Red and Fallow Deer Determine the Density of Ixodes Ricinus Nymphs Containing Anaplasma Phagocytophilum

Katsuhisa Takumi (  [email protected] ) Centre for Zoonoses and Environmental Microbiology Centre for Infectious Disease Control National Institute for Public Health and the Environment (RIVM) Bilthoven The Netherlands Tim Hofmeester Swedish University of Agricultural Sciences Faculty of Natural Resources and Agricultural Sciences Hein Sprong Centre for Zoonoses and Environmental Microbiology Centre for Infectious Disease Control National Institute for Public Health and the Environment (RIVM) Bilthoven The Netherlands

Research

Keywords: Ixodes ricinus nymphs, Anaplasma phagocytophilum, phagocytophilum, anaplasmosis

Posted Date: October 26th, 2020

DOI: https://doi.org/10.21203/rs.3.rs-96286/v1

License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License

Version of Record: A version of this preprint was published on January 19th, 2021. See the published version at https://doi.org/10.1186/s13071-020-04567-4. 1 Red and fallow deer determine the density of Ixodes ricinus

2 nymphs containing Anaplasma phagocytophilum

1, 2 1 3 Katsuhisa Takumi ✉, Tim R. Hofmeester , and Hein Sprong

4 1 Centre for Zoonoses and Environmental Microbiology Centre for Infectious Disease Control

5 National Institute for Public Health and the Environment (RIVM) Bilthoven The Netherlands

6 2 Department of Wildlife Fish and Environmental Studies Swedish University of Agricultural

7 Sciences Skogsmarksgränd 7 907 36 Umeå Sweden

8 ✉ Correspondence: Katsuhisa Takumi

9

1 10 Abstract

11 Background: The density of Ixodes ricinus nymphs infected with Anaplasma phagocytophilum

12 is one of the parameters that determines the risk for humans and domesticated animals to

13 contract anaplasmosis. For this, I. ricinus larvae need to take a blood meal from free-ranging

14 ungulates, which are competent hosts for A. phagocytophilum.

15 Methods: Here, we compared the contribution of four free-ranging ungulate species, red deer

16 (Cervus elaphus), fallow deer (Dama dama), roe deer (Capreolus capreolus), and wild boar (Sus

17 scrofa) to A. phagocytophilum infections in nymphs. We used a combination of camera and live

18 trapping to quantify the relative availability of vertebrate hosts to questing ticks in nineteen

19 Dutch forest sites. Additionally, we collected questing I. ricinus nymphs and tested these for the

20 presence of A. phagocytophilum. Furthermore, we explored two potential mechanisms that could

21 explain differences between species: 1) differences in larval burden, which we based on data

22 from published studies, and 2) differences in associations with other, non-competent hosts.

23 Results: Principal component analysis indicated that the density of A. phagocytophilum infected

24 nymphs (DIN) was higher in forest sites with high availability of red and fallow deer, and to a

25 lesser degree roe deer. Initial results suggest that these differences are not a result of differences

26 in larval burden, but rather differences in associations with other species or other ecological

27 factors.

28 Conclusions: These results indicate that the risk for contracting anaplasmosis in the Netherlands

29 is likely highest in the few areas where red and fallow deer are present. Future studies are needed

30 to explore the mechanisms behind this association.

2 31 Background

32 Anaplasma phagocytophilum is the causative agent of human granulocytic anaplasmosis (HGA),

33 and it also causes disease and economic losses in domesticated animals [1–3]. The first human

34 case in Europe was reported in 1995. Since, HGA cases have only been occasionally reported

35 throughout Europe [4]. It is unclear to what extent HGA poses a health burden in Europe:

36 epidemiological data on the disease incidence and disease burden is either incomplete or lacking

37 from most European countries [2]. The non-specificity of the reported symptoms, poor

38 diagnostic tools and lack of awareness of public health professionals may also complicate these

39 estimations [5]. Anaplasma phagocytophilum is transmitted by the bite of an infected tick [6,7].

40 The main vector in Europe is Ixodes ricinus, which also transmits Borrelia burgdorferi sensu

41 lato, the causative agent of Lyme borreliosis, and several other pathogens [8]. The geographic

42 spread and density of I. ricinus infected with A. phagocytophilum is an important determinant of

43 the disease risk [9,10]. Anaplasma phagocytophilum seems to appear in all countries across

44 Europe with infection prevalence in nymphs (NIP) varying between and within countries from 0

45 to 25% [1]. Understanding which factors determine the spatial and temporal distribution of I.

46 ricinus infected with A. phagocytophilum is needed for risk assessments and for formulating

47 possible intervention strategies.

