Journal of Applied

Ecology

2007

44

, 1231–1242

© 2007 The Authors. Journal compilation © 2007 British Ecological Society

Blackwell Publishing Ltd

Incriminating bluetongue virus vectors with climate envelope models

BETHAN V. PURSE

1

, BENJAMIN J. J. MCCORMICK

1

, PHILIP S. MELLOR

2

, MATTHEW BAYLIS

3

, JOHN P. T. BOORMAN

4

, DAVID BORRAS

5

, IBRAHIM BURGU

6

, RUBEN CAPELA

7

, SANTO CARACAPPA

8

, FRANCISCO COLLANTES

9

, CLAUDIO DE LIBERATO

10

, JUAN A. DELGADO

11

, ERIC DENISON

2

, GEORGI GEORGIEV

11

, MEDHI EL HARAK

12

, STEPHAN DE LA ROCQUE, YOUSSEF LHOR

13

, JAVIER LUCIENTES

14

, OLGA MANGANA

15

, MIGUEL ANGEL MIRANDA

16

, NEDELCHO NEDELCHEV

11

, KYRIAKI NOMIKOU

15

, AYKUT OZKUL

6

, MICHAEL PATAKAKIS

15

, ISABEL PENA

7

, PAOLA SCARAMOZZINO

10

, ALESSANDRA TORINA

8

and DAVID J. ROGERS

1

1

Spatial Ecology and Epidemiology Group, Department of Zoology, South Parks Road, Oxford;

2

Institute for Animal

Health, Ash Road, Pirbright, Woking;

3

Veterinary Clinical Science, Leahurst, Neston, Cheshire, UK;

4

6, Beckingham

Rd, Guildford, Surrey, UK;

5

Institut de Biologia Animal de Balears, Laboratorio de Entomología, Departamento

Técnico, Palma de Mallorca, Spain;

6

Ankara University, Faculty of Veterinary Medicine, Virology Department,

Ankara, Turkey;

7

Departamento de Biologia, Universidade da Madeira, Funchal, Madeira, Portugal;

8

Istituto

Zooprofilattico Sperimentale della Sicilia, Palermo, Sicily, Italy;

9

Departamento de Zoologia. Facultad de Biologia.

Universidad de Murcia, Murcia. Spain;

10

Istituto Zooprofilattico Sperimentale delle Regioni Lazio e Toscana, Rome,

Italy;

11

National Diagnostic and Research Veterinary Medical Institute, Sofia, Bulgaria;

12

Virology department,

Biopharma Laboratory, Rabat, Morocco;

13

Ministère de l’Agriculture, du Développement Rural et des Pêches

Maritimes, Morocco;

14

Departamento de Patología Animal (Sanidad Animal), Facultad de Veterinaria, Zaragoza,

Spain;

15

Ministry of Rural Development and Food, Institute of Infectious and Parasitic Diseases, Parasitology

Department, Athens, Greece; and

16

Departamento de Biología, Laboratorio de Zoología, Universidad de las Islas

Baleares, Palma de Mallorca, Spain

Summary

1.

The spread of vector-borne diseases into new areas, commonly attributed toenvironmental change or increased trade and travel, could be exacerbated if novelvector species in newly invaded areas spread infection beyond the range of traditionalvectors.

2.

By analysing the differential degree of overlap between the environmental envelopesfor bluetongue, a devastating livestock disease, and its traditional (Afro-Asian) andpotential new (Palearctic) midge vectors, we have implicated the latter in the recentdramatic northward spread of this disease into Europe.

3.

The traditional vector of bluetongue virus, the Afro-Asian midge

Culicoides imicola

,was found to occur in warm (annual mean 12–20

°

C), thermally stable locations thatwere dry in summer (< 400 mm precipitation). The Palearctic

C. obsoletus

and

C. pulicaris

complexes were both found to occur in cooler (down to 7

°

C annual mean), thermallymore variable and wetter (up to 700 mm summer precipitation) locations.

4.

Of 501 recorded outbreaks from the 1998–2004 bluetongue epidemic in southernEurope, 40% fall outside the climate envelope of

C. imicola

, but within the species’ envelopesof the

C. obsoletus

and

C. pulicaris

complexes.

5.

The distribution in multivariate environmental space of bluetongue virus is closer tothat of the Palaearctic vectors than it is to that of

C. imicola

. This suggests that Palearcticvectors now play a substantial role in transmission and have facilitated the spread ofbluetongue into cooler, wetter regions of Europe.

Correspondence: Beth Purse, Spatial Ecology and Epidemiology Group, Department of Zoology, South Parks Road,Oxford OX1 3PS, UK. Tel: 01865 271197; E-mail: bethan.purse@zoo.ox.ac.uk

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,

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, 1231–1242

6.

