrocarbons associated with 

rapid algal cell division (e.g., heneicosahexaene [Osterroht et al., 1983]); and aldehydes produced from algal 

fatty acids [Jalliffier-Merlon et al., 1991]. 

Coastal phytoplankton blooms also play important 

roles in the production and release of chemically active 

trace gases to the atmosphere. An example is dimethylsulfide [Stefels et al., 1995], which is oxidized to sulfate in 

the atmosphere and then contributes to the acidity of 

rainfall [Turner et al., 1988] and climate modulation 

[Charlson et al., 1987]. Coastal phytoplankton production is also a globally significant source of ozone-depleting halocarbons, such as methyl bromide [Lobert et al., 

1995]. 

Particulate Organic Matter 

As phytoplankton transform inorganic materials into 

particulate organic matter during blooms (Figure 15), 

they change the abundance and chemical composition of 

the particles suspended in water. These changes are 

sometimes obscured because the total concentration of 

suspended particulate matter (SPM) can be high in 

shallow coastal waters [Ward and Twilley, 1986]. The 

SPM of estuaries is often dominated by mineral particles, and the small organic fraction is composed of 

complex molecules that are difficult to characterize 

chemically [Fichez et al., 1993]. The suspended POM of 

estuaries originates from many sources, including riverine inputs derived from freshwater or terrestrial plants, 

sewage, detritus from surrounding marshes, marine 

plankton, or primary production by vascular plants and 

algae. During blooms the phytoplankton production of 

POM can dominate the other sources, and the SPM 

becomes more biogenic in character (the labile, or utilizable, components become important relative to the 

refractory components). These changes in the SPM are 

reflected in the quantity of specific classes of organic 

compounds such as lipids [Kattner and Brockmann, 

1990], proteins [Billen and Fontigny, 1987], and carbohydrates [Fichez et al., 1993]. One geochemical consequence of the algal assimilation of reactive elements, 

such as C, N, P, Si, is a large shift in elemental composition (or "repackaging") [Lebo and Sharp, 1992] from 

dissolved inorganic forms to particulate organic forms 

[Ward and Twilley, 1986; Zwolsman, 1994]. In south San 

Francisco Bay, concentrations of particulate carbon 

(PC) vary over nearly 2 orders of magnitude, with maximum concentrations of biogenic PC during spring when 

phytoplankton biomass is high (Figure 18a). A common 

feature of blooms is a rapid increase in the concentrations of particulate carbon and nitrogen [Nakatsuka et 

ai., i992], particulate phosphorus [Sakamoto and 

Tanaka, 1989], and biogenic silica [Ragueneau et al., 

1994]. 

Geochemists use a variety of measurements to infer 

the origin, reactivity, and biochemical composition of 

the complex mixture of organic substances in coastal 

waters. These measurements can be sensitive indicators 

of the changing phytoplankton component of the POM 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 153 

during blooms. One simple indicator of the biogenic 

fraction of SPM is the ratio of particulate carbon to 

SPM. This ratio is commonly •0.05 [Zwolsman, 1994], 

but it can reach values as high as 0.35 during periods of 

high primary productivity [Cauwet, 1991]. A simple indicator of the phytoplankton fraction of POM is the 

ratio of chlorophyll a to PC [Jordan et al., 1991a; Cifuentes et al., 1988]. In south San Francisco Bay this 

index ranges from 0.001 to 0.03 (Figure 18b). Although 

the ratio of phytoplankton chlorophyll to carbon varies 

with growth conditions [Cloem et al., 1995], the maximum chlorophyll:PC ratio of 0.03 observed in spring is 

close to the ratio expected in a suspension of pure algal 

biomass. The minimum chlorophyll:PC ratio of 0.001 

indicates that most of the POM was then associated with 

components other than living phytoplankton biomass. 

Canuel et al. [1995] used analyses of lipid biomarkers to 

confirm that phytoplankton biomass constitutes most of 

the particulate carbon in San Francisco Bay during 

blooms but less than 20% of the particulate carbon 

during nonbloom conditions. 

A related index is based on the "standard" elemental 

composition of healthy phytoplankton, C:N:P = 

106:16:1 [Redfield, 1958]. If phytoplankton composition 

follows this Redfield ratio, then pure algal suspensions 

should have molar ratios of particulate carbon to particulate nitrogen (PC:PN) of 6.6 and ratios of PC to 

particulate phosphorus (PC:PP) of about 106. Departures from these ratios indicate that the POM might be 

composed of organic matter other than phytoplankton. 

In south San Francisco Bay the PC:PN ratio is typically 

greater than 8-9 except during spring, when it can fall to 

values below 7 (Figure 18c). In many other estuaries the 

PC:PN ratio lies in the range 6-8 during algal blooms 

but is >10 when the POM is dominated by nonphytoplankton components [Ward and Twilley, 1986; Jordan et 

al., 1991a]. Similar fluctuations in the PC:PP ratio occur 

in coastal waters, with highest ratios (230) during nonbloom periods and lowest ratios (96) during blooms 

[Sakamoto and Tanaka, 1989]. 

