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UC Davis
San Francisco Estuary and Watershed Science
Title
Disease in Central Valley Salmon: Status and Lessons from Other Systems
Permalink
https://escholarship.org/uc/item/8259p3t6
Journal
San Francisco Estuary and Watershed Science, 18(3)
ISSN
1546-2366
Authors
Lehman, Brendan M.
Johnson, Rachel C.
Adkison, Mark
et al.
Publication Date
2020
DOI
https://doi.org/10.15447//sfews.2020v18iss3art2
License
https://creativecommons.org/licenses/by/4.0/ 4.0
Peer reviewed
eScholarship.org Powered by the California Digital Library
University of California
1
Sponsored by the Delta Science Program and the UC Davis Muir Institute
ABSTRACT
Chinook Salmon (
Oncorhynchus tshawytscha
)
are increasingly vulnerable to anthropogenic
activities and climate change, especially at
their most southern range in California’s
Central Valley. There is considerable
interest in understanding stressors that
contribute to population decline and in
identifying management actions that
reduce the effects of those stressors. Along
the west coast of North America, disease
has been linked to declining numbers of
salmonids, and identified as a key stressor
that results in mortality. In the Central
Valley, targeted studies have revealed
extremely high prevalence of infectious
agents and disease. However, there has been
insufficient monitoring to understand the
effect that disease may have on salmon
populations. To inform future research,
monitoring, and management efforts, a
two-day workshop on salmon disease was
POLICY & PROGRAM ANALYSIS
Disease in Central Valley Salmon:
Status and Lessons from Other Systems
Brendan M. Lehman,*1,2 Rachel C. Johnson,2,3 Mark Adkison,4 Oliver T. Burgess,5 Richard E. Connon,6 Nann A. Fangue,7
J. Scott Foott,8 Sascha L. Hallett,9 Beatriz Martínez–López,10 Kristina M. Miller,12 Maureen K. Purcell,13 Nicholas A. Som,14,15
Pablo Valdes Donoso,11 Alison L. Collins16
SFEWS Volume 18 | Issue 3 | Article 2
https://doi.org/10.15447//sfews.2020v18iss3art2
* Corresponding author:
brendan.lehman@noaa.gov
1 Physical and Biological Sciences, Univ. of California,
Santa Cruz, Santa Cruz, CA 95060 USA
2 Southwest Fisheries Science Center, NMFS / NOAA
Santa Cruz, CA 95060 USA
3 Center for Watershed Sciences, Univ. of California,
Davis Davis, CA 95616 USA
4 Fish Health Lab, California Dept. of Fish and Game
Rancho Cordova, CA 95670, USA
5 Bay-Delta Office, US Bureau of Reclamation
Sacramento, CA 95814 USA
6 School of Veterinary Medicine, Univ. of California,
Davis Davis, CA 95616, USA
7 Department of Wildlife, Fish, and Conservation
Biology, University of California, Davis
Davis, CA 95616 USA
8 California–Nevada Fish Health Center, US Fish and
Wildlife Service, Anderson, CA 96007 USA
9 Department of Microbiology, Oregon State University
Corvallis, Oregon 97331-3804, USA
10 Center for Animal Disease Modeling and Surveillance,
Dept. of Medicine and Epidemiology,
School of Veterinary Medicine, Univ. of California, Davis
Davis, California 95616, USA
11 University of California Agricultural Issues Center
Davis, California 95616, USA
12 Pacific Biological Station, Fisheries and Oceans Canada
Nanaimo, British Columbia, V9T 6N7, Canada
13 Western Fisheries Research Center, US Geological Survey
Seattle, WA 98115 USA
14 US Fish and Wildlife Service
Arcata, California 95521 USA
15 Dept. of Fisheries Biology, Humboldt State University
Arcata, CA 95519 USA
16 The Metropolitan Water District of Southern California
Sacramento, CA 95814 USA
SAN FRA NCISCO ESTUARY & WATE RSHE D SCIEN CE
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VOLUME 18, ISSUE 3, ARTICLE 2
held at the University of California, Davis
(UC Davis) on March 14-15, 2018. This paper
summarizes the science presented at this
workshop, including the current state of
knowledge of salmonid disease in the Central
Valley, and current and emerging tools to
better understand its effects on salmon. We
highlight case studies from other systems
where successful monitoring programs have
been implemented. First, in the Klamath
River where the integration of several data-
collection and modeling approaches led to
the development of successful management
actions, and second in British Columbia
where investment in researching novel
technologies led to breakthroughs in the
understanding of salmon disease dynamics.
Finally, we identify key information and
knowledge gaps necessary to guide research
and management of disease in Central Valley
salmon populations.
KEY WORDS
pathogen, infectious disease,
Ceratonova shasta
(previously
Ceratomyxa shasta
), Pacific salmon
INTRODUCTION
Salmon populations along the west coast
of North America have been in decline
since the early 1900s. Pacific Salmon
are culturally iconic and economically
important, and there is considerable interest
in understanding factors that contribute
to their decline as well as in identifying
management tools to facilitate population
recovery. Salmon have adapted to persist
through extreme environmental conditions,
predation pressures, variable resource
availability, and disease. However, humans
have altered freshwater systems, reducing the
amount of spawning, rearing, and migratory
habitat required for abundant and persistent
populations of anadromous fishes.
Infectious agents likely play a role in
salmonid population dynamics. Yet,
quantifying this role remains challenging
because of difficulties observing and
sampling diseased fish in the wild (Hedrick
1998). Diseased fish functionally disappear
from existing monitoring programs because
they suffer disease-associated mortality such
as being eaten by predators (Miller et al.
2014). Therefore, by only sampling survivors,
researchers are often left with incomplete
and inadequate information, making it
difficult to implement sound, scientifically
accurate management decisions. Despite the
challenges, substantial progress has been
made toward understanding the effects of
infectious agents on Pacific Salmon at both
the individual and population levels. For
example, novel research techniques (Hallett
and Bartholomew 2006; Miller et al. 2014)
and the implementation of comprehensive
multi-agency monitoring networks (e.g., for
Ceratonova shasta
in the Klamath River) have
led to integration of pathogen monitoring
into adaptive management strategies. Along
the west coast of the United States and
Canada, pathogens and associated disease
are increasingly identified as a stressor
that contributes to mortality, and are
hypothesized to be one potential factor in
declining salmonid populations (St-Hilaire et
al. 2002; Belchik et al. 2004; Fujiwara et al.
2011; Jeffries et al. 2014a; Bass et al. 2019;
Teffer et al. forthcoming [2020]).
Improving the condition and survival
of both rearing and migrating Chinook
Salmon is necessary for their recovery in
California’s Central Valley (NMFS 2014)
.
To implement effective management actions to
increase survival, we need to understand the
individual and interactive effects of factors such
as temperature, flow, food availability, habitat
quality, predator-prey interactions, and disease.
Several salmon monitoring programs in the
Central Valley already exist to monitor these
factors. There have also been recent efforts to
improve the efficacy of these programs and their
ability to inform relevant management questions
(Johnson et al. 2017). To date, however, pathogen
and disease monitoring in the Central Valley as
important components of fish condition have
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SEPTEMBER 2020
https://doi.org/10.15447/sfews.2020v18iss3art2
been omitted from status and trend monitoring
frameworks, resulting in a lack of information for
practitioners to incorporate disease into robust
management plans (Johnson et al. 2017).
On March 14-15, 2018, UC Davis hosted a Salmon
Disease Symposium aimed at understanding
the present state of knowledge of Central Valley
salmon disease ecology, defining past and current
monitoring efforts, and identifying key knowledge
gaps. The goal of this review is to summarize
the information presented by the attendees of
this workshop. Additionally, we draw on research
and case studies from other systems to present
potential future research opportunities that could
provide fisheries and water managers with better
information for managing salmon populations.
Last, we provide recommendations for designing
a monitoring framework for salmon disease in the
Central Valley.1
INFECTIOUS AGENTS AND DISEASE OVERVIEW
Infectious agents that cause disease in salmon
include viral, bacterial, fungal, protozoan, and
myxozoan microparasites (Table 1) as well as
macroparasites such as sea lice. They are innately
part of the ecosystems in which salmon live
and have co-evolved with their salmon hosts.
However, rapid environmental changes can upset
the balance of host-pathogen interaction. While
1. To address the critical knowledge gaps of how infectious agents
may be affecting Central Valley Chinook Salmon populations, the
Delta Stewardship Council and the UC Davis Coastal and Marine
Sciences Institute convened a 2-day symposium to address our
current state of knowledge about infectious agents that affect
salmon, and discussed developing and available tools that can
be used to study infectious agents. On Day 1, case studies were
presented from other watersheds for which frameworks have been
developed to effectively monitor programs or model approaches
to understanding pathogen-host dynamics. Participants included
representatives from the US Fish and Wildlife Service, California
Department of Fish and Wildlife, University of California-Davis,
University of California-Santa Cruz, Canadian Department of
Fisheries and Oceans, Yurok Tribe, US Bureau of Reclamation, US
Geological Survey, Oregon State University, Marine Institute of
Ireland, Delta Science Program, The Metropolitan Water District
of Southern California and NOAA Fisheries. Day 2 was a focused
discussion with these experts on how their insights may be applied
to the Central Valley to develop a more comprehensive under-
standing of how infectious agents affect Central Valley Chinook
Salmon. Recordings of the presentations are made available at
https://ats.ucdavis.edu/ats-video/?kpid=0_9d46tt27. Contributions
authored entirely by non-USGS authors do not represent the views
or position of the USGS
some pathogens are highly virulent, many more
opportunistic pathogens only cause disease when
the host becomes compromised for other reasons,
such as unfavorable environmental factors. Even
under favorable conditions, salmon are constantly
exposed to a variety of pathogens. Whether or not
infection develops into a disease state in a fish
depends on pathogen exposure levels (external
agent), the susceptibility of the individual (host),
and the environment in which host and agent are
brought together. Collectively, this is known as
the epidemiological triad (Box 1).