48 Variations in the density of questing I. ricinus infected with A. phagocytophilum (DIN) have

49 partly been attributed to environmental factors such as differences in weather conditions [11,12],

50 habitat characteristics [13], as well as vertebrate communities [14]. Whereas small mammals and

51 birds are considered to feed the majority of immature I. ricinus, ungulates act as their main

52 propagation host [15]. It is however, still unclear which host species form the main reservoir for

53 A. phagocytophilum, and therefore contribute most to the density of infected ticks. Anaplasma

3 54 phagocytophilum has been found to infect many vertebrate species [1], but its genetic diversity

55 indicates that there are multiple genetic variants, or ecotypes, with distinct, but overlapping

56 transmission cycles, pathogenicity or geographical origin [16–18]. A variety of wildlife species,

57 like red deer (Cervus elaphus), fallow deer (Dama dama) wild boar (Sus scrofa), and European

58 hedgehog (Erinaceus europaeus), are harbouring A. phagocytophilum variants that can cause

59 disease in humans and domesticated animals, whereas roe deer (Capreolus capreolus), rodents

60 and birds seem to carry genetic variants that have until now not been associated with human

61 disease [17].

62 About two-thirds of tick bites reported in the Netherlands are I. ricinus nymphs [19]. Therefore,

63 the density of questing nymphs infected with A. phagocytophilum (DIN) is an important

64 ecological parameter that, together with the level of human exposure, determines tick-borne

65 disease risk [9,20]. The DIN is calculated by multiplying the density of questing I. ricinus

66 nymphs (DON) by nymphal infection prevalence (NIP). The transmission of A. phagocytophilum

67 predominantly relies on horizontal transmission between ticks and vertebrate hosts and on

68 transstadial transmission in its vectors, as vertical (transovarial) transmission has not been

69 documented for I. ricinus. Therefore, an I. ricinus larvae needs to take a blood meal from an

70 infected vertebrate host to become an infected I. ricinus nymph. The availability of (infected)

71 vertebrates to questing larvae generally drives the density of (infected) I. ricinus nymphs

72 [14,21,22].

73 Using data from a cross-sectional study estimating the availability of hosts with camera and live

74 traps in nineteen Dutch forest sites, we quantified a moment when a questing tick encounters an

75 ungulate, the probability of this event predicts both I. ricinus nymphal density, and A.

76 phagocytophilum DIN [14]. However, the reported association for A. phagocytophilum DIN left

4 77 a relatively large proportion of the variation among sites unexplained, which could be due to the

78 grouping of four ungulate species. The group of ungulates considered consisted of four species

79 that differed in their ecology and potentially in their ability as hosts for I. ricinus and A.

80 phagocytophilum.

81 Here, we present a re-analysis of the A. phagocytophilum data from the cross-sectional study to

82 disentangle the role of the four ungulate species in determining A. phagocytophilum DIN. We

83 first applied a principal component analysis to the camera and live trapping data to test if

84 availability of any of the four ungulate species or combinations of species was associated with A.

85 phagocytophilum DIN. Second, we used simple mathematical models to explore two potential

86 mechanisms that could explain differences between species: 1) differences in I. ricinus larval

87 burden, and 2) potential associations of the different ungulate species with alternative

88 incompetent host species.

89 Methods

90 Cross-sectional study

91 We made use of data from an extensive field survey that was carried out in nineteen 1-ha sites

92 located in forested areas in the Netherlands in 2013 and 2014. Data were collected on the density

93 of questing I. ricinus (blanket dragging), vertebrate communities (camera and live trapping), and

94 on the infection rates of tick-borne pathogens (qPCR detection). The sites, methodologies, and

95 the data have been described elsewhere as well as a series of detailed analyses [14,22–24].

5 96 Host attribution

97 We arranged the encounter probabilities for all forest sites (n=19) and vertebrate species (n=32)

98 into a matrix having 19 rows and 32 columns. We further arranged A. 19×32 99 phagocytophilum퐀 ∈ DIN ℝ into a vector matching the order of the forest sites along the rows of .

100 To attribute A. phagocytophilum DIN푏 to an assemblage of 32 vertebrate species, we factored the퐀

101 matrix into two orthogonal matrices

102 퐀 19×19 32×32 1 2 19 1 2 32 103 and a diagonal퐔 matrix = [푢 , 푢 , … , 푢 ] ∈with ℝ the singular and 퐕 values = [푣 , 푣 , … , 푣 ] ∈ ℝ and the 19×32 104 remaining entries equal횺 to ∈ zero. ℝ Theorem 2.5.2 [25] proves that휎1 ≥ 휎2 … ≥ 휎19. The≥ 0 column vectors 푇 105 and are principal components, also known as singular vectors.퐀 = 퐔횺퐕

106 푢The푖 A. 푣phagocytophilum푖 DIN increased at each forest site due to the first principal components

107 by the amount (Theorem 5.5.1 [25])

108 푢1 ⋅ 푏 19 퐀푣1 ∈ ℝ . (1) 109 We attributed Eq.(1) to roe deer because휎1 the highest contribution from the first principal

110 component comes from roe deer. Next, we applied the theorem again to quantify the inputs

111 from the lower푣1 principal components ,

푣2, 푣3 … 112 8 푖 19 푢 ⋅ 푏 푖 푦 = ∑ 푖 퐀푣 ∈ ℝ . 푖=2 휎 113 Lower components are ignored because the tail sum is negligible (2.43%) 19 2 9 19 푖=9 푖 114 compared to the whole푣 … cumulative 푣 sum . Next, we define∑ 휎 19 2 ∑푖=2 휎푖 115 + 푦− = max(푦,0), (2) 푦 = max(−푦, 0). (3)

6 116 Intuitively, we clipped the solution into the positive part and the negative part . We + − 117 attributed Eq.(2) to fallow deer, red deer푦 and wild boar because푦 the highest contributions푦 from

118 the second principal component and the third comes from these species.