Different sources of estuarine organic matter (anthropogenic, terrestrial, and marine) have different compositions of stable isotopes of elements such as C and N. 

These differences have been the basis for using isotope 

ratios of the POM to infer the relative importance of 

these different sources. The approach is based on the 

assumption that isotopic composition of estuarine POM 

is controlled by mixing between end-member sources. 

However, we now recognize that biogeochemical processes, including primary production, alter the isotopic 

composition of POM. In south San Francisco Bay the 

ratio of •3C to •2C in the POM (expressed as •3C, the 

deviation of the measured 13C:12C ratio from that in a 

carbonate standard [Fry and Wainright, 1991]) usually 

falls in the range - 27 to - 23 %o (Figure 18d). However, 

this ratio changes during spring blooms, when phytoplankton constitute the bulk of the POM and the •3C 

POM increases to -18 to -17%o (indicating enrichment in •3C). Comparable (or larger) shifts in the carbon 

isotopic composition of the POM have been observed in 

other estuaries [Fogel et al., 1992]. Fast growing coastal 

diatoms become particularly enriched in •3C (with •3C 

up to -13%o [Fry and Wainright, 1991]), and during 

diatom blooms the •3C POM can increase from -21 to 

-16%o in less than 1 week [Nakatsuka et al., 1992]. 

Although there is uncertainty about the biochemical 

mechanisms behind the variable discrimination of C 

isotopes by photosynthesis [Fry and Wainright, 1991; 

Fogel et al., 1992], it is clear now that phytoplankton 

primary production can alter the isotopic composition of 

particulate carbon. Similarly, phytoplankton primary 

production alters the N isotopic composition of POM, 

with rapid shifts of •5N from +9 to + 1%o during 

blooms as algae preferentially assimilate •4NO• and 

produce POM that is enriched in •4N [Nakatsuka etal., 

1992]. Interpretation of the variability of C and N isotopes in estuaries requires consideration of these biogeochemical transformations that become pronounced 

during blooms [Pennock et al., 1996]. 

Another emerging technique for characterizing POM 

is based on analyses for biomarkers, organic molecules 

that can be traced to specific groups of organisms 

[Mayzaud et al., 1989]. The lipid components of POM, 

particularly sterols and fatty acids, can give clues about 

the relative importance of algal, bacterial, or vascular 

plant sources of POM because each group of organisms 

synthesizes acharacteristic set of lipid molecules [Scribe 

et al., 1991]. For example, 14- and 16-carbon fatty acids 

are the most common fatty acids synthesized by algae, 

and these molecules are used as indicators of phytoplankton activity [Hama, 1991]. In south San Francisco 

Bay the lipid composition of the POM changes during 

the spring bloom, with large increases in the relative 

abundance of 14:0, 16:0, and 16:1co7c fatty acids [Canuel 

et al., 1995]. These same changes have been followed 

closely during the exponential growth phase of other 

coastal diatom blooms [Kattner and Brockmann, 1990]. 

The specific molecular composition of lipids can give 

information about the community composition of the 

phytoplankton because different classes of algae synthesize different signature molecules [Fraser et al., 1989; 

Mayzaud et al., 1989]. In south San Francisco Bay the 

abundance of 24-methylenecholesterol increases markedly during the spring bloom [Canuel et al., 1995; Canuel 

and Cloem, 1996], and this sterol is a major component 

of marine diatoms of the genus Thalassiosira (common 

members of the spring bloom community in this estuary; 

see Table 4). 

Responses of the Heterotroph Populations 

The complex suite of geochemical changes caused by 

algal blooms is an important mechanism of habitat 

change for consumer organisms. Some of these changes 

are beneficial because most of the DOM and POM 

produced during blooms can be used as a food resource 
154 ß Cloern' COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

a. Bacterial Biomass 

1õ0 ............ 

125 

lOO 

ßß 

_ _ 

ß 

ß 

ß 

ß e•e - 

ß ße e 

,• ø."1•.• ø ø o [ - I I I I I I 

J F I• A M • J • • •) N D 

b. Tintinnopsis i I ! i sp. i i I i i ! i c. Acartia i i c,lausi i na,uplii i i i I i I 

ß 100 t" ;ß ß 

•" • L. q ,' ß 

ß -lO •, :."•; 

ß ß i I 

... . :- 

ß ! f oo ß 

Years 1988-1991 Years 1978-1981 Years 1978-1981 

d. Spionid Polychaete Larvae 

i i I I i I i I i i i 

_ -16 

• -18 

- •. 

•' .20 

.22 

-24 

e. l•C: 12C Ratio of Clam Tissues 

i i i I i i i i i i ! 

