- Open Access
Multiflora rose invasion amplifies prevalence of Lyme disease pathogen, but not necessarily Lyme disease risk
© The Author(s). 2018
- Received: 24 March 2017
- Accepted: 5 January 2018
- Published: 23 January 2018
Forests in urban landscapes differ from their rural counterparts in ways that may alter vector-borne disease dynamics. In urban forest fragments, tick-borne pathogen prevalence is not well characterized; mitigating disease risk in densely-populated urban landscapes requires understanding ecological factors that affect pathogen prevalence. We trapped blacklegged tick (Ixodes scapularis) nymphs in urban forest fragments on the East Coast of the United States and used multiplex real-time PCR assays to quantify the prevalence of four zoonotic, tick-borne pathogens. We used Bayesian logistic regression and WAIC model selection to understand how vegetation, habitat, and landscape features of urban forests relate to the prevalence of B. burgdorferi (the causative agent of Lyme disease) among blacklegged ticks.
In the 258 nymphs tested, we detected Borrelia burgdorferi (11.2% of ticks), Borrelia miyamotoi (0.8%) and Anaplasma phagocytophilum (1.9%), but we did not find Babesia microti (0%). Ticks collected from forests invaded by non-native multiflora rose (Rosa multiflora) had greater B. burgdorferi infection rates (mean = 15.9%) than ticks collected from uninvaded forests (mean = 7.9%). Overall, B. burgdorferi prevalence among ticks was positively related to habitat features (e.g. coarse woody debris and total understory cover) favorable for competent reservoir host species.
Understory structure provided by non-native, invasive shrubs appears to aggregate ticks and reservoir hosts, increasing opportunities for pathogen transmission. However, when we consider pathogen prevalence among nymphs in context with relative abundance of questing nymphs, invasive plants do not necessarily increase disease risk. Although pathogen prevalence is greater among ticks in invaded forests, the probability of encountering an infected tick remains greater in uninvaded forests characterized by thick litter layers, sparse understories, and relatively greater questing tick abundance in urban landscapes.
- Lyme disease
- Borrelia burgdorferi
- Borrelia miyamotoi
- Anaplasma phagocytophilum
- Babesia microti
- Invasive species
- Forest fragment
Urbanization affects many aspects of vector-borne disease ecology . In the case of tick-borne disease systems such as Lyme disease (caused by Borrelia burgdorferi) in forested ecosystems, urbanization alters habitat suitability for vectors (i.e. ticks), vertebrate hosts, and as a result, pathogens. Human development in the Lyme disease endemic, mid-Atlantic region of the United States reduces overall forest cover and average patch size while increasing the area of edge and impervious surface. Reduced forest patch size, in particular, results in predictable changes to host community composition that increase acarological risk in terms of nymphal infection prevalence and density of infected nymphs [2–5]. Yet in human-dominated landscapes, patch size may have a smaller or perhaps unpredictable influence on host community relative to other effects of urbanization on forested ecosystems. How ecological characteristics of urban forest fragments affect acarological risk has not been well explored.
Complex land use histories in human-dominated landscapes form networks of diverse, heterogeneous forest fragments. In the urban mid-Atlantic region, clear-cutting, intensive agriculture, and urban sprawl have created a variety of forest fragment types on a spectrum between remnants of mature (> 100 yr. old) forests and forest fragments that have regrown from fallow agricultural land set aside while surrounding areas were developed . In the latter case, native tree species have competed with and grown alongside non-native species that were part of the agricultural landscape or subsequent development. As a result, regrown urban forest patches have closed canopies of mostly native trees with thick understories composed of non-native, invasive species . These two extremes of urban forest fragment types both face serious ecological problems (e.g. loss of native understory or reduced regeneration), with implications for tick-borne disease risk.
Due to changes to below-ground processes and browsing pressure from high density white-tailed deer (Odocoileus virginianus) populations (in Delaware, recent county surveys estimate between 18 and 52 deer/km2 ), mature forests may have sparse or no woody understories and cannot replace many species of dead or dying trees . Although they maintain a thick litter layer and low soil pH, which may help buffer mature forests from invasion by non-native plants , many native woody plants cannot regenerate. The thick litter layer maintained in these forests provides suitable habitat for blacklegged ticks (Ixodes scapularis), which are found in greater abundance in mature forests relative to other urbanized forest fragment types . In contrast, forest fragments with significant non-native plant invasion in the understory have high densities of invasive earthworms and very little leaf litter [12–15], which constrains tick abundance [11, 16, 17]. However, the dense understory structure provided by invasive plants may aggregate immature ticks and infective hosts, potentially amplifying acarological risk in invaded forest fragments [18–21].
Recent studies have identified greater pathogen prevalence in ticks and reservoir hosts associated with invasive shrubs [18–20, 22]. However, because leaf litter loss, which constrains tick abundance, is also associated with non-native plant invasion, it is unclear how tick-borne disease risk differs in regrown, invaded forest fragments compared to mature, uninvaded fragments. To contribute to our understanding of tick-borne disease ecology in urbanized landscapes, we designed a study in urban forest fragments with three objectives: (i) characterize B. burgdorferi and emerging tick-borne pathogen prevalence among questing ticks; (ii) test for differences in pathogen prevalence between forests invaded by non-native understory plants and uninvaded forests; and (iii) determine which habitat and landscape features influence pathogen prevalence.
