RESEARCH PAPER
Infectious disease in fish: global risk of viral hemorrhagicsepticemia virus
Luis E. Escobar . Joaquin Escobar-Dodero . Nicholas B. D. Phelps
Received: 27 November 2017 / Accepted: 15 June 2018
� Springer International Publishing AG, part of Springer Nature 2018
Abstract As the global human population continues
to increase and become more industrialized, the need
for safe, secure, and sustainable protein production is
critical. One sector of particular importance is seafood
production, where capture fishery and aquaculture
industries provide 15–20% of the global protein
supply. However, fish production can be severely
affected by diseases. Notably, viral hemorrhagic
septicemia, caused by the viral hemorrhagic sep-
ticemia virus (VHSv; Rhabdoviridae), may be one of
the most devastating viral diseases of fishes
worldwide. We explored the ecology and epidemiol-
ogy of VHSv using an ecological niche modeling
approach to identify vulnerable disease-free regions.
Results showed an impressive ecological plasticity of
VHSv. The virus was found in[ 140 fish species in
marine and freshwater ecosystems, with high diversity
of lineages in Eurasia. Sub-genotypes frommarine and
fresh waters were ecologically similar, suggesting
broad ecological niches, rather than rapid evolutive
adaptation to novel environments. Ecological niche
models predicted that VHSv may have favorable
physical (e.g., temperature, runoff), chemical (e.g.,
salinity, pH, phosphate), and biotic (i.e., chlorophyll)
conditions for establishing into areas with important
fish industries that, so far, are believed to be disease-
free (i.e., freshwater and marine ecosystems of Africa,
Latin America, Australia, and inland China). The
model and our review suggest fish species from the
Perciformes, Salmoniformes, and Gadiformes orders
are likely to be infected with VHSv in novel regions as
the virus expands its range to areas predicted to be at
risk. In conclusion, VHSv remains an emerging
disease threat to global food security and aquatic
biodiversity.
Keywords Disease � Ecological niche model �VHS �Viral hemorrhagic septicemia
Electronic supplementary material The online version ofthis article (https://doi.org/10.1007/s11160-018-9524-3) con-tains supplementary material, which is available to authorizedusers.
L. E. Escobar (&)
Department of Fish and Wildlife Conservation, Virginia
Tech, 310 West Campus Drive, Cheatham Hall, Room
101, Blacksburg, VA 24061, USA
e-mail: [email protected]
J. Escobar-Dodero
Facultad de Ciencias de la Vida, Universidad Andres
Bello, Santiago, Chile
N. B. D. Phelps
Minnesota Aquatic Invasive Species Research Center,
University of Minnesota, St. Paul, MN, USA
N. B. D. Phelps
Department of Fisheries, Wildlife and Conservation
Biology, University of Minnesota, St. Paul, MN, USA
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Rev Fish Biol Fisheries
https://doi.org/10.1007/s11160-018-9524-3
Introduction
The sustainability of capture fisheries and aquaculture
industries are vital to meeting the growing global
demand for protein. Aquatic food represents 15–20%
of the world’s population protein intake, with fish
production growth annually surpassing that of terres-
trial livestock including poultry, beef, and swine
(Lucas 2012; FAO 2014). According to the Food and
Agriculture Organization of the United Nations
(FAO), global production of fish has increased con-
sistently during the last 100 years, reaching approx-
imately 167million tons of fish products in 2014 (FAO
2016a). However, over the last 30 years, production
from global capture fisheries have remained stable,
while the aquaculture industry has been rising by 8.6%
annually (FAO 2014, 2016a). The growth can be seen
in terms of total production and number of species
produced in both freshwater and marine systems (FAO
2016a). Today, approximately 44% of worldwide fish
products are generated from aquaculture facilities in
marine (16%) and freshwater (28%) systems and are
valued at approximately US $137.7 billion (FAO
2016a). This shift towards aquaculture is largely in
response to the human need for fish products and
declining wild stocks (Penning et al. 2009).
The intensification of aquaculture has increased
infectious disease outbreaks in both farmed and wild
fish populations (Lafferty and Hofmann 2016). High
densities of fish can result in increased host stress and
modern fish trade promotes the geographic movement
of fish and byproducts, potentially driving disease
emergence and spread (Walker and Winton 2010;
Crane and Hyatt 2011; Owens 2012). Examples of this
include the geographic translocation of Infectious
Salmon Anemia virus from Europe to Chile (Kibenge
et al. 2009), causing catastrophic losses to the salmon
industry (Asche et al. 2009), wild fish infestations with
sea lice (Lepeophtheirus salmonis) amplified by
aquaculture facilities in Canada (Krkosek et al.
2005), and opportunistic infections with Flavobacte-
ria spp. in catfish (Shoemaker et al. 2003), to name a
few.
First reported from freshwater Rainbow trout
(Oncorhynchus mykiss, Salmonidae) in Europe in the
1930’s, viral hemorrhagic septicemia, caused by the
viral hemorrhagic septicemia virus (VHSv), is a
devastating fish disease (Wolf 1988; Kim and Faisal
2011). The VHSv is an RNA virus belonging to the
Novirhabdovirus genus within the Rhabdoviridae
family (Dietzgen et al. 2011), with a broad distribution
of lineages across continents (He et al. 2014), ecosys-
tems (i.e., marine and freshwater) (Smail and Snow
2011), and host species, infecting cool and cold water
fish (Einer-Jensen et al. 2004; Snow et al. 2004). Given
the wide range of fish species affected by the virus,
broad geographic distribution, pathogenicity, disease
course, mortality rates, and high dispersal potential,
VHSv could indeed be considered one of the most
serious viral pathogens of wild and farm-raised fish
worldwide (see Skall et al. 2005a, b; Kim and Faisal
2011).