ß 1990 

ß bloom 

./ 

ß 

f. Lipid Biomarkers in Clams 

I I I I I I I I I I I 

ß 

ß/1990 bloom 

i ß i .tt i i i i ,o i i i ß i i 

J FMAMJJA$0ND 

Years 1978-1981 Years 1990-1991 Years 1990-1991 

Figure 19. Seasonal changes in the abundance or biochemical composition of heterotrophs in south San 

Francisco Bay: (a) pelagic bacterial biomass (between USGS stations 21 and 32 for the years 1988-1991; data 

from Hollibaugh and Wong [1996]); abundances of (b) the tintinnid ciliate protozoan Tintinnopsisp., (c) 

nauplii of the copepod Acartia clausi, and (d) larvae of spionid polychaete worms (from near-surface pump 

samples at USGS stations 30 and 32 for the years 1978-1981; data from Hutchinson [1981, 1982]); and (e) ratio 

of •3C: •2C, expressed as •3C, and (f) concentration of the biomarker fatty acid 20:5o•3 in tissues of the clam 

Potarnocorbula arnurensis (between USGS stations 28 and 33 for the years 1990-1991; data from Cloern et al. 

[19931). 

by bacteria, protozoans, and invertebrates. There are 

two different pathways through which phytoplanktonderived organic matter can be assimilated and converted 

into new biomass (production) of heterotrophs (Figure 

15). The microbial food chain is based on the assimilation of DOM by bacterioplankton; it directly supports 

the production of protozoan communities [e.g., Van 

Boekel et al., 1992]. The metazoan (multicellular animal) 

food chain is based on the consumption of phytoplankton and organisms of the microbial food chain. Both 

pathways are important, and investigations of the past 

decade have shown that much (up to 60%) of the phytoplankton primary production passes through the bacterial trophic level [Fuhrman, 1990] or is consumed 

directly by protozoans [McManus and EderingtonCantrell, 1992]. 

•1-•1_ _ 1•'__1 ..... 11 _J I 1, 1 1 

z nc nnAagc is now wen estaonsnea between the production of algal metabolites and the rapid utilization of 

these as substrates to support bacterial production in 

coastal waters [Larsson and Hagstr6rn, 1982; Lancelot 

and Billen, 1984]. As the rate of bacterial production 

increases in response to the enhanced primary productivity of blooms, we would then expect corresponding 

increases in the abundance or biomass of the bacterioplankton. This population response is well documented 

in mesocosm (large enclosure) experiments [Painting et 

al., 1989; Riemann et al., 1990; Norrman et al., 1995] and 

in some coastal waters [Billen and Fontigny, 1987; Van 

Boekel et al., 1992] and sediments [Yap, 1991]. However, 

strong correlations between bacterial abundance and 

phytoplankton primary productivity are not always observed in nature because bacterioplankton populations 

are influenced by losses to microzooplankton (protozoan) grazers or bacterial viruses [Bratbak et al., 1990]. 

Bacterial losses to the microzooplankton can equal the 

rate of bacterial production [Coffin and Sharp, 1987]. 

This means that the rate of energy flow through the 

microbial food chain can increase in proportion to primary productivity, even when the total biomass of bacteria changes little. This may explain why the biomass of 

bacteriopiankton in south San Francisco Bay •s most 

variable during spring months (Figure 19a), because 

rapid increases in bacterial biomass are often followed 

by increased abundance of bacterial consumers [Van 

Boekel et al., 1992]. The degree of coupling between 

bacterial and primary productivity is temperature-dependent [Coffin and Sharp, 1987; Pomeroy et al., 1991], 

and it can be damped by the input of terrestrial sources 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 155 

of DOM that can also support bacterial production 

[Ducklow and Kirchman, 1983; Kirchman et al., 1989]. 

Other populations of the pelagic food web respond to 

the production of high-quality organic matter during 

blooms, because the heterotrophs are often food-limited 

[Durbin et al., 1983]. In south San Francisco Bay, some 

species of tintinnid ciliates (protozoans that build protective shells) are present only in spring (Figure 19b). 

Sudden large population outbreaks of these protozoans 

are common in coastal waters, and these events are 

closely linked to seasonal changes in phytoplankton primary productivity. Tintinnid ciliates produce cysts when 

food availability is low; the cysts sink to the sediments 

and remain dormant until food availability increases. 

The development of cysts into active cells is triggered by 

dissolved organic substances produced by the phytoplankton [Kamiyama, 1994], and this adaptive response 

allows the tintinnids to exploit conditions of high food 

availability during blooms. 

