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Klamath River Fish Health Studies
Oregon State University, GSA Contract #GS09T13BHD0052
First Reporting Cycle April 01, 2013 - June 30, 2014
ANNUAL REPORT
Principal Investigator: Jerri Bartholomew
Co-principal Investigator: Sascha Hallett
Contributing Scientists: Rich Holt, Julie Alexander, Gerri Buckles, Adam Ray, . Ryan Craig, Stephen Atkinson
Confluence of the Trinity River and the Klamath River mainstem.
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Summary The myxozoan parasite Ceratomyxa shasta infects the intestine of salmonid fish and is responsible for
high mortality in juvenile salmon in the Klamath River basin. This report describes results of monitoring
conducted in 2013. The Bartholomew Lab at Oregon State University has been monitoring the spatial
and temporal abundance of the parasite in that basin for over five years using sentinel fish exposures,
river water sampling and polychaete sampling. Also described here are several models that are being
developed to better predict disease effects under various conditions.
Assay of water samples collected from monitoring sites showed that parasite levels in 2013 were above
levels detected in 2011 and 2012. Parasite density increased to about 1 spore/L in May and June in the
infectious zone but remained below 10 spores/L, which is the threshold that would result in significant
mortality in Chinook and coho salmon. Despite the low levels, there were two interesting trends
detected: the shift of the most highly infectious area of the river from near Beaver Creek (Rkm 258) to
Seiad Valley (Rkm 207) and the high levels of parasite below the Trinity River at Tully Creek (Rkm 62).
Parasite density at Tully Creek was above 5 spores/L beginning in August and peaked at 10 spores/L in
October.
Results of sentinel fish exposures generally supported the water sampling data, with low mortality (2.9%
- 12.9%) in Chinook salmon held at Orleans (Rkm 90), Seiad Valley and Beaver Creek during May and
June. Results of coho sentinel exposures showed higher than expected loss, with mortality between 25
and 44.8% at Beaver Creek and Seiad Valley. The higher loss in this species is explained by an increase in
parasite genotype II (causes mortality in coho) in water samples compared with 2012, although
genotype I (causes mortality in Chinook) was still predominant. Coho mortality was also more affected
by temperature. Mortality in both species was higher at the downriver sites, supporting the shift of the
infectious zone suggested by the water sample data. Sentinel exposures at Tully Creek suggest that both
genotype I and genotype II were present. For exposures in the Williamson River, in the upper Klamath
basin, we had predicted that changes in stocking practices would result in decreasing levels of the
parasite. However, sentinel exposures of susceptible rainbow trout in the Williamson River resulted in
high mortality, as in previous years.
Year-round average polychaete densities were highest (>10,000/m2) in river sections in the Klamath
River above Iron Gate Dam in the JC Boyle bypass reach and Keno eddy, and they maintained this
density year-round. Immediately downstream of Iron Gate Dam (I-5, Tree of Heaven and Beaver Creek)
polychaete densities were lower and there was a seasonal pattern, with peak densities in summer that
exceeded the highest densities at all other sites with the exception of JC Boyle. Densities declined
through fall and winter and began to increase in spring. Polychaete densities below the Scott and
Salmon Rivers (Seiad Valley, Orleans) were intermediate, and the seasonal pattern was not as
pronounced as in populations in the mid-section of the river. Infection prevalence was highest in winter
samples, especially from populations collected from the lower river sites (Seiad Valley, Orleans). This
likely reflects the higher proportion of adults that likely became infected in fall. Detection of higher
density populations with infected individuals at these lower river sites supports the observation of a
shift in the infectious zone downriver. Elevated discharge during the winter and spring of 2011 is
hypothesized to have reduced the suitability of some habitats for the polychaete and this may have
contributed to the downriver shift in the infectious zone.
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Several models are being developed independently and through collaboration with the USFWS and
USGS to enable better prediction of disease-related mortality under current and future scenarios and to
identify management actions that could decrease disease effects. We developed mixture cure models
that quantified the effects of water temperature, discharge, and parasite concentration on parasite-
induced mortality for both Chinook and coho salmon. These models provide estimates of daily survival
rates and of population level parasite-induced mortality that can be incorporated into salmon
population and production models. This additional information facilitates a better understanding of
juvenile salmon survival in the Klamath River, which will allow managers to better account for the
effects of disease dynamics. This is the first known application of a mixture cure model to a wildlife
pathogen and provides a powerful yet flexible analytical method that could be used to manage other
populations.
We are continuing to develop an epidemiological model for C. shasta and preliminary use of the model
shows that management actions should target more than a single parameter in the life cycle of C.
shasta. Existing data gaps currently limit the identification of how different parameters will respond to
changes in environmental factors but provides an excellent framework for directing future studies and
management actions. To predict future disease patterns, we have run simulations for two different
climate scenarios, including CCCMA and NCAR. Following a low magnitude peak flow, e.g., 2010, the
probability of polychaete presence in study reach 2 was modeled at 39.8% and for an intermediate
magnitude peak discharge, modeled at 30.4%. Under both the CCCMA and NCAR, the probability of
polychaete presence is reduced under higher peak discharges. Additional climate scenarios will be
examined using this approach as we continue to refine the predictive model for polychaete hosts.
Also in collaboration with the USFWS, we have developed two-dimensional hydraulic models (2DHM)
and a statistical model for predicting polychaete distribution and density. We predicted the distribution
of M. speciosa under several alternate hydrographs (1,200cfs and 7,950 cfs) to simulate dry and wet
water year scenarios. Our preliminary results suggest that manipulating the hydrograph could influence
distribution of polychaete hosts because the probability of polychaetes was significantly reduced (>25%)
between the wet and dry scenarios. Validation of the model predictions using real data collected at
both the low and high peak discharge scenarios are needed before we can evaluate whether
manipulation of the hydrograph may in turn influence prevalence of C. shasta and disease in salmonids,
but the preliminary results are very exciting.
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Contents Research outcomes ....................................................................................................................................... 6
D.2.1 Develop a long-term dataset on disease severity for Chinook and coho salmon that
encompasses years differing in the magnitude and timing of flows, temperatures during spring and
summer, and adult returns. The following metrics will be measured at established index locations in
the upper and lower Klamath River during each study year. ................................................................... 6
D.2.1 (a) Quantification of parasites in water samples to include data collection during spring out
migration. .............................................................................................................................................. 6
D.2.1 (b) Estimate infection and disease severity in sentinel Chinook and coho salmon. ................. 11
D.2.1 (c) Characterize density and population of the invertebrate (polychaete) host. ...................... 27
D.2.2 Develop an index for predicting disease severity for Chinook and coho salmon that is validated
by correlating data on infection prevalence and disease severity in each fish species with genotype-
specific spore densities in water collected at each site. ......................................................................... 33
D.2.2 (a) Develop a method for high throughput genotyping of C. shasta ........................................ 33
D.2.2 (b) Develop an index for predicting disease severity for Chinook and coho salmon ................ 35
D.2.3 Produce a validated epidemiological model that identifies sensitive parameters in the host-
parasite life cycle, simulates the effect of potential management strategies on the different stages of
the life cycle, and predicts disease severity in juvenile salmonid population under different parasite
densities, temperatures, flows). The following data gaps will be investigated: ..................................... 43
D.2.3 (a) Magnitude of adult myxospore input .................................................................................. 43
D.2.3. (b) Parasite source below the Trinity River confluence............................................................ 47
D. 2.3 (c) Recolonization rate of polychaetes ..................................................................................... 49
D.2.4 Produce a validated model of polychaete distribution and density for different scenarios
predicted for discharge manipulations, water years, and dam removal. ............................................... 51
D.2.4 (a) Add polychaete density and infection prevalence data to the physical model to predict the
amount, suitability and stability of habitat under various stream flow regimes. .............................. 51
D.2.4 (b) Validate the model to target variable flows and different polychaete population dynamics.
Refine the model as necessary. .......................................................................................................... 52
D.2.5 Develop and synthesize a dataset, encompassing environmental risk factors and their
relationship with polychaete host ecology, to facilitate predictions about how polychaete densities
and infection levels may change under future climate and temperature regimes. ............................... 54
D.2.6 Regular dissemination of research findings to provide stakeholders, managers, researchers and
the general public ready access to current information and historical datasets pertinent to C. shasta in
the Klamath River. ................................................................................................................................... 56
D.2.6 (a) Preliminary Result Summaries ............................................................................................. 56
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D.2.6 (b) Annual Reports: The contractor will provide Reclamation an annual report of research for
this study, per the schedule listed below. .......................................................................................... 56
D.2.6 (c) Website to be maintained by the contractor for dissemination of results and project
information to the public. ................................................................................................................... 56
D.2.6 (d) Annual Klamath River Fish Health Workshops will review results of disease research, and
will be coordinated by the contractor. ............................................................................................... 57
D.2.6 (e) Annual project coordination meeting with project collaborators. ...................................... 57
D.2.6 (f) Submit findings for publication in peer-reviewed scientific journals. .................................. 57
References .............................................................................................................................................. 59
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Research outcomes
D.2.1 Develop a long-term dataset on disease severity for Chinook and coho salmon that encompasses
years differing in the magnitude and timing of flows, temperatures during spring and summer, and adult
returns. The following metrics will be measured at established index locations in the upper and lower
Klamath River during each study year.
D.2.1 (a) Quantification of parasites in water samples to include data collection during spring out
migration.
D.2.1 (a) Methods
Water samples were collected by ISCOs (automatic samplers) from three Klamath River mainstem sites,
the I5 rest area (KI5), Orleans (KOR), and Tully Creek (KTC) once a week from March through October
and weekly throughout the year at two mainstem sites, upstream of the confluence with Beaver Creek
(KBC) and Seiad Valley (KSV) (Figure D.2.1a1). An additional ISCO collected water samples weekly at the
Kinsman fishtrap (KMN) through the outmigration period, March to May.
Figure D.2.1.a.1. Klamath River index sites for 2013 with site abbreviations and river kilometers (Rkm).
The use of automated water samplers and the field assistance provided by the Karuk and Yurok tribes
allowed weekly collections which represented 24 hr composite water samples. The ISCOs were
programmed to begin sampling at 8 am and 1 L was collected from the river every 2 hr for 24 hr, then
the total sample was mixed manually and 4 x 1 L samples taken. All samples were chilled until filtered,
within 24 hr of collection.
Water samples were also taken at the six sentinel fish sites during the exposures in May and June; at
Beaver Creek and Seiad Valley in April and September; and at Seiad Valley and Tully Creek in July. Four 1
L samples were collected manually at the start and end of each exposure.
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DNA was extracted from three of the four replicate filtered 1 L samples collected at each site and time
point using a commercial kit, then assessed with qPCR for the presence of C. shasta DNA. Each sample
was run in duplicate and sample pairs with values differing by more than 1 Cq were rerun. Samples with
1 undetected well and 1 detected well of less than Cq 38 were rerun. Samples that were undetected
(both wells) were assigned a Cq value of 42 and included in the site average. Positive (tissue or artificial
template) and negative (molecular grade water) controls were included in each qPCR run. An inhibition
test (IPC) was performed on one replicate sample from each site and time point. Samples with inhibition
less than 2 Cq had their final Cq value adjusted by this level of inhibition whereas samples with inhibition
greater than 2 Cq were diluted and rerun. Each data point on a graph represents the average of 3 1 L
water samples collected at that time point. Following the guidelines of Bustin et al. 2009, the term
‘quantification cycle’ (Cq) is used for the cycle number at which a sample fluoresces and crosses a
standard threshold.
D.2.1 (a) Results and discussion
Temporal patterns of parasite distribution were consistent with previous years in the mainstem Klamath
River with the onset of spore presence in April and densities above 1 spore/L in May. Spore density was
near 5 spores/L at Seiad Valley and Tully Creek from May through June while Beaver Creek had sporadic
parasite levels >1 spore/L in late June. Kinsman parasite level spiked in mid-April to 5 spores/L and then
remained around 1 spore/L for the remainder of outmigration. Tully Creek parasite density was >5
spores/L from August to November and had a peak density of >10 spores/L in early October. Orleans
parasite levels were above 1 spore/L from August to November (Figure D.2.1a2).
