Different Ecological Niches for Ticks of Public Health Significance in Canada

Vanessa Gabriele-Rivet; Julie Arsenault; Jacqueline Badcock; Angela Cheng; Jim Edsall; Jim Goltz; Joe Kennedy; L. Robbin Lindsay; Yann Pelcat; Nicholas H. Ogden

doi:10.1371/journal.pone.0131282

Abstract

Tick-borne diseases are a growing public health concern as their incidence and range have increased in recent decades. Lyme disease is an emerging infectious disease in Canada due to northward expansion of the geographic range of Ixodes scapularis, the principal tick vector for the Lyme disease agent Borrelia burgdorferi, into central and eastern Canada. In this study the geographical distributions of Ixodid ticks, including I. scapularis, and environmental factors associated with their occurrence were investigated in New Brunswick, Canada, where few I. scapularis populations have been found to date. Density of host-seeking ticks was evaluated by drag sampling of woodland habitats in a total of 159 sites. Ixodes scapularis ticks (n = 5) were found on four sites, Ixodes muris (n = 1) on one site and Haemaphysalis leporispalustris (n = 243) on 41 sites. One of four adult I. scapularis ticks collected was PCR-positive for B. burgdorferi. No environmental variables were significantly associated with the presence of I. scapularis although comparisons with surveillance data in neighbouring provinces (Québec and Nova Scotia) suggested that temperature conditions may be too cold for I. scapularis (< 2800 annual degree days above 0°C [DD > 0°C]) across much of New Brunswick. In contrast, the presence of H. leporispalustris, which is a competent vector of tularaemia, was significantly (P < 0.05) associated with specific ranges of mean DD > 0°C, mean annual precipitation, percentage of clay in site soil, elevation and season in a multivariable logistic regression model. With the exception of some localized areas, temperature conditions and deer density may be too low for the establishment of I. scapularis and Lyme disease risk areas in New Brunswick, while environmental conditions were suitable for H. leporispalustris at many sites. These findings indicate differing ecological niches for two tick species of public health significance.

Citation: Gabriele-Rivet V, Arsenault J, Badcock J, Cheng A, Edsall J, Goltz J, et al. (2015) Different Ecological Niches for Ticks of Public Health Significance in Canada. PLoS ONE 10(7): e0131282. https://doi.org/10.1371/journal.pone.0131282

Editor: Brian Stevenson, University of Kentucky College of Medicine, UNITED STATES

Received: April 30, 2015; Accepted: June 1, 2015; Published: July 1, 2015

Copyright: © 2015 Gabriele-Rivet et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: Jim Edsall Insect Identification Services provided support in the form of a salary for author JE, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of all authors are articulated in the ‘author contributions’ section.

Competing interests: JE is the owner of Jim Edsall Insect Identification Services. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Introduction

Ticks are vectors of bacterial, viral and protozoal pathogens of importance for human and animal health [1]. An increasing incidence of tick-borne diseases has been reported world-wide in recent years, which constitutes a critical concern for public and animal health [2, 3]. Emerging and re-emerging tick-borne diseases include Lyme disease, tularemia, Rocky Mountain spotted fever, ehrlichiosis, anaplasmosis, and babesiosis [4, 5]. Lyme disease, a bacterial disease caused by the spirochete Borrelia burgdorferi, is the most commonly reported tick-transmitted infection in temperate zones of the northern hemisphere, particularly in the United States and Europe [6–8]. The principal tick vector for B. burgdorferi in eastern and central North America is Ixodes scapularis [9]. Northward expansion of the geographic range of I. scapularis, from the United States into Eastern and Central Canada, is occurring and has resulted in an increased risk for Lyme disease in parts of southern Canada [10]. Associated with the range expansion of both I. scapularis and B. burgdorferi, the incidence of Lyme disease in Canada has risen markedly during recent years [10, 11]. The ticks are thought to be mostly introduced into Canada by migratory birds moving north in the springtime [12]. Mammalian hosts, such as the white-tailed deer Odocoileus virginianus Zimmermann, likely also play a role in dispersing ticks although mostly over short distances to nearby habitats [13]. Ticks carried by dispersing hosts, as well as the reservoir-competent hosts themselves, may be infected with B. burgdorferi and introduce the bacterium to locations where tick populations have become established resulting in the emergence of new Lyme disease risk areas [14].

Climate and landscape features as well as host densities affect the geographic distributions and densities of many tick species [15–19]. The ability of I. scapularis to survive and establish a self-sustaining, reproducing population in a new environment depends on these abiotic and biotic factors. Temperature seems to be an important limiting factor for the expansion of I. scapularis populations in Canada, via effects on rates of tick development from one life stage to another [20, 21]. Low temperatures increase the duration of developmental periods and consequently increase the duration of the life cycle and, as a result, the proportion of ticks that die before the cycle has been completed [20]. Rising temperatures associated with climate change are expected to permit or accelerate the northward spread of ticks such as I. scapularis [21–23]. In certain types of woodlands, the litter layer conditions provide a suitable environment for ticks to survive while undergoing development or seeking hosts, and protect them from unfavorable temperatures and humidity in winter and summer [24–26]. It is likely that a combination of interrelated factors including climate, soil types, drainage, aspect, elevation and the plant community affects how favourable the litter layer is for ticks [24, 27]. Finally, sufficient numbers of hosts need to be present for the ticks to survive as they are obligate parasites. For example white-tailed deer are key hosts for adult I. scapularis and densities of >7 per km² have been considered essential for tick persistence [28, 29].

In 1998, I. scapularis in Canada was restricted to Long Point on the shores of Lake Erie, in Ontario [30]. More recently, established I. scapularis populations have been identified in multiple areas of southern Québec, Ontario, Manitoba, Nova Scotia and New Brunswick [11]. In New Brunswick, field surveillance campaigns in 2008 and 2010 revealed sites with I. scapularis ticks only in the Saint-John area. Subsequently, another localised area where I. scapularis ticks occur was found on Grand Manan Island. Passive tick surveillance data have suggested that I. scapularis populations may be becoming established in other areas in New Brunswick [14]. In eastern Canada there is little information on other tick vectors of Lyme disease (e.g. I. dentatus) [31] or tick species such as Dermacentor variabilis and Haemaphysalis leporispalustris that may be vectors of tick-borne diseases of public health importance such as tularaemia [32]. The present study was undertaken to i) evaluate the extent to which populations of I. scapularis and other tick species of public health importance may have become established in New Brunswick; and ii) to better understand the environmental determinants of their niches.

Materials and Methods

Site selection

A cross-sectional study was conducted between May and September 2014 to determine the presence of I. scapularis in New Brunswick and assess occurrence of other exophilic tick species. The study locations were selected to maximise our knowledge of the current distribution of I. scapularis and other ticks while encompassing enough study sites to provide information on the suitability of a variety of woodland types within four lowland ecoregions of New Brunswick (Fundy Coastal, Valley Lowlands, Eastern Lowlands and Grand Lake Lowlands as defined by New Brunswick Department of Natural Resources [33]). The number of sites per ecoregion (totalling > 140 sites for the whole study) was determined to detect differences in prevalence of tick-positive sites amongst ecoregions of 0 versus 0.25 with 80% power and alpha of 0.05. The algorithm for site selection was 1) selection of ecoregion as described above; 2) selection of woodlands (all types) of a minimum size of 200 x 200 m; 3) random selection of 280 sites from these woodlands; 4) removal of sites with no road access and within 50 m of any water body or wetland; 5) identification of cadastres to obtain owner information; and 6) final selection based on securing permission to visit the sites from the land owners where this was possible. Selected sites comprised woodlands on crown land which is open access, and private woodlands to which non-motorised access is not restricted in New Brunswick, although permissions were sought in most cases. No sites involved protected areas that would require permits for sampling and ethical or other permits were not required for collecting ticks by drag sampling.

Tick collection

Each site was sampled once by one field operative. Sampling was conducted within a 10,000 m² grid (200 m X 50 m). The collection of host-seeking ticks was carried out by dragging a 1-m² flannel through vegetation over twenty 50 m transects with a pause every 10 m to inspect the flannel for ticks. GPS locations were collected at the start of field sampling. Ticks of any species collected were placed into tubes containing filter paper moistened with sterilised water and transported by courier to the National Microbiology Laboratory (NML) in Winnipeg where tick species were identified and any I. scapularis ticks tested by PCR for the tick-borne pathogens Borrelia burgdorferi, B. miyamotoi, Anaplasma phagocytophilum and Babesia microti [34].

Environmental determinants of tick occurrence

Environmental variables for each study site were obtained from two sources, data collected at the site at the time of visit and data obtained from georeferenced databases.

Environmental data collected at each site visit.

At each site during the visit, environmental data collected were i) Elevation aspect (categorized as hill, slope or level table), ii) Soil moisture characteristic (wet, moist, fresh or dry), iii) Soil texture composition (the percentage of soil comprising loam and clay on a scale of 0–100% using the methodology described in Lee et al. [35] and used in previous studies on environmental determinants of tick survival [36]), and iv) Dominant tree species within each site [35]. On the basis of tree species, the habitat of each site was categorized with reference to the New Brunswick forest classifications scheme [33] as 0 (woodlands of moist but well-drained fertile lowland soils—climax forest/closed canopy/shade tolerant), 1 (woodlands of well drained sandy soils), 2 (woodlands of wetlands/swamp) or 3 (woodlands comprising shade intolerant and/or pioneer species indicating disturbed woodlands).