It is important to distinguish the differences
among the presence of infectious agents in the
environment, whether or not those agents have
infected the host, and whether that infection
has led to disease. Dozens of infectious agents
known to infect Pacific salmonids persist in the
environment at all times. For example, many
microparasites such as the myxozoans Ceratonova
shasta and Parvicapsula minibicornis are present
in freshwater environments year-round, but
the density and virulence of spores fluctuates
through time and space (Bartholomew et al.
2007; Hallett et al. 2012). Host organisms have
developed immune system coping mechanisms
to deal with constant exposure. Often, fish host
multiple pathogens and parasitic organisms at
any given time without exhibiting any noticeable
disease or adverse effect. For bacterial or viral
infections, an infected fish only becomes
diseased if the replication of the pathogen within
its body becomes sufficiently aggressive that
homeostasis is compromised. Alternatively,
homeostasis is compromised by the effects of
other environmental stressors, which facilitates
the invasion and proliferation of a pathogen in
the organism. Additionally, disease can be caused
by the host’s response to the pathogen (e.g.,
inflammation in response to Tetracapsuloides
bryosalmonae causing proliferative kidney disease
(PKD) (Hedrick et al. 1993).
Water quality, contaminants, food availability,
and other stressors in the environment can
facilitate pathogen invasion (Hedrick 1998).
Disease occurrence and progression in fish
is critically dependent on water temperature
SAN FRA NCISCO ESTUARY & WATE RSHE D SCIEN CE
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VOLUME 18, ISSUE 3, ARTICLE 2
because it affects both the immune functions of
the host and contributes to increased pathogen
replication (Noe and Dickerson 1995; Marcogliese
2008). Poor water quality in close proximity
to effluent discharge from large point sources
(such as water treatment facilities) includes a
multitude of chemicals that may directly affect
fish health (Hasenbein et al. 2014; Sutton et al.
2016; McGovarin et al. 2018). Low dissolved
oxygen, elevated temperatures, salinity intrusion
during drought years, and contaminants can also
have synergistic effects with water quality and
infection. Not only are fish more susceptible to
infection after poor water quality induces stress,”
but the opposite also holds true: an infected fish
may be more sensitive to effects from poor water
quality (Clifford et al. 2005; Eder et al. 2008),
because both directly affect their immune system.
Much of what is known about Pacific salmonid
diseases comes from rearing fish at high
densities in hatchery settings (Naish et al. 2007).
Effects of disease are more readily observed in
captive populations compared to wild animal
Table 1 Common pathogens of Pacific salmonids and brief descriptions of their effect
Infectious agent
and disease Life form Description
Ceratonova shasta
Enteronecrosis
Myxozoan
parasite
(Cnidaria)
C. shasta
is a myxosporean parasite that infects the digestive tract of salmonids.
It has a complex life cycle that includes an invertebrate freshwater host: an
annelid that lives on the benthic substrate of low gradient rivers.
C. shasta
actinospores are released into the water column by annelid hosts and go on to
infect salmon where they replicate in the tissue of the fish, infecting primarily
the intestinal tract but becoming systemic in more severe infections. Infected
juveniles or postmortem (post-spawn) adult salmon release myxospores, which
are not infectious to other fish until completing their life cycle within an annelid
host. Warmer water temperatures increase the rate of replication and chance
of infection. Juvenile fish inhabiting water with particularly elevated densities of
C. shasta
actinospores are likely to become overloaded and die.
Parvicapsula
minibicornis
Glomerulonephritis
Myxozoan
parasite
(Cnidaria)
P. minibicornis
is a myxosporean parasite with the same invertebrate host as
C. shasta
. It infects the kidney and the cause of death is presumed to be renal
failure.
Tetracapsuloides
bryosalmonae
Proliferative kidney
disease (PKD)
Myxozoan
parasite
(Cnidaria)
T. bryosalmonae
is a malacosporean parasite with a two-host life cycle that
alternates between salmonids and freshwater bryozoans (colonial single-celled
animals). It causes swelling of the kidney and spleen, and ultimately death.
Ichthyophthirius
multifiliis
White spot disease
Protozoan
ectoparasite
(Ciliophora)
One of the most common parasites of freshwater fishes, also known as Ich.
It is detectable as white spots (trophozoites) on the skin of fish. The ciliate
damages gills and skin, causing ulcers and reducing the respiratory efficiency of
the fish. Heavy infection can result in death. The infectious stage is a theront. It
has a direct life cycle but typically is not transmitted fish to fish (requires some
development off fish).
Flavobacterium
columnare
Columnaris
Bacterium
F. columnare
is a gram-negative bacterium that can exist in water for several
weeks. Infected fish develop external lesions (skin and gill) during warm water
conditions which affect oxygen uptake and osmotic regulation.
Renibacterium
salmoninarum
Bacterial kidney
disease (BKD)
Bacterium
Diseased salmon are often identifiable by abdominal fluid build-up and
swelling. The bacteria cannot survive in the water column for long periods,
and transmission between fish can occur both vertically and horizontally.
R.
salmonarium
can stay dormant within its salmonid host until the fish undergoes
stress such as temperature shock or malnourishment.
Infectious
hematopoetic
necrosis (IHN)
Virus
The IHN virus is a rhabdovirus that affects all life stages of salmonids. It is
transmitted both horizontally (waterborne) and vertically (from adults to eggs). It
causes abdominal distension and hemorrhaging and may cause high mortality in
juvenile salmon.
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SEPTEMBER 2020
https://doi.org/10.15447/sfews.2020v18iss3art2
populations. In a hatchery setting, the sub-lethal
effects of temporary disease outbreaks are less
ecologically relevant than in the wild because
food availability is not limited and there are no
predators. Fish health staff can often respond to
outbreaks by providing treatment or manipulating
water quality, such that disease can be a
negligible factor to their survival. Conversely,
adult salmon that are tightly confined in pre-
spawning areas can be highly susceptible to
pathogen transfer between individuals.
The potential disease risks posed by hatchery
stocks to free-ranging salmon is a topic of high
concern, but there are relatively few examples
demonstrating an effect (see Naish et al. 2007).
In recent decades, using fish health approaches to
control disease in hatcheries has been successful
(Munson et al. 2010). Many freshwater salmon
hatcheries rely on strict biosecurity
—
including
a secure water supply
—
to prevent entry of
pathogens from free-ranging fish in adjacent
waters.
Because salmon are migratory and move through
different environments (freshwater, estuarine,
marine), they have an extremely energetically
demanding life history. Their immune function
can be compromised at many critical life stages,
making them more susceptible to infectious
agents (Miller et al. 2014). While not all
pathogens can transcend these environments,
some are transmitted by the host between these
environments, where they can become more
—
or
less
—
virulent (Miller et al. 2014). The viral load of
piscine orthoreovirus (PRV) detected in juvenile
Atlantic salmon (Salmo salar) in freshwater
was observed to increase in fish transferred to
seawater (Løvoll et al. 2012). It is thus possible for
a fish to become infected in one environment and
for a disease outbreak to occur after it transitions
to another environment, creating further
difficulties in determining sources of infectious
mortalities.
While disease outbreaks occasionally affect
cohorts of fish catastrophically, the indirect
effects of decreased physiological functions
may have additional consequences on salmon
populations that are less evident. Individuals
that expend energy to suppress infection may do
so to the detriment of swimming performance,
thus decreasing their ability to avoid predators,
forage, and negotiate complex migratory
BOX 1
Epidemiological Triad
Occurrence of disease results from the interaction among
host, environment, and disease-agent components
(e.g., salmon, water quality, and pathogen). Critical host
components might be age, sex, genetic background,
and nutritional and physiological status affected during
or before exposure to a pathogen. Environmental
components include alterations in climate, contaminants,
food availability, habitat type, etc. Each of the three
components can alter the others (e.g., proximity to a
contaminant discharge [effluent/runoff] may affect water
quality and decrease food availability, thus changing the
nutritional status of an individual, or may allow a pathogen
to establish in a new area or host). In the context of a
rapidly changing environment, and increases in extreme
events, all three components will be subject to changes
that can alter salmonid success. Understanding the role of
pathogens in the Central Valley is crucial to management
and conservation of salmonid species.
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VOLUME 18, ISSUE 3, ARTICLE 2
Salmonid diseases can present a significant
challenge to the aquaculture industry, where
outbreaks can substantially affect the economic
viability of a single fish farm or an industry
as a whole. For example, in 2007, a widespread
outbreak of infectious salmon anemia (ISA)
disrupted the Chilean salmon farming industry,
and led to a 700,000-ton decrease in production
worth about $2 billion (Asche et al. 2009).
These disease-related losses went beyond the
decline in production. ISA also reduced output
quality, causing Chile to suffer lower prices and
lose market share, at least temporarily. New
pathways. Several studies have observed salmon
challenged with pathogens to have decreased
critical swimming speed (Tierney and Farrell
2004; Kocan et al. 2009) and increased risk of
predation (Miller et al. 2014). To date, there is
a limited understanding of how these indirect
effects influence salmon population dynamics
because they are difficult to measure in situ
since diseased fish that have died and dropped
out of the system cannot be sampled. This is
further confounded by the complex and dynamic
environmental conditions that salmon experience
throughout their life cycle.
