Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 641 2019 NORTHEASTERN NATURALIST 26(3):641–655 Tick Burdens in a Small-Mammal Community in Virginia Leah R. Card1,*, William J. McShea1, Robert C. Fleischer2, Jesús. E. Maldonado2, Kristin Stewardson2, Michael G. Campana2, Patrick A. Jansen3,4, and Justin M. Calabrese1 Abstract - Virginia has seen dramatic increases in reported cases of Lyme disease and Rocky Mountain spotted fever, but basic knowledge on the community ecology of these tick-borne diseases is poor. We examined the tick burdens of 5 small-mammal species in northwest Virginia from October 2011 to December 2012. We live-trapped individuals, quantified the tick burdens, assessed the burden structure, and tested a subset of the ticks for tick-borne pathogens. We found the tick burdens to be composed predominantly of Ixodes scapularis (Black-Legged Tick), and Ixodes sp. ticks, with Amblyomma americanum (Lone Star Tick) and Dermacentor variabilis (American Dog Tick) also present at lower densities. We detected Borrelia burgdorferi (prevalence 15%), Rickettsia spp. (4%), Anaplasma phagocytophilum (4%), and Hepatozoon spp. (1%). Black-Legged Ticks, a species which has shown range expansion in recent decades, tested positive for B. burgdorferi (17%) and for multiple pathogens in individual ticks. For better predictions of tick-borne disease risk across the Mid-Atlantic region, we recommend tracking changes in tick communities by continuous monitoring of tick burdens, densities of questing ticks, and prevalence of tickborne pathogens. Introduction Many of the tick-borne diseases affecting humans have increased in geographic range and number of reported cases in the United States in recent years (Dantas- Torres et al. 2012). This increase has been especially strong in Virginia, which has seen dramatic increases in reported cases of Lyme disease and Rocky Mountain spotted fever over the last decade (Brinkerhoff et al. 2014, CDC 2017, Nadolny et al. 2014). Of the 10 states with the highest reports for Lyme disease from 2006 to 2016, Virginia has had the second highest rate of increase, following Pennsylvania (CDC 2018). While no single factor seems primarily responsible, increases in disease prevalence have been attributed to tick range expansion, increases in human– tick interactions, and changes in biodiversity and habitat (Gubler et al. 2001, Nadolny et al. 2014). Small mammals play an important role in the prevalence of tick-borne pathogens, as they are both hosts to feeding ticks and reservoir hosts for pathogens 1Conservation Ecology Center, Smithsonian Conservation Biology Institute, National Zoological Park, 1500 Remount Road, Front Royal, VA 22630. 2Center for Conservation Genomics, Smithsonian Conservation Biology Institute at the National Zoological Park, 3001 Connecticut Avenue NW, Washington, DC 20008. 3Center for Tropical Forest Science, Smithsonian Tropical Research Institute, Roosevelt Avenue, Balboa, Ancón, Republic of Panamá. 4Department of Environmental Sciences, Wageningen University, PO Box 47, 6700 AA Wageningen, Netherlands. *Corresponding author - leahrcard@gmail.com. Manuscript Editor: Daniel Keppie Northeastern Naturalist 642 L.R. Card, et al. 2019 Vol. 26, No. 3 (Dallas et al. 2012). While not adversely affected by the pathogens (Tilly et al. 2008), small-mammal species differ in quality as reservoir hosts (Ostfeld and Keesing 2012), with some being major carriers of pathogens (e.g., Peromyscus leucopus (Rafinesque) [White-Footed Mouse] and the Lyme disease pathogen Borrelia burgdorferi (Johnson)), and others as poor quality hosts, a “dead end” for the pathogen. LoGiudice et al. (2003) found that high vertebrate biodiversity and community composition can lead to lower prevalence of Lyme disease. Small-mammal hosts can also impact overall tick populations as many immature ticks feed primarily on such hosts (Smart and Caccamise 1988). Due to their importance, tick burdens (all of the ticks attached to an individual host) have been the focus of many studies. Past research on tick burdens has often been limited to examinations of a single tick species, mammal host species, or tick-borne pathogen. Recent tick research in Virginia and the surrounding region focused on pathogen prevalence in host-seeking, or “questing”, ticks (Henning et al. 2014; Herrin et al. 2014; Nadolny et al. 2011, 2014), and have not assessed the tick burdens of small mammals. All studies that have assessed tick burdens of small mammals in Virginia and surrounding states are decades old (Levine et al. 1991, Sonenshine and Haines 1985, Sonenshine and Stout 1968, Zimmerman et al. 1987). Therefore, there is a