Study area and tick collection
Forest fragments (6–16 ha) consisted of mixed deciduous hardwood stands and varied in understory woody species composition, particularly in the extent of non-native R. multiflora invasion (Fig. 1, Additional file 1: Figure S1). Each year we trapped ticks in eight forest fragments, four of which had understories with 10–58% of total area covered by R. multiflora invasion (hereafter: invaded), and four fragments lacked R. multiflora invasion (< 1%), (hereafter: uninvaded). Within invaded sites, we captured ticks at four sets of paired traps: one trap within R. multiflora cover and its pair 25 m away, not in R. multiflora. Paired traps were separated by 25 m to eliminate the possibility that both traps could be attracting the same ticks . In uninvaded sites, we deployed traps at four random points, separated by at least 25 m. We used a total of 64 trap locations over the 2 yr. study, and half of the traps were active on any given trap night. To avoid weather-related impacts on tick questing behavior, we always deployed paired traps together, and baited in equal numbers of invaded and uninvaded fragments on the same nights. We transported all captured ticks to the laboratory live, in individual microcentrifuge tubes, froze them at -80 °C, and later identified them to species and life stage with dichotomous keys [25–27].
Covariate data collection
Summary of vegetation and landscape covariates measured at the trap scale by forest type and location, modified from . Covariates are summarized as mean ± standard error. Different superscript letters A, B, C denote significant differences among groups (P < 0.05) detected using analysis of variance (ANOVA), blocking on site, followed up with Tukey’s post-hoc comparisons when there were more than two groups
Invaded: in rose
Invaded: not in rose
Nudds at 0.5–1.0 m (%)
18.0 ± 3.9A
73.9 ± 4.5B
53.3 ± 5.9C
Rose cover, 12.5 m radius (%)
2.5 ± 0.2A
11.2 ± 0.6B
7.0 ± 0.6C
Leaf litter volume (l/m2)
28.0 ± 2.8A
6.1 ± 1.4B
6.7 ± 1.2B
Coarse woody debris (%)
6.5 ± 0.9A
3.4 ± 0.7B
4.2 ± 0.7B
Rose cover, 2.5 m radius (%)
0.0 ± 0.0A
67.1 ± 2.2B
3.5 ± 0.7A
Distance to agriculture (m)
288.3 ± 54.7A
156.7 ± 24.6B
159.6 ± 24.6B
Distance to edge (m)
67.8 ± 9.1A
39.8 ± 8.8B
41.9 ± 8.4B
Distance to road (m)
154.7 ± 16.7
135 ± 18.1
133.4 ± 15.4
Distance to residential (m)
716.9 ± 377.6
186.2 ± 31.5
174.4 ± 32.9
Distance to stream (m)
371.8 ± 62.7A
148.4 ± 35.7B
134.1 ± 35.6B
0.8 ± 0.1A
0.4 ± 0.1B
0.2 ± 0.0B
2.7 ± 0.5
4.5 ± 0.9
2.1 ± 0.4
Mean larvae per mouseb
0.4 ± 0.1
0.5 ± 0.1
0.7 ± 0.2
Summary of vegetation and landscape covariates measured at the patch scale by forest type (invaded or uninvaded), modified from . Covariates are summarized as mean ± standard error. Superscript letters A, B denote significant differences among groups (P < 0.05) detected using analysis of variance (ANOVA), blocking on site
Rose cover (%)
0.8 ± 0.5A
36.9 ± 7.7B
Total understory cover (%)
19.6 ± 4.4A
41.6 ± 6.1B
Leaf litter volume (l/m2)
13.9 ± 1.1A
6.8 ± 0.9B
Fagus grandifolia (%)
8.5 ± 2.8A
0.7 ± 0.2B
Acer spp. (%)
0.7 ± 0.1A
21.2 ± 1.2B
Year of canopy closure
1916.7 ± 4.9A
1963 ± 5.1B
Non-native stems (%)
9.1 ± 2.7A
40.0 ± 3.3B
Average tree dbh (m)
0.6 ± 0.0
0.6 ± 0.0
Quercus spp. (%)
42.0 ± 6.4A
11.0 ± 5.8B
Mean mice per nest boxa
0.4 ± 0.1
0.5 ± 0.2
Mean larvae per mousea
0.7 ± 0.2
0.9 ± 0.3
Bird territory densityb
3.6 ± 0.5
5.3 ± 0.8
We measured landscape variables at each trap location in ArcGIS using a 2007 Delaware land use land cover layer , focusing on variables that could influence habitat suitability for ticks and/or hosts and that reflected the human-dominated landscape context of the study area [32, 33]: distance to nearest road, stream, agriculture, forest edge and residential development. We also used data from prior [11, 28] and concurrent studies (Adalsteinsson et al., unpublished data) to quantify abundance of ticks, potential hosts, and host-tick interactions in the study area. Tick abundance at the trap-level was the number of I. scapularis nymphs captured at a given trap, standardized by effort (number of trap nights). The densities of ground-foraging bird territories in forest fragments were estimated from spot-mapping surveys conducted during two breeding seasons . Concurrent studies of P. leucopus abundance and parasitism by immature ticks (Adalsteinsson et al., unpublished data) provided estimates of mouse abundance and parasitism rates at the trap and forest fragment scale. To study P. lecuopus abundance, we checked 15 nest boxes per forest fragment once per month; for trap-level estimates, mouse abundance was the mean of the number of mice caught during fall (larval tick season) at the two nest boxes nearest to the trapping location. For patch-level estimates, the number of mice caught at nest boxes in fall was averaged across all 15 nest boxes in a given forest fragment. Larval tick burdens were the mean number of larvae per mouse at either the two closest nest boxes (trap-level) or across all 15 nest boxes (patch-level).