Synthesis and applications

. The risk to Northern Europe now depends on how muchof the distributions of the widespread, abundant Palearctic midge vectors (the

C. obsoletus

and

C. pulicaris

complexes) bluetongue can occupy, perhaps determined by thermalconstraints on viral replication. This was highlighted by the sudden appearance insummer 2006 of bluetongue virus at latitudes of more than 50

°

North – approximately6

°

further North than previous outbreaks in southern Europe. Future surveillance forbluetongue and for related

Culicoides

-borne pathogens should include studies to recordand explain the distributional patterns of all potential Palearctic vector species.

Key-words

: bluetongue virus, climate,

Culicoides imicola

,

C. obsoletus

,

C. pulicaris

,environmental envelope.

Journal of Applied Ecology

(2007)

44

, 1231–1242 doi: 10.1111/j.1365-2664.2007.01342.x

Introduction

Modelling the environmental envelopes of vectors andvector-borne pathogens by statistical matching of theirgeographical distributions with environmental datahas been used widely to (1) reveal the potentialenvironmental factors driving their distributions and(2) predict their distributions in unsurveyed places(Rogers & Randolph 2003). The environmental envelopequantified by distribution modelling is analogous to aspecies’ realized niche (Austin

et al

. 1990; Guisan &Zimmerman 2000), i.e. the hypervolume, defined byenvironmental dimensions, within which that speciescan survive and reproduce in the face of competitors,predators and pathogens (Hutchinson 1957). Morerarely these models have been used to investigate theoverlap of the geographical and environmental distri-butions of pathogens and hosts, offering the potentialto tease apart the relative roles of different host speciesand vectors in disease transmission cycles (Peterson &Shaw 2003; Peterson

et al

. 2004).When diseases are introduced or spread into new

areas by increased trade and travel, or followingenvironmental changes, it is essential to re-assess thepieces of the epidemiological puzzle – the pathogenstrains, hosts and vectors involved in transmission (Rogers& Randolph 2003). Bluetongue (BT) is a devastatingmidge-borne disease of ruminants that spread recentlyacross Europe from its traditional Afro-tropical ‘home’.Historically, bluetongue virus (BTV) (the pathogenthat leads to bluetongue) made only brief, rare incursionsinto fringe areas of Europe, with the Afro-Asian bitingmidge vector,

Culicoides imicola

s.s. Kieffer (referred tohereafter as

C. imicola

), being largely responsible fortransmission (Mellor & Boorman 1995). Since 1998,however, six strains of BTV have entered Europevirtually simultaneously from at least two directions,and have spread across 12 countries and up to 800 kmfurther north than reported previously (Purse

et al

.2005). Early on in this process, bluetongue occurredbeyond the known northern range limit of

C. imicola

(even though this species itself had shifted northwardover the same period), thus suggesting a role for

Palearctic

Culicoides

species as vectors. BTV spread inEurope has resulted in massive disruption of trade inanimals and animal products and caused the deaths ofover 1·5 million sheep since 1998 (Mellor & Wittmann2002; Calistri

et al

. 2003).A link between BTV emergence and regional climate

change has already been suggested. The most compellingpiece of evidence is that BTV and

C. imicola

expandedtheir ranges into those locations that have warmed themost during the 1990s, but have not done so in loca-tions that remained cool, or decreased in temperatureduring the same period (Purse

et al

. 2005). Regionalwarming may have increased the importance of Palearcticvector complexes in transmission by increasing theirpopulation sizes and survival rates and by increasingtheir individual susceptibility through developmentaltemperature effects (Wittman & Baylis 2000). Thatthese Palearctic vectors, primarily the

C. obsoletus

and

C. pulicaris

species’ complexes (hereafter, Palearctic

Culicoides

), have played some role in BTV transmissionduring the current epidemic has been established byfine-scale temporal and spatial overlap of their distri-butions with outbreaks (De Liberato

et al

. 2003;Torina

et al

. 2004; De Liberato

et al

. 2005) and by virusisolation from wild-caught Palearctic

Culicoides

inseveral sites (Savini

et al

. 2003, 2005; De Liberato

et al

.2005). Despite this, the involvement of these species’complexes in transmission has been generally assumedto have been relatively minor. Much vector surveillanceeffort has been directed towards defining

C. imicola

freezones (e.g. Conte

et al

. 2003), between which vaccinatedanimals could legally be moved for trade or seasonaltranshumance – regardless of the abundance of thePalearctic

Culicoides

in those zones. It is only since 2004that the cessation of all adult

Culicoides

activity, ratherthan simply that of

C. imicola

, has to be proved in adestination area before vaccinated (with live-attenuatedvaccines) animals can be moved there (EC 2004).