Georeferenced environmental data.

The following environmental features were extracted using ArcGIS version 10.2.2 (ESRI, Redlands, CA): i) Site elevation from Canadian Digital Elevation Model (CDEM) which has a geographic resolution of 20 m (Government of Canada, Natural Resources Canada, Earth Sciences Sector, Mapping Information Branch, GeoAccess Division, 2010, www.geogratis.gc.ca/site/eng/extraction); ii) Forestry data from the Digital Forest Resource Inventory data (2012) of the Natural Resources of New Brunswick. A circular buffer of 200 m was delineated around each site GPS point and the dominant tree species and the mean values of elevation were extracted for each buffer. The sites were classified into the same four classifications as described for the site-observed tree data using the dominant tree species in the buffer.

Land surface temperature (LST) for each site was derived from MOD11C3, a remotely-sensed Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, from 2009 to 2014, with a spatial resolution of 250 m. The monthly mean temperature above 0°C (averaged from the daytime and nighttime passes) was multiplied by the number of days in that month and then cumulatively added for each month of the year to obtain an estimate of the annual cumulative degree-days > 0°C (DD > 0°C) at each site. The mean annual DD > 0°C from 2009 to 2014 was subsequently calculated. According to the results obtained from Ogden et al. [21], approximately 2800 DD > 0°C was considered the minimum threshold temperature conditions for the establishment of self-sustaining populations of I. scapularis ticks. For each site, the number of years from 2009 to 2014, when the temperature was suitable for I. scapularis (i.e. DD > 0°C equal to or above 2800) was calculated. This six-year period was selected because the duration of the I. scapularis lifecycle is two to three years in length [21], and we considered that the temperature conditions over two to three potential I. scapularis lifecycles prior to and including the study period were the most appropriate for considering the temperature suitability of the sites. Additionally, the temperature-variable basic reproduction number R₀ of I. scapularis (the capacity of this species to reproduce given certain environmental conditions) was also estimated for each site location for each year using the I. scapularis population model described by Wu et al [37] and calibrated by the MODIS temperature data. The annual R₀ of I. scapularis at each site was averaged for the 2009 to 2014 time frame.

The total annual precipitation was obtained for each year from 2009 to 2013 (the most recently available data) for the GPS position of each site using an interpolated grid at a spatial resolution of 10 km developed by the National Land and Water Information Service of Canada [38] and mean annual precipitation calculated.

Estimates of densities of white-tailed deer (Odocoileus virginianus) were derived from in-house models developed by the New Brunswick Natural Resources, which is based upon roadkill and harvest data for each wildlife management zone in New Brunswick. The deer density estimate for the wildlife management zone in which a site occurred was ascribed to that site.

Statistical analyses

Analysis of environmental determinants.

The prevalence of sites where ticks were found was determined for each tick species, with 95% exact confidence limits. Logistic regression models were built in SAS version 9.3 (SAS Institute Inc., Cary, NC) to explore the relationships between environmental variables and occurrence of each tick species identified in the study. The models also accounted for ecoregions and season (‘spring’ being May and June, ‘summer’ being July and August and ‘autumn’ being September). The season of each visit was included as this could possibly have an effect on the sensitivity of detection due to different tick instars being active in different seasons. Two explanatory variables, which were the number of years with a DD > 0°C equal to 2800 or above, and the mean R₀, are meaningful only for I. scapularis ticks and were therefore not considered for other ticks. A list of all explanatory variables is presented in Table 1. The models employed maximum likelihood logistic regression except when the numbers of positive sites were low, or when no positive sites were obtained in one category of the predictor, in which case the exact inference method for logistic regression was employed, which is recommended for analyzing unbalanced or sparse binary datasets [39]. The assumption of linearity between each continuous variable and the log odds of the outcome was verified using graphical method with categorization [40] as well as by visual inspection of Lowess smoothed graphs produced in STATA (StataCorp, College Station, TX). When the linearity assumption of continuous variables was not respected, the variables were categorized using the 33^rd and 66^th percentiles as cut-offs. All explanatory variables with P values ≤0.10 from univariate analyses were considered eligible for the multivariable logistic regression analysis allowing for liberal inclusion of variables. Pairwise Pearson correlations among explanatory variables selected from univariate analyses were calculated on the continuous scale. If a strong correlation (r| > 0.7|) was detected only one variable was included in the full model based on the strongest biological plausibility. The final model was obtained using a backward selection procedure with P>0.05 as the rejection criterion. The goodness-of-fit of the model was assessed by applying the Hosmer-Lemeshow statistic test and the area under the Receiver Operating Characteristic (ROC) curve (AUC) was used as a measure of the predictive ability of the model.

Download:

Table 1. Descriptive statistics of explanatory variables and results from univariate analyses for occurrence of I. scapularis and H. leporispalustris at the 159 field sites visited during the study.

https://doi.org/10.1371/journal.pone.0131282.t001

To test the validity of threshold temperature conditions of 2800 of DD > 0°C for invasion and persistence of populations of I. scapularis, field surveillance data collected in this study on I. scapularis were combined with field surveillance data obtained mostly by drag sampling in recent years in Québec and Nova Scotia (see [41] for details). For each location where field surveillance has taken place, the number of years in the last six years (2009–2014) in which DD > 0°C was > 2800 was obtained from the MODIS data described above. ROC analysis in STATA was then conducted to assess the specificity and sensitivity of the number of years when DD > 0°C was > 2800 to predict the presence or absence of I. scapularis at surveillance sites. The positive and negative predictive values (PPV and NPV) for the presence of I. scapularis for the number of years DD > 0°C was > 2800 were calculated using the formulae below. Where TP, FP, TN and FN are true positives, false positives, true negatives and false negatives, respectively. See S1 File for surveillance data collected or used.

Spatial analysis.

Geographic patterns of tick populations could be due to environmental suitability for the ticks alone, but may be confounded by patterns of spread from a source location. This may be particularly pertinent for I. scapularis which is expanding its geographic range in Canada [42]. The following analyses explored the possibility that geographic patterns were associated with spread rather than environmental suitability alone. First, the presence of spatial clusters of positive sites for each tick species discovered was explored using the Kulldorff spatial scan test in SatScan version 9.2 [43]. The Bernoulli model was used with a maximum cluster size of up to 50% of the population at risk. The significance (P < 0.05) of clusters was determined through 999 Monte Carlo replicates. Spatial clusters of tick-positive sites could, however, be due to spatial clusters of key environmental variables, so for any spatial cluster we explored whether environmental variables significantly associated with tick presence also explained the spatial cluster using logistic regression in which site presence in the cluster was the outcome, and the environmental variable was the explanatory variable. Second, we undertook ‘clustering’ analysis (i.e. whether the distribution of positive sites was more clustered or dispersed than a random distribution for a range of distances), using the Ripley spatial K-function [44], performed in ROCR package version 1.0–5 in R [45]. In this analysis, the plot of the difference (D) between the K-function calculated for positive sites and the K-function calculated for negative sites against distance was evaluated against a hypothesis of complete spatial randomness.

Results

Tick collection

A total of 159 sites that fulfilled the criteria for inclusion in the study were visited from May 27^th to September 24^th 2014. Sites were distributed over six ecoregions to obtain the sample size desired. This included the four initially targeted ecoregions as well as the Central Uplands and Northern Uplands ecoregions (Fig 1). One I. scapularis tick was found in each of three sites, of which two were adults and one was a larva. Additionally, two adult ticks were found on another site. This results in a prevalence of 2.5% of sites with I. scapularis ticks (exact 95% confidence interval [CI] = 0.7%-6.3%). A total of 243 H. leporispalustris were found on 41 sites with a range of 1 to 67 ticks per site, which corresponds to 25.8% of all sites visited (95% CI = 19.2%-33.3%). More than 90% of these H. leporispalustris ticks were larvae; the remainder were nymphs. In addition, one Ixodes muris nymph was detected on one site. Details on the numbers of ticks collected are presented in Table 2 and the locations of tick collection are shown in Fig 1. The adult I. scapularis were found in June, July and August, and the larval I. scapularis was found in September. Larval and nymphal H. leporispalustris were collected from June to September. For nymphal H. leporispalustris, a unimodal pattern of seasonal activity peaking in July-August was observed, and while peak activity of larvae occurred in September, a second peak occurred in July suggesting a bimodal seasonal pattern of activity (Fig 2).

Download:

Fig 1. Distribution of sampling sites and tick-positive sites.

Sites of occurrence of I. scapularis (green), H. leporispalustris (blue), I. scapularis and H. leporispalustris (pink) and I. muris and H. leporispalustris (yellow) are shown. The black circle indicates a significant cluster of sites where H. leporispalustris ticks were found. The two sites where I. scapularis were found in previous field studies are identified by red stars. The map was created in ArcGIS Version 10.2 (ESRI. Redlands, CA).

https://doi.org/10.1371/journal.pone.0131282.g001

Download:

Fig 2. The seasonal activity of immature H. leporispalustris.

The seasonality is expressed as the proportion of the total number of ticks of each instar collected in each month of the study.

https://doi.org/10.1371/journal.pone.0131282.g002

Download:

Table 2. Numbers of ticks of each species and instar collected during the study.