Parasite density was higher in 2013 than observed in 2012 (Figure D.2.1a3). In 2012, parasite levels at
Beaver Creek, Seiad Valley and Orleans remained below 1 spore/L and at Tully Creek levels were
sporadically above 1 spore/L. Parasite levels at the Kinsman trap had increased presence in mid-May
and mid-June, later than that seen in 2013.
Parasite levels at all sites decreased to less than 1 spore/L in July 2013. Temperature data collected from
HOBO data loggers attached to the ISCOs intake lines showed that temperatures rose above 21o C for an
extended period of time during July (Figure D.2.1a4). The impact of temperature on spore production
and viability has been discussed in previous studies and is a possible factor for the drop in spore density
seen in July 2013: Temperature increases have been correlated with an increase in spore production in
spring and with a decrease in spore density in summer, suggesting a threshold. The threshold may be
related to loss of viability and disintegration of delicate actinospore stages at higher temperatures.
The spatial distribution of parasite in 2013 showed a shift in the peak parasite density relative to 2008-
2009. In previous years the highest density (hot spot) of parasite had been at Beaver Creek.
Comparison of the monthly average parasite density for June from 2008-2013 indicates that the density
at Beaver Creek in 2013 is lower than in all years except 2012. While parasite density at Seiad Valley in
the same 5 year window was higher in 2013 than all of the years except 2009. Parasite levels also
increased at Orleans in 2013. This suggests that the “hot spot” for parasite density has shifted
downstream from Beaver Creek to Seiad Valley (Figure D.2.1a5). Densities at Tully Creek continued to
remain high relative to other sites in 2013, with levels similar to those measured at Seiad Valley in the
first half of the year but levels highest at Tully Creek from August onwards.
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FIGURE D.2.1.a.2. Density of Ceratomyxa shasta in water samples collected at six Klamath River mainstem sites in
2013. Each data point is the average Cq of 3 x 1L water samples. A lower Cq value indicates more parasite is
present. The dotted line represents approximately 1 spore/L. Site abbreviations are explained in Figure D.2.1.a1.
Figure D.2.1.a.3. Parasite levels were higher in 2013 than in previous years 2011 (A) and 2012 (B)
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Figure D.2.1.a.4. A temperature increase in July 2013 coincided with parasite levels dropping below 1 spore/L at KBC (A), KSV (B), and KOR (C).
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Figure D.2.1.a.5. Average monthly parasite level for 2008-2013. Parasite density in June 2013 (black line with orange dots) was lower at KBC (A) and higher at KSV (B) than in previous years.
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D.2.1 (b) Estimate infection and disease severity in sentinel Chinook and coho salmon.
D.2.1 (b) Methods
Sentinel fish exposures were conducted according to the sites and schedule in D.2.7 and D.2.8. There
were five exposures for 72 hr each at up to eight index sites (Figure D.2.1.1) in the lower and upper
Klamath River mainstem in 2013 during the following dates: April 19-22, May 14-17, June 25-28, July 16-
19 and September 20-23. As in previous years, known C. shasta-susceptible rainbow trout stock from
Roaring River Hatchery (Oregon Department of Fish and Wildlife) were held at all sites. Klamath River
fall Chinook from Iron Gate Hatchery (IGH) (California Department of Fish and Wildlife) were held at all
sites except for one location, the Lonesome Duck Resort on the Williamson River. A limited number of
coho salmon juveniles from Iron Gate Hatchery were held near Beaver Creek and Seiad Valley in May
and June and Tully Creek in July. Also, Trinity River Hatchery Chinook were held near Tully Creek in July.
Generally, the number of each fish species held in live cages other than when noted was 40 rainbow
trout, 40 IGH fall Chinook salmon and 30 coho salmon. In April, the sentinel juvenile fish were
approximately 0.5-1.5g, in May 2.0-5.0g, June 3.0-7.0g, July 4.0-15.0g and in September 15.0-20.0g.
Following the river exposure, the fishes were transported to the OSU John L. Fryer Salmon Disease Lab
(SDL), Corvallis, Oregon and held in well water at a water temperature similar to the river water
temperature during the 72 hr exposure. However, if river water temperatures averaged greater than
18°C, fish were maintained in no greater than 18°C water post-exposure because attempting to hold fish
at higher water temperatures such as 20-22°C made infections of Flavobacterium columnare, the cause
of columnaris disease, difficult to prevent. During the last hour of transport, the fish were given 1-2
ug/mL Furanase bath in their transport containers to prevent columnaris disease. Also, within one to
two weeks of their arrival at the SDL, all fish were treated with formalin baths and oxytetracycline
medicated food for prevention of external parasites and bacterial infections. Control groups of each fish
stock not exposed at the Klamath River sites were included for each monthly exposure and given the
same preventative treatments as the river exposed fish. All groups of fish were monitored daily for C.
shasta clinical disease signs for two months. Moribund fishes were euthanized and examined
microscopically for C. shasta-infection by observing wet mounts of lower gut material; if no myxospores
were observed then intestinal samples were collected for C. shasta PCR testing. A subsample of
moribund fish from each group was also necropsied for other parasite and bacterial infections to
eliminate those as causes of loss. Mortality percentages given in the results section below represent
total fish loss with C. shasta-infections determined microscopically or by PCR testing from fish that
succumbed later than five days after they were brought to the laboratory.
The effect of post-exposure rearing water temperature on C. shasta infections in juvenile Chinook and
coho salmon and rainbow trout was also studied. During the April, May, June and September exposures
in the Klamath River near Beaver Creek, 80 Chinook and rainbow trout were exposed and then each
group divided into two groups and held at 13 and 18°C upon arrival at the SDL. For coho salmon, 60 fish
were exposed then distributed into two tanks at each temperature and only in May. In June, there were
only sufficient coho salmon to hold at one temperature (18°C). In July, 80 rainbow trout exposed near
Seiad Valley were brought to the SDL and divided into two tanks and held at either 13 or 18°C. No
exposed Chinook survived due to high river water temperatures at Seiad Valley.
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Methods specific to each of the exposures are listed below:
April 19-22 exposures: Susceptible rainbow trout and IGH fall Chinook were exposed in the Klamath
River at two lower mainstem sites, upstream of the Beaver Creek confluence (KBC: 80 of each species)
and near Seiad Valley (KSV; 40 of each species). The river water temperatures during exposure ranged
from 12-13°C so all of KSV and half of the KBC fishes were held at 13°C upon return to the laboratory;
the remainder were held at 18°C to compare the effect of post-exposure rearing water temperature.
May 14-17 exposures: Susceptible rainbow trout and IGH fall Chinook were exposed at six sites including
the lower Williamson River (WMR-NC) at the confluence of Williamson River and Upper Klamath Lake on
Nature Conservancy land, Keno Eddy (KED) above JC Boyle Dam, near the I5-bridge below Iron Gate Dam
(KI5), near Beaver Creek (KBC) at Fisher's RV Park, Seiad Valley (KSV) at Mr. W. Johnson's land and
Orleans (KOR) at Sandy Bar Resort. The KI5 site was chosen in 2013 as an alternative to the Klamath
River Country Estates site above Klamathon Bridge site that was no longer available. The KI5 site is 10
RKm downstream of the Klamath River Country Estates site that had been used in previous years. IGH
coho juveniles were held near KBC and KSV. At KBC, three groups of 50 fish each of Chinook were held
in separate live cages to evaluate variation in infection rates among the fish in cages. Upon return to the
SDL, half of each of the Chinook groups were placed at either 13° or 18°C (to approximate ambient river
temperature) and then monitored for clinical disease signs of C. shasta. The rainbow trout (80 fish) and
coho (60 fish) exposed at KBC also were divided and half held at each temperature. Fish groups from
other sites were held at 18°C.
June 25-28 exposures: Fishes were placed at seven sites including two locations on the lower
Williamson River (Nature Conservancy at the mouth of the river, WMR-NC and Lonesome Duck Resort 9
Rkm upriver, WMR-LD) and at the same other four sites as the May exposure. Susceptible rainbow trout
and Chinook from IGH were held at six sites but only rainbow trout were exposed at the WMR-LD site.
Coho juveniles from IGH were held only at KBC and KSV. At KBC, as in May, three groups of 50 fish each
of Chinook were held in separate live cages to evaluate variation in infection rates among the fish in
cages. Upon return to the SDL, half of each of the Chinook groups were placed at either 13° or 18°C and
then monitored for C. shasta. Also, the rainbow trout (80 fish) exposed at KBC were divided and held at
each temperature. Water temperatures averaged 14°C on the Williamson River to nearly 20°C at KBC.
Fish groups were held at 18°C, except for the KBC Chinook and rainbow trout water temperature
comparison groups which were held at 13°C.
July 16-19 exposure: Susceptible rainbow trout and IGH fall Chinook were exposed at two lower Klamath
River mainstem sites, KSV and below the confluence of the Trinity River near Tully Creek (KTC). Four
groups of 25 Chinook each and two groups of 40 rainbow trout each were held in separate live cages at
KSV. At KTC, with the assistance of Hoopa and Yurok fishery personnel, 40 Trinity River Hatchery (TRH)
and IGH Chinook, 40 rainbow trout and 30 IGH coho were placed in live cages. Surface water
temperatures at the time fish were placed in the live cages were higher than 23°C. After the 70 hr
exposure at KSV, the Chinook in all four cages had died. The rainbow trout were found stressed and
some were dead. The temperature logger at KSV recorded maximum temperature during the exposure
of 25.9°C. At KTC, a few fish were dead in most groups but the remainder survived. To avoid excessive
loss from columnaris disease, all groups from the July exposure were held at 18°C except for one
rainbow trout group from KSV which was held at 13°C.
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September 20-23 exposure: Susceptible rainbow trout and IGH Chinook were exposed in the Klamath
River at two lower mainstem sites, upstream of the Beaver Creek confluence (KBC: 80 of each species)
and near Seiad Valley (KSV; 40 of each species). The river water temperatures during exposure averaged
18°C, therefore all of KSV and half of the KBC fishes were held at 18°C upon return to the laboratory; the
remainder were held at 13°C to compare the effect of post-exposure rearing water temperature.
D.2.1 (b) Results and Discussion
Average water temperatures during the 72 hr exposures at all sites and the laboratory post-exposure
rearing temperature are shown in Table D.2.1.b.1. Average water temperatures were 13°C during the
exposure in April, ranged from 16-18°C in May, 14-20 °C in June, 23-24°C in July and 18°C in September.
The maximum laboratory rearing water temperature of 18°C was chosen to avoid loss from F.
columnare. For comparison, Figure D.2.1.b.1 shows the average daily water temperature during the
months of March to September near Beaver Creek for the 2008-2013 years. Water temperatures in the
spring of 2013 appear to be generally higher than previous years including the years of 2008 and 2009
when juvenile Chinook losses were relatively high.
Table D.2.1.b.1. Average Klamath River water temperature (°C) at sentinel sites during the 72 hr fish in 2013.
Site April 19-22
May 14-17
June 25-28
July 16-19
Sept 20-23
Williamson R-NC 16 14
Williamson R-LD 14
Keno Eddy 17 18
Klamath R I5 18 19
Beaver Creek 13 18 20 18
Seiad Valley 13 17 20 24 18
Orleans 16 19
Tully Creek 23
Lab rearing 13 18 18 18 18
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Figure D.2.1.b.1. Average daily water temperatures during the months of March-September during the years 2008-2013 at the sentinel site near Beaver Creek on the Klamath River mainstem.
