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Title (dcterms:title)
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Eng
Seasonal Variation of the Genus Dinophysis within Puget Sound, Washington: Understanding Harmful Algai Blooms through Species Identification
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Date (dcterms:date)
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2014
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Creator (dcterms:creator)
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Eng
Runyan, Jennifer Sun
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Subject (dcterms:subject)
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Eng
Environmental Studies
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extracted text (extracttext:extracted_text)
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SEASONAL VARIATION OF THE GENUS DINOPHYSIS
WITHIN PUGET SOUND, WASHINGTON:
UNDERSTANDING HARMFUL ALGAL BLOOMS THROUGH
SPECIES IDENTIFICATION
by
Jennifer Sun Runyan
A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
June 2014
© 2014 by Jennifer Sun Runyan. All rights reserved.
This Thesis for the Master of Environmental Studies Degree
by
Jennifer Sun Runyan
has been approved for
The Evergreen State College
by
________________________
Erin Martin, Ph. D.
Member of the Faculty
________________________
Date
ABSTRACT
Seasonal Variation of the Genus Dinophysis within Puget Sound, Washington:
Understanding Harmful Algal Blooms through Species Identification
Jennifer Sun Runyan
Though harmful algal blooms have been present in Puget Sound, Washington for
years, it is only since June of 2011 that Dinophysis has started causing illnesses.
This dinoflagellate exudes dinophysistoxins and okadaic acid which are
responsible for diarrhetic shellfish poisoning. The purpose of this study was to
examine any seasonal patterns exhibited by Dinophysis spp. and to see if the
abundance of Dinophysis spp. varied by location. Lastly, this study assessed
changes in phytoplankton community composition before, during and after the
presence of Dinophysis blooms. Phytoplankton samples were collected from
Sequim Bay, Penn Cove, and Quartermaster Harbor by a citizen science program
known as SoundToxins. Results showed Dinophysis spp. did vary seasonally and
by site. Dinophysis was the most abundant during the summer at all sites and had
a significantly greater abundance during summer at Sequim Bay and
Quartermaster Harbor (p= 0.04, p= 0.037) during this period relative to other
times of the year . Penn Cove had the lowest population of Dinophysis and the
highest variability in salinity throughout the year, suggesting that Dinophysis is
likely impaired by too much freshwater. As for community composition
Protoperidinium was the most positively correlated with Dinophysis at all three
sites (Sequim Bay p<0.001, Quartermaster Harbor p< 0.001 Penn Cove p= 0.024).
Correlations between other species varied by site. Species richness was found to
be greater when Dinophysis was present than when Dinophysis was absent at
Quartermaster Harbor and Sequim Bay (p= 0.001, p<0.001). Currently the
literature does not provide any studies in regard to phytoplankton identification
down to genus level within Puget Sound. These results suggest that Dinophysis
abundance varies seasonally, and is affected by variation in salinity, and such
knowledge is important Washington’s shellfish industry, Native American Tribes,
scientists, and recreational clam diggers. It is important to minimize health risks
and economic loss through early detection of harmful algal blooms.
Table of Contents
LIST OF FIGURES .............................................................................................v
LIST OF TABLES ...............................................................................................vi
ACKNOWLEDGEMENTS .................................................................................vii
INTRODUCTION ...............................................................................................1
LITERATURE REVIEW ....................................................................................4
Introduction ..........................................................................................................4
Harmful Algal Blooms .........................................................................................6
Other Economic and Human Impacts of Harmful Algal Blooms in
Washington ..............................................................................................12
Phytoplankton Ecology ............................................................................15
METHODS ..........................................................................................................20
Site Description ........................................................................................20
Quartermaster Harbor ..............................................................................20
Penn Cove ................................................................................................20
Sequim Bay ..............................................................................................21
Sound Toxin Sample and Data Collection ...............................................22
Lab Analysis ............................................................................................22
Statistical Analysis ...................................................................................24
RESULTS ............................................................................................................26
Variations in Dinophysis ..........................................................................26
Dinophysis and Phytoplankton Community Composition
Correlations ..............................................................................................29
Differences in Phytoplankton Communities ............................................31
Diversity of Phytoplankton Communities ...............................................34
iv
Temperature-Salinity Characteristics.......................................................35
DISCUSSION ......................................................................................................38
Seasonality of Dinophysis ........................................................................38
Phytoplankton Community Composition ................................................41
Phytoplankton Diversity ..........................................................................47
INTERDISCPLINARY STATEMENT AND CONCLUSIONS ........................52
Ocean Acidification and Climate Change Impacts on Harmful Algal
Blooms .....................................................................................................52
Washington Tribes ...................................................................................61
Citizen Science.........................................................................................64
CONCLUSION ....................................................................................................66
v
List of Figures
Figure 1. Map of Study Sites ..............................................................................21
Figure 2. Seasonality of Dinophysis ...................................................................28
Figure 3. NMS Ordinations at Three Sites..........................................................33
Figure 4. Variability of Surface Temperatures ...................................................36
Figure 5. Variabilitiy of Surface Salinity ............................................................36
Figure 6. Abundance of Dinophysis and Correlated Genera ..............................45
Figure 7. Climate Change Shellfish Toxicity .....................................................57
vi
List of Tables
Table 1. Diatom and Dinoflagellate Differences ................................................6
Table 2. Significantly Correlated Genera with Dinophysis ................................31
Table 3. Phytoplankton Species Richness, Evenness, and Diversity ..................34
Table 4. Phytoplankton Correlated with Dinophysis ..........................................45
vii
List of Appendices
Appendix 1. Phytoplankton Abundance at Sequim Bay ......................................76
Appendix 2. Phytoplankton Abundance at Quartermaster Harbor ......................90
Appendix 3. Phytoplankton Abundance at Penn Cove ........................................105
viii
Acknowledgements
I want to thank all the people that have supported me during this entire thesis process. In
particular, I would like to thank Dr. Erin Martin for her guidance and incredible support. I
would also like to thank Dr. Gerardo Chin-Leo for his wise phytoplankton insight. I also
would like to thank Teri King from Washington Sea Grant who has taken time out of her
busy schedule to help form this thesis and for allowing me to work with SoundToxins.
Lastly, but most importantly, I would like to thank my friends, family, and especially
Eugene Disney for all of their love and support.
ix
INTRODUCTION
With harmful algal blooms (HABs) increasing in frequency, it is important to gain
a better understanding of their function within the marine food web (Lewitus et al. 2012;
Smayda & Reynolds 2001). Phytoplankton are not only the base of the marine food web,
but also provide a significant amount of oxygen to the atmosphere and the water, and also
aid in carbon sequestration (Anderson et al. 2012; Archer 2010). The invisible world in
which phytoplankton live in, is a difficult one filled with fierce competition. This
includes competition between phytoplankton species for nutrients and competition to
avoid predation by zooplankton, small fish, bivalves, or even other phytoplankton
(Pitcher et al. 2010; Kozlowky- Suzuki et al. 2006; Smayda & Reynolds 2003; Smayda &
Reynolds 2001). Phytoplankton have developed special adaptations to survive these
rivalries. One adaptation is through development of toxins. Toxin production not only
provides an anti-predatory defense mechanism, but is also a way to combat intraspecific
competition (Smayda 1997). Though this toxin production is aimed towards
phytoplankton survival, larger marine organisms and humans are caught in the crossfire.
Therefore, it is integral to understand what causes harmful algal species to bloom, how
our health is affected by them, and to set up proactive measures to combat harmful algal
blooms.
Focusing in on the economic impact of HABs on the aquaculture industry alone,
in the coastal US from 1987-2000, there was an 82 million dollar loss per year due to
harmful algal blooms (Joshens et al. 2010). Puget Sound in Washington is of the largest
producers of shellfish, especially for clam and mussel sales. In 2003, there was a 19
million dollar loss (13.5 million pounds) in the local shellfish industry due to a harmful
1
algal bloom (Trainer et al. 2007). Not only are the economy and the shellfish producers
being affected by these blooms but so are other organisms such as marine mammals,
marine birds, and humans (Lewitus et al. 2012).
Monitoring and accurately detecting harmful algal blooms is critical to promote
human health, the economy, and to ensure the health of the surrounding ecosystems.
SoundToxins is a citizen science organization located within Puget Sound, WA, with
goals of establishing ―a cost-effective monitoring program that will be led by state
managers, tribal harvesters, and commercial fish and shellfish farmers. The SoundToxins
program aims to provide sufficient warning of harmful algal blooms to enable early or
selective harvesting of seafood, thereby minimizing risks to human health and reducing
economic losses to Puget Sound fisheries‖ (www.soundtoxins.org). SoundToxins
monitors the presence and abundance of the follow harmful algal genera: Pseudonitzschia, Alexandrium, Dinophysis, and Heterosigma. These four genera are the main
genera that form HABs within Puget Sound.
These harmful algal bloom species have been in Puget Sound for hundreds of
years. Alexandrium, for instance, was first discovered in Puget Sound in the early 1900s
and monitoring for Alexandrium has been a common occurrence since 1957 (Moore et al.
2009). Dinophysis, another HAB species that has been documented in the global ocean
for many years, is just now starting to cause concern in Puget Sound. In July of 2011 at
Sequim Bay State Park, the first case of illness caused by Dinophysis was reported to
Department of Health. Due to this sudden onset of Dinophysis producing toxins causing
illnesses, scientists have started to pay greater attention to Dinophysis. This thesis is one
of a very few set of studies that use SoundToxins data to understand the seasonality of
2
Dinophysis at several locations within Puget Sound. Further, it is one of the few studies
that has examined Dinophysis distribution in Puget Sound and how it varies seasonally.
Studies in Puget Sound have yet to address phytoplankton community composition down
to the genus level throughout seasons, which tremendously limits our ability to
understand HABs given that community compositional data can provide insight into why
HABs occcur. Understanding phytoplankton succession throughout seasons may give us
an insight into what other phytoplankton Dinophysis commonly occurs with. Therefore, if
we see a particular genus that generally co-occurs with Dinophysis, we can be on the
lookout for Dinophysis. Providing baseline phytoplankton resident data in Puget Sound
waters will enable scientists to use this information to see how the phytoplankton
community might change in the future.
3
LITERATURE REVIEW
Introduction
Recorded deaths from harmful algal blooms have occurred as early as 1793 when
three of Captain George Vancouver’s Royal Navy Crew became ill and one died after
consuming shellfish from Poison Cave in Canada (Lewitus et al. 2012). Phytoplankton
genera such as Alexandrium, Pseudo-nitschia, and Dinophysis are well- known organisms
causing shellfish toxicity to a variety of organisms, including humans. Various
monitoring programs have been put in place to understand where, when, and how these
organisms produce toxins. This because these organisms do not always exude their
toxins.
Long-term monitoring efforts of harmful algal blooms within Puget Sound reveal
that several genera of toxic phytoplankton have been present since the early 1900s. The
genus Dinophysis, which may exude okadaic acid and dinophysistoxins, can cause
diarrhetic shellfish poisoning (DSP) in humans, and has existed in the Pacific Northwest
for many years (Trainer et al. 2013). The first reported case of DSP in Washington was
June 2011 (Eberhart et al. 2013; Taylor et al. 2013; Trainer et al. 2013). Though this DSP
case was the first in Washington state, it is unknown to why the emergence of DSP has
become so prevalent since Dinophysis has been present in Pacific Northwest waters for
many years (Trainer et al. 2013). This puzzle of why DSP has only become a recent
problem has been addressed by organizations such as SoundToxins (a citizen science
harmful algal bloom monitoring network), Washington Department of Health, and
various scientists from NOAA and local tribes, but more work is needed to gain a better
understanding. Current research within Puget Sound has suggested seasonal patterns of
4
Dinophysis as well as possible physical conditions in which this genus thrives, but it is
still unclear if one particular species of Dinophysis causes greater toxin production than
another (Reguera et al. 2014). Though we may have a basic understanding of
Dinophysis seasonality in Puget Sound, weekly monitoring by SoundToxins enables
Department of Health to triage the order in which they test for mussel toxin detection.
Not only is there seasonality within Dinophysis, but also within the phytoplankton
community in general. For example, diatoms dominate in spring, while dinoflagellates
dominate in summer. Though this is a coarse outline of phytoplankton seasonality, the
resolution may be fine-tuned to observe seasonality at the genus level. Understanding
phytoplankton succession at this level may allow greater forecasting of Dinophysis if
there is a specific genus, or perhaps specific combinations of genera, that proceed
Dinophysis. This thesis will address seasonal phytoplankton community succession and
Dinophysis species composition at several locations within Puget Sound. This
information is important because the literature has yet to demonstrate patterns of
phytoplankton genera that are present right before Dinophysis. This thesis will bring us
one step closer to understanding if certain genera can predict the presence of Dinophysis
or if Dinophysis alters the community composition significantly after its presence. This
literature review will provide essential background knowledge of phytoplankton,
phytoplankton ecology, harmful algal bloom dynamics, and how harmful algal blooms
have affected the local economy.
5
Harmful Algal Blooms
Harmful algal blooms (HABs) are defined as algal blooms that negatively affect
the health of marine organisms and humans through one of three main mechanisms:
physical damage, eutrophication, or toxin production (Joshens et al. 2010). These
phytoplankton are generally categorized into two groups, diatoms and dinoflagellates
(Table 1). Most HAB species are dinoflagellates. Smayda (1997) suggests that
flagellates, including those that are considered as HABS, have a lower nutrient uptake
affinity than diatoms, meaning that nutrients are less available to them. Several ways to
combat this include using phycotoxins for intraspecific competition and anti-predatory
defense mechanisms.
General
Characteristics
Range
Habitat
Diatoms
Dinoflagellates
Poles to tropics, most abundant in
polar to temperate regions
All oceans, most successful in
tropics
Freshwater, saltwater, and
brackish water. Found in benthos,
planktos, in sea ice, sediments,
and air. Can be free, living,
epiphytic, endophytic, epizoic,
and endozoic.
Freshwater, saltwater, and brackish
water. Found in benthos, planktos,
interstially in sand and soil, snow,
and sea ice. Can be free living,
symbiotic, or parasitic.
Size Class
5-200 µm
2-200 µm , although Noctiluca can
reach 2mm
Cell Wall
Composed of silica
Composed of cellulose
Patterned variety of pores, ribs,
spines, ridges, and delevations in
frustule (shell).
Presence or absence of plates,
arrangement and shape of plates,
horns, spines, ridges, and
reticulations.
Flagella
None
Two
Morphological
Two orders:
Two groups:
Identifying
Characteristics
6
Differences
Centrales (centric diatoms) which
are radially symmetric, Pennales
(pennate diatoms) which are
longitudinally symmetric)
Desmokonts- two dis-similar
flagella arising from the anterior
part of the cell
Dinokonts- a transverse and
longitudinal flagella
Examples of HAB
species in
Washington
Pseudo-nitzschia spp.
Alexandrium spp, Dinophysis spp.
Table 1. Differences between diatoms and dinoflagellates (Horner 2002)
Physical properties of phytoplankton can physically damage marine organisms.
An example of this would be the siliceous spines from the genus Chaeteroceros. These
spines can stick into the gill filaments of a fish causing irritation. Mucous is then created
by fish to coat the gills in order to relieve this irritation. In promoting greater mucous
production, the gills are no longer efficient enough to extract oxygen from the water,
thereby causing the fish to die from suffocation. Though this type of bloom is rare, there
was an incident in Dabob Bay, Washington in October of 1991 where cell abundance did
reach up to 103 cells per liter (Horner et al. 1997).
Eutrophication, is an indirect, non-toxic mechanism of killing organisms. An
increase in nutrients brings an increase in all types of phytoplankton. Phytoplankton
continue to proliferate until nutrients are depleted. These phytoplankton die and are
consumed by bacteria. These bacteria use up the oxygen in the water column thus
creating anoxic conditions. With a lack of oxygen, many organisms perish (Valeila
1995). In 2003 at Carr Inlet in Puget Sound, Washington, there was a eutrophic event that
was brought upon by a spring bloom and highly stratified waters (Edwards et al. 2007).
7
Other algal blooms are harmful through toxin production. These toxins are
thought to be exuded or are found within the phytoplankton. Zooplankton eat these
harmful phytoplankton, and the toxins bioaccumulate and biomagnify up the food chain.
The end result can be sick marine mammals, birds, and even humans. Humans may
become sick in one of two ways, 1) eating large fish which consumed toxic
phytoplankton and/or 2) eat filter-feeding organisms such as clams, oysters, mussels, and
crabs which have directly fed upon the toxic phytoplankton (Landsberg 2002).
