DEVELOPMENT
AND
APPLICATION
OF
A
FISH
EMBRYO
BIOASSAY
FOR
STUDIES
OF
SURFACE
WATER
TOXICITY
IN
THE
BRAZOS
RIVER
by
Matthew
D.
Meyer,
B.S.
A
Thesis
In
BIOLOGY
Submitted
to
the
Graduate
Faculty
of
Texas
Tech
University
in
Partial
Fulfillment
of
the
Requirements
for
the
Degree
of
MASTER
OF
SCIENCES
Approved
Reynaldo
Patiño
Chairperson
of
the
Committee
Stephen
B.
Cox
Lauren
S.
Gollahon
Fred
Hartmeister
Dean
of
the
Graduate
School
December,
2009
Copyright
2009,
Matthew
Meyer
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
ACKNOWLEDGMENTS
I
would
like
to
thank
my
graduate
committee
chairman,
Dr.
Reynaldo
Patiño,
for
his
valuable
guidance
and
advice
throughout
this
project.
I
would
also
like
to
thank
the
other
members
of
my
graduate
committee,
Drs.
Stephen
Cox
and
Lauren
Gollahon
for
their
guidance.
I
thank
Tonya
Pinkerton
of
the
Texas
Tech
Cooperative
Fish
and
Wildlife
Research
Unit
for
her
assistance
and
the
Department
of
Biological
Sciences
for
their
teaching
assistantship.
I
thank
Dr.
Bibek
Sharma,
Prakash
Sharma,
Leticia
Torres
and
Dylan
Kuhne
for
their
assistance
in
the
field
and
laboratory.
I
am
especially
thankful
for
my
family,
friends,
labmates,
and
officemates
for
their
help,
moral
support
and
much‐needed
humor.
Funding
for
this
research
was
provided
by
the
USGS
Texas
Cooperative
Fish
and
Wildlife
Research
Unit.
ii
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
TABLE
OF
CONTENTS
Acknowledgments ..................................................................................................ii
Abstract................................................................................................................... v
List
of
Tables ......................................................................................................... vii
List
of
Figures ....................................................................................................... viii
I.
Background ..........................................................................................................1
Surface
water
quality
in
the
United
States .................................................1
Municipal
wastewater
effluent...................................................................2
Eutrophication
and
algal
blooms ................................................................4
Golden
algal
blooms
and
their
impacts
on
aquatic
biota ...........................5
Golden
algal
toxins
and
their
mechanisms .................................................6
Use
of
fish
embryos
in
water
toxicity
studies .............................................8
Significance
and
objectives
of
present
study..............................................9
Literature
cited .........................................................................................10
II.
Development
and
application
of
a
fish
embryo
bioassay
for
studies
of
surface
water
toxicity
in
the
Brazos
River.............................................................17
Abstract.....................................................................................................17
Introduction ..............................................................................................19
Materials
and
Methods.............................................................................21
Zebrafish
embryo
toxicity
assay....................................................21
Double
Mountain
Fork
study ........................................................23
CLS
water
dilution
test ..................................................................25
iii
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Embryotoxic
activity
at
tertiary‐treated
wastewater
discharge
site
(NF4).......................................................................26
Statistical
analysis .........................................................................26
Results.......................................................................................................28
Effect
of
water
hardness,
salinity
and
pH
on
embryo
survival ..........................................................................................28
Spatial
and
temporal
patterns
of
surface
water
quality
in
the
Double
Mountain
Fork............................................................28
Spatial
and
temporal
patterns
of
surface
water
toxicity
in
the
Double
Mountain
Fork ..................................................................30
General
associations
between
water
quality
and
toxicity ............32
Discussion .................................................................................................32
Literature
cited .........................................................................................49
Appendices
A.
Measurements
of
water
quality .........................................................55
B.
Results
of
surface
water
treatments
(without
DADPA) ......................57
C.
Results
of
surface
water
treatments
(with
DADPA)............................60
iv
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
ABSTRACT
The
Double
Mountain
Fork
of
the
Brazos
River
is
located
in
west
Texas
(USA)
and
consists
of
North
and
South
Forks.
The
North
Fork,
which
includes
Lubbock’s
Canyon
Lakes
System
(CLS),
receives
wastewater
effluent
and
urban
stormwater
runoff
and
has
experienced
harmful
(golden)
algal
blooms
during
winter
months
since
2003.
Golden
alga
(Prymnesium
parvum)
is
known
to
produce
toxic
compounds
capable
of
killing
gilled
aquatic
organisms.
The
South
Fork,
which
includes
Lake
Alan
Henry,
receives
no
wastewater
or
urban
runoff
and
has
not
experienced
golden
algal
blooms.
Little
is
known
about
the
quality
of
surface
water
in
the
Double
Mountain
Fork
as
habitat
for
aquatic
life.
The
objectives
of
this
study
were
to
(1)
characterize
a
zebrafish
embryo
toxicity
assay
for
use
in
field
studies
of
surface
water
quality,
and
(2)
use
this
bioassay
to
characterize
seasonal
and
spatial
patterns
of
surface
water
toxicity
in
the
Double
Mountain
Fork.
For
the
bioassay,
embryos
were
placed
in
24‐well
plates
(1
embryo/well)
containing
the
appropriate
solutions
within
30
min
postfertilization,
and
mortality
was
recorded
at
hatching
(72
h
postfertilization
at
28.5
°C).
Within
the
range
observed
in
most
freshwater
habitats,
it
was
found
that
general
(nonspecific)
water
quality
variables
such
as
hardness,
salinity
and
pH
did
not
affect
embryo
viability.
Thus,
the
zebrafish
embryo
assay
provides
a
useful
new
tool
to
assess
the
quality
of
aquatic
habitats
from
a
toxicity
standpoint.
For
the
field
study,
standard
water
quality
parameters
were
measured
and
water
samples
were
collected
for
the
bioassay
quarterly
between
March
2008
and
March
2009
from
five
sites
on
the
North
Fork
(three
in
the
CLS
and
two
downstream)
and
three
sites
on
the
South
Fork
(two
in
Lake
Alan
Henry
and
one
upstream).
However,
the
site
on
the
South
Fork
upstream
of
Lake
Alan
Henry
had
to
be
excluded
from
all
analysis
because
its
relatively
high
salinity
values
fell
within
the
lethal
range
for
zebrafish
embryos.
Principal
component
analysis
identified
salinity/conductivity
v
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
and
total
hardness
(calcium
carbonate
equivalents)
as
the
measured
water
quality
variables
that
best
separate
the
North
(higher
values)
and
South
Forks
(lower
values;
excluding
the
upstream
site).
Zebrafish
embryos
were
exposed
to
water
samples
in
the
presence
or
absence
of
DADPA,
a
compound
that
enhances
the
potency
of
golden
alga
toxin.
North
Fork
water
was
generally
more
toxic
than
South
Fork
water,
especially
in
winter
months
when
golden
algal
blooms
typically
occur.
In
fact,
a
golden
algal
bloom
and
associated
fish
kill
that
occurred
in
the
CLS
in
March
2008
coincided
with
extremely
high
levels
of
embryotoxic
activity
in
water
from
the
affected
sites.
Water
toxicity
was
also
enhanced
in
the
presence
of
DADPA
in
most
samples
from
the
North
Fork,
but
generally
not
from
the
South
Fork.
Overall,
these
observations
suggest
that
the
results
of
the
zebrafish
embryo
bioassay
represent
measures
of
golden
algal
toxicity
in
surface
water
from
the
Double
Mountain
Fork.
Nonparametric
(regression
tree)
and
parametric
(AIC
criterion)
multiple
regression
analyses
indicated
a
positive
association
at
the
landscape
level
between
total
water
hardness
and
its
toxicity
in
the
bioassays.
These
observations
are
consistent
with
knowledge
that
divalent
cations
of
water
hardness
(calcium,
magnesium)
serve
as
cofactors
for
golden
algal
toxicity,
and
with
the
present
observations
of
higher
hardness
as
well
as
toxicity
in
surface
water
from
the
North
Fork
relative
to
the
South
Fork.
Curiously,
in
the
presence
of
DADPA,
North
Fork
water
downstream
of
a
tertiary‐treated
wastewater
discharge
(i.e.,
the
two
sites
downstream
of
the
CLS)
was
highly
toxic
throughout
the
year.
This
observation
suggests
that
municipal
wastewater
effluent
may
be
supplying
chronic
low
levels
of
golden
algal‐like
toxin
to
the
North
Fork.
However,
confirmation
of
this
hypothesis
will
require
further
study.
vi
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
LIST
OF
TABLES
2.1
Factor
loading
matrix
for
the
first
two
components
of
principal
component
analysis
of
water
quality
variables
(except
dissolved
oxygen)
for
all
sampling
sites
and
dates
(excluding
SF‐1)............................39
2.2
Regression
model
for
predicting
embryo
mortality
based
on
water
quality
parameters.
Backwards
elimination
multiple
regression
was
used
to
eliminate
variables
based
on
AIC.
βi
represents
the
standardized
partial
regression
coefficient .................................................40
A.1
Measurements
of
water
quality ..................................................................55
B.1
Results
of
surface
water
treatments
(without
DADPA) ...............................57
C.1
Results
of
surface
water
treatments
(with
DADPA) .....................................60
vii
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
LIST
OF
FIGURES
2.1
Study
sites
in
the
Double
Mountain
Fork
of
the
Brazos
River.
Five
sites
were
sampled
in
the
North
Fork,
three
within
the
Canyon
Lakes
System
(NF‐1
through
NF‐3)
and
two
just
downstream
of
this
system
(NF‐4
and
NF‐5).
In
the
South
Fork,
three
sites
were
chosen,
one
upstream
of
Lake
Alan
Henry
(SF‐1),
one
on
its
middle
section
(SF‐2),
and
the
third
near
further
downstream
near
the
boat
launch
(SF‐3).
Map
source:
nationalatlas.gov;
Lake
Alan
Henry
was
digitally
superimposed
and
its
size
is
not
according
to
scale ....................................41
2.2
Percent
zebrafish
embryo
survival
at
different
concentrations
of
water
hardness
and
salinity
(top)
and
values
of
pH
(bottom).
Hardness/salinity
bars
represent
percent
survival
of
one
replicate
and
pH
bars
represent
the
mean
of
two
replicates
(±
SE).
Each
replicate
represents
one
plate
containing
20
embryos.
Bars
with
common
letters
are
not
significantly
different ............................................42
2.3
Biplot
of
principal
components
1
and
2.
Data
within
the
biplot
bear
numbers
that
represent
specific
sampling
locations
(1‐5,
NF1‐NF5;
7‐8,
SF2‐SF3).
Ninety‐five
percent
confidence
ellipses
are
centered
on
data
for
the
North
(NF)
and
South
(SF)
Forks.
The
vectors
of
hardness,
salinity
and
conductivity
seem
to
best
separate
the
ellipses .........................................................................................................43
2.4
Biplot
of
principal
components
1
and
2.
Data
within
the
biplot
bear
numbers
that
represent
specific
sampling
dates
(1,
March
2008;
4,
June
2008;
7,
September
2008;
10,
December
2008;
12,
February
2009;
13,
March
2009).
Ninety‐five
percent
confidence
ellipses
are
centered
on
each
sampling
date.
The
vector
of
temperature
seems
to
best
separate
the
ellipses
although
pH
also
seemed
to
follow
the
separation
axis .............................................................................................44
viii
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
2.5
Percent
zebrafish
embryo
mortality
exposed
to
surface
water
collected
from
the
study
sites.
Black
bars
(plain
surface
water)
represent
the
mean
of
two
replicates
(±
SE)
and
white
bars
(surface
water
+
DADPA)
represent
the
value
of
one
replicate.
White
bars
are
absent
for
March
2008
because
DADPA‐treated
surface
water
was
not
used
at
this
date;
and
March
2008
is
absent
from
the
South
Fork
column
of
graphs
because
water
was
not
collected
at
this
date.
For
plain
surface
water,
bars
with
common
letter
are
not
significantly
different
(p
<
0.05)...................................................................45
2.6
Percent
zebrafish
embryo
mortality
in
NF‐2
water
diluted
in
the
presence
or
absence
of
DADPA.
Dilution
water
was
dechlorinated
tap
water.
