infectious disease in fish: global risk of viral ......affected by diseases. notably, viral...

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RESEARCH PAPER Infectious disease in fish: global risk of viral hemorrhagic septicemia virus Luis E. Escobar . Joaquin Escobar-Dodero . Nicholas B. D. Phelps Received: 27 November 2017 / Accepted: 15 June 2018 Ó 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 from marine 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 Á Ecological niche model Á VHS Á Viral hemorrhagic septicemia Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11160-018-9524-3) con- tains supplementary material, which is available to authorized users. 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 123 Rev Fish Biol Fisheries https://doi.org/10.1007/s11160-018-9524-3

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Page 1: Infectious disease in fish: global risk of viral ......affected by diseases. Notably, viral hemorrhagic septicemia, caused by the viral hemorrhagic sep-ticemia virus (VHSv; Rhabdoviridae),

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

123

Rev Fish Biol Fisheries

https://doi.org/10.1007/s11160-018-9524-3

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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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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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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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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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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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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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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

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(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

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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.

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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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