Results of the sentinel exposures in April, May, June, July and September are summarized in Table D.2.1.b.2 for all exposures in 2013 and are shown for each month in Figures D.2.1.b.2- D.2.1.b.4. The percent loss represent fish that were moribund or dead and were removed from the tanks during the post-exposure rearing, not including any loss that occurred in the first five days. These fish were found to be positive for infections of C. shasta either by microscopic observation for myxospores in gut wet mounts or PCR testing of gut tissue. The results for each exposure are discussed below after each figure along with a comparison with previous year’s results.
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TABLE D.2.1.b.2. Percent loss attributable to infection by C. shasta by site and fish species in 2013 following a three-day river exposure. Fishes are held at ambient Klamath River temperature at the Salmon Disease Laboratory and monitored for disease signs for two months post-exposure. Numbers represent total loss from 5 days after the fish were brought to the laboratory and are based on the observation of myxospores in wet mounts and include PCR testing on all microscopically negative fish. ChF = Fall Chinook, TRH = Trinity River Hatchery.
Exposure dates Exposure site IGH Chinook IGH coho Rainbow trout TRH Chinook
April 19-22 KBC-13°C 0 6.4 KBC-18°C 2.6 21.1 KSV 0 25
May 14-17 WMR-NC 0 100 KED 0 65 KI5 0 43.6 KBC-13°C 0,0,0 0 82.1 KBC-18°C 0,0,0 25 94.9 KSV 2.9 30 100 KOR 9.8 97.8
June 25-28 WMR-NC 0 100 WMR-LD 94.9 KED 0 91.2 KI5 0 39.6 KBC-13°C 0,0,0 65.1 KBC-18°C 7.4,0.8.0 28.6 95.0 KSV 12.9 44.8 97.5 KOR 2.5 100
July 16-19 KSV-13°C 26.3 KSV-18°C 77.8 KTC 3.1 4.3 60.0 2.9
September 20-23 KBC-13°C 0 17.9 KBC-18°C 0 30 KSV 0 70.7
April 19-22 exposure (Figure D.2.1.b.2): At termination, on June 26 after 65 days rearing at the SDL, no
Chinook held at 13°C died of C. shasta. Only one Chinook (2.6%) from the group held at 18°C with a C.
shasta eye infection was detected at KBC (Table D.2.1.b.2). No Chinook exposed in the river at KSV died.
Rainbow trout exposed at KBC and held at 18°C incurred a 21.1% loss from C. shasta, and at 13°C, 6.4%.
Rainbow trout exposed in the river at KSV had a 25.0% loss. All groups of fishes from the April exposures
experienced very low losses from C. shasta.
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Figure D.2.1.b.2. Per cent mortality with C. shasta infections of rainbow trout (Rbt) and IGH fall Chinook salmon exposed April 19-22, 2013 at two index sites in the lower Klamath River and held for 65 days post-exposure at 13°C.
Figure D.2.1.b.3. Comparison of percent loss from C. shasta infections in rainbow trout (Rbt) and IGH Chinook (Chf) exposed in 72 hr sentinel studies near Beaver Creek during April 2009-2013.
When comparing the C. shasta loss of IGH Chinook exposed in April during 2013 with previous years
since 2009 (Figure D.2.1.b.3) at KBC, in 2009 about 14% of the Chinook died. No Chinook have died in
April since 2009. Also, in April 2009, the rainbow trout loss was just under 100% and about 80% in 2010
but very low in 2011 and 2013.
May 14-17 exposure: The May exposure groups were terminated on July 24, at 68 days post-exposure.
No Chinook exposed at WMR-NC, KED, KI5 or KBC died, while 2.9% of KSV fish with C. shasta infections
died post-exposure and 9.8% of fish exposed at KOR. The coho salmon held at 18°C post-exposure were
the most severely affected with 25% loss with C. shasta infections in the KBC group and 30.0% loss in the
KSV group. No coho salmon exposed at KBC and held at 13°C post-exposure died. Rainbow trout
exposed at WMR-NC died the fastest post-exposure. The loss of rainbow trout at KED was 65%, a level
notably higher than in previous years. In the lower river, rainbow trout loss was about 43.6 % at KI5 and
greater than 94% at KBC, KSV and KOR. For this May exposure, the highest Chinook mortality occurred
at the most downriver exposure site (KOR) tested. Coho salmon were only exposed at two locations but
0 0 0
20
40
60
80
100%
C. s
ha
sta
mo
rtal
ity Rbt Chinook
KOR KSV KBC KI5 KED WMRnc
0 0 0 0 0 0 0
20
40
60
80
100
2009 2010 2011 2012 2013
% C
. sh
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Rbt Chf coho
17
their loss was greater than any Chinook salmon groups.
Figure D.2.1.b.4. Percent loss of rainbow trout (RbT), IGH fall Chinook and coho salmon with C. shasta infections after being exposed May 14-17, 2013 in selected Klamath River sites. The rainbow trout and Chinook salmon juveniles were exposed at all six locations while the coho salmon were exposed near Beaver Creek (KBC) and Seiad Valley (KSV). All groups were held for 68 days post-exposure at 18°C.
When comparing the May exposure loss from C. shasta in IGH Chinook and coho salmon at the upper
Klamath River sites, no infections were detected in the Williamson River (WMR-NC) and only a low
percent of infection was detected in Chinook in 2010 at KED. Sentinel exposures of coho salmon at the
WMR-NC were only done in May in two years and never was done at Keno Eddy. The greatest loss of
Chinook occurred in 2008 and 2009 at KBC and KSV and both locations are considered the "hot zone"
where more fish become infected than elsewhere in the lower river. In May 2010-2013 Chinook salmon
exposed for 72 hr had losses from C. shasta that were very low or none died. For coho salmon, the May
exposures resulted in the greatest percent infections at KBC in 2007 and 2008 and also at KSV in 2008. In
2013, coho salmon had a 25% C. shasta infection at KBC and 30% at KSV that was greater than coho
exposed in May of 2010, 2011 and 2012. Also, the sentinel coho were more affected in May 2013 than
the Chinook salmon.
Rainbow trout exposed at all locations in May 2013 became infected with C. shasta, however the fish
exposed at WMR-NC died from C. shasta most rapidly of all sites tested (Figure D.2.1.b.6). Rainbow
trout exposed at KSV and KOR died at the second fastest rate and losses were slowest near KI5.
0 0 0 0
0
20
40
60
80
100%
C. s
ha
sta
mo
rtal
ity
Rbt Chinook coho
KOR KSV KBC KI5 KED WMRnc
18
Figure D.2.1.b.5. Comparison of percent loss from C. shasta of juvenile IGH Chinook salmon (upper figure) and coho salmon (lower figure) at six index sites in May of 2007-2013. The Chinook salmon were exposed at most sites and most years, zeros indicate exposure but no loss. The coho salmon were not exposed at all locations each year and no exposures at KED have ever been done.
0 0 0 0 0 0 0 0 0 0 0 0 0 0
10
20
30
40
50
60
70
80
90
100
KOR KSV KBC KI5 KED WMR NC
% C
. s
ha
sta
mo
rta
lity
2007 2008 2009 2010 2011 2012 2013
0 0 0 0 0
10
20
30
40
50
60
70
80
90
100
KOR KSV KBC KKB KED WMR NC
% C
. s
ha
sta
mo
rta
lity
2007 2008 2009 2010 2011 2012 2013
19
Figure D.2.1.b.6. Percent survival of rainbow trout exposed in sentinel cages for 72 hr in May 2013 at six index sites in the upper and lower Klamath River.
June 25-28 exposure: The June exposure groups were terminated on August 29 and 30th (62 - 63 days post-exposure). During their rearing at the SDL, only one Chinook exposed at WMR-NC had died but C. shasta was not detected, either microscopically or by PCR (Figure D.2.1.b.7). No Chinook died following exposure at KED. One Chinook from KI5 died and no myxospores were found microscopically (PCR testing on this fish and one from the KBC coho salmon exposure was not possible, thus although no parasite was observed microscopically, we could not confirm that the two fishes were or were not infected). For the three groups of Chinook exposed at KBC and held at 18°C, overall C. shasta-loss was 5.2% (7.4% in one tank, 8% in the second and 0% in the third tank). Therefore, for these three groups of Chinook exposed at KBC in separate cages in close proximity, the loss was low (0-8%) from C. shasta. This test will be repeated in 2014. No Chinook from KBC held at 13°C post-exposure died. Loss of Chinook at KSV was 12.9% and 2.5% at KOR. Coho exposed at KBC incurred a 28.6% C. shasta loss compared to 44.8% for those exposed at KSV. At six sites, more than 91% of the rainbow trout exposed died; the exception was at KI5 (39.6%). Following the June exposure, more juvenile coho salmon died than Chinook salmon, similar to the May exposure. The susceptible rainbow trout died at 90-100% from C. shasta at six of the seven sites tested. Losses were lowest (39.6%) at the KI5 site.
The Oregon Department of Fish and Wildlife has stopped planting C. shasta susceptible rainbow trout into Spring Creek, a tributary in the Williamson River watershed, in 2011. A reduction in C. shasta infection in susceptible rainbow trout was not detected in the sentinel fish exposures at the WMR-NC and WMR-LDR sentinel sites tested in 2013.
20
Figure D.2.1.b.7. Percent mortality of rainbow trout (Rbt), IGH fall Chinook and coho salmon exposed June 25-28, 2013 at seven different Klamath River sentinel index sites and held for 62-63 days post-exposure at 18°C.
No C. shasta infections were detected in IGH Chinook and coho salmon exposed at the upper Klamath
River sites, in the Williamson River or KED, in June (Figure D.2.1.b.7). Sentinel exposures of coho salmon
at the Williamson River were only done in June in two years and never was done at KED (Figure
D.2.1.b.8). The greatest loss of Chinook occurred in 2007, 2008 and 2009 at KBC and KSV and both
locations are considered the "hot zone" where more fish become infected than elsewhere in the lower
river. In June 2010-2013, Chinook salmon exposed for 72 hr incurred low losses from C. shasta, i.e. less
than 20%. For coho salmon, the June exposures resulted in the greatest percent infections at KBC and
KSV in 2007, 2008, 2011 and 2013. In June 2013, coho salmon had a 28.6% C. shasta infection at KBC
and 44.8% at KSV that was greater than coho exposed in June 2010 and 2012. The sentinel coho were
more affected in June 2013 than the Chinook salmon.
0 0 0 0
20
40
60
80
100
KOR KSV KBC KI5 KED WMR NC WMR LD
% C
. sh
ast
a m
ort
alit
y
Rbt Chinook coho
KOR KSV KBC KI5 KED WMR-NC WMR-LD
21
Figure D.2.1.b.8. Comparison of percent loss from C. shasta of juvenile IGH Chinook salmon (upper figure) and coho salmon (lower figure) at six index sites exposed in June of 2007-2013. The Chinook salmon were exposed at most sites and most years, zeros indicate exposure but no loss. The coho salmon were not exposed at all locations each year and no exposures at KED have ever been done.
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
20
40
60
80
100
KOR KSV KBC KI5 KED WMR NC
% C
. sh
asta
mo
rta
lity
2007 2008 2009 2010 2011 2012 2013
0 0 0 0 0
20
40
60
80
100
KOR KSV KBC KKB KED WMR NC
% C
. sh
asta
mo
rta
lity
2007 2008 2009 2010 2011 2012 2013
22
Figure D.2.1.b.9. Percent survival of C. shasta-susceptible rainbow trout exposed at seven index sites in the Klamath River basin during June 25-28, 2013.
Figure D.2.1.b.10. Comparison of percent C. shasta mortality for rainbow trout exposed in June 2007-2013 at seven index sites of the Klamath River basin.
The June exposure of susceptible rainbow trout in the Klamath River basin at seven index sites
comparing the percent C. shasta mortality for 2007-2013 shows consistent high loss of fish from all sites
except at KED and at KKB below Iron Gate Dam. In some years, very low loss of rainbow trout was
observed at KED but in 2013 very high loss occurred (Figure D.2.1.b.10). Likewise, the KKB and KI5 sites
appear to be quite variable among years in the level of C. shasta infection.