Note that all adult ticks were males.

https://doi.org/10.1371/journal.pone.0131282.t002

One of the four I. scapularis adult ticks collected was positive for B. burgdorferi. PCR was not performed on the larval I. scapularis since the transmission of B. burgdorferi from female to their larval progeny does not seem to occur [46]. DNA of B. miyamotoi, A. phagocytophilum and B. microti were not detected in the four I. scapularis adult ticks.

Environmental determinants of tick occurrence

Statistical models were developed for both I. scapularis and H. leporispalustris, with the exact inference method for logistic regression being employed for I. scapularis due to the sparse data. None of the continuous variables respected the linearity assumption and they were therefore categorized (Table 1). No variables were significantly associated with the presence of I. scapularis at the P<0.05 level of significance.

On univariable analyses for H. leporispalustris, five variables were significant at the P < 0.01 level, which were level of clay, mean elevation, mean DD > 0°C, mean annual precipitation and season (Table 1). Collinearity amongst these variables was not detected. All five predictors were retained in the final model after the backward selection procedure. Results from the full model are detailed in Table 3. The Hosmer-Lemeshow test of goodness of fit for the resulting model was not significant (P = 0.54) which indicates that the model fit the data well. Additionally, the AUC was 0.88 suggesting a high predictive ability of the model. Sites with higher annual DD>0°C (> 2739.3) were at greater risk of H. leporispalustris compared to sites with medium (2653.5–2739.3) and low (< 2653.5) annual DD>0°C. The range of mean annual DD>0°C at H. leporispalustris-positive sites was 2461 to 3003, with mean and median values of 2733 and 2746, respectively.

Download:

Table 3. Final multivariable logistic regression model for predicting occurrence of H. leporispalustris.

https://doi.org/10.1371/journal.pone.0131282.t003

Data on I. scapularis surveillance conducted from 2007 to 2012 were available from 87 sites in Nova Scotia (where I. scapularis was found at 32) and 213 sites in Québec (where I. scapularis was found at 101), as well as two known localised areas where I. scapularis populations occur in New Brunswick, in addition to the 159 sites investigated in this study. Therefore there were data from a total of 461 sites for ROC analysis (Fig 3). As shown in Fig 3, sites in New Brunswick were colder than sites in Nova Scotia or Québec with only 20% (33/162) of sites in New Brunswick having experienced > 2800 DD > 0°C in more than one year from 2009–2014, compared to 70% (61/87) of sites in Nova Scotia and 90% (191/213) of sites in Québec. Ixodes scapularis were found at 37% (32/87) of sites in Nova Scotia and 47% (101/213) of sites in Québec. The overall area under the ROC curve was 0.78 (95% CI = 0.74–0.82) and details of the ROC analysis results are shown in Table 4. The sensitivity of detection of I. scapularis-positive sites was high using the criterion of multiple years in which DD > 0°C was > 2800, reaching values > 90%. Ixodes scapularis were found at only 3 of 77 sites at which temperature conditions did not reach > 2800 DD > 0°C in at least one year. Specificity was, however, comparatively low (as low as 17%), although this would be consistent with southeastern Canada being a zone of I. scapularis emergence where not all climatically suitable habitats would be expected to be occupied yet by tick populations, resulting in ‘false negative’ locations in the ‘gold standard’ field surveillance data. Consistent with this, the criterion of one or more years with DD > 0°C > 2800 had high (near or over 90%) negative predictive value for I. scapularis, while positive predictive value was considerably lower, consistent with climatically suitable sites not yet being occupied by I. scapularis populations (Table 4).

Download:

Fig 3. Relation of temperature conditions and results of field surveillance for I. scapularis in eastern Canada.

The map shows the number of years from 2009–2014 in which DD > 0°C was greater than the model-based threshold for I. scapularis population survival obtained for southeastern Quebec and the Maritime provinces (New Brunswick, Prince Edward Island and Nova Scotia) from MODIS satellite data at a spatial resolution of 250 m. Sites where field surveillance for I. scapularis has occurred are indicated by circles (for locations where I. scapularis were found) and crosses (for locations where I. scapularis were not found). The map was created in ArcMap 10.2.2 (ESRI. Redlands, CA).

https://doi.org/10.1371/journal.pone.0131282.g003

Download:

Table 4. Results of ROC analysis of the sensitivity and specificity of the number of years from 2009–2014 in which DD > 0°C was > 2800 for predicting the presence of I. scapularis-positive sites in Québec, Nova Scotia and New Brunswick using surveillance data collected in this and in previous studies.

https://doi.org/10.1371/journal.pone.0131282.t004

Spatial analysis

No spatial clusters of positive sites for I. scapularis were detected (relative risk [RR] = 38.75, P = 0.24, Fig 1). A cluster was however detected for H. leporispalustris (RR = 3.47, P = 0.012) with a radius of 127.96 km, containing 75 sites in the south of New Brunswick (Fig 1). An exact regression logistic model was developed to predict whether H. leporispalustris-positive sites were inside or outside the spatial cluster on the basis of environmental variables. Mean annual precipitation and mean DD > 0°C were found significant in the univariate analysis and both were subsequently retained in the final model (Tables 5 and 6). This suggested that the observed spatial cluster of positive sites in southern New Brunswick was likely associated with the spatial pattern of these two key environmental variables. In evaluating spatial autocorrelation of tick-positive sites using ‘clustering’ analysis, the D function remained within the envelope formed by upper and lower bounds of values consistent with an absence of significant clustering of tick-positive sites for both tick species [47].

Download:

Table 5. Results of univariate analyses for predicting whether H. leporispalustris-positive sites were inside or outside the spatial cluster.

https://doi.org/10.1371/journal.pone.0131282.t005

Download:

Table 6. Final multivariable exact logistic regression model for predicting whetherH. leporispalustris-positive sites were inside or outside the spatial cluster.

https://doi.org/10.1371/journal.pone.0131282.t006

Discussion

Ixodes scapularis ticks were found in only 4 of 159 sites in this study, which suggests that populations of this tick are currently rare in New Brunswick and that risk from Lyme disease is mostly very low. Even on the sites where I. scapularis were collected, tick abundance is very low. These findings could be the result of the introduction of adventitious ticks dispersed by migratory birds or the existence of a recently established population with ticks present at very low density [12, 14]. An immature tick was found at one site, and multiple ticks (two adult males) were found at another, possibly suggesting that reproducing populations are present at these two sites. However, at two sites only one adult male tick was collected and at one of these sites annual DD > 0°C was not >2800 in any year from 2009 to 2014, which was an uncommon finding in our whole 461 site database of field surveillance. While in general detecting at least one I. scapularis by drag sampling suggests the presence of a reproducing tick population, the presence of only one adult tick could mean that the tick was an adventitious tick carried into the site from another location in Canada or the US by a migratory bird [48]. One of the two I. scapularis adult ticks found on the same site was PCR-positive for B. burgdorferi. This tick may have been an adventitious tick that acquired infection as an immature tick in its location of origin [48], or have acquired infection on the site and provide evidence of local transmission of B. burgdorferi by an established tick population, which would have greater implications for public health. Further study is required to confirm whether or not these ticks came from a reproducing population in the early phase of establishment when tick abundance would be expected to be low [14], or if these ticks were more likely adventitious ticks. To date we have found that drag sampling is equally sensitive at detecting I. scapularis throughout the May to October period, likely because the large adults active in spring and autumn are easy to see but of relatively low abundance, while much smaller nymphs and larvae active in late spring to early autumn are more difficult to see but more numerous than adults [48]. It would, however, be prudent to undertake longitudinal studies at these sites and include examination of hosts (particularly captured rodent), because use of the latter increases sensitivity of detection of tick populations especially for tick populations at low densities [48]. A conclusion on the presence or absence of reproducing I. scapularis populations could be more certainly made if drag sampling and rodent capture were used together in a longitudinal study [48].

Unsurprisingly given the small number of positive sites, no environmental factors were found to be significantly associated with the presence of I. scapularis and no spatial clusters of positive sites were detected. According to passive tick surveillance data, I. scapularis ticks are certainly dispersed into New Brunswick, and most of these likely come from the US by migratory birds or terrestrial hosts in the west of the province [48], and there is no reason to believe that the woodland types occurring in New Brunswick are intrinsically inhospitable to I. scapularis. Indeed, populations have established in some locations in New Brunswick (a location close to Saint-John and on Grand Manan Island), and I. scapularis has been shown to be able to establish in a wide range of coniferous, deciduous and mixed forest woodland types elsewhere in the United States and Canada [21, 25, 27, 49, 50]. Two factors may have been limiting however. First, the temperature conditions at the majority of sites were below, and the rest close to, the lower limits for I. scapularis population persistence obtained in previous studies [21] (Fig 3). There were stark differences in the proportions of surveillance sites positive for I. scapularis between Québec and Nova Scotia combined, and New Brunswick. These differences were associated with similarly stark differences between these regions in the numbers of recent years in which DD > 0°C were above the predicted threshold for I. scapularis population survival. Second, over most of the province, the estimated density of white-tailed deer was below the lower (7/km²) limit for I. scapularis population survival deduced in studies in neighbouring Maine [29] (Fig 4). Either or both of these factors may be limiting I. scapularis over much of New Brunswick. However, there are locations in southern New Brunswick, not investigated in this study, where temperature conditions have become favorable for I. scapularis, particularly the Saint John River system, South-West corner adjacent to Maine, the Moncton area and locations on the coast opposite to Prince Edward Island (Fig 3). These regions could possess microclimates where temperature conditions are suitable for I. scapularis establishment. Furthermore, there may be locations with microclimates too small to be detected by MODIS despite its high resolution. Unpublished road kill data also suggest that in localized areas, particularly in peri-urban areas, deer densities may exceed 7/km² in the south of the province where temperature conditions are also more likely to be suitable for I. scapularis. Therefore it may be prudent to continue to undertake surveillance to detect emerging I. scapularis populations and Lyme disease risk in these regions.