Some species of copepods also have dormant stages 

that are produced and hatch in response to changing 

food availability. This explains why nauplii (larval stages) 

of the copepod Acartia clausi are most abundant in south 

San Francisco Bay during spring (Figure 19c). Nauplii 

develop from resting eggs in the sediments (a function of 

temperature [Sullivan and McManus, 1986]) and from 

the eggs produced by the existing adult stock. For estuarine-coastal copepods such as Calanus pacificus, Acartia 

tonsa, and Acartia hudsonica the rate of egg production 

is highly influenced by the abundance and composition 

of the phytoplankton [Durbin et al., 1983; Runge, 1985; 

Beckman and Peterson, 1986; Sullivan and McManus, 

1986]. These copepods have a common response of 

negligible egg production at chlorophyll a concentrations of 1-2 •g L -• [Durbin et al., 1983] and maximal egg 

production rates when chlorophyll a concentration exceeds about 10 •g L -•. These zooplankton species store 

only small food reserves, so the population growth rate 

of copepods is sensitive to fluctuations in phytoplankton 

biomass inthe range of 1-10 •g L -• chlorophyll a. This 

coupling between zooplankton production and phytoplankton blooms may propagate to higher levels of the 

food web because strong coherence has been observed 

between larval fish abundance and spring plankton 

blooms in some coastal waters [Townsend, 1984]. 

Benthic and pelagic heterotrophs share the same food 

resource in shallow coastal waters, so population responses of the benthic animals are also coupled to phytoplankton dynamics. Biologists have long recognized a 

close timing between the onset of reproduction of 

benthic invertebrates and phytoplankton blooms [Starr et 

al., 1990]. In south San Francisco Bay the pelagic larval 

stages of some polychaete worms are most abundant 

during the spring (Figure 19d), and reproduction of 

other species such as mussels, urchins [Starr et al., 1990], 

barnacles [Starr et al., 1991], and oysters [Ruiz et al., 

1992] is coupled to the timing of phytoplankton blooms. 

This synchrony provides the Obvious advantage of ensuring an abundant food supply for larvae as they develop in 

variable environments. The mechanism of this synchrony 

is the induction of spawning by metabolites produced 

and released into the water by the phytoplankton [Starr 

et al., 1990]. 

A second response of benthic invertebrates is their 

seasonal growth cycle. The cosmopolitan estuarine clam 

Macoma balthica has monthly fluctuations of growth rate 

in San Francisco Bay that are coherent with monthly 

fluctuations in phytoplankton biomass: the growth period coincides with the seasonal phytoplankton blooms, 

and the growth rate changes from year to year in response to the magnitude of the annual phytoplankton 

bloom [Thompson and Nichols, 1988]. Comparable studies with other species in other estuaries, such as the 

mussel Mytilus edulis [Smaal and van Stralen, 1990], the 

clam Yoldia notabilis [Nakaoka, 1992], and the oyster 

Ostrea edulis [Ruiz et al., 1992], show that the growth rate 

of benthic suspension feeders is often near zero (or 

negative) except during episodes of rapid growth supported by the enhanced food availability during phytoplankton blooms. Interannual fluctuations in the population growth of benthic invertebrates are caused by 

year-to-year fluctuations in the abundance of the phytoplankton food resource during the growing season [Beukema and Cadde, 1991; Powell et al., 1995]. 

The biochemical composition of the benthic invertebrates changes as animals grow and accumulate storage 

products, such as lipids and carbohydrates, during periods of high phytoplankton biomass [Wenne and Styczynska-Jurewicz, 1985; Ruiz et al., 1992]. These changes in 

the biochemical composition of consumer organisms can 

be linked directly to fluctuations in phytoplankton biomass with the same biomarker analyses used to characterize POM. The approach is based on observations that 

the biochemical composition of animals, including the 

13C' 12C ratio of their tissues, reflects the composition of 

their food resources [DeNiro and Epstein, 1978]. In south 

San Francisco Bay the carbon isotopic composition of 

the clam Potamocorbula amurensis has a seasonal cycle 

very similar to the seasonal fluctuations in g•3C POM. 

Carbon in the tissues of P. amurensis has an isotopic 

signature indicative of nondiatom food sources (g•3C of 

-25 to -22%0) during winter and early spring (Figure 

19e). However, the g•3C of P. amurensis increases rapidly during spring and reaches an annual maximum of 

-17%o in April, similar to the g•3C of the POM when 

phytoplankton biomass constitutes most of the POM. 

This coherence between the seasonal fluctuations of •3C 

enrichment in both the food source and P. amurensis 

shows that the growth of this filter feeder is supported by 

the assimilation of phytoplankton produced during the 

spring bloom. Fry and Wainright [1991] also interpreted 

seasonal enrichments ofzooplankton •3C as evidence 

that •3C-rich diatom carbon is transferred to the zooplankton trophic level. 

Molecular biomarkers provide confirmatory evidence 

that algal biomass is directly incorporated into the pro- 
156 ß Cloern: COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

duction of organisms at higher trophic levels. Fatty acids 

are useful biomarkers because some polyunsaturated 

fatty acids (PUFA) are essential dietary factors for animals that can only be synthesized by algae. An example 

is the 20-carbon fatty acid 20:5o03, one of the major 

PUFAs produced by diatoms [Fraser et al., 1989]. In 

south San Francisco Bay the concentration of this fatty 

acid in the tissues of the clam Potamocorbula amurensis 

increased by a factor of 10-30 within weeks after the 

spring diatom bloom in 1990 (Figure 19f). Mesocosm 

experiments have also been used to demonstrate the 

enhanced transfer of dietary fatty acids from phytoplankton to zooplankton and then to larval fish during 

phytoplankton blooms [Fraser et al., 1989]. 