0
20
40
60
80
100
�KTC �KOR �KSV �KBC �KKB �KED �WMR
% C
. sh
asta
mo
rta
lity
2007 2008 2009 2010 2011 2012 2013
23
Figure D.2.1.b.11. Percent mortality from C. shasta of rainbow trout (Rbt), IGH and TRH fall Chinook (ChF) and IGH coho salmon exposed July 16-19 at Tully Creek below the confluence of the Trinity River (KTC) and rainbow trout at Seiad Valley (KSV). The exposed fish were place in the river for 70-72 hr and held at the SDL for 62 post-exposure days at 18°C.
July 16-19 exposures: The July exposure groups were terminated on September 19 (62 days post-
exposure). Even though water temperatures were very high during the river exposure, only 2.9% of the
TRH Chinook, 3.1% of the IGH Chinook and 4.3% of the IGH coho exposed near KTC were found to be
infected with C. shasta (Figure D.2.1.b.11). At KSV, where only rainbow trout survived the exposure,
there was 77.8% loss at 18°C and 26.3% at 13°C. At KTC, 60% of the exposed rainbow trout had C. shasta
infections. With the high water temperatures that the sentinel fish encountered during their exposure, it
was surprising that loss from C. shasta was so low.
Figure D.2.1.b.12. Percent mortality of rainbow trout and IGH fall Chinook salmon exposed September 20-23, 2013 at two different Klamath River sentinel index sites, near Beaver Creek and Seiad Valley and held for 63 days post-exposure at 18°C.
September 20-23 exposure: The September exposure groups were terminated on November 25 (63 days
post-exposure). No loss occurred in the IGH ChF exposed at KBC or KSV in September (Figure D.2.1.b.12).
3.1 2.9 4.3
0
20
40
60
80
100
KTC KSV
% C
. sh
ast
a m
ort
alit
y Rbt ChF-IGH ChF-TRH coho
0 0 0
20
40
60
80
100
KOR KSV KBC KI5 KED WMR NC
% C
. sh
ast
a m
ort
alit
y
no coho exposed in September Rbt Chinook
24
The greatest loss from C. shasta infection in susceptible rainbow trout occurred in those held at 18°C at
the SDL after being exposed at KSV (70.7%) followed by KBC at 30%. Rainbow trout exposed at KBC and
held at 13°C had 17.9% loss with C. shasta infections.
Figure D.2.1.b.13. Comparison of percent loss from C. shasta of juvenile IGH Chinook salmon (upper figure) and coho salmon (lower figure) at six index sites exposed in September of 2007-2013. The Chinook salmon were exposed at most sites in September in 2007,2008 and 2009 but only near Beaver Creek and Seiad Valley in 2011, 2012 and 2013. Zeros indicate exposure but no loss. The coho salmon were not exposed at all locations each year and no exposures at KED have ever been done. No exposures of coho salmon were done in September of 2013.
Comparison of percent C. shasta infections in Chinook salmon exposed in September of 2007-2013 at
selected sites in the Klamath River basin shows that generally C. shasta infections in this month are very
low (Figure D.2.1.b.13). Only in 2007 and 2008 were sentinel Chinook found to become infected, but at a
low level. Exposures in other years were negative. High losses of coho salmon were observed at KBC in
2007 and 2008, at KSV in 2008. Coho salmon have not been available for sentinel studies in September
so not too much can be determined other than there was considerable C. shasta infections in the coho
salmon exposed at several index sites in 2008.
0 0 0 0 0
20
40
60
80
100
KOR KSV KBC KKB KED WMR
% C
s m
ort
alit
y
2007 2008 2009 2010 2011 2012 2013
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
20
40
60
80
100
KOR KSV KBC KKB KED WMR
% C
s m
ort
alit
y
2007 2008 2009 2010 2011 2012 2013
25
Figure D.2.1.b.14. Effect of post-exposure rearing water temperature on infections of C. shasta in Klamath River fish stocks exposed for 72 hr near Beaver Creek (KBC) in April, May, June and September, and in July at Seiad Valley (KSV) in 2013. Eighty IGH Chinook salmon (Chf) and rainbow trout (Rbt) were exposed each month then divided in half and held at either 13 or 18°C for about 60 days. Sixty coho salmon were exposed at Beaver Creek in May then divided in half and held at the same two temperatures.
In the comparison of post-exposure rearing water temperatures of 13°C and 18°C and effect on loss of
fish with C. shasta infections, some increased percent of infection with C. shasta was observed in all
species of fish held at the higher water temperature (Figure D.2.1.b.14). In all sentinel tests for each
month the rainbow trout held at 18°C died at a higher rate. For the Chinook, in April, loss at 18°C was
2.6% versus 0% at 13°C. In May no Chinook died at either temperature, but in June 5.2% of the Chinook
died at 18°C but none at 13°C. For coho salmon there was a large water temperature effect in May
where 25% died with C. shasta infections at 18°C and 0% at 13°C.
26
Figure D.2.1.b.15. Comparison of C. shasta mortality of Juvenile IGH fall Chiinook and coho salmon exposed in the Klamath River near Beaver Creek for 72 hr in May and June in years 2007-2013.
Comparison of sentinel results for the IGH Chinook and coho salmon exposed at KBC in 2007 - 2013
indicate a shift toward more severe effects of C. shasta on the Chinook than coho from 2007 to 2009
(Figure D.2.1.b.15). In 2007, the loss of juvenile coho was very high while the Chinook loss was lower. In
2008, both species suffered high loss in May and June. In 2009, the greatest loss occurred in May and
June in the fall Chinook. In general however, losses for both species due to C. shasta have been high in
May and June of 2007-2009. In contrast, for 2010-2013, Chinook suffered decreased infection and
mortality from C. shasta. In 2011 and 2013, the coho loss was much higher at KBC.
Figure D.2.1.b.16. Comparison of C. shasta mortality of Juvenile IGH fall Chinook and coho salmon exposed in the Klamath River near Seiad Valley for 72 hr in May and June in years 2007-2013.
The comparison of C. shasta mortality of juvenile IGH fall Chinook and coho salmon exposed at KSV for
72 hr in May and June of years 2007-2013 show similar results as the comparison for the same years at
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
20
40
60
80
100
M J S M J S A M J S O A M J S A M J S A M J S A M J J S
% C
. shasta
mort
alit
y
Chinook Coho
2007 2008 2009 2010 2011 2012 2013
0 0 0 0 0 0 0 0
20
40
60
80
100
M J S M J S A M J S O A M J S A M J S A M J S A M J J S
% C
. shasta
mort
alit
y
Chinook Coho
2007 2008 2009 2010 2011 2012 2013
27
KBC (Figure D.2.1.b.16). No comparison can be made for Chinook and coho in 2007 since no coho
salmon were exposed at KSV in that year. The coho salmon loss from C. shasta in 2011 and 2013 was
much higher than the Chinook. Also, in 2013 there appears to be a slight downstream shift of greater C.
shasta rate at KSV compared to KBC (Figure D.2.1.b.17).
Figure D.2.1.b.17. Percent survival of Chinook and coho at KBC and KSV index sites and Chinook at KOR exposed in June 2013. Note scale is 60-100%.
D.2.1 (c) Characterize density and population of the invertebrate (polychaete) host.
D.2.1 (c) Overview
The aim of this task is to describe polychaete populations in the Klamath River during the year. Spring
and fall are of interest because they overlap with peak juvenile salmon outmigration (spring) and adult
salmon returns (fall), winter is important for understanding the dynamics of C. shasta infection in this
host, and summer is important for understanding polychaete host population dynamics. Our specific
objectives were to describe the density of M. speciosa populations, to survey populations for prevalence
of C. shasta infection, and to examine relationships among these factors and the environments of 7 sites
on the Klamath River.
D.2.1 (c) Methods
Polychaetes were collected four times per year in winter (March 13-15), spring (June 3-6), summer (July
22-27), and fall (September 31-October 4). Polychaete samples were collected by targeting previously
identified polychaete assemblages at seven sites; from upstream to downstream these include Keno
(KN), the Boyle bypass reach (JCB), I-5 bridge (I5), Tree of Heaven Campground (TOH), Fisher’s RV park
near Beaver Creek (BC), Siead Valley (SV), and Dolan’s Bar near Orleans (OR) (FigureD.2.1c.1). Three
samples were collected at each site with a modified Hess sampler (a joint section of PVC pipe with an
aperture 229 cm2, fitted with an 84µm collection net) and a scraping device. Samples were preserved in
60%
80%
100%
Pe
rce
nt
surv
ival
KBC Chf
KBC coho
KSV Chf
KSV coho
KOR Chf
28
70% ETOH in the field and returned to the laboratory (J.L. Fryer Salmon Disease Laboratory, Oregon
State University, Corvallis, OR) for processing. All samples were subsampled by placing the entire
sample into a sorting tray (20cmx28cm, Wildco, FL) and randomly selecting three 25cmx25cm
subsamples. Subsamples were stained (20%Rose Bengal, Fisher Scientific) and polychaetes were
counted using a dissecting microscope (20-50x magnification).
Figure D.2.1c.1. Locations of monitoring sites from upstream (KN) to downstream (OR) shown by black circles, USGS discharge gages (green circles), and 2013 water year (October 1 2012-September 30 2013) discharge profiles for each river section.
Polychaete density: Subsample counts were adjusted to account for misidentified specimens and
missed (progeny and immature) polychaetes that were observed in the samples. Adjusted polychaete
density was calculated as [(adjusted count/# subsamples)/grid cell area*tray area/Hess area] and
expressed per m2 for each sample.
Prevalence of infection and estimated densities of infected polychaetes: Prevalence of C. shasta
infection in polychaetes was determined using polychaetes collected for density estimates (see above).
Up to 200 polychaetes per sample, or as many as were available if fewer than 200, were prepared for
DNA extraction and tested for C. shasta infection by qPCR (Hallett and Bartholomew 2006).
D.2.1 (c) Results and Discussion
Polychaete density: Polychaete population dynamics differed among river sections. In the lower river
section, M. speciosa densities were higher at the SV monitoring site than at OR in all seasons but we
29
noted an overall trend of lower densities at these sites in winter and spring that increased through
summer and peaked in the fall. In the middle river section, we observed low densities in winter and
spring, with peak densities occurring in summer and intermediate densities in fall but M. speciosa
densities did not differ among the I5, TOH and BC sites. In the upper river section, M. speciosa densities
were higher at the JCB site and lower at the KN site and we observed extremely high densities at the JCB
site year round. In contrast, we observed a slight peak in summer at the KN site.
Figure D.2.1c.2. Densities of Manayunkia speciosa, the polychaete host of Ceratomyxa shasta at 7 monitoring sites in 2013.
Prevalence of infection and the density of infected polychaetes: assays for C. shasta are still in progress
for July (I5, TOH, and BC) and October (all sites) samples. Of those completed (Table D.2.1c.1), there
were site specific differences: We detected higher prevalence in winter samples than spring or summer
samples at OR and SV sites (lower river), no infection in middle river sites in winter or spring samples,
and higher infection prevalence in summer samples than winter or spring samples at KN and JCB sites
(upper river). The highest densities of infected M. speciosa were estimated at JCB in summer
(398,337+3,983 M. speciosa per m2).
30
Figure D.2.1c.3. Prevalence of Ceratomyxa shasta in Manayunkia speciosa and density of infected M. speciosa at 7 monitoring sites in 2013.
Density, prevalence of infection and the environments of monitoring sites: The environments of lower
river sites (OR and SV) are protected pools characterized large boulder and bedrock substrates. These
sites were selected to be representative of the highest discharge conditions and most variable water
temperatures of our monitoring sites, and we expected densities of M. speciosa would be low at these
sites, particularly in winter and spring, when compared to sites in the middle and upper river sections.
We expected polychaete densities would be higher at sites in the middle and upper river where water
temperature and discharge would be less variable. Densities were always highest at JCB (upper section);
even in winter 2013 following the only notable flow event, densities were >150,000 m-2. This is likely
explained by the combination of the high stability in the hydrograph (Figure D.2.1c.1) and high food
availability in this reach. The remainder of the year, densities in at this site were 200,000-323,000m-2).