Not only are Palearctic

Culicoides

common andwidespread across Central and Northern Europe, butsome of their field populations have been shown tohave levels of vector competence equivalent to that of

C. imicola

(Carpenter

et al

. 2006). Consequently, for

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,

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accurate risk assessment it is essential to determine(1) the relative extent to which Palearctic vector com-plexes and the major Old World vector,

C. imicola

, arecurrently involved in BTV transmission, in bothgeographical and environmental space and (2) to whatextent and along which environmental axes had theenvironmental envelope of BTV extended by the early2000s due to its transmission by Palearctic vectorspecies. A Mediterranean-wide analysis of the currentenvironmental drivers of

C. imicola

distribution (forcountry-specific analyses see Baylis

et al

. 2001; Tatem

et al

. 2003) is also a prerequisite for examining whetherthis species’ envelope has changed over time or whetherthe environment itself has changed, bringing about aredistribution of the species in space, over time.

Here, our first objective is to determine the climaticdimensions that best define the current environmentalenvelope of

C. imicola

across Africa and southernEurope. This vector was the target of historical surveil-lance efforts and is hence well-recorded, at least alongthe northern fringes of its range (i.e. in southern Europe),enabling us to establish the maximum extent of its geo-graphical distribution in this region. This study is limitedto consideration of the climatic dimensions of a species’envelope but, given available data, habitat or host dimen-sions could be investigated simultaneously withinthe same model framework. Our second objective is tocompare the extent of overlap of the key environmentaldeterminants of

C. imicola

’s distribution with areasof BTV transmission and the overlap of Palearctic

Culicoides

vectors with BTV transmission to shed lighton the magnitude and nature of the role of these differentvectors in transmission. To date, Palearctic

Culicoides

have been recorded mainly only across the southernportions of their Palearctic distributions, in countriesaffected by bluetongue since 1998. This study thereforecaptured only part of their full geographical distribu-tions (although at latitudes relevant to current BTVepidemics) in Europe which we know, from sporadichistorical records, to be much more widespread in areasnorth of the Southern Europe outbreak area.

Materials and methods

Detailed methods are given in the Supplementarymaterial (Appendix S1). Briefly, point or commune-leveldistribution records for BTV and for its vectors,

C. imicola

and the

C. obsoletus

and

C. pulicaris

complexes(Palearctic

Culicoides

), were collated across southernEurope and North Africa from 1998 to 2004. At aspatial resolution of one-sixth of a degree latitude andlongitude (the resolution of the environmental data),there were 180 presence and 215 absence records for

C. imicola

. Unusually for distribution data, these absencerecords were based on extensive field sampling in andnear the outbreak zones. Because very few sampledabsences were available for the widespread Palearctic

Culicoides

, presence data only (428 and 410 presencerecords for the

C. obsoletus

and

C. pulicaris

complexes,

respectively) were used as a baseline estimate of theirdistributions across environmental space. There were501 records of BTV presence, covering a substantialproportion of the total area affected during the recentbluetongue epidemic in Europe (Fig. 1). One-sixth of adegree of monthly climatic data for the period 1996–99were obtained from the Climate Research Unit (CRU)at the University of East Anglia, UK (data set CRU TS1·2, http://www.cru.uea.ac.uk/~timm/grid/CRU_TS_1–2.html; Mitchell

et al

. 2004), and temporal Fourierprocessed (Rogers

et al

. 1996) to produce a set of 17climatic predictor variables: the annual mean, maximumand minimum of temperature and vapour pressure aswell as their amplitudes and phases of the annual andbi-annual cycles and the mean annual amount,summer amount and winter amount of precipitation.The predictor variables that were most important indefining the environmental envelope of

C. imicola

wereidentified using forward stepwise discriminant analysesof clustered bootstrap samples of the presence–absencedata sets (Rogers 2006). Classification accuracy wasassessed using the Kappa coefficient, an index of agree-ment between two categorical classifications (here theobserved and the predicted classes).

To quantify the overlap of BTV and different vectordistributions in multivariate space, defined by thepredictor variables identified above, we calculated themultivariate environmental distances (MahalanobisDistance: MD) between known outbreak areas of BTVand known areas of presence of

C. imicola

and of thetwo Palaearctic vectors,

C. obsoletus

and

C. pulicaris

.As the distribution of any pathogen, transmitted byseveral vectors, is composed of subsets of the distribu-tions of each of its vectors, such measures of separationmay indicate the relative importance of each vectorspecies in disease transmission.

Results

model selection

Annual mean temperature was the key variabledetermining the distribution of C. imicola in Europe. Itwas the first variable to be selected in 494 of 500 (99%)bootstrap sample model runs and the average kappavalue [± standard deviation (SD)] for single variablemodels using just annual mean temperature was0·61 (± 0·045). These models achieved 76·8% (± 4·3%)correct predictions, with a mean sensitivity of 0·81(± 0·02) and specificity of 0·84 (± 0·03). Overall,adequate predictions of the distribution of C. imicola

across Europe could be achieved with three variables inthe models. The addition of the second and thirdvariables produced increments of 0·04 on average in thekappa values and 3% in the percentage of correctpredictions. Addition of a fourth variable gave incrementsof only 0·02 in the kappa value and 1% in the percentageof correct predictions. In all 500 of the three-variablebootstrap models, six combinations of three variables

1234B. V. Purse et al.