The Importance of Algal Species Composition 

We conclude this section with a reminder that not all 

phytoplankton species are equal. The rapid production 

of dimethylsulfide in coastal waters is associated with 

blooms of only some phytoplankton species (Emiliania 

huxleyi [Wolfe et al., 1994]; Gyrodinium aureolum [Turner 

et al., 1988]; Phaeocystis sp. [Stefels et al., 1995]). The flux 

of this climatically active trace gas to the atmosphere is 

therefore a function of the phytoplankton community 

composition as well as biomass and productivity. Only 

some species of cyanobact•ria fix atmospheric nitrogen 

[Carpenter et al., 1992], only the diatoms and silicoflagellates influence the cycling of silica [Tr•guer et al., 1995], 

and the methylated forms of arsenic produced during 

blooms are species-dependent [Froelich et al., 1985]. 

Nondiatoms appear to fractionate inorganic carbon [Fry 

and Wainright, 1991] and nitrogen [Montoya and McCarthy, 1995] isotopes less than diatoms. The fate of 

phytoplankton (e.g., grazing versus sedimentation) depends on the size and sinking rate of the cells produced 

during blooms [Fahnenstiel et al., 1995]. Therefore the 

rates and pathways through which blooms act as agents 

of geochemical change are highly dependent on the 

species composition of the bloom communities. 

This same comment applies to the linkage between 

algal blooms and other trophic levels, because phytoplankton communities include a diverse array of cell 

sizes, morphologies, and biochemical compositions. 

Within this diversity of forms is a broad range of suitability as food resources for consumer organisms. Copepods can select among food items, and estuarine-coastal 

species appear to have a preference for dinoflagellates 

and microzooplankton over diatoms [Kleppel et al., 

1991]. The production of viable eggs by the copepod 

Temora stylifera is 4-6 times faster on a diet of Prorocenrrwn tninitnurn (a dinolqagellate) compared with the 

diatom Thalassiosira rotula [Ianora and Poulet, 1993]. 

This may be partly a response to the higher nutritional 

quality of the dinofiagellate species, although the diatom 

T. rotula produces a powerful inhibitor of cell division 

that can block the development of copepod eggs [Poulet 

et al., 1994]. Other species, such as the prymnesiophyte 

Phaeocystis pouchetii, can suppress feeding [Bautista et 

al., 1992] and egg production [Van Rijswijk et al., 1989] of 

copepods. Among the dinoflagellates, some species are 

poor food resources for copepods [Huntley et al., 1986], 

and others (e.g., Dinophysis acuminata) synthesize toxins 

that repel copepod grazers [Carlsson et al., 1995]. Therefore species composition of the phytoplankton community ultimately affects zooplankton production by changing the feeding and reproduction rate of copepods 

[Poulet et al., 1994]. This appears to be true for the 

benthic fauna as well [Beukema and Cad•e, 1991]. 

Although phytoplankton primary production is a 

prominent source of organic matter to support production at higher trophic levels, exceptional blooms dominated by one or several species can cause major ecological disturbance, sometimes leading to large economic 

losses. Blooms of the red tide flagellate Olisthodiscus 

luteus disrupt plankton food webs by inhibiting the 

growth of microzooplankton [Verity and Stoecker, 1982]. 

Dense, persistent blooms of species such as the chrysophyte Aureococcus anorexefferens [Cosper et al., 1987; 

Tracey, 1988] or the red tide dinoflagellate Ptychodiscus 

brevis [Summerson and Peterson, 1990] can cause reproductive failure and mortality of shellfish such as mussels 

and bay scallops. Toxin-producing species can cause 

mortality at higher levels of the food web: the prymnesiophyte Chrysochromulina polylepsis produces a toxin 

that can cause mass mortalities of fish [Estep and MacIntyre, 1989], the newly discovered "phantom" dinoflagellate Pfiesteria piscicida causes fish kills in the Pamlico 

and Neuse estuaries [Burkholder et al., 1992], and diatoms of the genus Pseudonitzschia produce domoic acid, 

which is toxic to vertebrates and has caused mortalities 

of pelicans and cormorants [Walz e! al., 1994]. Because 

of these strong species-specific attributes of the phytoplankton, the linkages between algal bloom dynamics 

and the biogeochemical system are best established 

through programs that include measures of phytoplankton community composition to identify the occurrence 

of species that play particular roles in the cycling of 

elements and production of heterotrophs. 