BOX 2
Disease Terminology
Term Description
Clinical Recognizable and/or standardized signs and symptoms of disease progression.
Endemic An infectious agent or disease that is established in a particular population in a given
geographical area.
Epidemic An often sudden increase in the level of disease in a specific population over a given period
of time.
Exposed When an individual has encountered an infectious agent. Necessary for infection to take
place. However, not necessarily the case that infection occurs.
Infection The entry, establishment, and replication of pathogens inside a host organism, but not
necessarily resulting in disease.
Infectious Individuals who are infected and can transmit an infectious agent to other individuals.
Infectious
agent
Something that infiltrates another living thing. An infectious agent may or may not be a
pathogen.
Infectious
disease
A type of illness caused by a pathogenic agent, including viruses, bacteria, fungi, protozoa,
parasites.
Latent period Period of time between occurrence of infection and the onset of infectiousness (when the
infected individual becomes infectious).
Morbidity Being in a diseased, or non-normal state.
Outbreak An unexpected increase in the prevalence of a particular disease over a given time-period
and geographic range. A general term that may refer either to an epidemic or a pandemic.
Pandemic
An increase in the occurrence of a particular disease over a very large region, such as a
continent or the entire globe, that is greater than what is expected over a given period of
time.
Parasite
An organism that lives in or on an organism of another species (its host) and benefits by
deriving nutrients at the host’s expense. Parasites can be a category of pathogen, but not all
parasitic organisms are pathogens.
Pathogen A biological agent that causes disease.
Prevalence The proportion of cases of diseased individuals at a specific time.
Virulence The ability of an infectious agent to produce disease.
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regulations to control ISA increased production
costs for salmon farms. The effects of ISA led
to economic losses for both the industry and
the national economy. In 2009, 79% of salmon
farms shut down, costing 20,000 jobs. Disease
management strategies that have developed in
aquaculture may inform future efforts to manage
disease in wild fish populations.
QUANTIFYING DISEASE RISK, SPREAD, AND
EFFECTS ON A POPULATION LEVEL
Population-level effects from infectious agents
are not easily observed, and successful evaluation
requires a combination of high-quality data and
robust models (Peeler and Taylor 2011). Data
obtained from research and monitoring programs
can be used in models to test hypotheses about
pathogen transmission, disease risk, and effects
on a population (e.g., how does water temperature
influence disease progression). Although some
infectious agents cause disease quickly (acute
pathogens), other agents may not cause a disease
state until weeks or months after infection.
Infection or disease prevalence can also be
underestimated as a result of only sampling
survivors, because affected fish have been lost
to direct or indirect mortality (e.g., predation).
This makes monitoring cohorts of fish through
large complex systems such as the Central Valley
difficult.
Data Collection
Many different sampling and survey
methodologies are available to collect data on
infectious agents and determine their effect on
salmon. Tools exist to quantify the presence
of infectious agents in the system as well as
determine their effect on fish health.
River water samples can be used to map the spatial
and temporal distribution of infectious agents
and potential exposure landscapes of salmon to
diseases in a watershed (Hallett and Bartholomew
2006; Richey et al. 2018). Advancements in
environmental DNA (eDNA) technology are
allowing researchers to rapidly determine the
presence and abundance (e.g., cells L-1) of multiple
agents in a single sample in near-real time
(Nguyen et al. 2018). As costs fall and sensitivity
increases, it will become easier to pinpoint hot
spots of infectious agents and associate them with
environmental variables and/or identify sources.
For infectious agents with indirect life cycles that
involve an additional host, this non-salmonid
can be assessed for prevalence of infection. This
additional host infection prevalence and density
can provide information on infectious hot spots
(e.g., annelid host (Manayunkia occidentalis;
[Atkinson et al. 2020]) for Ceratonova shasta;
[Alexander et al. 2014]).
To determine whether infectious agents present
in the environment result in infected or diseased
individuals, it is necessary to sample fish. Non-
lethal testing methods to assess infection status
are reliable for some but not all fish pathogens,
but assessing disease status by non-lethal
methods is often more difficult. However, diseases
that can be assessed by visual or non-lethal
methods allow disease state to be integrated
with other populations assessments (e.g., mark-
recapture approaches; [Groner et al. 2018]).
Typically, more invasive techniques are needed
to determine disease state. Histopathology is one
of the more traditional methods used to assess
the progression of disease within fish (Kent et al.
2013). Researchers examine thinly cut sections
of fixed and stained tissue under a microscope
for the presence of pathogens, parasites, or tissue
damage associated with a particular pathogen
or parasite. Histopathology is highly effective
in determining the disease state of a fish, but
usually requires lethal sampling and that tissues
be carefully preserved and transported, which
may be difficult in field settings. Moreover,
histopathology, traditionally applied on dead and
dying cultured fish to determine cause of death,
may not be highly sensitive to detection of early
stages of disease development that would be more
commonly observed in random samples of wild
fish (Miller et al. 2014, 2017).
Molecular and genomic methods have been
established to detect the presence and/or
abundance of infectious agent DNA within a host
fish (Miller et al. 2014, 2016; Teffer et al. 2009,
2017). For instance, quantitative polymerase
SAN FRA NCISCO ESTUARY & WATE RSHE D SCIEN CE
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VOLUME 18, ISSUE 3, ARTICLE 2
chain reaction PCR (qPCR) is often but not
always more sensitive than traditional diagnostic
techniques based on culture. Additionally, these
molecular diagnostic tests are especially relevant
for the detection of unculturable organisms. The
detection of an infectious agent within host tissue
does not necessarily indicate that the individual
is progressing to a diseased state, but rather
highlights that the fish is infected. As described
above, other techniques such as histopathology
are often used in conjunction to assess whether
infection is resulting in physiological harm to the
fish. These molecular/genomic techniques can also
be used to determine the expression of host genes,
for example, those associated with immunity, as
a means to quantify host response and predict
the potential for disease (Connon et al. 2012;
Jeffries et al. 2014a, 2014b; Teffer et al. 2018;
Hurst et al. 2019). In fact, specific gene expression
signatures of infection are being identified using
this approach (Miller et al. 2017). Integration of
pathogen and host gene profiling may represent
a better non-lethal approach
—
particularly for
systemic infections that often occur with viral
diseases
—
and potentially requires only a small
amount of gill tissue (Mordecai et al. 2019, 2020).
Deploying sentinel fish allows researchers to
experimentally test the “infectiousness” of a
particular area (Foott and Imrie 2017; Richey
et al. 2018). Typically, juvenile salmon from
hatcheries are pre-screened for pathogens and
then placed in cages in situ for several days to
several weeks; brought back to an aquarium
facility where they are reared and monitored for a
period of time, potentially under different thermal
regimes; and then assessed for either infection
or disease. Data on severity of infection
—
percent
morbidity and time to morbidity
—
are also
collected (e.g., Ray et al. 2015). When performed
across multiple locations and over time, sentinel
fish studies can be a powerful tool to describe the
risk of infection throughout a system.
Stress challenge studies can also be carried out
to determine how stress affects replication and
disease development of naturally occurring
pathogens (e.g., Teffer et al. 2018; Bass et al.
2019). These studies have not only revealed
thermally sensitive pathogens, but have addressed
the role of catch-and-release fisheries on disease
development and survival.
To understand disease dynamics in a system,
disease studies need to incorporate multiple
types of sampling. Where few or no specific
resources are available for disease monitoring,
simple metrics of fish health can easily be added
to already existing sampling programs. On
the Columbia River, established juvenile fish-
collection facilities collect information on simple
metrics that include
—
but are not limited to
—
the
number of fish with body injury, predation marks,
and disease and parasite symptoms (FPC 2017).
Recent studies have demonstrated that some
of these simple metrics can provide invaluable
insight into the factors associated with juvenile
salmonid survival and, ultimately, adult returns.
Evans et al. (2014) found that steelhead from the
Snake River and upper Columbia River without
external disease symptoms were 3.7 and 4.5 times
more likely, respectively, to survive to adulthood
than steelhead with severe external symptoms
of disease. Additionally, they found that Snake
River steelhead were 1.2 times more likely, and
upper Columbia River steelhead were 7.7 times
more likely, to survive if they had no signs of
fin damage. The same fish were evaluated for
expression of gene response to immune functions
using qPCR. Visual fish condition estimates were
found to match genetically determined bad, poor,
and healthy individuals (Connon et al. 2012),
confirming that these relatively simple metrics of
fish condition and disease monitoring represent
an approach untapped in California to evaluate
factors associated with juvenile salmonid survival
and adult returns.
Models and Decision Support Tools
Both knowledge-driven (i.e., mechanistic) and
data-driven approaches (or combination of
both) can be used to develop models to aid in
decision-making. For example, compartmental-
based models, in which we assume that each
individual in the population can be considered
“susceptible,” “infected,” or “recovered” (SIR
models) in specific time-periods, can be used to
model disease progression based on just a few
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parameters such as infection and recovery rates
(Ogut et al. 2005). More advanced SIR-extended
models can consider environmental factors such
as the effect of water temperature, water quality,
or flow. However, these models may contain
many unrealistic assumptions (e.g., homogeneous
population, random mixing, closed population,
lifetime immunity, single transmission mode,
static incubation period, etc.), leading to complex
parameterization, and limiting their capacity to
effectively represent reality. Therefore, to better
inform decision-making, more complicated models
are often required. Bayesian models to reconstruct
aquatic pathogen transmission or ecological niche
models to predict potential spread are now being
developed for certain economically important
pathogens such as infectious hematopoietic
necrosis virus (IHNV) and viral hemorrhagic
septicemia virus (VHSV) (Escobar et al. 2017;
Ferguson et al. 2018; Paez et al. 2020). Although
more complex models for free-ranging salmon
populations are still relatively scarce, in the
commercial salmon industry similarly complex
models are increasingly being used to simulate
disease transmission, and to identify risk factors
and high-risk areas where management should be
prioritized (Haredasht et al. 2019).