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were frequently chosen (Table 1), especially combinations1 and 3. These two combinations included annualmean, annual amplitude and maximum temperature orannual mean temperature, and the bi-annual amplitudes

of temperature and summer precipitation as predictors,respectively.

All six three-variable combinations performed wellin both testing and training (Table 1, Fig. S1). Kappa

Fig. 1. Recorded distribution of (a) BTV, (b) Culicoides imicola and (c) C. pulicaris complex and C. obsoletus complex in theMediterranean Basin between 1998 and 2004.

Table 1. Most commonly selected three-variable model combinations in bootstrap runs of models of Culicoides imicola

distribution in Europe

Combinationno.

Three variables in model Frequency (%) ofmodel’s selectionin bootstrap runs1st 2nd 3rd

1 Ann. mean temp. Ann. amp. temp. Ann. max. temp 75 (15%)2 Ann. mean temp. Ann. amp. temp. Bi-ann. amp temp 20 (4%)3 Ann. mean temp. Summ. amt. prec. Bi-ann. amp temp 71 (14%)4 Ann. mean temp. Summ. amt. prec. Ann. phase. vap. 21 (4%)5 Ann. mean temp. Ann. amp. temp. Ann. amt. prec. 16 (3%)6 Ann. mean temp. Ann. amp. temp. Wint. amt. prec. 15 (3%)

Ann. = annual; Bi-ann. = bi-annual; Amp. = amplitude; Summ. = summer; Wint. = winter; Amt = amount; Temp. = temperature; Prec. = precipitation.

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values ranged from 0·655 to 0·673 in training vs. 0·610–0·641 in testing and the proportion of correct predictions(presence and absence combined) ranged from 0·828 to0·838 in training vs. 0·807–0·823 in testing). Combinations1 and 3 performed the best across test and trainingpartitions and the geographical distribution of C. imicola

presence predicted by each model is compared below.The key temperature and precipitation predictorvariables in these combinations were used subsequentlyto define and investigate the climate space occupied byBTV and its vectors in Europe.

climatic predictors of the distribution of C. I M I C O L A in europe

Although the single presence cluster and two absenceclusters used in the distribution models are definedstatistically, and their number based on the best fitsof the most parsimonious models, it is biologicallyinformative that areas of C. imicola presence in the eastand west Mediterranean Basin can all be captured inmodels by a single environmental cluster that hasbroadly consistent properties in terms of key variablemeans and covariances across this wide geographicalarea (Fig. S2). Figure 4 shows how these presence andabsence clusters map geographically.

Overall, C. imicola occurs in Europe where temperaturesare high on average (annual mean temperatures rangefrom 12 to 20 °C) and stable throughout the year (hencelow values of the annual amplitude in Table 2). Theseasonal range in Fourier-fitted temperatures in presencesites (P) is approximately 13 °C, with temperaturesrarely dropping below 9 °C in winter and rising to abroad peak in late summer (August), remaining at orabove 23 °C for at least 3 months of the year (Fig. 2).Precipitation levels in areas of C. imicola presence arehigh in winter and low in summer (summer precipitation

amounts range from 0 to 400 mm and winter precipi-tation amounts from 120 to 1200 mm).

C. imicola is absent in the east and central Mediter-ranean Basin (absence category 1), where conditionsare cooler (annual mean temperatures range from 0to 18 °C; Fig. S2, Table 2) than in areas of C. imicola

presence. In the summer, temperatures in absence areasreach similar highs to those in areas of C. imicola

presence (around 23 °C), but winter temperatures dropmuch lower (as low as 4 °C). Though absence areashave the same average annual precipitation levels asC. imicola presence locations, they are wetter insummer (summer precipitation amounts range from0 to 500 mm; Fig. S2) and drier in winter.