One
replicate
(plate
of
24
embryos)
per
treatment
was
used
in
this
experiment ...............................................................................46
2.7
Percent
zebrafish
embryo
mortality
in
NF‐4
water
and
water
collected
64
m
upstream
of
NF4.
Bars
represent
mean
percent
embryo
mortality
(±
SE,
n
=
2)
for
the
surface
water
treatment
(n
=
2)
and
the
value
of
a
single
replicate
for
the
DADPA
treatment.
Water
was
collected
on
July
9,
2009.
The
different
letters
on
the
surface
water
bars
indicate
a
significant
difference
(P
<
0.05) ....................47
2.8
Regression
tree
for
predicting
embryo
mortality
based
on
water
quality
parameters.
Hardness
(mg/L
in
calcium
carbonate
equivalents)
is
the
first
splitting
variable,
followed
by
pH.
Numbers
(e.g.,
0.328)
directly
below
each
leaf
(i.e.,
grouping)
show
the
predicted
mean
proportion
of
embryo
mortality.
The
sample
size
associated
with
each
grouping
(e.g.,
n
=
8)
also
is
shown ...........................48
ix
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
CHAPTER
I
BACKGROUND
Surface
water
quality
in
the
United
States
Environmental
policy
and
protection
in
the
United
States
before
1970
was
based
on
managing
the
environment
as
a
natural
resource.
Environmental
quality
played
almost
no
role
in
environmental
regulation.
Water
quality
regulation
was
left
to
the
states,
with
only
little
direction
from
the
Food
and
Drug
Administration,
Department
of
Agriculture
and
Public
Health
Service
(Andrews,
1999).
In
1970,
the
United
States
Environmental
Protection
Agency
(USEPA)
was
formed.
Since
that
time,
the
mission
of
the
USEPA
has
been
to
protect
human
health
and
the
environment
(USEPA,
2007).
In
1972,
the
United
States
Congress
passed
the
Federal
Water
Pollution
Control
Amendments
(the
Clean
Water
Act).
The
Clean
Water
Act
provided
$50
billion
dollars
for
the
construction
of
wastewater
treatment
facilities
throughout
the
United
States.
As
a
result,
wastewater
effluent
was
controlled
and
steps
were
taken
to
improve
human
and
aquatic
ecosystem
health.
Under
the
Clean
Water
Act,
states
were
given
the
rights
to
control
their
own
water
quality
standards,
as
long
as
those
standards
complied
with
the
act’s
criteria
of
maintaining
fishable
waters
that
were
able
to
support
aquatic
life
(Terry,
1996).
Despite
the
development
of
federal
and
state
regulations,
contamination
of
aquatic
environments
and
the
consequent
deterioration
of
habitats
for
aquatic
organisms
remain
huge
concerns.
Surface
water
contaminants
are
numbered
in
the
thousands.
Some,
such
as
heavy
metals,
synthetic
detergents,
pesticides
(e.g.
pyrethrins
and
pyrethroids),
inorganic
contaminants
(e.g.
chlorine,
ammonia
and
sulfides)
and
organic
contaminants
(e.g.
polychlorinated
biphenyls,
dioxins,
and
polycyclic
aromatic
hydrocarbons)
have
been
the
target
of
many
studies
and
have
well
characterized
effects
on
aquatic
organisms
(Rand
et
al.,
2003).
Of
concern
to
this
1
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
thesis
are
the
surface
water
quality
issues
of
municipal
wastewater
effluent,
stormwater
runoff
and
harmful
algal
blooms.
In
addition
to
pharmaceuticals
and
other
potentially
toxic
chemicals,
wastewater
effluent
contains
high
levels
of
nitrogen
(N)
and
phosphorous
(P)
(Carey
and
Migliaccio,
2009).
Stormwater
runoff
may
also
contribute
relatively
high
levels
of
toxicants
and
other
pollutants,
including
nutrients,
to
receiving
waters
(Skinner
et
al.,
1999;
Vaze
et
al.,
2004;
Kayhanian
et
al.,
2007).
Excessive
nutrient
loading
in
surface
waters
can
lead
to
algal
blooms,
which
in
turn
may
lower
dissolved
oxygen
levels
and
cause
health
impairment
or
death
of
aquatic
organisms;
some
algal
species
also
produce
toxins
(Landsberg,
2002).
Municipal
wastewater
effluent
Municipal
wastewater
effluent
is
primarily
a
byproduct
of
the
processing
of
domestic
wastewater
treatment.
This
process
involves
removing
physical,
chemical
and
biological
contaminants
from
wastewater
by
a
series
of
physical,
chemical
and
biological
processes.
When
wastewater
arrives
at
a
wastewater
treatment
facility,
it
is
typically
subjected
to
three
stages
of
treatment:
primary,
secondary,
and
tertiary.
Primary
treatment
consists
of
(1)
removing
large
object
with
a
raked
bar
screen
and
(2)
separating
wastewater
into
solid
and
liquid
phases
by
sedimentation.
Secondary
treatment
consists
of
the
biological
degradation
of
waste
and
other
contents
of
primary‐treated
wastewater.
Tertiary
treatment
consists
of
any
combination
of
various
additional
treatments
to
further
improve
effluent
quality
before
it
is
discharged.
Sometimes
this
involves
disinfection
(e.g.,
U.V.
radiation)
as
the
last
step
in
the
polishing
of
the
effluent.
Although
wastewater
treatment
is
an
effective
means
for
removing
most
biological
and
chemical
contaminants,
wastewater
effluent
remains
of
concern
because
it
may
contain
concentrations
of
contaminants
(nutrients
and
toxicants)
high
enough
to
negatively
affect
aquatic
biota.
The
ecological
impacts
of
wastewater
2
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
effluent
are
of
particular
concern
in
streams
that
are
dominated
or
considerably
influenced
by
effluent
(Brooks
et
al,
2006).
Common
toxicants
in
wastewater
effluent
include
chlorine,
ammonia,
organophosphate
insecticides
(e.g.
diazinon,
malathion,
chlorpyrifos,
chlorfenvinphos),
metals
(e.g.
cadmium,
copper,
chromium,
lead,
nickel,
zinc),
dechlorination
chemicals
and
polymers,
surfactants
and
estrogenic
compounds
(United
States
Environmental
Protection
Agency,
1999).
Estrogenic
chemicals
(e.g.
17β‐estradiol
(E2)
and
17α‐ethynylestradiol
(EE2))
are
of
particular
concern,
as
they
can
disrupt
the
reproductive
system
and
health
of
organisms.
Reproductive
(endocrine)
disruption
has
been
reported
in
fishes
found
in
waters
that
receive
a
significant
input
of
wastewater
effluent
(Purdom
et
al.,
1994;
Jobling
et
al.,
1998).
Although
numerous
chemicals
can
be
classified
as
“endocrine
disrupters,”
estrogenic
hormones
are
thought
to
have
the
greatest
effect
on
the
function
of
the
endocrine
system
in
fishes
(Desbrow
et
al.,
1998;
Routledge
et
al.,
1998).
These
estrogens
are
used
as
oral
contraceptives
(EE2)
and
for
hormone
replacement
therapy
(E2).
Humans
excrete
these
estrogenic
hormones
as
sulfate
or
glucuronide
conjugates
in
urine
and
feces.
The
metabolized
estrogens
can
be
transformed
back
into
their
original
form
by
common
glucuronidase
and
sulfatase
enzymes
(Orme
et
al.,
1983).
Estrogenic
compounds
are
often
not
fully
removed
from
wastewater
effluent
that
is
released
into
the
environment.
Seasonal
patterns
of
toxic
activity
may
occur
in
wastewater.
Hemming
et
al.
(2004)
reported
that
in
fathead
minnow
exposed
to
wastewater,
significant
increases
in
plasma
vitellogenin
concentrations
were
detected
in
the
months
of
December
and
March
(winter),
but
not
in
June
or
August
(summer).
Water
temperature
may
affect
bacterial
metabolic
activity
in
a
wastewater
treatment
plant,
thereby
affecting
concentration
of
contaminants
(including
estrogens)
in
wastewater
effluent.
If
temperatures
are
low
during
winter
months,
bacterial
metabolic
activity
may
be
decreased,
and
toxicity
of
wastewater
effluent
may
increase
during
this
time
of
the
3
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
year.
On
a
shorter
time
scale,
Martinovic
et
al.
(2008)
reported
that
the
estrogenic
activity
of
effluent
from
a
modern
sewage
treatment
plant
was
extremely
variable
(42
±
25.4
[mean
±
SD]
ng
17ß‐estradiol
equivalents/L)
and
showed
no
daily
patterns
during
an
18‐day
observation
period.
Eutrophication
and
algal
blooms
Anthropogenic
activities
have
had
major
impacts
on
aquatic
ecosystems
by
altering
the
cycles
of
growth‐limiting
nutrients,
such
as
N
and
P.
Agricultural
(e.g.,
Matson
et
al.,
1997)
and
urban
(Vaze
et
al.,
2004)
runoff
are
important
sources
of
N
and
P,
but
discharge
of
wastewater
seems
to
be
the
most
significant
contributor
to
the
eutrophication
of
aquatic
habitats
(Carey
and
Migliaccio,
2009).
Land
(via
wastewater
and
runoff)
and
atmospheric
loading
of
P
to
aquatic
ecosystems
has
increased
over
time
(Brunner
and
Backofen,
1998;
Bennett
et
al.,
2001;
Carey
and
Migliaccio,
2009).
In
the
United
States,
the
mean
concentration
of
total
P
in
rivers
and
streams
is
far
greater
than
the
mesotrophic‐eutrophic
total
P
boundary
(Smith
et
al.,
1987;
Dodds
et
al.,
1998).
These
observations
indicate
that
water
quality
in
the
majority
or
rivers
and
streams
in
the
United
States
is
poor
from
the
viewpoint
of
eutrophication
(Smith
et
al.,
1999).
In
fact,
of
102
reservoirs
in
Texas
for
which
enough
data
was
available
over
a
10
year
period,
all
classified
as
mesotrophic‐to‐hypereutrophic
with
not
a
single
reservoir
ranking
as
oligotrophic
(Texas
Commission
on
Environmental
Quality,
2008).
An
increase
in
abundance
of
algae
is
one
of
the
most
common,
readily
visible
effects
of
N
and
P
loading
into
an
aquatic
ecosystem
(Carpenter
et
al.,
1998).
When
inorganic
P
is
added
to
a
flowing
river
or
stream,
periphyton
biomass
increases
and
this
increase
in
primary
productivity
is
cascaded
into
stream
consumer
populations
(Hershey
et
al.,
1988).
Eutrophication
and
algal
blooms
negatively
affect
both
lakes
and
rivers
(Reckhow
and
Chapra,
1983;
USEPA,
1996),
and
reduction
of
algal
biomass
is
associated
with
successful
eutrophication
control
projects
(Smith,
1998).
Eutrophic
4
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
lakes
often
show
a
shift
in
dominance
by
cyanobacteria,
where
some
species
produce
highly
toxic
compounds
(Skulberg
et
al.,
1984;
Carmichael,
1991).
In
addition
to
producing
toxins
that
can
cause
fish
kills,
cyanobacteria
form
water
surface
scums
and
decrease
drinking
water
quality
(Klemer
and
Konopka,
1989;
Kann
and
Smith,
1999;
Smith
et
al.,
2003).
Harmful
blooms
of
about
200
different
species
of
cyanobacteria
and
algae
have
been
documented
in
aquatic
habitats
ranging
from
freshwater
to
brackish
to
marine
(Landsberg,
2002).
Golden
algal
blooms
and
their
impacts
on
aquatic
biota
Golden
alga
(Prymnesium
parvum)
is
a
small
euryhaline
and
eurythermal
organism
that
produces
toxic
compounds
(Otterstrøm
and
Steeman‐Nielsen,
1940;
Yariv
and
Hestrin,
1961;
Edvardsen
and
Imai,
2006;
Sager
et
al.,
2008).
The
first
incidence
of
a
golden
algal
bloom
in
Texas
(USA)
was
recorded
in
1985
in
the
Pecos
River
(Sager
et
al.,
2008).