We also included data collected previously to characterize vegetation at the patch level: proportions of Fagus grandifolia, Acer spp., Quercus spp., Liriodendron tulipifera, or Liquidambar styraciflua as dominant canopy trees; percent of total area covered by R. multiflora; mean leaf litter volume measured at 15 locations in the patch; percent of ground covered by understory plants (all spp.); percentage of understory woody stems that were non-native; and year of canopy closure .
We used a modified version of the DNeasy Blood & Tissue Kit (Qiagen, Venlo, Netherlands) protocol to extract DNA from ticks. Here, we explain the steps in which we deviated from the manufacturer’s protocol. First, we used sterile pipette tips to manually crush each I. scapularis nymph individually in 20 μl of Hyclone Dulbecco’s phosphate buffer saline solution (Thermo Fisher Scientific, Waltham, USA). Next, we incubated samples with lysis buffer ATL and proteinase K in a 56 °C hot water bath for 3 h. We performed an extra spin step at 13,000× rpm to remove trace ethanol after the Buffer AW2 wash. Finally, we modified the last step by eluting our samples twice (50 μl each time), for a final product of 100 μl. We checked concentrations of a subset of our samples using a NanoDrop UV-Vis spectrophotometer (Thermo Fisher Scientific, Waltham, USA) to confirm successful DNA extractions.
We tested ticks for the presence of Borrelia burgdorferi (sensu lato), Anaplasma phagocytophilum, and Babesia microti using a previously described multiplex PCR assay . In addition, ticks were also tested for the presence of Borrelia miyamotoi in a TaqMan PCR assay using the following primers and probe: F770-5′-ACC TGC AAC CTT CGG ATT C-3′; R771-5′-TGG TTG TAG CTC AGT TGG TAG-3′; P1277-CalRd610-5′-CTT GTA TCG AAC TAC ACC CAT AGC TC-3′-BHQ2.
A sufficient number of ticks tested positive for Borrelia burgdorferi to allow statistical analyses; however, infection prevalence was too low for the remaining pathogens to determine patterns related to invasion and other habitat and landscape features. We tested for spatial autocorrelation in B. burgdorferi prevalence across forest fragments using a spline correlogram in package ncf  in R .
WAIC table of best models. Variables in the model set are coarse woody debris (CWD), leaf litter volume (litter), distance to the nearest road (dist. Road), mouse abundance in fall (mice), total understory cover (total cover), and nymphal tick capture rate (tick abundance). Field headings refer to the effective number of parameters (pWAIC), the difference between WAIC estimates for each model and the top-ranked model (ΔWAIC), the Akaike weight (Weight), the standard error of the WAIC estimate (SE), and the standard error of ΔWAIC value (ΔSE)
CWD + litter + dist. Road + mice
CWD + litter + dist. Road
CWD + litter + dist. Road + mice + total cover
CWD + litter + dist. Road + mice + tick abundance
In our comparison of invaded and uninvaded forest fragments, we found that B. burgdorferi prevalence among questing ticks did not differ within invaded forests, but that the infection prevalence in ticks from invaded forests was almost double that in ticks from uninvaded forests. Borrelia burgdorferi was the most common pathogen detected in nymphal I. scapularis from our study sites, followed by A. phagocytophilum and B. miyamotoi. Only one I. scapularis nymph was co-infected with B. burgdorferi and A. phagocytophilum, and we did not detect Ba. microti in any of the ticks tested. At finer scales within both invaded and uninvaded sites, infection prevalence was positively related to coarse woody debris, distance to the nearest road, mouse abundance, and extent of understory cover within the forest fragment. We found a negative relationship between infection prevalence and both leaf litter and tick abundance. Rosa multiflora invasion and the additional factors positively influencing pathogen prevalence point to suitable habitat characteristics for small mammal and bird hosts that are competent pathogen reservoirs.
Invaded and uninvaded fragments represent two extremes of different, degraded habitat fragment types that can be separated by the presence/absence of R. multiflora invasion in our landscape. Uninvaded sites have deep litter layers, sparse understory, high densities of questing nymphs, and relatively low infection prevalence (mean = 0.079). Invaded sites have very little leaf litter, dense understory structure, fewer questing nymphs, and roughly double the infection prevalence (mean = 0.159). Our modeling results showed that the total understory cover in a forest fragment positively influences pathogen prevalence. Understory structure, which is provided almost exclusively by invasive plants, may aggregate immature ticks and infective hosts, resulting in increased pathogen prevalence among ticks in invaded forest fragments [19–21]. Because B. burgdorferi is not transmitted transovarially , infected free-living nymphs acquire the bacteria by feeding on an infected host during their larval stage. Similarly, potential pathogen hosts must acquire B. burgdorferi by being fed upon by an infected nymph. Therefore, both immature stages of ticks must interact with infected hosts to elevate pathogen prevalence among nymphs .