With increases in computational power and
the ability to collect ever more demographic,
environmental, and spatio-temporal surveillance
data, the use of disease forecasting models
will increasingly inform decision-making for
surveillance and control. For example, platforms
such as Disease BioPortal (http://bioportal.
ucdavis.edu), allow for the rapid visualization
and analysis of multiple databases. The
possibility to access multiple data types (e.g.,
disease surveillance, fish demographics, and
environmental information) in one place and
to use multi-scale analytical capabilities (e.g.,
space-time-genomic visualization and analysis)
allows diverse analyses. These include risk factor
analysis, social network analysis, molecular
epidemiology, cluster analysis and anomaly
detection, risk assessment, and spatio-temporal
risk mapping. The integration of novel machine
learning algorithms, agent-based simulation
models, and other Big Data analytics can be
used to help prevent and control infectious
diseases in animal populations. They can identify
patterns and high-risk areas and inform the
implementation of targeted, more cost-effective
interventions. The goal of platforms like this is
to improve surveillance, risk assessment, and
modeling of infectious diseases by optimizing
data collection, integration, standardization,
and storage. Disease BioPortal also improves
data accessibility and usability to improve risk
communication, awareness, and involvement (e.g.,
citizen science, participatory epidemiology, etc.)
among decision-makers and the general public.
INFECTIOUS AGENTS AND DISEASE
MONITORING IN CENTRAL VALLEY SALMON
Currently, there is no system-wide monitoring
framework for aquatic infectious agents that
cause disease in wild salmon in the Central
Valley. However, there have been multiple short-
term sampling efforts since 1997. Many of
these studies identified biologically significant
concentrations of infectious agents in the water
and high prevalence among wild fish.
Infectious agents associated with diseased
Chinook Salmon in the wild have been observed
in the Feather, Merced, Sacramento, San
Joaquin, and Stanislaus rivers as well as in the
Sacramento-San Joaquin River Delta (Table 2).
Survey approaches, sampling locations and dates,
and species of interest were not consistent, and
varied among years. The longest sampling effort
was conducted by the US Fish and Wildlife
Service’s National Wild Fish Health Survey
(NWFHS). The NWFHS was developed in 1997
after the discovery that the infectious agent of
salmonid Whirling Disease, Myxobolus cerebralis,
was responsible for decimating wild trout
populations in the Intermountain West.
At the time, little was known about infectious
agents in fisheries and the US Fish and Wildlife
Service (USFWS) recognized that valued fishery
stocks were at risk. Knowledge about infectious
agents was needed to improve management of
hatchery and wild populations, so the USFWS
developed standardized methodologies to ensure
SAN FRA NCISCO ESTUARY & WATE RSHE D SCIEN CE
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VOLUME 18, ISSUE 3, ARTICLE 2
Table 2 Summary and findings of major salmonid disease-related monitoring efforts performed by the US Fish and Wildlife Service
in the Central Valley since 2000
Salmonid
spp.aRegion Significant findingbPathogens of
interestbMethods
Life
stages
Study
years
Lead
agency
Funding
agencyd
Chinook,
spring and
fall-run
Feather River High POI for C. shasta in
most years
C. shasta,
P. minibicornis
Sentinel fish Juveniles 2015–2018 USFWS USBR
Relevant citation: Foott JS, Imrie A. 2016. Prevalence and severity of Ceratonova shasta and Parvicapsula minibicornis infection of natural Feather
River juvenile Chinook Salmon (January–May 2016). Anderson (CA): US Fish and Wildlife Service California–Nevada Fish Health Center.
Available from:
http://www.fws.gov/canvfhc/reports.asp
Chinook,
winter-run
Upper Sacramento
River
C. shasta infectivity
deemed low during
survey period
C. shasta,
P. minibicornis
Sentinel fish,
eDNA, wild fish
sampling
Juveniles 2015–2016 USFWS CVPIA
Relevant citation: Foott JS, Stone R, Voss S, Nichols K. 2017. Ceratonova shasta and Parvicapsula minibicornis (Phylum Cnidaria: Myxosporea )
infectivity for juvenile Chinook salmon (Oncorhynchus tshawytscha) in the upper Sacramento River: July–November 2016. Anderson (CA): US Fish and
Wildlife Service California–Nevada Fish Health Center. Available from:
http://www.fws.gov/canvfhc/reports.asp
Chinook,
fall-run Stanislaus River
No viral agents or
significant parasite
or systemic bacterial
infections were detected
in smolts
General fish
health screen
Wild fish sampling Juveniles 2011 USFWS AFRP
Relevant citation: Foott S, Fogerty R. 2011. FY2011: Juvenile Stanislaus River Chinook salmon pathogen and physiology assessment: January–May
2011. Anderson (CA): US Fish and Wildlife Service California–Nevada Fish Health Center. Technical report.
Available from:
http://www.fws.gov/canvfhc/reports.asp
Chinook,
fall-run Stanislaus River
No significant infections
detected in smolt
survival to San Joaquin
R; no notable disease
T. bryosalmonae
Wild fish sampling Juveniles 2010 USFWS AFRP
Relevant citation: Nichols K. 2010. California-Nevada Fish Health Center FY2010 health, energy reserves and smolt development of juvenile Stanislaus
River Chinook Salmon, 2010. Anderson (CA): US Fish & Wildlife Service California-Nevada Fish Health Center. Technical report.
Available from:
http://www.fws.gov/canvfhc/reports.asp
Chinook,
fall-run
Stanislaus,
Tuolumne, Merced,
and San Joaquin
rivers
T. bryosalmonae
detected in 80%
of Merced, 7% of
Stanislaus and 25% of
mainstem San Joaquin
River smolts.
T. bryosalmonae
Wild fish sampling Juveniles 2013 USFWS NWFHS
Relevant Citation: Nichols K. 2013. FY2013 San Joaquin, Stanislaus, Tuolumne and Merced River Chinook smolt quality assessment. Anderson (CA):
US Fish and Wildlife Service California–Nevada Fish Health Center. Technical report. Available from:
http://www.fws.gov/canvfhc/reports.asp
Chinook,
fall-run San Joaquin River T. bryosalmonae
observed in smolts
T. bryosalmonae
Wild fish sampling Juveniles 2000 USFWS CALFED
Relevant Citation: Nichols K, Foott JS, Burmester R. 2001. Health monitoring of hatchery and natural fall-run Chinook Salmon juveniles in the San
Joaquin River and Delta, April June 2000. Anderson (CA): US Fish and Wildlife Service California–Nevada Fish Health Center.
Chinook,
fall-run
Stanislaus,
Toulumne, Merced,
and San Joaquin
rivers
T. bryosalmonae
observed in smolts
T. byrosalmonae
Wild fish sampling Juveniles 2001 USFWS CALFED
Relevant Citation: Nichols K, Foott JS. 2002. Health monitoring of hatchery and natural fall-run Chinook Salmon juveniles in the San Joaquin River and
tributaries, April–June 2001. Anderson (CA): US Fish and Wildlife Service California–Nevada Fish Health Center.
Chinook,
fall-run Merced River
T. bryosalmonae
observed in Chipps
Island re-captures
T. byrosalmonae
Laboratory
studies, surveyed
marked fish
Juveniles 2005 USFWS AFRP
Relevant citation: Foott JS, Stone E, Nichols K. 2007. Proliferative kidney disease (Tetracapsuloides bryosalmonae) in Merced River hatchery juvenile
Chinook Salmon: mortality and performance impairment in 2005 smolts. California Fish and Game 93(2):57-76.
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SEPTEMBER 2020
https://doi.org/10.15447/sfews.2020v18iss3art2
that data collected in different regions were
comparable and useful for management decisions.
Unfortunately, funding for the program is limited,
and sampling events in the Central Valley have
been driven by staff availability, sample permits,
and collection opportunities. A few multi-year
data sets on the Feather and Sacramento rivers
have provided some insight into prevalence and
infection levels of fish (Foott 2014; Foott and
Imrie 2016, 2017; Foott et al. 2017).
The USFWS sampled wild-origin Chinook Salmon
fry caught in rotary screw traps and beach
seines to investigate infections of C. shasta
and P. minibicornis in the Feather River during
2013-2018 (Foott and Imrie 2017). Collection of
longitudinal water samples revealed a 12-mile
section of the river that is highly infective for
C. shasta, but just 26 river miles downstream
of this reach, below the confluence with the
Yuba River, there is reduced infectivity. Initial
detection in fry occurred in late January through
February when water temperature was 10 °C to
12 °C. In the highly infective reach, sampling
of Chinook Salmon at river mile 45 showed
that the prevalence of C. shasta infection was
fairly consistent (46% to 68%) during drought
years (2015, 2016, and 2018) (Figure 1) but
dropped significantly during a high-flow year
in 2017 (Foott and Imrie 2016). The prevalence
of C. shasta was similar or greater 26 miles
downstream, but the number of fish in a clinical
diseased state was 3 to 6 times lower. This is
likely because diseased upstream fish died
from direct (disease) or indirect (e.g., predation)
mortality before reaching the downstream
sampling location.