푣2 푣3 119 Larval tick burden on ungulates

120 Ungulates generally contribute relatively little as hosts for feeding I. ricinus larvae compared to

121 rodents and birds [15]. Nevertheless, as important hosts for A. phagocytophilum, ungulates might

122 feed a significant fraction of larvae that later become A. phagocytophilum infected nymphs.

123 Thus, differences in larval burden between ungulate species could attribute to differences in their

124 importance as hosts contributing to A. phagocytophilum DIN. To explore this, we compiled data

125 from published studies that collected I. ricinus larvae attached to individual ungulates [see

126 Additional file 1 Table 5]. We extracted species, the number of checked animals, and the number

127 of I. ricinus larvae attached to the animals. We fit the negative binomial model (log-link) to the

128 number of larval ticks using the number of animals and the species as predicting variables. We

129 tested the significance of the species predicting variable by performing the likelihood ratio test.

130 Associations with other woodland species

131 We explored if differences between species could be explained by associations of the different

132 ungulate species with the availability of other host species. Here, two species might appear

133 related due to the probability condition (The sum of rates over the host species must equal to

134 one). To remove this potential bias, we performed the following analysis using the encounter

135 rates instead of the encounter probability. For this, we calculated the Pearson correlation in the

136 encounter rate for each ungulate species with each other woodland species. We fit the binomial

137 model (logit link) to the frequency of positive and negative correlation values using the ungulate

7 138 species as a predicting variable. We tested the significance of the predicting variable by

139 performing the likelihood ratio test.

140 Absent species interaction, correlation values should be close to zero and the deviation from the

141 expected value zero should be symmetric. It is possible to calculate the probability of observing

142 as many or more negative correlation values as actually observed in the vertebrate community,

143 푛 1 푛 −푛 ∑ ( ) . (4) 2 푗=푘 푗 144 This is a partial sum of binomial probability densities where a correlation value is negative with

145 probability . The vertebrate community counts members. The number of negative correlation 1 146 values observed2 in the vertebrate community equals푛 . All computations were implemented

147 using the R language [26]. 푘

148 Results

149 Tick densities

150 We collected a total of 16,568 I. ricinus nymphs at the 19 forest sites. Most of the collected

151 nymphs (n = 13,967) were tested for the presence of A. phagocytophilum DNA resulting in an

152 overall infection prevalence of 3.3 % (456 infected nymphs) which we used to calculate the

153 density of infected nymphal ticks (DIN). Using correlation analyses, we detected a significant

154 correlation between the number of positive nymphs, NIP, and DIN (Table 1). DIN of A.

155 phagocytophilum lacked a clear correlation with the density of nymphal ticks (DON; Table 1).

8 156 Host attribution

157 The encounter of an I. ricinus larva with a woodland species is a critical event to a successful A.

158 phagocytophilum transmission. We quantified the probability of an encounter event based on the

159 information collected using camera and live-traps in the 19 forest sites [see Additional file 1 Fig

160 4]. We found that the majority of the observed A. phagocytophilum DIN can be attributed to the

161 encounter probabilities of fallow deer, red deer and wild boar (Fig.1), based on the correlation of

162 the attributed DIN to the three free-ranging ungulate species (Fig.2). We, however, did not find a

163 correlation with the attributed DIN to roe deer (Table 2).

164 Larval tick burden on ungulate species

165 Based on the data extracted from twelve studies in the literature, which together report 24,794 I.

166 ricinus larvae attached to 1,860 individual ungulates in six European countries, we found no

167 support for the hypothesis that differences in I. ricinus larval burden could have caused the

168 differences in association with A. phagocytophilum DIN among the four ungulate species (Table

169 3).

170 Reducing availability of woodland species

171 The encounter rate of roe deer correlated negatively with the encounter rates of 14 woodland

172 species and positively with 17 (Table 4). The probability of exceeding the number of negative

173 correlations is 0.81. The other free-ranging ungulates showed a different pattern: Encounter rates

174 of red deer correlated negatively with encounter rates of 23 woodland species, fallow deer with

175 26 woodland species, and wild boar with 23 woodland species (Table 4). Consequently, we

176 found a clear difference among these ungulate species in the frequency of negative correlations

177 with other woodland species (P-value = 0.010623, deviance = 11.2140483, d.f. = 3). The

9 178 probability of exceeding the number of negative correlation is low: Red deer: 0.01 Fallow deer:

179 0.00027 and Wild boar: 0.01 .