C. imicola is also absent in the western MediterraneanBasin (absence category 2), which also tends to becooler on average (annual mean temperatures range

Table 2. Means (± SD) and medians of important environmental variables across pixels in each observed absence and presence category of the Culicoides

imicola distribution in Europe

Units

Means (± sd)absenceGroup 1n = 180

Group 2n = 34

Presencen = 181

MediansabsenceGroup 1n = 180

Group 2n = 34

Presencen = 181

Kruskal–Wallis test between groups

χ2Location ofpairwise differences

Ann. mean. temp. 0·1 °C 127·2 (± 22·8) 137·9 (± 14·3) 159·4 (± 15·4) 124·7 163·5 277·4 164·7* P greater than bothA1 and A2

Ann. max. temp 231·3 (± 17·1) 214·7 (± 14·8) 241·9 (± 13·9) 177·4 71·3 242·3 75·08* All pairs differentAnn. amp. temp. 100·7 (± 14·1) 70·5 (± 13·3) 76·5 (± 11·8) 283·8 94·6 132·1 189·7* A1 greater than A2

and PBi-ann. amp. temp. 6·7 (± 2·6) 11·6 (± 2·7) 10·3 (± 2·3) 117·1 295·5 260·2 169·0* A1 lower than A2

and PAnn. phase. vap. Decimal 7·4 (± 0·2) 7·5 (± 0·1) 7·6 (± 0·2) 123·0 235·9 265·5 144·7* A1 lower than A2

months and PAnn. amt. prec. mm/year 696·5 (± 90·5) 1256·3 (± 226·9) 716·1 (± 173·3) 181·9 375·0 180·8 89·4* A2 greater than A1

or PSumm. amt. prec. 277·6 (± 97·2) 437·7 (± 101·5) 225·4 (± 85·3) 214·5 345·6 153·9 87·6* All pairs differentWint. amt. prec. 418·9 (± 102·3) 818·7 (± 144·8) 490·7 (± 136·7) 150·8 369·3 212·8 110·4* All pairs different

*All tests significant at the 0·0001 level. A1 is absence category 1, A2 is absence category 2 and P is the presence category of C. imicola. Abbreviations as per Table 1 and Vap. = vapour pressure.

Fig. 2. Fourier fitted series of temperature across differentcategories of presence and absence of Culicoides imicola inEurope. A1 is absence category 1, A2 is absence category 2 andP is the presence category of C. imicola.

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from around 10–17 °C; Fig. S2) than areas of presence.In this region both presence and absence areas have anarrow seasonal temperature range, dropping below 7 °Cin winter and rising to a broad peak of around 21 °C inlate summer (August) (Fig. 2). Year-round precipitationlevels are higher (summer precipitation amounts rangefrom 200 to 700 mm; Fig. S2) in areas of C. imicola

absence category 2 than in areas either of C. imicola

presence or of C. imicola absence category 1 (Table 2).

predicted distribution of C. I M I C O L A in europe

The colours from yellow to red in Fig. 3 indicate theBayesian posterior probability (P) (from 0·5 < P < 1)

that each pixel in Europe was suitable for C. imicola

presence during the late 1990s derived from the twobest three-variable model combinations (1 and 3 inTable 1). The predicted geographical distributionsof C. imicola are identical in 93% of sites (kappavalue comparing two sets of predictions = 0·85, Fig. 4)and each corresponds closely to the observed dis-tribution of C. imicola in the areas that have beensampled. Areas of disagreement between the twomodels, and the small number of false predictions madeby each one, tend to be distributed along the northernrange limit of C. imicola and in large parts of NorthAfrica (Tunisia and Libya), which is predicted to beunfavourable for C. imicola by model 1 but favourableby model 3 (Fig. 4).

Fig. 3. Predicted probability of the presence of Culicoides imicola s.s. (a) from model 1 with annual mean temperature, annualamplitude of temperature and annual maximum temperature (b) model 3 with annua; mean temperature, summer amount ofprecipitation, bi-annual amplitude of temperature. No prediction is made when a pixel is too environmentally dissimilar from thetraining presence–absence data set, defined as pixels for which the Mahalanobis Distance (MD) exceeds 30 MD units. See Fig. 2for key to site classes.

Fig. 4. Areas of agreement and disagreement between two models of Culicoides imicola distribution in Europe overlaid with thepresence of BTV in Europe from available commune and point level data only.

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overlap of btv and its vectors in european climate space

When the C. imicola predictions shown in Fig. 4 areoverlain with data for the current distribution of BTVin Europe, constructed only from available commune-and point-level data (Fig. 4), it is striking that a largenumbers of locations affected by BTV in central andeastern Europe lie north of the predicted distributionlimit of C. imicola.

The overlap of the distribution of BTV and C. imicola

in climate space in Europe is shown in Fig. 5a,c,e. Onthe two axes shown in Fig. 5a, 43·5% (218/501) of BTVrecords fall outside the 95% confidence ellipse ofC. imicola presence points, and do so in the directionsof much lower annual mean temperatures (to 6 or 7 °C)and greater ranges of annual temperature (> 9 °C).BTV transmission, below an annual mean temperatureof 15 °C, also extends into locations with more than500 mm to around 700 mm of summer precipitation.

Fig. 5. Climate space occupied by BTV and its vectors. The axes of bivariate climate space are defined by different pairings ofthree important determinants of Culicoides imicola distribution annual mean temperature (in 0·1 °C), annual amplitude oftemperature (in 0·1 °C), and summer amount of precipitation (in mm per summer). In (a) (c) and (e) the overlap between thepresence of BTV and the presence of C. imicola in environmental space is shown. In (b) (d) and (f), their overlap with the presenceof other Palearctic Culicoides is also shown.