Download:

Fig 4. White-tailed deer densities.

Estimated densities of white-tailed deer/km² are shown for each wildlife management zone in New Brunswick for 2014. The map was created in ArcGIS Version 10.2 (ESRI. Redlands, CA).

https://doi.org/10.1371/journal.pone.0131282.g004

In contrast to I. scapularis, H. leporispalustris ticks were found on many (> 25%) sites in New Brunswick and were abundant on most sites where they were found. Haemaphysalis leporispalustris is a vector of Francisella tularensis, the bacterial agent of tularaemia and this pathogen has been isolated from this tick species at sites elsewhere in Canada [51, 52] and from snowshoe hares in New Brunswick [53]. It is primarily a parasite of rabbits and hares although larvae and nymphs will also readily feed on birds [54] and it occasionally bites humans [55, 56]. The risk of it directly transmitting tularaemia to humans in New Brunswick is likely very low. However, it likely plays a role in F. tularensis transmission amongst wildlife reservoirs, thus indirectly contributing to risk to hunters who may acquire F. tularensis infection directly from infected wild animals [57]. The finding of H. leporispalustris on many sites served to validate the capacity of our field technique to detect questing exophilic ticks (and that negative results for I. scapularis were not false negative results) but also suggested that I. scapularis and H. leporispalustris may have very different ecological niches beyond simply differences in host species.

The results from the logistic regression modelling suggested that there was greater likelihood of finding H. leporispalustris on sites with high (> 2739) or medium (2653 to 2739) DD > 0°C compared to sites with low (< 2653.5) DD > 0°C. This is consistent with findings in California, where the presence of H. leporispalustris was correlated with the mean annual DD > 10°C [17]. However in contrast to I. scapularis, for which the ROC analysis of surveillance data supported an approximate minimum DD > 0°C of 2800 for persistence of populations, H. leporispalustris were found on sites with DD > 0°C as low as 2461 and the mean value of DD > 0°C of H. leporispalustris-positive sites was < 2800. Therefore, H. leporispalustris populations appear capable of surviving in a colder climate than I. scapularis. Higher precipitation (> 1243 mm) was associated with a greater likelihood of collecting H. leporispalustris compared to low precipitations (< 1181 mm) suggesting that a more humid environment may increase survival rates, and/or activity and detectability by drag sampling, of H. leporispalustris. In general more humid environments favour Ixodid tick survival and activity [58, 59]. Soil containing a medium proportion of clay (20% to 49%) was more associated with H. leporispalustris than soils with a high proportion of clay (>49%). The amount of clay in the soil may have an indirect relationship with the presence of H. leporispalustris by affecting other environmental qualities such as the litter layer and understorey plant communities that impact tick survival. High moisture levels in clay soils may promote growth of micro-organisms directly deleterious to tick survival [60]. Ixodes scapularis may, however, be more resistant than H. leporispalustris to clay soils [24]. The presence of H. leporispalustris was more likely on sites at low (< 66 m) and high (> 145 m) elevations compared to sites at intermediate elevations (66–145 m). Why this is the case is unclear when the model accounts for climate and associations with woodland and soil types and levels of moisture. However we speculate that this reflects effects of climatic conditions, vegetation composition or host density at a fine geographic scale. We accounted for the seasonality of the activity of H. leporispalustris and the observed pattern of activity (Fig 2) was consistent with other studies in which peak infestations of hosts by immature H. leporispalustris occurs in late summer [61, 62]. It has been suggested that adult H. leporispalustris feed on hosts in spring and the eggs they lay give rise to a peak of larvae in late summer while the spring peak may represent larvae that overwinter [61].

Our analysis of the spatial pattern of H. leporispalustris-positive sites revealed a significant spatial cluster in the south of the province but the occurrence of this cluster could be explained by the spatial pattern of temperature and rainfall conditions suitable for the tick. This idea was supported by the lack of spatial autocorrelation of H. leporispalustris-positive sites, i.e. sites were not significantly more likely to be H. leporispalustris-positive if they neighboured an H. leporispalustris-positive site. We interpret these findings as supportive of the idea that the spatial pattern of occurrence of H. leporispalustris in New Brunswick is due to the spatial pattern of an environment suitable for this tick, rather than providing evidence of recent spatial spread. Again this supports the idea that the climatological niche for H. leporispalustris is different to that of I. scapularis and perhaps has been less affected (at least in the geographic area under study here) to recent changes in climate. For I. scapularis, there has been evidence in previous studies for a spatial pattern of occurrence of I. scapularis associated with spread from one location to an adjacent location as well as effects of a warming climate [42, 63].

A single nymphal I. muris tick was collected; however I. muris ticks are more nidicoulous than I. scapularis and H. leporispalustris and rarely quest on vegetation [64]. That this tick was uncommonly found by drag sampling does not infer, therefore, that the tick is uncommon in New Brunswick. From 2007 to 2014, 66 submissions of I. muris were received by the authors as part of the passive tick surveillance in New Brunswick and 13 of these ticks were removed from humans. This verifies that I. muris will occasionally feed on humans and it is a competent, albeit inefficient, vector of B. burgdorferi [65] so cryptic transmission cycles associated with this tick, as can occur with other tick species (e.g. [31]), cannot be ruled out.

In conclusion, this study revealed that populations of I. scapularis ticks are currently uncommon in most of New Brunswick and this is most likely due to a combination of unsuitable or suboptimal conditions of temperature and abundance of key hosts (white tailed deer). Nevertheless, I. scapularis were found and our study suggests the occurrence of focal areas of possibly suitable environment and ongoing field surveillance targeted to sentinel at-risk locations, such as peri-urban and suburban areas of southern New Brunswick, may be prudent. By evaluating the wider occurrence of I. scapularis in neighbouring Nova Scotia and Québec, the study provided empirical support for model-derived estimates of approximately 2800 DD > 0°C as being minimum temperature conditions required for this tick, thus further supporting projected distributions of the tick with climate change [42]. The study also revealed that the tick H. leporispalustris was widespread in southern New Brunswick and in contrast to I. scapularis, its populations are capable of surviving temperature conditions less than 2500 DD > 0°C and show little evidence of recent spread in New Brunswick. Therefore these two Ixodid tick species, which are vectors of several important zoonotic diseases, have different ecological niches underlining the need to assess the occurrence of vectors and risk from vector-borne zoonoses separately according to their individual ecologies.

Supporting Information

S1 File. Surveillance data collected or used in the study.

These data include locations of study sites and results of surveillance (presence/absence of tick species) as well as explanatory variables used in the final multivariable logistic regression model for predicting occurrence of H. leporispalustris.

https://doi.org/10.1371/journal.pone.0131282.s001

(XLSX)

Acknowledgments

We thank the New Brunswick Department of Health and Department of Aquaculture, Agriculture & Food for their support in conducting this study.

Author Contributions

Conceived and designed the experiments: NHO LRL YP JG JB. Performed the experiments: JE NHO JG LRL. Analyzed the data: VGR NHO JA. Contributed reagents/materials/analysis tools: JG LRL JK AC. Wrote the paper: VGR NHO JA JB JG JK AC YP LRL JE.