180 Discussion

181 Re-analysing a cross-sectional study of observed A. phagocytophilum DIN at nineteen Dutch

182 forest sites [14], we show that most of the variation in DIN can be explained by differences in

183 encounter probability among ungulates species that were not taken into account in the original

184 analysis. We found a clear association of A. phagocytophilum DIN with the encounter

185 probabilities of fallow deer, red deer and wild boar. A first exploration of two potential

186 mechanism that could cause the difference among ungulate species in their contribution to the

187 DIN indicated that negative associations of fallow deer, red deer and wild boar with the

188 encounter rate of other woodland species is a likely candidate for the found differences. In

189 contrast, we did not find support for an explanation based on differences in I. ricinus larval

190 burden. In the Netherlands, fallow deer, red deer and wild boar only occur in a few specific areas

191 (Fig.3). Therefore, we cannot rule out if found associations with other woodland species are a

192 result of ecological (interspecies) interactions or species associations with different habitats and

193 wildlife management. It is, however, clear that forested areas where fallow deer, red deer or wild

194 boar occur likely have the highest risk for humans and domesticated animals for being exposed

195 to A. phagocytophilum though tick bites. Targeted health campaigns to increase the awareness

196 amongst health professionals might help to identify HGA cases, and may further be used for

197 stimulation of preventive measures.

10 198 Previous research linking species difference to Anaplasma

199 phagocytophilum

200 We did not find differences among ungulates in their I. ricinus larval burden based on published

201 studies. However, the number of studies was limited (n = 12), especially for some species (n = 1

202 for fallow deer and wild boar). Thus, the lack of differences is likely a result of large variation in

203 larval burdens and limited sample sizes. Especially as studies comparing I. ricinus burden among

204 different ungulate species in single study sites did find differences among species [27,28]. This

205 indicates that there is a need for more comparative studies investigating differences in I. ricinus

206 burden of the different ungulates related to differences in infection prevalence with A.

207 phagocytophilum in both hosts and feeding ticks.

208 We found a negative association in the encounter rates of fallow deer, red deer and wild boar

209 with the encounter rates of other woodland species, which could be caused by both ecological

210 interactions and management practices. Contrary to roe deer, these three species have a very

211 limited distribution in the Netherlands occurring mainly in the dunes along the coast (fallow

212 deer) and on a large forested area in the middle of the Netherlands called the Veluwe (Fig.3).

213 This restricted distribution is completely due to present and past wildlife management [29]. Both

214 of these areas are characterized by relatively high sandy soils resulting in relatively low

215 productivity [30]. As a result, both the coastal dunes and the Veluwe harbor a limited number of

216 species, which could explain the negative associations we found. Simultaneously, there could be

217 additional interspecific interactions explaining some of our results. An experimental study [31]

218 reported an evidence for cascading effects by ungulates on a temperate forest ecosystem.

219 Experimentally excluding fallow deer, roe deer, red deer, wild boar, and mouflon (Ovis

220 orientalis) from a temperate forest ecosystem in the Veluwe decreased the density of soil grains,

11 221 increased litter depth, invertebrate biomass and rodent activity. Future studies are needed to test

222 for the contribution of either mechanism on the found negative associations.

223 The bacterium A. phagocytophilum is divided into four ecotypes based on the groEL sequences

224 and the host-association [16]. These ecotypes differ in their zoonotic potential, with ecotype I

225 being able to cause HGA in humans and anaplasmosis in domesticated animals. This is

226 concerning, as red and fallow deer are considered host species for ecotype I [16]. Thus, the peaks

227 in A. phagocytophilum DIN in areas with a high encounter probability with fallow deer and red

228 deer indicates that these nymphs are likely infected with ecotype I. In contrast, roe deer are

229 considered hosts for the non-zoonotic ecotype II. As the geographic distribution of fallow and

230 red deer in The Netherlands (Fig.3) is far more restricted than the distribution of roe deer, this

231 would imply that the risk of acquiring HGA is largely restricted to areas where red/fallow deer

232 are present. This might be one of explanations for the low incidence of (reported) HGA cases.

233 Strikingly, we did not find a correlation of A. phagocytophilum DIN at the forests sites with the

234 encounter probability of a questing nymphs with roe deer (Fig.2). This contrasts with the finding

235 that the density of questing nymphal ticks in the same forest sites correlated with the encounter

236 probability [14]. Thus, we detected in this cross-sectional study some degree of impedance in the

237 A. phagocytophilum life cycle and no evidence of any impedance in the tick life cycle at the

238 forest sites where roe deer is the predominant competent species. This appears to be a common

239 situation in the Dutch forest areas with some exception. We observed a high A. phagocytophilum

240 DIN at the forest site Halfmijl (HM) (Fig.2). Only roe deer and none of the other free- ranging

241 ungulates was captured by the camera trapping at the forest site.

12 242 Conclusion

243 In conclusion, our re-analysis of the cross-sectional study suggests that the risk of contracting

244 anaplasmosis in the forest with fallow deer, red deer and wild boar is high compared to the

245 remaining forest sites where roe deer is the predominant competent host. Geographical

246 distribution of deer species in The Netherlands imply that the risk of acquiring HGA is largely

247 restricted to areas where red/fallow deer are present. Additional studies are required to test the

248 inference based on our associative study.