This next section will go into greater depth about one of the harmful algal bloom
species known as Dinophysis. Certain species of Dinophysis may produce a suite of
toxins comprising of okadaic acid, dinophysistoxins, and pectenotoxins (Reguera et al.
2014). This particular genus has only recently become a problem within Puget Sound
since 2011. Therefore, understanding the history of this organism in other parts of the
world, in a lab setting, and its general ecology will enable further research to occur within
Puget Sound.
Dinophysis
There are 120 species of Dinophysis in the world, but approximately only twelve
species of Dinophysis have been found to have okadaic acid and dinophysistoxins in
them. Oddly enough, only six species out of the twelve have been identified in causing
diarrhetic shellfish poisoning (DSP). Within Puget Sound, there are eight species of
Dinophysis where groups such as SoundToxins, monitors for on a weekly basis. Of the
eight species, only six are considered to have okadaic and dinophysistoxins and are as
8
follows: D. fortii, D. acuminata, D. acuta, D. norvegica, D. tripos and D. rotundata
(Reguera et al. 2014; Lewitus et al. 2012; Trainer et al 2010; Maso & Garces 2006).
Though okadaic acid and dinophysistoxins mainly come from Dinophysis,
Prorocentrum has also been suggested to contribute to DSP as well (Reguera et al. 2014;
Trainer et al. 2013). Still, Dinophysis is the main culprit for many of the DSP illnesses
and not Prorocentrum (Reguera et al. 2014). Symptoms of DSP include diarrhea, nausea,
vomiting, and abdominal pains. These effects can start as early as 30 minutes to several
hours after toxin consumption, with complete recovery taking up to three days.
Hospitalization is often rare. Chronic exposure of low levels of okadaic acid has also
been identified as a tumor promoter in the digestive system (Trainer et al. 2013; Trainer
et al. 2010; Manerio et al 2008; Maso & Garces 2006; Van Dolah 2000).
Most Dinophysis spp. are considered as a mixotrophic dinoflagellate, where the
organism can photosynthesize as well as consume ciliates (Hattenrath-Lehmann. et al
2013). In a laboratory culture setting, Dinophysis acuminata and Dinophysis norvegica
preyed upon Myrionecta rubra, a ciliate, by myzocytosis, also known as cellular
vampirism (Imai & Nishitani 2001, Park et al. 2006). D. acuminata fed upon this marine
ciliate by extracting M. rubra’s cytoplasm through D. acuminata’s peduncle (Park et al.
2006). Dinophysis has yet to be seen to selectively feed upon phytoplankton or ciliates in
its natural habitat, but the remains of ciliates have been found in the digestive vacuoles of
D.acuminata, D. norvegica, and D.fortii (Pizarro et al. 2008).
Other organisms, such as shellfish and copepods feed upon Dinophysis. A study
by Kozlowky- Suzuki et al. (2006) showed that copepods readily chose Dinophysis as
9
prey. There was some evidence of copepods decreasing the amount of Dinophysis
consumed as other phytoplankton availability increased. Their results suggested that
copepods ate a significant amount of Dinophysis, enough to reduce their populations.
Okadaic acid and dinophysistoxins accumulation was minimal in the copepods that
ingested Dinophysis, therefore suggesting that these toxins became more dilute within the
copepod. If the copepod were to be eaten by a fish, the fish would have an even more
dilute amount of toxins within it. With this is mind, DSP symptoms can only then be
obtained by humans through the direct consumption of shellfish (Manerio et al 2008).
Though many of these early closures and cases were in Europe, the West Coast of
the U.S. first reported DSP in 2003. Okadaic acid was first discovered in manila clams
grown in British Columbia in low amounts. There have also been cases in California,
Mexico, and Washington. The first DSP reported illness in the United States occurred in
2011 from blue mussels (Mytilus edulis) collected at a pier at Sequim Bay State Park
(Lewitus et al. 2012, Lloyd et al. 2013, Trainer et al. 2013). The first closure in
Washington due to okadaic acid and dinophysistoxins was off of the Pacific coast of
Washington at Ruby Beach in 2012 (Eberhart et al. 2013). It is difficult to understand
why reports of DSP are only recently being reported within the past two years. This
could be due to underreporting of illnesses by the public, a lack of understanding of DSP
by doctors, or of toxic species of Dinophysis only becoming recently present. Unlike
many harmful algal blooms, a change in the color of the water is not indicative of the
presence of Dinophysis (Kozlowsky-Suzuki et al 2006). Cell densities as low as 200
cells/L can cause enough toxin accumulation to cause harm to humans (Trainer et al.
2013).
10
When toxins reach or exceed their prescribe limits, shellfish harvest areas are
either controlled or closed to avoid consumption of toxic shellfish. These measures are
used to prevent contaminated shellfish reaching the marketplace and avoidance of
gastrointestinal discomfort. Various rapid testing techniques such as the Jellett Rapid
Test, ELISA, and the protein phosphatase 2A inhibition assay (PP2A), are currently
being used to detect the presence of dinophysistoxins and oakadaic acid from shellfish
tissue samples. This allowed shellfish growers to test pre-harvest samples thus preventing
any illnesses. A study by Eberhart et al. (2013), tested all three techniques to show if one
test was more effective than the others. The Jellet Rapid Test is an immunochromatographic system similar to pregnancy test strips. The results of the test provided
a high number of false negatives. As for the ELISA, the enzyme-linked immunosorbent
assay, the test provided a false positive 22% of the time. Lastly, the PP2A, showed the
least amount of false negatives and false positives, therefore making it the best choice for
rapid testing of dinophysistoxins and oakadaic acid. These three tests were compared to
the current regulatory testing methods, liquid chromatography with mass spectroscopy, to
ensure accuracy of the rapid tests.
11
Other Economic and Human Impacts of Harmful Algal Blooms in Washington
Pseudo-nitzschia
Pseudo-nitzschia has been observed off the West Coast of the U.S. since the
1920s (Lewitus et al. 2012). This diatom generally produces the marine biotoxin, domoic
acid (DA) and tends to bloom during the late spring and summer (Horner & Postel 1993).
Ten out of the twelve species of Pseudo-nitzschia that reside off the west coast are known
to produce domoic acid. Unfortunately, these species may change in toxin potency
depending on the location of Pseudo-nitzschia. For example, in Washington, the most
toxic Pseudo-nitzschia species are P.pseudodelicatissima, P. cuspidata and P.australis,
while in California, the most toxic are P.autralis and P.multiseries (Trainer et al. 2010).
Domoic acid poisoning in humans is known as Amnesic Shellfish Poisoning (ASP) and
has the following symptoms: headache, gastrointestinal disorders, and short-term
memory loss (affecting the hippocampus). These symptoms can occur as early as 24-48
hours from when the toxic shellfish was consumed (Lewitus et al. 2012; Trainer et al.
2010). Though, shellfish and some finfish are the main way to consume DA, other
organisms have also been known to be vectors of DA and these include Pacific sardines,
northern anchovies (Engraulis mordax), krill (Euphausia pacifica), market squid (Loligo
opalescens), and some benthic invertebrates. ASP also affects other higher trophic
organisms other than humans, such as California sea lions (Zalophus californianus),
harbor porpoises (Phocoena phocoena), common dolphins (Delphinus delphis), grey
whales (Eschrichtius robustus), western grebes (Aechmophorus occidentalis), and other
marine birds and mammals (Bargu et al. 2012; Fire et al. 2010; Shumway et al. 2003;
Scholin et al. 2000)
12
Domoic acid within shellfish was first discovered in Canada when three people
died and 105 people became ill from eating contaminated blue mussels from Prince
Edward Island in 1987 (Lewitus et al. 2012). On the West Coast of the U.S., the first
documented case was in the summer of 1991 off Monterey Bay, California (Fritz et al.
1992). Instead of humans being directly affected by domoic acid, this time Brandt’s
cormorants (Phalacrocorax penicillatus) and brown pelicans (Pelecanus occidentalis)
mortalities occurred from eating anchovies that earlier consumed Pseudo-nitzschia. This
Pseudo-nitzschia event then expanded Northern California, Oregon, and lastly to
Washington by fall of 1991 (Wekell et al. 1994). Off of the Washington coastline, 25
human illnesses were reported due to Amnesic Shellfish Poisoning and the crab fishing
industry was forced to shut down at a $7 million (Lewitus et al. 2012).
In September 2003 at Kilisut Harbor, Washington, a monospecific bloom of
Pseudo-nitzschia australis closed shellfish harvesting. The regulatory limit of domoic
acid is 20 ppm, but when blue mussels were bioassayed for domoic acid concentrations,
levels reached up to 29 ppm. This was the first documented shellfish closure due to
domoic acid within Puget Sound (Bill et al. 2006). Not only were blue mussels (Mytilus
edulis) affected, but so were littleneck clams (Protothaca staminea), manilla clams
(Tapes philippinarum), geoduck clams (Panopea abrupta), and Pacific oysters
(Crassostrea gigas). All of the bivalves listed can expel the toxin over a period of hours
to days, but it is unknown how geoduck clams manage domoic acid. Puget Sound is one
of the largest producers of shellfish, especially for clam and mussel sales which created at
least $19 million (13.5 million pounds) in 2003 (Trainer et al. 2007). Pseudo-nitzschia is
not the only harmful algal bloom genus that has caused problems in Puget Sound.
13
Alexandrium, a dinoflagellate, is another key player in harmful algal blooms within the
Pacific Northwest.
Alexandrium
Alexandrium produces a saxitoxin derivative compounds causing Paralytic
Shellfish Poisoining (PSP) and can be found between May through October all along the
U.S. West Coast (Horner et al. 1997). Alexandrium is not the only dinoflagellate to
produce this toxin but is the main genus associated with PSP in the Pacific Northwest.
Other dinoflagellates which can produce saxitoxin compounds include Gymnodinium and
Pyrodinium (Lewitus et al 2012). Nausea, vomiting, light headedness, and incoherent
speech are some mild symptoms of PSP. The main symptom of PSP starts with numbness
and tingling around the mouth and lips, spreading over the rest of the face, down the
neck, and continuing down the body. In severe cases, there is death due to respiratory
failure. These symptoms can occur 30 minutes to three hours after tainted seafood
consumption (Backer et al. 2006).
The first recorded death of PSP occurred in 1793 when three of Captain George
Vancouver’s Royal Navy crew became ill and one crew member died after consuming
shellfish from Poison Cave (Lewitus et al. 2012). From 1962 to 1989, toxic PSP events
occurred in 22 of the 28 years off the coast of California (Horner et al. 1997). These PSP
events occur quite often and affect many organisms. Shellfish varieties that are generally
affected by PSP include Pacific oysters (Crassostrea gigas), manila clams (Tapes
philippinarum), razor clams (Siliqua patula), geoduck clams (Panopea abrupta), butter
14
clams (Saxidomus giganteus), littleneck clams (Protothaca staminea), varnish clams
(Nuttallia obscurata), various rock scallops, and various mussel species. Not only are
these bivalves affected by PSP, but so are a range of other organisms such as gooseneck
barnacles (Pollicipes polymerus), moon snails (Lunatia heros), spiny lobsters (Panulirus
spp.), Dungeness crabs (Metacarcinus magister), and various whelk and cockle species
(Lewitus et al. 2012).
As mentioned previously, the aquaculture industry within Puget Sound is an
integral part of the local economy. The Washington coast as well as Puget Sound has
been identifying Alexandrium in their waters since the early 1900s. A biotoxin
monitoring program has been set in place since 1957 by Washington’s Department of
Health to test mussel tissue for saxitoxin (Moore et al. 2009). The monitoring program
became useful right away when the first shellfish closure occurred in 1957 at Sequim Bay
and Discovery Bay. There are two possible thoughts on how Alexandrium migrated to
south Puget Sound waters. First, is that currents from Whidbey Island basin brought
Alexandrium further into Puget Sound. Second, Alexandrium cells or toxin concentrations
were not in high enough to raise any concern until 1957. It was not until 1988 when the
first shellfish closure occurred in south Puget Sound at Carr Inlet (Cox et al. 2008).
Phytoplankton Ecology
This section will provide some insight into why certain genera of phytoplankton
bloom through the lens of phytoplankton community interactions, temperatures, and
salinity.
15
Phytoplankton Community Interaction
Seasonal changes in diatom and dinoflagellate assemblages are complex. A study
by Hutchinson (1961) tried to understand why many species of phytoplankton can coexist
while competing for a limited amount of resources. Hutchinson came up with the
―paradox of the plankton‖ suggesting that communities of phytoplankton are organized
by processes beyond nutrient competition such as habitat viability, species interaction,
and phytoplankton dispersal. A study by Cloern & Dufford (2005) took Hutchinson’s
concept of the ―paradox of the plankton‖ and applied it to their study in San Francisco
Bay where they observed phytoplankton species composition for a decade. Cloern &
Dufford came up with eight principles of phytoplankton community assembly and they
are as follows 1) Cell size is determined by nutrient supply and selective grazing, 2)
Diatoms respond quickly to nutrient pulses, 3) Pelagic habitats select phytoplankton
species on the basis of their own form and function, 4) Pelagic communities are shaped
by species interactions across trophic levels, 5) Phytoplankton species have mixed
nutritional modes, 6) Phytoplankton species have variable life histories, 7) Pelagic
ecosystems are open, away from coastal areas , and 8) Communities respond to largescale climatic periodicity. These principles validated Hutchinson’s ―paradox of
plankton‖ and strengthened the current knowledge that phytoplankton composition is
influenced by more than just community composition and nutrients.
Other studies have focused on phytoplankton community composition at a more
coarse scale by trying to understand the seasonal cycle of diatoms and dinoflagellates.
These studies suggest diatoms dominate during spring, heterotrophic organisms and
dinoflagellates dominate during the summer, and dinoflagellates dominate in the late
16
summer and early fall (Margalef 1978, Smayda & Reynolds 2003; Pitcher et al. 2010).
Margalef’s Mandala (1978) supports the seasonality of phytoplankton by suggesting that
phytoplankton adaptations are specific to their habitat types, which are defined by
turbulence intensity and nutrient concentrations (Cloern & Dufford 2005; Smayda &
Reynolds 2001). Though there has been much research on phytoplankton community
composition, each study must focus on a variety of factors to understand why a certain
species is dominating the water column. Temperature and salinity are two factors that
will be discussed in further detail.
Temperature
Since the specific heat capacity of water enables the ocean to mildly fluctuate in
temperature, the greatest difference in temperature is found between seasons. Warmer
summer waters bring stratification to the water column where the warmer water layer is
on top, the cooler and saltier water down below. Since calm waters create stratification
which does not allow the diatom frustules to be picked up by the currents, they become
too heavy and sink to the bottom (Lehman 2000). Dinoflagellates, on the other hand, do
well in these stratified waters since they have two flagella which enable them to move up
and down the water column. It is the flagella that enable the dinoflagellates to become the
more dominant group of phytoplankton during the summer and early autumn months
(Trainer et al. 2010).
Gisselson et al. (2002) suggest that D.novegica cells aggregating along the
thermocline at 15 to 20 m depth and the presence of digestive vacuoles in up to 22% of
the population found there shows that D.norvegica can find suitable prey at the
17
thermocline. There is also some evidence that Dinophysis spp. migrate vertically within
the water-column at some locations but not at others (Gonzalez-Gil et al. 2010;Pizzaro et
al. 2008). Other studies have shown that Dinophysis spp. may prefer certain temperature
ranges such as D.acuminata being significantly correlated with temperatures ranging
from 11.1 to 26.6°C (Hattenrath-Lehmann et al. 2013). Another study by Gonzalez-Gil et
al. (2010) suggested that D.acuminata can be observed at temperatures from 13 to 22°C.
This wide temperature range attributes to D.acuminata’s long growing season (spring to
autumn) (Reguera et. al 2014). Though temperature has been discussed in relation to
seasonality or as an independent factor, temperature does not act independently. Salinity
may vary depending upon the temperature of the water since warmer water generally
holds saltier water.
Nutrients
Salinity may also play a role in phytoplankton ecology where high nutrient
concentrations are generally found either at or below the pycnocline (Anderson et al
1995). Many HAB species, such as Dinophysis, have been found to take advantage of
this nutrient gradiation through a 24 hour vertical migration. Since Dinophysis, and all
dinoflagellates, have flagella, these flagella enable them to move through the water
column. During the night, dinoflagellates will migrate downwards towards the nutrient
rich pycnocline region where they can uptake nitrates and other nutrients. During the day,
these dinoflagellates migrate back up to the surface waters in order to use the sunlight
and the nutrients that they recently acquired for photosynthesis (Anderson 1995).