Since
then,
many
other
states
have
reported
golden
algal
blooms
including
Alabama,
Arizona,
Arkansas,
California,
Florida,
Hawaii,
Louisiana,
Maine,
Mississippi,
New
Mexico,
North
Carolina,
Oklahoma,
South
Carolina,
Washington
and
Wyoming
(Sager
et
al.,
2008).
Golden
alga
blooms
have
been
linked
to
the
deaths
of
millions
of
fishes
of
many
different
species
in
the
state
of
Texas
(Sager
et
al.,
2008).
The
mechanisms
responsible
for
the
spread
of
golden
alga
blooms
are
uncertain
(Edvardsen
and
Imai,
2006;
Sager
et
al.,
2008),
but
it
is
likely
that
contributing
factors
include
the
high
salt
content
and
eutrophication
of
surface
waters
where
most
blooms
have
been
reported.
Major
golden
alga‐related
fish
kills
have
been
reported
from
Lubbock’s
Canyon
Lake
System
(CLS,
Figure
2.1)
to
areas
of
the
Brazos
near
Houston,
Texas
(Texas
Parks
and
Wildlife,
2007).
In
the
period
between
1981
and
2003,
estimates
place
the
number
of
fish
killed
by
golden
algal
blooms
in
the
Brazos
River
Basin
at
over
8
million
(Texas
Parks
and
Wildlife,
2007).
5
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
The
North
Fork
of
the
Double
Mountain
Fork
of
the
Brazos
River
(Figure
2.1)
is
influenced
by
wastewater
effluent
and
urban
runoff
(Smith
et
al.,
1979;
City
of
Lubbock
Office
of
Water
Utilities,
2007).
Golden
algal
blooms
have
been
recorded
in
the
CLS
since
2003
(Texas
Parks
and
Wildlife,
2007).
In
2003,
Buffalo
Springs
Lake
(NF3,
Figure
2.1)
experienced
a
significant
fish
kill
due
to
P.
parvum,
with
an
approximate
death
toll
of
124,799
individuals
(Texas
Parks
and
Wildlife,
2007).
This
kill
had
a
major
impact
on
fish
populations
in
the
lake
(Munger
et
al.,
2005).
During
the
same
time,
Texas
Parks
and
Wildlife
(2007)
reported
Lakes
1‐6
of
the
CLS
had
an
estimated
9,130
mortalities.
Buffalo
Springs
Lake
also
experienced
a
fish
kill
in
2005,
which
was
limited
to
a
single
small
cove.
Another
major
golden
alga‐related
fish
kill
in
the
CLS
was
reported
in
the
period
of
March
3‐17,
2008
(Texas
Parks
and
Wildlife,
2009).
Golden
algal
toxins
and
their
mechanisms
Prymnesins
are
reportedly
toxins
that
golden
alga
produce
and
have
been
classified
as
glycosides
by
Igarashi
et
al.
(1996,
1999).
However,
golden
alga
seems
to
cause
a
variety
toxic
effects
(ichthyotoxic,
cytotoxic,
neurotoxic,
antibacterial,
et
cetera)
(Shilo,
1971)
and
there
is
insufficient
information
at
the
present
time
judge
whether
all
these
activities
are
associated
with
a
single
compound
or
type
of
toxin.
Therefore,
in
this
thesis
the
term
“golden
alga
toxin”
is
used
generically
to
refer
to
the
compound
or
compounds
responsible
for
the
ichthyotoxic
activity.
The
exact
mechanisms
of
golden
alga
toxin
are
unknown,
but
this
toxin
is
reportedly
able
to
change
cell
membrane
permeability
and
fluidity
(Shilo,
1971).
Shilo
(1981)
reported
that
golden
alga
toxin
affects
gilled
aquatic
organisms.
In
fishes,
golden
alga
toxin
seems
to
increase
the
permeability
of
epithelial
cells
in
the
gill.
Disruption
in
ion
and
water
balance
is
believed
to
result
in
the
affected
organisms
(Edvardsen
and
Imai,
2006).
However,
damage
to
the
gill
epithelium
would
also
have
immediate
effects
on
respiratory
gas
exchange,
which
depending
on
the
duration
and
6
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
severity
of
exposure
could
be
directly
or
synergistically
lethal
to
fishes.
Gill
repair
was
reported
in
fishes
after
affected
individuals
were
removed
from
golden
alga‐
contaminated
water
(Shilo,
1981).
Certain
water
quality
parameters,
such
as
salinity,
pH
and
water
temperature
affect
golden
alga
growth
and
toxicity.
Baker
et
al.
(2007)
reported
that
the
maximal
growth
of
P.
parvum
in
laboratory
conditions
occurred
at
27
°C,
22
practical
salinity
units
and
light
intensity
of
275
µmol
photons
∙
m‐2
∙
s‐1.
Shilo
(1981)
reported
no
correlation
between
golden
alga
density
and
water
toxicity.
Namely,
toxicity
can
be
observed
at
low
golden
alga
density,
and
high
densities
can
result
in
no
toxicity.
Golden
alga
toxicity
is
increased
in
water
temperatures
below
30
°C
and
pH
above
7
(Shilo
and
Shilo,
1953).
Several
studies
have
shown
that
experimental
manipulations
of
water
pH
affect
golden
alga
densities
and
toxicity
(McLaughlin,
1958;
Ulitzer
and
Shilo,
1966;
Sager
et
al.,
2007;
Valenti
et
al.,
in
press).
The
potency
of
golden
alga
toxin
seems
to
be
higher
at
pH
above
7.
Additionally,
Ulitzur
and
Shilo
(1964)
reported
that
the
ichthyotoxic
activity
of
golden
alga
was
increased
as
pH
of
their
culture
medium
was
raised
from
7
to
8
or
9
in
the
presence
of
3,3’‐
diaminodipropylamine
(DADPA,
see
next
paragraph).
Although
the
ionization
state
of
the
toxin
was
proposed
to
exert
considerable
influence
on
its
toxicity
(Valenti
et
al.,
in
press),
the
exact
mechanisms
by
which
water
quality
conditions
affect
golden
alga
cell
density
or
toxin
potency
are
unknown.
DADPA
is
a
cationic
polyamine
and
seems
to
serve
as
cofactor
(i.e.
a
substance
whose
presence
is
essential
for
the
activity
of
a
chemical)
for
golden
alga
ichthyotoxic
activity.
Ulitzer
and
Shilo
(1964)
used
DADPA
to
activate
golden
algal
toxin
for
use
in
an
assay
system
for
the
determination
of
its
ichthyotoxicity.
They
also
used
several
other
polyamines
(spermine,
spermidine,
tetraethylene
pentamine)
to
increase
golden
alga
ichthyotoxic
activity.
DADPA
increased
ichthyotoxic
activity
of
golden
alga
by
5x,
while
spermine
and
tetraethylene
pentamine
increased
7
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
ichthyotoxic
activity
by
10x
and
7.5x,
respectively.
Johnson
and
Dalløkken
(1999)
also
reported
that
several
polyamines
act
as
cofactors
of
golden
alga
ichthyotoxicity.
Yariv
and
Hestin
(1961)
reported
that
polyamines
may
also
influence
the
ichthyotoxicity
of
Chrysochromulina
leadbeateri
as
well
as
enhance
its
growth.
Chrysochromulina
leadbeateri
is
a
member
of
Prymnesiophyceae,
the
same
family
of
golden
alga.
However,
not
all
algal
ichthyotoxins
require
a
cofactor
or
react
equally
to
a
cofactor.
For
example,
saponins,
a
class
of
common
plant
toxins
that
have
similar
properties
as
golden
algal
toxin,
do
not
require
a
cofactor
(Yariv
and
Hestin,
1961).
Hwang
et
al.
(2003)
reported
that
although
several
polyamines
(e.g.
spermidine
and
spermine)
can
enhance
the
growth
of
Alexandrium
minutum,
these
compounds
do
not
affect
the
ichthyotoxicity
of
this
algal
species.
Thus,
it
appears
that
the
influence
of
polyamines
on
algal
ichthyotoxicity
is
species‐
or
toxin‐specific.
The
metallic
cations,
calcium
and
magnesium,
are
also
known
to
potentiate
golden
alga
toxicity
(Yariv
and
Hestrin,
1961;
Ulitzer
and
Shilo,
1964,
1966).
It
should
be
noted
that
calcium
and
magnesium
are
the
principal
ions
contributing
to
the
hardness
of
most
surface
waters
and
thus,
when
their
concentrations
in
water
are
high,
so
is
total
water
hardness.
This
situation
may
explain,
at
least
in
part,
why
toxic
blooms
of
golden
alga
in
inland
waters
typically
occur
in
slightly
brackish
aquatic
habitats
(Sager
et
al.,
2008),
as
salinity
and
hardness
of
surface
waters
are
typically
positively
correlated.
Use
of
fish
embryos
in
water
toxicity
studies
Very
few
studies
have
used
fish
embryos
for
toxicity
screens
in
the
laboratory
and
even
fewer
studies
have
used
these
assays
to
examine
the
quality
of
surface
waters.
However,
there
is
growing
interest
in
the
use
of
fish
embryos
as
an
alternative
tool
to
examine
the
presence
and
potency
of
aquatic
toxicants
(Scholz
et
al.,
2008).
Schulte
and
Nagel
(1994)
and
Nagel
(2002)
have
proposed
the
use
and
standardization
of
the
zebrafish
embryo
for
laboratory
toxicity
testing.
In
their
8
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
protocols
(Schulte
and
Nagel,
1994;
Nagel,
2002),
eggs
are
exposed
in
Petri
dishes
soon
after
fertilization
and
exposures
are
terminated
at
48
hours
post
fertilization
(hpf).
The
Organisation
for
Economic
Co‐operation
and
Development
(OECD)
(2006)
has
also
proposed
a
similar
zebrafish
embryo
toxicity
test,
the
fish
embryo
toxicity
test,
for
international
standardization.
The
OECD
(2006)
recommends
exposure
of
newly
fertilized
eggs
in
multi‐well
culture
plates
and
termination
after
48
hpf.
Assay
termination
is
at
48
hpf
because
the
zebrafish
embryo
is
not
considered
an
animal
for
regulatory
purposes.
Most
of
these
proposed
assays
are
meant
for
toxicity
screens
in
the
laboratory
using
defined
rearing
water
conditions,
although
the
zebrafish
embryo
has
been
recently
used
to
assay
the
acute
toxicity
of
wastewater
effluent
(Schulz
et
al.,
2008).
To
our
knowledge,
there
are
no
existing
or
proposed
protocols
for
the
use
of
fish
embryos
in
toxicity
assays
for
field
(surface)
water
samples.
Significance
and
objectives
of
present
study
Although
water
flowing
in
the
North
Fork
of
the
Double
Mountain
Fork
of
the
Brazos
River
originates
largely
from
wastewater
effluent
and
stormwater
runoff
and
is
also
known
to
harbor
golden
alga,
very
little
is
known
about
the
quality
of
this
water
for
the
early
life
stages
of
fishes.
Furthermore,
nothing
is
known
about
the
ability
of
golden
algal
toxin
to
affect
fish
embryo
viability.
Knowledge
of
the
potential
impact
of
golden
algal
toxin
to
fish
embryos
is
important
because
the
viability
of
fish
populations
depends
on
larval‐juvenile
recruitment
into
adult
populations.
Therefore,
the
objectives
of
this
study
are
to
(1)
characterize
a
zebrafish
embryo
toxicity
assay
for
use
in
field
studies
of
surface
water
quality,
and
(2)
use
the
zebrafish
embryo
toxicity
assay
to
characterize
seasonal
and
spatial
patterns
in
surface
water
toxicity
in
the
upper
Brazos
River
(Double
Mountain
Fork).
9
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
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Texas
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December
2009
CHAPTER
II
DEVELOPMENT
AND
APPLICATION
OF
A
FISH
EMBRYO
BIOASSAY
FOR
STUDIES
OF
SURFACE
WATER
TOXICITY
IN
THE
UPPER
BRAZOS
RIVER,
TEXAS
Abstract
The
Double
Mountain
Fork
(DMF)
of
the
Brazos
River
(Texas,
USA)
consists
of
North
and
(NF)
South
Forks
(SF).
The
NF,
but
not
the
SF,
is
influenced
by
wastewater
effluent
and
urban
runoff
and
has
also
experienced
toxic
blooms
of
golden
alga
(GA)
(Prymnesium
parvum).