Concentrations of C. shasta and P. minibicornis in
the Feather River are variable throughout the out-
migration season. Since the majority of Feather
River juvenile Chinook Salmon out-migrate as
fry early in the season (December-February), it is
difficult to say how the severe infection levels in
Salmonid
spp.aRegion Significant findingbPathogens of
interestbMethods
Life
stages
Study
years
Lead
agency
Funding
agencyd
Chinook,
fall-run Merced River T. bryosalmonae
observed in wild smolts
T. byrosalmonae
Sentinel and wild
fish sampling Juveniles 2012 USFWS
Relevant citation: Nichols K, Bolick A, Foott JS. 2012. FY2012 Merced River Chinook Salmon health and physiology assessment, March-May 2012.
Anderson (CA): US Fish and Wildlife Service California–Nevada Fish Health Center. Technical report.
http://www.fws.gov/canvfhc/reports.asp
Chinook,
fall-run
Sacramento and
San Joaquin rivers
C. shasta in Sacramento
River
C. shasta
Wild fish sampling Juveniles 1997–2016 USFWS NWFHS
Relevant citation:
https://www.fws.gov/wildfishsurvey/
Chinook all
runs Sacramento River IHNV, C. shasta, bacterial
infections
IHN virus,
C. shasta
Adult brood stock adults 1997–2016 USFWS NWFHS
Relevant citation:
https://www.fws.gov/wildfishsurvey/
Chinook,
fall-run Sacramento River
IHNV transmission from
sick hatchery fish to wild
fry is unlikely in natural
conditions
IHN virus
Laboratory
studies, surveyed
marked fish
Juveniles early
2000’s USFWS
Relevant citation: Foott JS, Free T, McDowell KD, Arkush KD, Hedrick RP. 2006. Infectious hematopoietic necrosis virus transmission and disease
among juvenile Chinook salmon exposed in culture compared to environmentally relevant conditions. San Franc Estuary Watershed Sci 4(1).
https://doi.org/10.15447/sfews.2006v4iss1art2
a. Chinook = Chinook Salmon
b. POI = prevalence of infection, C. shasta = Ceratonova shasta, P. minibicornis = Parvicapsula minibicornis, T. bryosalmonae = Tetracapsuloides
bryosalmonae, IHNV = infectious hematopoietic necrosis virus
c. USFWS = US Fish and Wildlife Service
d. USBR (US Bureau of Reclamation), CVPIA (Central Valley Improvement Act), AFRP (Anadromous Fish Restoration Program), USFWS (US Fish
and Wildlife Service), CALFED (CALFED Bay-Delta Program), NWFHS (National Wild Fish Health Survey
Table 2 Summary and findings of major salmonid disease-related monitoring efforts performed by the US Fish and Wildlife Service
in the Central Valley since 2000 (Continued)
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March and April (Figure 1) may affect population
dynamics. Approximately 6% to 13% of the out-
migrating juveniles pass through the highly
infective zone in March as older, larger fish.
Sampling from the NWFHS also established that
a portion of the Sacramento River appears to
be infectious for a majority of the year (Foott
et al. 2017). In 2013, approximately 27% of the
wild fall-run Chinook Salmon fry collected
from the Red Bluff Diversion Dam were found
to have early stage infections of C. shasta. In
2014, wild juvenile fall-run Chinook Salmon
from the lower Sacramento River in rotary
screw traps at Tisdale and Knights Landing were
taken to the lab and held for 21 days. Mortality
ranged from 18% to 69% in each captive group;
91% to 100% of those fish exhibited evidence
of clinical disease associated with C. shasta.
In 2015, hatchery-origin fish were used as
sentinel fish and placed in cages in the river
for 5 days, then held in the lab for 21 days.
Histologic examination revealed that most fish
had a high level of C. shasta infection and
were diseased. In the summer and fall of 2016,
sentinel fish were deployed and water samples
collected between Keswick Dam and Red Bluff
Diversion Dam to establish the first longitudinal
map of C. shasta spore concentrations in the
Sacramento River. Concentrations were higher in
the downstream reaches, although few were above
the > 10 spore L-1 threshold previously associated
with high mortality (Hallett et al. 2012). In 2016,
sentinel fish mortality and rates of infection were
lower than the previous 3 years, likely a result
of the diluting effect of higher flows and lower
water temperature.
Although monitoring of infectious agents and
disease severity has been inconsistent in the
Sacramento-San Joaquin watershed, results from
various NWFHS sampling efforts indicate that
there are particular river reaches with high water
concentrations of C. shasta DNA, at levels shown
to cause fish mortality. In high-flow years, the
concentrations of parasite DNA at these particular
reaches were lower, and the infection rates of
juvenile salmon were lower. It is also likely that
0%
20%
40%
60%
80%
100%
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
2015
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
2016
2015
2016
2018
Julian week
Prevalence of infecon Prevalence of infecon Prevalence of infecon
Figure 1 Prevalence of Ceratonova shasta infection in wild
juvenile Feather River Chinook Salmon sampled near river mile
45 in Julian weeks 2
through
18 during 2015, 2016, and 2018.
Infectious rates in 2017 were substantially lower because of
high water flow, but sampling design was different from other
years and should not be directly compared (data not shown).
Julian week corresponds to January (2–4), February (5–8),
March (6–13), April (14–17), and May (18). Infection prevalence
is categorized as CS1 (infected with little to no histological
signs of inflammation, open columns) or CS2 (infected with
histological signs of inflammation and determined to be in a
disease state, yellow columns). Percentage of fish tested that
had quantitative PCR levels > 3 log10 of copies of parasite DNA
are represented with gray dot. Parasite DNA levels > 3 log10
are predictive of a disease state.
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lower water temperatures during high-flow years
may contribute to lower prevalence of infection.
While monitoring for disease in wild populations
has been limited, the California Department
of Fish and Wildlife (CDFW) has developed
and maintained a robust, long-term disease
monitoring program for enhancement and
mitigation of salmon and steelhead hatcheries
under their management. The CDFW monitoring
program begins with the screening of ovarian
fluid and tissue samples from the brood fish for
Renibacterium salmoninarium, the causative
agent of bacterial kidney disease (BKD), and
viruses including IHNV. The fertilized eggs are
disinfected during the water-hardening process
and raised with regular health monitoring
until release into the wild. Hatchery staff are
continually trained in fish husbandry, biosecurity,
and fish pathology so they can quickly identify
and respond to issues that affect the health and
well-being of their fish stocks. Hatchery staff are
trained to identify changes in feeding, behavior,
or increased losses that require investigation by
department veterinarians for potential health.
The CDFW veterinarians diagnose the problem(s)
and recommend changes in husbandry or
prescribe treatments for pathogens or parasites, if
necessary.
DESIGNING EFFECTIVE MONITORING
PROGRAMS
Leveraging Existing Monitoring Programs
Designing effective fish disease monitoring
programs may not always require starting
completely from scratch; instead, it may be
beneficial to integrate disease evaluation into
ongoing monitoring or research programs. In
addition to upfront monetary and time savings,
existing monitoring programs may be interested
in sponsoring related disease work if the new
information can be used to address relevant
questions of the existing project. For example,
adding a disease monitoring framework to
existing programs that track key aspects of
populations, such as abundance and size (Grote
and Desgroseillier 2016; David et al. 2017), or
migration timing and survival (McMichael et
al. 2011; Harnish et al. 2012) may help these
programs to explain variations and trends in past
data. In addition, existing monitoring programs
that have already implemented efficient methods
for safely capturing and handling fish have likely
secured the required federal and state agency
permits, and it is possible that fish captured
under their current program and protocols could
be made available for disease monitoring without
significant modifications. An additional benefit
is that existing monitoring programs will have
established protocols for data recording, transfer,
quality assurance, and storage. Finally, there is
another benefit related to the potential application
of models or tools generated from disease
monitoring research program data. If coupled to
existing data from current monitoring programs,
these tools could be coupled with historical data
collected before the onset of fish disease work.
This may allow hind-casted estimates of fish
disease and increase the time-period available
for analysis, which in turn could better inform
larger-scale biological assessments for resource
management planning.
Metrics That Matter I: For the Population
Although there are tangible benefits to leveraging
existing population monitoring programs, it is
equally important to make sure that the disease
monitoring itself is designed to provide sufficient
information about fish demographics to allow
population-level effects to be directly assessed.
For example, although tracking infection and
disease incidence over an out-migration season
can provide valuable information about temporal
patterns (True et al. 2017a), these data need
to be integrated over multiple generations of
abundance to estimate population-level infection
or disease rates (Som et al. 2016). Further,
emerging technologies continue to improve the
ability to detect and quantify various disease
agents (Hallett et al. 2012; Miller et al. 2014).
However, changes in diagnostic test sensitivity
or specificity must be considered when analyzing
trends in long-term data sets that have been
collected over a period when monitoring
technologies were also improving. To address
these differences and calibrate methods, tests on
both historical and new data should initially be
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run in parallel. This approach has been proven
successful in the Klamath River watershed
during a transition from histology to qPCR as the
primary surveillance tool to assess the prevalence
of C. shasta infection (True et al. 2017b).
To account for potential biases in the data sets,
disease surveillance programs must consider the
biology of the infective agents and the nature
of the fish population under study. Highly acute
disease agents that cause rapid mortality may
result in an underestimate of infection rates
in sampled fish, biasing the true population-
level effect of the disease (Heisey et al. 2006).
Other disease agents may cause sub-clinical
infections that never progress to disease or are
cleared by the host. In these cases, the severity
of infection within the fish population might
inform population-level effects rather than
quantifying the prevalence of the pathogen
within the environment (True et al. 2015). Finally,
some disease agents are strongly driven by
environmental variables (e.g., water temperature)
and incorporation of these variables may better
predict the occurrence and or timing of mortality.