Waterborne transmission is the natural and domi-
nant route of VHSv infection (Hershberger et al.
2011). Oral transmission has been associated with
VHSv infection but in lesser magnitude; nevertheless,
predation of infected fish cannot be excluded as a
potential transmission route (Schonherz et al. 2012;
Getchell et al. 2013). Once infected, fish can develop a
series of symptoms including the hemorrhagic signs
characteristic of VHS (Wolf 1988) with internal
lesions that include edema (liquid in cavities of the
body and tissues) and petechiae (minor bleeding) in
visceral organs, muscle, and brain, and external
lesions including exophthalmia (protrusion of the
eyeball), skin darkening, and pale gills. Behavioral
alterations can appear, including anorexia, lethargy,
and erratic swimming (Skall et al. 2005b; Emmeneg-
ger et al. 2013; Lovy et al. 2013; Cornwell et al. 2014;
Munro et al. 2015).
Based on the structural composition of the nucle-
oprotein and glycoprotein, four VHSv genotypes have
been identified (I, II, III and IV) which are also divided
in sub-genotypes (i.e., Ia–Ie and IVa–IVc) (Einer-
Jensen et al. 2004; Snow et al. 2004). In general,
research on VHSv has largely focused on understand-
ing the distribution of the virus from the microscopic
to local scale (Estepa and Coll 1997; Gaudin et al.
1999; Isshiki et al. 2002; Arkush et al. 2006; Vo et al.
2015) [but see (King et al. 2001b; Cornwell et al.
2015)]. There have been limited explorations on the
global distribution of this pathogen, the biogeographic
factors limiting its distribution, or the potential areas at
risk for future epidemic (VHSV Expert Panel and
Working Group 2010).
Given the critical importance of aquaculture to
global food security and the continued risk of VHSv
emergence in new geographic areas around the world,
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we reviewed the ecology and epidemiology of this
virus across its entire distribution. This study is the
first comprehensive review of VHSv cases and species
affected around the world coupled with ecological
data. We defined two main goals: (1) describe the
biogeographic patterns of VHSv lineages (i.e., their
geographic and environmental distribution), and,
based on this knowledge, (2) forecast potential
distribution of VHSv spread in marine and freshwater
ecosystems. Accomplishing these goals provided
information to understand the ecology and geography
of VHSv at a global scale, and also provided the tools
to identify high risk areas to improve disease moni-
toring and surveillance where, according to our
models, aquaculture industries could be impacted in
the future.
Methods
First, an assessment of susceptible species was con-
ducted based on a literature review of infected species.
Then, we used ecological niche modeling methods
based on a type of logistic-regression linking VHSv
cases with environmental variables. Models were
developed for the entire VHSv range at a coarse scale
and complementary models at fine resolution were
developed for inland and marine regions. Cases of
VHSv lineages were represented in geographic coor-
dinates, while environmental variables were summa-
rized in global grids.
VHSv distribution
A comprehensive scoping study of worldwide VHSv
cases was conducted using repositories and peer-
review literature (Arksey and O’Malley 2005; Levac
et al. 2010). The retrieved information included
genotype, geographic location, and host species
infected by region by year. We grouped records by
region, order, family, and species. To identify suscep-
tible fish species, we searched for reports of fish
infections including evaluation of natural outbreaks,
and those identified as susceptible in laboratory
challenge studies. Occurrence records of VHSv from
around the globe, comprising mainly Europe and Asia,
were collected from the FishPathogens repository
(Jonstrup et al. 2009). Most VHSv cases from North
America were collected primarily from Escobar and
colleagues (Escobar et al. 2017) who in turn collected
the data from the Molecular Epidemiology of Aquatic
Pathogens viral hemorrhagic septicemia virus repos-
itory (USGS 2013). These two online repositories
were consulted to include data up to February 2016.
Complementary VHSv cases were gathered from
scientific literature (see (Meyers et al. 1994; Takano
et al. 2001; Dopazo et al. 2002; Hedrick et al. 2003;
Kim et al. 2003, 2009, 2011; Dixon et al. 2003; Gagne
et al. 2007; Lee et al. 2007; Faisal and Schulz 2009;
Altuntas and Ogut 2010; Faisal and Winters 2011;
Frattini et al. 2011; Millard and Faisal 2012; Faisal
et al. 2012; Garver et al. 2013; Gadd 2013; Minamoto
et al. 2014; Cornwell et al. 2014; Moreno et al. 2014;
Ogut and Altuntas 2014a; Ahmadivand et al. 2016)).
Geographic coordinates of VHSv cases were grouped
according to genotype information, when available
(Fig. 1; Supporting Information S1). Reports without
coordinates were georeferenced using Google Earth,
and VHSv locations in forms of maps without detailed
geographic coordinates were orthorectified to extract
coordinates using the Georeferencer tool in QGIS Pisa
(QGIS Development Team 2015). In all, 1095 geo-
graphic coordinates were collected for wild and
farmed fishes infected with VHSv. After removing
duplicates, 598 VHSv locations remained for fresh-
water and marine models (Ia = 102, Ib = 37, Ic = 5,
Id = 24, Ie = 9, II = 13, III = 27, IVa = 95, IVb =
103, IVc = 4, not genotype identified = 233).