SOME LESSONS AND QUESTIONS TO GUIDE 

FUTURE RESEARCH 

My primary objective in this review was to present 

phytoplankton ecology as an example of multidisciplinary science. The problem of coastal bloom dynamics 

requires consideration of the linkages between the geologic, hydrod•amic, climatic, hydrologic, geochemical, 

and biological components of the Earth system. Results 

from sustained investigation of San Francisco Bay illustrate some general lessons about these linkages. They 

also help to identify the large gaps in our understanding 

of these linkages, and I conclude with three questions 

that will persist as central elements of coastal ecosystem 

research into the next century. 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 157 

Some lessons 

1. Phytoplankton blooms are key agents of geochemical variability in coastal ecosystems. A biogeochemical function of phytoplankton primary production 

is the transformation of reactive inorganic substances 

into organic matter. During blooms these transformations are rapid and give rise to measurable changes in 

oxygen concentration; CO2 and p H; dissolved nutrients 

such as nitrate, phosphate, and silicate; speciation and 

form of reactive trace metals such as cadmium, zinc, and 

arsenic; production of climatically active trace gases such 

as dimethylsulfide; and isotopic fractionation of elements such as C and N. 

2. The rapid production of fresh organic matter 

during blooms triggers a complex suite of responses at 

other trophic levels. These responses include stimulation 

of bacterial productivity, growth of microzooplankton, 

and reproduction and growth of consumer animals (zooplankton, mollusks, worms, and crustaceans). 

3. Phytoplankton blooms can be understood in the 

context of a simple population budget that expresses rate 

of population change as the sum of local (in situ) processes plus transport processes. Both sets of processes 

respond to fluctuations in physical forcings that originate 

in the ocean, atmosphere, and watefshed. As an example, vertical mixing is a key determinant of phytoplankton population growth rate; mixing is influenced by tidal 

(oceanic) current stresses at the bottom, wind (atmospheric) stresses on the water surface, and riverine (watershed) inputs of fresh water. 

4. Phytoplankton biomass varies at all spatial and 

temporal scales at which we make measurements, and 

blooms do not necessarily develop uniformly within an 

estuarine basin. Temporal and spatial variability are 

coupled; small-scale patchiness is ephemeral, but the 

mesoscale patterns of variability can persist for days or 

weeks. Mesoscale patchiness is shaped by the basin-scale 

water circulation and mixing, and it can be altered rapidly by events that disrupt the mean circulation. The 

timescales of phytoplankton biomass variability are determined by the timescales of the physical sources of 

biomass change, such as the semidiurnal and neapspring tidal fluctuations, seasonal and interannual fluctuations of river flow, and episodic and seasonal fluctuations of the wind forcing. 

5. In south San Francisco Bay the timing of blooms 

is set partly by the tides, which fluctuate and establish 

windows of opportunity for phytoplankton population 

growth as periods of low tidal energy and slow vertical 

mixing. The magnitude of the spring blooms is set, at 

least in part, each year by the particular hydrologic and 

weather conditions operating during these tidal windows. Therefore the timing of blooms (from an astronomical forcing) is predictable, but the magnitude of 

blooms is determined by aperiodic forcings and is therefore unpredictable. This observation could be the basis 

for a framework of estuarine comparison, organized 

around the hypothesis that strongly tidal SCEs have 

strongly periodic variability, whereas weakly tidal SCEs 

are characterized by aperiodic fluctuations around the 

seasonal cycles. 

6. Although SCEs have recurrent annual cycles of 

phytoplankton blooms, the timing, magnitude, and species composition of these blooms all change from year to 

year. Large departures from the mean annual pattern 

are caused by exceptional climatic or hydrologic conditions, such as events of extreme precipitation and river 

discharge or anomalous regional wind forcings. 

7. Colonization of SCEs by exotic species can lead 

to major (sometimes permanent) disturbance at the ecosystem level. The invasion of northern San Francisco 

Bay by the clam Potamocorbula amurensis has caused a 

fivefold reduction in annual primary production, near 

complete disappearance of the summer diatom bloom, 

and diverse changes in the pelagic heterotroph community. Coastal ecosystems are particularly susceptible to 

this mode of global change, and our conceptual models 

of coastal ecosystems must include recognition that the 

ecosystems we are currently studying can be profoundly 

altered in the future by the introduction of exotic species 

that disrupt trophic interactions. 

8. Shallow coastal waters are nutrient-rich, turbid, 

characterized by large variability at short timescales and 

small spatial scales, and highly influenced by the rapid 

exchanges of materials with the bottom sediments. 

Therefore the traditional conceptual models of pelagic 

oceanography do not work as a framework for understanding phytoplankton bloom dynamics in the shallow 

coastal zone. 

Question 1: What Determines Species Composition of 

Blooms? 