18
Dinophysis has been found anywhere between 29 to 34 parts per thousand (Gonzalez-Gil
et al. 2010 ; Pizarro et al. 2008; Aubrey et al. 2000; Peperzak 1996). This adaptation also
allows them to do well in areas where there’s a great amount of freshwater input, where
the freshwater creates a layer on top of the salt water (Trainer et al. 2013).
Even with understanding temperature and salinity, nutrients are another important
factor in understanding phytoplankton community composition and even toxin
production in HABS. Other factors that are also important in understanding harmful algal
bloom dynamics and community composition are competition between phytoplankton
genera and phytoplankton predation. These three factors were not integrated into this
study due to the lack of time and data availability. Therefore, this thesis focused
primarily on temperature, salinity, and seasonality data of phytoplankton genera
composition collected from the SoundToxins volunteers. This study focuses on
phytoplankton community composition in relation to Dinophysis species presence in
Puget Sound. This study hopes to elucidate on several questions: 1) Does the presence of
Dinophysis species vary seasonally within Puget Sound 2) does Dinophysis species also
vary by location with varying salinity levels and 3) are there certain phytoplankton
communities that are present either before, during, or after Dinophysis presence?
19
METHODS
Site Description
Three current sampling sites from SoundToxins were chosen out of 15 sites that
spread over Puget Sound. The sites are as follows: Penn Cove, Sequim Bay, and
Quartermaster Harbor (Figure 1). Each location chosen provided comprehensive data
sets on a weekly (March through October) or bi-weekly basis (November- February)
throughout 2012—2013. Comprehensive regular phytoplankton sampling, water and air
temperature measurements, and salinity measurements were conducted. Furthermore,
volunteers for the sites have also been consistent throughout 2012 to 2013.
Quartermaster Harbor
Quartermaster Harbor (47° 22' 20.748" W, -122° 27' 15.6522" N) is a shallow,
southward facing bay between Vashon and Maury islands and connects over a shallow
sill to the southern end of the Main Bain in south Puget Sound (Figure 1). The shallow
inner bay has an average depth of 6 m (Tobin & Horner 2010). Phytoplankton tow from
these locations were generally taken at two to three meters in depth from Quartermaster
Harbor marina.
Penn Cove
Penn Cove tidelands (48° 14' 1.0782" W, -122° 43' 23.34" N), located in Whidbey
Basin, contains the waters east of Whidbey Island and North of the Main Basin. There is
no sill across the entrance to the Whidbey Basin, therefore, it is a much deeper basin with
depths ranging from 8 m in Skagit Bay to 177 m in Saratoga Passage, between Whidbey
20
Island and Camano Island. This relative shallowness is accompanied by a high
percentage of tidelands (Downing 1983).This location is also intermediate in depth
between shallow Quartermaster Harbor and deep Sequim Bay. Penn Cove samples are
taken from the Penn Cove Shellfish Farm dock.
Sequim Bay
Sequim Bay (48° 2' 28.1616" W, -123° 1' 32.1378" N ) is connected to the ocean
by the Strait of Juan de Fuca, with the passage having a maximum depth of 200 m and
160 km in length. A double sill, located in Admiralty Inlet, at the entrance of Puget
Sound separates it from the Strait of Juan de Fuca (Moore et al. 2008). Sequim Bay
samples are taken from a dock located within Sequim Bay State Park.
Penn Cove
Sequim Bay
Quartermaster Harbor- Dockton Pier
Figure 1. Puget Sound, Washington, showing locations of sampling locations.
21
SoundToxin Sample and Data Collection
Samples were originally collected by volunteers of the SoundToxins harmful algal
bloom monitoring program (Chadsey et al. 2011). SoundToxins protocol had volunteers
collect vertical net tow samples using a 20-µm mesh net from a dock several meters from
the shore. This tow was conducted by first determining the depth of the water column at
the time of the tow. Once the general depth was known, the plankton net was cast down
close to the bottom and then towed upwards throughout the water column at
approximately 1 meter/second. This was repeated two additional times. Depths of the
tow varied, but were generally around one meter to four meters. Net tow samples were
poured into 20 mL scintillation vials and preserved by adding 1mL of a 1% buffered
formalin solution.
To obtain water temperature and salinity data, a thermometer was put into the
bucket holding the surface sea water. The data collector allowed the thermometer to be
submerged in the water for one minute and before the reading was taken. In order to
determine salinity, one or two drops of the water from the bucket were added to the
refractometer. This data was then added to the SoundToxins website.
Laboratory Analysis
Only archived samples collected from April 2012 to April 2013 were analyzed.
Samples collected in the field by the volunteers were analyzed and preserved within
several hours of sample retrieval. To take a subsample of this preserved net tow sample,
the scintillation vial is first mixed at least 20 times to create a homogenous solution.
22
Relative phytoplankton abundance was determined on a 0.1 ml aliquot of the sample.
Though the community composition is recorded by relative abundance, the main focus of
SoundToxins is to identify, enumerate, and report the presence of specifically four toxic
genera (Pseudo-ntizschia, Alexandrium, Heterosigma akashiwo, and Dinophysis).
For this study, all of the phytoplankton present within the sample were identified
and enumerated down to genus level, and all Dinophysis were identified to species level
on a Palmer Maloney counting cell (holding the 0.1 ml aliquot of the sample) on a Zeiss
Universal Compound Microscope using phase contrast and light illumination (Hasle
1978). Smaller flagellates and some zooplankton that were difficult to discern due to the
formalin preservation were not included in enumeration. Severely dense net tow samples
were counted only using half of the chamber (Guillard 1978). Samples were enumerated
in triplicates. Net tow enumeration data and cod end volume (the volume of the collection
container attached to the phytoplankton net) were used to calculate whole water
abundance (Equation 1).
cells
cells
Net tow cell concentration (
) x Cod end volume(L) Total volume filtered (L) Whole water cell abundance (
)
L
L
Equation 1. Calculation for whole water cell abundance from net tow samples.
Whole water cell abundance (henceforth referred to as cell abundance) was used to
understand seasonality of phytoplankton and to note any trends of a particular genus that
happened to be present, before, during, or after the presence of Dinophysis.
In order to calculate variability between subsamples of an aliquot, triplicate whole
water abundances were first averaged. Standard deviation, standard error, and coefficient
of variation were then calculated for each sample.
23
Statistical Analysis
All data was checked for normality. That data was not normally distributed even
when the data was log and square-root transformed. Therefore, resampling methods were
applied.
Resampling ANOVAs were used to determine significant difference between
sampling sites and seasonality of Dinophysis for each site. Resampling correlations were
used to understand if there was any correlation between Dinophysis and any other
phytoplankton genera. Those genera significantly correlated with Dinophysis were used
to gain a refined understanding of when those populations bloomed in relation to
Dinophysis. Temperature and salinity were two other factors correlated with Dinophysis.
MRPP/NMS Ordinations were used to see if there was a pattern between
Dinophysis and the phytoplankton community at each site. At each site, the seasonal
fluctuations of Dinophysis abundance provided the breaks in bins by which Dinophysis
was grouped. All phytoplankton genera present within each site were also categorized
based upon the Dinophysis abundance. Pair-wise comparisons were also calculated to
highlight any significant differences between each phytoplankton community based on
the set criteria. In Quartermaster Harbor, three criteria were set as (1) No Dinophysis, (2),
Dinophysis cell abundance less than or equal to 20 cells/L, (3) Dinophysis cell abundance
greater than 20 cells/L. The change in criterion was set at 20 cells/L because that was
the lowest concentration of Dinophysis present throughout the year. In Sequim Bay,
three criteria were set as (1) No Dinophysis, (2) Dinophysis cell abundance less than or
equal to 350 cells/L, and (3) Dinophysis cell abundance greater than 350 cells/L. In Penn
Cove, three criteria were set (1) No Dinophysis and (2) Dinophysis population less than
10 cells/L, and (3) Dinophysis population greater than 10 cells/L.
24
Lastly, species evenness, species richness, Simpson’s diversity index, and
Shannon-Wiener’s diversity index were conducted twice, once when Dinophysis was
present and then again when Dinophysis was not present to understand if Dinophysis may
impact these measurements of phytoplankton community.
25
RESULTS
Variations in Dinophysis Abundance at Different Sampling Locations
All sites exhibited seasonality within Dinophysis with higher concentrations
during the summer and the lower concentrations during the winter. Specific trends such
temperature, salinity, phytoplankton community composition in relation to the presence
of Dinophysis, and the differences between phytoplankton communities will be described
below.
At Quartermaster Harbor, Dinophysis abundance ranged from 0 to 184 cells/L
over the course of the year, with higher estimates of abundance during the summer. To
understand if there was a difference between Dinophysis and seasonality at Quartermaster
Harbor, a resampling ANOVA was conducted and showed there was a significant
difference between seasons (p-value= 0.001, F (3,29)). The fall average was 7± 9
cells/L. The spring combined average was 0± 0 cells/L. In summer, the average was 75±
63cells/L. In winter, the average was 1.5± 2.5 cells/L.
At Sequim Bay, Dinophysis abundance ranged from 0 to 1393 cells/L over the
course of the year, with the higher estimates of abundance during the early fall. To
understand if there was a difference between Dinophysis and seasonality, a resampling
ANOVA was conducted and showed a significant difference (p=0.05, F (4,34)). In the
fall the average was 280 ± 523.5 cells/L. In spring 2012 and 2013 combined average was
200± 309.1 cells/L. In summer, the average was 408± 253.3 cells/L. In the winter, the
average was 0± 0 cells/L.
26
Dinophysis exhibited the lowest abundance measurements over the course of the
year at Penn cove with cell counts ranging from 0 to only 36 cells/L. This resampling
ANOVA showed no significant viability seasonally (p-value= 0.487, F(3.19). In the fall,
the average was 0± 0 cells/L. In spring of 2012 and 2013 combined, the average was 6
±13.4 cells/L. In summer, the average was 9 ± 15.4 cells/L. In winter, the average was 2
±2.6 cells/L.
Lastly, a resampling ANOVA was conducted to note the difference of Dinophysis
populations at each location. Dinophysis population data from the entire year was
compared from site to site. No significant differences of Dinophysis populations were
found between locations (p-value= 0.995, F(2,92)). Over the entire data set (April 2012April 2013), the average at Sequim Bay was 242 ±335.1 cells/L. At Quartermaster
Harbor, the average was 23 ±45.7 cells/L. At Penn Cove, the average was 4 ± 9.9
cells/L. Since Dinophysis was not identified numerous times, this lended many zeros in
the data set which could explain the lack of a significant difference even though there
were clear differences in abundance estimates between sites.
27
Abundance (Cells/L)
A 200
150
100
50
0
Apr
Jun
Aug
Oct
Dec
Feb
Apr
Dec
Feb
Apr
Dec
Feb
Apr
2012-2013
Abundance (Cells/L)
B 1400
1200
1000
800
600
400
200
0
Apr
Jun
Aug
Oct
2012-2013
Abundance (Cells/L)
C 40
30
20
10
0
Apr
Jun
Aug
Oct
2012-2013
Figure 2. Seasonality of Dinophysis during 2012-2013 at the A) Quartermaster Harbor, B)
Sequim Bay, and C) Penn Cove.
28
Dinophysis and Phytoplankton Community Composition Correlations
Quartermaster Harbor
There were several phytoplankton genera that were significantly correlated with
Dinophysis. Protoperidinium and Scripsiella were significantly correlated with
Dinophysis (Protoperidinium: p< 0.001, r2=0.55, n =22; Scripsiella: p = 0.007, r2=0.27,
n = 20) Since Dinophysis, Scripsiella, and Protoperidinium are all dinoflagellates, it is
common to see them during the summer months (see explanation in discussion). Lastly,
Coscinodiscus, a diatom, was significantly correlated with Dinophysis ( p = 0.02, r2=
0.23, n= 21) (Table 1).
In Quartermaster Harbor, there were several genera of phytoplankton that were
significantly correlated with Dinophysis but likely arose because there was too little data,
or they were a spurious correlation. Amylax, a dinoflagellate, was significantly
correlated, but to was a spurious correlation since Amylax was rarely present in the
samples (r=0.65, p =0.02, n=3). Gonyaulax, also a dinoflagellate,was also significantly
correlated with Dinophysis, but this was likely spurious (r=0.62, p = 0.026, n=3).
Sequim Bay
There were several phytoplankton genera that were significantly correlated with
Dinophysis. Ceratium, had a significant correlation (p = 0.028, r2= 0.13, n= 15). Two
other dinoflagellates, as in Quartermaster Harbor, Protoperidinium and Scripsiella, were
also significantly correlated with Dinophysis (Protoperidinium: p = 0.001, r2=0.48,
n= 28; Scripsiella: p = 0.02, r2= 0.15, n= 24). Several diatoms were also significantly
correlated with Dinophysis. Pseudo-nitzschia large and small cell type both significantly
29
correlated with Dinophysis (Pseudo-nitzschia large cell type: r= 0.37, p = 0.04, n= 26;
Pseudo-nitzschia small cell type: r= 0.31, p = 0.05, n= 12) (Table 1).
In Sequim Bay, there were several spurious correlations. Kofoidinium, a
dinoflagellate, was significantly correlated with Dinophysis (p = 0.013,, r2= 0.23, n=4).
Oxyphysis, another dinoflagellate, was also significantly correlated with Dinophysis (p=
0.035, r2=0.15, n=4).
Penn Cove
There were several phytoplankton genera that were significantly correlated with
Dinophysis including Ceratium, Chaetoceros, Protoperidinium, Thalassionema, and
Thalassiosira (Ceratium: p = 0.047, r2=0.34, n=5; Chaetoceros: p = 0.011, r2 =0.61,
n= 21; Protoperidinium: p= 0.024, r2= 0.55, n= 14; Thalassionema: p = 0.035, r2=0.49,
n= 16; Thalassiosira: p = 0.042, r2= 0.20, n= 23) (Table 1).
In Penn Cove, Navicula, Licmorpha, and Eucampia were significantly correlated
with Dinophysis (Navicula: p = 0.031, r2=0.34, n=4; Licmorpha : p = 0.001, r2= 0.01,
n=1; Eucampia: p = 0.05, r2= 0.33, n= 2).
30
Genera
Protoperidinium
Ceratium
Scripsiella
Chaetoceros
Thalassionema
Thalassiosira
Coscinodiscus
Penn Cove
0.55
0.34
n/a
0.61
0.5
0.2
n/a
Quartermaster Harbor
0.48
n/a
0.15
n/a
n/a
n/a
0.23
Sequim Bay
0.56
0.13
0.27
n/a
n/a
n/a
n/a
Table 2. Presenting R2 values for significantly correlated genera with Dinophysis.
Differences in Phytoplankton Communities
In order to assess differences in phytoplankton community composition in relation
to Dinophysis, MRPP / NMS Ordinations were conducted for each site.
Quartermaster Harbor
There was a statistically significant difference between the communities (A=0.24,
p=0.001) (Figure 2). Pair-wise comparisons showed greatest difference between criterion
2 and 3, therefore suggesting the greatest difference when Dinophysis populations were
either below 20 cells/L and when Dinophysis cells were greater than 20 cells/L (A=
0.04,p= 0.02). Comparisons between criteria 1 and 3 as well as 1 and 2 did not differ
significantly (Criteria 1 vs. 3: A=0.06, p< 0.001; Criteria 1 vs. 2: A= 0.019, p= 0.12).
Sequim Bay
There was statistical difference between the communities (A= 0.071, p=0.001)
(Figure 2). Pair-wise comparisons showed greatest difference between 1 vs. 2 and 2 vs. 3,
therefore suggesting the greatest difference when Dinophysis populations are between
31
Dinophysis being absent and cell abundance less than or equal to 350 cells/L and a
difference when Dinophysis populations are present at either below or above 350 cells/L
(Criteria 1 vs. 2: A= 0.03, p= 0.01; Criteria 2 vs. 3: A= 0.04, p=0.013). There was no
difference between criteria 1 and 3 (A =0.11, p<0.001).
Penn Cove
There was not a statistical difference between the communities (A= 0.001,
p= 0.67) (Figure 2). This is to be expected since Dinophysis abundance was low
throughout the year, therefore making it difficult to assess any real pattern.
32
Quartermaster Harbor NMS Ordination
Axis 2
Population
No Dinophysis present
Dinophysis population less than 20 cells/L
Dinophysis population greater than 20 cells/L
Axis 1
Sequim Bay NMS Ordination
Axis 2
Population
No Dinophysis
Dinophysis population less than 350 cells/L
Dinophysis population greater than 350 cells/L
Axis 1
Penn Cove NMS Ordination
Axis 2
Population
No Dinophysis present
Dinophysis population less than 10 cells/L
Dinophysis pouplation greater than 10 cells/L
Axis 1
Figure 3. NMS Ordinations at three sites.