Ecological niches
Biogeographic explorations to determine the geo-
graphic and environmental distribution of VHS lin-
eages were done using ecological niche modeling
theory and methods. An ecological niche is defined as
the set of environmental conditions in a region,
necessary for a species to persist without the need of
immigration (Peterson et al. 2011). According to
Hutchinson (Hutchinson 1957), ecological niches are
demarcated first in environmental dimension and then
expressed in the geographic space (Colwell and
Rangel 2009) (for a deeper explanation see Supporting
Information S2).
Ecological niche models by sub-genotype
Ecological niche models by sub-genotype were devel-
oped in the model calibration area defined based on
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our hypothesis of VHSv dispersal potential. To the
best of our knowledge, the VHSv reports in inland
North America represent a new introduction of the
virus into the Great Lakes region, thus, the dispersal of
VHSv across inland North America may be a proxy of
dispersal potential for VHSv. We measured the
maximum distance between VHSv reports in this
area, * 2100 km (details in Supporting Information
S2), and used this distance as a buffer surrounding all
the occurrence reports of VHSv to establish our model
calibration area used in posterior analyses (Fig. 2a). In
the model calibration area, we first explored patterns
of VHSv distribution based on climatic information
covering freshwater and marine ecosystems. Climate
explains biomes worldwide and is a good approxima-
tion to understand biogeographic patterns of organism
distribution (Martınez-Meyer et al. 2004).
Specifically, we used 19 bioclimatic variables devel-
oped based on long-term values of temperature and
precipitation from ecoClimate (Table 1). ecoClimate
is an open access repository of global climate data
covering freshwater and marine regions at 0.5� spatialresolution for the period 1950–1999 (Lima-Ribeiro
et al. 2015). Using ArcGIS 10.3 (ESRI 2017), we first
limited the original ecoClimate variables to the model
calibration area (Fig. 2a), then, we developed a
principal components analysis (PCA) for standardiza-
tion of variables, reduction of correlation, and dimen-
sionality reduction, retaining the new components
summarizing C 99.9% of the information from the
original variables (Peterson et al. 2011). The retained
components were used to calibrate the ecological
niche models by VHSv sub-genotype using Maxent
3.3.3k (Phillips et al. 2006), parameterizing each
Fig. 1 Global distribution of viral hemorrhagic septicemia
virus (VHSv) reports. Global distribution of VHSv genotypes
(green dots). a The geographic location of VHSv sub-genotype
IVa in the Pacific coast of North America (red points); b sub-
genotypes IVb and IVc in the Great Lakes region (red squares)
and Atlantic coast of Canada (red triangles), respectively, and
genotype III (green triangle); c sub-genotypes Ia (blue points),
Ib (yellow squares), Ic (orange points), Id (purple triangles), Ie
(gray squares), II (light blue points), and III (green triangle) in
Eurasia; d sub-genotypes IVa (red points) and Ib (yellow square)
in Japan and South Korea. Point location without a reported
VHSv genotype are also displayed (pink crosses)
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Rev Fish Biol Fisheries
Fig. 2 Model calibration area and areas of model transference.
a Model calibration area based on a proxy of VHSv dispersal,
used for ecological niche modeling. Model selection, similarity
tests, and final calibration were developed in this region (dark
gray). b Area used for ecological niche model transference to
inland freshwaters, based on regions reporting Rainbow trout
industries (dark gray; see methods). c Area used for ecological
niche model transference to marine coastal regions (dark gray)
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model based on the data available for each sub-
genotype (details in Supporting Information S2).
Visualization and posterior analysis of inland and
marine data in a multidimensional environmental
scenarios were conducted using NicheA software
(Qiao et al. 2016).