Understory structure facilitates interactions between immature ticks and competent B. burgdorferi reservoir hosts [22, 46, 47], but see . White-footed mouse (Peromyscus leucopus) and breeding bird densities are positively correlated with understory structure [47, 49–51] [i.e. invasive plants, in our landscape (unpublished data)]. Within invaded forests, immature ticks are aggregated in stands of invasive shrubs [11, 20, 21]. We hypothesize that larval ticks in uninvaded sites derive a greater proportion of blood meals from larger-bodied hosts that are less-competent B. burgdorferi reservoirs [52, 53]. We expect that this is in contrast to larval tick blood meals in invaded sites, which we predict are composed of a greater proportion of small-bodied hosts that are positively affected by understory structure  and are competent B. burgdorferi reservoirs [53–55]. Future work should use blood meal analysis or identification of ospC types in B. burgdorferi-positive ticks to understand how non-native plant invasion affects the interaction between specific hosts and ticks, and the resulting implications for transmission of human-invasive B. burgdorferi strains [56–58].
An additional hypothesis to explain greater nymphal infection prevalence in invaded sites concerns tick overwinter survival. Invaded habitats lack the litter layer that comprises suitable off-host tick habitat [11, 16, 17]. Ticks depend on the high humidity microclimate within the litter to conserve moisture and to buffer themselves from environmental fluctuations . However, saturated soils coupled with extremely low temperatures may also lead to decreased overwinter survival . Recent studies show that ixodid ticks infected with B. burgdorferi have greater energy reserves and are more robust to desiccation [61–64]. Therefore, the harsh litter-free environment of invaded forests may exert stronger pressure against over-winter survival of uninfected ticks, thus increasing overall infection prevalence.
The negative relationships of nymphal infection prevalence with leaf litter and tick abundance raise questions about our understanding of Lyme disease ecology in over-browsed, mature forest fragments. Uninvaded, mature forest fragments that lack understory structure have greater litter volumes and questing tick abundance than invaded forests. We hypothesize that the lack of understory structure in uninvaded fragments shifts the composition of blood meal hosts toward reservoir-incompetent species such as white-tailed deer or other large-bodied hosts [53, 65]. Talleklint & Jaenson  also detected a negative relationship between tick density and infection prevalence at high tick densities (> 20 nymphs/m2), which they attributed to greater roe deer (Capreolus capreolus) densities. Elevated deer densities could account for both greater tick density and lesser infection prevalence if deer act as both reproductive hosts and the dominant blood meal source [66, 67]. The close proximity among our study sites suggests that deer do not account for differences in tick abundance; most sites are close enough to be within a single deer’s home range [68–70] (Additional file 1: Figure S1). However, deer may reduce infection prevalence by shifting blood meals away from reservoir competent hosts that do not find suitable understory cover in over-browsed, uninvaded fragments.
The importance of invasion, habitat, and landscape variables from our models suggest that understory structure and woody debris aggregate infectious hosts and larval ticks, increasing pathogen transmission. Coarse woody debris, total understory cover, distance to road, and white-footed mouse abundance, variables that directly or indirectly represent the distribution of reservoir hosts, were positively related to infection prevalence. Coarse woody debris provides cover, nest sites, movement corridors, and foraging opportunities for immature tick hosts such as white-footed mice, Sorex and Blarina shrews, and ground-foraging birds [71–75]. Shrews, in particular, are often overlooked in terms of their importance in the Lyme disease system, despite evidence that they can feed and infect more ticks than white-footed mice . Outside of the Pacific Northwest and southern Appalachian regions of the USA, there is a dearth of studies on habitat associations of shrews ; in regions where shrews have been well studied, coarse woody debris appears to be an important habitat component [77–80]. Similarly, total understory cover represents the structure available to white-footed mice and shrub-nesting birds [47, 49, 50]. The importance of distance to road suggests that perhaps small mammals and birds avoid hard edges near roads in our landscape, or at least that larval ticks encounter infectious hosts farther from roads.
Although nymphal infection prevalence was greater in invaded forests, acarological risk in terms of density of infected nymphs may be higher in uninvaded sites; the uninvaded sites examined in this study supported ~3 times as many questing nymphs compared to invaded sites . Although uninvaded sites lack understory structure and therefore support lower densities of immature tick hosts, their relatively intact litter layers may allow nymphal ticks to survive longer  and quest more often , creating more opportunities to attach to humans than in invaded forests. Perhaps in uninvaded fragments, restoration of native understory structure  that promotes greater host diversity could reduce densities of questing infected nymphs.
We are grateful for the cooperation of land agencies involved in this study: Newark City Parks, New Castle County Parks, Delaware State Parks, and Mt. Cuba Center. We thank the following individuals who helped collect field data: Z. Ladin, K. Handley, J. Nimmerichter, A. Lutto, K. Serno, J. Bondi, C. Piazza, L. Newton, and J. Curry. We are grateful for advice on DNA extraction protocols from S. Seifert, E. Stromdahl, and R. Nadolny, and for laboratory assistance from M. Brown. We also wish to thank C. Graham for assisting in the development of the Borrelia miyamotoi PCR assay.