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On the pairs of axes indicated in Fig. 5b,c, 44·5% (223/501) and 44·7% (224/501) of BTV records, respectively,fall outside the 95% confidence ellipse of C. imicola

presence points, into wetter as well as cooler areas.When the sampled distributions of the C. obsoletus

(grey circles) and C. pulicaris (grey crosses) complexesare superimposed on these same pairs of axes (Fig. 5b,d,f),they co-occur across most of the environmentalspace they occupy and also overlap extensively with theclimate envelope of C. imicola in Europe (representedhere by the 95% ellipse of C. imicola presence) at annualmean temperatures of 12 °C to 17 °C. Importantly,however, they extend into locations that are much cooler,having annual average temperatures of 7–8 °C (particularlyin locations that have high annual amplitudes intemperature; Fig. 5b,d) and wetter, having summerprecipitation amounts of up to 600 mm (Fig. 5d,f). Onall three pairs of axes, their distributions in climatespace overlap much of the space beyond the C. imicola

envelope (or ellipse) and into which BTV transmissionhas extended. While the Iberian and Moroccantransmission sites fell broadly inside the C. imicola

envelope in two dimensions, those that fell outsidewere geographically distributed in central and east-ern Europe – just south (in Greece, Lazio and Tuscanyand Sicily) or just north (in Greece, Bulgaria andthe Balkans) of the northern range limit of C. imicola.

On the basis of MDs, areas of BTV transmissionwere found to be approximately twice as far in multi-variate space from areas of C. imicola presence as theywere from areas of presence of Palearctic Culicoides, orfrom sites containing any vector at all (all three vectorcomplexes/species combined) (Fig. 6a). Areas of BTVtransmission (232 squares) that occurred within C. imicola’snorthern range limit were equally close in multivariatespace to areas of presence of C. imicola, the C. obsoletus

complex and the C. pulicaris complex (Fig. 6b), whilethose northward of this limit (269 squares) were two tothree times further from areas of presence of C. imicola

than they were from areas of presence of the PalearcticCulicoides, or from sites containing any vector at all(Fig. 6c).

Discussion

climatic predictors of the distribution of C. I M I C O L A in europe

The association of C. imicola populations withlocations that are warm on average and remain warmyear-round, indicated by the models presented here, isbroadly consistent with recent subcontinental studiesof this species’ distribution (Wittman et al. 2001;Conte et al. 2003; De Liberato et al. 2003). Wittmanet al. (2001), for example, found that at least 8 monthswith a mean temperature greater than 12·5 °C favouredthe presence of C. imicola at sites in Iberia. The precisebiological basis of these associations for C. imicola isunknown, but many population processes of Culicoides

are known to be highly temperature-dependent (Melloret al. 2000; Wittmann & Baylis 2000).

C. imicola populations are also associated withlocations that are reasonably dry, particularly in

Fig. 6. Box-plots comparing average accuracy statisticsacross Mahalanobis distances (MD) between the distributionsof BTV and each different vector complexes or species for(a) all BTV sites, (b) BTV sites south of Culicoides imicola’snorthern range limit and (c) BTV sites north (> 0·5 degrees) ofC. imicola’s northern range limit. In each case, MD values arecalculated across 10 000 pairs of randomly selected BTV sitesand vector presence sites (adjusted for the covariance of theentire distribution data set of the vector). The boxes have linesat the lower quartile, median and upper quartile values whilewhiskers extending from the boxes indicate the full extent ofdata set and red crosses indicate outliers. Notches represent arobust estimate of the uncertainty about the medians for box-to-box comparison. Boxes whose notches do not overlapvertically indicate that the medians of the two complexesdiffer at the 5% significance level.

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summer (with some populations withstanding zeroprecipitation in this season). This is consistent with thisspecies’ habit of breeding in wet or damp, but notflooded, organically enriched soil (Braverman et al.1974; Walker 1977; Braverman 1978). In Europe, thepeak adult activity of C. imicola s.s., and thus the peakrequirement for moist breeding sites, coincides withlate summer/early autumn. This association in Europe(cf. Rawlings et al. 1998) mirrors this species’ require-ments in core areas of its distribution such as SouthAfrica, where populations are restricted to areas withrainfall of 300–700 mm per year (Meiswinkel & Baylis1998). Areas with higher rainfall are unlikely to besuitable for C. imicola because the pupae and larvae ofthis species are unable to swim or float in free water, asdo those of many other Culicoides species, and sodrown or are washed away when the breeding sites areflooded (Nevill 1971). In comparisons in Cyprus andIsrael, C. imicola was observed to breed in habitats thatwere generally drier than those preferred by otherspecies of Culicoides (Braverman et al. 1974; Mellor &Pitzolis 1979).