Table 1 Variables used for the VHSv ecological niche models
Models by sub-genotype Models in inland Models in marine areas
Abbr. Variable Unit Abbr. Variable Unit Abbr. Variable Unit
Bio1 Annual mean
temperature
�C Bio1 Annual mean
temperature
�C Calcite Mean calcite
(CaCO3)
concentration
mol/m3
Bio2 Mean diurnal range �C Bio2 Mean diurnal range �C Chlomean Mean chlorophyll A
concentration
mg/m3
Bio3 Isothermality % Bio4 Temperature
seasonality
% Cloudmean Mean cloud fraction %
Bio4 Temperature
seasonality
% Bio7 Temperature annual
range
�C pH pH values in the
ocean
–
Bio5 Maximum temperature
of warmest month
�C Bio8 Mean temperature
of wettest quarter
�C Phosphate Phosphate
concentration
lmol/l
Bio6 Minimum temperature
of coldest month
�C Bio12 Annual
precipitation
mm Salinity Dissolved salt
content
Practical
salinity scale
(PSS)
Bio7 Temperature annual
range
�C Bio15 Precipitation
seasonality
% Sstmean Mean sea surface
temperature
�C
Bio8 Mean temperature of
wettest quarter
�C Bio17 Precipitation of
driest quarter
mm Sstrange Sea surface
temperature range
�C
Bio9 Mean temperature of
driest quarter
�C
Bio10 Mean temperature of
warmest quarter
�C
Bio11 Mean temperature of
coldest quarter
�C
Bio12 Annual precipitation mm/
m2
Bio13 Precipitation of wettest
month
mm/
m2
Bio14 Precipitation of driest
month
mm/
m2
Bio15 Precipitation
seasonality
mm/
m2
Bio16 Precipitation of wettest
quarter
mm/
m2
Bio17 Precipitation of driest
quarter
mm/
m2
Bio18 Precipitation of
warmest quarter
mm/
m2
Bio19 Precipitation of coldest
quarter
mm/
m2
Models by sub-genotype ‘‘ecoClimate’’ variables at coarse scale (i.e., 0.5� spatial resolution) (Lima-Ribeiro et al. 2015). Models in
inland areas ‘‘WorldClim’’ variables at fine scale (i.e., 0.05� spatial resolution) (Hijmans et al. 2005). Models in marine areas ‘‘Bio-
ORACLE’’ environmental layers (0.09� spatial resolution) (Tyberghein et al. 2012)
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Finally, we explored ecological niche similarities
among VHSv sub-genotypes in environmental and
geographic dimensions. We used the Jaccard index
(Jaccard 1912) ranging from 0 to 1 to measure the
overlap of convex polyhedrons constructed with the
binary Maxent models for each sub-genotype in the
multidimensional environmental space estimated
using NicheA (Qiao et al. 2016). We also used the
Schoener’s D index (Warren et al. 2010) ranging from
0 to 1 to measure the overlap of the binary ecological
niche models by sub-genotype developed in Maxent
and expressed in the form of a geographic raster of
suitable (i.e., 1) and unsuitable conditions (i.e., 0).
Both indices were plotted to identify if patterns of
niche similarity remained consistent among both
environmental and geographic dimensions.
Ecological niche models in freshwater and marine
ecosystems
Additionally, more detailed ecological niche models
of VHSv were developed for freshwater and marine
ecosystems using the protocol describe above, but
with environmental variables at finer spatial resolu-
tion. These models forecasted specific areas at risk in
terms of environmental suitability for VHSv. First, all
cases were pooled for those occurring in freshwater or
marine ecosystems. Location in brackish zones were
included in both ecosystems when occurrences over-
lapped environmental rasters. Freshwater models were
calibrated using a subset of the 19 bioclimatic
variables from the Worldclim repository (Hijmans
et al. 2005), including information of temperature and
precipitation at 0.05� for the period 1970–2000, the
latter being a proxy of water accumulation. Marine
models were calibrated using a subset of 23 satellite-
based geophysical, biotic, and climatic variables from
the Bio-ORACLE (Tyberghein et al. 2012), reposi-
tory, including sea surface temperature, oxygen,
chlorophyll, salinity, pH, nitrate, phosphate, silicate,
and cloud cover at 0.09� for the period 2005–2010.
The number and correlation of original variables in
each dataset (i.e., freshwater or marine) were reduced
by removing variables with correlation C 0.7, retain-
ing those with higher biological association to the
virus (Escobar et al. 2017). Freshwater and marine
models were calibrated in the model calibration area
(Fig. 2a; Supporting Information S2) for a posterior
model transference to regions of interest, but also
outside the calibration area, including countries with
significant aquaculture industries producing suscepti-
ble species, such as Rainbow trout (Fig. 2b) (Neukirch
and Glass 1984; Skall et al. 2004; FAO 2016b). We
also considered neighbor regions to VHSv endemic
countries assuming that the closeness to infected
countries may be of special risk for VHSv spread.
Marine variables were transferred to the coastal areas
of these countries based on a 370 km buffer from the
shoreline (i.e., exclusive economic zone as area of
potential aquaculture activity; Fig. 2c). Standard
deviations were estimated from 1000 permutations to
account for variability in the final models. The most
important environmental variables for model calibra-
tion were identified usingMaxent, interpreting them as
the most likely variables that explain the presence of
VHSv across its distribution. Continuous models were
converted to binary using a threshold value based on
our tolerance of omission error (i.e., E = 5%), which
represents the removal of 5% of the occurrence points
with lowest suitability values predicted by the model
(Peterson et al. 2008). This removal was assumed to
represent sink populations found in the less suit-
able conditions where VHSv has been detected to date
(Peterson 2014).
Results
The review of VHSv cases resulted in 144 fish species
reported infected with the virus and 4 genera not
identified at species level (Supporting Information
S3). Annual reports of novel fish species confirmed
VHSv-positive, ranged from 0 to 17 with an average
of * 3 new fish species detected annually since 1962
(Fig. 3). The fish orders with the more species reported
infected with VHSv were Perciformes (n = 49),
Salmoniformes (n = 16), and Gadiformes (n = 14).
Genotype IV had the widest documented host range
(n = 70 fish species), followed by I (n = 31), III
(n = 20), and II (n = 5). Genotype was not reported in
33 fish species infected with VHSv (Supporting
Information S3). Genotype I was most frequent in
orders Perciformes (6), Gadiformes (6) and Pleu-
ronectiformes (6), while VHSv genotype II was only
found in Cupleiformes (2), Cypriformes (1), Gadi-
formes (1), and Petromyzontiformes (1). Genotype III
occurred with highest frequency in orders Perciformes
(5) and Gadiformes (5), while VHSv genotype IV
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Rev Fish Biol Fisheries
occurred mainly in Perciformes (23), Cypriniformes
(9), and fish species from the order Salmoniformes (8).