It is important that any disease monitoring
program develop metrics that matter, not only for
the population and infectious agent of interest,
but also metrics to inform management.
Metrics That Matter II: To Inform Management
Disease agent monitoring and research programs
are essential to understanding agent-host ecology
and estimating effects of the disease agent on
fish populations. However, understanding how
the disease agent and fish host interact with each
other and their environment, and knowing how
severely the disease agent may be affecting a fish
population, will not likely be the final program
objectives. If the effects of a disease agent are
severe enough to prompt new monitoring and
research programs, the likely goal is remediation
via changes to resource management practices.
Models and other quantitative tools are
increasingly being used to help inform resource
management decisions (Parrott et al. 2012).
Data collected during monitoring programs help
inform models, which in turn identify data gaps
that need targeted studies. Building models for
effective resource management decision-making
requires both an appropriate model structure,
and attention to the quality and resolution of the
data used to inform the model (Getz et al. 2018).
Fish population dynamics models, developed by
the motivation to inform future management,
have been constructed to include disease agent
dynamics (Perry et al. 2018). Additionally, there
are models that target specific elements of agent-
host ecology (Alexander et al. 2016), which
have been applied to simulate how resource
management alternatives might affect disease
risk (Som et al. 2016). In the above cases, disease
agent monitoring and research projects were
specifically tailored for inclusion in decision
support tools.
The following case studies highlight how the
integration of several data collection and
modeling approaches led to the development
of successful management actions, and where
investment in novel technologies led to
breakthroughs in understanding salmon disease
dynamics.
Case Study 1: Management of C. shasta in the
Klamath Watershed
At the UC Davis Salmon Disease Symposium,
several researchers presented on the Klamath
watershed system as a good example of a
comprehensive, established disease monitoring
program that is used to inform management. The
Klamath system demonstrates why monitoring
is needed, how monitoring programs can be
developed, and how data may be used to inform
management decisions. Many of the approaches
used in the Klamath watershed could be directly
applicable to the Central Valley region.
In 2002, a large mortality event in the
Klamath watershed that involved over 34,000
fish (mostly adults), resulting from infection
by Flavobacterium columnare (a bacterium,
Columnaris) and Icthyophthirius multifiliis (a
ciliate, Ich) brought awareness to the effects
infectious agents can have (Belchik et al. 2004).
Since then, C. shasta has also been identified as
a key factor that limits recovery of salmon in
the Klamath River (Foott et al. 2002; Fujiwara
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et al. 2011). Although C. shasta infects both the
adult and juvenile life stages, in the Klamath
watershed the disease most affects juveniles. This
is in contrast to other watersheds in the Pacific
Northwest where adults experience mortality
from C. shasta infections after re-entering
freshwater to spawn (Bartholomew 1998; Hallett
and Bartholomew 2006). In 2007, in response to
ongoing disease issues, state and federal agencies
began working collaboratively with academics,
tribal groups, industries, land-owners, and
consultants to develop an informative, long-term
monitoring program. The goal of this work-group
was to improve the understanding of disease
dynamics in the Klamath River system, and
build predictive epidemiological models and risk
assessments to inform management and mitigate
disease. This monitoring program can identify
spatial and temporal patterns of C. shasta, and
enables exploration of the relationships among
parasite occurrence, host infection, and abiotic
factors such as water temperature and flow.
Monitoring
The monitoring approach was dictated by the life
cycle of C. shasta, with particular consideration
for the specific life stages most likely affected by
management actions. C. shasta is a waterborne
parasite with a two-host life cycle, so a three-
pronged monitoring approach was developed that
focused on the fish host, the annelid alternate
host, and the parasite itself. Index sites were
established along the Klamath River mainstem
and in several tributaries. Collection of free-
ranging, out-migrant juveniles occurs weekly
from late March through August. Sentinel fish
exposures occur three times during juvenile out-
migration (in April, May, and June) and once
during adult returns (September). Annelids are
sampled quarterly (four times per year), and the
water sampling effort occurs weekly at all sites
from late March through October and at two sites
throughout the year.
Fish Sampling
To collect empirical data on the potential effect
of C. shasta on out-migrating juvenile salmonids,
researchers deploy sentinel fishes at multiple sites
and collect free-ranging fish at existing rotary
screw traps in different locations. Juveniles are
analyzed using both histological and molecular
methods (qPCR) to assess their prevalence and
severity of infection and determine disease state
(Voss et al. 2018). Since heavily diseased fish
usually die before being sampled, sentinel fish
provide additional data on infection and disease
over time and space (with known exposure
history). After river exposure, sentinel fishes
are held at ambient river temperature in the
laboratory to mimic what free-ranging fish may
experience, and are eventually subjected to light
microscopy and PCR analysis (Stocking et al.
2006).
Sampling for Alternate Host
Similar to many parasites, C. shasta, requires
an alternate host to complete its life cycle,
and it is the alternate host that releases
the infectious stage for fish. For C. shasta,
understanding the distribution of the annelid
alternate host and its life history is critical for
informing f low management actions to reduce
C. shasta concentrations. A multi-year study
was implemented to evaluate annelid habitat
preference in the context of multiple flow
regimes (Alexander et al. 2016), which involved
two-dimensional hydraulic modeling to predict
hydraulic conditions (depth/velocity) across a
range of discharge values; optimizing sampling
to quantify annelid habitat preferences; and
coordinating with the federal reservoir facility to
release managed/prescribed flows.
Long-term monitoring of annelid populations was
initiated by collecting benthic samples at multiple
sites throughout the year, providing density
estimates through space and time. Following light
microscopy counts, the prevalence of infection
within annelids was determined using molecular
methods (Alexander et al. 2014).
Water Sampling for Parasites
Outside its hosts, C. shasta distributes passively
through the water column. Water samples can
be collected manually or using programmable
sampling units. Quantitative molecular analysis
can determine parasite density (spore L-1) and the
genotype (Hallett et al. 2012).
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Results
These data sets have provided significant insights
into the role that C. shasta plays in the Klamath
River watershed. Monitoring results are shared
online in near-real time so that managers can
make timely, informed decisions about the timing
of release of flows and fish from the hatcheries.
Infection rates in free-ranging salmonids,
average juvenile salmonid catch-per-day, parasite
abundance in water samples, and sentinel fish
exposures are updated weekly during the juvenile
out-migration season (https://microbiology.science.
oregonstate.edu/content/monitoring-studies; https://
www.fws.gov/Arcata/fisheries/projectUpdates/
KRTrapCatchSummaries/2019/Klamath%20
Trap%20Upd ate%2023apr2019.pdf ).
Samples from free-ranging fish are used to
estimate the prevalence of infection (POI; the
percentage of fish with C. shasta infections).
Prevalence of infection can be tracked over
time within a year and summarized annually.
These data can be overlaid with fish abundance
estimates from rotary screw traps. The integration
of these weekly estimates is important, because
the within-year time-series of each process can
vary dramatically. For instance, there are years
(e.g., 2014, Figure 2A when weekly POI quickly
increased to elevated levels, but only after a
majority of juveniles had out-migrated. Other
years (e.g., 2009, Figure 2B), peak levels of POI
matched peak out-migration of juveniles. And
some years (e.g., 2012, Figure 2C) POI and juvenile
out-migration completely overlapped, but overall
infection levels were very low. If most fish have
already moved through the system before POI has
increased, the overall effect on the population
may be of less concern.
Over the past 10 years, mortality of juvenile
Chinook Salmon estimated by sentinel studies as
a result of C. shasta has varied (Figure 3). True
et al. (2017a) established a disease threshold of
C. shasta in naturally infected fish by defining
qPCR levels associated with advanced clinical
disease that is highly likely to result in mortality
as the infection progresses at temperatures of
15 °C to 18 °C. Over five sampling seasons (2013
–
2017), even at high prevalence of infection, up
to 80% of the fish did not have qPCR levels that
would be predictive of severe disease.
The multi-year study to evaluate annelid habitat
preference in the context of multiple flow regimes
found that under high flow conditions, annelids
are scoured from the benthos, and populations
A B C
Figure 2 Weekly stratified abundance estimates of juvenile Chinook Salmon (solid black lines) and Ceratonova shasta prevalence
of infection (POI; dashed red line), for 3 years of monitoring on the Klamath River. Typically, the majority of salmon passed before the
onset of C. shasta (as shown in panel A), but in some years there was significant overlap, suggesting increased risk of salmon out-
migrants to C. shasta than in other years (see panels B and C).
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SEPTEMBER 2020
https://doi.org/10.15447/sfews.2020v18iss3art2
take time to re-establish. Scouring flows might
be one method to control the alternate host of
C. shasta and thus reduce fish being exposed to
the infectious stage.
Water sampling efforts have allowed for a higher
resolution of where the parasite is located in
the system, and the temporal distribution of
the parasite. Typically, C. shasta levels were
found to increase in the spring
—
overlapping
with the peak of rising water temperatures and
juvenile salmon out-migration. However, the
system varied substantially from one year to the
next, with densities in some years remaining
below 5 spores L-1 and exceeding 100 spores L-1
in others (Figure 4). Initial surveys indicated
that the tributary rivers that feed the Klamath
(Trinity, Salmon, Scott, and Shasta rivers) are
not contributing large amounts of spores to the
system, which helps direct sampling efforts to
continue focusing on the mainstem (Hallett and
Bartholomew 2006).