A
zebrafish
embryo
assay
was
developed
for
a
study
of
spatial
and
temporal
patterns
of
water
toxicity
in
the
DMF.
Embryos
were
placed
in
24‐well
plates
(1
embryo/well)
containing
the
appropriate
solutions
within
30
min
postfertilization,
and
mortality
was
recorded
at
72
h
postfertilization.
The
bioassay
was
validated
by
showing
tolerance
to
different
levels
of
nonspecific
water
quality
variables
(hardness,
salinity,
pH)
within
the
range
observed
in
most
freshwater
habitats.
Standard
water
quality
parameters
were
measured
and
water
samples
were
collected
quarterly
for
the
bioassay
between
March
2008
and
March
2009
from
five
sites
on
the
NF
and
three
sites
on
the
SF.
However,
the
upstream
site
on
the
SF
was
eliminated
because
its
high
salinity
values
fell
within
the
lethal
range
for
zebrafish
embryos.
Embryos
were
exposed
to
water
samples
in
the
presence
or
absence
of
DADPA,
a
compound
that
enhances
the
potency
of
GA
toxin.
NF
water
generally
was
more
toxic
than
SF
water,
especially
in
winter
months
when
GA
blooms
typically
occur.
In
fact,
coinciding
with
a
major
GA‐related
fish
kill,
water
from
the
first
three
upstream
sites
in
the
NF
was
highly
embryotoxic
in
March
2008.
Water
toxicity
was
enhanced
in
the
presence
of
DADPA
in
most
samples
from
the
NF,
but
generally
not
the
SF.
These
observations
suggest
that
the
bioassay
is
detecting
GA
toxicity.
Principal
component
analysis
identified
salinity
and
hardness
as
the
water
quality
variables
that
best
separate
the
NF
and
SF.
Nonparametric
(regression
tree)
and
17
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
parametric
(AIC
criterion)
multiple
regression
analyses
indicated
a
positive
association
at
the
landscape
level
between
water
hardness
and
its
toxicity
in
the
bioassays.
These
observations
are
consistent
with
knowledge
that
divalent
cations
(calcium,
magnesium)
serve
as
cofactors
for
golden
algal
toxicity,
and
with
the
present
observations
of
higher
hardness
as
well
as
toxicity
in
surface
water
from
the
NF
relative
to
the
SF.
18
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Introduction
Anthropogenic
activities
have
impacted
aquatic
ecosystems
by
altering
amounts
and
cycles
of
growth‐limiting
nutrients
(eutrophication);
introducing
toxic
chemicals
into
the
environment;
or
changing
other
physicochemical
traits
of
water
such
as
the
amount
of
suspended
and
dissolved
materials
or
temperature
levels
(Heath,
1995).
Although
agriculture
is
one
major
source
of
anthropogenic
nutrients
such
as
nitrogen
and
phosphorous
(Matson
et
al.,
1997),
urbanization
(including
discharges
of
wastewater
and
stormwater
runoff)
also
greatly
contributes
to
eutrophication
and
other
changes
in
the
chemical
composition
of
aquatic
habitats
(Kszos,
1990;
Cole
et
al.,
1993;
Caraco
et
al.,
1995;
Howarth
et
al.,
1995,
1996;
Meybeck,
1998;
Skinner
et
al.,
1999;
Brannon
Andersen
et
al.,
2004;
Vaze
et
al.,
2004;
Kayhanian
et
al.,
2007;
Lewis
et
al.,
2007;
Carey
and
Migliaccio,
2009).
In
the
United
States,
the
mean
concentration
of
total
phosphorus
in
rivers
and
streams
is
far
above
the
mesotrophic‐eutrophic
total
phosphorus
boundary
(Smith
et
al.,
1987,
1999;
Dodds
et
al.,
1998).
Pharmaceuticals
and
personal
care
products
(PPCPs)
carried
by
wastewater
are
also
of
concern
to
the
health
of
aquatic
ecosystems
(Daughton
and
Ternes,
1999).
An
increase
in
abundance
of
algae
is
one
of
the
most
common,
readily
visible
effects
of
nutrient
loading
into
an
aquatic
ecosystem
(Reckhow
and
Chapra,
1983;
Carpenter
et
al.,
1998).
Some
algal
species
produce
toxins
and
may
generate
harmful
algal
blooms
(Landsberg,
2002).
Golden
alga
(Prymnesium
parvum)
is
a
small,
euryhaline
and
eurythermal
organism
that
produces
toxins
capable
of
killing
gilled
aquatic
organisms
(Otterstrøm
and
Steeman‐Nielsen,
1940;
Yariv
and
Hestrin,
1961;
Edvardsen
and
Imai,
2006;
Sager
et
al.,
2008).
The
first
incidence
of
a
P.
parvum
bloom
in
inland
waters
of
the
United
States
occurred
in
the
Pecos
River
in
Texas
in
1985,
and
at
the
present
time
a
total
of
16
states
have
reported
blooms
(Sager
et
al.,
2008).
Golden
algal
blooms
have
been
linked
to
the
deaths
of
millions
of
fishes
of
many
different
species
in
the
state
of
Texas
(Sager
et
al.,
2008).
The
environmental
19
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
factors
responsible
for
triggering
golden
algal
blooms
or
their
toxicity
are
not
fully
understood
(Edvardsen
and
Imai,
2006;
Sager
et
al.,
2008).
One
unique
aspect
of
golden
algal
blooms
in
inland
(typically
brackish)
waters
in
Texas
is
that
they
tend
to
occur
when
water
temperatures
are
seasonally
low
(Sager
et
al.,
2008).
The
Brazos
River
(Texas)
has
experienced
golden
algal
blooms
since
the
early
1980’s
(Texas
Parks
and
Wildlife,
2007).
The
origin
of
the
North
Fork
of
the
Double
Mountain
Fork
of
the
Brazos
River
is
the
Canyon
Lake
System
(CLS)
in
Lubbock
County
(Texas,
USA).
This
lake
system
is
supplied
primarily
with
municipal
wastewater
effluent
and
urban
runoff
(Smith
et
al.,
1979;
City
of
Lubbock
Office
of
Water
Utilities,
2007).
Golden
algal
blooms
have
been
recorded
in
the
CLS
since
2003
(Texas
Parks
and
Wildlife,
2007).
Nutrients
and
other
compounds
in
wastewater
effluent
and
urban
runoff
may
be
contributing
to
the
conditions
necessary
for
these
blooms.
The
South
Fork
of
the
Double
Mountain
Fork
includes
Lake
Alan
Henry
in
Garza
County
(Texas,
USA),
a
reservoir
created
in
1993.
The
South
Fork
does
not
receive
municipal
wastewater
effluent
or
urban
runoff
and
there
are
no
reports
of
P.
parvum
blooms
for
this
section
of
the
Brazos
River.
The
Double
Mountain
Fork
of
the
Brazos
River
thus
provides
a
suitable
field
site
for
studies
of
golden
alga
and
the
environmental
factors
that
control
or
allow
bloom
events.
Bioassays
of
toxicity
are
valuable
tools
in
the
field
of
ecotoxicology.
The
current
vertebrate
model
for
assays
of
golden
algal
toxicity
is
the
fathead
minnow
(Pimephales
promelas,
juvenile
or
adult)
(Southard
and
Fries,
1995),
although
western
mosquitofish
(Gambusia
affinis)
and
guppy
(Poecilia
reticulata)
have
also
been
used
(Ulitzur
and
Shilo,
1964,
1966;
Southard
and
Fries,
1995).
There
is
growing
interest
in
using
fish
embryos
as
an
alternative
tool
to
examine
the
presence
and
potency
of
aquatic
toxicants
(Scholz
et
al.,
2008).
One
reason
is
that
fish
embryos
can
be
more
sensitive
to
certain
toxicants
than
fish
at
later
stages
of
development
or
in
vitro
cell
assays
(Schulte
and
Nagel,
1994;
Lange
et
al.,
1995;
Nagel,
2002;
Busquet
et
al.,
2008).
Although
the
zebrafish
(Danio
rerio)
embryo
has
been
recently
used
to
20
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
assay
the
acute
toxicity
of
wastewater
effluent
(Schulz
et
al.,
2008),
to
our
knowledge
there
are
no
existing
or
proposed
protocols
for
the
use
of
fish
embryos
in
assays
of
field
(surface)
water
toxicity.
Any
biological
assay
system
that
is
used
in
the
laboratory
for
the
purpose
of
monitoring
anthropogenic
degradation
of
surface
water
quality
must
be
able
to
withstand
natural
(nonspecific)
variability
in
water
quality.
Some
of
the
relevant
physicochemical
variables
of
water
quality
in
the
field
include
hardness,
salinity
and
pH.
Therefore,
the
objectives
of
this
study
are
to
(1)
characterize
a
zebrafish
embryo
toxicity
assay
for
use
in
field
studies
of
surface
water
quality,
and
(2)
use
this
assay
to
characterize
seasonal
and
spatial
patterns
of
surface
water
toxicity
in
the
upper
Brazos
River
(Double
Mountain
Fork).
Materials
and
Methods
Zebrafish
Embryo
Toxicity
Assay.
Methods
for
the
zebrafish
embryo
toxicity
assay
were
modified
from
Schulte
and
Nagel
(1994),
Nagel
(2002)
and
OECD
(2006).
The
main
difference
is
that
earlier
procedures
terminated
the
exposures
at
48
hours
postfertilization
(hpf)
whereas
in
the
present
study
the
exposures
continued
until
72
hpf,
which
is
often
considered
the
end
of
the
embryonic
period
in
zebrafish
raised
under
similar
environmental
conditions
(Kimmel
et
al.,
1995).
Fertilized
eggs
were
collected
as
previously
described
(Patiño
et
al.,
2003;
Mukhi
and
Patiño,
2007).
Briefly,
8
female
and
4
male
adult
zebrafish
were
placed
together
in
a
breeding
chamber
the
evening
before
spawning,
immediately
before
lights‐off.
Breeding
chambers
contained
a
false
bottom,
separated
by
a
screen
from
the
main
chamber,
in
which
the
fertilized
eggs
were
collected.
Eggs
were
retrieved
30
minutes
after
commencement
of
spawning
the
next
morning
(at
lights‐on)
and
immediately
placed
in
Petri
dishes
containing
the
appropriate,
pre‐warmed
(28.5
°C)
control
or
treatment
water.
Successful
fertilization
was
recognized
by
the
ability
of
embryos
to
reach
the
4‐cell
stage
by
one
hour
after
fertilization,
as
observed
under
a
stereomicroscope.
Fertilized
eggs
were
then
placed
in
24‐well
culture
plates
[1
egg
21
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
per
well,
wells
containing
1
mL
of
the
appropriate,
pre‐warmed
(28.5
°C)
control
or
treatment
water],
and
the
plates
were
placed
in
an
incubator
(DROS33D2;
Power
Scientific,
Inc.,
Pipersville,
PA)
with
a
temperature
of
28.5
°C
and
photoperiod
of
12L:12D.
Water
was
replaced
every
24
hours
with
the
appropriate
control
or
treatment
water
(pre‐warmed),
and
eggs
were
observed
every
12
hours
under
a
stereomicroscope.
The
main
observational
endpoint
was
mortality
(egg
coagulation
or
lack
of
heartbeat),
and
developmental
stage
(Kimmel
et
al.,
1995)
was
also
generally
monitored.
Exposures
for
this
study
were
terminated
at
72
hpf.
The
effects
of
different
levels
of
salinity,
total
hardness
and
pH
(within
the
range
expected
for
most
surface
waters)
were
determined
in
zebrafish
embryos.
For
this
purpose,
embryos
were
incubated
in
water
of
total
hardness
(mg/L)
of
1000,
800,
600,
400,
200,
and
13.4
(reconstituted
water).
Embryos
were
also
incubated
in
water
of
constant
hardness
(13.4
mg/L)
but
a
varying
salinity
(mg/L)
of
2000,
1600,
1200,
800,
400,
and
310
(reconstituted
water)
to
match
the
salinities
of
water
at
the
different
hardness
levels.
Each
treatment
(including
reconstituted
water)
was
conducted
in
a
separate
culture
plate
(n
=
24
embryos
per
treatment).