33
Diversity of Phytoplankton Communities
Genera richness, genera evenness, Shannon’s diversity index, and Simpson’s
diversity index were calculated at each site. These calculations were conducted twice,
once when Dinophysis was present and then again when Dinophysis was not present to
understand if Dinophysis may impact these measurements of phytoplankton community.
All tests provided non-significant results, except for richness, which yielded significant
differences at Quartermaster Harbor and Sequim Bay (Quartermaster Harbor: p = 0.001;
Sequim Bay: p< 0.001). Richness tended to be greater when Dinophysis was present than
when Dinophysis was absent.
Location
Sequim Bay (P)
Sequim Bay (A)
Penn Cove (P)
Penn Cove (A)
Quartermaster
Harbor (P)
Quartermaster
Harbor (A)
Richness
(S)
17.63 ± 4.08*
11.53 ± 4.13*
12.33 ± 3.61
10.36 ± 3.70
Evenness
(E)
0.49 ± 0.24
0.56 ± 0.31
0.50 ± 0.17
0.60 ± 0.19
Shannon’s
Diversity
Index
(H)
1.36± 0.68
1.35 ± 0.67
1.22 ± 0.41
1.40 ± 0.55
Simpson’s
Diversity
Index
(D')
0.57 ± 0.25
0.59 ± 0.27
0.53 ± 0.18
0.61 ±0 .19
17.37± 4.54*
0.57 ± 0.26
1.61 ± 0.74
0.62 ± 0.28
12.07 ± 5.23*
0.56 ± 0.26
1.22 ± 0.60
0.56 ± 0.26
Table 3. Locations either noted P (Dinophysis present ) or A (Dinophysis absent) with averages
and standard deviations for the following tests: (S) Richness, (E) Evenness, (H) Shannon’s
Diversity Index, and (D’) Simpson’s Diversity Index. * Showed significant p-values.
34
Temperature - Salinity Characteristics
In order to gain greater detail into how Dinophysis may behave, temperature and
salinity data may provide some insight. Temperature within Puget Sound waters varied
by locations but all showed a general trend of the water temperature warming during the
summer and cooling in the winter. Sequim Bay consistently exhibited the coolest
temperatures, which ranged from 6°C to 16°C, thus varying 10°C throughout the year.
Quartermaster Harbor temperatures ranged from 8°C to 19°C, with a slightly larger
variation of 11°C throughout the year. Lastly, Penn Cove temperature ranged from 7°C
to 16°C for 8 months of the year starting on 8/20/2012. Earlier temperature between the
dates of 4/9/2012-8/19/2012 was discarded due to the water quality probe malfunctioning
(Figure 1).
Surface salinity within Puget Sound also varied by locations. Penn Cove had the
most estuarine conditions with salinity measurements varying between 19-30 ppt, while
Sequim Bay’s salinity was the highest, with measurements of 30-35ppt. Quartermaster
Harbor’s salinity measurements were in between the other two sites with salinity readings
of 23-29 ppt (Figure 1). These salinity measurements are analogous to their locations
with Penn Cove’s salinity having the greatest variation being located near the Skagit
River in a more estuarine environment, while Sequim Bay has much of an oceanic
influence (ocean salinity is around 33ppt). Given the large variability in temperature and
salinity, these factors could be the cause of variability in abundance of Dinophysis.
Temperature and salinity were not significantly correlated with each other (Penn
Cove r=0.46, p = 0.996; Sequim Bay r= -0.72, p = 1; Quartermaster Harbor r= -0.27, p =
0.929).
35
Temperature (degrees Celcius)
20
18
16
14
12
Quartermaster Harbor
10
8
Penn Cove
6
Sequim Bay
4
2
0
Dec
Apr
Jul
Oct
Jan
May
2012-2013
Figure 4. Surface temperature at the three sampling sites.
40
35
Salinity (ppt)
30
25
20
Quartermaster Harbor
15
Penn Cove
Sequim Bay
10
5
0
Dec
Apr
Jul
Oct
Jan
May
2012-2013
Figure 5. Variability in surface salinity at all three sites.
To assess whether these environmental variables influenced the abundance of
Dinophysis, correlation analysis was conducted between Dinophysis abundance and these
variables. However, Dinophysis abundance was not significantly correlated with salinity
36
at any of the three sites(Penn Cove: r= 0.27, p = 0.137; Sequim Bay: r= -0.49, p =1;
Quartermaster Harbor: r= -0.46, p = 0.999).However, Dinophysis was significantly
positively correlated with temperature for Quartermaster Harbor (p= 0.037, r2= 0.28). As
for Penn Cove, there was not a significant correlation between Dinophysis populations
and temperature (p = 0.325, r2= 0.07). Lastly, in Sequim Bay, there was a significant
relationship between Dinophysis population and temperature (p = 0.004, r2= 0.31).
Protoperidinium was also significantly correlated with Dinophysis at all three
sites, therefore, could temperature affect Protoperidinium, which then may be influencing
the abundance of Dinophysis? At Sequim Bay, Protoperidinium and temperature were
significantly correlated (p =0.001, r2= 0.53). At Quartermaster Harbor, Protoperidinium
and temperature were also significantly correlated (p= 0.015, r2= 0.35). However,
Protoperidinium was not significantly correlated with salinity at these sites. However, at
Penn Cove, Protoperidinium and temperature were not significantly correlated (p= 0.067,
r2= 0.60) while Protoperidinium and salinity were significantly correlated (p= 0.042, r2=
24).
37
DISCUSSION
The focus of this study was to address the following questions: 1) Is there
seasonal variation in Dinophysis between the three locations within Puget Sound with
contrasting influence to the ocean sites, 2) Does the presence of Dinophysis species also
vary by location, and 3) Are there certain phytoplankton communities present either
before, during, or after Dinophysis presence. This discussion section will address each
question individually in detail.
Seasonality of Dinophysis
Dinophysis displayed multiple peaks in abundance (cells/L) at all sites.
Quartermaster Harbor and Sequim Bay had the greatest Dinophysis abundance for the
longest amount of time, spanning almost four months, bracketing the summer dry season,
from June to October. As for Penn Cove, Dinophysis abundance peaked during three
months, April, August, and December. Dinophysis’ presence in the summer is part of the
dinoflagellate seasonality. Dinoflagellates can outcompete diatoms during the summer
when waters are more stratified due to non-upwelling conditions that stratify the water
and create salinity and temperature gradients. Snowpack melting during the late spring
and early summer allows for additional freshwater input while the lack of upwelling
creates calm waters enabling surface water temperatures to increase (Lehman 2000;
Horner et al. 1997; Moore et al. 2008). Diatoms prefer upwelling conditions (generally
during the spring) which allow nutrients, such as silica, to be ready available towards the
surface of the water column, where diatoms typically reside (Trigueros & Orive 2001;
Cloern & Dufford 2005; Smayda & Reynolds 2001). In contrast, dinoflagellates have
flagella that allow them to move up and down the water column, enabling them to
38
outcompete other phytoplankton when nutrients become stratified within the water
column and are depleted from surface waters. This mobility allows them to move
towards the top of the water column to photosynthesize and then down a bit further to
take up nutrients (Gonzalez-Gil et al. 2010; Anderson 1995). Though a stratified water
column generally proves advantageous to Dinophysis and other dinoflagellates, an
overabundance of freshwater may diminish their populations as shown at Penn Cove.
Dinophysis abundance was 1-2 orders of magnitude less at Penn Cove than the
other two sites. The abundance of Dinophysis present at Penn Cove also peaked during
the summer, but also peaked in April and December. Mackas & Harrison (1997) suggest
that approximately one-fourth to one-third of the freshwater input into Puget Sound is
due to Skagit river runoff into Skagit Bay. With Penn Cove situated in Skagit Bay, this
could be one possible explanation as to why there was such a strong difference in
population at this site in comparison to Quartermaster Harbor and Sequim Bay.
Dinophysis was present throughout the rest of the year, but in small numbers. Maximum
abundance reached 36 cells/L in April, then again at 32 cells/L in August, and lastly with
the smallest peak with 7 cells/L in December. Penn Cove had the greatest amount of
freshwater influence with salinity ranging from 19 to 33 ppt. Though salinity may be a
key factor to why Dinophysis abundance is so low (see discussion below) , other factors
such as temperature may also play a role.
Looking into relationships between Dinophysis abundance and temperature /
salinity may also provide further support that populations are controlled by seasonal
factors since Dinophysis are usually associated with warm surface water temperatures,
stable salinities, and low nutrients (Trainer et al. 2010). Water temperature can be a
39
controlling factor for phytoplankton abundance and can reflect seasonal changes
(Lehman 2000). As stated earlier, Dinophysis prefers warmer, stratified waters, which
are found generally during the summer. Sequim Bay is a good example of this for when
temperatures reached above 10° C, Dinophysis abundance was always greater than 200
cells/L, from June through October. This time period represented the highest cell counts
that were found throughout the year. This is consistent with a study by Gonzalez- Gil et
al. (2010) which suggested that Dinophysis acuminata was observed at temperatures from
13 to 22°C. As such, Sequim Bay’s correlation between Dinophysis and temperature
showed a strong positive relationship. Quartermaster Harbor also showed a strong
positive correlation between Dinophysis and temperature, where abundance was
maximized at temperatures at 16°C during the summer. As for Penn Cove, the
temperature probe malfunctioned, therefore providing inaccurate readings. Nonetheless,
at Penn Cove during the summer, the second largest peak in Dinophysis was in August.
Though positive correlations were found between Dinophysis and temperature, much of
the stratification within the water column in Puget Sound is due to changes in salinity,
driven by freshwater inputs instead of temperature driven (Moore et al. 2008).
Salinity gradients also occur depending on the location of the sampling site within
Puget Sound. Sequim Bay has the greatest salinity due to its proximity to the ocean,
while Penn Cove, has more of an estuarine environment due to the freshwater output
from the Skagit River. Studies have suggested that Dinophysis prefers salinity levels
from approximately 29-34 parts per thousand and/or maybe be found either in or below
the pycnocline (Gonzalez-Gil et al. 2010 ; Pizarro et al. 2008; Aubrey et al. 2000;
40
Peperzak 1996). The phytoplankton community structure may also change depending
upon the salinity as well as temperature.
Phytoplankton Community Composition
Phytoplankton communities are shaped by species interactions across trophic
levels, their nutritional modes, their form and function, and life histories (Cloern &
Dufford 2005). Therefore, understanding which phytoplankton either come before, coexist, or follow Dinophysis may provide additional insight into what we do not currently
know about Dinophysis. For this study, seasonal phytoplankton succession was
noticeable at each site. Diatoms dominated spring, early summer, and fall, while the
dinoflagellates dominated during the late summer at all three sites. This pattern is
consistent with other reports in temperate regions, where diatoms are also prevalent
during spring and fall months (Rynearson et al. 2006). Sequim Bay had the greatest
abundance of diatoms with a peak at 289,061 cells/L and dinoflagellates with a peak at
9,068 cells/L . Not only did Sequim Bay have the greatest abundance of diatoms and
dinoflagellates, but it also was the most diverse. Sequim bay had 48 genera total, with 31
diatom genera and 17 dinoflagellate genera. Quartermaster Harbor was next with 42 total
genera, 26 genera belonging to diatoms and 16 genera belonging to dinoflagellates.
Lastly, Penn Cove had 33 total genera with 25 genera belonging to diatoms and 8 genera
belonging to dinoflagellates. Though Penn Cove had the most variable range in salinity
which were suitable for phytoplankton growth and survival, the temperature range (716C) was the coolest out of all three sites. The combination of temperature and select
salinity values during the winter and early spring were not as favorable for phytoplankton
growth (Cloern & Dufford,2005). Though there was much variability in the amount and
41
type of phytoplankton present at each site, seasonal community succession was a
constant.
Our phytoplankton community succession data followed Margalef’s Mandala,
which suggests that phytoplankton seasonal variability starts with a general void of
phytoplankton in the winter, a diatom bloom during the spring, then a dinoflagellate
bloom during the summer and early fall (Pitcher et al. 2010; Smayda & Reynolds 2001;
Margalef et al. 1979). This general knowledge of when certain groups of phytoplankton
are present throughout the year provides a baseline to when we can supposedly expect
certain types of phytoplankton, especially harmful algal blooms. Unfortunately, there is
still much uncertainty regarding when harmful algal blooms may occur due to their
complex nature. Smayda & Reynolds (2003) suggest that diatom blooms have five
major features to their bloom behavior, but that dinoflagellate blooms, in contrast, are
unpredictable and ephemeral. Some of the positively correlated phytoplankton with
Dinophysis in the data set have similar characteristics to Dinophysis , such as taxonomy,
habitat, temperature, and/or salinity preferences. These may be beneficial in providing a
better understanding of this complex dinoflagellate.
In order to gain a finer resolution into the community composition data,
correlations between Dinophysis and all genera at each site were performed. Certain
phytoplankton genera were positively correlated with Dinophysis, and they all varied
dependent upon the site. Protoperidinium spp. was the only genus significantly correlated
with Dinophysis at all three sites. Protoperidinium and Dinophysis not only both
consume smaller phytoplankton but are also considered neritic species (Gonzalez-Gil et
al. 2010; Trigueros & Orive 20010), Therefore, due to their common neritic habitat,
42
feeding in similar trophic levels, and preference for stratified waters, it would not be
uncommon to observe Dinophysis around the same time as Protoperidinium. Therefore,
could Protoperidinium be used to forecast the presence of Dinophysis? Unfortunately,
this was not the case. Protoperidinium came before, co-existed, and followed
Dinophysis.
At Quartermaster Harbor, additional genera that were positively correlated with
Dinophysis included Scripsiella trochoidea, and Coscinodiscus spp. (Table 4).
S. trochoidea is a cosmopolitan species found in coastal temperate waters. Coscinodiscus
spp. found in Washington are generally considered a cosmopolitan genus found within
temperate waters (Horner et al. 2002). Scripsiella has been found present before
Dinophysis due to nutrient control under vertical stratification of the water column
(Pitcher et al. 2010; Smayda & Reynolds 2001). Though Scripsiella did show a positive
relationship with Dinophysis, Scripsiella was not a consistent precursor to Dinophysis at
Quartermaster Harbor.
At Sequim Bay, additional genera significantly correlated with Dinophysis
included Ceratium fusus, Scripsiella trochoidea, and Pseudo-nitzschia spp.(Table 4).
C. fusus is a cosmopolitan dinoflagellate that can be found in estuarine and oceanic
environments (Horner 2002). Therefore, Sequim Bay is a suitable habitat for C. fusus.
Though some of the literature states that C. fusus grows better when temperatures are
above 16⁰ C and salinity between 12-38 ppt, our data does not show an increase in C.
fusus abundance above 16⁰ C. Other literature has suggested that phytoplankton
communities consisting of Dinophysis acuminata, Ceratium spp, and Protoperidinium
are all considered larger neritic species that take advantage of a stratified water column
43
with high seasonal irradiance, which is normally present during the summer (GonzalezGil et a. 2010; Pizarro et al. 2008; Smayda & Reynolds 2001; Trigueros & Orive 2001).
Lastly, Pseudo-nitzschia spp. is a diatom that can be present throughout summer and that
can grow under a wide range of conditions from polar to temperate and equatorial waters
to neritic and open ocean environments (Orsini et al. 2004; Horner et al. 2000).
At Penn Cove, additional genera significantly correlated with Dinophysis include
Chaetoceros spp., Thalassiosira spp., and Thalassionema nitzschioides (Table 4).
Chaetoceros spp. is a diatom that does well in a variety of conditions from neritic to
pelagic ,estuarine or oceanic, and even warm to temperate waters (Horner 2002).
Chaetoceros’s versatility allows it to be a dominant phytoplankton genus for most of the
year for all three sites. It is only at Penn Cove, that Chaetoceros spp. is significantly
correlated with Dinophysis. Thalassiosira is another versatile diatom abundant at each
site, but is only correlated with Dinophysis at Penn Cove (Horner 2002). Lastly,
Thalassiosira is a cosmopolitan diatom found in neritic and coastal waters and been
found to bloom in late summer off the coast of British Columbia (Hay 2003; Horner
2002). These correlations provide insight into what is co-occuring alongside of
Dinophysis, but assessing how these phytoplankton groups distribute themselves in
different Dinophysis population gradients may provide another avenue to examine how
phytoplankton behave.