The University of Delaware, USDA McIntire Stennis, and the Aeroecology Program at University of Delaware supported this work. DB was supported by a grant from the National Science Foundation (DEB 1354184).
Availability of data and materials
The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.
SAA, WGS, JJB, VD and DB designed the study. SAA trapped ticks, collected field data, and extracted DNA from ticks. JLB obtained permits to collect vertebrate data. WGS, JJB and VD contributed habitat and landscape data. AH performed PCR assays on DNA samples from the ticks. SAA analyzed the data. SAA, WGS and JJB wrote the paper. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Data on white-footed mice was collected under Delaware State Scientific Collecting Permit #2013-007 W and with approval from University of Delaware’s Institutional Animal Care and Use Committee under protocol #1249, both of which were issued to JLB.
Consent for publication
The authors declare that they have no competing interests.
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- Bradley CA, Altizer S. Urbanization and the ecology of wildlife diseases. Trends Ecol Evol. 2007;22:95–102.View ArticlePubMedGoogle Scholar
- Allan BF, Keesing F, Ostfeld RS. Effect of forest fragmentation on Lyme disease risk. Conserv Biol. 2003;17:267–72.View ArticleGoogle Scholar
- LoGiudice K, Ostfeld RS, Schmidt KA, Keesing F. The ecology of infectious disease: effects of host diversity and community composition on Lyme disease risk. Proc Natl Acad Sci USA. 2003;100:567–71.Google Scholar
- LoGiudice K, Duerr ST, Newhouse MJ, Schmidt KA, Killilea ME, Ostfeld RS. Impact of host community composition on Lyme disease risk. Ecology. 2008;89:2841–9.View ArticlePubMedGoogle Scholar
- Zolnik CP, Falco RC, Kolokotronis S-O, Daniels TJ. No observed effect of landscape fragmentation on pathogen infection prevalence in blacklegged ticks (Ixodes scapularis) in the northeastern United States. PLoS One. 2015;10:e0139473.View ArticlePubMedPubMed CentralGoogle Scholar
- Vellend M, Verheyen K, Flinn KM, Jacquemyn H, Kolb A, Van Calster H, et al. Homogenization of forest plant communities and weakening of species-environment relationships via agricultural land use. J Ecol. 2007;95:565–73.View ArticleGoogle Scholar
- Huebner CD, Steinman J, Hutchinson TF, Ristau TE, Royo AA. The distribution of a non-native (Rosa multiflora) and native (Kalmia latifolia) shrub in mature closed-canopy forests across soil fertility gradients. Plant Soil. 2014;377:259–76.View ArticleGoogle Scholar
- Rogerson J, Globetti M, Hossler R, Moore E, Reynolds K, Hotton D, et al. Delaware Deer Management Plan. Delaware Department of Natural Resources and Environmental Control. 2010. http://www.dnrec.delaware.gov/fw/Hunting/Documents/Deer%20Plan%20-%20FINAL%2005212010.pdf. Accessed 20 Oct 2015.
- Rossell CR, Patch S, Salmons S. Effects of deer browsing on native and non-native vegetation in a mixed oak-beech forest on the Atlantic coastal plain. Northeast Nat. 2007;14:61–72.View ArticleGoogle Scholar
- Bernard MJ, Neatrour MA, McCay TS. Influence of soil buffering capacity on earthworm growth, survival, and community composition in the western Adirondacks and Central New York. Northeast Nat. 2009;16:269–84.View ArticleGoogle Scholar
- Adalsteinsson SA, D’Amico V, Shriver WG, Brisson D, Buler JJ. Scale-dependent effects of nonnative plant invasion on host-seeking tick abundance. Ecosphere. 2016;7(3):e01317.View ArticlePubMedPubMed CentralGoogle Scholar
- Lawrence B, Fisk MC, Fahey TJ, Suárez ER. Influence of nonnative earthworms on mycorrhizal colonization of sugar maple (Acer saccharum). New Phytol. 2003;157:145–53.View ArticleGoogle Scholar
- Suárez ER, Fahey TJ, Yavitt JB, Groffman PM, Bohlen PJ. Patterns of litter disappearance in a northern hardwood forest invaded by exotic earthworms. Ecol Appl. 2006;16:154–65.View ArticlePubMedGoogle Scholar
- Hale CM, Frelich LE, Reich PB. Changes in hardwood forest understory plant communities in response to European earthworm invasions. Ecology. 2006;87:1637–49.View ArticlePubMedGoogle Scholar
- Nuzzo VA, Maerz JC, Blossey B. Earthworm invasion as the driving force behind plant invasion and community change in northeastern north American forests. Conserv Biol. 2009;23:966–74.View ArticlePubMedGoogle Scholar
- Schulze TL, Jordan RA, Hung RW. Suppression of subadult Ixodes scapularis (Acari: Ixodidae) following removal of leaf litter. J Med Entomol. 1995;32:730–3.View ArticlePubMedGoogle Scholar