Reconstituted
water
consisted
of
Reverse
Osmosis
(RO)
water
containing
310
mg/L
R/O
Right
salt
mixture
(Cat.
#
00238;
Kent
Marine,
Acworth,
GA)
and
water
hardness
was
adjusted
by
adding
CaCl2
∙
H2O
(CAS
10034‐99‐8,
Sigma‐Aldrich,
St.
Louis,
MO)
and
MgSO4
∙
7H2O
(CAS
10035‐04‐8;
Sigma‐Aldrich,
St.
Louis,
MO)
in
the
appropriate
amounts
(with
both
contributing
equal
units
of
hardness
in
calcium
carbonate
equivalents).
Salinity
was
adjusted
in
reconstituted
water
by
adding
the
appropriate
amounts
of
NaCl
(CAS
7647‐14‐5;
Fisher
Scientific,
Fair
Lawn,
NJ).
Nominal
values
of
water
hardness
and
salinity
were
confirmed
by
direct
measurement
of
test
solutions.
Water
hardness
was
measured
with
a
Hach
DR/890
colorimeter
(Hach
Company,
Loveland,
CO);
and
salinity
with
a
YSI
556
water
quality
multiparameter
probe
(YSI,
Yellow
Springs,
OH).
Operation
and
calibration
of
these
instruments
were
conducted
according
to
vendor
instructions.
22
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
The
effects
of
pH
were
tested
at
one‐unit
increments
from
6
to
9.
Each
treatment
was
conducted
in
duplicate
culture
plates
(n
=
20/plate
for
total
of
40
embryos
per
treatment),
and
each
plate
contained
4
internal
control
wells
(combined
n
=
32
for
all
plates).
Water
for
this
experiment
consisted
of
reconstituted
water
(310
mg/L
R/O
Right)
with
294
mg/L
CaCl2
∙
H2O
and
123.3.mg/L
MgSO4
∙
7H2O
(nominal
hardness
in
calcium
carbonate
equivalents,
263
mg/L;
nominal
salinity,
627
mg/L).
Water
pH
was
adjusted
to
6,
7,
8,
and
9
using
200
mM
HCl
or
200
mM
NaOH.
After
pH
was
adjusted,
water
was
placed
in
an
incubator
at
28.5
°C.
To
confirm
pH
stability,
before
each
exposure
was
started,
pH
was
measured
and
recorded;
and
during
daily
water
exchanges,
pH
was
measured
again
in
pooled
water
removed
from
the
culture
plates
within
each
treatment.
In
all
of
these
tests,
mortality
and
gross
developmental
abnormalities
were
recorded
every
12
hours
by
observing
the
condition
of
all
embryos.
Embryonic
developmental
stage
(Kimmel
et
al.,
1995)
was
recorded
every
12
hours
for
10
individuals
per
treatment
plate.
Double
Mountain
Fork
Study.
The
Double
Mountain
Fork
of
the
Brazos
River
in
west
Texas
(USA)
consists
of
North
and
South
Forks
(Figure
2.1).
The
North
Fork
begins
with
a
series
of
artificial
lakes
in
the
City
of
Lubbock
(Texas),
the
Canyon
Lake
System
(CLS)
(Figure
2.1).
At
its
head
(site
NF1),
the
CLS
receives
reclaimed
municipal
wastewater
following
irrigation
over
a
land
application
site
(wastewater
used
for
irrigation
is
secondary‐treated).
Tertiary‐treated
effluent
is
also
directly
discharged
into
the
North
Fork
downstream
of
the
CLS
(at
site
NF4).
The
South
Fork
(sites
SF1
through
SF3,
Figure
2.1)
is
located
in
Garza
and
Kent
Counties
(Texas).
Lake
Alan
Henry
(SF3)
is
a
man‐made
reservoir.
Unlike
the
North
Fork,
at
the
present
time
the
South
Fork
has
no
known
inflow
of
municipal
wastewater
or
urban
runoff
and
no
reported
incidences
of
P.
parvum
blooms.
23
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Sampling
sites
for
this
study
(Figure
2.1)
in
the
NF
include,
in
downstream
order:
NF1
(known
as
Lake
1);
NF2
(Lake
6);
NF3
(at
the
head
of
Buffalo
Springs
Lake);
NF4
(immediately
downstream
of
tertiary‐treated
effluent
discharge;
intersection
of
FM
400
and
North
Fork);
and
NF5
(about
5
km
downstream
of
NF4;
intersection
of
CR
7300
and
North
Fork).
Sites
NF1
through
NF3
are
lentic
habitats
and
sites
NF4
and
NF5
represent
flowing
stream.
South
Fork
sites
included,
in
downstream
order:
SF1
(intersection
of
Highway
84
and
South
Fork);
SF2
(cove
in
the
middle
section
of
Lake
Alan
Henry;
Gobbler
Creek,
on
Road
3549);
and
SF3
(Lake
Alan
Henry
near
boat
ramp).
At
SF3
in
June
and
September
of
2008,
water
samples
were
collected
approximately
400
meters
east
of
the
marina’s
boat
ramp.
At
SF3
in
December
2008,
and
February
and
March
of
2009,
samples
were
collected
at
the
end
of
a
pier
located
at
the
boat
ramp.
Site
SF1
is
on
the
river
(water
at
this
site
is
typically
not
flowing
but
forming
pools,
except
during
and
for
some
time
after
rainfall
events),
whereas
sites
SF2
and
SF3
are
lentic
(lake)
habitat.
Samples
were
collected
at
all
North
Fork
locations
on
March
9,
2008
for
preliminary
toxicity
testing.
Two
samples
per
location
were
collected
in
precleaned
1‐
gallon
amber
glass
bottles.
At
each
site,
water
samples
were
collected
by
uncapping
the
sample
collection
bottles
and
letting
them
fill
slowly
by
immersion
just
below
the
water
surface,
while
being
careful
not
to
disturb
sediment
in
shallow
waters.
After
collection,
sampling
bottles
were
immediately
capped
and
stored
in
a
cooler
with
wet
ice.
Upon
returning
to
the
laboratory,
sampling
bottles
were
placed
in
a
walk‐in
refrigerator
at
4
°C.
In
situ
water
quality
parameters
were
also
determined
at
each
sampling
site
using
a
pre‐calibrated
YSI
556
multiparameter
meter.
Oxidation‐
reduction
potential
(ORP),
pH,
temperature,
conductivity,
salinity,
and
dissolved
oxygen
(DO)
were
measured.
In
addition,
a
pre‐calibrated
Oakton
T‐100
turbidimeter
(Oakton
Instruments,
Vernon
Hills,
IL)
was
used
to
determine
water
turbidity
on
site
in
subsamples
taken
from
each
sample
replicate.
Upon
returning
to
the
laboratory
at
Texas
Tech
University,
total
water
hardness
was
measured
in
subsamples
taken
from
24
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
each
sample
replicate
using
the
Hach
DR/890
colorimeter;
accuracy
of
the
method
was
monitored
by
use
of
standard
calcium
and
magnesium
hardness
solutions.
Within
a
few
hours
of
returning
to
the
laboratory,
water
samples
were
subsampled
for
use
in
the
zebrafish
embryo
toxicity
assay.
On
the
evening
of
the
sampling
day
and
every
evening
during
the
bioassay,
40
ml
of
water
from
each
sampling
bottle
(stored
at
4
°C)
were
placed
in
respective
250‐mL
beakers;
the
beakers
were
loosely
covered
with
aluminum
foil
and
transferred
to
the
incubator
for
at
least
12
hours
before
use
in
the
bioassay
for
temperature
equilibration
(following
the
start
of
the
incubation
in
the
morning
of
the
first
day,
water
was
replaced
in
the
morning
of
the
second
and
third
days).
Each
sample
replicate
was
used
(dispensed)
in
20
wells
of
a
single,
respective
plate,
and
the
remaining
4
wells
in
each
plate
received
reconstituted
water
(described
previously).
Thus,
two
plates
were
used
per
sampling
site.
Embryo
incubation
and
observations
were
as
already
described.
Subsequently,
water
samples
from
the
selected
sites
in
the
North
and
South
Forks
(Figure
2.1)
were
collected
on
June
2008,
September
2008,
December
2008,
February
2009
and
March
2009.
Procedures
for
water
collection,
water
quality
determination,
and
embryo
assays
were
as
already
described.
In
addition,
water
from
one
replicate
per
site
was
used
in
the
bioassay
with
or
without
3,3’‐
diaminodipropylamine
(DADPA;
1.772
M;
CAS
56‐18‐8;
Sigma‐Aldrich,
St.
Louis,
MO),
a
polyamine
known
to
enhance
the
potency
of
golden
alga
toxin
(Ulitzur
and
Shilo,
1964;
Southard
and
Fries,
1995)
at
a
3
mM
concentration.
Reconstituted
water
was
also
tested
in
the
presence
or
absence
of
DADPA.
Detailed
procedures
for
the
preparation
of
DADPA
stock
solution
for
use
in
these
tests
are
described
by
Southard
and
Fries
(1995).
CLS
water
dilution
test.
After
conducting
the
first
field
test
in
the
North
Fork
on
March
9,
2008
(see
above)
and
learning
of
golden
algal
bloom‐related
fish
kills
in
the
CLS
during
the
period
of
March
3‐17,
2008
(Texas
Parks
and
Wildlife,
2009),
water
from
NF2
was
again
collected
on
March
16,
2008
and
stored
frozen
(‐20
°C)
for
25
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
further
analysis
(NF2
was
selected
for
this
analysis
because
of
its
extremely
high
level
of
toxicity;
see
Results).
The
purpose
of
this
sampling
was
to
examine
the
influence
of
DADPA
on
water
toxicity
at
different
dilutions.
Several
weeks
later
(April
14,
2008),
this
water
sample
was
thawed
and
tested
for
embryotoxicity
in
a
series
of
dilutions
with
dechlorinated
tap
water
to
achieve
the
following
concentrations:
100
(undiluted),
50,
25,
12.5,
6.25,
3.125,
and
0
%.
Each
dilution
was
prepared
in
the
presence
or
absence
of
DADPA.
Each
treatment
solution
was
dispensed
into
respective
culture
plates
(n
=
24
embryos
per
treatment)
as
previously
described.
Two
additional
plates,
each
containing
12
wells
with
dechlorinated
tap
water
and
12
wells
with
reconstituted
water
(1
plate
with
and
1
plate
without
DADPA)
were
used
as
reference.
Embryotoxic
activity
at
tertiary‐treated
wastewater
discharge
site
(NF4).
After
conducting
the
seasonal
field
study
and
discovering
that
water
samples
from
sites
NF4
and
NF5
had
high
levels
of
toxicity
in
the
presence
of
DADPA
throughout
the
year
(see
Results),
a
study
was
designed
to
further
assess
if
wastewater
effluent
was
a
source
of
toxicity.
For
this
purpose,
two
water
samples
were
collected
on
July
9,
2009
from
a
location
64
meters
upstream
of
NF4,
and
two
samples
from
NF4
(immediately
downstream
of
discharge).
Procedures
for
water
collection,
water
quality
determination,
and
the
embryo
assay
were
as
described
previously.
Water
from
one
sample
replicate
per
location
was
also
used
in
the
presence
of
DADPA,
and
reconstituted
water
was
tested
in
the
presence
or
absence
of
DADPA.
Statistical
analysis.
All
statistical
analyses
were
conducted
in
program
R
(R
Foundation
for
Statistical
Computing,
Vienna,
Austria)
with
a
statistical
level
of
significance
of
α
=
0.05.
For
the
toxicity
assays,
embryos
were
categorized
as
either
dead
or
alive
at
72
hpf.
For
toxicity
tests
lacking
replication
(n
=
1
culture
plate
per
treatment),
such
as
the
salinity‐hardness
and
the
DADPA‐non
DADPA
contrasts,
observations
were
simply
used
for
gross
comparison
between
treatments.
26
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
The
response
variable,
percent
of
embryos
dead
at
72
hpf,
was
arcsine‐
transformed
prior
to
all
statistical
analysis.
One‐way
ANOVA
and
Tukey’s
Honestly
Significant
Difference
(HSD)
tests
were
used
to
determine
differences
in
embryo
survival
among
pH
treatments
for
the
validation
of
the
embryo
bioassay.