Ten fish species were reported positive to more than
one VHSv genotype (see more details in table of
Supporting Information S3). Reports were distributed
only across the Northern Hemisphere with no reports
from tropical or Southern Hemisphere regions
(Figs. 1, 2a). However, based on the presence of
susceptible hosts and potential translocation through
aquaculture activities, areas of interest for model
projection were included in all the Southern Hemi-
sphere as well (Fig. 2).
Climatic variables from ecoClimate were highly
correlated (e.g., bio1 had a q[ 0.9 with bio6, bio11,
and bio10, similar to bio16 vs. bio12 and bio 13;
Supporting Information S4), thus, the first three
principal components summarized 98.39% of the
overall variability, and eight components included
[ 99.9% of all the information and were used for
generating models of sub-genotypes. Sub-genotype
models required regularization coefficients ranging
from 0.5 to 1.5 to obtain the best model fit (Supporting
Information S5). Explorations of niche similarities
resulted in an agreement of estimations between
Schoener’s D and Jaccard indices for most compar-
isons, especially for sub-genotypes Ia, Id, IVb, and IVc
(Fig. 4). Ecological niche models of sub-genotypes Ia,
Id, IVb, and IVc have low similarity with models of
other sub-genotypes. Niche similarities were higher
for comparisons between Ib versus Ic, Ic versus Ib, Ic
versus Ie, Ie versus Ic, III versus IVa, III versus Ib, and
IVa versus III due to the broad niche breath for some
sub-genotypes. For example, when sub-genotypes III
and IVa were displayed in environmental dimensions
we observed that both populations occupied a similar
environmental space; however, sub-genotype IVa had
a broader niche entirely containing sub-genotype III
(Fig. 5).
The final models from the calibration area were
projected to inland areas in 77 countries (Fig. 2b) and
coastal areas in 19 countries (Fig. 2c). Inland predic-
tions included eight uncorrelated variables (i.e., bio1,
bio2, bio4, bio7, bio8, bio12, bio15, bio17; Table 1;
Supporting Information S6) and a regularization
coefficient of 1 provided the best model fit in Maxent
(Supporting Information S5). The environmental
Fig. 3 Cumulative number of fish species reported positive to VHSv between 1962 and 2015
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Rev Fish Biol Fisheries
variables of inland models with highest percent
contribution included annual mean temperature
(bio1, 42.8%), precipitation of driest quarter (bio17,
24.8%), and mean diurnal range (bio2, 12.7%). Eight
uncorrelated environmental variables were used for
ecological niche models developed in coastal areas
(i.e., calcite, mean chlorophyll, mean cloud fraction,
phosphate, salinity, and mean and range of sea surface
temperature; Table 1; Supporting Information S7).
The final Maxent ecological niche model for coastal
areas was calibrated with a regularization coefficient
of 1.5 (Supporting Information S5). The
Fig. 4 Niche similarity tests. Pairwise comparisons of
Schoener’s D (y axis) and Jaccard indices (x axis) between
one Viral Hemorrhagic Septicemia virus sub-genotype versus
all the other sub-genotypes. E.g., the first scatterplot denotes
sub-genotype Ia versus sub-genotypes Ib (blue), Ic (light green),
Id (yellow), Ie (black), II (light blue), III (pink), IVa (brown),
IVb (orange), IVc (green)
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Rev Fish Biol Fisheries
environmental variables of marine models with high-
est percent contribution included mean chlorophyll-
a concentration (chlomean, 60.3%), mean sea surface
temperature (Sstmean, 27.3%), and sea surface tem-
perature range (Sstrange, 4.5%). Freshwater and
marine ecological niche models allowed predictions
at a finer resolution and uncertainty estimations by
pixel cell (Supporting Information S8 and S9).
According to Maxent, the two most important vari-
ables for inland and marine regions were annual mean
temperature (42.8%) and precipitation of driest quarter
(24.8%), and mean chlorophyll-a concentration
(60.3%) and mean sea surface temperature (27.3%),
respectively.
Freshwater forecasts found suitability for VHSv in
Asia, Europe, Africa, the Americas and, Australia
(Fig. 6). Continuous suitable areas were found across
the Great Lakes region of North America and in
Europe including coastal areas of the Black Sea in
Turkey. Scattered areas were found in Central Amer-
ica, southern parts of Chile, Ecuador, Colombia,
Argentina, and Venezuela. The models predicted
environmental suitability for VHSv across the Hima-
layas, Australia, and inland China. VHSv’s suitable re-
gions were also predicted in broad coastal areas in the
Pacific coast of North America from northern Mexico
to Alaska, the Atlantic coast of North America from
Florida in the United States to Nova Scotia province in
Canada, southern coasts of Iceland, coastal regions of
northern Europe including the North Sea, Blatic Sea,
English Channel, the coast of Western Sahara, the
Gulf of Cadiz, and small portions the Alboran Sea.
Additionally, suitability was found in the Yellow Sea
in southern China, coastal zones surrounding South
Korea, and Japan (Fig. 6).