Densities were comparable at KN, I5, TOH, and BC; <10,000m-2 in winter and spring, peaking in summer
(highest at TOH: 144,374 m-2), and intermediate in fall (10,000-50,000m-2). We suggest the summer
peak is related to decreased variability in the hydrograph and the increased water temperature which
may constrain food availability during non-summer months. In warmer spring seasons, the peak
summer density may shift earlier, perhaps overlapping with the peak period of juvenile outmigration.
The observed densities at SV were higher than expected; they increased from >17,000m-2 in winter to
>182,000m-2 in fall. Although densities were an order of magnitude lower at OR, we observed a similar
trend with densities increasing from spring (>4,000m-2) to fall (>78,000m-2). We attribute this trend to
an increase in food availability in the lower river towards the end of the summer, likely following a
stagnation in periphyton growth.
31
We hypothesize that adult salmon returning to the river in the fall transport myxospores upstream and
deposit them immediately downstream from Iron Gate Dam 1) infecting nearby polychaetes (I5, TOH,
and BC) in later fall-early spring, that 2) infected polychaetes located proximal to Iron Gate Dam are the
source of infection for juvenile salmon outmigrating in spring, and 3) that infected juvenile salmon
outmigrating in spring deposit myxospores in the lower river infecting polychaetes at SV and OR in the
summer, which provides a source of actinospores for returning adult fish in fall. Consequently, we
expected prevalence of C. shasta infection would be highly seasonal and variable among sites. We
expected to observe infected polychaetes in the summer and fall in the lower river section, and in the
fall, winter, and spring in the middle river sites. We expected prevalence to be similar year round in the
upper river sites because trout inhabit these reaches and are present year round. Although prevalence
assays are still in progress we can discuss the winter, spring and summer results (excluding middle river
summer results as assays are still in progress). Infected polychaetes were detected at three sites in
winter including OR and SV (lower river) and JCB (upper river). In spring, infected polychaetes were only
detected at SV. In summer, infected polychaetes were detected at all sites except KN (upper river) and
I5 (lower river). In fall, infection was detected in polychaetes from all sites except TOH, with the highest
prevalence detected in polychaetes at BC. Overall, prevalence was highest in winter samples collected
at OR (6.5%) and SV (3.7%) and relatively low (<2%) for the remainder of the year, with the one
exception of the fall sample at BC (3.6%).
32
Table D.2.1c.1. Number of polychaete molecular pools positive for C. shasta, number of polychaetes assayed in pools, and prevalence of C. shasta infection in March, June, July, and October 2013 at index monitoring sites.
Month Site total C. shasta positive total polychaetes assayed for C. shasta Prevalence of infection
March OR 4 62 6.45
SV 6 163 3.68
BC 0 20 0
TOH 0 46 0
I5 0 0 .
JCB 2 420 0.48
KN 0 279 0
June OR 0 26 0.00
SV 4 258 1.55
BC 0 34 0.00
TOH 0 36 0.00
I5 0 10 0.00
JCB 0 328 0.00
KN 0 323 0.00
July OR 3 408 0.74
SV 5 418 1.20
BC 4 602 0.66
TOH 1 730 0.14
I5 0 250 0
JCB 5 408 1.23
KN 1 339 0
October OR 3 222 1.35
SV 2 464 0.43
BC 1 28 3.57
TOH 0 21 0
I5 2 157 1.27
JCB 1 677 0.15
KN 1 226 0.44
33
D.2.2 Develop an index for predicting disease severity for Chinook and coho salmon that is validated by
correlating data on infection prevalence and disease severity in each fish species with genotype-specific
spore densities in water collected at each site.
D.2.2 (a) Develop a method for high throughput genotyping of C. shasta
D.2.2 (a) Overview
We developed an improved protocol to genotype C. shasta, which was less subject to inhibition. The
ITS1 gene was amplified in a SYTO9 qPCR and the proportions of genotypes present were determined
using Sanger sequencing. This assay was used to inform the cure model described below. In parallel, we
began development of an alternative, higher resolution genotyping approach to distinguish between the
coho and rainbow trout genotype II biotypes. This novel approach involved determination of the
genome and transcriptome of the various C. shasta genotypes and is described further below. In
addition to the genetic work, we developed a model to quantify the relationship of environmental
factors (water temperature and discharge) and parasite density on C. shasta induced mortality in both
Chinook and coho salmon. The objective of this model was to provide disease related mortality rates
that can be incorporated into larger salmon population models to improve production and escapement
predictions, to better manage the Klamath River salmon population.
D.2.2 (a) Genetic Methods
Genomic DNA samples and library preparation: We isolated ITS1-genotype II parasite spores
(“coho/rainbow genotype”) from infected fish intestines using PercollR gradient centrifugation. We then
extracted and purified total genomic DNA from the spores with a QIAGEN kit, prepared a single-strand
DNA library and performed an emulsion PCR using kits.
Genome sequencing and assembly: The genome library was sequenced at the Center for Genome
Research and Biocomputing at OSU, on a single lane of an Illumina HiSeq2000 machine, using 100nt
paired-end reads. Trial subsets of these sequence data were assembled using two software packages,
CLCBio and Velvet, with a range of parameters to assess the best assembly strategy (to produce the
fewest scaffolds but with the longest contigs).
Transcriptome RNA samples and library preparation: Samples of parasite ITS1-genotype I (“Chinook
genotype”) and biotypes IIR (“rainbow”) and IIC (“coho”) were collected from infected intestinal tissue,
and frozen in RNAlater. Total RNA was extracted from each sample using a commercial kit, then cDNA
libraries prepared using a protocol being developed by Dr Eli Meyer (OSU Zoology). Libraries underwent
several rounds of quality checking and quantification before being barcoded to permit multiple samples
to be run within a single lane of the Illumina HiSeq2000 sequencer. The libraries were sequenced using
100nt paired-end reads. Transcriptome read data were analysed and filtered initially by the Illumina
sequencer, before additional filtering, assembly and annotation were performed using Trinity and BLAST
software on the OSU computational infrastructure.
Genotyping assay: During determination of the C. shasta genome and transcriptome, we continued to
refine our existing genotyping approach, SYTO9 qPCR and direct sequencing, and used it to determine
the C. shasta genotypes in water samples from KBC, including during salmon outmigration. These
genotype data feed into the cure model outlined below.
34
D.2.2 (a) Genetic Results
We successfully extracted high quality, single-genotype genomic DNA from purified parasite spores.
Genome sequencing was delayed one month due to a hardware failure in the Illumina HiSeq2000
genome sequencer. Ultimately, we obtained ~450 million reads, which were filtered and assembled
using Velvet, to produce a draft genome assembly of ~15,000 scaffolds at ~200x coverage of known
single-copy genes.
We successfully extracted high quality RNA for the three genotypes. As there are no published protocols
for RNA library preparation from myxozoan parasites, we had to trial different methods and modify an
existing protocol, with assistance from Dr Meyer. This lengthened this part of the project. Once libraries
were prepared, sequencing was delayed again by a hardware failure in the Illumina sequencer.
Ultimately we obtained ~20 million raw reads for each parasite library. These raw reads libraries were
then filtered and assembled into ~50,000 gene contigs.
Annotation of these transcriptomes and correlation of C. shasta genome and transcriptome sequences
are ongoing, to find targets for assay development. In the interim, we have further tested and improved
our existing genotype assay and generated genotype data for KBC from 2006 through 2013 (Figures
D.2.2.a.1. & a.2.). Although genotype I was more abundant than type II for most of 2013, type II was
conspicuous in January and was more abundant in 2013 than in 2012, which is reflected in the sentinel
fish studies in which more coho became diseased in 2013 than in 2012.
Figure D.2.2.a.1. Density (spores/L) of Ceratomyxa shasta ITS1 genotypes in water samples collected at the KBC index site from 2006 through 2013. Type I typically corresponds with disease in Chinook and type II with coho.
05
10152025303540455055606570
Jan
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Mar
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May
-06
Jul-
06
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Jan
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Jan
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Jan
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13
IIIIII
Spo
res/
L
35
Figure D.2.2.a.2. Higher resolution of the 2011-2013 data. Density (spores/L) of Ceratomyxa shasta genotypes in water samples collected at the KBC index site from 2006 through 2013. Type I typically corresponds with disease in Chinook and type II with coho.
D.2.2 (b) Develop an index for predicting disease severity for Chinook and coho salmon
We have developed a model for predicting Chinook and coho mortality that can be used as an index for
predicting disease severity.
D.2.2 (b) Model Methods:
We identified a mixture cure model, an alternative to traditional survival analysis method, which best fit
the C. shasta mortality patterns observed for both Chinook and coho salmon. To develop this model we
used data collected from sentinel trials conducted at KBC from 2006-2010 consisting of 33 trials for
Chinook (n=1463 fish) and 30 trials for coho (n=1238 fish; Hallett et al. 2012). For each exposure trial we
obtained genotype specific (Type I for Chinook and Type II for coho) parasite numbers, water
temperatures during the 3 day exposure and during the rearing period at the SDL, and discharge.
The mixture cure model is unique from other survival analysis methods for two reasons. First, it divides
the population into two groups 1) susceptible individuals– those that experience the event of interest
and 2) cured individuals– those that survive the event of interest. Second, this model is comprised to
two separate equations a logistic equation that estimates the probability of mortality and a standard
survival model the estimates the rate of mortality for the susceptible individuals (Othus et al 2012). We
developed our models with six covariates in each equation: concentration of species-specific parasite (TI
for Chinook and TII for coho), water temperature during exposure period (ET), water temperature during
holding period at SDL (HT), discharge (Q), interaction between parasite concentration and water
temperature (TI x HT and TII x HT), and interaction between parasite concentration and discharge (TI x Q
and TII x Q) that acts as a proxy estimate of dose.
We used a maximum likelihood method to estimate the various parameters in the model. The most
parsimonious model was selected using Akaike Information Criterion (AIC; Akaike 1973, Burnham and
Anderson 2002). In addition, we visually assessed the model fit by comparing the estimated Kaplan-
Meier survival curves of the observed data to curves predicted by the mixture cure model. Lastly, we
evaluated the influence of the different environmental factors on parasite induced mortality by plotting
the minimum, mean, and maximum values of HT and Q against the minimum, mean, and maximum
36
values of TI and TII.
D.2.2 (b) Model Results:
Two separate models were developed, one each for Chinook and coho. The final Chinook model did not
include the ET covariate from the logistic component and TI x HT covariate from the survival component
(Table 2.2.1). All of the covariates in the logistic component of the Chinook model were positively
associated with parasite-induced mortality and all the covariates in the survival component were
negatively associated with the survival rate (Table 2.2.2). The final coho model excluded ET and TII x HT
from the logistic component and TII x Q from the survival component (Table 2.2.1). In the logistic
component of the final coho model, HT, TII, and Q were positively associated with probability of
mortality; however TII x Q was associated with a decrease in the probability of mortality (Table 2.2.2). In
the survival component all covariates except ET and TII x HT were negatively associated with survival
rate. Even though Chinook and coho respond differently to C. shasta induced mortality, the models
were able to capture the three characteristics (delayed onset of mortality, a period of high mortality,
and a plateau in which no additional mortality occurs) for a majority of the observed sentinel exposures
(Fig 2.2.1 a and b). HT had a greater influence than Q on the rate of parasite induced mortality for both
Chinook and coho; however, Q had greater influence on total mortality of coho than Chinook (Figure
2.2.2 a and b).
37
Table 2.2.b.1. Model selection results for Chinook and coho mixture cure models based on Weibull distribution. All covariates are shown for the global model, with other models showing terms removed from the global model.