Water sampling has also enabled identification of
multiple parasite genotypes that affect individual
salmonid species differently (Atkinson and
Bartholomew 2010a, 2010b). This knowledge
informs management about the risk posed to
different salmon species. For instance, C. shasta
Type I is associated with increased mortality
in Chinook Salmon while Coho Salmon
(Oncorhynchus kisutch) are more susceptible to
Type II (Hallett et al. 2012). The proportion of
C. shasta genotypes differs throughout the year
and among the sites (Atkinson and Bartholomew
2010b; Hallett et al. 2012). Generally, Type I is
more abundant in the Klamath watershed, which
is consistent with it being a predominantly
WMR
KED
Ki5
KBC
KSV
KOR
0
10
20
30
40
50
60
70
80
90
100
2009 2010 2011 2012 2013 2014 2015 2016 2017
000000000
00000000
2.5 00000
40.5
25.6
2.4
86.7
20
17.1 16
5.2
40
46.3
29.5
7.5
72.1
12.5
9.3
17.9
12.9
46.5
7.7
60
2.6
13.5
2.4 0
52.5 5
39.5
81.1
0
Percent Ceratonova shasta-associated mortality
Figure 3 Comparison of percent mortality from Ceratonova shasta of juvenile Iron Gate Hatchery Chinook Salmon at six index
sites in the Klamath watershed exposed in June of 2009–2017. The Chinook Salmon (40 in a cage per site) were exposed for 72
hours, then monitored for 60 to 90 days in the laboratory; zeros indicate exposure but no loss. The percent change represents fish
that were moribund or dead and were removed from the tanks during the post-exposure rearing (any change that occurred during
the first 5 days was excluded). Fish were regarded as positive for infections of C. shasta, either by microscopic observation for
myxospores in intestinal wet mounts or PCR testing of intestinal tissue. Sites are ordered in direction of river flow, upstream (front)
to downstream (back). WMR and KED are in the upper basin, above Iron Gate Dam, a barrier to anadromous salmonid migration.
WMR, Williamson River; K, Klamath mainstem; KED, Keno Eddy; Ki5 at I5 Bridge; KBC, near Beaver Creek; KSV, Seiad Valley; KOR,
Orleans. Map available at https://microbiology.science.oregonstate.edu/content/monitoring-studies
SAN FRA NCISCO ESTUARY & WATE RSHE D SCIEN CE
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VOLUME 18, ISSUE 3, ARTICLE 2
Chinook Salmon-dominated system. Results
from parallel water sampling and fish exposures
revealed that Coho Salmon are sensitive to lower
densities of Type II C. shasta spores than Chinook
Salmon are to Type I spores (Hallett et al. 2012).
Management Actions
Data from this multi-step monitoring program
focused on the complete C. shasta life cycle are
being used to inform several different types
of management actions. Data on prevalence
of infection were used in the 2013 Biological
Opinion (NMFS 2013) for the federal Klamath
Irrigation Project by developing an incidental take
statement for Coho Salmon based on prevalence
of infection in Chinook Salmon (Chinook Salmon
data were used a proxy species because of the
limited information available on Coho Salmon).
In 2017 and 2018, water samples and out-
migrants were required to be processed as soon
as possible and made available to agencies
and stake-holders for discussion and possible
action. Management actions could include flow
releases from reservoirs, or modifying the release
timing of juvenile Chinook Salmon from the
hatcheries. Potential emergency flow triggers
were actinospore density (spores L-1) and POI in
free-ranging salmonids. Increasing flow from
reservoirs could have a range of effects on the
parasite that depend on the timing, magnitude,
and duration of the event. Increased flows
could dilute or move the parasite, disturb the
annelid habitat, affect transmission efficiency or
move juvenile salmonids downstream or adults
upstream past the infection zone. In the 2019
Biological Opinion (NMFS 2019), three types
of flow of different dimensions are defined to
achieve these outcomes: (1) a surface flushing
flow; (2) a deep flushing flow; (3) enhanced flow
in the springtime. During salmonid out-migration,
a consortium of Klamath Basin technical experts
convene weekly via conference call to review data
updates (hydrologic, meteorological, and disease)
and discuss adaptive management options.
Data on myxospore, actinospore, annelids, and
fish were used to develop an epidemiological
model that incorporates both the juvenile and
adult salmon life stages to identify which
life stage of juvenile Chinook Salmon is most
sensitive to C. shasta. (Ray et al. 2015). Models
Figure 4 Density of Ceratonova shasta in water samples collected at the Beaver Creek index site (KBC) in the Klamath watershed
from 2009
–
2017. Each point is the average of 3 x 1L from a 24-hr composite water sample. The maximum level in 2015 exceeded 1,000
spores L-1. Note the high densities of C. shasta observed in 2009 and 2014–2016.
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SEPTEMBER 2020
https://doi.org/10.15447/sfews.2020v18iss3art2
are also being developed to predict the infection
prevalence of fish, predict the timing of annelid
population expansions, and understand how
climate change may affect C. shasta dynamics.
Multi-agency collaboration has been one of the
most important aspects of the development and
success of this monitoring program. A consistent
source of funding has been essential to plan
and execute regular collection and processing of
samples. Occasions when funding was absent and
lapses in data collection occurred have resulted in
critical data gaps.
Case Study 2—Using Novel Approaches to Study
Infectious Agents in British Columbia
Salmon productivity in British Columbia has
been declining for > 30 years. In the Fraser
River, Sockeye Salmon (Oncorhynchus nerka)
had one of the lowest returns on record in 2009,
with < 2 million returning fish, a considerable
discrepancy from the escapement of 10 million
fish predicted by management models. Concern
over declining Sockeye Salmon productivity,
combined with the increasingly poor predictive
power of escapement models used to manage the
fisheries, resulted in a federal judicial inquiry
(known as the Cohen Commission) into the
declines of Sockeye Salmon in the Fraser River.
The goal of the Cohen Commission inquiry was
to investigate factors contributing to (1) multi-
decade declines in survival of Sockeye Salmon,
(2) the poor returns in 2009, and (3) high
inaccuracy in escapement model predictions
used to manage fisheries. Infectious disease as a
contributing factor to declining Sockeye Salmon
productivity was identified as one of the 13 key
hypotheses explored. Through expert testimony,
there was general scientific consensus that
conditions in the early marine environment was a
key determinant of year-class strength, and that
infectious disease could contribute to the multiple
stressors that affect salmon during this critical
stage. However, in the final Recommendations
(Cohen 2012), the court ruled that there was
insufficient information on the pathogens that
affected salmon in the ocean to evaluate the level
of contribution of infectious disease to declining
productivity, and the specific pathogens that may
be involved. Moreover, the court ruled that it
was important to determine the risk of infectious
agent transmission from marine net pens as
a contributing factor in disease occurrence in
free-ranging migratory salmon. After the Cohen
Commission investigation there was an increase
in support and resources to investigate the role of
disease in free-ranging salmon, improve disease
risk assessment, and build a better understanding
of the interplay between cultured and free-
ranging fish.
In 2014, in response to the Cohen Commission
recommendations, Fisheries and Oceans Canada,
the Pacific Salmon Foundation, and Genome
British Columbia collaborated in the development
of the Strategic Salmon Health Initiative (SSHI), a
large multi-disciplinary project that uses science
and innovation to identify the role of infectious
disease in declines of Sockeye, Chinook, and Coho
Salmon. This was the first program of its kind
to explore a broad base of potential pathogens
(viruses, bacteria, fungal, and protozoan
parasites) known or expected to cause disease
in salmon worldwide, and the interplay between
wild and cultured salmon (both aquaculture and
enhancement hatcheries). Over 3 years, the SSHI
screened 28,000 fish from wild, hatchery, and
aquaculture settings for more than 60 potential
pathogens (e.g., Nekouei et al. 2018; Tucker et al.
2018; Laurin et al. 2019) and discovered several
novel viruses (Mordecai et al. 2019, 2020).
Among this program’s accomplishments were
characterizing previously unrecognized diseases
on salmon farms (Di Cicco et al. 2017, 2018),
developing a novel host biomarker panel that
predicts the presence of a viral disease state in
salmon (Miller et al. 2017), and developing new
in situ hybridization techniques to identify where
infectious agents are occurring within diseased
tissue (Di Cicco et al. 2018).
The foundation of the program was based on
the development of a novel high-throughput
molecular technology to quantitatively monitor
dozens of infectious agents at once (described in
Miller et al. 2016). To gain an understanding of
what infectious agents were present, the program
initially screened for 47 infectious agents
SAN FRA NCISCO ESTUARY & WATE RSHE D SCIEN CE
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known or suspected to cause disease in salmon
worldwide, with additional agents added as they
were discovered. Monitoring was not restricted
to infectious agents known in British Columbia
because during the testimony in the Cohen
Commission, it became clear that many agents
associated with emerging disease in other parts
of the world had never been assessed in North
America. Application of the pathogen monitoring
platform revealed detection of 38 of the original
47 infectious agents screened in British Columbia
salmon. After replacing assays to agents not
detected in the first 10,000 fish surveyed, the
program has now documented over 50 infectious
agents in British Columbia salmon. Half of these
agents were first detected in juvenile salmon
in freshwater, of which the majority were
natural components of salmon ecosystems (i.e.,
they had little to do with aquaculture-to-wild
transmission).