Summary of key findings
Analyses suggest that VHSv may have favorable
conditions for spread and establishment beyond the
current areas affected in the Northern Hemisphere. For
Fig. 5 Ecological niche
modeling comparisons in
environmental space.
a Example of two VHSv
sub-genotypes, III (green)
and IVa (red), occurring in
regions geographically
distant. b Ecological niche
models of two VHSv sub-
genotypes, III (green) and
IVa (red), overlap in
environmental dimensions,
suggesting similar
environmental conditions
occupied by both sub-
genotypes. Environmental
space created based on
values (gray points) of the
first three principal
components of 19
bioclimatic variables
(X = PC1, Y = PC2,
Z = PC3)
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Rev Fish Biol Fisheries
example, freshwater and marine ecosystems of Africa,
Latin America, Australia, and inland China were
found suitable for VHSv in terms of environmental
conditions. Strikingly, areas suitable have fish taxa
potentially susceptible of VHSv infection as suggested
by the phylogenetic relationship with fishes known to
be affected by VHSv. That is, our study suggests that
fish species from the Perciformes, Salmoniformes, and
Gadiformes orders are likely to be infected with VHSv
Fig. 6 Ecological niche models of VHSv in freshwater and
marine ecosystems. The potential geographic distribution of
VHSv based on environmentally suitable conditions (red) were
identified in a Europe; b The Great Lakes region and the east
coast of North America; c The west coast of northern North
America; d Central America and northern South America;
e southern South America; f northwestern coast of Africa;
g Kenya; h Himalaya Mountains, China, and Japan; and
i southern Australia
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Rev Fish Biol Fisheries
in novel regions as the virus expands its range to areas
predicted to be at risk.
Discussion
Susceptible fishes
Across all regions of the world, in freshwater and
marine environments, we found VHSv-susceptible
fish species of ecological or economical importance.
The order Perciformes had the highest number of fish
species susceptible, mainly in wild fishes in Europe
(Skall et al. 2005a; Moreno et al. 2014; Munro et al.
2015) (Supporting Information S3), while Salmoni-
formes was the second (Meyers et al. 1994; Mortensen
et al. 1999; Skall et al. 2005a; Gadd et al. 2011; Garver
et al. 2013; Sandlund et al. 2014). Historically,
Salmoniformes production has been significantly
impacted by VHSv epidemics. For example, Rainbow
trout, a Salmoniforme, is highly susceptible to geno-
types I (Skall et al. 2004) and genotype III (Dale et al.
2009). Indeed, mass mortalities of Rainbow trout
infected with VHSv and the subsequent management
interventions has had a major impact on the European
aquaculture industry (Jimenez de la Fuente et al. 1988;
Skall et al. 2005b). However, in the Great Lakes
region of North America, native Salmoniformes have
been shown to be susceptible to VHSv with minimal
mortality rates (Kim and Faisal 2010, 2011; Weeks
et al. 2011; Emmenegger et al. 2013; Garver et al.
2013). In this region, besides Salmoniformes fishes,
VHSv has affected native wild Perciformes fishes,
causing massive fish kills (Groocock et al. 2007;
Lumsden et al. 2007; Faisal et al. 2012). We argue that
Perciformes could play a key role in the ecology and
epidemiology of VHSv and their role as a carrier group
should not be overlooked considering the broad range
of host species found infected.
The order Pleuronectiformes has been associated
with VHSv outbreaks in economically important fish
species in Asia and Europe (Schlotfeldt et al. 1991;
Ross et al. 1994; Takano et al. 2000; Isshiki et al. 2001;
Kim et al. 2009). This shows that the virus can infect
distant regions and taxa (Lopez-Vazquez et al. 2011).
Additionally, several wild fish belonging to the order
Gadiformes have been infected with VHSv across
Eurasian coasts (Ogut and Altuntas 2014b), Atlantic
and Pacific Oceans (Meyers et al. 1992; Mortensen
et al. 1999; Smail 2000; King et al. 2001b; Dixon et al.
2003; Skall et al. 2005a; Sandlund et al. 2014;Wallace
et al. 2014), and in the Great Lakes region in North
America (Thompson et al. 2011).
Fish from the order Clupeiformes are also suscep-
tible and carriers of VHSv in different regions
including Europe (Mortensen et al. 1999; King et al.
2001a; Skall et al. 2005a; Moreno et al. 2014; Ogut
and Altuntas 2014a, b; Wallace et al. 2014) and North
America (Kocan et al. 1997; Hedrick et al. 2003;
Cornwell et al. 2012; Faisal et al. 2012; Garver et al.
2013) from fish kills and asymptomatic individuals.
Finally, fish from the Esociformes order are known to
be susceptible to VHSv with mortality reports in
farmed and wild fish in Europe and North America
(Meier and Jørgensen 1980; Enzmann et al. 1993;
Millard and Faisal 2012) including the Great Lakes
region (Elsayed et al. 2006). Many other fishes from
several orders are susceptible to VHSv as several
surveys have shown (Mortensen et al. 1999; Hedrick
et al. 2003; Moreno et al. 2014; Ogut and Altuntas
2014b) (Supporting Information S3), occasionally
from single, sometimes asymptomatic, reports.