Blank cells indicate that no covariates were removed. (z) = logistic model, S (t) = survival model, k = number of estimated parameters, MLL = maximized log-likelihood, AIC = Akaike’s Information Criterion
Number Component Model k MLL AIC ΔAIC
Chinook salmon Global (z) HT+ET+TI+Q+TI*HT+TI*Q 15 -519.93 1069.87 1.53
S (t) HT+ET+TI+Q+TI*HT+TI*Q 1 (z) 14 -561.66 1151.32 82.98
S (t) - ET
2 (z) - ET 14 -520.54 1069.08 0.74
S (t)
3 (z) - (ET + HT * TI) 13 -533.40 1092.81 24.47
S (t) 4 (z) - (ET + TI * Q) 13 -525.68 1077.36 9.02
S (t) 5 (z) - ET 13 -616.85 1259.70 191.36
S (t) - TI * Q Final (z) - ET 13 -521.17 1068.34 0.00
S (t) - TI * HT 6 (z) - (ET + HT * TI) 12 -533.96 1091.92 23.58
S (t) - TI * HT 7 (z) - (ET + TI * Q) 12 -526.30 1076.60 8.26
S (t) - TI * HT 8 (z) - ET 12 -619.32 1262.65 194.31
S (t) - (TI * HT + TI * Q) Coho salmon
global (z) HT+ET+TII+Q+TII*HT+TII*Q 15 -662.51 1355.02 3.27
S (t) HT+ET+TII+Q+TII*HT+TII*Q 1 (z) 14 -664.79 1357.59 6.36
S (t) - ET 2 (z) - ET 14 -663.48 1354.96 3.73
S (t) 3 (z) - (ET + TII * Q) 13 -667.01 1360.02 8.79
S (t) 4 (z) - (ET + TII * HT) 13 -665.51 1353.01 1.78
S (t) 5 (z) - ET 13 -674.55 1357.10 5.87
S (t) - TII * HT 6 (z) - ET 13 -663.61 1353.21 1.98
S (t) - TII * Q 7 (z) - (ET + TII * HT + TII * Q) 12 -667.06
1358.12 6.89
S (t) 8 (z) - (ET + TII * HT) 12 -665.80 1355.60 4.37
S (t) - TII * HT final (z) - (ET + TII * HT) 12 -663.62 1351.23 0.00
S (t) - TII * Q 9 (z) - (ET + TII * HT + TII *Q) 11 -667.06 1356.13 4.90
S (t) - TII * Q 10 (z) - (ET + TII * HT) 11 -666.60 1355.19 3.96
S (t) - (TII * Q + TII * HT)
38
Table 2.2.b.2. Parameter coefficients for final mixture cure models for both Chinook and coho salmon
Component Covariate Coefficient SE
Chinook salmon Logistic Intercept -0.280 0.101 HT 0.389 0.045 TI 0.123 0.010 Q 0.022 0.005 TI x HT 0.019 0.004 TI x Q 0.001 0.0003 Survival Intercept 3.424 0.013 HT -0.084 0.003 ET -0.037 0.005 TI -0.007 0.001 Q -0.003 0.001
TI x Q -0.001 0.0001
Log(scale) -1.561 0.030 Coho salmon Logistic Intercept -0.555 0.091 HT 0.524 0.045 TII 0.115 0.009 Q 0.012 0.003 TII x Q -0.001 0.0004 Survival Intercept 3.907 0.034 HT -0.134 0.018 ET 0.038 0.153 TII -0.020 0.003 Q -0.006 0.001 TII x HT 0.003 0.001 Log(scale) -1.136 0.034
39
a)
40
Figure 2.2.b.1. a) Estimated Kaplan-Meier (thin) and mixture cure model (thick) survival curves for a) Chinook and b) coho sentinel trials conducted in the Klamath River, with 95% confidence intervals (dashed).
b)
41
Figure 2.2.b.2. Response of predicted survival probability from the a) Chinook and b) coho mixture cure model at minimum (a and d), mean (b and e), and maximum (c and f) values of Chinook / coho-specific Ceratomyxa shasta L-1 (TI / TII). The top row (a, b, and c) represents the interacting effect of holding temperature (HT) and TI/TII on the predicted survival probability. The bottom row (d, e, and f) represents the interacting effect of discharge (Q) and TI/TII on the predicted survival. The lines within each panel correspond with minimum (solid), mean (dashed), and maximum (dotted) observed values of HT and Q.
42
2.2 (b)Discussion:
This is the first known application of a mixture cure model to a wildlife pathogen and provides a new
powerful yet flexible survival analytical method that can be used in other populations. We developed
two mixture cure models that quantified the effects of water temperature, discharge, and parasite
concentration on parasite-induced mortality for both Chinook and coho salmon in the Klamath River.
These models provide estimates of daily survival rates and of population level parasite-induced
mortality that can be incorporated into salmon population and production models. This additional
information allows for a more detailed understanding of juvenile salmon survival in the Klamath River;
which in turn will allow managers to better account for the effects of disease dynamics on this stock.
Although each model captured the observed mortality traits for both Chinook and coho for a majority of
sentinel exposures there were some instances where the models did not replicate any of the
characteristics. To improve the fit of these models requires more fine-scale field data collection and
potentially some laboratory studies. The parasite concentration data used to develop these models
were collected during the start and end of the sentinel exposures and assumed to be constant during
the 3 day period. However this assumption may not be appropriate as Hallett and Bartholomew (2006)
observed varying parasite concentrations over a 24 hour period. Continuous water sampling during the
exposure period could help improve the estimates of parasite concentration. Although discharge (Q)
was an important covariate in both models it is broad-scale metric that does not capture the variation
among the different river features (i.e. riffles, runs, pools). In these models Q is assumed to be a proxy
for velocity, which is an important abiotic factor with respect to the transmission of the parasite to its
hosts (Ray and Bartholomew 2013). To improve the fit of these models may be achieved by including
fine-scale velocity measurements near the sentinel exposure cages. In addition to more refined
environmental measurements, understanding how interactions among different genotypes and other
pathogens affect the disease dynamics in the salmon host may improve the predictive abilities of these
models.
For further detail on the model development and analysis or discussion please refer to this manuscript
which has been accepted for publication in Transactions of American Fisheries Society and is also
available in the PhD Dissertation of Dr. R. Adam Ray.
Ray, RA, Perry, RW, Som, NA, and Bartholomew JL (2014) Using cure models for analyzing the influence
of pathogens on salmon survival. Transactions of American Fisheries Society. In press.
R Adam Ray PhD dissertation: http://hdl.handle.net/1957/43334
43
D.2.3 Produce a validated epidemiological model that identifies sensitive parameters in the host-
parasite life cycle, simulates the effect of potential management strategies on the different stages of the
life cycle, and predicts disease severity in juvenile salmonid population under different parasite
densities, temperatures, flows). The following data gaps will be investigated:
D.2.3 (a) Magnitude of adult myxospore input
D.2.3 (a) Study Objective:
To develop an epidemiological model of the Ceratomyxa shasta life cycle and conduct a series of
sensitivity analyses to identify which stage is the most suitable target for management actions to reduce
the effect of this parasite on the Klamath River salmon population. The goal of the epidemiological
model is to evaluate the basic reproductive number (R0) which has an inherent threshold value of one,
below which the pathogen is unable to persist within a host population (Dietz, 1993). Once we define
an equation for R0 we can implement different management scenarios and observe what is needed to
drive the system below the threshold value of one.
D.2.3 (a) Methods:
Ceratomyxa shasta has a complex life cycle involving four hosts (juvenile and adult salmon and winter
and summer polychaete populations) and four spore stages (spring and fall actinospores and summer
and winter myxospores; Fig 2.3.1). We developed a series of 8 differential equations to describe the
interactions between the different hosts and spore stages (eq 2.3.1-8).
( )
( ) ( )
( )
( ) ( )
( )
( ) ( )
( )
( ) ( )
We then mathematically evaluated these equations to define a basic reproductive number (R0) using
vector notation described by Van den Driessche and Watmough (2002). Then using the R0 equation (eq
2.3.9) we conducted a series of sensitivity analyses that represent potential management actions.
44
√( )( ) ( ) ( )( ( )( )( )
( ) ( ) ( )( )( )( )( )( )
( )
For each sensitivity analysis we increased and decrease a single parameter value by 100% of the original
value. We analyzed the effects of increasing and decreasing each of the host population densities (Oj,
Oa, Psu and Pw), parasite production from each host (λoj, θsu, λoa and θw) and also transmission rate of C.
shasta to each of its hosts (βsp, βsu, βf and βw). We also analyzed the effects of simultaneously decreasing
two parameters, winter polychaete populations (Pw) and transmission rate of the myxospore from the
adult salmon to winter polychaete host (βw).
D.2.3 (a) Results:
The sensitivity analyses conducted showed management actions that focus on a single parameter (i.e.
host densities, parasite production, or transmission) produce small changes in R0, unless the parameter
is essentially 0 (Fig 2.3.a1). However the analysis did show that management actions should not be
performed during the summer months as alterations in the summer polychaete populations (Psu) or
summer transmission rates (βsu) caused even less change in the R0 values than during other times of the
year. Altering the value of two parameters simultaneously (Pw and βw) did not have any multiplicative
or synergistic effect on the R0 values (Fig 2.3.a.2, Fig 2.3.a.3). However reducing each parameter by a
similar amount had a greater effect on R0 than the alteration of a single parameter value.
Figure D.2.3.a.1. Life cycle of the myxozoan parasite Ceratomyxa shasta showing involvement of juvenile (Oj) and adult (Oa) Chinook salmon and the polychaete (Psu and Pw) hosts.
45
Figure D2.3.a.2. Response of R0 values to percent changes in a)host density, Oj, Oa, and Pw (solid line) and Psu (dashed line), b) parasite production per host (λoj, θsu, λoa and θw), all lines overlap, and c) transmission rates βsp, βf,
and βw (solid line) and βsu (dashed line ). The R0 threshold value of 1 (dotted line), below which the parasite cannot persist in the populations is represented by the dotted line.
a)
c)
b)
46
Figure D.2.3.a.3. Contour plot comparing the response of R0 values to changes in both winter polychaete
density (Pw) and myxospore transmission (βw) parameter values range from 0-2 x 10-6.
D.2.3 (a) Discussion:
From the development and analysis of this epidemiological model we identified that management
actions should target more than a single parameter in the life cycle of C. shasta. Although this analysis
did not identify any parameters that were more sensitive than any others we did identify that
management actions should not be implemented during the summer periods. The structure of the R0
equations indicates that transmission rates (β) and host densities might be the most influential as they
occur in both the numerator and denominator.
This models capabilities of identify target parameter(s) is limited as a result of existing data gaps and
lack of knowledge as to how different parameters will respond to changes in environmental factors. In
the current model we assumed that each of the four transmission parameters were of equal value.
Although this is highly unlikely we only had empirical data for the transmission of actinospores to the
juvenile salmon host from Ray and Bartholomew (2013) and used this as a starting value for each of the
other transmission rates. Foott et al. (2013) provided data on myxospore production from adult
carcasses and showed that a relatively small proportion of the population may be responsible for a
majority of myxospores produced. For our model we assumed equal production from all infected adult
salmon. This could be important if a method or relationship is identified to target the removal these
highly productive carcasses. Additionally this model does not take into account the spatial distribution
of adult carcasses to polychaete populations. It may be possible to identify a specific reach of river
where a majority of carcasses settle in close proximity to large polychaete populations. If these areas
exist they could be directly targeted by management actions by removing adult carcasses and disrupting
polychaete habitat/populations. This may also be achieved by allowing adult salmon to migrate beyond
Iron Gate Dam thereby dispersing the source of myxospores and limiting transmission to polychaete
host. Lastly, we assume a linear relationship between the parameters and theoretical management
actions; e.g. a 10% increase in discharge results in a 10% in transmission, etc. It is possible and likely
47
that many of these interactions have threshold values around which significant shifts in the response
can occur. This model provides a framework for directing future studies, to quantify existing data gaps,
and management actions, that should influence more than a single parameter.