To study the effects of pathogens on wild
migratory fish in freshwater and marine
environments, researchers in the SSHI
employed other ecological approaches. They
paired pathogen-screening gill biopsy samples
with telemetry tracking studies, performed
holding studies to assess effects of high water
temperatures and stress from catch-and-release
fisheries on disease progression, and evaluated
predation-related consequences of disease. A wide
range of new knowledge has come from these
studies, including:
1. Wild fish with a high burden of pathogens,
or detection of specific pathogens, are more
likely to die (Furey et al., forthcoming);
Jeffries et al. 2014a; Miller et al. 2014; Teffer
et al. 2017);
2. Yearling Chinook Salmon carry higher
prevalence and loads of agents than sub-
yearling fish, of interest because in British
Columbia the yearling Chinook Salmon
populations are in the most dramatic decline
(Tucker et al. 2018);
3. Sockeye Salmon smolts from a year of record
low productivity carried higher prevalence
and infective burden of pathogens than those
from an average year (Nekouei et al. 2018).
Models are currently under development that
use up to 10 years of infective agent data
to identify agents correlated with cohort
strength in Sockeye, Chinook, and Coho
Salmon;
4. Infectious profiles in smolts increase their
risk from predation, with the presence of
specific agents and overall burden of agents
a predictor of risk of being consumed by
predators (Miller et al. 2014; Furey et al.,
for thcoming);
5. Adult salmon compromised by stress and/or
disease migrate faster than fish that appear
to be healthier. These fish “push” to migrate
faster and arrive on the spawning grounds
earlier, but die prematurely in much higher
numbers (Miller et al. 2011; Drenner et al.
2017);
6. The environment in which salmon are
sampled has a stronger effect on infectious
profiles than stock, hatchery-wild, or life-
history type (Tucker et al. 2018; Thakur et al.
2019);
7. Many pathogens replicate faster in higher
water temperatures, resulting in stronger
disease dynamics (Teffer et al. 2018);
8. Side-by-side tracking and holding studies
reveal that the same pathogens that affect
juveniles are associated with premature
mortality in adult salmon (Teffer et al. 2018;
Bass et al. 2019).
In evaluations of pathogen distribution between
aquaculture and free-ranging fish, SSHI
researchers found that free-ranging salmon
carry a high diversity of fungal and protozoan
parasites, many of which are from the freshwater
environment. There is evidence that some of
these parasites can cause disease and reduce
the survival of wild fish (Jeffries et al. 2014a;
Tucker et al. 2018; Wang 2018; Thakur et al.
2019). Conversely, salmon in marine net pens
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https://doi.org/10.15447/sfews.2020v18iss3art2
carry a higher diversity of bacterial pathogens
in saltwater (Laurin et al. 2019), most of which
are known to cause disease on farms. Current
efforts are focused on investigating whether
these bacterial agents can be transmitted to free-
ranging fish in the vicinity of farms. Finally,
research has shown that aquaculture and free-
ranging fish carry a diversity of viruses, most of
which were not previously known.
The SSHI has been successful in large part
because of constant communication among
scientists, regulators, and the public. The science
agencies in the initiative have regular briefings
with managers and regulators, including the
Fisheries Minister’s and Prime Minister’s offices;
are actively working with salmon enhancement
programs and consulting with industry; and
have strong public, non-governmental agency,
and First Nation Support for evidence-based
science. To effectively communicate findings, lead
agencies give regular presentations at scientific
conferences and to fisheries and aquaculture
advisory boards and media groups.
RECOMMENDATIONS FOR BUILDING AN
INFECTIOUS AGENT MONITORING PROGRAM IN
THE CENTRAL VALLEY
Infectious diseases have been routinely
documented in Central Valley salmon in nature.
Yet, a monitoring and modeling framework is
lacking to quantify the extent to which disease
may play a significant and unrecognized role
in salmon population dynamics. State and
federal agencies in California have invested
significant resources to improve salmon survival
and maintain sustainable populations. These
resources are put toward efforts to restore
habitat, manage flows and temperature, reduce
predation, and monitor juvenile fish emigration
at key locations. Despite these efforts and the
commitment of resources, salmonid populations
remain at a fraction of historical population sizes
(NMFS 2016a, 2016b). As agencies implement
new methods to identify monitoring metrics
intended to improve salmonid survival, such
as Structured Decision Making and Life-Cycle
Models (Zeug et al. 2012; Hendrix et al. 2014),
existing monitoring programs could be improved
by including a comprehensive fish-condition and
disease-monitoring component to help identify
factors that limit salmonid population recovery
in the Central Valley (Johnson et al. 2017). This
is critical because there may be years where
habitat conditions favor pathogen prevalence,
salmon susceptibility to infection, and increased
prevalence of infection. Conditions such as warm
water temperatures with reduced flows may
represent such years. Establishing a robust disease
monitoring, research, and modeling framework in
the Central Valley will be particularly important
to ensure actions intended to recover salmon
are indeed mitigating for the direct and causal
stressors.
Participants of the UC Davis Salmon Disease
Symposium workshop agreed that multi-faceted
monitoring approaches provide the most useful
information. Data collection focused on both the
distribution of pathogens (e.g., water sampling)
to detect exposure landscapes in concert with
monitoring and sentinel fish condition to
understand salmon-disease dynamics would
provide more value than a single type of data
source alone. Novel molecular techniques utilizing
eDNA, qPCR, and high-throughput sequencing
will improve data resolution when paired with
traditional methods such as counting mature
spores or observing signs of clinical disease.
In addition, there are a number of opportunities
to use data that have already been collected from
established monitoring programs. The integration
and evaluation of these data sets can provide a
foundation for formulating hypotheses, and guide
the design and implementation of a well leveraged
disease monitoring framework. For example,
time-series of salmon survival across the out-
migration route from acoustic telemetry studies
could be coupled with pathogen prevalence data
and used to model prevalence of infection.
Although health monitoring of fish at any of
the current Central Valley sampling sites is not
consistent, a robust system-wide juvenile salmon
monitoring framework is already in place in the
Central Valley. There are many opportunities
SAN FRA NCISCO ESTUARY & WATE RSHE D SCIEN CE
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VOLUME 18, ISSUE 3, ARTICLE 2
to leverage these already existing monitoring
efforts by incorporating additional data or
sample collection (e.g. non-lethal gill tissue
sampling) at rotary screw traps or beach seine
sites along the salmon out-migration corridor.
This kind of sequential sampling
—
of prevalence
of disease in salmon across space and over time
in monitoring locations where salmon abundance
is estimated
—
is one powerful approach used to
quantify mortality in salmon populations from
disease (Figures 1 and 2). Many of these fish
monitoring stations have existed for decades.
Designing a disease monitoring framework,
with agreed-upon protocols implemented within
already existing fish or environmental sampling
efforts, may provide the additional benefit of
being able to hindcast models to help understand
what happened in the past. Streamlining data
collection into already existing programs will
also reduce the need for obtaining permits, travel,
and staffing.
Based on the case studies from other salmon
systems highlighted in this paper and the
workshop, we recommend initiating a multi-
year watershed-wide monitoring effort to
establish a reliable baseline for the distribution
of infectious agents and disease prevalence
in the Sacramento River watershed (Figure 5).
Ideally, this monitoring framework would use the
following sampling approaches: (1) periodic water
sampling at key longitudinal locations to assess
the presence and abundance of infectious agents
at different times or under varying conditions;
(2) sampling of wild juvenile fish from already
existing rotary screw traps to provide real-time
information on prevalence of infection
—
using
both simple non-lethal visual metrics as well as
tissue sampling for histopathology and genetic
analysis; and 3) deploying groups of caged
sentinel fish at key longitudinal locations in
different regions of the watershed through time
to quantify the relationship between waterborne
pathogen levels and disease. This three-tiered
data-collection approach would provide the
necessary data to parameterize and develop
infectious-disease transmission models linked to
key environmental co-variates. These baseline
data and decision-support models may identify
critical water conditions or infective locations,
and inform avenues of future research to develop
management tools to mitigate vulnerabilities from
infectious disease.
To date, what we do know about salmon disease
in the Central Valley has come from different
research groups and agencies temporarily funding
small-scale studies. To build robust models that
describe disease dynamics at the population scale
with a focus on management actions that can
reduce the effect of disease, a holistic monitoring
and research approach with sustained funding
is required. There must be sufficient resources
to synthesize data in addition to data collection,
sample processing, and data reporting into an
accessible database. Finally, creating a formal
forum for salmon disease researchers to regularly
meet, share data, and provide guidance on the
implementation of a watershed-scale infectious
disease monitoring plan would be of tremendous
benefit to advancing and communicating the
current state of knowledge within and outside of
the scientific community.
ACKNOWLEDGMENTS
This article would not be possible without the
contributions of the participants of the Salmon
Disease Workshop including Esteban Soto, Dave
Hillemeier and Jeffrey Fisher. We would like to
thank Nir Oskenberg and Eva Bush of the Delta
Stewardship Council and Shauna Oh of the
University of California, Davis for assistance with
organizing the workshop. Thank you to Nicholas
Demetras for providing excellent technical
and stylistic feedback on the manuscript.
Funding for this article was provided by UC
Davis Coastal and Marine Sciences Institute,
the Delta Stewardship Councils Delta Science
Program, and The Metropolitan Water District of
Southern California. Funding from the California
Department of Fish and Wildlife, Proposition 1,
(grants #P1696002 and P1890651) to NAF
and REC supported their contribution to this
manuscript. Funding for research in the Klamath
Basin case study was provided by the Bureau of
Reclamation, US Department of Interior, as part of
its mission to manage, develop, and protect water
23
SEPTEMBER 2020
https://doi.org/10.15447/sfews.2020v18iss3art2
and related resources in an environmentally and
economically sound manner in the interest of the
American public. Funding was provided through
Interagency Agreement # R15PG00065 to Oregon
State University. The views in this publication are
the authors’ and do not necessarily represent the
views of Reclamation.
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