44
Site
Penn Cove
Penn Cove
Penn Cove
Quartermaster Harbor
Quartermaster Harbor
Quartermaster Harbor
Sequim Bay
Sequim Bay
Sequim Bay
Sequim Bay
Sequim Bay
Genus
Protoperidinium
Chaetoceros
Thalassionema
Protoperidnium
Coscinodiscus
Scripsiella
Protoperidnium
Scripsiella
Ceratium
Pseudo-nitzschia Lg
Pseudo-nitzschia Sm
p-value
0.001
0.011
0.035
0.001
0.02
0.007
0.001
0.02
0.028
0.04
0.05
Table.4. Phytoplankton genera that are positively correlated with Dinophysis at each site. The pvalue denotes the significance of the correlation.
A)
Cell Abundance (Cells/L)
100000
10000
Chaetoceros
1000
Dinophysis
100
Protoperidinium
10
1
4/12
6/12
8/12
10/12
12/12
2/13
Cell Abundance (Cells/L)
B)
400
300
Dinophysis
200
Coscinodiscus
Protoperidinium
100
0
4/9
6/9
8/9
10/9
12/9
2/9
45
Cell Abundance (Cells/L)
C)
1500
1000
Dinophysis
Scripsiella
500
Protoperidinium
0
4/2
6/2
8/2
10/2
12/2
2/2
4/2
Figure 6. Abundance of Dinophysis and the most positively correlated genera at each site. a)
Penn Cove, b) Quartermaster Harbor, and c) Sequim Bay.
Referring once more to Cloern & Dufford (2005) they suggest that phytoplankton
communities are shaped by species interactions across trophic levels, their nutritional
modes, their form and function, and life histories. NMS ordinations were performed to
get a better understanding of whether or not the phytoplankton communities were shaped
by the presence of Dinophysis. These group distributions created by the NMS
ordinations allowed us to see if these phytoplankton community groups that might have
been similarly influenced by not only Dinophysis but other possible factors such as
nutritional mode and their form and function.
Each NMS ordination had different Dinophysis population criteria due to the
different amounts of Dinophysis present at each site. At Sequim Bay, the clustering
between groups was the most significant. The greatest difference between groupings was
between the criteria 1 (No Dinophysis) and criteria 2 (Dinophysis cells up to 350 cells/L).
This could be due to a multiple of reasons from Dinophysis using its toxins as a possible
46
phytoplankton deterent (Smayda 1997), to predation, to physiochemical factors
(nutrients, light, currents). Where Sequim Bay had the greatest amount of differences
between groups, Penn Cove had the least. There was no significant difference
phytoplankton between the presence or absence of Dinophysis. Not only is Dinophysis
population low at this location, the freshwater input from the Skagit River could alter the
amount and types of phytoplankton present (Mackas & Harrison 1997). Because of
these factors, it is not unlikely for Penn Cove to have a more homogenous pattern
between their criteria groups. Lastly, at Quartermaster Harbor, the most significant
differences are between criteria 1 (No Dinophysis) and criteria 3 (Dinophysis cells greater
than 20 cells/L). The clustering between these groups also reflect these differences. Since
the difference between criteria 1 and criteria 3 is 20 cells/L, this might be enough of a
difference, while the difference between criteria 1 and criteria 2 is only 10 cells/L. Much
like Sequim Bay, the same reasoning can apply to where these groupings may occur due
to the presence of Dinophysis, predation, or nutrients. Examining species richness,
species evenness, Shannon Weiner’s diversity index, and Simpson’s index might give us
a better idea to why these groupings cluster.
Phytoplankton Diversity
A study by Hutchinson (1961) tried to understand why many species of
phytoplankton can coexist while competing for a limited amount of resources. In the
―paradox of plankton‖, when there is a competition for limited nutrients, the superior
species should be able to outcompete the others, but in fact, that is generally not the case.
Hutchinson came up with a hypothesis for the ―paradox of the plankton‖ suggesting that
communities of phytoplankton are organized by processes beyond nutrient competition
47
such as habitat viability, species interaction, and phytoplankton dispersal. With this
concept in mind, species evenness, species richness, Shannon-Wiener’s diversity index,
and Simpson’s index were calculated to gain a better understanding of how the
phytoplankton communities were composed when Dinophysis was present versus absent.
Species evenness is defined as a measure of relative abundances of species in an
assemblage (Gotelli & Ellison 2013). At all sites, there was no significant difference in
evenness when Dinophysis was present and absent. Though, there was no significant
difference between communities when Dinophysis was present and absent, their midranging values provides us with information that the phytoplankton community was a bit
patchy in their distributions. A possible flaw in separating the groups into presence and
absence of Dinophysis is that Dinophysis will be present when conditions are right for
dinoflagellates to grow and when Dinophysis is absent, the conditions will be better
suited for diatoms. Consequently, this evenness is measuring more of the seasonal trend,
(with dinoflagellates dominating in the summer and early fall and the diatoms dominating
in the spring) than the in-between periods of when Dinophysis is present for a week and
then absent the next.
Species richness will provide another aspect of community composition by
measuring the number of species in an assemblage (Gotelli & Ellison 2013). Species
richness was significantly higher at Sequim Bay and Quartermaster Harbor when
Dinophysis was present, but not Penn Cove. These results seem a bit counterintuitive,
since Smayda (1997) suggested to the reason why some dinoflagellates are toxic is to
combat intraspecific competition. It may be possible that the presence of Dinophysis may
deter predators therefore allowing a greater diversity of phytoplankton to survive.
48
Shannon-Wiener index and the Simpson’s index both measure species diversity
(Gotelli & Ellison 2013). Both indices at all three sites showed no significant difference
between the presence and absence of Dinophysis. Once more, it is possible that the
diversity measurements could have been compared on a seasonal scale (diatoms vs.
dinoflagellates) than on a weekly or bi-weekly scale. Lastly, it could also be due to a
small sample size since only one year of data was used. Though species evenness and
both diversity indices did not show a significant change in population before and after
Dinophysis, these analyses do show that there wasn’t a monopoly of the phytoplankton
by any one particular genus.
Conclusion
Dinophysis abundance varies seasonally and spatially. Seasonal variation was
significant at Sequim Bay and Quartermaster Harbor. The highest abundance of
Dinophysis was at Sequim Bay, the most oceanic site, followed by Quartermaster Harbor,
and lastly Penn Cove, the most estuarine site. Protoperidinium was the most significantly
correlated with Dinophysis at each site and correlations between other species varied
depending upon the site. Scaling back and looking at the phytoplankton community, the
NMS ordinations showed that Sequim Bay showed the greatest evidence of a significant
pattern suggesting that the phytoplankton community did change depending upon
whether Dinophysis was absent or when Dinophysis cells reached up to 350 cells/L.
Phytoplankton richness was also significantly greater at Sequim Bay when Dinophysis
was present, echoing the NMS ordination. Quartermaster Harbor showed slight
significance between phytoplankton communities and Dinophysis in the NMS ordination
and also showed significance in species richness; once again with species richness greater
49
when Dinophysis is present. Penn Cove showed no statistical differences between
phytoplankton communities and Dinophysis by the NMS ordination and showed no
significant difference in species richness. Knowing when Dinophysis is present, what
species are present, and how the phytoplankton community is being affected will give us
insight into how Dinophysis behaves within Puget Sound.
Understanding how Dinophysis behaves is important to Washington’s shellfish
industry, Native American Tribes, and the general public. It is important to minimize
health risks and economic loss through early detection of harmful algal blooms. One
important result from this thesis is that though Dinophysis is most abundant during the
summer, it is also found at other at other times of the year; therefore, recreational
shellfish consumers should ensure that conditions are suitable for shellfish harvesting
regardless of season.
Dinophysis studies have been published within Puget Sound, mostly after the DSP
event in Sequim Bay State Park from 2011. Since then many scientists from various
organizations including NOAA, Washington Department of Health, and the Jamestown
S’Klallam Tribe, have been trying to gain a better understanding of why Dinophysis has
recently been causing DSP events. This thesis is one of a few studies that are able to
define Dinophysis down to species level at several sites within Puget Sound. Since some
species of Dinophysis are considered to be more toxic than others, understanding what
conditions Dinophysis spp. prefers or cataloging trends of where certain Dinophysis spp.
tend to inhabit, will be quite beneficial. This thesis also provided information on the
seasonal genera found within three sites of Puget Sound, which is the first of its kind.
Horner & Postel (1993) did provide phytoplankton community composition data along
50
the Washington coast, while Newton & Horner (2003) provided phytoplankton
community composition data within Willapa Bay, but not within Puget Sound. Baseline
phytoplankton community composition data will enable future studies to gain a glimpse
into what the phytoplankton community was composed of in 2012-2013. This baseline
data may have implications in ocean acidification or climate change studies to compare
how the diatom, dinoflagellate, or harmful algal bloom community has shifted.
51
INTERDISCPLINARY STATEMENT AND CONCLUSIONS
Harmful algal blooms have profound consequences stretching from loss of
recreational and commercial fishing opportunities, reduction of food supply, and loss of
community identity (Bauer et al.2009). Shellfish have provided sustenance, community
identity, and an important source of income within the recreation and commercial fishing
industries for many coastal communities, but especially local Washington tribes.
Therefore, it is imperative that we are able to understand general characteristics and
preferable conditions of harmful algal blooms, such as Dinophysis, and are able to predict
their future patterns. Washington waters are already starting to feel the effects of climate
change and ocean acidification (Feely et al. 2010). This chapter will discuss how
changing climate conditions will affect harmful algal blooms and how multiple
stakeholders, such as Washington tribes, state agencies, federal agencies, community
members, citizen science organizations and shellfish farms, work collaboratively to
address the complexities of harmful algal blooms. Lastly, I will discuss how this thesis
could be improved for future studies.
Ocean Acidification and Climate Change Impacts on Harmful Algal Blooms
Increasing concentrations of greenhouse gases are expected to lower pH, increase
surface water temperatures, and cause changes to vertical mixing and upwelling (Moore
et al. 2008). The potential consequences of these changes for harmful algal blooms have
only recently been explored. Harmful algal blooms have increased around the world and
are expected to continue to increase as a result of ocean acidification and climate change.
The continuation of an increase of harmful algal blooms will affect the global carbon
cycle, tourism, ecosystems, fishing industry, and human health. The aim of this section is
52
to address how global change (i.e. ocean acidification and climate change) will affect
harmful algal blooms.
Ocean Acidification’s Impact on Phytoplankton and Harmful Algal Bloom Species
An increase in ocean acidity is likely to influence phytoplankton community
composition. This more acidic environment tends to favor certain phytoplankton genera
and inhibit others (Schippers et al. 2004; Hallegraeff 2010) . Looking forward in the next
hundred years or so, Earth is expected to have similar conditions to the Mesozoic era
(Huber et al. 1996). In the Mesozoic era, CO2 levels in the atmosphere were up towards
800 ppm due to large volcanic eruptions. This era favored dinoflagellate and
coccolithophorids because of the low nutrient availability and warm water stratification,
in which ocean temperatures slowly rose worldwide ranging from 17°C to 33°C (Huber
et al. 1995). Today with the ocean waters becoming more acidic, these calcifying
coccolithophorids will find their shells slowly dissolving making it difficult for them to
survive. The dinoflagellates, with their cellulose composition will be able to adapt to
these new waters.
Since dinoflagellates and diatoms have frustules (shells) made out of either
cellulose or silica they are not likely to be susceptible to dissolution under more acidic
conditions. A study by Fu et al. (2010) suggests that saxitoxin production by
Alexandrium was greater under higher pCO2 conditions and with greater amounts of
sunlight due to toxin production being linked to their photosynthetic activity. Other
harmful algal bloom species, such as the diatom Pseudo-nitzschia, can react negatively to
53
a change in pH, whether conditions become more acidic or more basic. Sun et al. (2011)
suggests that Pseudo-nitzschia exude high concentrations of domoic acid in treatments
combing high pCO2 with low pH, which would be expected under conditions of enhanced
ocean acidification. Nutrient limitation such as phosphate under these high pCO2
conditions also increases the amount of domoic acid production by Pseudo-nitzschia.
Other studies have shown the opposite, that a lower pCO2 with higher pH can trigger
Pseudo-nitzschia to create more domoic acid. Lundholm et al. (2004) suggests that under
the stress of pH, Pseudo-nitzschia multiseries produces similar amounts of domoic acid
as it would under silicate or phosphate limitations. It has also been proposed that this
greater production of toxin could be encouraged by carbon limitation with increasing pH
(Lundholm et al. 2004, Trimborn et al. 2007). Kudela et al. (2002) suggests that
environmental stressors, such as silica limitation or even the amount of light, may cause
an increase in toxin production by Pseudo-nitzschia. Though results of studying both
dinoflagellates and diatom species differ, a common theme is that change in the pCO2
and nutrient limitations can cause an increase in toxin production.
Climate Change Impacts on Harmful Algal Blooms
El Nino/Southern Oscillation and the Pacific Decadal Oscillation (ENSO and
PDO) both have warm and cool periods. These periods for ENSO last for six to eighteen
months and for PDO, about twenty to thirty years (Mantua & Hare 2002). During these
warm periods, the sea surface temperature increases therefore reducing upwelling and
increasing stratification (Rasmusson & Carpenter 1982). Since phytoplankton growth is
determined by nutrients, vertical mixing, temperature, and sunlight, the reduced
54
upwelling and increased stratification can influence the phytoplankton community
composition (Hallegraeff 2010).
Since warmer waters will increase stratification, this alters the suitable growing
conditions for certain phytoplankton genera. Diatoms need a well-mixed water column
in order to take advantage of the nutrients and sunlight. When the water column becomes
stratified, the nutrients and sunlight are no longer conveniently located. Therefore,
diatoms are unable to reach both resources. Dinoflagellates, on the other hand, have two
flagella which enable them to migrate through the water column taking advantage of the
nutrients near the pycnocline at night and then using those nutrients for photosynthesis
during the day (Anderson 1995). Therefore, dinoflagellates are expected to be favored
over other phytoplankton under future climate conditions that increase stratification by
warming the temperature (Moore et al. 2008).
Dinoflagellates comprise the majority of harmful algal blooms species with many
of them residing in tropical waters. Gambierdiscus toxicus is an example of a tropical
armored dinoflagellate that is associated with ciguatera fish poisoning and is found as an
epiphyte on macroalgae. The macroalgae is then eaten by herbivorous/ominivorous fish,
which we in turn, consume (Friedman et al. 2008). Ciguatera fish poisoning causes
neurological symptoms such as tingling in extremities and heat reversal. Symptoms can
last anywhere from days to weeks, but can last for years. Ciguatera has no cure, but the
symptoms can be treated (Hokama 1998). Since the toxins within the fish are lipophilic,
they bioaccumulate within the fish. This fish can no longer be sold in the market place,
therefore causing an economic loss to the fisherman. Tropical unarmored dinoflagellates,
such as Karenia brevis, can also create a negative influence on the economy and human
55
health. Since K.brevis does not have any armored plates, unlike Gambierdiscus, this
enables the cells to lyse in wave action, therefore releasing an aerosolized toxin known as
brevetoxin. This aerosolized brevetoxin can cause respiratory illnesses, especially those
who have asthma (Fleming et al. 2005). Illnesses are not the only drawback to K. brevis
blooms. Beach closures due to these brevetoxins also affect the local tourism industry.
Businesses located on the beach, such as hotels and restaurants, and recreational beach
go-ers are unable to take advantage of their prime location (Larkin&Adams 2007).
Therefore, as temperatures begin to rise, these tropical HAB species’ habitat will
continue to increase into higher latitudes and cause even more problems in local
communities (Hallegraeff 2010).
Temperate dinoflagellates such as Alexandrium are also a cause for concern.
Alexandrium is responsible for paralytic shellfish poisoning. Water temperatures greater
than 13°C have been found to promote Alexandrium catenella blooms, thus increasing
the possibility for PSP events. In Puget Sound, water temperatures reach their highest
during late summer and early fall, therefore providing perfect temperature and habitat
(stratified waters) for A. catenella, which are actually seen during those seasons (Figure
10). Historically, on average, there’s about a 68 day window for prime Alexandrium
growth at Sequim Bay. As ocean temperatures begin to rise, this will increase the
amount of favorable days for A. catenella to bloom. It is important to note though, that
even though these projections show an increase in A.catenella’s population, this does not
take into considering any other biological or physical factors acting simultaneously in the
future (Moore et al. 2008).