- Burtis JC, Fahey TJ, Yavitt JB. Impact of invasive earthworms on Ixodes scapularis and other litter-dwelling arthropods in hardwood forests, central New York state, USA. Appl Soil Ecol. 2014;84:148–57.View ArticleGoogle Scholar
- Lubelczyk CB, Elias SP, Rand PW, Holman MS, Lacombe EH, Smith RP. Habitat associations of Ixodes scapularis (Acari: Ixodidae) in Maine. Environ Entomol. 2004;33:900–6.View ArticleGoogle Scholar
- Elias SP, Lubelczyk CB, Rand PW, Lacombe EH, Holman MS, Smith RP. Deer browse resistant exotic-invasive understory: an indicator of elevated human risk of exposure to Ixodes scapularis (Acari: Ixodidae) in southern coastal Maine woodlands. J Med Entomol. 2006;43:1142–52.View ArticlePubMedGoogle Scholar
- Williams SC, Ward JS, Worthley TE, Stafford KC. Managing Japanese barberry (Ranunculales: Berberidaceae) infestations reduces blacklegged tick (Acari: Ixodidae) abundance and infection prevalence with Borrelia burgdorferi (Spirochaetales: Spirochaetaceae). Environ Entomol. 2009;38:977–84.View ArticlePubMedGoogle Scholar
- Allan BF, Dutra HP, Goessling LS, Barnett K, Chase JM, Marquis RJ, et al. Invasive honeysuckle eradication reduces tick-borne disease risk by altering host dynamics. Proc Natl Acad Sci USA. 2010;107:18523–7.Google Scholar
- Prusinski MA, Chen H, Drobnack JM, Kogut SJ, Means RG, Howard JJ, et al. Habitat structure associated with Borrelia burgdorferi prevalence in small mammals in New York state. Environ Entomol. 2006;35:308–19.View ArticleGoogle Scholar
- Kensinger BJ, Allan BF. Efficacy of dry ice-baited traps for sampling Amblyomma americanum (Acari: Ixodidae) varies with life stage but not habitat. J Med Entomol. 2011;48:708–11.View ArticlePubMedGoogle Scholar
- Falco RC, Fish D. Horizontal movement of adult Ixodes dammini (Acari: Ixodidae) attracted to CO2-baited traps. J Med Entomol. 1991;28:726–9.View ArticlePubMedGoogle Scholar
- Keirans JE, Durden LA. Illustrated key to nymphs of the tick genus Amblyomma (Acari: Ixodidae) found in the United States. J Med Entomol. 1998;35:489–95.View ArticlePubMedGoogle Scholar
- Keirans JE, Litwak TR. Pictorial key to the adults of hard ticks, family Ixodidae (Ixodida: Ixodoidea), east of the Mississippi River. J Med Entomol. 1989;26:435–48.View ArticlePubMedGoogle Scholar
- Durden LA, Keirans JE. Nymphs of the genus Ixodes (Acari: Ixodidae) of the United States: taxonomy, identification key, distribution, hosts, and medical/veterinary importance. Entomol Monogr. 1996;vol:1–50.Google Scholar
- Rega C. Impacts of soil calcium availability and non-native plant invasions on an urban forest bird community. University of Delaware 2012. http://udspace.udel.edu/handle/19716/11728. Accessed 2 Jun 2015.
- Nudds TD. Quantifying the vegetative structure of wildlife cover. Wildl Soc Bull. 1977;5:113–7.Google Scholar
- Wolff JO. The effects of density, food, and interspecific inference on home range size in Peromyscus leucopus and Peromyscus maniculatus. Can J Zool. 1985;63:2657–62.View ArticleGoogle Scholar
- State of Delaware, Office of Management and Budget, Delaware Geographic Committee. 2007 Delaware land use and land cover. 1st Edition. Dover, Delaware: State of Delaware, Office of Management and Budget, Delaware Geographic Data Committee. 2007. http://www.state.de.us/planning/info/lulcdata/2007_lulc.htm. Accessed 23 Jan 2014.
- Nicholson MC, Mather TN. Methods for evaluating Lyme disease risks using geographic information systems and geospatial analysis. J Med Entomol. 1996;33:711–20.View ArticlePubMedGoogle Scholar
- Bunnell JE, Price SD, Das A, Shields TM, Glass GE. Geographic information systems and spatial analysis of adult Ixodes scapularis (Acari: Ixodidae) in the middle Atlantic region of the USA. J Med Entomol. 2003;40:570–6.View ArticlePubMedGoogle Scholar
- Hojgaard A, Lukacik G, Piesman J. Detection of Borrelia burgdorferi, Anaplasma phagocytophilum and Babesia microti, with two different multiplex PCR assays. Ticks Tick-Borne Dis. 2014;5:349–51.View ArticlePubMedGoogle Scholar
- Bjornstad, ON. ncf: Spatial nonparametric covariance functions. 2016. https://cran.r-project.org/web/packages/ncf/ncf.pdf
- Development Core R, Team R, Language A. Environment for statistical computing. Vienna, Austria: R Foundation for Statistical. Computing. 2014; http://www.R-project.org
- Stan Development Team. Stan: A C++ Library for Probability and Sampling. 2015. http://mc-stan.org.