A
Student’s
t‐test
was
used
to
compare
differences
in
embryo
mortality
in
upstream
and
downstream
water
at
site
NF4.
Linear
mixed
effects
models
provide
a
flexible
framework
for
examining
repeated
measures
designs
(Pinheiro
and
Bates,
2000).
Therefore,
in
the
surface
water
toxicity
bioassays,
a
linear
mixed
effects
model
was
used
to
test
for
differences
in
mortality
(72
hpf)
among
sites
and
dates.
The
effects
of
date
and
the
interaction
of
site
and
date
were
considered
fixed
effects
factors
(there
were
not
enough
degrees
of
freedom
to
look
at
the
independent
effects
of
site).
Because
the
same
sites
were
measured
over
time,
intercepts
for
each
site
were
allowed
to
vary
randomly
(i.e.,
were
considered
random
effects).
In
addition,
separate
cross‐sectional
analyses
(one‐way
ANOVA
with
Tukey’s
HSD
post‐hoc
analysis)
were
used
to
compare
embryo
mortality
among
sampling
dates
at
each
sampling
site.
Principal
Component
Analysis
(PCA)
was
used
to
examine
geographic
or
temporal
patterns
of
water
quality
in
the
Double
Mountain
Fork
(i.e.,
water
hardness,
turbidity,
temperature,
pH,
conductivity,
salinity
and
ORP).
Eigenvalues
and
percent
variance
were
determined
for
each
component
to
judge
the
contribution
of
each
component
to
the
PCA,
and
factor
scores
were
used
to
examine
which
water
quality
parameters
were
most
prominent
in
each
component.
To
examine
the
association
between
water
quality
parameters
and
toxicity
in
the
bioassay,
two
regression
approaches
were
used.
Prior
to
analysis,
the
two
replicate
measures
of
mortality
at
each
site
and
date
were
averaged.
This
averaged
proportion
was
then
used
as
the
dependent
variable
in
regression
approaches
with
water
quality
measures
acting
as
independent
variables.
A
total
of
40
observations
(one
record
of
water
quality
parameters
per
date
per
site)
were
used.
In
the
first
27
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
approach,
a
backwards
elimination
multiple
regression
model
was
used
to
determine
the
suite
of
water
quality
parameters
that
were
significantly
related
to
mortality.
Akaike
Information
Criterion
(AIC)
was
used
to
eliminate
variables
from
the
model
(Venables
and
Ripley,
2002).
In
the
second
approach,
a
nonparametric
regression
(classification)
tree
(Therneau
and
Atkinson,
2008)
was
created
to
predict
mean
percent
embryo
mortality.
Results
Effect
of
water
hardness,
salinity
and
pH
on
embryo
survival.
Embryo
survival
was
unaffected
at
various
levels
of
water
hardness
and
salinity.
Zebrafish
embryo
survival
was
100%
for
all
hardness
treatments
(13.4‐1000
mg/L
of
calcium
carbonate
equivalents)
and
96‐100%
for
all
salinity
treatments
(310‐2000
mg/L)
(Figure
2.2).
Also,
no
gross
developmental
abnormalities
were
observed
and
there
were
no
differences
in
embryonic
developmental
stages
among
treatments.
Embryo
survival
at
pH
6,
7
and
8
was
100%,
and
at
pH
9
was
95%
(Figure
2.2).
Embryo
survival
at
pH
9
was
significantly
different
from
other
treatments
(one‐way
ANOVA
and
Tukey’s
HSD,
p
<
0.05).
Embryo
survival
was
97%
in
the
reconstituted
water
treatment
(pH
7.4).
No
gross
developmental
abnormalities
were
observed
and
there
were
no
differences
in
embryonic
developmental
stages
among
treatments.
Measurement
of
pH
before
and
after
exposure
confirmed
the
accuracy
and
stability
of
the
pH
of
experimental
solutions
during
the
exposures.
Spatial
and
temporal
patterns
of
surface
water
quality
in
the
Double
Mountain
Fork.
In
the
South
Fork,
salinity
and
conductivity
values
at
SF1
were
higher
than
at
other
sites
(on
either
the
South
or
North
Fork)
and
also
showed
an
exceptionally
strong
seasonal
pattern
with
up
to
a
10‐fold
difference
between
the
lowest
and
the
highest
values.
The
lowest
salinities
at
this
site
were
observed
in
the
fall
and
the
highest
value
in
summer
(range,
2.6‐22.8
mg/L;
see
Appendix
A.1).
A
clear
seasonal
pattern
was
also
observed
for
hardness
at
SF1,
although
the
28
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
magnitude
of
the
change
was
much
reduced
compared
to
salinity,
and
the
actual
values
(range,
484‐1025
mg/L
in
calcium
carbonate
equivalents;
Appendix
A.1)
were
comparable
to
those
observed
in
the
North
Fork
(but
higher
than
those
in
SF2
and
SF3,
see
below).
Except
during
periods
of
rainfall,
water
flow
in
SF1
was
minimal
and
the
aquatic
habitat
was
often
fragmented
into
pools.
Salt
residue
was
often
visible
on
the
riverbed
above
the
water
line.
Because
the
basic
physical
and
chemical
traits
(and
toxicity;
see
below)
of
SF1
habitat
are
markedly
different
than
those
of
the
other
sites
of
this
study
irrespective
of
geographic
(fork)
association
and
season,
water
quality
data
from
this
site
were
excluded
from
the
present
general
analysis
of
patterns.
Dissolved
oxygen
concentrations
were
abnormally
high
especially
at
sites
NF4
and
NF5.
These
two
sites
have
fast
flowing
water,
which
makes
measurements
with
the
multiparameter
probe
unstable
and
difficult
to
determine.
Measured
concentrations
at
these
sites
commonly
ranged
between
15
and
30
mg/L,
values
that
are
far
above
saturation
levels
for
freshwater
within
the
temperature
range
measured
in
this
study.
Thus,
dissolved
oxygen
data
were
also
removed
from
the
present
analysis.
Principal
component
analysis
of
measured
water
quality
parameters
at
all
samples
sites
(except
SF1)
and
dates
indicated
that
approximately
67%
of
the
variability
in
water
quality
was
accounted
for
by
the
first
two
components,
both
with
eigenvalues
>
1
(Table
2.1).
Salinity,
conductivity
and
hardness
(factor
loadings
≥
|0.40|)
were
the
major
contributing
factors
in
component
one;
whereas
turbidity
and
temperature
(factor
loadings
≥
|0.40|)
were
the
major
contributing
factors
in
component
two.
Ninety‐five
percent
confidence
ellipses
for
water
quality
data
grouped
by
fork
showed
a
remarkably
clear
separation
between
the
North
and
South
Fork
along
the
salinity,
conductivity,
and
hardness
vectors
on
the
PCA
biplot
(Figure
2.3).
In
fact,
salinity
(g/L,
mean
±
SE)
combined
over
all
sampling
sites
and
dates
in
the
North
Fork
29
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
was
1.2
±
0.1
and
in
the
South
Fork
(excluding
SF1)
was
0.54
±
0.1;
conductivity
(μЅ/cm,
mean
±
SE)
in
the
North
Fork
was
2228
±
137
and
in
the
South
Fork
was
1169
±
22;
and
total
hardness
(mg/L,
mean
±
SE)
in
the
North
Fork
was
552.5
±
34.4
and
in
the
South
Fork
was
165.5
±
5.9.
In
addition,
confidence
ellipses
for
data
grouped
by
date
seemed
to
separate
most
clearly
along
the
temperature
vector
on
the
PCA
biplot,
and
to
a
lesser
extent
along
the
pH
vector
(Figure
2.4).
Water
temperatures
(°C,
mean
±
SE)
combined
over
all
sampling
sites
at
each
sampling
date
varied
as
expected
according
to
seasonal
climatic
fluctuations:
March
2008,
10.4
±
1.6;
June
2008,
25.4
±
0.4;
September
2008,
21.3
±
0.6;
December
2008,
7.7
±
1.4;
February
2009,
8.6
±
0.9;
and
March
2009,
10.1
±
1.0.
Water
pH
(mean
±
SE)
combined
over
all
sampling
sites
was
6.8
±
0.1
for
March
2008,
7.5
±
0.2
for
June
2008,
7.7
±
0.2
for
September
2008,
7.2
±
0.2
for
December
2008,
6.9
±
0.2
for
February
2009,
and
7.0
±
0.2
for
March
2009.
Spatial
and
temporal
patterns
of
surface
water
toxicity
in
the
Double
Mountain
Fork.
Overall
water
toxicity
(either
in
the
absence
or
presence
of
DADPA;
see
below)
was
generally
higher
for
North
Fork
sites
than
South
Fork
sites
(except
SF1;
Figure
2.5).
In
the
North
Fork,
water
toxicity
was
very
high
in
the
CLS
(NF1‐NF3)
in
March
2008
(Figure
2.5)
(one‐way
ANOVA
and
Tukey’s
HSD,
p
<
0.05),
coinciding
with
reports
of
golden
alga‐related
fish
kills
in
various
locations
within
the
CLS
from
early
to
mid‐March
2008
(Texas
Parks
and
Wildlife,
2009).
At
NF4,
water
toxicity
in
March
2008
and
February
2009
seemed
to
be
slightly
elevated
compared
to
other
dates
(p
<
0.05).
At
NF5,
there
were
no
significant
differences
in
water
toxicity
among
sampling
dates
(one‐way
ANOVA,
p
>
0.05).
In
the
South
Fork,
exposure
to
SF1
water
in
June
2008
and
March
2009,
when
salinity
was
at
the
highest
recorded
values
(22.8
and
15.1
g/L,
respectively),
yielded
100%
embryo
mortality
(Figure
2.5).
The
toxicity
of
SF1
water
was
low
at
other
times
of
the
year
(Figure
2.5).
Water
toxicity
was
generally
low
throughout
the
year
at
SF2
and
SF3
but
some
seasonal
changes
were
measurable.
At
SF2,
mortality
during
30
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
February
2009
was
significantly
higher
than
during
June
2008
or
December
2008
(one‐way
ANOVA
and
Tukey’s
HSD,
p
<
0.05).
At
SF3,
mortality
during
February
2009
was
significantly
higher
than
during
all
other
dates
(one‐way
ANOVA
and
Tukey’s
HSD,
p
<
0.05).
For
the
comparative
purpose
of
this
study,
toxicity
assessments
for
SF1
water
are
questionable
because
salinities
at
this
site
fell
outside
the
range
validated
for
the
zebrafish
embryo
assay.
With
few
exceptions
(notably
at
times
of
the
year
other
than
winter),
the
presence
of
the
polyamine,
DADPA,
tended
to
increase
water
toxicity
in
samples
collected
from
the
CLS
(NF1‐NF3)
(Figure
2.5).
At
NF4
and
NF5,
water
in
the
presence
of
DADPA
yielded
very
high
levels
of
toxicity
(100%
embryo
mortality)
throughout
the
sampling
period
of
this
study
regardless
of
the
level
of
toxicity
observed
in
the
absence
of
DADPA
(Figure
2.5;
note
that
there
was
no
DADPA
treatment
with
the
March
2008
samples
collected
from
these
sites).
NF2
water
collected
in
March
2008,
during
a
toxic
bloom
of
golden
alga,
lost
its
toxicity
more
readily
when
diluted
in
plain
dilution
(dechlorinated
tap)
water
than
in
dilution
water
containing
DADPA
(Figure
2.6).
Namely,
in
the
absence
of
DADPA,
NF2
water
was
no
longer
toxic
at
a
dilution
level
of
25%;
whereas
in
the
presence
of
DADPA,
fully
lethal
embryotoxicity
was
still
evident
at
a
dilution
of
6.25%
and
considerable
toxicity
(>
60%)
remained
even
after
dilution
to
3.125%
(Figure
2.6).
No
gross
developmental
abnormalities
were
observed
and
there
were
no
changes
in
embryonic
developmental
stage
among
the
different
treatment
conditions.
The
presence
of
DADPA
did
not
seem
to
affect
the
toxicity
of
South
Fork
water
except
for
the
sample
collected
from
SF1
in
December
2008
(Fig.
2.5).
In
the
follow‐up
test
using
NF4
and
upstream
samples
collected
in
July
2009,
DADPA‐treated
NF4
water
once
again
caused
100%
embryo
mortality
but
DADPA‐
treated
upstream
water
caused
<
50%
embryo
mortality
(Figure
2.7).