56
Figure 7. Taken from Moore et al. (2008). Showing This figure shows the potential climate
change impacts on Puget Sound shellfish toxicity. Moore et al. (2008) state that ―Climatological
monthly means of reconstructed sea surface temperature (SST) in Sequim Bay, Puget Sound,
using detrended SST records at Race Rocks, British Columbia from 1921 to 2007. The 13°C
threshold for accelerated growth of Alexandrium catenella is shown, and the mean annual
window of favorable SST conditions is shaded for present day conditions. Scenarios for warmer
SSST conditions by 2, 4, and 6C are shown in gray with the associated widening of the window
of increased opportunity for A.catenella growth.‖
Impacts of Phytoplankton on the Global Carbon Cycle
As the sea surface temperatures rise and the pH lowers, not only does the
phytoplankton community composition likely change to favor dinoflagellates and an
increase in toxin production, but conditions can also favor other organisms such as bluegreen algae (Schippers et al. 2004). When conditions become favorable, there can be
large blooms. These blooms may last several days to several weeks, but when all of the
nutrients are consumed, these organisms are either eaten by larger organisms (such as
phytoplankton, clams, or small fish), where they may ultimately be respired to carbon
57
dioxide, or they may sink to the bottom of the ocean repackaged as fecal pellets. They
may be degraded along the way, but a fraction of the carbon may eventually reach the
ocean floor. The death of these phytoplankton and blue-green algae may contribute a
significant amount to the carbon buried in the ocean sediment. A study by Menden-Deuer
and Lessard (2000) suggest that dinoflagellates are significantly denser in carbon than
diatoms. Therefore, as we consider the future of the possible phytoplankton communities,
there may be greater oceanic carbon sequestration by dinoflagellates through larger
blooms and their structural ability to hold greater amounts of carbon.
On the other hand, it is possible that warmer waters, could mean a diminishing
winter convection. This loss of convection, translates into weaker upwelling and less
nutrients reaching the surface of the ocean. Since phytoplankton, especially diatoms, rely
upon the nutrients being swept up from the depths and brought to the surface this can
severely reduce the amount of primary production leading to a weaker biological pump
(Woods & Barkmann 1993; Anderson et al. 2012). This positive feedback loop may
reduce the amount of carbon sequestration by phytoplankton.
Anthropogenic Inputs
In order to predict how future harmful algal blooms will change in the future we
must understand human behavior. Run-off, pollution, and even the distribution of plastic
debris in the ocean can promote harmful algal growth. A study by Maso et al. (2003)
showed that Alexandrium and other dinoflagellates were found to bind to plastics floating
in the ocean. The cysts (resting spores) of Alexandrium were found in clumps on plastic
58
debris and other dinoflagellates embedded themselves on macroalgal growth found on
plastic debris. These pieces of debris can then travel into new waters and establish new
harmful algal bloom colonies. For a long time, ballast water has been the main
contributor for transportation of harmful algal bloom species to a new location. Now, we
must consider other anthropogenic inputs such as plastic pollution.
Due to the amount of variability in biotic and abiotic factors in understanding the
current and future phytoplankton ecological processes, not one specific study or model
holds all the answers. It is imperative to continue to model and collect evidence as to
how phytoplankton behave in various conditions. It is also important to be able to have
baseline phytoplankton community composition data and harmful algal bloom
monitoring programs in place. Knowing what the current phytoplankton community
structure is composed of and tracking changes throughout the year might provide insight
to the direction of how the phytoplankton communities change. Harmful algal bloom
monitoring programs, such as Washington’s SoundToxins, enable communities to be
aware of what harmful algal blooms are currently present though weekly phytoplankton
observation. These monitoring programs provide a better understanding of how
phytoplankton communities change through time. Harmful algal blooms are a multifaceted problem that will definitely need interdisciplinary tools to predict their future
behavior.
59
Summary
Though many studies have shown a variety of results in regards to phytoplankton
community composition in greater acidified waters and under certain climate change
conditions, it is uncertain to how quickly these changes will occur. In order to address
how global change (i.e. ocean acidification and climate change) will affect harmful algal
blooms, it was difficult to focus only on factors of ocean acidification. Climate change is
another problem that will also affect phytoplankton in the future, therefore, it is important
to address both issues in this complex environmental puzzle. Currently, studies have
suggested the following answers: (1) with greater stratified waters due to warming of the
sea surface and possibly less upwelling that these conditions will favor dinoflagellates,
(2) with sea water pH becoming more acidic, calcifying organisms such as
coccolithophorids will have to combat their shells slowly dissolving, (3) greater amounts
of CO2 and acidic waters can increase the amount of toxin production from harmful algal
genera, (4) a change in the amount and types of nutrients available in the future will favor
certain phytoplankton genera, (5) warmer waters will enable tropical harmful algal bloom
dinoflagellates to increase from their current habitat range, and (5) an increase in
temperature will increase the amount of favorable days for A.catenella to bloom. These
results are only taking into consideration of the abiotic factors affecting phytoplankton,
but there are biotic factors that can influence phytoplankton populations and community
structure.
60
Washington Tribes
―Shellfish figure prominently in the Northwest Native American myths and
legends. In one creation story, humankind is said to have colonized the planet after
escaping from a tightly sealed clam’s shell. In another, more light-hearted tale, shellfish
are banished to a life in beach sand, after being sentenced by other animals for malicious
gossiping. This, the story explains, is why beach walkers frequently see small spurts of
water shooting up from the sand. The clams are trying to clear the silt and seawater
they’ve swallowed while attempting to tell their spiteful tales.‖ – Heaven on the Half
Shell: The Story of the Northwest’s Love Affair with the Oyster
For centuries, Washington tribes have depended on the bivalves residing along the
coastline for subsistence, trade, woodcarvings, and for ceremonial apparel and rites.
Many of the mussels, clams, abalone, and oyster shells brought in substantial revenue to
the various coastal tribes from trade and shellfish harvest. Unfortunately, harmful algal
blooms have affected much of their shellfish harvest. Since many of the harmful algal
blooms tend to be seasonal, tribal elders were believed to know when it was safe to
harvest. This information was then passed down generation to generation. Though the
seasonal bloom information was consistently and accurately passed down, the frequency
of when blooms occurred did not. With populations growing and expanding over
decades, anthropogenic inputs into the local waterways have increased the amount and
frequency of blooms (Bauer et al. 2009). Decadal patterns of shellfish toxicity have
indicated that the frequency, magnitude, and geographical scope of saxitoxin, exuded by
Alexandrium catenella in Puget Sound, has been increasing since the 1950s (Moore et al.
2009).
Fortunately, programs such as the Olympic Region Harmful Algal Blooms
(ORHAB) partnership, collaborate with Indian Tribes, state resource managers, coastal
communities, researchers, and shellfish-dependent groups, to help provide harmful algal
bloom monitoring coordination and dissemination of information (Chadsey et al. 2011).
61
The Quileute tribe has a heavy dependence on clams. They not only have a phrase for
―clam hungry‖, ta’a Wshi xa’ iits ‘os, but 20% of their total annual harvest goes to
subsistence while the other 80% is a source of earnings from clam sales for tribal
members (Bauer et al. 2009). The Quileute Indian Tribe has explored methods for rapid
detection of certain biotoxins, such as domoic acid and saxitoxin, using stick-like instant
read indicators. These stick assays, taking about one hour to produce a result, have
provided adequate forewarning of possible shellfish biotoxin contamination. These stick
indicators are of extra importance for tribes such as the Quileute, Quinalt, and the Makah
due to the remoteness of their locations (Northwest Fisheries Science Center &
Washington Sea Grant 2002). Though the stick indicator is a step in the right direction, it
is not always 100% accurate. Other monitoring techniques, though they take more time,
provide greater accuracy. Understanding when the toxic phytoplankton are present and if
the toxins exuded are above the toxin threshold is of vital importance. If harmful algal
blooms can be detected earlier enough or their mechanisms under which they bloom can
be better understood, it may allow a more economically robust industry and less negative
impacts to the regional Native American tribes.
In 1998, the Quinault Indian Nation suffered great economic loss from the ASP
closures. This long episode of domoic acid presence within the clams created a prolonged
hiatus in harvesting. This hiatus created a disinterest within the commercial markets
therefore leaving the Quinault for other clam distributors temporarily (Northwest
Fisheries Science Center and Washington Sea Grant 2002).
The tribal clam industry was not the only industry hit by the increase of harmful
algal blooms. In that same year, the Quileute Indian Nation’s Dungeness crab fishery had
62
similar setbacks. The domoic acid levels from Pseudo-nitzschia blooms were above the
regulatory limit within the viscera of the crab. Because this domoic acid was
concentrated within the viscera, the crab processors removed the gut to save what was
left of the crab harvest. Because much of the weight was removed from the crab, the per
pound value return of the crab was half the amount they expected to receive (Northwest
Fisheries Science Center and Washington Sea Grant 2002). Domoic acid is not the only
toxin creating problems for the shellfish industry.
Commercial geoduck fisheries ran by Jamestown S’Klallam, Puyallup, and
Suquamish tribes have been greatly impacted by PSP closures. A recall of the tainted
geoducks caused a loss of $30,0000. Butter clams, littleneck clams, horse clams and
manila clams used for ceremonial events and as a part of the Jamestown S’Klallam tribe’s
traditional diet. Clams are also an integral part of the Puyallup tribe’s culture, being used
in weddings, funerals, and ceremonial dinners (Lewitus et al. 2012). With PSP limiting
the amount of bivalves being consumed, saxitoxin monitoring is now common practice
for Washington Department of Health. In order to be able to monitor these various HAB
species, it is important to understand what conditions are optimal for phytoplankton
growth and to see if seasonality may play a role in this ever changing marine
environment. Citizen science programs, such as SoundToxins, can provide an
inexpensive monitoring network to look for seasonal changes in phytoplankton growth
and report back to Washington’s Department of Health.
63
Citizen Science
Citizen science, research conducted by amateur or non-professional scientists,
allows organizations to broaden their sample sizes and create community awareness of a
particular environmental issue or study. Harmful algal blooms are an environmental
issue that affects the coast of Washington and Puget Sound. These blooms blanket the
coastline seasonally and pose as a threat to the shellfish industry and human health.
Awareness of various scientific topics, such as harmful algal blooms, can create greater
ecosystem stewardship through community involvement in research (Conrad&Hilchey
2011). Using citizen scientists could allow community members insight into how
harmful algal blooms affect the local community as well as how to mitigate their
occurrence. The benefits and challenges of integrating volunteers must be assessed in
order to see if the data collected is legitimate. Proper training on data collection and
subject matter is imperative for a successful citizen science program.
Citizen science volunteer programs have grown in number in recent years; they
incorporate one or more of the following: government agencies, industry, academia,
community groups, and local institutions to collaborate by monitoring, tracking, and
responding to local environmental issues (Whitelaw et al. 2003). Creating citizen
awareness of environmental issues often pressures policy makers to support
environmental measures and develops more informed citizens when voting for
environmental initiatives. It also increases environmental democracy, scientific literacy,
social capital, citizen inclusion in local issues, benefits to government, and benefits to
ecosystems being monitored (Conrad&Hilchey 2011) For example, on Martha’s Vinyard
in Massachusetts, a neighborhood pond association formed a citizen science organization
64
out of concern for declining water quality. Nonprofit organizations, local environmental
managers, and the pond association worked on a number of pollution initiatives to
improve the water quality. Newsletters and annual reports now feature ―Pond
Reminders‖ which help the community remember how to provide proper boat
maintenance and general green gardening techniques to minimize polluted run-off
(Karney 2000, Conrad&Hilchey 2011). With the knowledge gained through observation,
sampling, and data collecting, these citizens can take this experience and apply it to other
environmental issues they observe or are able to understand an ecosystem better due to
the organisms in which they studied and surveyed.
SoundToxins implements harmful algal bloom monitoring within the Puget Sound
that includes professional scientists, from organizations such as NOAA, Washington
Department of Health, and Washington Sea Grant, as well as individuals from informal
education facilities, formal educational facilities, local Native American tribes, the
aquaculture industry, and concerned citizens. Their annual two-day training consists of an
introduction to phytoplankton the methods used by SoundToxins to monitor
phytoplankton, including microscope training and phytoplankton ID training. The second
day is used to report back to the volunteers on how the SoundToxins data is used. Due to
the rigorous standards set by the SoundToxins sampling protocol, the constant feedback
volunteers receive from sending in their data, and professional support for volunteer
concerns, the data coming from SoundToxins is able to be used to aid in early warning of
harmful algal blooms. Understanding how and when these phytoplankton blooms occur
using SoundToxins data can help decrease the amount of toxic shellfish related illnesses
and possibly even the frequency of which these blooms occur.
65
Conclusion
This thesis tries to understand if there is a way to forecast the presence of
Dinophysis and where certain species tend to reside. Though no particular genus was
identified a constant precursor to the presence of Dinophysis it is important to note that
Dinophysis generally conforms to the traditional diatom-dinoflagellate seasonal patterns.
The year round presence of Dinophysis and the fact that this species can exude its
biotoxins within a small population presents a unique challenge in understanding its
behavior.
In order to gain a better understanding where certain species of Dinophysis
resides and if there are any phytoplankton genera that can provide us with a forewarning
of Dinophysis, this study would have to look at a larger time scale of at least five years
and at several other locations, preferably another station in the middle of Puget Sound
and several in south Puget Sound. Setting a wider cast of sampling stations will allow us
to gain a finer resolution of the phytoplankton community present throughout all seasons.
Also, incorporating nutrient, chlorophyll, and weather data into the study will provide
greater strength and open up other possible explanations for the patterns exhibited by
phytoplankton.
Overall, a holistic approach needs to be taken to further understand harmful algal
bloom ecology, how anthropogenic sources and climate change affect harmful algal
blooms, harmful algal bloom toxin mechanisms, understand what can evoke a sense of
responsibility and change of behaviors to ensure less pollution and nutrients enter the
ocean. This thesis is only a small piece to this very complex puzzle. Hopefully through
66
the continuation of citizen science programs, such as SoundToxins, communities can find
ways to gain a better understanding of this ever evolving phenomenon.