References

1. Sonenshine DE, Mather TN. Ecological dynamics of tick-borne zoonoses. New York: Oxford University Press; 1994.
2. Dantas-Torres F, Chomel BB, Otranto D. Ticks and tick-borne diseases: a One Health perspective. Trends Parasitol. 2012;28(10): 437–46. pmid:22902521
- View Article
- PubMed/NCBI
- Google Scholar
3. Parola P, Raoult D. Tick-borne bacterial diseases emerging in Europe. Clin Microbiol Infect. 2001;7(2): 80–3. pmid:11298147
- View Article
- PubMed/NCBI
- Google Scholar
4. Stromdahl EY, Hickling GJ. Beyond Lyme: Aetiology of tick‐borne human diseases with emphasis on the South‐Eastern United States. Zoonoses Public Health. 2012;59: 48–64. pmid:22958250
- View Article
- PubMed/NCBI
- Google Scholar
5. Kalluri S, Gilruth P, Rogers D, Szczur M. Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: a review. PLoS Path. 2007;3(10):e116.
- View Article
- Google Scholar
6. Bacon RM, Kugeler KJ, Mead PS; Centers for Disease Control and Prevention (CDC). Surveillance for Lyme Disease—United States, 1992–2006. Morb Mortal Weekly Rep. 2008;57(10): 1–9.
- View Article
- Google Scholar
7. Kurtenbach K, Hanincová K, Tsao JI, Margos G, Fish D, Ogden NH. Fundamental processes in the evolutionary ecology of Lyme borreliosis. Nat Rev Microbiol. 2006;4(9): 660–9. pmid:16894341
- View Article
- PubMed/NCBI
- Google Scholar
8. Lindgren E, Jaenson TG, Organization WH. Lyme borreliosis in Europe: influences of climate and climate change, epidemiology, ecology and adaptation measures. WHO Regional Office for Europe Copenhagen; 2006.
9. Burgdorfer W, Barbour AG, Hayes SF, Benach JL, Grunwaldt E, Davis JP. Lyme disease-a tick-borne spirochetosis? Science. 1982;216(4552): 1317–9. pmid:7043737
- View Article
- PubMed/NCBI
- Google Scholar
10. Ogden NH, Lindsay LR, Morshed M, Sockett PN, Artsob H. The emergence of Lyme disease in Canada. Can Med Assoc J. 2009;180(5): 1221–4.
- View Article
- Google Scholar
11. Public Health Agency of Canada. Lyme disease and other tick-borne diseases: Information for healthcare professionals. 2015. Available: http://www.phac-aspc.gc.ca/id-mi/tickinfo-eng.php.
12. Ogden NH, Lindsay LR, Hanincová K, Barker IK, Bigras-Poulin M, Charron DF, et al. Role of migratory birds in introduction and range expansion of Ixodes scapularis ticks and of Borrelia burgdorferi and Anaplasma phagocytophilum in Canada. Appl Environ Microbiol. 2008;74(6): 1780–90. pmid:18245258
- View Article
- PubMed/NCBI
- Google Scholar
13. Madhav NK, Brownstein JS, Tsao JI, Fish D. A dispersal model for the range expansion of blacklegged tick (Acari: Ixodidae). J Med Entomol. 2004;41: 842–52. pmid:15535611
- View Article
- PubMed/NCBI
- Google Scholar
14. Ogden NH, Lindsay LR, Leighton PA. Predicting the rate of invasion of the agent of Lyme disease Borrelia burgdorferi. J Appl Ecol. 2013;50: 510–8.
- View Article
- Google Scholar
15. Estrada-Peña A. Forecasting habitat suitability for ticks and prevention of tick-borne diseases. Vet Parasitol. 2001;98: 111–32. pmid:11516582
- View Article
- PubMed/NCBI
- Google Scholar
16. Schulze TL, Jordan RA, Hung RW. Effects of microscale habitat physiognomy on the focal distribution of Ixodes scapularis and Amblyomma americanum (Acari: Ixodidae) nymphs. Environ Entomol. 2002;31(6): 1085–90.
- View Article
- Google Scholar
17. Eisen L, Eisen RJ, Lane RS. Geographical distribution patterns and habitat suitability models for presence of host-seeking Ixodid ticks in dense woodlands of Mendocino county, California. J Med Entomol. 2006;43(2): 415–27. pmid:16619628
- View Article
- PubMed/NCBI
- Google Scholar
18. Lindström A, Jaenson TG. Distribution of the common tick, Ixodes ricinus (Acari: Ixodidae), in different vegetation types in southern Sweden. J Med Entomol. 2003;40(4): 375–8. pmid:14680099
- View Article
- PubMed/NCBI
- Google Scholar
19. Dobson ADM, Randolph SE. Modelling the effects of recent changes in climate, host density and acaricide treatments on population dynamics of Ixodes ricinus in the UK. J Appl Ecol. 2011;48: 1029–37.
- View Article
- Google Scholar
20. Ogden NH, Lindsay LR, Beauchamp G, Charron D, Maarouf A, O'Callaghan CJ, et al. Investigation of relationships between temperature and developmental rates of tick Ixodes scapularis (Acari: Ixodidae) in the laboratory and field. J Med Entomol. 2004;41(4): 622–33. pmid:15311453
- View Article
- PubMed/NCBI
- Google Scholar
21. Ogden NH, Bigras-Poulin M, O'callaghan CJ, Barker IK, Lindsay LR, Maarouf A, et al. A dynamic population model to investigate effects of climate on geographic range and seasonality of the tick Ixodes scapularis. Int J Parasitol. 2005;35(4): 375–89. pmid:15777914
- View Article
- PubMed/NCBI
- Google Scholar
22. Ogden NH, Maarouf A, Barker IK, Bigras-Poulin M, Lindsay LR, Morshed MG, et al. Climate change and the potential for range expansion of the Lyme disease vector Ixodes scapularis in Canada. Int J Parasitol. 2006;36(1): 63–70. pmid:16229849
- View Article
- PubMed/NCBI
- Google Scholar
23. Ogden NH, St-Onge L, Barker IK, Brazeau S, Bigras-Poulin M, Charron DF, et al. Risk maps for range expansion of the Lyme disease vector, Ixodes scapularis, in Canada now and with climate change. Int J Health Geogr. 2008;7: 24. pmid:18498647
- View Article
- PubMed/NCBI
- Google Scholar
24. Ogden NH, Barker IK, Beauchamp G, Brazeau S, Charron DF, Maarouf A, et al. Investigation of ground level and remote-sensed data for habitat classification and prediction of survival of Ixodes scapularis in habitats of southeastern Canada. J Med Entomol. 2006;43: 403–14. pmid:16619627
- View Article
- PubMed/NCBI
- Google Scholar
25. Lindsay LR, Barker IK, Surgeoner GA, Mcewen SA, Gillespie TJ, Addison EM. Survival and development of the different life stages of Ixodes scapularis (Acari: Ixodidae) held within four habitats on Long Point, Ontario, Canada. J Med Entomol. 1998;35(3): 189–99. pmid:9615533
- View Article
- PubMed/NCBI
- Google Scholar
26. Lindsay LR. Factors limiting the density of the black-legged tick, Ixodes scapularis, in Ontario, Canada Ph. D Thesis. University of Guelph. 1995.
27. Guerra M, Walker E, Jones C, Paskewitz S, Cortinas MR, Stancil A, et al. Predicting the risk of Lyme disease: habitat suitability for Ixodes scapularis in the north central United States. Emerg Infect Dis. 2002;8(3): 289–97. pmid:11927027
- View Article
- PubMed/NCBI
- Google Scholar
28. Rand PW, Lubelczyk C, Holman MS, Lacombe EH, Smith RP. Abundance of Ixodes scapularis (Acari: Ixodidae) after the complete removal of deer from an isolated offshore island, endemic for Lyme disease. J Med Entomol. 2004;41(4): 779–84. pmid:15311475
- View Article
- PubMed/NCBI
- Google Scholar
29. Rand PW, Lubelczyk C, Lavigne GR, Elias S, Holman MS, Lacombe EH, et al. Deer density and the abundance of Ixodes scapularis (Acari: Ixodidae). J Med Entomol. 2003;40(2): 179–84. pmid:12693846
- View Article
- PubMed/NCBI
- Google Scholar
30. Lindsay R, Artsob H, Barker I. Distribution of Ixodes pacificus and Ixodes scapularis re concurrent babesiosis and Lyme disease. Can Commun Dis Rep. 1998;24(15): 121–2. pmid:9704540
- View Article
- PubMed/NCBI
- Google Scholar
31. Hamer SA, Hickling GJ, Sidge JL, Rosen ME, Walker ED, Tsao JI. Diverse Borrelia burgdorferi strains in a bird-tick cryptic cycle. Appl Environ Microbiol. 2011;77(6): 1999–2007. pmid:21257811
- View Article
- PubMed/NCBI
- Google Scholar
32. Ogden NH, Artsob H, Margos G, Tsao J. Other tick-borne bacterial diseases (including Lyme disease, relapsing fever and tularemia). In: Daniel E, Sonenshine E, Roe RM, editors. The Biology of Ticks: Oxford University Press; 2014. pp 278–312
33. New Brunswick Department of Natural Resources. Our Landscape Heritage: The story of ecological land classification in New Brunswick. Fredericton, New Brunswick, Canada 2007. Available: http://www2.gnb.ca/content/gnb/en/departments/natural_resources/ForestsCrownLands/content/ProtectedNaturalAreas/OurLandscapeHeritage.html.
34. Dibernardo A, Cote T, Ogden NH, Lindsay LR. The prevalence of Borrelia miyamotoi infection, and co-infections with other Borrelia spp. in Ixodes scapularis ticks collected in Canada. Parasit Vectors. 2014;7: 183. pmid:24731287
- View Article
- PubMed/NCBI
- Google Scholar
35. Lee HT, Bakowsky WD, Riley J, Bowles J, Puddister M, Uhlig P, et al. Ecological land classification for southern Ontario: first approximation and its application: Ontario Ministry of Natural Resources, Southcentral Science Section, Science Development and Transfer Branch. SCSS Field Guide FG-02; 1998.
36. Bouchard C, Beauchamp G, Leighton PA, Lindsay R, Bélanger D, Ogden NH. Does high biodiversity reduce the risk of Lyme disease invasion. Parasit Vectors. 2013;6(1): 195.
- View Article
- Google Scholar
37. Wu X, Duvvuri VR, Lou Y, Ogden NH, Pelcat Y, Wu J. Developing a temperature-driven map of the basic reproductive number of the emerging tick vector of Lyme disease Ixodes scapularis in Canada. J Theor Biol. 2013;319: 50–61. pmid:23206385
- View Article
- PubMed/NCBI
- Google Scholar
38. McKenney DW, Hutchinson MF, Papadopol P, Lawrence K, Pedlar J, Campbell K, et al. Customized spatial climate models for North America. Bull Amer Meteor Soc. 2011;92(12): 1611–22.
- View Article
- Google Scholar
39. Derr RE, editor. Performing exact logistic regression with the SAS system. Proc Twenty-Fifth Annual SAS® Users Group International Conference; 2000.
40. Dohoo IR, Martin W, Stryhn HE. Veterinary epidemiologic research. McPike SM, editor. VER Inc, Charlottetown, Prince Edward Island, Canada; 2003. 706 p.
41. Ogden NH, Koffi JK, Pelcat Y, Lindsay LR. Environmental risk from Lyme disease in central and eastern Canada: a summary of recent surveillance information. Can Commun Dis Rep. 2014;40: 74–82.
- View Article
- Google Scholar
42. Ogden NH, Radojevic M, Wu X, Duvvuri VR, Leighton PA, Wu J. Estimated effects of projected climate change on the basic reproductive number of the Lyme disease vector Ixodes scapularis. Environ Health Perspect. 2014;122(6): 631–8. pmid:24627295
- View Article
- PubMed/NCBI
- Google Scholar
43. Kulldorff M. A spatial scan statistic. Comm Statist Theory Meth. 1997;26(6):1481–96.
- View Article
- Google Scholar
44. Ripley BD. The second-order analysis of stationary point processes. J Appl Probab. 1976;13(2): 255–66.
- View Article
- Google Scholar
45. R Development Core Team. R: A language and environment for statistical computing. Vienna, AustriaR version 3.1.2. 2014. Available: http://www.R-project.org.
46. Patrican LA. Absence of Lyme disease spirochetes in larval progeny of naturally infected Ixodes scapularis (Acari: Ixodidae) fed on dogs. J Med Entomol. 1997;34(1): 52–5. pmid:9086711
- View Article
- PubMed/NCBI
- Google Scholar
47. Waller LA, Gotway CA. Applied spatial statistics for public health data. statistics Wsipa, editor. United States of America: John Wiley & sons; 2004.
48. Ogden NH, Koffi JK, Lindsay LR. Assessment of a screening test to identify Lyme disease risk. Can Commun Dis Rep. 2014;40: 83–7.
- View Article
- Google Scholar
49. Ginsberg HS, Zhioua E. Nymphal survival and habitat distribution of Ixodes scapularis and Amblyomma americanum ticks (Acari: Ixodidae) on Fire Island, New York, USA. Exp Appl Acarol. 1996;20(9): 533–44.
- View Article
- Google Scholar
50. Ginsberg HS, Zhioua E, Mitra S, Fischer J, Buckley PA, Verret F, et al. Woodland type and spatial distribution of nymphal Ixodes scapularis (Acari: Ixodidae). Environ Entomol. 2004;33(5): 1266–73.
- View Article
- Google Scholar
51. Philip CB, Parker R. Occurrence of tularaemia in the rabbit tick (Haemaphysalis leporispalustris) in Alaska. Public Health Reports (1896–1970). 1938: 574–5.
52. Ditchfield J, Meads EB, Julian RJ. Tularemia of Muskrats in Eastern Ontario. Can J Public Health. 1960;51: 474–8. pmid:13723090
- View Article
- PubMed/NCBI
- Google Scholar
53. Wobeser G, Campbell GD, Dallaire A, McBurney S. Tularemia, plague, yersiniosis, and Tyzzer’s disease in wild rodents and lagomorphs in Canada: A review. Can Vet J. 2009;50(12): 1251. pmid:20190973
- View Article
- PubMed/NCBI
- Google Scholar
54. Bishopp FC, Trembley HL. Distribution and Hosts of Certain North American Ticks. J Parasitol. 1945;31: 1–54.
- View Article
- Google Scholar
55. Brown JH. The rabbit tick, Haemaphysalis leporis-palustris Pack., as an ectoparasite of man. Can Entomol. 1945;77: 176.
- View Article
- Google Scholar
56. Harrison BA, Engber BR, Apperson CS. Ticks (Acari: Ixodida) uncommonly found biting humans in North Carolina. J Vector Ecol. 1997;22(1): 6–12. pmid:9221733
- View Article
- PubMed/NCBI
- Google Scholar
57. Black DM, Thomson J. Tularaemia in British Columbia. Can Med Assoc J. 1958;78(1): 16. pmid:13489618
- View Article
- PubMed/NCBI
- Google Scholar
58. McCabe GJ, Bunnell JE. Precipitation and the occurrence of Lyme disease in the northeastern United States. Vector-Borne Zoonotic Dis. 2004;4(2): 143–8. pmid:15228815
- View Article
- PubMed/NCBI
- Google Scholar
59. Furlanello C, Neteler M, Merler S, Menegon S, Fontanari S, Donini A, et al., editors. GIS and the random forest predictor: Integration in R for tick-borne disease risk assessment. Proceedings of DSC; 2003: Citeseer.
60. Yoder JA, Benoit JB, Zettler LW. Moisture requirements of a soil imperfect fungus, Scopulariopsis brevicaulis Bainier, in relation to its tick host. Int J Acarol. 2003;29(3): 271–7.
- View Article
- Google Scholar
61. Campbell A, Ward RM, Garvie MB. Seasonal activity and frequency distributions of ticks (Acari: Ixodidae) infesting snowshoe hares in Nova Scotia, Canada. J Med Entomol. 1980;17(1): 22–9.
- View Article
- Google Scholar
62. Kollars TM, Oliver JH. Host associations and seasonal occurrence of Haemaphysalis leporispalustris, Ixodes brunneus, I. cookei, I. dentatus, and I. texanus (Acari: Ixodidae) in southeastern Missouri. J Med Entomol. 2003;40(1): 103–7. pmid:12597662
- View Article
- PubMed/NCBI
- Google Scholar
63. Leighton PA, Koffi JK, Pelcat Y, Lindsay LR, Ogden NH. Predicting the speed of tick invasion: an empirical model of range expansion for the Lyme disease vector Ixodes scapularis in Canada. J Appl Ecol. 2012;49: 457–64.
- View Article
- Google Scholar
64. Goethert HK, Lubelcyzk C, LaCombe E, Holman M, Rand P, Smith RP Jr, Telford SR 3rd. Enzootic Babesia microti in Maine. J Parasitol. 2003;89(5): 1069–71. pmid:14627162
- View Article
- PubMed/NCBI
- Google Scholar
65. Dolan MC, Lacombe EH, Piesman J. Vector Competence of Ixodes muris (Acari: Ixodidae) for Borrelia burgdorferi. J Med Entomol. 2000;37(5): 766–8. pmid:11004792
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Sonenshine DE, Mather TN. Ecological dynamics of tick-borne zoonoses. New York: Oxford University Press; 1994.