The lessons noted above come from a search for 

patterns, mechanisms, and ecosystem-level responses to 

phytoplankton blooms as revealed through measurements made at one set of scales. Emphasis is placed on 

chlorophyll variability as an index of the phytoplankton 

population response to physical variability. These kinds 

of lessons can be used as a first step in the process of 

understanding coastal blooms as features of the Earth 

system that are subject to change as we alter the climate 

system and hydrologic cycle, as we alter the water chemistry through inputs of contaminants and nutrients, and 

as we continue to translocate species. However, this first 

step is based on a narrow perspective that does not 

consider the rich details of phytoplankton population 

variability at the species level. Smetacek and Pollehne 

[1986, p. 404] call these details a "source of irritation to 

modern empirical ecologists." Hopefully it is clear at this 

point why the details are important. The recent discovery of Poulet et al. [1994] that some diatom species 

produce a potent chemical inhibitor of egg development 

is a compelling example of why we need to understand 

the processes that determine species composition of 

phytoplankton blooms. If we want to fully understand 

population fluctuations of copepods, sea urchins, or fish, 
158 ß Cloern' COASTAL PHYTOPLANKTON BLOOMS 34, 2 / REVIEWS OF GEOPHYSICS 

then we need to understand the forces that select for 

those algal species that play critical roles in the production of food and in the synthesis of molecules that 

interfere with population recruitment at these higher 

trophic levels. Similarly, geochemists need to understand 

population variability of those phytoplankton species 

that are active in the production of trace gases, the 

isotopic fractionation of C and N, the biochemical transformations of trace metals, and the cycling of nutrients. 

Smetacek and Pollehne [1986] suggesthat our inability 

to understand or predict bloom dynamics at the species 

level is the result of a conceptual framework that overemphasizes the "physicochemical paradigm." Smetacek 

[1986] suggests the need for an "ecosystem paradigm" 

based on a natural history orientation to understand life 

history cycles, with recognition that phytoplankton species distributions reflect not only adaptations to the 

immediate environment during the growth (bloom) 

phase of population cycles, but also life cycle strategies, 

such as production of resting stages, that ensure persistence of the population through the nongrowth phases. 

Work toward an ecosystem paradigm should be based on 

Margalef's [1978] reminder (cited by Legendre et al. 

[1984, p. 629]) that "Organisms are not only carriers of 

molecules, but they are subject to natural selection." 

Question 2' How Do Toxic Contaminants Alter 

Blooms and Their Biogeochemical Functions? 

The urgency of this question comes from the certainty 

that coastal ecosystems in the developed world are contaminated with toxic substances such as heavy metals, 

chlorinated hydrocarbons, and petrochemicals and the 

likelihood that SCEs in the developing world will become progressively more contaminated in the future 

[Windom, 1992; Nixon, 1995]. It is now well established 

that phytoplankton blooms can change the concentration and geochemical form of some trace metals [Slauenwhite and Wangersky, 1991]. However, there is much less 

certainty about the impacts of toxic contaminants on 

phytoplankton community composition, primary production, and population growth. The limited experimental work suggests that chronic low level inputs of toxic 

elements can alter the evolution of phytoplankton communities by eliminating sensitive species (e.g., dinoflagellates [Brand et al., 1986]) and selecting for more 

tolerant forms [Sanders and Cibik, 1988; Kuwabara et al., 

1989]. 

A second aspect of this question comes from the 

likelihood that interactions between toxic substances 

and phytoplankton blooms produce effects that propas,•,- rvrat-a to upper *•""•':• LIUI. JIIII•, IK,,V•.,13. • .... • UIIK;; r• ...... 111UklK;; • ..... k, kJUlkl • be '•- tmougn ..... 

phytoplankton uptake of trace metals (or organic contaminants such as PCBs and DDT [Mailhot, 1987] and 

subsequent transfer of these toxic substances to animals 

that ingest and assimilate phytoplankton. It appears that 

the transfer efficiency of metals from phytoplankton to 

consumers depends on the degree to which algae can 

assimilate and sequester the different elements inside 

their cell membranes [Reinfelder and Fisher, 1991]. 

Therefore ecosystem-level effects of toxic contaminants 

may be set, in part, by the efficiency with which phytoplankton can act as agents of bioaccumulation and trophic transfer. Ecosystems scientists are beginning to 

recognize that toxic contaminants are human forces of 

change just as potent as global warming, habitat destruction, and introductions of exotic species. As we pursue 

this hypothesis, one focus should be directed to under- , 

standing the role of blooms as events that move toxic 

substances into the food resource of animals and to 

those substances for which phytoplankton are especially 

efficient at assimilation and trophic transfer. 

Question 3: How Is Nutrient Enrichment Changing 

Coastal Ecosystems? 