VHSv genotypes
The distribution of VHSv sub-genotypes was site-
specific (Fig. 1 and Supporting Information S3),
supporting previous reports from limited data (Mor-
tensen et al. 1999; King et al. 2001b; Skall et al. 2005a;
Ogut and Altuntas 2014b). Genotype IV had the
greatest host species diversity, thus, this genotype
would be a candidate for plausible spillover into novel
species as it successfully invades freshwater and
marine systems in North America. Conversely, the low
similarity estimated from the narrow niches of Ia and
Id suggests that these sub-genotypes are specialized or
restricted to specific environmental conditions
(Fig. 4). Sub-genotypes with high values of overlap
and high similarity with other genotypes suggest broad
niches associated with generalist VHSv sub-geno-
types. Genotypes of broad niches would then be highly
adaptable and with high potential for spillover to other
fish species or regions. We note that geographic
distance is not necessarily indicative of environmental
difference. For example, we found VHS genotype III
in areas geographically isolated with one population in
northern Europe and another restricted off eastern
Newfoundland, in an area known as the Grand Banks
123
Rev Fish Biol Fisheries
(Fig. 5). While the presence of this genotype near
Newfoundland appears odd by itself—considering the
abrupt changes in topography in the area and the high
volume of fresh water flowing from the Artic current
(i.e., Labrador Current and sea ice) that generates
shallow, cold, low salinity sea water (Fratantoni and
McCartney 2010). This supports the idea of environ-
mental similarity among populations of this genotype
across its entire geographic distribution.
Europe presents the highest diversity of VHSv
lineages and is here proposed as the nucleus of VHSv
emergence and diversification. Thus, this region may
be of special interest to explore the potential effects of
co-infections (presence of more than one VHSv
genotype in the same individual host) in wild fish.
That is, future research may include assessing the
effects of co-infections on VHSv virulence, immune
response, and virus evolution. Understanding the
effects of co-infections would help to understand
how co-infections impact individuals and populations,
and will facilitate to identify areas with co-circulation
of genotypes to quantify the propensity of these areas
for VHSv epidemics.
VHSv risk areas
Our ecological niche model predicts VHSv suitable ar-
eas across the world, beyond the areas where the
disease is currently endemic. Some novel areas
predicted at risk include Argentina, Australia, Chile,
Mexico and Portugal (Fig. 6). Tropical countries like
Colombia and Ecuador showed suitability in high-
lands, especially in freshwaters of the Andes region,
which could support VHSv replication due to the cold
temperatures in these areas. Canada, China, France,
Germany, Italy, Spain, Turkey, and United Kingdom
showed suitable conditions for VHSV and had
reported VHSv outbreaks in the past; however, we
predicted suitable areas for VHSv in these countries
beyond the sites of previous records (Figs. 1, 6). On
the other hand, Norway and Denmark have been free
of VHSv for a decade (Dale et al. 2009; Kahns et al.
2012), but were predicted as areas of high risk by our
models. Indeed, Norway experienced a VHSv out-
break in 2007 (Dale et al. 2009), supporting the status
of a high risk area. Of the areas predicted VHSv
suitable, United States, Chile, Denmark, France, Italy,
Norway, and Turkey are of particular concern due to
the importance of farmed Rainbow trout, posing a risk
for their respective aquaculture industries. The models
also predicted some surprising patterns in freshwaters,
with suitable conditions predicted in the Great Lakes
region but only partial suitability to the northern areas
of Lake Superior. Likewise, a similar pattern was
observed in marine ecosystems in eastern Sweden in
the Gulf of Bothnia (Fig. 6). Such inconsistencies
could be related to the particularly low temperatures at
the latitudes where these lakes occur. Laboratory
assessments found that VHSv tolerates temperatures
ranging between 10 and 20 �C (Winton et al. 2007;
Goodwin and Merry 2011). Thus, temperatures below
this range may limit the presence of the virus in the
host or can be associated to fish species non suscep-
tible to VHSv.
Using reports from wild and farmed individuals
could be a limitation of the model to characterize
suitable landscape conditions where outbreaks could
occur (Peterson 2014); however, we found that
locations with VHSv-positive farms generally
reported wild fishes VHSv-positive (Einer-Jensen
et al. 2004; Dale et al. 2009), thus, suggesting that
the occurrences used provided the ecological signal to
identify the conditions environmentally suitable for
VHSv. Considering the high number of fish species
VHSv positive, our modeling framework was focused
on the abiotic environmental conditions suitable for
VHSv (Supporting Information S2), neglecting the
presence of susceptible fish. However, a more detailed
exploration at a local scale should consider the
presence and density of fish species from the orders
found highly susceptible to the virus. Furthermore,
correlative ecological niche models are impacted by
the areas selected for calibration (Barve et al. 2011).
Here, models were calibrated using a hypothesis of
dispersal potential estimated base on the spread of
VHSv in the last decade in the Great Lakes region.
This scenario, however, may be an overestimation of
viral translocation facilitated by human intervention
given other possible pathways of dispersal. Regardless
of the limitations, the information obtained from the
ecological niche models provide a signal of plausible
areas at risk that can be employed to justify VHSv
prevention and control methods including movement
restriction to reduce the potential spread of the virus to
naıve areas and species.