[ref2] 2. Dantas-Torres F, Chomel BB, Otranto D. Ticks and tick-borne diseases: a One Health perspective. Trends Parasitol. 2012;28(10): 437–46. pmid:22902521
View Article
PubMed/NCBI
Google Scholar

[3] View Article

[4] PubMed/NCBI

[5] Google Scholar

[ref3] 3. Parola P, Raoult D. Tick-borne bacterial diseases emerging in Europe. Clin Microbiol Infect. 2001;7(2): 80–3. pmid:11298147
View Article
PubMed/NCBI
Google Scholar

[7] View Article

[8] PubMed/NCBI

[9] Google Scholar

[ref4] 4. Stromdahl EY, Hickling GJ. Beyond Lyme: Aetiology of tick‐borne human diseases with emphasis on the South‐Eastern United States. Zoonoses Public Health. 2012;59: 48–64. pmid:22958250
View Article
PubMed/NCBI
Google Scholar

[11] View Article

[12] PubMed/NCBI

[13] Google Scholar

[ref5] 5. Kalluri S, Gilruth P, Rogers D, Szczur M. Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: a review. PLoS Path. 2007;3(10):e116.
View Article
Google Scholar

[15] View Article

[16] Google Scholar

[ref6] 6. Bacon RM, Kugeler KJ, Mead PS; Centers for Disease Control and Prevention (CDC). Surveillance for Lyme Disease—United States, 1992–2006. Morb Mortal Weekly Rep. 2008;57(10): 1–9.
View Article
Google Scholar

[18] View Article

[19] Google Scholar

[ref7] 7. Kurtenbach K, Hanincová K, Tsao JI, Margos G, Fish D, Ogden NH. Fundamental processes in the evolutionary ecology of Lyme borreliosis. Nat Rev Microbiol. 2006;4(9): 660–9. pmid:16894341
View Article
PubMed/NCBI
Google Scholar

[21] View Article

[22] PubMed/NCBI

[23] Google Scholar

[ref8] 8. Lindgren E, Jaenson TG, Organization WH. Lyme borreliosis in Europe: influences of climate and climate change, epidemiology, ecology and adaptation measures. WHO Regional Office for Europe Copenhagen; 2006.