249 List of abbreviations

250 HGA: Human granulocytic anaplasmosis. DON: Density of questing Ixodes ricinus nymphs.

251 DIN: Density of infected nymphs. NIP: Infection prevalence in nymphs.

252 Declarations

253 Ethics approval and consent to participate

254 Not applicable

255 Consent for publication

256 Not applicable

257 Availability of data and material

258 The datasets used and/or analysed during the current study are available from the corresponding

259 author on reasonable request

13 260 Competing interests

261 The authors declare that they have no competing interests

262 Funding

263 This research was financially supported by the Dutch Ministry of Health, Welfare and Sport

264 (VWS), by a grant from the ZonMw (project number 50‐52200‐98‐313, Ticking on Pandora’s

265 box) and a grant from the European Interreg North Sea Region program, as part of the NorthTick

266 project.

267 Authors’ contributions

268 KT analysed and interpreted the data regarding the vertebrate, tick and the tick-borne pathogen,

269 and wrote the manuscript. TH interpreted the analyses and was a major contributor in writing the

270 manuscript. HS seeded the study, provided the funding and reviewed the manuscript.

271 Acknowledgements

272 Not applicable

273 Reference

274 1. Stuen S, Granquist EG, Silaghi C. Anaplasma phagocytophilum–a widespread multi-host

275 pathogen with highly adaptive strategies. Front Cell Infect Microbiol. 2013;3:31.

276 2. Matei IA, Estrada-Peña A, Cutler SJ, Vayssier-Taussat M, Varela-Castro L, Potkonjak A, et

277 al. A review on the eco-epidemiology and clinical management of human granulocytic

278 anaplasmosis and its agent in Europe. Parasit Vectors. 2019;12:599.

14 279 3. Hovius E, Bruin A de, Schouls L, Hovius J, Dekker N, Sprong H. A lifelong study of a pack

280 Rhodesian ridgeback dogs reveals subclinical and clinical tick-borne Anaplasma

281 phagocytophilum infections with possible reinfection or persistence. Parasit Vectors.

282 2018;11:238.

283 4. Azagi T, Hoornstra D, Kremer K, Hovius JWR, Sprong H. Evaluation of Disease Causality of

284 Rare Ixodes ricinus-Borne Infections in Europe. Pathogens. 2020;9.

285 5. Tijsse-Klasen E, Koopmans MPG, Sprong H. Tick-borne pathogen - reversed and

286 conventional discovery of disease. Front Public Health. 2014;2:73.

287 6. Fourie JJ, Evans A, Labuschagne M, Crafford D, Madder M, Pollmeier M, et al. Transmission

288 of Anaplasma phagocytophilum (Foggie, 1949) by Ixodes ricinus (Linnaeus, 1758) ticks feeding

289 on dogs and artificial membranes. Parasit Vectors. 2019;12:136.

290 7. Ogden NH, Casey ANJ, French NP, Woldehiwet Z. A review of studies on the transmission of

291 Anaplasma phagocytophilum from sheep: implications for the force of infection in endemic

292 cycles. Exp Appl Acarol. 2002;28:195–202.

293 8. Sprong H, Azagi T, Hoornstra D, Nijhof AM, Knorr S, Baarsma ME, et al. Control of Lyme

294 borreliosis and other Ixodes ricinus-borne diseases. Parasit Vectors. 2018;11:145.

295 9. Mather TN, Nicholson MC, Donnelly EF, Matyas BT. Entomologic index for human risk of

296 Lyme disease. Am J Epidemiol. 1996;144:1066–9.

297 10. Sprong H, Hofhuis A, Gassner F, Takken W, Jacobs F, Vliet AJH van, et al. Circumstantial

298 evidence for an increase in the total number and activity of Borrelia-infected Ixodes ricinus in

299 the Netherlands. Parasit Vectors. 2012;5:294.

15 300 11. Coipan EC, Jahfari S, Fonville M, Maassen CB, Giessen J van der, Takken W, et al.

301 Spatiotemporal dynamics of emerging pathogens in questing Ixodes ricinus. Front Cell Infect

302 Microbiol. 2013;3:36.

303 12. Lejal E, Marsot M, Chalvet-Monfray K, Cosson J-F, Moutailler S, Vayssier-Taussat M, et al.

304 A three-years assessment of Ixodes ricinus-borne pathogens in a French peri-urban forest. Parasit

305 Vectors. 2019;12:551.

306 13. Hamšíková Z, Silaghi C, Takumi K, Rudolf I, Gunár K, Sprong H, et al. Presence of Roe

307 Deer Affects the Occurrence of Anaplasma phagocytophilum Ecotypes in Questing Ixodes

308 ricinus in Different Habitat Types of Central Europe. Int J Environ Res Public Health. 2019;16.

309 14. Takumi K, Sprong H, Hofmeester TR. Impact of vertebrate communities on Ixodes ricinus-

310 borne disease risk in forest areas. Parasit Vectors. 2019;12:434.

311 15. Hofmeester TR, Coipan EC, Wieren SE van, Prins HHT, Takken W, Sprong H. Few

312 vertebrate species dominate the Borrelia burgdorferi s.l. life cycle. Environmental Research

313 Letters. IOP Publishing; 2016;11:043001.

314 16. Jahfari S, Coipan EC, Fonville M, Leeuwen AD van, Hengeveld P, Heylen D, et al.