This question is motivated by concern about the 

harmful effects of nutrient enrichment caused by the 

application of fertilizers in river basins, the discharge of 

urban wastes, and the combustion of fossil fuels [Justid et 

al., 1995]. A simplistic answer to this question is that 

nutrient enrichment stimulates primary production (the 

process of eutrophication [Nixon, 1995]), leading to accumulations of phytoplankton biomass, episodes of noxious blooms, depletions of dissolved oxygen as the 

blooms decay, and mortality of fish or shellfish. Although this sequence of acute responses to nutrient 

enrichment has been observed [Justid, 1987; Rosenberg 

and Loo, 1988], responses to chronic nutrient enrichment in most coastal ecosystems are probably more 

subtle, are more difficult to detect or measure, and 

follow a sequence of stages leading toward these acute 

symptoms. There is considerable evidence that increased 

nutrient concentrations in coastal waters have led to 

biological change in recent decades; compelling examples come from long-term observations in the Baltic 

[Rosenberg et al., 1990; Gran•li et al., 1990], German 

Bight [Radach et al., 1990], Chesapeake Bay [Harding, 

1994; Cooper, 1995], and southern North Sea [Cad•e, 

1986; Cadre and Hegeman, 1991]. However, there is also 

considerable uncertainty about how nutrient enrichment 

leads to ecosystem change in the coastal zone. As we 

work to answer this question, our broad goal should be 

a global conceptual model of how coastal eutrophication 

works. This conceptual model should recognize the following: 

1. Eutrophication is an ecological process, so it 

should be studied from an ecosystem perspective that 

considers all the interacting physical, chemical, trophic, 

and life history processes of phytoplankton population 

fluctuation [Hecky and Miham, 1988].•ative applications of this perspective will also be required to resolve 

the relative importance of natural processes such as 

climate anomalies [e.g., Vieira and Chant, 1993] and 

anthropogenic nutrient enrichment as mechanisms that 

trigger exceptional blooms of harmful algal species. 

2. Ecosystem responses to chronic nutrient enrichment might occur as a sequence of successional stages, 
34, 2 / REVIEWS OF GEOPHYSICS Cloern: COASTAL PHYTOPLANKTON BLOOMS ß 159 

and the early responses might be subtle community shifts 

in the phytoplankton, benthic invertebrates [Elmgren, 

1989], attached algae [McComb and Lukatelich, 1995], or 

rooted plants [Orth and Moore, 1983]. 

3. Changing nutrient ratios is an important element 

of coastal eutrophication that appears to selectively promote blooms of nondiatom species [Conley et al., 1993] 

as human activities increase the availability of N and P 

relative to Si [Justif et al., 1995]. 

4. A conceptual framework is needed to explain the 

great range of sensitivity to nutrient enrichment among 

different coastal water bodies. It is not clear at this point 

why some SCEs, such as San Francisco Bay, do not 

exhibit obvious symptoms of nutrient enrichment. The 

strong couplings between primary production and 

benthic consumption may be a partial explanation [Cloern, 1982; Herman and Scholten, 1990; Hily, 1991]. 

Coastal ecosystems with a short retention time [Balls et 

al., 1995] or strong tidal mixing [Tr•guer and Qu•guiner, 

1989; Monbet, 1992] appear to be more resilient to the 

acute effects of nutrient enrichment than weakly tidal 

systems with slow circulation. Therefore this global conceptual model should incorporate both the trophic interactions and the physical processes that influence the 

pathways through which nutrient enrichment can alter 

phytoplankton populations. 

These three research questions are closely interconnected, so they should be pursued together as components of integrated programs to identify the patterns of 

ecosystem change in the coastal zone, the underlying 

mechanisms of those changes, and the interactions between these different mechanisms of change. 

ACKNOWLEDGMENTS. The San Francisco Bay program of the United States Geological Survey was conceived by 

David Peterson, T. John Conomos, Fred Nichols, and David 

McCulloch, who introduced me to the complexities of estuarine ecosystems. This program has continued for nearly 3 

decades because the science leadership of John Bredehoeft, 

Roger Wolff, and Robert Hirsch included a commitment to 

sustained programs of fundamental research as integral components of the USGS mandate as the nation's Earth science 

agency. My own commitment to estuarine science has been 

sustained for 2 decades by the boundless energy and enthusiasm of my dear friends Brian Cole and Andrea Alpine. The 

interdisciplinary nature of this review comes from USGS and 

academic colleagues who continue to broaden my perspectives 

of geochemistry, microbiology, benthic ecology, fluid mechanics, and approaches for data synthesis: Sam Luoma, Ron 

Oremland, Ralph Cheng, Jan Thompson, Steve Hager, Fred 

Nichols, Tim Hollibaugh, Alan Jassby, Elizabeth Canuel, Jane 

Caffrey, Jeff Koseff, Stephen Monismith, Linda Huzzey, and 

Joe Rudek. Illustrations in this review were designed by Jeanne 

DiLeo and David Jones. Alan Chave, Brian Cole, Christian 

Grenz, Debbie Hutchinson, Alan Jassby, Steven Lohrenzen, 

Lisa Lucas-Vidergar, Jon Pennock, and Tom Torgersen gave 

thoughtful suggestions for improving the original manuscript. 

Tom Torgersen was the editor responsible for this paper. 

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