- Guo J, Lee D, Sakrejda K, Gabry J, Goodrich B, de Guzman J, et al. rstan: R Interface to Stan. 2016. https://cran.r-project.org/web/packages/rstan/.
- McElreath R. Rethinking: an R package for fitting and manipulating Bayesian models. 2016. https://github.com/rmcelreath/rethinking.
- McElreath R. Statistical rethinking: a Bayesian course with examples in R and Stan. 1st ed. Boca Raton, FL, USA: CRC Press; 2016.Google Scholar
- Watanabe S. Asymptotic equivalence of Bayes cross-validation and widely applicable information criterion in singular learning theory. J Mach Learn Res. 2010;11:3571–94.Google Scholar
- Gelman A, Hwang J, Vehtari A. Understanding predictive information criteria for Bayesian models. Stat Comput. 2014;24:997–1016.View ArticleGoogle Scholar
- Yamashita T, Yamashita K, Kamimura RA. Stepwise AIC method for variable selection in linear regression. Commun Stat Theory Methods. 2007;36:2395–403.View ArticleGoogle Scholar
- Rollend L, Fish D, Childs JE. Transovarial transmission of Borrelia spirochetes by Ixodes scapularis: a summary of the literature and recent observations. Ticks Tick-Borne Dis. 2013;4:46–51.View ArticlePubMedGoogle Scholar
- Buskirk JV, Ostfeld RS. Controlling Lyme disease by modifying the density and species composition of tick hosts. Ecol Appl. 1995;5:1133.View ArticleGoogle Scholar
- Adler GH, Telford SR, Wilson ML, Spielman A. Vegetation structure influences the burden of immature Ixodes dammini on its main host, Peromyscus leucopus. Parasitology. 1992;105:105–10.View ArticlePubMedGoogle Scholar
- Willson MF, Comet TA. Bird communities of northern forests: ecological correlates of diversity and abundance in the understory. Condor. 1996;98:350–62.View ArticleGoogle Scholar
- Devevey G, Brisson D. The effect of spatial heterogenity on the aggregation of ticks on white-footed mice. Parasitology. 2012;139:915–25.View ArticlePubMedGoogle Scholar
- Adler GH, Wilson ML. Demography of a habitat generalist, the white-footed mouse, in a heterogeneous environment. Ecology. 1987;68:1785.View ArticleGoogle Scholar
- Leston LFV, Rodewald AD. Are urban forests ecological traps for understory birds? An examination using northern cardinals. Biol Conserv. 2006;131:566–74.View ArticleGoogle Scholar
- Croci S, Butet A, Georges A, Aguejdad R, Clergeau P. Small urban woodlands as biodiversity conservation hot-spot: a multi-taxon approach. Landsc Ecol. 2008;23:1171–86.View ArticleGoogle Scholar
- Cagnacci F, Bolzoni L, Rosà R, Carpi G, Hauffe HC, Valent M, et al. Effects of deer density on tick infestation of rodents and the hazard of tick-borne encephalitis. I: empirical assessment. Int J Parasitol. 2012;42:365–72.View ArticlePubMedGoogle Scholar
- Barbour AG, Bunikis J, Fish D, Hanincová K. Association between body size and reservoir competence of mammals bearing Borrelia burgdorferi at an endemic site in the northeastern United States. Parasit Vectors. 2015;8:299.View ArticlePubMedPubMed CentralGoogle Scholar
- Donahue JG, Piesman J, Spielman A. Reservoir competence of white-footed mice for Lyme disease spirochetes. Am J Trop Med Hygeine. 1987;36:92–6.View ArticleGoogle Scholar
- Ginsberg HS, Buckley PA, Balmforth MG, Zhioua E, Mitra S, Buckley FG. Reservoir competence of native north American birds for the Lyme disease spirochete Borrelia burgdorferi. J Med Entomol. 2005;42:445–9.View ArticlePubMedGoogle Scholar
- Brisson D, Dykhuizen DE. ospC diversity in Borrelia burgdorferi: different hosts are different niches. Genetics. 2004;168:713–22.View ArticlePubMedPubMed CentralGoogle Scholar
- Önder Ö, Shao W, Kemps BD, Lam H, Brisson D. Identifying sources of tick blood meals using unidentified tandem mass spectral libraries. Nat Commun. 2013;4:1746.View ArticlePubMedPubMed CentralGoogle Scholar
- Vuong H, Canham CD, Fonseca DM, Brisson D, Morin PJ, Smouse PE, et al. Occurrence and transmission efficiencies of Borrelia burgdorferi ospC types in avian and mammalian wildlife. Infect Genet Evol. 2014;27:594–600.View ArticlePubMedGoogle Scholar
- Stafford KC. Survival of immature Ixodes scapularis (Acari: Ixodidae) at different relative humidities. J Med Entomol. 1994;31:310–4.View ArticlePubMedGoogle Scholar
- Brunner JL, Killilea M, Ostfeld RS. Overwintering survival of nymphal Ixodes scapularis (Acari: Ixodidae) under natural conditions. J Med Entomol. 2012;49:981–7.View ArticlePubMedGoogle Scholar