A manuscript describing the model development and sensitivity analysis is currently in preparation as:
Ray, RA and Bartholomew JL (2014) Using an epidemiological model to quantify sensitivity of myxozoan
(Ceratomyxa shasta) disease dynamics to demographic parameters. In prep. A version of this
manuscript– although the model has since been modified – is also available in the PhD dissertation of
Dr. Adam Ray: R Adam Ray PhD dissertation: http://hdl.handle.net/1957/43334
D.2.3. (b) Parasite source below the Trinity River confluence
D.2.3 (b) Overview:
To investigate the occurrence of C. shasta below the Trinity River confluence and ascertain whether
waterborne stages were actinospores or myxospores, we conducted concurrent sentinel fish exposures
and longitudinal water sampling. Collaborative polychaete sampling with the Yurok Tribe planned for
late summer was prevented by high flows and will be conducted next summer.
D.2.3 (b) Methods:
With the assistance of the Yurok and Hoopa tribal biologists, Roaring River Hatchery C. shasta-
susceptible rainbow trout and fall Chinook were exposed July 16-19 at two lower Klamath River
mainstem sites, KSV and KTC. Four groups of 25 Chinook each and two groups of 40 rainbow trout each
were held in separate live cages at KSV. At KTC, 40 Trinity River Hatchery (TRH) and Iron Gate Hatchery
(IGH) Chinook, 40 rainbow trout and 30 IGH coho were held in live cages. Surface water temperatures at
the time fish were placed in the live cages were higher than 23°C. After the 70 hr exposure at KSV, the
Chinook in all four cages had died. The rainbow trout were found stressed and some were dead. The
temperature logger at KSV recorded maximum temperature during the exposure of 25.9°C. At KTC, a
few fish were dead in most groups but the remainder survived. To avoid excessive loss from columnaris
disease, all groups from the July exposure were held at 18°C except for one rainbow trout group from
KSV which was held at 13°C. Monitoring ended September 19 (62 days post-exposure).
Yurok tribal biologists collected water samples during the sentinel fish exposures on July 17 from 9 sites
spanning 72 Rkm which straddled index site KTC. The samples were filtered and sent to OSU for parasite
analysis.
D.2.3 (b) Results:
Even though water temperatures were very high during the river exposure and thus likely to exacerbate
infection, only 2.9% of the TRH Chinook, 3.1% of the IGH Chinook and 4.3% of the IGH coho exposed
near KTC were found to be infected with C. shasta (Table D.2.3.b.1). At KSV, where only rainbow trout
survived the exposure, there was 77.8% loss at 18°C and 26.3% at 13°C. At KTC, 60% of the exposed
rainbow trout were infected with C. shasta.
48
Table D.2.3.b.1. Percent mortality of fishes exposed July 16-19 at two sites in the lower Klamath River. TRH= Trinity River Hatchery; IGH= Iron Gate Hatchery; ChF= fall Chinook salmon; RbT= rainbow trout.
Site July Exposure
TRH ChF IGH ChF Coho RbT
KSV 77.8
KTC 2.9 3.1 4.3 60
Parasite levels were low (< 1 spore/L) upstream of the Trinity River confluence with the Klamath River
mainstem but were higher (between 1 and 10 spores/L) for 30 Rkm downstream of KTC; the highest
levels were detected immediately downstream of KTC (Figure 2.3.b.1.).
Figure 2.3.b.1. Average density of C. shasta in three water samples collected July 17 2013 (top) and July 19 2014 (bottom) at 9 sites in the lower Klamath River. KTC= Tully Creek monitoring index site; KOR= Orleans monitoring index site.
D.2.3 (b) Discussion:
Parasite levels in the KTC monitoring water samples reached around 10 spores/L early July, and thus this
study was scheduled for later that month (Figure 2.3.b.2.). However, in the interim, parasite levels
49
decreased to around 1 spore/L. Despite the low parasite levels, one of each salmon species exposed at
KTC died from C. shasta-infection. This indicates that actinospores contributed to the total spore
densities measured at that time and that both genotype I (which causes mortality in Chinook) and
genotype II (which is fatal for coho) were present.
D. 2.3 (c) Recolonization rate of polychaetes
D.2.3 (c) Overview:
Management actions that target the polychaete host are desirable because of the high conservation
value of salmonid hosts and the logistical constraints associated with targeting waterborne parasite
stages. Salmonid whirling disease (also caused by a myxozoan parasite that alternately infects an
invertebrate host) has been successfully managed in hatcheries through actions that reduce obligate
invertebrate host densities (Hoffman and Hoffman 1972, Wagner 2002). Reducing densities of M.
speciosa may be one method for managing ceratomyxosis. One action that has been proposed to reduce
M. speciosa population densities involves manipulating the discharge from Iron Gate Dam to increase
flow heterogeneity (Jordan 2012).
The aim of this task is to describe recolonzation for two polychaete populations in the Klamath River.
The populations were identified during a study completed in 2010-2011 by our laboratory (Jordan et al.
in review) and include sites where high densities of polychaetes were observed inhabiting fine
substrates in depositional environments in 2010 but not in 2011 (Figure D.2.3c.1). Elevated discharge in
the winter and spring of 2011 (peak discharge 5,700 cfs) is hypothesized to have reduced the suitability
of these habitats for M. speciosa.
Figure D.2.3.c.1. Polychaete populations at select sampling sites in the Klamath River in summer 2010 and summer 2011. The red circles identify two sites that are being monitored to determine the period of time required for recolonization to occur.
50
D.2.3 (c) Methods:
Habitats are examined visually for the presence of polychaete tubes every summer (Figure D.2.3c.2) and
density samples are collected to verify visual observations.
Figure D.2.3c.2. Polychaetes can be detected visually when they are present at high densities. We use a combination of visual observations and density samples to monitor Jordan et al. in review’s sites for polychaete recolonization. Polychaete tubes are visible in the 100% cover photo, whereas no tubes are seen in the 0% cover photo.
D.2.3 (c) Results and Discussion:
Polychaete tubes have not been observed in either habitat since 2010. We will to continue to monitor
these sites for polychaetes in 2014. We attribute the failure to recolonize these areas to the occurrence
of peak discharge from Iron Gate Dam above 2,000 cfs in 2012 and 2013. We hypothesize that if
discharge remains below 2,000 cfs this year, we will see polychaete hosts begin to recolonize habitats
dominated by fine sediments.
51
D.2.4 Produce a validated model of polychaete distribution and density for different scenarios predicted
for discharge manipulations, water years, and dam removal.
D.2.4 (a) Add polychaete density and infection prevalence data to the physical model to predict the
amount, suitability and stability of habitat under various stream flow regimes.
D.2.4 (a) Overview
The causative agent of salmonid ceratomyxosis, Ceratonova (syn Ceratomyxa) shasta, requires the
freshwater polychaete, Manayunkia speciosa in order to produce the actinospore stages that are
infective for salmon. The demand for effective disease management solutions for Klamath River salmon
has generated inquiries of the feasibility for flow manipulation to reduce M. speciosa populations. We
are involved in the data handling for a large, collaborative (USFWS and OSU) modeling effort aimed at
developing and testing models for predicting the distribution and density of the polychaete host.
D.2.4 (a) Methods
We used a tandem modeling approach to predict the distribution of M. speciosa and evaluate the
effects of three discharge scenarios in sections of the Klamath River. Two-dimensional hydraulic models
(2DHM) were built for three river sections using topographic survey data, water surface elevation
profiles, stage-discharge relationships, and spatial maps of substrate (Wright 2014). The 2DHMs were
used to describe hydraulic variation and stratify sampling locations across depth velocity gradients
within substrate classes. Benthic samples collected in July 2012 were used to build a statistical model
estimating the relationship between physical habitat characteristics and the distribution of M. speciosa.
This model is then used to predict the distribution of M. speciosa under various peak discharge
scenarios, which would be used as a management guide. The predictive model was tested against an
independent dataset collected in summer 2013.
D.2.4 (a) Results and Discussion
The best fitting statistical model demonstrated that in summer, distribution is associated with substrate,
as well as depths and velocity conditions during peak discharge predicted from the 2DHMs during the
immediate water year (Figure D.2.4.a.1). This suggested that the peak flow values from the previous
winter (2012), when used to predict depth and velocity during peak flow, when coupled with substrate,
were strong determinants of polychaete distribution the following summer (2012). We evaluated the
predictive accuracy of the model using an independent dataset collected in July 2013, used the peak
discharge in 2013 to run the 2D models, and found the model to comparably predict the distribution of
M. speciosa in 2013, even though peak discharge differed between the two years.
52
Figure D.2.4a1. Polychaete sampling locations at one of our model sites in July 2012. Black circles denote sites where polychaetes were present and white triangles denote sites where polychaetes were absent. The predicted probability is modeled across the entire reach and high probabilities are shown in dark colors where dark grey indicates 75-100% probability of polychaetes, and low probabilities are shown in light colors with white representing 0-25% probability of polychaetes. Overall, the model fit was excellent; observations matched predicted probabilities at sampling 86.5% of the time.
D.2.4 (b) Validate the model to target variable flows and different polychaete population dynamics.
Refine the model as necessary.
D.2.4 (b) Overview
Alteration of the natural flow regime is hypothesized to increase habitat available to the polychaete
host, leading to amplification of C. shasta. Consequently, there is considerable interest in management
actions that could reduce polychaete host population distribution and density. One proposed action
involves manipulating discharge from Iron Gate Dam to increase flow heterogeneity during potential
high risk disease years. However, the relationship between flow variability and the distribution and
density of polychaete hosts is not well understood.
To understand and quantify the relationship between discharge and polychaete host density we used
two different models. First a two-dimensional hydraulic models (2DHM) was developed for three river
sections located within a section of the river where parasite densities are high (river kilometers 281,264,
and 259; Wright et al. 2014). This model predicts depth, velocity, and shear stress at each site which are
used to predict the amount of available polychaete habitat for a given discharge once fed into the
statistical model described in D.2.3c, above. Although the models can be used to predict values for any
53
discharge, it is important to note they were calibrated and validated for discharges in 2011-2012 that
ranged from 33.25-159.16 cms (1188-5685 cfs). Thus, predictions outside this range have not been
validated with real data. Next, a logistic regression model was developed to predict the probability of
polychaete presence given the habitat available predicted from the 2DHM.
D.2.4 (b) Methods
We predicted the distribution of M. speciosa under several alternate hydrographs, 1,200cfs and 7,950
cfs, to simulate dry and wet water year scenarios, respectively. The values were selected to fall within
the range of discharge possible for future management solutions.
D.2.4 (b) Results and Discussion
When we predicted the distribution of M. speciosa under the alternate peak discharge scenarios, our
preliminary results suggest that manipulating the hydrograph could influence distribution of polychaete
hosts (Figure D.2.4.b.1) because the probability of polychaetes decreased 25% (2 reaches) to 28% (one
reach) between the two scenarios. Validation of the model predictions using real data collected at both
the low and high peak discharge scenarios are needed before we can evaluate whether manipulation of
the hydrograph may in turn influence prevalence of C. shasta and disease in salmonids, but the
preliminary results are very exciting.
Figure D.2.4b1. The effect of a water year’s peak flow on the probability of polychaetes at locations in the Tree of Heaven Study reach. Predicted polychaete distributions under two modeled peak discharge scenarios including a dry water year having a peak discharge of 1,200 cfs out of Iron Gate Dam (left) and a wet water year having a peak discharge of 7,950 cfs (right).
54
D.2.5 Develop and synthesize a dataset, encompassing environmental risk factors and their relationship
with polychaete host ecology, to facilitate predictions about how polychaete densities and infection
levels may change under future climate and temperature regimes.
D.2.5 Overview
Climate change influences disease dynamics, but predicting the magnitude and direction of change for
management is challenging. Much of the current literature has focused on the effects of increasing
temperatures on disease occurrence and severity. However, shifts in precipitation patterns will also
influence disease dynamics, especially for the invertebrate host of C. shasta. We have begun to examine
the potential effects of future climate scenarios in the Klamath River CA, USA on the C. shasta life cycle.