In
the
absence
of
DADPA,
the
toxicity
of
water
was
also
lower
upstream
than
at
NF4
(Figure
2.7;
31
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Student’s
t‐test,
p
<
0.05).
No
gross
developmental
abnormalities
were
observed
and
there
were
no
changes
in
embryonic
developmental
stage
among
treatments.
DADPA
added
to
dechlorinated
tap
water
or
reconstituted
water
had
no
effect
on
zebrafish
embryos.
General
associations
between
water
quality
and
toxicity.
For
reasons
already
noted,
water
quality
and
toxicity
data
for
SF1
and
dissolved
oxygen
values
for
all
sites
were
excluded
from
the
regression
analyses.
The
regression
tree
model
suggested
that,
among
the
water
quality
variables
examined
in
this
study,
hardness
plays
the
most
important
role
in
associating
water
quality
with
toxicity
in
the
bioassays.
According
to
the
model,
if
surface
water
hardness
is
greater
712.5
mg/L,
32.8%
of
a
test
population
of
embryos
would
be
expected
to
die
in
the
bioassay
(Figure
2.8).
However,
if
hardness
is
lower
than
712.5
mg/L,
pH
became
the
next
most
important
water
quality
parameter
although
its
predicted
levels
of
mortality
were
lower
than
for
water
hardness
(Figure
2.8).
The
relationship
between
water
toxicity
and
pH
was
negative.
The
backwards
elimination
multiple
regression
model
with
the
lowest
AIC
value
suggested
that
water
temperature,
hardness
and
ORP
played
the
most
important
roles
in
associating
water
quality
with
toxicity
in
the
bioassays
(Table
2.2).
ORP
had
the
strongest
association
with
a
standardized
partial
regression
coefficient
of
‐6.00
x
10‐1,
followed
by
hardness
(4.08
x
10‐1)
and
temperature
(‐3.12
x
10‐1).
Discussion
Protocols
for
the
use
of
fish
embryos
in
toxicity
testing
involve
the
addition
of
test
materials
to
(reconstituted)
water
of
a
defined
chemical
composition
(OECD,
2006;
Scholz
et
al.,
2008).
Although
the
zebrafish
embryo
is
also
being
used
by
some
to
examine
the
toxicity
of
more
complex
mixtures,
such
as
wastewater
(Scholz
et
al.,
2008),
its
application
to
field
studies
of
water
toxicity
requires
an
assessment
of
the
performance
of
the
model
under
nonspecific
physicochemical
conditions
that
are
32
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
likely
to
differ
among
aquatic
habitats.
The
results
of
this
study
showed
that,
within
the
range
found
in
most
freshwater
aquatic
habitats,
different
levels
of
hardness
(13.4‐1000
mg/L),
salinity
(310‐2000
mg/L)
and
pH
(6‐9)
had
little
or
no
direct
effect
on
embryo
viability.
Percent
embryo
survival
at
pH
9
was
statistically
different
(5%
lower;
p
<
0.05)
from
survival
at
pH
6‐8,
but
this
difference
is
so
small
(representing
only
1
dead
embryo
of
20
embryos
per
replicate
compared
to
no
deaths
in
the
other
treatments)
that
it
is
unlikely
to
be
biologically
relevant.
Thus,
the
tolerance
of
the
zebrafish
embryo
to
changes
in
basic
water
quality
suggests
that
it
can
be
used
as
model
for
field
studies
of
water
toxicity
even
if
the
condition
of
these
traits
varies
among
habitats.
However,
when
interpreting
the
results
of
any
bioassay
using
field
samples,
it
is
important
to
recognize
that
differences
in
certain
physicochemical
conditions
of
water
can
influence
the
potency
of
toxicants.
One
well‐known
example
in
teleosts
is
the
modulation
by
hardness
of
the
toxicity
of
certain
heavy
metals
(Sorensen,
1991).
Water
quality
conditions
in
the
Double
Mountain
Fork
varied
both
spatially
and
seasonally.
Principal
component
analysis
indicated
that
total
water
hardness
(expressed
as
content
of
calcium
carbonate
equivalents),
conductivity
and
salinity
(component
1);
and
turbidity
and
temperature
(component
2)
best
explained
the
variation
in
water
quality.
The
factor
loading
value
was
also
close
to
the
selected
cutoff
of
|0.40|
for
pH
in
component
1
and
for
total
water
hardness
in
component
2.
Biplots
of
components
1
and
2
showed
a
clear
spatial
separation
of
water
quality
data
along
gradients
of
total
water
hardness,
conductivity
and
salinity
between
the
North
(higher
values)
and
South
Fork
(lower
values).
This
observation
is
consistent
with
the
knowledge
that
the
source
of
North
Fork
water
is
primarily
urban
runoff
and
wastewater
effluent
(Smith
et
al.,
1979;
City
of
Lubbock
Office
of
Water
Utilities,
2007),
which
typically
contain
relatively
high
levels
of
total
dissolved
solids
(Kszos,
1990;
Meybeck,
1998;
Skinner
et
al.,
1999;
Brannon
Andersen
et
al.,
2004;
Vaze
et
al.,
2004;
Kayhanian
et
al.,
2007;
Lewis
et
al.,
2007)
including
cations
of
hardness
(Lewis
33
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
et
al.
2007).
In
fact,
mean
water
hardness
in
the
North
Fork
was
over
three
times
higher
than
the
South
Fork,
and
both
mean
conductivity
and
salinity
(which
are
related
to
each
other)
were
approximately
twice
higher
in
the
North
Fork
(these
comparisons
do
not
include
data
from
SF1).
However,
other
hydrological
and
geological
factors
cannot
be
excluded
as
contributors
to
differences
in
the
dissolved
solid
content
between
the
two
forks.
An
assessment
of
these
factors
is
beyond
the
scope
of
the
present
study.
Data
grouped
by
date
in
the
biplots
indicated
a
temporal
(seasonal)
separation
of
water
quality
along
the
temperature
and
pH
vectors.
This
observation
with
temperature
is
consistent
with
the
normal
seasonal
changes
in
air
and
water
temperatures.
In
the
present
study,
the
coldest
overall
water
temperatures
in
the
Double
Mountain
Fork
were
recorded
in
December
(average
<
8
°C)
and
the
highest
temperatures
in
June
(average
>
25
°C).
The
nature
of
the
association
between
temperature
and
turbidity
suggested
by
component
2
of
the
PCA
is
uncertain.
Water
pH
in
the
Double
Mountain
Fork
also
showed
a
seasonal
pattern
with
lower
mean
values
in
winter
and
higher
values
in
summer.
The
zebrafish
embryotoxic
activity
of
surface
water
from
the
Double
Mountain
Fork
also
varied
spatially
and
seasonally.
Namely,
water
samples
taken
from
the
North
Fork
generally
had
higher
toxicity
compared
to
the
South
Fork
(except
SF1,
see
later
discussion);
and,
in
the
North
Fork,
samples
collected
in
the
winter/early
spring
(especially
in
2008)
were
also
generally
more
toxic
than
at
other
times
of
the
year.
Several
different
lines
of
evidence
indicate
that
at
least
a
portion
of
this
toxicity,
if
not
the
majority,
is
related
to
the
presence
of
golden
alga
toxin.
The
strongest
evidence
is
perhaps
the
seasonality
of
water
toxicity
in
the
North
Fork.
The
highest
levels
of
toxicity
in
the
bioassay
were
recorded
in
samples
from
the
CLS
(sites
NF1
through
NF3)
serendipitously
collected
in
March
2008,
during
the
course
of
a
documented
golden
algal
bloom
that
resulted
in
many
fish
deaths
in
the
lake
system
(Texas
Parks
and
Wildlife,
2009).
In
addition,
the
AIC‐based
multiple
regression
model
34
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
indicated
a
general
negative
association
at
the
landscape
level
between
field
water
temperatures
and
toxicity
levels
in
the
bioassay.
Thus,
seasonally
colder
water
temperatures
in
the
field
tend
to
yield
greater
levels
of
toxicity
in
the
zebrafish
embryo
bioassay
(note
that
the
bioassay
is
conducted
at
a
constant
temperature
in
the
laboratory).
In
fact,
water
temperatures
in
the
CLS
during
the
March
2008
golden
algal
bloom
(Texas
Parks
and
Wildlife,
2009)
were
<
10
°C
(close
to
7
°C
in
NF2
and
NF3).
Although
the
prevalence
of
toxic
golden
algal
blooms
during
the
coldest
months
of
the
year
is
well
documented
for
Texas
surface
waters
(Sager
et
al.,
2008),
the
ecophysiological
mechanism
for
these
winter
blooms
is
unknown
(Baker
et
al.,
2007).
To
our
knowledge,
no
other
toxic
algal
blooms
are
known
to
occur
in
Texas
inland
waters
during
winter.
The
potentiating
effect
of
DADPA
on
the
toxicity
of
water
samples,
especially
samples
collected
from
the
North
Fork
where
golden
alga
is
known
to
reside
and
bloom
(see
preceding
discussion),
also
supports
the
conclusion
that
at
least
a
fraction
of
the
water
toxicity
measured
in
this
study
is
due
to
the
presence
of
golden
alga
toxin.
DADPA
and
a
number
of
other
polyamines
have
been
shown
to
directly
enhance
the
ichthyotoxic
potency
of
golden
alga
toxin
(Ulitzur
and
Shilo,
1964,
1966;
Southard
and
Fries,
1995),
and
DADPA
is
currently
used
in
(posthatch)
fish
bioassays
for
golden
alga
toxin
activity
(Southard
and
Fries,
1995).
Although
polyamines
may
also
activate
toxins
of
other
algal
species
related
to
golden
alga
(Collins,
1978;
Edvardsen
and
Imai,
2006;
Johnsen
et
al.,
1999;
Legrand
et
al.,
2000),
toxins
from
unrelated
algal
and
plant
species
seem
to
be
unaffected
by
the
addition
of
these
substances
(Yariv
and
Hestrin,
1961;
Hwang
et
al.,
2003).
Overall,
the
apparent
specificity
of
the
potentiating
effect
DADPA
for
toxins
of
golden
alga
and
related
species
further
supports
the
conclusion
that
the
water
toxicity
measured
in
the
present
study
is
at
least
partly
due
to
the
presence
of
golden
alga
toxin
–
especially
given
the
unique
seasonal
niche
of
toxic
golden
algal
blooms
in
Texas
(see
preceding
discussion).
35
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
The
results
of
both
approaches
to
multiple
regression
used
in
this
study
indicated
that
surface
water
toxicity
in
the
Double
Mountain
Fork
is
positively
associated
with
water
hardness;
however,
no
relationship
was
observed
between
water
toxicity
and
salinity
in
either
analysis.
These
observations
can
also
be
interpreted
in
the
context
of
current
knowledge
of
the
mechanisms
of
action
of
golden
alga
toxin.
Namely,
divalent
cations
that
are
responsible
for
water
hardness
(Ca
and
Mg),
but
not
monovalent
cations
that
contribute
primarily
to
water
salinity
(Na
and
K),
serve
as
cofactors
for
golden
alga
toxin
activity
(Yariv
and
Hestrin,
1961;
Edvardsen
and
Imai,
2006).
In
fact,
although
P.
parvum
grows
best
at
salinities
>
0.8
g/L
(Edvardsen
and
Imai,
2006),
addition
of
NaCl
at
a
concentration
of
3
g/L
(in
tap
water
of
undetermined
salinity)
suppressed
the
activity
of
golden
alga
toxin
in
a
fish
bioassay
(Ulitzur
and
Shilo,
1964).
These
observations
suggest
the
existence
of
a
complex
interaction
between
salinity
and
golden
alga
growth
and
ichthyotoxicity.
However,
the
role
of
divalent
cations
of
hardness
in
promoting
or
activating
golden
alga
toxin
seems
clear.
Thus,
the
results
of
this
study
are
consistent
with
a
scenario
where
higher
water
hardness
levels
in
the
North
Fork
provide
the
appropriate
conditions
for
the
activation
of
golden
alga
toxin.