Although clustering of the presence and absencedata was employed to achieve multinormality – astatistical prerequisite for discriminant analysis – it isinteresting that the presence of C. imicola was bestdescribed throughout the Mediterranean using a singlepresence cluster only, while two clusters or types wererequired to describe locations in which C. imicola isabsent, corresponding broadly to a western vs. a centraland eastern Mediterranean absence type. Comparingthe properties of each of these clusters suggests that thecombination of seasonal conditions of temperatureand precipitation, rather than temperature alone(as suggested by Baylis & Rawlings 1998; Rawlingset al. 1998; Wittman et al. 2001) limits this species’expansion northward in the Mediterranean and thespecies faces different challenges to further expansionin the East and West of this region. In the north-westMediterranean (e.g. in northern Portugal), C. imicola

was absent in areas that were cooler and wetter year-roundthan areas of C. imicola presence. Because most habitatsin central and northern areas of Europe receivesubstantial amounts of precipitation, the risk thatC. imicola breeding sites will be flooded may be uniformlyhigh and thus limit significantly this species’ expansionnorthward across the continent. Locations in centraland eastern areas where the species was absent (e.g.north-west Greece and Bulgaria) were as warm insummer but dropped to much lower temperatures inwinter. They were also wetter in summer, when thedemand for moist but not flooded breeding sites ishighest, and drier in winter.

It is, of course, probable that many other factors suchas soil type (Baylis et al. 1999), soil moisture availability(or a correlate, the Normalized Difference VegetationIndex – Baylis et al. 1998; Baylis & Mellor 2001; Tatemet al. 2003), slope and farm husbandry methods(Meiswinkel et al. 2000) determine the distribution of

C. imicola populations at finer spatial scales. For example,within quite large areas that are too wet on average insummer, C. imicola may be able to select patchesof drier microhabitats where breeding sites will notbecome flooded. Models based on environmental datasets at coarse spatial resolution will record such areasas ‘too wet’ rather than as ‘suitable’. Nevertheless, theavailability of such dry patches for selection may bereduced within a ‘wet’ square compared to a ‘dry’square. In fact, the predominance of macroclimate indetermining distribution patterns of organisms at scalesof 10 km2 and above is widely recognized (Andrewartha& Birch 1954; Currie 1991) and our study of the climaticenvelope of C. imicola at a similar spatial scale hasrevealed consistent characteristics of the complexrelationship between this species and the climateacross the Mediterranean. This analysis provides auseful baseline estimate of the current (late 1990s)climatic limits of C. imicola across Europe, againstwhich to test for past and future changes in these limits.It also allows broad-scale definition of those areascurrently at risk of BTV transmission by this species.

overlap of btv and its vectors in environmental space in europe

Palearctic Culicoides are not only abundant and wide-spread in northern Europe, but also extend southwardinto North Africa (Szadziewski 1984; Baylis et al.1997), Turkey (Jennings 1983) and the Middle East(Braverman & Galun 1973; Braverman et al. 1974).Despite their extensive geographical overlap with bothC. imicola and areas of historical BTV incursions thereis little evidence, either from temporal or fine-scale spatialoverlap with the distribution of historical outbreaks,that Palearctic Culicoides previously played a majorrole in transmission within the historical limits of C.

imicola in Africa (Mellor et al. 1984; Mellor et al.1985). By contrast, our study supports a major role forthese alternative vectors to C. imicola during thecurrent epidemic. Indeed, the overall distribution ofBTV transmission was closer to the distributions of thePalaearctic species complexes (both the C. obsoletus

and C. pulicaris complexes), on average, than it was tothe distribution of C. imicola, in both bivariate andmultivariate environmental space. This indicates thatthese species complexes make a significant contributionto BTV’s distribution across Europe, not only north-ward of the range of C. imicola (in south-central andsouth-east Europe) but also within C. imicola’s range(where the distribution of BTV inside the range was notappreciably closer in climate space to the distributionof C. imicola than it was to the distributions of thePalearctic species complexes). The fact that transmis-sion sites located northward of the range of C. imicola

are not only geographically distant from known C. imicola

populations but also lie well outside the climaticenvelope of this species make it less plausible that thepresence of this species has simply been overlooked by

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surveillance efforts in these areas. Moreover, thisspecies is unlikely to move into these more northerlyareas in the near future, without a substantial shift in itsclimatic envelope. This leaves unanswered, however,the question of why the Palearctic vectors were appar-ently unimportant for BTV transmission historically inAfrica.

We acknowledge that BTV was recorded as presentin a few restricted areas of environmental space wherethe Palearctic vectors were recorded as ‘absent’.Although other vectors may be important in theselocations, we suspect that most of these gaps will befilled as surveillance efforts are directed at detectingthese Palaearctic species. Nevertheless, this illustratesthe importance of continually updating our picture ofthe environmental distributions of pathogens andvectors as new data become available.