[ref9] 9. Burgdorfer W, Barbour AG, Hayes SF, Benach JL, Grunwaldt E, Davis JP. Lyme disease-a tick-borne spirochetosis? Science. 1982;216(4552): 1317–9. pmid:7043737
View Article
PubMed/NCBI
Google Scholar

[26] View Article

[27] PubMed/NCBI

[28] Google Scholar

[ref10] 10. Ogden NH, Lindsay LR, Morshed M, Sockett PN, Artsob H. The emergence of Lyme disease in Canada. Can Med Assoc J. 2009;180(5): 1221–4.
View Article
Google Scholar

[30] View Article

[31] Google Scholar

[ref11] 11. Public Health Agency of Canada. Lyme disease and other tick-borne diseases: Information for healthcare professionals. 2015. Available: http://www.phac-aspc.gc.ca/id-mi/tickinfo-eng.php.

[ref12] 12. Ogden NH, Lindsay LR, Hanincová K, Barker IK, Bigras-Poulin M, Charron DF, et al. Role of migratory birds in introduction and range expansion of Ixodes scapularis ticks and of Borrelia burgdorferi and Anaplasma phagocytophilum in Canada. Appl Environ Microbiol. 2008;74(6): 1780–90. pmid:18245258
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref13] 13. Madhav NK, Brownstein JS, Tsao JI, Fish D. A dispersal model for the range expansion of blacklegged tick (Acari: Ixodidae). J Med Entomol. 2004;41: 842–52. pmid:15535611
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref14] 14. Ogden NH, Lindsay LR, Leighton PA. Predicting the rate of invasion of the agent of Lyme disease Borrelia burgdorferi. J Appl Ecol. 2013;50: 510–8.
View Article
Google Scholar

[42] View Article

[43] Google Scholar

[ref15] 15. Estrada-Peña A. Forecasting habitat suitability for ticks and prevention of tick-borne diseases. Vet Parasitol. 2001;98: 111–32. pmid:11516582
View Article
PubMed/NCBI
Google Scholar

[45] View Article

[46] PubMed/NCBI

[47] Google Scholar

[ref16] 16. Schulze TL, Jordan RA, Hung RW. Effects of microscale habitat physiognomy on the focal distribution of Ixodes scapularis and Amblyomma americanum (Acari: Ixodidae) nymphs. Environ Entomol. 2002;31(6): 1085–90.
View Article
Google Scholar

[49] View Article

[50] Google Scholar

[ref17] 17. Eisen L, Eisen RJ, Lane RS. Geographical distribution patterns and habitat suitability models for presence of host-seeking Ixodid ticks in dense woodlands of Mendocino county, California. J Med Entomol. 2006;43(2): 415–27. pmid:16619628
View Article
PubMed/NCBI
Google Scholar

[52] View Article

[53] PubMed/NCBI

[54] Google Scholar

[ref18] 18. Lindström A, Jaenson TG. Distribution of the common tick, Ixodes ricinus (Acari: Ixodidae), in different vegetation types in southern Sweden. J Med Entomol. 2003;40(4): 375–8. pmid:14680099
View Article
PubMed/NCBI
Google Scholar

[56] View Article

[57] PubMed/NCBI

[58] Google Scholar

[ref19] 19. Dobson ADM, Randolph SE. Modelling the effects of recent changes in climate, host density and acaricide treatments on population dynamics of Ixodes ricinus in the UK. J Appl Ecol. 2011;48: 1029–37.
View Article
Google Scholar

[60] View Article

[61] Google Scholar

[ref20] 20. Ogden NH, Lindsay LR, Beauchamp G, Charron D, Maarouf A, O'Callaghan CJ, et al. Investigation of relationships between temperature and developmental rates of tick Ixodes scapularis (Acari: Ixodidae) in the laboratory and field. J Med Entomol. 2004;41(4): 622–33. pmid:15311453
View Article
PubMed/NCBI
Google Scholar

[63] View Article

[64] PubMed/NCBI

[65] Google Scholar

[ref21] 21. Ogden NH, Bigras-Poulin M, O'callaghan CJ, Barker IK, Lindsay LR, Maarouf A, et al. A dynamic population model to investigate effects of climate on geographic range and seasonality of the tick Ixodes scapularis. Int J Parasitol. 2005;35(4): 375–89. pmid:15777914
View Article
PubMed/NCBI
Google Scholar

[67] View Article

[68] PubMed/NCBI

[69] Google Scholar

[ref22] 22. Ogden NH, Maarouf A, Barker IK, Bigras-Poulin M, Lindsay LR, Morshed MG, et al. Climate change and the potential for range expansion of the Lyme disease vector Ixodes scapularis in Canada. Int J Parasitol. 2006;36(1): 63–70. pmid:16229849
View Article
PubMed/NCBI
Google Scholar

[71] View Article

[72] PubMed/NCBI

[73] Google Scholar

[ref23] 23. Ogden NH, St-Onge L, Barker IK, Brazeau S, Bigras-Poulin M, Charron DF, et al. Risk maps for range expansion of the Lyme disease vector, Ixodes scapularis, in Canada now and with climate change. Int J Health Geogr. 2008;7: 24. pmid:18498647
View Article
PubMed/NCBI
Google Scholar

[75] View Article

[76] PubMed/NCBI

[77] Google Scholar

[ref24] 24. Ogden NH, Barker IK, Beauchamp G, Brazeau S, Charron DF, Maarouf A, et al. Investigation of ground level and remote-sensed data for habitat classification and prediction of survival of Ixodes scapularis in habitats of southeastern Canada. J Med Entomol. 2006;43: 403–14. pmid:16619627
View Article
PubMed/NCBI
Google Scholar

[79] View Article

[80] PubMed/NCBI

[81] Google Scholar

[ref25] 25. Lindsay LR, Barker IK, Surgeoner GA, Mcewen SA, Gillespie TJ, Addison EM. Survival and development of the different life stages of Ixodes scapularis (Acari: Ixodidae) held within four habitats on Long Point, Ontario, Canada. J Med Entomol. 1998;35(3): 189–99. pmid:9615533
View Article
PubMed/NCBI
Google Scholar

[83] View Article

[84] PubMed/NCBI

[85] Google Scholar

[ref26] 26. Lindsay LR. Factors limiting the density of the black-legged tick, Ixodes scapularis, in Ontario, Canada Ph. D Thesis. University of Guelph. 1995.

[ref27] 27. Guerra M, Walker E, Jones C, Paskewitz S, Cortinas MR, Stancil A, et al. Predicting the risk of Lyme disease: habitat suitability for Ixodes scapularis in the north central United States. Emerg Infect Dis. 2002;8(3): 289–97. pmid:11927027
View Article
PubMed/NCBI
Google Scholar

[88] View Article

[89] PubMed/NCBI

[90] Google Scholar

[ref28] 28. Rand PW, Lubelczyk C, Holman MS, Lacombe EH, Smith RP. Abundance of Ixodes scapularis (Acari: Ixodidae) after the complete removal of deer from an isolated offshore island, endemic for Lyme disease. J Med Entomol. 2004;41(4): 779–84. pmid:15311475
View Article
PubMed/NCBI
Google Scholar

[92] View Article

[93] PubMed/NCBI

[94] Google Scholar

[ref29] 29. Rand PW, Lubelczyk C, Lavigne GR, Elias S, Holman MS, Lacombe EH, et al. Deer density and the abundance of Ixodes scapularis (Acari: Ixodidae). J Med Entomol. 2003;40(2): 179–84. pmid:12693846
View Article
PubMed/NCBI
Google Scholar

[96] View Article

[97] PubMed/NCBI

[98] Google Scholar

[ref30] 30. Lindsay R, Artsob H, Barker I. Distribution of Ixodes pacificus and Ixodes scapularis re concurrent babesiosis and Lyme disease. Can Commun Dis Rep. 1998;24(15): 121–2. pmid:9704540
View Article
PubMed/NCBI
Google Scholar

[100] View Article

[101] PubMed/NCBI

[102] Google Scholar

[ref31] 31. Hamer SA, Hickling GJ, Sidge JL, Rosen ME, Walker ED, Tsao JI. Diverse Borrelia burgdorferi strains in a bird-tick cryptic cycle. Appl Environ Microbiol. 2011;77(6): 1999–2007. pmid:21257811
View Article
PubMed/NCBI
Google Scholar

[104] View Article

[105] PubMed/NCBI

[106] Google Scholar

[ref32] 32. Ogden NH, Artsob H, Margos G, Tsao J. Other tick-borne bacterial diseases (including Lyme disease, relapsing fever and tularemia). In: Daniel E, Sonenshine E, Roe RM, editors. The Biology of Ticks: Oxford University Press; 2014. pp 278–312

[ref33] 33. New Brunswick Department of Natural Resources. Our Landscape Heritage: The story of ecological land classification in New Brunswick. Fredericton, New Brunswick, Canada 2007. Available: http://www2.gnb.ca/content/gnb/en/departments/natural_resources/ForestsCrownLands/content/ProtectedNaturalAreas/OurLandscapeHeritage.html.

[ref34] 34. Dibernardo A, Cote T, Ogden NH, Lindsay LR. The prevalence of Borrelia miyamotoi infection, and co-infections with other Borrelia spp. in Ixodes scapularis ticks collected in Canada. Parasit Vectors. 2014;7: 183. pmid:24731287
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref35] 35. Lee HT, Bakowsky WD, Riley J, Bowles J, Puddister M, Uhlig P, et al. Ecological land classification for southern Ontario: first approximation and its application: Ontario Ministry of Natural Resources, Southcentral Science Section, Science Development and Transfer Branch. SCSS Field Guide FG-02; 1998.