67
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APPENDICES
APPENDIX 1. SEQUIM BAY PHYTOPLANKTON COMPOSITION
Date
6/5/2012
Date
6/12/2012
Genus
Chaetoceros
Cyindrotheca
Detonula
Dinophysis
Ditylum
Eucampia
Leptocylindrus
Noctiluca
Odontella
Proboscia
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Akashiwo sanguinea
Chaetoceros
Cylindrotheca
Dinophysis
Ditylum
Eucampia
Kofoidinium
Leptocylindrus
Minescula
Navicula
Noctiluca
Odontella
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Average (Cells/L)
48563.3
293.9
9110.2
257.1
257.1
330.6
5804.1
220.4
293.9
36.7
514.3
SE
6036.6
73.5
902.8
132.4
97.2
168.3
1182.4
73.5
194.4
36.7
146.9
14914.3
320.2
4298.0
12269.4
73.5
1836.7
1028.6
2130.6
Average (Cells/L)
18.1
979.6
1741.5
707.5
108.8
18.1
18.1
2258.5
18.1
36.3
54.4
254.0
108.8
453.5
63.6
847.3
73.5
573.8
194.4
446.9
SE
18.1
83.1
268.5
158.1
31.4
18.1
18.1
583.0
18.1
18.1
31.4
18.1
0.0
48.0
23673.5
349.9
76
Date
6/19/2012
Date
6/26/2012
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Alexandrium
Chaetoceros
Dinophysis
Leptocylindrus
Noctiluca
Odontella
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Scripsiella
Rhizosolenia
Thalassionema
Genus
Actinoptychus
Ceratium
Chaetoceros
Cylindrotheca
Dinophysis
Kofoidinium
Leptocylindrus
Licmorpha
Minescula
Odontella
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
Thalassionema
9378.7
9759.6
72.6
72.6
90.7
199.5
Average (Cells/L)
32.3
32.3
937.1
1744.9
48.5
64.6
32.3
420.1
1702.0
414.9
18.1
36.3
18.1
18.1
SE
32.3
32.3
85.5
335.8
32.3
32.3
32.3
116.5
83238.1
5490.9
3134.4
387.8
14637.8
96.9
Average (Cells/L)
148.0
44.4
66.6
44.4
961.7
29.6
177.6
14.8
14.8
88.8
710.2
520.0
223.9
824.5
96.9
SE
78.3
0.0
14.8
25.6
53.3
14.8
51.3
14.8
14.8
0.0
51.3
72381.6
313.2
1035.7
24265.3
207.1
44.4
411.1
363.6
29.6
25.6
77
Date
7/3/2012
Date
7/10/2012
Date
7/17/2012
Thalassiosira
Genus
Cylindrotheca
Dinophysis
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg Cell
type
Scripsiella
Rhizosolenia
Thalassionema
Genus
Akashiwo sanguinea
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Heterocapsa
Leptocylindrus
Noctiluca
Odontella
Polykrikos
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Scripsiella
Thalassionema
Thalassiosira
Genus
Actinoptychus
Asterionellopsis
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Dinophysis
Ditylum
Eucampia
Gonyaulax
14.8
Average (Cells/L)
350.3
420.4
175.2
490.5
14.8
SE
70.1
60.7
35.0
70.1
70873.8
455.4
68316.3
105.1
Average (Cells/L)
61.2
81.6
20.4
61.2
40.8
449.0
40.8
653.1
40.8
40.8
102.0
530.6
4245.2
126.3
7355.1
60.7
SE
35.3
40.8
20.4
35.3
40.8
20.4
20.4
81.6
40.8
20.4
54.0
108.0
201346.9
86244.9
122.4
81.6
571.4
Average (Cells/L)
144.2
108.2
10203.4
360.5
180.3
72.1
252.4
288.4
937.4
36.1
3396.6
825.5
70.7
81.6
40.8
SE
72.1
62.4
593.5
144.2
72.1
36.1
44.2
95.4
157.2
36.1
78
Date
7/24/2012
Date
7/31/2012
Heterocapsa
Leptocylindrus
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Skeletonema
Tropedoneis
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Alexandrium
Asteromphalus
Chaetoceros
Cylindrotheca
Detonula
Dinophysis
Dissodinium
Ditylum
Heterocapsa
Leptocylindrus
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Scripsiella
Stephanopyxis
Thalassionema
Thalassiosira
Tropedoneis
Genus
Actinoptychus
Alexandrium
Chaetoceros
Cylindrotheca
Dinophysis
Ditylum
Gonyaulax
108.2
1045.6
468.7
62.4
157.2
95.4
4651.0
172592.5
504.8
108.2
72.1
108.2
685.0
Average (Cells/L)
115.6
115.6
693.9
185.0
46.3
208.2
23.1
92.5
23.1
346.9
46.3
1665.3
115.6
390.0
1724.2
236.4
62.4
36.1
0.0
200.7
SE
61.2
61.2
40.1
61.2
23.1
40.1
23.1
23.1
23.1
0.0
23.1
80.1
46.3
23.1
108453.1
92.5
69.4
23.1
809.5
23.1
Average (Cells/L)
360.5
252.4
2271.4
216.3
216.3
288.4
216.3
23.1
884.1
61.2
40.1
23.1
61.2
23.1
SE
190.8
36.1
62.4
62.4
0.0
95.4
62.4
79
Date
8/7/2012
Date
8/21/2012
Guinardia
Heterocapsa
Leptocylindrus
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Actinoptychus
Asterionellopsis
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dactyliosen
Detonula
Dinophysis
Ditylum
Heterocapsa
Leptocylindrus
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzchia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Alexandrium
432.7
396.6
649.0
288.4
5119.7
396.6
62.4
36.1
124.9
36.1
406.3
36.1
72.1
180921.1
216.3
144.2
180.3
432.7
2235.4
Average (Cells/L)
1138.8
63.3
21.1
8456.5
780.3
738.1
21.1
147.6
485.0
147.6
42.2
2530.6
168.7
7718.4
400.7
36.1
11060.4
62.4
36.1
95.4
165.2
72.1
SE
193.3
63.3
21.1
750.6
55.8
117.4
17.2
21.1
55.8
21.1
42.2
73.1
42.2
562.3
76.0
126.5
36.5
379.6
49199.3
400.7
210.9
316.3
2087.8
Average (Cells/L)
51.9
239.5
1921.1
76.0
55.8
63.3
131.7
SE
8.5
80
Date
8/28/2012
Date
Asteromphalus
Bacteriastrum
Cerataulina
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dactyliosen
Dinophysis
Ditylum
Kofoidinium
Leptocylindrus
Noctiluca
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Skeletonema
Thalassiosira
Tropidoneis
Genus
Alexandrium
Asteromphalus
Ceratium
Chaetoceros
Cylindrotheca
Dinophysis
Gonyaulax
Leptocylindrus
Noctiluca
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-ntizschia Lg. Cell
type
Scripsiella
Skeletonema
Thalassiosira
Genus
103.7
31.1
10.4
321.6
228.2
31.1
20.7
145.2
145.2
10.4
10.4
93.4
10.4
10.4
1089.3
155.6
10.4
0.0
10.4
51.9
57.8
18.0
10.4
74.8
10.4
10.4
10.4
18.0
10.4
10.4
95.1
53.9
83.0
10.4
166.0
197.1
10.4
Average (Cells/L)
339.3
248.8
791.7
22.6
67.9
565.5
45.2
22.6
22.6
226.2
248.8
181.0
10.4
10.4
10.4
20.7
10.4
SE
103.7
59.8
254.9
22.6
0.0
59.8
22.6
22.6
27.7
22.6
59.8
22.6
22.6
22.6
22.6
90.5
Average (Cells/L)
22.6
22.6
22.6
90.5
SE
81
9/4/2012
Date
9/11/2012
Alexandrium
Amylax
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Leptocylindrus
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Scripsiella
Genus
Akashiwo sanguinea
Alexandrium
Asterionellopsis
Asteromphalus
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Dinophysis
Ditylum
Eucampia
Kofoidinium
Leptocylindrus
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Skeletonema
Thalassiosira
3748
26
698
52
52
52
310
78
52
78
155
52
230
26
157
26
52
26
78
45
26
45
45
26
26
103
Average (Cells/L)
429
3686
86
29
1857
2714
86
314
57
743
257
86
29
229
57
143
29
457
26
26
SE
70
429
49
29
273
206
49
76
29
114
49
49
29
57
57
143
29
29
171
49
29
114
229
1257
29
29
29
234
82
Date
9/18/2012
Date
10/2/2012
Genus
Akashiwo sanguinea
Alexandrium
Asteromphalus
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Dinophysis
Ditylum
Eucampia
Lauderia
Leptocylindrus
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Akashiwo sanguinea
Alexandrium
Asteromphalus
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Leptocylindrus
Noctiluca
Oxyphysis
Pleurosigma
Protoperidinium
Pseudo-nitzcshia Lg. Cell
type
Average (Cells/L)
96
39
19
328
675
347
19
19
135
598
77
58
19
116
116
SE
19
19
19
126
84
0
19
19
19
168
19
33
19
33
33
29
24
19
96
19
19
39
906
Average (Cells/L)
413
29
22
973
15
133
1739
501
59
44
29
15
324
24
96
19
19
19
184
SE
53
29
15
68
15
44
103
78
59
26
15
15
15
29
29
83
Date
10/9/2012
Date
10/31/2012
Date
11/6/2012
Stephanopyxis
Scripsiella
Thalassionema
Genus
Akashiwo sanguinea
Alexandrium
Ceratium
Cylindrotheca
Dinophysis
Licmorpha
Oxyphysis
Protoceratium
Protoperidinium
Scripsiella
Genus
Amylax
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Eucampia
Heterocapsa
Leptocylindrus
Minuscula
Protoperidinium
Pseudo-nitzschia Lg Cell
type
Scripsiella
Thalassiosira
Genus
Cerataulina
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Dinophysis
Lauderia
Leptocylindrus
Pleurosigma
15
206
15
Average (Cells/L)
22
88
862
133
1393
22
22
44
243
155
Average (Cells/L)
16
1629
403
16
127
32
16
16
47
16
47
15
64
15
SE
22
88
108
38
138
22
22
44
22
58
SE
16
202
57
16
32
32
16
16
27
16
27
79
348
158
Average (Cells/L)
12
179
71
12
36
12
24
24
12
12
57
84
42
SE
12
36
21
12
24
12
24
24
12
12
84
Date
11/19/2012
Date
12/3/2012
Date
12/18/2012
Protoperidinium
Scripsiella
Skeletonema
Thalassiosira
Genus
Ceratium
Cerataulina
Chaetoceros
Cylindrotheca
Detonula
Dinophysis
Ditylum
Leptocylindrus
Navicula
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Alexandrium
Ceratium
Chaetoceros
Coscinodsicus
Cylindrotheca
Leptocylindrus
Paralia
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Chaetoceros
Cylindrotheca
Gonyaulax
18
24
24
24
Average (Cells/L)
129
9
156
18
9
9
28
46
46
18
18
12
24
29
12
SE
60
9
34
9
9
9
22
24
9
9
9
9
28
55
37
9
Average (Cells/L)
235
39
180
23
47
8
8
39
9
28
16
24
9
SE
59
8
34
0
14
8
8
21
16
8
23
39
47
Average (Cells/L)
76
69
38
16
10
14
8
14
SE
30
13
20
85
Date
1/2/2013
Date
1/15/2013
Date
1/31/2013
Date
2/13/2013
Leptocylindrus
Navicula
Paralia
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Scripsiella
Thalassionema
Genus
Akashiwo sanguinea
Chaetoceros
Cylindrotheca
Paralia
Protoperidinium
Pseudo-nitzshcia Lg. Cell
type
Thalassionema
Thalassiosira
Genus
Chaetoceros
Cylindrotheca
Paralia
Skeletonema
Thalassionema
Thalassiosira
Genus
Chaetoceros
Coscinodiscus
Cylindrotheca
Leptocylindrus
Navicula
Paralia
Protoperidinium
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Alexandrium
Asterionellopsis
23
15
30
8
8
0
8
8
8
8
38
8
61
Average (Cells/L)
14
9
18
28
9
8
8
15
SE
9
9
18
16
9
18
9
18
Average (Cells/L)
13
102
63
63
76
25
Average (Cells/L)
34
11
79
57
11
45
11
23
45
45
11
Average (Cells/L)
14
204
9
9
9
SE
13
34
25
25
44
13
SE
0
14
41
23
11
11
11
23
11
11
11
SE
14
62
86
Date
2/27/2013
Date
3/13/2013
Date
3/18/2013
Chaetoceros
Corethron
Coscinodiscus
Cylindrotheca
Eucampia
Leptocylindrus
Paralia
Skeletonema
Thalassionema
Thalassiosira
Genus
Asterionellopsis
Chaetoceros
Cylindrotheca
Paralia
Pseudo-nitzschia Sm. Cell
type
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Asterionellopsis
Chaetoceros
Corethron
Cylindrotheca
Ditylum
Eucampia
Leptocylindrus
Odontella
Paralia
Pleurosigma
Pseudo-nitzschia Sm. Cell
type
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Asterionellopsis
Bascillaria
Chaetoceros
177
14
14
27
14
136
27
82
27
109
Average (Cells/L)
522
784
174
73
36
14
14
27
14
59
27
0
14
27
SE
115
242
0
29
29
58
44
102
319
Average (Cells/L)
576
16359
37
208
37
12
61
24
12
24
15
38
25
38
52
SE
121
695
21
68
21
12
24
15
12
12
98
49
416
6208
Average (Cells/L)
1541
15
25667
12
12
53
127
SE
83
15
342
87
Date
3/25/2013
Date
4/9/2013
Coscinodiscus
Cylindrotheca
Leptocylindrus
Navicula
Paralia
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Asterionellopsis
Chaetoceros
Cylindrotheca
Ditylum
Leptocylindrus
Licmorpha
Paralia
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Scripsiella
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Asterionellopsis
Cerataulina
Chaetoceros
Cylindrotheca
Detonula
Leptocylindrus
Licmorpha
Odontella
Navicula
45
688
75
45
15
30
26
60
15
26
15
15
15
15
195
15
30
150
703
13050
Average (Cells/L)
471
25357
471
46
15
15
61
61
40
15
15
15
40
184
SE
66
785
15
0
15
15
40
15
15
19
106
91
61
760
6214
Average (Cells/L)
71
24
47286
595
48
107
24
24
71
40
26
40
106
132
SE
0
24
1256
63
48
24
24
19
71
88
Paralia
Pleurosigma
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Scripsiella
Thalassionema
Thalassiosira
48
405
24
48
214
41
143
71
167
952
41
41
48
104
89
APPENDIX 2. QUARTERMASTER HARBOR PHYTOPLANKTON
COMPOSITION
Date
4/9/2012
Date
5/28/2012
Date
6/12/2012
Genus
Actinoptychus
Chaetoceros
Cylindrotheca
Detonula
Eucampia
Leptocylindrus
Odontella
Pleurosigma
Pseudo-nitzschia Lg. cell
type
Pseudo-nitzschia Sm. Cell
type
Skeletonema
Thalassionema
Thalassiosira
Tropodeneis
Genus
Actinoptychus
Chaetoceros
Cylindrotheca
Ditylum
Leptocyclindrus
Licmorpha
Noctiluca
Odontella
Pleurosigma
Protoceratium
Protoperidinium
Pseudo-nitzschia Lg. cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Actinoptychus
Average (Cells/L)
30
554
40
29413
60
20
239
40
SE
17
54
10
268
17
10
35
10
459
53
70
90
190
1098
10
Average (Cells/L)
13
8546
70
13
19
16
25
10
3
3
44
26
17
26
70
10
SE
13
350
6
3
5
3
3
5
3
3
8
67
22
25
10
6
10
Average (Cells/L)
7
5
22
11
5
3
0
SE
7
90
Date
6/18/2012
Date
6/23/2012
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Leptocylindrus
Noctiluca
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassiosira
Genus
Akashiwo sanguinea
Astrionellopsis
Ceratium
Chaetoceros
Coscinodiscus
Ditylum
Eucampia
Oxyphysis
Polykrikos
Pleurosigma
Prorocentrum
Protoperidinium
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Actinoptychus
Alexandrium
Amylax
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
2
128
15
82
7
7
5
34
2
11
4
6
4
0
2
2
5
15
7
5
44
Average (Cells/L)
8
4
333
36
20
4
8
8
4
4
325
91
56
24
4
4
36
Average (Cells/L)
96
45
3
5
66
90
578
40
2
0
7
2
7
SE
4
4
54
0
14
4
4
4
4
4
60
28
21
12
4
4
12
SE
12
10
3
3
3
15
74
5
91
Date
6/29/2012
Date
7/15/2012
Heterocapsa
Kofoidinium
Noctiluca
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. cell
type
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassiosira
Tropidoneis
Genus
Alexandrium
Amylax
Asteromphalus
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Ditylum
Kofoidinium
Licmorpha
Noctiluca
Oxyphysis
Pleurosigma
Polykrikos
Prorocentrum
Protoperidinium
Rhizosolenia
Scripsiella
Skeletonema
Thalassiosira
Tropedoneis
Genus
Alexandrium
Ceratium
Coscinodiscus
Dinophysis
5
3
13
19
34
5
3
3
7
3
32
122
133
3
3
157
3
Average (Cells/L)
780
20
3
8
17
112
20
173
6
3
8
14
6
14
3
59
67
6
235
3
22
3
Average (Cells/L)
138
178
6
184
9
11
10
3
3
12
3
SE
27
7
3
0
8
7
7
20
6
3
5
7
3
6
3
13
5
6
30
3
15
3
SE
11
27
3
11
92