315 Circulation of four Anaplasma phagocytophilum ecotypes in Europe. Parasit Vectors.

316 2014;7:365.

317 17. Jaarsma RI, Sprong H, Takumi K, Kazimirova M, Silaghi C, Mysterud A, et al. Anaplasma

318 phagocytophilum evolves in geographical and biotic niches of vertebrates and ticks. Parasit

319 Vectors. 2019;12:328.

320 18. Langenwalder DB, Schmidt S, Silaghi C, Skuballa J, Pantchev N, Matei IA, et al. The

321 absence of the drhm gene is not a marker for human-pathogenicity in European Anaplasma

322 phagocytophilum strains. Parasit Vectors. 2020;13:238.

16 323 19. Hofhuis A, Kassteele J van de, Sprong H, Wijngaard CC van den, Harms MG, Fonville M, et

324 al. Predicting the risk of Lyme borreliosis after a tick bite, using a structural equation model.

325 PLoS ONE. 2017;12:e0181807.

326 20. Randolph SE. Tick ecology: processes and patterns behind the epidemiological risk posed by

327 ixodid ticks as vectors. Parasitology. 2004;129 Suppl:S37–65.

328 21. Krawczyk AI, Duijvendijk GLA van, Swart A, Heylen D, Jaarsma RI, Jacobs FHH, et al.

329 Effect of rodent density on tick and tick-borne pathogen populations: consequences for infectious

330 disease risk. Parasit Vectors. 2020;13:34.

331 22. Hofmeester TR, Jansen PA, Wijnen HJ, Coipan EC, Fonville M, Prins HHT, et al. Cascading

332 effects of predator activity on tick-borne disease risk. Proc Biol Sci. 2017;284.

333 23. Hofmeester TR, Sprong H, Jansen PA, Prins HHT, Wieren SE van. Deer presence rather than

334 abundance determines the population density of the sheep tick, Ixodes ricinus, in Dutch forests.

335 Parasit Vectors. 2017;10:433.

336 24. Krawczyk AI, Bakker JW, Koenraadt CJM, Fonville M, Takumi K, Sprong H, et al.

337 Tripartite Interactions among Ixodiphagus hookeri, Ixodes ricinus and Deer: Differential

338 Interference with Transmission Cycles of Tick-Borne Pathogens. Pathogens. 2020;9.

339 25. Golub GH, Van Loan CF. Matrix computations (3rd ed.). USA: Johns Hopkins University

340 Press; 1996.

341 26. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R

342 Foundation for Statistical Computing; 2015;

343 27. Pacilly FCA, Benning ME, Jacobs F, Leidekker J, Sprong H, Wieren SEV, et al. Blood

344 feeding on large grazers affects the transmission of Borrelia burgdorferi sensu lato by Ixodes

345 ricinus. Ticks Tick Borne Dis. 2014;5:810–7.

17 346 28. Matuschka FR, Heiler M, Eiffert H, Fischer P, Lotter H, Spielman A. Diversionary role of

347 hoofed game in the transmission of Lyme disease spirochetes. Am J Trop Med Hyg.

348 1993;48:693–9.

349 29. van Wieren S, Groot Bruinderink G. Ungulates and their management in the netherlands. In:

350 Apollonia M, Andersen R, Putman R, editors. European ungulates and their management in the

351 21th century. Cambridge University Press; 2010. pp. 165–83.

352 30. Kooijman A, Smit A. Grazing as a measure to reduce nutrient availability and plant

353 productivity in acid dune grasslands and pine forests in the netherlands. Ecological Engineering.

354 2001;17:63–77.

355 31. Ramirez JI, Jansen PA, Ouden J den, Moktan L, Herdoiza N, Poorter L. Above- and below-

356 ground cascading effects of wild ungulates in temperate forests. Ecosystems. Springer Science;

357 Business Media LLC; 2020;

358 32. Hornok S, Horváth G, Jongejan F, Farkas R. Ixodid ticks on ruminants, with on-host initiated

359 moulting (apolysis) of Ixodes, Haemaphysalis and Dermacentor larvae. Vet Parasitol.

360 2012;187:350–3.

361 33. Mysterud A, Qviller L, Meisingset EL, Viljugrein H. Parasite load and seasonal migration in

362 red deer. Oecologia. 2016;180:401—407.

363 34. Mysterud A, Hatlegjerde IL, Sørensen OJ. Attachment site selection of life stages of Ixodes

364 ricinus ticks on a main large host in Europe, the red deer (Cervus elaphus). Parasit Vectors.

365 2014;7:510.

366 35. Handeland K, Qviller L, Vikøren T, Viljugrein H, Lillehaug A, Davidson RK. Ixodes ricinus

367 infestation in free-ranging cervids in Norway–a study based upon ear examinations of hunted

368 animals. Vet Parasitol. 2013;195:142–9.