- Naumov RL. Longevity of forest and taiga ticks (Ixodidae) infected and non-infected with Borrelia burgdorferi groups. Parazitologiya. 2003;37:527–32.Google Scholar
- Herrmann C, Gern L. Survival of Ixodes ricinus (Acari: Ixodidae) under challenging conditions of temperature and humidity is influenced by Borrelia burgdorferi sensu lato infection. J Med Entomol. 2010;47:1196–204.View ArticlePubMedGoogle Scholar
- Herrmann C, Gern L. Search for blood or water is influenced by Borrelia burgdorferi in Ixodes ricinus. Parasit Vectors. 2015;8:6.View ArticlePubMedPubMed CentralGoogle Scholar
- Herrmann C, Voordouw MJ, Gern L. Ixodes ricinus ticks infected with the causative agent of Lyme disease, Borrelia burgdorferi sensu lato, have higher energy reserves. Int J Parasitol. 2013;43:477–83.View ArticlePubMedGoogle Scholar
- Telford SR III, Mather TN, Moore SI, Wilson ML, Spielman A. Incompetence of deer as reservoirs of the Lyme disease spirochete. Am J Trop Med Hygeine. 1988;39:105–9.View ArticleGoogle Scholar
- Talleklint L, Jaenson TGT. Relationship between Ixodes ricinus density and prevalence of infection with Borrelia-like spirochetes and density of infected ticks. J Med Entomol. 1996;33:805–11.View ArticlePubMedGoogle Scholar
- Gray JS, Kahl O, Janetzki C, Stein J, Guy E. The spatial distribution of Borrelia burgdorferi-infected Ixodes ricinus in the Connemara region of county Galway, Ireland. Exp Appl Acarol. 1995;19:163–72.View ArticlePubMedGoogle Scholar
- Rhoads CL, Bowman JL, Eyler B. Home range and movement rates of female exurban white-tailed deer. J Wildl Manag. 2010;74:987–94.View ArticleGoogle Scholar
- Etter DR, Hollis KM, Deelen TRV, Ludwig DR, Chelsvig JE, Anchor CL, et al. Survival and movements of white-tailed deer in suburban Chicago, Illinois. J Wildl Manag. 2002;66:500.View ArticleGoogle Scholar
- Grund MD, McAninch JB, Wiggers EP. Seasonal movements and habitat use of female white-tailed deer associated with an urban park. J Wildl Manag. 2002;66:123.View ArticleGoogle Scholar
- Roche BE, Schulte-Hostedde AI, Brooks RJ. Route choice by deer mice (Peromyscus maniculatus): reducing the risk of auditory detection by predators. Am Midl Nat. 1999;142:194–7.View ArticleGoogle Scholar
- Greenberg CH. Response of white-footed mice (Peromyscus leucopus) to coarse woody debris and microsite use in southern Appalachian treefall gaps. For Ecol Manag. 2002;164:57–66.View ArticleGoogle Scholar
- Lohr SM, Gauthreaux SA, Kilgo JC. Importance of coarse woody debris to avian communities in loblolly pine forests. Conserv Biol. 2002;16:767–77.View ArticleGoogle Scholar
- McCay TS, Komoroski MJ. Demographic responses of shrews to removal of coarse woody debris in a managed pine forest. For Ecol Manag. 2004;189:387–95.View ArticleGoogle Scholar
- Jones CG, Lindquist ES. Utilization of woody debris by Peromyscus leucopus in a fragmented urban forest. Southeast Nat. 2012;11:689–98.View ArticleGoogle Scholar
- Brisson D, Dykhuizen DE, Ostfeld RS. Conspicuous impacts of inconspicuous hosts on the Lyme disease epidemic. Proc R Soc B Biol Sci. 2008;275:227–35.View ArticleGoogle Scholar
- Carey AB, Johnson ML. Small mammals in managed, naturally young, and old-growth forests. Ecol Appl. 1995;5:336–52.View ArticleGoogle Scholar
- McCay TS, Laerm J, Menzel MA, Ford WM. Methods used to survey shrews (Insectivora: Soricidae) and the importance of forest-floor structure. Brimleyana. 1998;25:110–9.Google Scholar
- Brannon MP. Niche relationships of two syntopic species of shrews, Sorex fumeus and S. cinereus, in the southern Appalachian Mountains. J Mammal. 2000;81:1053–61.View ArticleGoogle Scholar
- Butts SR, McComb WC. Associations of forest-floor vertebrates with coarse woody debris in managed forests of western Oregon. J Wildl Manag. 2000;64:95.View ArticleGoogle Scholar
- Yuval B, Spielman A. Duration and regulation of the developmental cycle of Ixodes dammini (Acari: Ixodidae). J Med Entomol. 1990;27:196–201.View ArticlePubMedGoogle Scholar
- Randolph SE, Storey K. Impact of microclimate on immature tick-rodent host interactions (Acari: Ixodidae): implications for parasite transmission. J Med Entomol. 1999;36:741–8.View ArticlePubMedGoogle Scholar
- Morlando S, Schmidt SJ, LoGiudice K. Reduction in Lyme disease risk as an economic benefit of habitat restoration. Restor Ecol. 2012;20:498–504.View ArticleGoogle Scholar