The overlap in Europe between the PalaearcticCulicoides and C. imicola affords ample opportunityfor ‘hand-over’ events of the virus between the traditionaland novel vectors to occur (cf. Mellor 1996). Predictingwhere in geographical and environmental space suchevents are most likely is crucial. The advantage of usingdiscriminant analysis or logistic regression to describeenvironmental envelopes rather than alternativeprograms such as garp (Peterson & Shaw 2003; Petersonet al. 2004) is that the contribution of different environ-mental variables to the model can be assessed clearlyand used to define important dimensions in which tovisualize species’ interactions most effectively (such asthose between different vectors) in environmentalspace. This is particularly powerful when combinedwith temporal Fourier processing to extract informationon the seasonality of climate that is crucial in drivingvariation in vector-borne diseases (Rogers & Randolph2003). In addition, Mahalanobis distances can be usedto assess the broad-scale overlap and shifts of species’distributions in multivariate environmental space forany set of interacting species (e.g. herbivore–plant orpredator–prey systems). As the latter reduces severalenvironmental dimensions to a one-dimensionalmeasure of separation, it overcomes the lack of toolsfor visualizing environmental space in more thanthree dimensions simultaneously (Soberon & Peterson2005).

The environmental envelope modelling approachholds particular promise for examining the broad-scalegeographical and environmental interactions of hosts,vectors and pathogens, because arthropod vectors arehighly sensitive to climate and their environmentalenvelopes can probably be summarized adequatelywith a few important environmental dimensions. Theyare also dispersive, and may be expected to ‘fill’ rapidlyall available environmental space in a region and respondquickly to changes in the geographical distribution ofenvironmental space following environmental changeor disturbance. This is in contrast to the rare, habitatspecialists to which these models are most oftenapplied in the field of conservation.

Most importantly, this study indicates the degree towhich we need to adjust our historical picture of theseasonal conditions of temperature and precipitationthat favour BTV transmission, and therefore thelikelihood of its invasion elsewhere. Sellers & Mellor(1993) found that the 12·5 °C isotherm for the coldestmonth of the year broadly delineated the historicaldistribution of Culicoides-borne disease outbreaks (aswell as locations where adult C. imicola could surviveyear-round) in the Mediterranean. Transmission nowoccurs in locations where the average annual (ratherthan winter) temperatures are as low as 12 °C. Theseconditions (outside the envelope of C. imicola) arewithin the distributions of the Palearctic Culicoides.These vectors will allow BTV to extend into colder,wetter locations, with annual average temperatures aslow as 7–8 °C and summer precipitation amounts of upto 600–700 mm. Until 2004, BTV had only occupiedthe southern-most portion of these novel vector speciescomplexes’ distributions. In summer 2006, however,bluetongue virus suddenly appeared at latitudes ofmore than 50° North, in Belgium, Germany and theNetherlands (Anonymous 2006a, b, c) – approximately6° further North than previous outbreaks in southernEurope and, significantly, well within the core of theranges of the Palearctic Culicoides. How far bluetonguemight extend in the future, within the distributions ofthese Palaearctic species complexes, depends inter alia

on the thermal limits to viral replication (Van Dijk &Huismans 1982), as well as on the distributions andrelative capacity to act as BTV vectors, of subspecieswithin these complexes.

Our study highlights the dynamism of the BTV–Culicoides system in Europe. Future surveillance andresearch effort for bluetongue and for related Culicoides-borne pathogens (such as African horse sicknessvirus and epizootic haemorrhagic disease virus thathave historically shared similar vectors) should aim torecord and explain the distributional patterns, host andhabitat preferences of all potential Palearctic vectorcomplexes as well as the traditional, African–Asianvectors.

Acknowledgements

BVP is currently supported by BBSRC/DEFRA ResearchGrant (BBSRC grant no. BBS/B/00603, Defra Grantno. SE4104) ‘Epidemiology & control of orbiviraldiseases in the UK, with particular reference to blue-tongue & African horse sickness’ and was previouslysupported by EU project (Contract no. QLK2-CT-2000–00611). The authors would like to thank Prof SarahRandolph for helpful comments on the manuscript.

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Received 21 September 2006; final copy received 29 March 2007

Editor: Philip Stephens

Supplementary material

The following supplementary material is available forthis article.

Appendix S1. Detailed Methods and Culicoides dis-tribution data.

Fig. S1. Box plots comparing average accuracy statisticsacross training sets and test sets for six three-variablemodels of C. imicola distribution in Europe.

Fig. S2. Climate space occupied by locations inpresence and absence categories of C. imicola in Europe,visualised on bivariate scatter plots of importantclimatic determinants of distribution

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