18 369 36. Kiffner C, Lödige C, Alings M, Vor T, Rühe F. Abundance estimation of Ixodes ticks (Acari:

370 Ixodidae) on roe deer (Capreolus capreolus). Exp Appl Acarol. 2010;52:73–84.

371 37. Pato FJ, Panadero R, Vázquez L, López CM, Díaz P, Vázquez E, et al. Seroprevalence of

372 Borrelia burgdorferi sensu lato in roe deer (Capreolus capreolus) from northwestern Spain. J Zoo

373 Wildl Med. 2013;44:660–5.

374 38. Tälleklint L, Jaenson TG. Infestation of mammals by Ixodes ricinus ticks (Acari: Ixodidae) in

375 south-central Sweden. Exp Appl Acarol. 1997;21:755–71.

376 39. Vázquez L, Panadero R, Dacal V, Pato FJ, López C, Díaz P, et al. Tick infestation (Acari:

377 Ixodidae) in roe deer (Capreolus capreolus) from northwestern Spain: population dynamics and

378 risk stratification. Exp Appl Acarol. 2011;53:399–409.

379 40. Vor T, Kiffner C, Hagedorn P, Niedrig M, Rühe F. Tick burden on European roe deer

380 (Capreolus capreolus). Exp Appl Acarol. 2010;51:405–17.

381 41. Król N, Chitimia-Dobler L, Dobler G, Karliuk Y, Birka S, Obiegala A, et al. Tick burden on

382 European roe deer (Capreolus capreolus) from Saxony, Germany, and detection of tick-borne

383 encephalitis virus in attached ticks. Parasitol Res. 2020;119:1387–92.

384

19 385 Figure legends

386

387 Figure 1: PCA plot of encounter probabilities. A black dot is a position of a forest site in 2nd and

388 3rd PCA coordinates. A box contains two letters abbreviating a forest site name. A green box

389 indicates a high Anaplasma phagocytophilum DIN. A red box dicates a low Anaplasma

390 phagocytophilum DIN. A green dot is a position of a woodland species. The species name is

391 placed in a distance away from the green dot to avoid excessive overlaps.

20 392

393 Figure 2: The three free-ranging ungulates except roe deer support Anaplasma phagocytophilum

394 DIN. Observed Anaplasma phagocytophilum DIN was calculated by multiplying the density of

395 questing Ixodes ricinus nymphs by the Anaplasma phagocytophilum NIP. Bar heights in the

396 middle panel (Others referring to fallow deer, red deer and wild boar) were calculated using

397 Eq.(2). Bar heights in the right panel were calculated using Eq.(1).

21 398

399 Figure 3: Ungulate presence The Netherlands 2000 - 2020. Source:

400 https://www.verspreidingsatlas.nl Green: roe deer. Red: red deer. Blue: fallow deer. Black: wild

401 boar.

402

22 403 Tables

404 Table 1: Density of nymphs infected with A. phagocytophilum (DIN) is unrelated with the

405 density of nymphs (DON).

DON Test Positive NIP DIN

DON

Test 0.7

Positive 0.26 0.48

NIP 0.11 0.22 0.93

DIN 0.34 0.41 0.94 0.91

406 Table entries are Pearson correlations calculated using Additional file 1 Table 6. Numerals are

407 bold when p-value is less than 0.05. DON: Density of questing Ixodes ricinus nymphs. Test:

408 Number of questing Ixodes ricinus nymphs tested for the presence of Anaplasma

409 phagocytophilum. Positive: Number of Anaplasma phagocytophilum presence in questing Ixodes

410 ricinus nymphs. NIP: Positive divided by Test. DIN: Density of infected Ixodes ricinus nymphs.

411

23 412 Table 2: Observed Anaplasma phagocytophilum DIN lacks a correlation with roe deer and

413 correlates with the other fee-ranging ungulates.

Observation Others Roe deer

Observation

Others 0.64

Roe deer -0.02 -0.56

414 Table entries are Pearson correlations. Numerals are bold when p-value is less than 0.05.

415

24 416 Table 3: Analysis of larval ticks on four ungulate species.

Model theta Resid. df 2 x log-lik. Test df LR stat. Pr(Chi)

Samples 0.289 18 -293.764

Samples + Species 0.317 15 -291.179 1 vs 2 3 2.585 0.46

417 Additional file 1 Table 5 displays the data.

418

25 419 Table 4: Frequency of positive and negative correlations in encounter rates with 32 woodland

420 species.

Positive Negative

Roe.Deer 18 14

Fallow.Deer 6 26

Red.Deer 9 23

Wild.Boar 9 23

421 A cell displays a number of woodland species having a positive (or negative) correlation with the

422 ungulate species. Additional file 1 Table 7 displays the data.

423

26 424 Additional file 1

425

426 Figure 4: Encounter probability [14] for each forest site (row) and an individual vertebrate

427 species (column) increases from 0 (light circle) to 1 (dark circle). A row sum equals to 1.

428

27 429 Table 5: Number of larval ticks on four ungulate species.

