- 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.
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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