Previous
laboratory
studies
have
shown
a
positive
relationship
between
experimentally
manipulated
pH
and
toxicity
of
field
water
samples
or
algal
culture
media
containing
(McLaughlin,
1958;
Ulitzur
and
Shilo,
1964,
1966;
Shilo
and
Sarig,
1989;
Valenti
et
al.,
in
press);
namely,
reducing
or
increasing
the
pH
of
field
water
samples
or
culture
media
reduces
or
increases
their
toxicity
levels,
respectively.
These
observations
provided
useful
insights
to
understand
the
mechanism
of
golden
alga
toxin
(Valenti
et
al.,
in
press)
and
also
led
to
the
suggestion
that
variability
in
pH
among
aquatic
habitats
may
account
for
variability
in
golden
alga
toxicity
and
incidence
of
fish
kills
at
the
landscape
level
(Sager
et
al.,
2008;
Valenti
et
al.,
in
press).
However,
depending
on
watershed
geochemistry
and
hydrology,
differences
in
pH
among
aquatic
habitats
may
be
also
accompanied
by
differences
in
other
36
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
physicochemical
traits
of
water
that
could
affect
the
production
or
activity
of
golden
alga
toxin.
In
the
present
study,
the
results
of
the
regression
tree
analysis
suggested
that
after
hardness,
the
next
best
predictor
of
water
toxicity
in
samples
collected
from
the
Double
Mountain
Fork
was
pH
lower
than
7.4.
In
fact,
water
pH
in
the
Double
Mountain
Fork
showed
a
seasonal
trend,
with
lower
values
in
winter
and
higher
values
in
summer.
Moreover,
and
more
importantly,
pH
values
ranged
from
6.4
to
7.3
in
the
CLS
during
the
March
2008
toxic
bloom
of
P.
parvum
(Appendix
A.1).
These
pH
values
are
significantly
lower
than
those
reported
during
toxic
blooms
of
golden
alga
elsewhere
in
Texas
(e.g.,
≥
8.2;
Valenti
et
al.,
in
press).
Thus,
at
the
landscape
level,
variability
in
pH
among
aquatic
habitats
may
not
be
a
reliable
indicator
of
their
potential
to
support
the
development
of
toxic
P.
parvum
blooms.
The
multiple
regression
model
also
indicated
that
ORP
is
negatively
associated
with
surface
water
toxicity.
However,
a
specific
mechanism
for
this
a
relationship
is
unknown,
and
there
is
little
information
in
the
literature
to
suggest
that
such
a
relationship
is
important.
Inspection
of
a
simple
linear
regression
using
ORP
as
a
predictor
of
mortality
in
the
bioassay
indicates
that
much
of
the
relationship
within
these
data
is
driven
by
one
point
(data
not
shown).
Further
work
needs
to
be
done
to
validate,
or
potentially
rule
out,
the
potential
influence
of
ORP
on
water
toxicity
in
the
Double
Mountain
Fork.
Water
collected
from
NF4
and
NF5
had
relatively
low
levels
of
toxicity
throughout
the
year.
However,
while
NF4
samples
collected
in
July
2009
also
showed
a
relatively
low
level
of
toxicity
(average
embryo
mortality,
30%),
this
toxicity
was
significantly
higher
than
that
observed
in
samples
collected
upstream,
beyond
the
influence
of
the
wastewater
stream
(10%).
This
observation
indicates
that
the
wastewater
effluent
contains
a
higher
content
of
toxic
factors
than
the
upstream
flow.
Moreover,
in
the
presence
of
DADPA,
all
samples
collected
from
NF4
(including
July
2009)
and
NF5
consistently
caused
100%
embryo
mortality
in
the
bioassay
regardless
of
date
of
collection;
whereas
embryo
mortality
caused
by
the
July
2009
37
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
sample
collected
upstream
of
NF4
was
<
50%.
Overall,
these
observations
are
consistent
with
a
scenario
where
municipal
tertiary‐treated
effluent
being
released
into
the
North
Fork
contains
a
chronic
low
level
of
golden
alga
toxin‐like
activity
year‐
round.
However,
wastewater
effluents
are
complex
mixtures
and
identification
of
the
DADPA‐enhanced
toxicity
will
require
further
study.
The
SF1
site
on
the
South
Fork
showed
strong
seasonal
patterns
of
salinity
with
the
highest
values
in
June
and
lowest
in
the
fall.
Increased
salinity
in
the
upper
Brazos
River
is
observed
as
water
in
isolated
streambed
pools
evaporates
(Ostrand
and
Wilde,
2004).
All
salinity
values
measured
at
this
site
exceeded
the
range
used
to
validate
the
bioassay
and
also
reached
levels
previously
reported
to
be
lethal
to
zebrafish
embryos
(Sawant
et
al.,
2001).
The
high
level
of
toxicity
measured
in
June
2008
and
March
2009
for
SF1
water
was
likely
due
to
the
lethal
effects
of
high
salinity.
Thus,
not
only
was
SF1
an
“outlier”
in
regards
to
water
chemistry
but
the
toxicity
assay
used
was
inappropriate
for
this
site.
In
conclusion,
this
study
found
that
varying
hardness,
salinity
and
pH
(within
tested
concentrations/levels)
have
no
effect
on
embryo
survival.
Therefore,
the
zebrafish
embryo
toxicity
assay
is
a
useful
new
tool
for
studies
of
surface
water
toxicity.
Also,
the
zebrafish
embryo
toxicity
assay
has
successfully
been
used
to
characterize
seasonal
and
spatial
patterns
in
surface
water
toxicity
in
the
upper
Brazos
River.
North
Fork
water
was
generally
more
toxic
than
South
Fork
water,
especially
in
winter
months
when
golden
algal
blooms
typically
occur.
This
study
also
concluded
that
the
toxicity
of
North
Fork
water
was
due
to
golden
alga
toxin
and
that
hardness,
temperature
and
perhaps
ORP
may
influence
this
water
toxicity.
Golden
algal
toxin
may
be
a
major
contributor
of
Brazos
River
water
toxicity
and
tertiary‐
treated
wastewater
effluent
from
Lubbock’s
municipal
wastewater
treatment
facility
may
be
supplying
chronic
low
levels
of
golden
alga‐like
toxin
to
the
North
Fork.
Lastly,
this
study
is
the
first
known
to
report
lethality
of
golden
algal
toxin
to
an
embryo,
a
non‐gilled
organism.
38
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Table
2.1.
Factor
loading
matrix
for
the
first
two
components
of
principal
component
analysis
of
water
quality
variables
(except
dissolved
oxygen)
for
all
sampling
sites
and
dates
(excluding
SF‐1).
Variable
Hardness
Turbidity
Temperature
pH
Conductivity
Salinity
ORP
Component
1
2
‐0.44
0.39
0.05
0.74
0.31
0.44
0.37
0.23
‐0.51
0.15
‐0.51
0.09
‐0.23
‐0.16
Eigenvalue
3.41
1.25
%
Variance
48.71
17.84
Cumulative
%
Variance
48.71
66.55
Note:
factors
with
values
|0.40|
are
bolded
39
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Table
2.2.
Regression
model
for
predicting
embryo
mortality
based
on
water
quality
parameters.
Backwards
elimination
multiple
regression
was
used
to
eliminate
variables
based
on
AIC.
βi
represents
the
standardized
partial
regression
coefficient.
Variable
βi 95%
CI
‐1
Hardness
4.08
x
10 0.16
to
0.66
Temperature
‐3.12
x
10‐1
‐0.57
to
‐0.06
ORP
‐6.00
x
10‐1
‐0.85
to
‐0.35
40
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.1.
Study
sites
in
the
Double
Mountain
Fork
of
the
Brazos
River.
Five
sites
were
sampled
in
the
North
Fork,
three
within
the
Canyon
Lakes
System
(NF‐1
through
NF‐3)
and
two
just
downstream
of
this
system
(NF‐4
and
NF‐5).
In
the
South
Fork,
three
sites
were
chosen,
one
upstream
of
Lake
Alan
Henry
(SF‐1),
one
on
its
middle
section
(SF‐2),
and
the
third
near
further
downstream
near
the
boat
launch
(SF‐3).
Map
source:
nationalatlas.gov;
Lake
Alan
Henry
was
digitally
superimposed
and
its
size
is
not
according
to
scale.
41
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.2.
Percent
zebrafish
embryo
survival
at
different
concentrations
of
water
hardness
and
salinity
(top)
and
values
of
pH
(bottom).
Hardness/salinity
bars
represent
percent
survival
of
one
replicate
and
pH
bars
represent
the
mean
of
two
replicates
(±
SE).
Each
replicate
represents
one
plate
containing
20
embryos.
Bars
with
common
letters
are
not
significantly
different.
42
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.3.
Biplot
of
principal
components
1
and
2.
Data
within
the
biplot
bear
numbers
that
represent
specific
sampling
locations
(1‐5,
NF1‐NF5;
7‐8,
SF2‐SF3).
Ninety‐five
percent
confidence
ellipses
are
centered
on
data
for
the
North
(NF)
and
South
(SF)
Forks.
The
vectors
of
hardness,
salinity
and
conductivity
seem
to
best
separate
the
ellipses.
43
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.4.
Biplot
of
principal
components
1
and
2.
Data
within
the
biplot
bear
numbers
that
represent
specific
sampling
dates
(1,
March
2008;
4,
June
2008;
7,
September
2008;
10,
December
2008;
12,
February
2009;
13,
March
2009).
Ninety‐
five
percent
confidence
ellipses
are
centered
on
each
sampling
date.
The
vector
of
temperature
seems
to
best
separate
the
ellipses
although
pH
also
seemed
to
follow
the
separation
axis.
44
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.5.
Percent
zebrafish
embryo
mortality
exposed
to
surface
water
collected
from
the
study
sites.
Black
bars
(plain
surface
water)
represent
the
mean
of
two
replicates
(±
SE)
and
white
bars
(surface
water
+
DADPA)
represent
the
value
of
one
replicate.
White
bars
are
absent
for
March
2008
because
DADPA‐treated
surface
water
was
not
used
at
this
date;
and
March
2008
is
absent
from
the
South
Fork
column
of
graphs
because
water
was
not
collected
at
this
date.
For
plain
surface
water,
bars
with
common
letter
are
not
significantly
different
(p
<
0.05).
45
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.6.
Percent
zebrafish
embryo
mortality
in
NF‐2
water
diluted
in
the
presence
or
absence
of
DADPA.
Dilution
water
was
dechlorinated
tap
water.
One
replicate
(plate
of
24
embryos)
per
treatment
was
used
in
this
experiment.
46
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.7.
Percent
zebrafish
embryo
mortality
in
NF‐4
water
(downstream)
and
water
collected
64
m
upstream
of
NF4.
Bars
represent
mean
percent
embryo
mortality
(±
SE,
n
=
2)
for
the
surface
water
treatment
(n
=
2)
and
the
value
of
a
single
replicate
for
the
DADPA
treatment.
Water
was
collected
on
July
9,
2009.
The
different
letters
on
the
surface
water
bars
indicate
a
significant
difference
(P
<
0.05).
47
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Figure
2.8.
Regression
tree
for
predicting
embryo
mortality
based
on
water
quality
parameters.
Hardness
(mg/L
in
calcium
carbonate
equivalents)
is
the
first
splitting
variable,
followed
by
pH.
Numbers
(e.g.,
0.328)
directly
below
each
leaf
(i.e.,
grouping)
show
the
predicted
mean
proportion
of
embryo
mortality.
The
sample
size
associated
with
each
grouping
(e.g.,
n
=
8)
also
is
shown.
48
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
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Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
APPENDIX
A
MEASUREMENTS
OF
WATER
QUALITY
Table
A.1.
Measures
of
water
quality.
55
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Table
A.1. Continued
56
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
APPENDIX
B
RESULTS
OF
SURFACE
WATER
TREATMENTS
(WITHOUT
DADPA)
Table
B.1.
Results
of
surface
water
treatments
(without
DADPA).
57
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Table
B.1.
Continued
58
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Table
B.1.
Continued
59
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
APPENDIX
C
RESULTS
OF
SURFACE
WATER
TREATMENTS
(WITH
DADPA)
Table
C.1.
Results
of
surface
water
treatments
(with
DADPA).
60
Texas
Tech
University,
Matthew
D.
Meyer,
December
2009
Table
C.1.
Continued
61