Species Samples DOL Reference

Fallow.deer 115 5719 [28]

Red.deer 32 0 [32]

Red.deer 147 4140 [28]

Red.deer 38 305 [27]

Red.deer 49 70 [33]

Red.deer 33 256 [34]

Red.deer 197 416 [35]

Wild.boar 9 73 [27]

Roe.deer 35 3 [32]

Roe.deer 224 621 [35]

Roe.deer 80 862 [36]

Roe.deer 67 577 [28]

Roe.deer 154 459 [37]

Roe.deer 37 9805 [38]

Roe.deer 367 1052 [39]

Roe.deer 142 268 [40]

Roe.deer 2 130 [41]

Roe.deer 50 0 [41]

Roe.deer 54 8 [41]

Roe.deer 28 30 [41]

430

28 431 Table 6: Summary of tests for the presence of Anaplasma phagocytophilum in questing Ixodes

432 ricinus nymphs.

DON Test Positive NIP DIN

BU 2200 688 0 0.000 0.000

DW 1647 1650 68 0.041 67.876

HM 1531 624 36 0.058 88.327

EN 1379 1397 62 0.044 61.201

ST 1134 1129 9 0.008 9.040

VH 1039 1039 4 0.004 4.000

DK 870 858 31 0.036 31.434

BB 869 742 6 0.008 7.027

RB 859 863 7 0.008 6.968

KB 794 791 2 0.003 2.008

VA 765 763 42 0.055 42.110

PW 760 767 114 0.149 112.960

AW 726 678 39 0.058 41.761

ZM 680 665 21 0.032 21.474

MH 640 639 11 0.017 11.017

VL 403 398 2 0.005 2.025

PD 130 130 1 0.008 1.000

HD 120 120 1 0.008 1.000

SD 22 26 0 0.000 0.000

433

29 434 Table 7: Correlation in encounter rates between ungulates and other forest species [14].

Roe.Deer Fallow.Deer Red.Deer Wild.Boar

Beech.Marten 0.345 -0.130 -0.215 -0.150

Blackbird 0.325 -0.180 -0.358 -0.200

Blue.Tit 0.266 -0.068 -0.111 -0.078

Chaffinch -0.071 -0.068 -0.111 -0.078

Common.Starling 0.266 -0.068 -0.111 -0.078

Eurasian.Jay 0.185 0.100 0.357 0.265

Eurasian.Red.Squirrel 0.108 -0.069 -0.316 -0.220

Eurasian.Siskin 0.244 -0.068 -0.111 -0.078

Eurasian.woodcock -0.231 0.872 -0.153 -0.106

European.Badger 0.247 -0.228 -0.133 -0.051

European.Hare 0.189 -0.196 -0.320 -0.224

European.Pine.Marten -0.037 -0.033 0.475 0.344

European.Rabbit -0.145 -0.075 -0.123 -0.086

Fallow.Deer -0.327 1.000 -0.110 -0.083

Great.Spotted.Woodpecker 0.233 0.034 -0.187 -0.130

Great.tit 0.358 -0.220 -0.363 -0.253

Mistle.Thrush -0.207 -0.059 0.661 0.085

Red.Deer -0.435 -0.110 1.000 0.685

Red.Fox 0.024 -0.004 -0.247 -0.090

Redwing 0.293 -0.068 -0.111 -0.078

Roe.Deer 1.000 -0.327 -0.435 -0.325

30 Song.Thrush 0.085 -0.189 -0.312 -0.217

Stock.Dove 0.326 -0.116 -0.191 -0.133

Western.Hedgehog -0.259 0.317 -0.222 -0.155

Western.Polecat 0.256 0.073 -0.240 -0.167

Wild.Boar -0.325 -0.083 0.685 1.000

Wood.Pigeon -0.299 -0.047 -0.087 -0.039

Bank.vole -0.065 -0.198 0.459 0.253

Wood.mouse 0.193 -0.094 -0.144 -0.057

Field.vole -0.306 -0.070 0.458 0.248

Common.shrew -0.191 -0.169 0.331 0.164

Pygmy.shrew -0.069 -0.121 0.067 0.209

435

31 Figures

Figure 1

PCA plot of encounter probabilities. A black dot is a position of a forest site in 2nd and 3rd PCA coordinates. A box contains two letters abbreviating a forest site name. A green box indicates a high Anaplasma phagocytophilum DIN. A red box dicates a low Anaplasma phagocytophilum DIN. A green dot is a position of a woodland species. The species name is placed in a distance away from the green dot to avoid excessive overlaps. Figure 2

The three free-ranging ungulates except roe deer support Anaplasma phagocytophilum DIN. Observed Anaplasma phagocytophilum DIN was calculated by multiplying the density of questing Ixodes ricinus nymphs by the Anaplasma phagocytophilum NIP. Bar heights in the middle panel (Others referring to fallow deer, red deer and wild boar) were calculated using Eq.(2). Bar heights in the right panel were calculated using Eq.(1). Figure 3

Ungulate presence The Netherlands 2000 - 2020. Source: https://www.verspreidingsatlas.nl Green: roe deer. Red: red deer. Blue: fallow deer. Black: wild boar. Figure 4

Encounter probability [14] for each forest site (row) and an individual vertebrate species (column) increases from 0 (light circle) to 1 (dark circle). A row sum equals to 1.

Supplementary Files

This is a list of supplementary les associated with this preprint. Click to download.

Additionalle1.docx