We noted that human population densities are
overall heaviest in some areas of highest potential
infection in Europe and North America (Fig. 6). This
123
Rev Fish Biol Fisheries
pattern could suggest that VHSv spread and estab-
lishment may be facilitated by human intervention
(e.g., recreational fishing and aquaculture). On the
other hand, VHSv models may be revealing the
influence of sampling bias—more reports in areas
with more people may result in models overpredicting
highly populated regions. Additionally, other organ-
isms overlapping with the distribution of VHSv could
influence its presence and detectability. For example,
considering that fish species vary in their susceptibility
to VHSv, future research could focus on the associ-
ation of the community composition on the prevalence
of VHSv, to determine if an increase in fish species
diversity reduces the prevalence of VHSv—a.k.a.
dilution effect (Schmidt and Ostfeld 2001). Addition-
ally, co-infections of VHSv and other piscine rhab-
doviruses may reduce the detectability and systemic
distribution of one of the viruses, suggesting apparent-
competition at the cell level (Brudeseth et al. 2002).
However, the use of ecological niche modeling to
reconstruct biotic interactions among multiple species
is still in its infancy (Anderson 2016), and more
research is necessary to assess the abilities of ecolog-
ical niche modeling to reconstruct complex biotic
interaction in disease systems.
While we believe the best available and most
complete data were used for this analysis, there are
nevertheless limitations given the types and quality of
data available. For example, each dataset was assem-
bled with a different methodology, including the use
of atmosphere–ocean global climate models (i.e.,
ecoClimate), interpolation of data from climatic
stations (i.e., Worldclim), and data interpolating
variational analysis (Bio-Oracle), resulting in different
values of uncertainty and assumptions. ecoClimate
provides a realistic estimation of global processes
associated with climate, covering a comprehensive
period and providing data for inland and marine
regions (Lima-Ribeiro et al. 2015); however, values
are expressed at coarse resolution (50 km) and vari-
ables may be highly correlated requiring a reduction in
number and collinearity. Worldclim provides infor-
mation of temperature and precipitation from a
comprehensive period from which most ecological
niche modeling estimations are developed (Hijmans
et al. 2005); however, data from countries with limited
number of climatic stations are underrepresented and
most values are simulated—i.e.,\ 1% values in the
climatic layers are real data (Peterson 2014). Bio-
Oracle was produced using averages of satellite-
derived data with most values representing real data
and providing information from environmental pat-
terns in the ocean at fine spatial resolution (Tyberghein
et al. 2012); however, these data cover a narrow period
and are representative of the surface of the sea,
neglecting the environmental conditions under the
surface, which are known to be dynamic and complex.
Finally, the models were based on static variables
since we used environmental data that captured long-
term patterns across the landscape. Future research to
account for spatial and temporal variability, such as
water currents, would create more dynamic models
that can be used to determine potential sites of origin,
paths of spread, and potential locations of future VHSv
outbreaks.
Final remarks
Our detailed analyses focused on specific areas for
model calibration, strict model transference into novel
regions, detailed model parametrization, model fit
evaluations, and fine resolution of uncorrelated envi-
ronmental variables. This allowed us to develop
detailed maps of potential VHSv establishment
(Fig. 6), and also provide uncertainty estimations to
better inform results’ interpretation (S7 and S8). We
found that VHSv has the potential to affect a broad
range of taxa, geographic areas, and environmental
conditions. The general patterns suggest that the
geographic distribution of VHSv is expected to
increase if the virus is translocated to suitable areas
across South America, Australia, and Asia. VHSv is
also expected to infect novel fish species not reported
in this study, with some generalist virus genotypes
potentially more prone to spillover due to the broad
environmental space currently occupied (e.g., geno-
type IV).
The risk of continued VHSv emergence in wild and
farm-raised fish is of considerable importance given
the history of VHSv. The increasing number of VHSv
reports, highlight the importance of proper surveil-
lance not only in aquaculture facilities, but also in wild
species. Our results should guide efforts to develop
active epidemiological surveillance programs in areas
where VHSv is not yet detected and reinforces the
need for proactive regulatory and management inter-
vention when fish and equipment translocation occurs
from endemic regions into areas predicted suitable.
123
Rev Fish Biol Fisheries
The risk maps generated in this study can also help to
design future phylogeographic analysis (e.g., full-
genome sequence analysis) of VHSv across its distri-
bution to determine the fish species acting as reser-
voirs and end-hosts unable to maintain the virus in the
long term. This approach can also elucidate the role of
water flow (e.g., rivers) and humans (e.g., recreational
fishing) in the spread of the virus.
Lastly, VHSv has potential for global translocation
resulting in considerable risk to the fish industry, but
also to local native fish communities. Thus, VHSv is
an example of a pathogen requiring multidisciplinary
and international collaborative efforts under the One
Health approach, to facilitate the participation of
professionals from animal health, economics, interna-
tional policy, and epidemiology. The dramatic mor-
talities, potential for spill over novel fish species, and
broad geographic distribution of VHSv, justify an
integrated effort aiming to prevent and mitigate the
impacts of this virus in the areas predicted at risk.
Acknowledgements Authors thank Gael Kurath for her
invaluable discussion on the ecology of VHSv. LEE thanks A.
Townsend Peterson and Huijie Qiao for their crucial role in
developing disease biogeography theory and methods employed
here. Andres Perez provided comments in an early version. This
study was supported by the Minnesota Environment and Natural
Resources Trust Fund and the Minnesota Aquatic Invasive
Species Research Center. LEE thanks the University of
Minnesota Institute of the Environment for grant MiniGrants
MF-0010-15 used to support the internship of JED inMinnesota.
LEE had full access to all the data in the study and had final
responsibility for the decision to submit for publication.
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