Date
8/6/2012
Date
8/13/2012
Gonyaulax
Noctiluca
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Thalassiosira
Genus
Akashiwo sanguinea
Asterionellopsis
Ceratium
Chaetoceros
Cosdinodiscus
Cylindrotheca
Dinophysis
Ditylum
Eucampia
Oxyphysis
Pleurosigma
Polykrikos
Prorocentrum
Protoperidinium
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Akashiwo sanguinea
Alexandrium
Ceratium
Chaetoceros
Cosdinodiscus
Cylindrotheca
Dinophysis
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Sm. Cell
type
21
89
28
95
364
3
13
5
11
22
77
31
Average (Cells/L)
9
5
381
41
23
14
5
5
9
9
5
5
390
109
63
50
5
5
41
Average (Cells/L)
10
63
324
48
13
32
44
51
124
187
6
8
SE
5
5
61
0
16
8
5
5
5
5
5
5
67
28
24
32
5
5
14
SE
10
36
31
10
8
13
6
18
5
49
3
3
93
Date
8/20/2012
Date
8/28/2012
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Alexandrium
Asteromphalus
Ceratium
Chaetoceros
Cosdinodiscus
Dinophysis
Leptocylindrus
Lingulodinium
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassiosira
Genus
Akashiwo sanguinea
Alexandrium
Amylax
Asteromphalus
Ceratium
Chaetoceros
Cylindrotheca
Dinophysis
Leptocylindrus
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
48
156
95
13
25
Average (Cells/L)
95
3
441
70
17
20
173
11
28
6
148
70
120
134
14
3
6
Average (Cells/L)
91
121
23
13
451
53
3
106
161
60
10
93
88
10
11
29
8
3
SE
15
3
15
16
8
7
20
3
16
6
16
16
12
13
6
3
3
SE
45
20
4
5
51
8
3
12
48
8
5
13
5
10
171
53
3
44
4
94
Date
9/3/2012
Date
9/10/2012
Skeletonema
Thalassionema
Thalassiosira
Genus
Akashiwo sanguinea
Alexandrium
Asteromphalus
Ceratium
Chaetoceros
Coscinodiscus
Dinophysis
Ditylum
Eucampia
Gonyaulax
Oxyphysis
Pleurosigma
Polykrikos
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Akashiwo sanguinea
Alexandrium
Asteromphalus
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Ditylum
Kofoidinium
Leptocylindrus
Oxyphysis
Pleurosigma
23
3
18
Average (Cells/L)
3
3001
96
232
83
17
25
13
3
3
60
25
7
96
129
13
3
9
SE
3
71
9
13
17
7
6
7
3
3
34
6
7
23
11
20
50
10
17
30
20
3
Average (Cells/L)
558
188
11
817
618
28
4
53
75
4
36
128
85
6
21
6
9
6
6
3
SE
15
20
11
28
27
4
4
6
11
4
7
9
12
95
Date
9/17/2012
Date
9/24/2012
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. cell
type
Pseudonitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Akashiwo sanguinea
Alexandrium
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Ditylum
Eucampia
Kofoidinium
Leptocylindrus
Licmorpha
Odontella
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Akashiwo sanguinea
Alexandrium
Asteromphalus
25
85
4
18
476
22
39
21
36
96
135
274
Average (Cells/L)
109
21
224
194
54
6
30
6
6
3
18
3
3
51
24
15
24
9
6
9
16
19
13
SE
26
6
13
13
5
6
6
3
6
3
0
3
3
18
3
11
6
160
26
9
15
9
21
6
54
Average (Cells/L)
563
11
7
5
6
0
11
3
18
SE
81
7
7
96
Date
10/1/2012
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Eucampia
Guinardia
Kofoidinium
Noctiluca
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Genus
Akashiwo sanguinea
Ceratium
Chaetoceros
Coscinodiscus
Dinophysis
Ditylum
Eucampia
Guinardia
Kofoidinium
Leptocylindrus
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
441
185
19
4
22
7
7
4
4
44
15
33
19
32
32
7
4
6
4
4
4
4
22
10
6
4
67
19
22
7
7
Average (Cells/L)
1325
385
179
4
26
4
4
4
9
22
4
22
13
13
19
13
11
7
7
SE
133
69
36
4
8
4
4
4
4
4
4
9
8
8
22
20
22
13
4
26
9
4
16
13
4
15
97
Date
10/8/2012
Date
10/15/2012
Genus
Akashiwo sanguinea
Asteromphalus
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Dinophysis
Ditylum
Eucampia
Kofoidinium
Leptocylindrus
Oxyphysis
Pleurosigma
Prorocentrum gracile
Prorocentrum reticulatum
Protoperidinium
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassiosira
Genus
Akashiwo sanguinea
Ceratium
Chaetoceros
Detonula
Dinophysis
Ditylum
Eucampia
Kofoidinium
Oxyphysis
Pleurosigma
Prorocentrum
Protoperidinium
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Average (Cells/L)
872
6
83
46
6
3
3
6
6
9
3
6
6
3
15
3
14
3
9
3
3
34
Average (Cells/L)
6946
60
72
4
8
4
8
4
11
4
45
11
8
53
6
57
4
SE
27
3
11
5
3
3
3
3
3
0
3
3
6
3
8
3
8
3
5
3
3
13
SE
638
4
15
4
4
4
8
4
7
4
17
11
8
15
4
17
4
98
Date
10/22/2012
Date
10/29/2012
Date
11/5/2012
Genus
Akashiwo sanguinea
Ceratium
Chaetoceros
Detonula
Dinophysis
Ditylum
Eucampia
Kofoidinium
Leptocylindrus
Oxyphysis
Prorocentrum
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Scripsiella
Skeletonema
Thalassiosira
Genus
Akashiwo sanguinea
Ceratium
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Kofoidinium
Lauderia
Leptocylindrus
Protoperidinium
Thalassiosira
Genus
Akashiwo sanguinea
Ceratium
Chaetoceros
Dinophysis
Gonyaulax
Kofoidinium
Leptocylindrus
Pleurosigma
Prorocentrum
Scripsiella
Average (Cells/L)
2119
25
28
8
3
5
3
5
3
3
3
5
SE
173
7
9
4
3
5
3
3
3
3
3
3
3
5
5
18
Average (Cells/L)
1283
14
19
6
3
3
3
3
8
6
33
Average (Cells/L)
2158
11
5
5
3
3
3
3
16
8
3
3
3
3
SE
68
3
11
3
3
3
3
3
5
3
8
SE
195
3
3
3
3
3
3
3
12
5
99
Date
11/18/2012
Date
11/26/2012
Date
12/3/2012
Date
12/10/2012
Date
12/17/2012
Thalassiosira
Silicoflagellate
Genus
Akashiwo sanguinea
Pleurosigma
Genus
Akashiwo sanguinea
Ceratium
Chaetoceros
Dinophysis
Pseudo-nitzschia Lg. Cell
type
Stephanopyxis
Thalassiosira
Genus
Akashiwo sanguinea
Chaetoceros
Coscinodiscus
Cylindrotheca
Leptocylindrus
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Skeletonema
Thalassiosira
Genus
Ceratium
Chaetoceros
Cylindrotheca
Silicoflagellate
Genus
Asteromphalus
Chaetoceros
Coscinodiscus
Dinophysis
Ditylum
Melosira
Paralia
Pleurosigma
Pseudo-nitzschia Lg. Cell
type
16
3
Average (Cells/L)
8
3
Average (Cells/L)
77
6
6
9
5
3
SE
0
16
SE
23
3
3
5
3
3
6
Average (Cells/L)
6
9
15
6
9
3
3
6
SE
3
9
3
3
5
6
18
3
9
Average (Cells/L)
3
18
9
3
Average (Cells/L)
6
34
12
3
3
6
6
3
6
10
3
5
SE
3
5
5
3
SE
3
11
3
3
3
3
3
3
3
3
100
Date
1/2/2013
Date
1/14/2013
Date
1/29/2013
Rhizosolenia
Scripsiella
Skeletonema
Thalassiosira
Silicoflagellate
Genus
Asteromphalus
Ceratium
Chaetoceros
Cylindrotheca
Leptocylindrus
Paralia
Pleurosigma
Pseudo-nitzschia Sm. Cell
type
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Ditylum
Leptocylindrus
Protoperidinium
Pseudo-nitzschia Lg. cell
type
Skeletonema
Thalassiosira
Genus
Asteromphalus
Chaetoceros
Coscinodiscus
Cylindrotheca
Detonula
Dinophysis
Leptocylindrus
Navicula
Paralia
6
6
6
18
6
Average (Cells/L)
3
3
99
12
3
12
3
6
3
6
5
3
SE
3
3
21
3
3
8
3
6
174
9
93
3
Average (Cells/L)
350
3
28
9
3
3
3
3
11
5
17
3
SE
43
3
5
5
3
3
3
15
93
456
Average (Cells/L)
3
161
3
26
10
6
10
3
3
6
19
28
SE
3
26
3
6
0
3
6
3
3
101
Date
2/12/2013
Date
2/20/2013
Date
3/12/2013
Pleurosigma
Protoperidinium
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Asteromphalus
Chaetoceros
Cylindrotheca
Detonula
Leptocylindrus
Paralia
Pleurosigma
Pseudo-nitzschia Sm. cell
type
Skeletonema
Thalassionema
Thalassiosira
Genus
Asteromphalus
Chaetoceros
Cylindrotheca
Detonula
Eucampia
Leptocylindrus
Paralia
Pleurosigma
Pseudo-nitzschia Lg. cell
type
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Asteromphalus
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Eucampia
3
3
26
29
74
3
Average (Cells/L)
3
190
194
3
7
7
7
3
3
3
3
8
3
SE
3
12
53
3
7
7
7
3
61
20
48
Average (Cells/L)
7
598
504
26
7
13
3
10
3
10
6
15
SE
7
96
90
9
7
9
3
6
7
42
13
55
3
Average (Cells/L)
6
184
42
1028
3
78
7
23
7
14
3
SE
6
10
28
50
3
19
102
Date
4/1/2013
Date
4/8/2013
Leptocylindrus
Odontella
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. cell
type
Pseudo-nitzschia Sm. cell
type
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
Tropedoneis
Genus
Chaetoceros
Coscinodiscus
Cylindrotheca
Ditylum
Eucampia
Leptocylindrus
Noctiluca
Odontella
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. cell
type
Pseudo-nitzschia Sm. cell
type
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Chaetoceros
Cylindrotheca
Ditylum
Eucampia
Lauderia
6
13
32
3
3
6
9
3
32
6
6
26
13
13
42
48
837
3
Average (Cells/L)
1874
3
174
21
284
9
3
75
6
6
3
12
13
13
12
15
157
3
SE
55
3
44
3
6
0
3
6
3
3
317
61
15
9
3
21
150
48
1344
Average (Cells/L)
2637
120
13
123
10
6
0
3
8
11
11
67
SE
107
17
3
28
0
103
Leptocylindrus
Lingulodinium
Noctiluca
Odontella
Pleurosigma
Prorocentrum
Protperidinium
Pseudo-nitzschia Lg. cell
type
Pseudo-nitzschia Sm. cell
type
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
93
3
3
50
17
3
13
12
3
3
6
3
3
3
47
9
7
27
53
502
103
13
279
3
9
18
103
24
3
15
104
APPENDIX 3. PENN COVE PHYTOPLANKTON COMPOSITION
Date
6/4/2012
Date
7/16/2012
Date
8/20/2012
Genus
Chaetoceros
Detonula
Leptocylindrus
Noctiluca
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Pseudo-nitzschia Sm. Cell
type
Rhizosolenia
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Chaetoceros
Cylindrotheca
Detonula
Ditylum
Leptocylindrus
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Skeletonema
Thalassiosira
Genus
Alexandrium
Astrerionellopsis
Ceratium
Chaetoceros
Detonula
Dinophysis
Ditylum
Eucampia
Leptocylindrus
Navicula
Noctiluca
Pleurosigma
Protoperidinium
Average (Cells/L)
251
236
82
257
15
SE
56
22
6
16
3
82
38
20
1131
76
3
262
6
Average (Cells/L)
5247
110
873
520
207
3
99
6
3
4
3
SE
116
12
29
53
18
224587
367
10820
780
Average (Cells/L)
53
53
24
5194
41
32
330
77
47
12
118
6
88
1883
7
164
35
SE
10
0
6
68
21
15
16
12
12
12
16
6
10
105
Date
9/3/2012
Date
9/17/2012
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Skeletonema
Thalassionema
Thalassiosira
Genus
Actinoptychus
Asterionellopsis
Chaetoceros
Coscinodiscus
Cylindrotheca
Dinophysis
Ditylum
Leptocylindrus
Noctiluca
Pleurosigma
Proboscia
Protoperidinium
Pseudo-nitzshcia Sm. Cell
type
Rhizosolenia
Skeletonema
Stephanopyxis
Thalassiosira
Genus
Actinoptychus
Asterionellopsis
Asteromphalus
Chaetoceros
Cyindrotheca
Detonula
Ditylum
Eucampia
Gymnodinium
Heterocapsa
Kofoidinium
Leptocylindrus
Pleurosigma
Protoperidinium
Pseudo-nitzshcia Lg. Cell
707
200
2007
35
1733
Average (Cells/L)
54
43
1473
6
34
4
11
40
117
23
32
43
10
16
136
10
84
SE
31
13
23
4
17
2
6
2
33
6
6
2
4
6
16
6
104
Average (Cells/L)
7
102
2
136
13
7
65
24
56
2
2
13
7
116
16
4
4
2
4
21
SE
7
5
2
14
2
5
3
4
5
2
2
5
4
7
0
106
Date
10/24/2012
Date
10/30/2012
Date
11/5/2012
type
Rhizosolenia
Scripsiella
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
Genus
Asteromphalus
Ceratium
Chaetoceros
Cylindrotheca
Diylum
Paralia
Pleurosigma
Protoperidinium
Scripsiella
Skeletonema
Thalassiosira
Silicoflagellate
Genus
Ceratium
Chaetoceros
Cylindrotheca
Leptocylindrus
Paralia
Pseudo-nitzschia Lg. Cell
type
Scripsiella
Skeletonema
Thalassiosira
Silicoflagellate
Genus
Actinoptychus
Alexandrium
Asterionellopsis
Chaetoceros
Cylindrotheca
Ditylum
Protoperidinium
Scripsiella
80
9
34
2
13
38
Average (Cells/L)
5
2
5
2
8
2
2
12
77
12
6
11
Average (Cells/L)
5
2
13
5
2
7
2
2
2
2
3
SE
3
2
3
2
3
2
2
2
10
2
2
4
SE
5
2
7
3
2
5
7
8
12
65
Average (Cells/L)
2
40
1
4
4
2
4
135
3
2
3
2
13
SE
2
7
1
0
2
1
4
16
107
Date
11/26/2012
Date
12/10/2012
Date
12/24/2012
Skeletonema
Thalassiosira
Silicoflagellate
Genus
Alexandrium
Asterionellopsis
Cerataulina
Ceratium
Chaetoceros
Cylindrotheca
Dinophysis
Ditylum
Heterocapsa
Leptocylindrus
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Cerataulina
Chaetoceros
Coscinodiscus
Cylindrotheca
Ditylum
Leptocylindrus
Meringosphaera
Pleurosigma
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Actinoptychus
Cerataulina
Chaetoceros
Cylindrotheca
Dinophysis
Ditylum
Leptocylindrus
Pleurosigma
6
6
37
Average (Cells/L)
1
1
1
1
27
3
2
7
1
13
3
11
1
7
16
Average (Cells/L)
4
63
1
4
2
12
1
1
6
1
5
15
Average (Cells/L)
7
8
135
4
7
7
14
7
1
1
4
SE
1
1
1
1
5
2
2
1
1
3
2
4
1
2
7
SE
2
2
1
2
1
2
1
1
3
1
3
2
SE
5
0
6
2
1
1
1
3
108
Date
1/11/2013
Date
1/28/2013
Date
2/18/2013
Protoperidinium
Scripsiella
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Cerataulina
Chaetoceros
Cylindrotheca
Dinophysis
Leptocylindrus
Navicula
Odontella
Paralia
Pleurosigma
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Cerataulina
Chaetoceros
Cylindrotheca
Dinophysis
Ditylum
Leptocylindrus
Pleurosigma
Protoperidinium
Pseudo-nitzschia Lg. Cell
type
Rhizosolenia
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Cerataulina
Chaetoceros
Cylindrotheca
Detonula
1
4
5
8
15
65
Average (Cells/L)
18
67
2
5
4
1
1
1
1
7
1
15
18
Average (Cells/L)
10
942
20
2
48
20
2
3
1
0
3
4
6
19
SE
6
6
1
2
2
1
1
1
1
6
1
2
4
SE
5
37
8
2
12
5
2
3
2
5
34
27
199
24
Average (Cells/L)
17
52
37
3
2
3
6
15
19
2
SE
2
8
9
3
109
Date
3/5/2013
Date
3/11/2013
Date
3/18/2013
Date
3/25/2013
Dinophysis
Ditylum
Leptocylindrus
Pleurosigma
Protoperidinium
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Coscinodiscus
Cylindrotheca
Scripsiella
Thalassiosira
Silicoflagellate
Genus
Cerataulina
Cylindrotheca
Dinophysis
Odontella
Protoperidinium
Scripsiella
Thalassiosira
Silicoflagellate
Genus
Chaetoceros
Cylindrotheca
Ditylum
Navicula
Pleurosigma
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Cerataulina
Chaetoceros
Cylindrotheca
Heterocapsa
Leptocylindrus
Licmorpha
2
10
3
5
6
6
79
2375
43
Average (Cells/L)
1
6
1
13
2
Average (Cells/L)
4
11
1
1
7
10
27
22
Average (Cells/L)
4
140
1
2
3
6
18
77
2
Average (Cells/L)
12
56
9
5
40
2
2
3
3
0
2
2
6
89
14
SE
1
1
1
4
2
SE
4
5
1
1
1
4
4
6
SE
2
10
1
1
0
2
1
5
1
SE
2
8
3
5
5
2
110
Date
4/8/2013
Navicula
Skeletonema
Thalassionema
Thalassiosira
Silicoflagellate
Genus
Chaetoceros
Cylindrotheca
Heterocapsa
Leptocylindrus
Protoperidinium
Skeletonema
Stephanopyxis
Thalassionema
Thalassiosira
2
2
7
360
10
Average (Cells/L)
4818
23
4
27
84
145
11
214
2801
2
2
5
36
0
SE
88
7
5
4
8
21
7
17
43
111