In the Klamath River Basin, summer air temperatures are predicted to increase ~3°C by 2045 and ~7°C in
the summer by 2085, but in the winter only 2°C by 2045 and ~4°C by 2085 (Barr et al. 2010). This
contrasts with predictions for many systems, where greater increases in winter temperatures are
forecasted. Water temperature in the Klamath River is predicted to increase ~1-3°C by 2060, depending
on the climate scenario (Perry et al. 2011). The increase in air temperature will influence precipitation
patterns the basin and the increase in water temperature will affect the biological and physiological
processes in the river.
The shift in precipitation from snow to rain will affect discharge magnitude and velocity, and changes in
either may affect interactions between M. speciosa and C. shasta. Although there is large variation in
predicted magnitudes of change, there is a consistent pattern of wetter winters and drier summers
(Mote 2003). Decreased summer discharges can increase habitat for invertebrate hosts (Marcogliese
2001) and lower water levels can cause vertebrate hosts to aggregate in greater densities. This increased
overlap between high densities of host (vertebrate and invertebrate) and parasite can lead to greater
infection prevalence and disease severity (Izyumova 1987; Holmes 1996). Although only a handful of
studies have examined the effects of water velocity on host-parasite interactions, they indicate a
consistent trend of decreased infection prevalence and disease severity as water velocity increases (see
Barker and Cone 2000; Bodensteiner et al. 2000). Myxozoan spores are passively transmitted to their
respective hosts, thus transmission of both spore stages have the potential to be influenced by water
velocity. A similar negative relationship between water velocity and infection prevalence in both
salmonid and oligochaete host was observed for M. cerebralis (Hallett and Bartholomew 2008) and C.
shasta (Bjork and Bartholomew 2008).
D.2.5 Methods
We are using a series of models to examine the risk of salmonid enteronecrosis (ceratomyxosis), the
disease caused by Ceratonova (syn Ceratomyxa) shasta. We plan to link a series of models designed
specifically for the Klamath River system including a fine-scale climate change model to predict future
stream temperatures and discharge (Perry et al. 2011), a 2-D hydraulic model coupled with a statistical
model to predict changes in polychaete populations under different river discharge scenarios (Task
D.2.4, above), a degree-day model to predict the potential number of generations per year under
different thermal regimes (Chiaramonte 2013), and an epidemiological model to quantify the risk of
disease in the salmon host under the different climate scenarios (Ray 2013).
The models and their outputs will be linked together to predict changes in disease severity in salmon as
55
a result of C. shasta infection under different future climate scenarios. In addition to these Klamath-
specific models there is a long-term data set on the intensity and distribution of C. shasta infections in
juvenile salmon. The focus of this task is to examine the effect of climate change on temperature and
precipitation on the phases of the C. shasta life cycle involving M. speciosa.
Models:
Global circulation models (GCM): Global circulation models (GCMs) provide information on predicted
temperature and precipitation patterns based on 5 different climatic scenarios: 1) CCCMA - warm/wet,
2) MIUB - warm/dry, 3) GFDL - average temperature and precipitation, 4) NCAR - cool/dry and 5) MIR -
cool/wet. These GCMs were selected based on their quantile ranking for both predicted temperature
and precipitation. Several other factors will be affected by climate change (i.e. increase in the number
and severity of storm events, acidification, UV-radiation); however temperature and precipitation
predictions are the most robust across the different models and also the focus of this task. Perry et al.
(2011) used the predictions to estimate water temperature and discharge values in the Klamath Basin
from 2012-2061. Water temperature predictions will be used in a degree-day model for the phases of
the C. shasta life cycle involving M. speciosa and viability of C. shasta spore stages. The predicted
precipitation and resulting discharge values are used in a hydraulic model to assess the effect of peak
flow on polychaete habitat.
D.2.5 Preliminary results and next steps
Modeling the effects of water temperature on interactions between C. shasta and M. speciosa:
experiments to determine the total number of degree days required for M. speciosa to become infected
with and produce actinospores for C. shasta genotypes I, IIR, and III are in progress in our laboratory.
The data will be incorporated into a degree day model developed by Chiaramonte (2013).
Modeling the effects of predicted changes in precipitation: We have run simulations for two different
climate scenarios, including CCCMA and NCAR. Following a low magnitude peak flow, e.g., 2010, the
probability of polychaetes in study reach 2 was modeled at 39.8% and for an intermediate magnitude
peak discharge, modeled at 30.4% (Table D.2.5.1). Under both the CCCMA and NCAR, the probability of
polychaetes is reduced under higher peak discharges (e.g., 2040 in CCCMA or 2050 in NCAR). Additional
climate scenarios will be examined using this approach as we continue to refine the predictive model for
polychaete hosts (Task D.2.4., above).
56
Table D.2.5.1. Water year, climate model, value of peak discharge, and predicted probability of polychaete hosts in model reach 2.
Water Year
model Winter peak
discharge
Probability of polychaetes
in reach 2
2010 Actual peak 1981 0.398
2012 Actual peak 4070 0.304
2020 CCCMA 7305 0.247
2030 CCCMA 4270 0.310
2040 CCCMA 14176 0.105
2050 CCCMA 12260 0.144
2060 CCCMA 2756 0.341
2020 NCAR 8770 0.216
2030 NCAR 4147 0.312
2040 NCAR 6060 0.273
2050 NCAR 9338 0.205
2060 NCAR 1657 0.432
D.2.6 Regular dissemination of research findings to provide stakeholders, managers, researchers and the
general public ready access to current information and historical datasets pertinent to C. shasta in the
Klamath River.
D.2.6 (a) Preliminary Result Summaries
The contractor will provide brief preliminary summary information to Reclamation on a monthly basis
each field season on an as-requested by Reclamation. Additionally, preliminary findings may also be
made available in the form of a professional presentation at a meeting with Reclamation and other
state, federal, and tribal agencies. BOR has been furnished with monthly reports during the monitoring
season and quarterly reports throughout the contract period, as per schedule and as per request by
BOR.
D.2.6 (b) Annual Reports: The contractor will provide Reclamation an annual report of research for this
study, per the schedule listed below.
This report will include a description of the study questions, methods of data collection and analyses,
results of data analyses, and a discussion of the significance of the data. Draft copies of the annual
report of research will be distributed to Reclamation and other interested parties for review before the
report is finalized. This item is part of this fulfillment.
D.2.6 (c) Website to be maintained by the contractor for dissemination of results and project
information to the public.
Final data is made available as it is completed; water sample data is shared at least monthly, more often
during outmigration; meeting agendas and abstract are made available.
57
D.2.6 (d) Annual Klamath River Fish Health Workshops will review results of disease research, and will be
coordinated by the contractor.
This meeting was held Tuesday March 4th in Fortuna California. Representatives from the Bartholomew
Lab (OSU), CA-NV Fish Health Center, Yurok and Hoopa Tribal Biologists, Arcata USFWS, BOR, PacifiCorp,
NOAA, NMFS, DWR, Stillwater Sciences and Riverbend Sciences participated. A summary report has
been submitted to BOR.
D.2.6 (e) Annual project coordination meeting with project collaborators.
This was held January 15 in Ashland. There were 17 participants representing the Yurok and Karuk
tribes, Ca-Nv Fish Health Center, Arcata USFWS, USGS, NOAA, BOR, PacifiCorp and OSU. A summary
report has been submitted to BOR.
D.2.6 (f) Submit findings for publication in peer-reviewed scientific journals.
The following manuscripts have been accepted for publication, are in review, or are in preparation:
Ray, RA, Perry, RW, Som, NA, and Bartholomew JL (2014) Using cure models for analyzing the influence
of pathogens on salmon survival. Transactions of American Fisheries Society. In press.
R Adam Ray PhD dissertation: http://hdl.handle.net/1957/43334
Ray, RA and Bartholomew JL (in prep) Using an epidemiological model to quantify sensitivity of
myxozoan (Ceratomyxa shasta) disease dynamics to demographic parameters. In prep.
Jordan M.S., Alexander, J.D., Grant, G.L., and J.L. Bartholomew (in review) Discharge drives interannual
variation in distribution and density of the invertebrate host (Manayunkia speciosa) of a salmon parasite
(Ceratomyxa shasta). Freshwater Science.
Alexander, J.D., Som N.A., Wright, K.A., Hetrick, N.J., and J.L. Bartholomew (in prep) Novel use of 2-D
models to predict the distribution and density of hosts under various water year contexts. Ecological
Applications
Alexander, J.D., Hallett, S.L, Stocking, R.W., Xue, L., and J.L. Bartholomew (in press) Host and parasite
populations after a ten year flood: Manayunkia speciosa and Ceratomyxa shasta in the Klamath River.
Northwest Science.
D.2.7 List of Data Collection Sites (Location Names, River Mile/KM)
(a) Fish exposure sites
(1) Williamson River – RKM 441
(2) Keno Eddy - RKM 369
(3) Klamathon Bridge – RKM 302 I5 RKM 287.2
(4) Beaver Creek – RKM 258
(5) Seiad Valley – RKM 207
(6) Orleans – RKM 90
(7) Tully Creek – RKM 62
58
Klamathon Bridge was replaced by the I5 rest stop site (KI5), Rkm 287.2.
(b) Water collection sites for parasite densities
(1) all of the fish exposure sites above
(2) Kinsman trap – RKM 235
(c) Polychaete index model sites (summer sampling)
(1) Tree of Heaven – RKM 279
(2) Beaver Creek – RKM 259
(3) Grange – RKM 271
No changes from the schedule.
(d) Polychaete index sites (quarterly)
(1) Keno Eddy - RKM 369
(2) JC Boyle
(3) Tree of Heaven – RKM 279
(4) Beaver Creek – RKM 258
(5) Seiad Valley – RKM 207
(6) Orleans – RKM 90
A seventh site, KI5 was added to the schedule.
D.2.8 Site Visit Schedule
(a) Sentinel fish exposures:
(1) late April - above Beaver Creek and near Seiad Valley
(2) mid-May – six mainstem sites
(3) mid-June – seven mainstem sites
(4) July – possible exposure above Beaver Creek
(5) mid-September - above Beaver Creek and near Seiad Valley
(6) late October - above Beaver Creek
The goal at each exposure site is 40 susceptible juvenile rainbow trout and 40 Iron Gate Hatchery (IGH)
fall Chinook salmon exposed for 72 hr. IGH coho will be exposed May and June at only Beaver Creek and
Seiad Valley.
Exposures were conducted according to the schedule.
(b) Water collection sites for parasite densities:
(1) all of the fish exposure sites during exposures
(2) Weekly all year at Beaver Creek, Seiad Valley
(3) Weekly from March through October at I5, Orleans and Tully Creek
(4) March through mid-June at I-5 and Kinsman traps
(c) Polychaete sampling - Quarterly
59
D.2.9 Sample Processing (Rolling vs Batch)
(a) Mortality data for sentinel fish to be collated weekly, with final data at the end of the 60 d holding
period
(b) Water sample analysis to be rolling with updates available biweekly
(c) Polychaete sample processing is rolling and updated annually
Acknowledgements
The Karuk and Yurok tribes assisted with water sample collection and filtration. Jamie Graene and
Johnny Catena (OSU) assisted with qPCR. California Department of Fish and Game (Keith Pomeroy and
crew at the Iron Gate Hatchery) provided Klamath River fall Chinook and coho salmon juveniles for our
sentinel studies. Roaring River Hatchery, Oregon Department of Fish and Wildlife, Scio, provided
susceptible rainbow trout. We are grateful to land owners who allow us access to conduct the sentinel
studies and water sampling: The Nature Conservancy and Lonesome Duck Resort both of Klamath Falls,
OR; The Sportsman’s Park Club near Keno, OR; Fisher’s RV Park at Klamath River, CA; Wally Johnson,
Seiad Valley; Sandy Bar Resort, Orleans, CA.
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