[ref36] 36. Bouchard C, Beauchamp G, Leighton PA, Lindsay R, Bélanger D, Ogden NH. Does high biodiversity reduce the risk of Lyme disease invasion. Parasit Vectors. 2013;6(1): 195.
View Article
Google Scholar

[115] View Article

[116] Google Scholar

[ref37] 37. Wu X, Duvvuri VR, Lou Y, Ogden NH, Pelcat Y, Wu J. Developing a temperature-driven map of the basic reproductive number of the emerging tick vector of Lyme disease Ixodes scapularis in Canada. J Theor Biol. 2013;319: 50–61. pmid:23206385
View Article
PubMed/NCBI
Google Scholar

[118] View Article

[119] PubMed/NCBI

[120] Google Scholar

[ref38] 38. McKenney DW, Hutchinson MF, Papadopol P, Lawrence K, Pedlar J, Campbell K, et al. Customized spatial climate models for North America. Bull Amer Meteor Soc. 2011;92(12): 1611–22.
View Article
Google Scholar

[122] View Article

[123] Google Scholar

[ref39] 39. Derr RE, editor. Performing exact logistic regression with the SAS system. Proc Twenty-Fifth Annual SAS® Users Group International Conference; 2000.

[ref40] 40. Dohoo IR, Martin W, Stryhn HE. Veterinary epidemiologic research. McPike SM, editor. VER Inc, Charlottetown, Prince Edward Island, Canada; 2003. 706 p.

[ref41] 41. Ogden NH, Koffi JK, Pelcat Y, Lindsay LR. Environmental risk from Lyme disease in central and eastern Canada: a summary of recent surveillance information. Can Commun Dis Rep. 2014;40: 74–82.
View Article
Google Scholar

[127] View Article

[128] Google Scholar

[ref42] 42. Ogden NH, Radojevic M, Wu X, Duvvuri VR, Leighton PA, Wu J. Estimated effects of projected climate change on the basic reproductive number of the Lyme disease vector Ixodes scapularis. Environ Health Perspect. 2014;122(6): 631–8. pmid:24627295
View Article
PubMed/NCBI
Google Scholar

[130] View Article

[131] PubMed/NCBI

[132] Google Scholar

[ref43] 43. Kulldorff M. A spatial scan statistic. Comm Statist Theory Meth. 1997;26(6):1481–96.
View Article
Google Scholar

[134] View Article

[135] Google Scholar

[ref44] 44. Ripley BD. The second-order analysis of stationary point processes. J Appl Probab. 1976;13(2): 255–66.
View Article
Google Scholar

[137] View Article

[138] Google Scholar

[ref45] 45. R Development Core Team. R: A language and environment for statistical computing. Vienna, AustriaR version 3.1.2. 2014. Available: http://www.R-project.org.

[ref46] 46. Patrican LA. Absence of Lyme disease spirochetes in larval progeny of naturally infected Ixodes scapularis (Acari: Ixodidae) fed on dogs. J Med Entomol. 1997;34(1): 52–5. pmid:9086711
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref47] 47. Waller LA, Gotway CA. Applied spatial statistics for public health data. statistics Wsipa, editor. United States of America: John Wiley & sons; 2004.

[ref48] 48. Ogden NH, Koffi JK, Lindsay LR. Assessment of a screening test to identify Lyme disease risk. Can Commun Dis Rep. 2014;40: 83–7.
View Article
Google Scholar

[146] View Article

[147] Google Scholar

[ref49] 49. Ginsberg HS, Zhioua E. Nymphal survival and habitat distribution of Ixodes scapularis and Amblyomma americanum ticks (Acari: Ixodidae) on Fire Island, New York, USA. Exp Appl Acarol. 1996;20(9): 533–44.
View Article
Google Scholar

[149] View Article

[150] Google Scholar

[ref50] 50. Ginsberg HS, Zhioua E, Mitra S, Fischer J, Buckley PA, Verret F, et al. Woodland type and spatial distribution of nymphal Ixodes scapularis (Acari: Ixodidae). Environ Entomol. 2004;33(5): 1266–73.
View Article
Google Scholar

[152] View Article

[153] Google Scholar

[ref51] 51. Philip CB, Parker R. Occurrence of tularaemia in the rabbit tick (Haemaphysalis leporispalustris) in Alaska. Public Health Reports (1896–1970). 1938: 574–5.

[ref52] 52. Ditchfield J, Meads EB, Julian RJ. Tularemia of Muskrats in Eastern Ontario. Can J Public Health. 1960;51: 474–8. pmid:13723090
View Article
PubMed/NCBI
Google Scholar

[156] View Article

[157] PubMed/NCBI

[158] Google Scholar

[ref53] 53. Wobeser G, Campbell GD, Dallaire A, McBurney S. Tularemia, plague, yersiniosis, and Tyzzer’s disease in wild rodents and lagomorphs in Canada: A review. Can Vet J. 2009;50(12): 1251. pmid:20190973
View Article
PubMed/NCBI
Google Scholar

[160] View Article

[161] PubMed/NCBI

[162] Google Scholar

[ref54] 54. Bishopp FC, Trembley HL. Distribution and Hosts of Certain North American Ticks. J Parasitol. 1945;31: 1–54.
View Article
Google Scholar

[164] View Article

[165] Google Scholar

[ref55] 55. Brown JH. The rabbit tick, Haemaphysalis leporis-palustris Pack., as an ectoparasite of man. Can Entomol. 1945;77: 176.
View Article
Google Scholar

[167] View Article

[168] Google Scholar

[ref56] 56. Harrison BA, Engber BR, Apperson CS. Ticks (Acari: Ixodida) uncommonly found biting humans in North Carolina. J Vector Ecol. 1997;22(1): 6–12. pmid:9221733
View Article
PubMed/NCBI
Google Scholar

[170] View Article

[171] PubMed/NCBI

[172] Google Scholar

[ref57] 57. Black DM, Thomson J. Tularaemia in British Columbia. Can Med Assoc J. 1958;78(1): 16. pmid:13489618
View Article
PubMed/NCBI
Google Scholar

[174] View Article

[175] PubMed/NCBI

[176] Google Scholar

[ref58] 58. McCabe GJ, Bunnell JE. Precipitation and the occurrence of Lyme disease in the northeastern United States. Vector-Borne Zoonotic Dis. 2004;4(2): 143–8. pmid:15228815
View Article
PubMed/NCBI
Google Scholar

[178] View Article

[179] PubMed/NCBI

[180] Google Scholar

[ref59] 59. Furlanello C, Neteler M, Merler S, Menegon S, Fontanari S, Donini A, et al., editors. GIS and the random forest predictor: Integration in R for tick-borne disease risk assessment. Proceedings of DSC; 2003: Citeseer.

[ref60] 60. Yoder JA, Benoit JB, Zettler LW. Moisture requirements of a soil imperfect fungus, Scopulariopsis brevicaulis Bainier, in relation to its tick host. Int J Acarol. 2003;29(3): 271–7.
View Article
Google Scholar

[183] View Article

[184] Google Scholar

[ref61] 61. Campbell A, Ward RM, Garvie MB. Seasonal activity and frequency distributions of ticks (Acari: Ixodidae) infesting snowshoe hares in Nova Scotia, Canada. J Med Entomol. 1980;17(1): 22–9.
View Article
Google Scholar

[186] View Article

[187] Google Scholar

[ref62] 62. Kollars TM, Oliver JH. Host associations and seasonal occurrence of Haemaphysalis leporispalustris, Ixodes brunneus, I. cookei, I. dentatus, and I. texanus (Acari: Ixodidae) in southeastern Missouri. J Med Entomol. 2003;40(1): 103–7. pmid:12597662
View Article
PubMed/NCBI
Google Scholar

[189] View Article

[190] PubMed/NCBI

[191] Google Scholar

[ref63] 63. Leighton PA, Koffi JK, Pelcat Y, Lindsay LR, Ogden NH. Predicting the speed of tick invasion: an empirical model of range expansion for the Lyme disease vector Ixodes scapularis in Canada. J Appl Ecol. 2012;49: 457–64.
View Article
Google Scholar

[193] View Article

[194] Google Scholar

[ref64] 64. Goethert HK, Lubelcyzk C, LaCombe E, Holman M, Rand P, Smith RP Jr, Telford SR 3rd. Enzootic Babesia microti in Maine. J Parasitol. 2003;89(5): 1069–71. pmid:14627162
View Article
PubMed/NCBI
Google Scholar

[196] View Article

[197] PubMed/NCBI

[198] Google Scholar

[ref65] 65. Dolan MC, Lacombe EH, Piesman J. Vector Competence of Ixodes muris (Acari: Ixodidae) for Borrelia burgdorferi. J Med Entomol. 2000;37(5): 766–8. pmid:11004792
View Article
PubMed/NCBI
Google Scholar

[200] View Article

[201] PubMed/NCBI

[202] Google Scholar

Figures

Abstract

Introduction

Materials and Methods

Site selection

Tick collection

Environmental determinants of tick occurrence

Environmental data collected at each site visit.

Georeferenced environmental data.

Statistical analyses

Analysis of environmental determinants.

Spatial analysis.

Results

Tick collection

Environmental determinants of tick occurrence

Spatial analysis

Discussion

Supporting Information

S1 File. Surveillance data collected or used in the study.

Acknowledgments

Author Contributions

References