strong need for tick-burden research in Virginia and the surrounding region, to provide researchers and the medical community with important updated information on ticks and tick-borne disease risk. This study aims to address this deficiency. We surveyed ticks and tick-borne pathogens within a small-mammal community in northwest Virginia. We examined the tick burdens on small mammals for the following: tick abundance, tick species composition, and tick-borne pathogen prevalence. In addition, we examined the abundance, diversity, and pathogen prevalence of questing ticks. Field-site Description This study was conducted in forests and fields at the Smithsonian Conservation Biology Institute (SCBI), near Front Royal, VA (Warren County; 38°53´15.6˝N, 78°9´54.6˝W). SCBI features long-term ecological monitoring projects including a Smithsonian Institution Forest Global Earth Observatory (ForestGEO), a 25.6-ha monitoring plot surveyed since 1990 (Bourg et al. 2013), and has been a National Ecological Observatory Network core site since 2014. These features make SCBI an ideal location for conducting a baseline tick survey, as the long-term data collected at this site could provide ecological context for understanding any future changes in the tick, pathogen, or host communities. Methods Small-mammal captures and tick collection We trapped small mammals from October to November 2011 and April to October 2012 (5460 trap-nights) using 8 cm × 9 cm × 23 cm live traps (Sherman, Tallahassee, FL). Each trapping session for the project consisted of 4 consecutive nights of trapping. The trapping period during fall of 2011 and from spring to fall Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 643 in 2012 coincided with tick phenology, thus capturing activity and abundance of larval and nymphal ticks (Gatewood et al. 2009). For 2012, trapping in the forest took place within the ForestGEO grid (680 m × 420 m), which was divided into 8 sections. The sections included 4 smaller sections (210 m x 160 m) with 88 trap grid-points, and 4 larger sections (210 m x 180 m) with 99 trap grid-points. Trapping took place at 2 of the 8 sections (including 1 of each size) with a total of 374 traps set at 187 trap locations. We set 2 traps facing opposite directions near each trap grid-point site, with 20 m between locations. We randomly selected the 2 grids (1 from each size) for trapping, which allowed for each section to be trapped for multiple sessions across the trapping period, varying from 2 to 8 trapping sessions. We also conducted trapping along 10 transects (100 m each), with 2 traps set every 10 m, for 1 session each in 3 fields and 3 forests in 2011 and in 2 fields in 2012. Trapping along transects with a total of 22 traps per transect enabled us to survey small mammals outside of the ForestGEO grid, in field and forest sections across SCBI that varied in area and shape. All captured animals were identified to species and sex, marked with an ear tag if unmarked, weighed, searched thoroughly for ticks, and then released at the point of capture. We did not use anesthesia during processing. We counted and collected all observed, attached ticks, which we then placed into vials filled with ethanol (Hersh et al. 2014, Schmidt et al. 1999). For all ticks, we also recorded the location of the tick attachment upon the host using 3 location categories (ear, face [including chin], and torso). All Peromyscus mice were identified as White-Footed Mice based on tail characteristics (Reid 2006). However, we recognize that the study may have included P. maniculatus (Wagner) (Deer Mice) as these Peromyscus species are difficult to differentiate in the field (Rich et al. 1996). Procedures for all animal captures were approved by the Smithsonian Institution’s Animal Use and Care Committee (#11-30). Tick collection from the environment To measure the density of questing ticks in the environment, we sampled ticks opportunistically from October to November 2011 and from May to October 2012 at SCBI using standard drag cloths (90 cm × 185 cm) for dragging at ground level (Brunner and Ostfeld 2008, Goddard 1993, Henning et al. 2014). We dragged the area around each mammal trap for 40 m2 in each individual survey, with a total survey area of 20,650 m2. These surveys provided a measure of questing tick density and diversity in the area surrounding each trap site. We dragged at each trap site as soon as logistically possible after mammal trapping, and sampling was completed within 1 week following mammal captures. Tick morphological identification All collected ticks were observed under a 6.3:1 (5‒378x magnification) microscope (Olympus CHA, Tokyo, Japan). Adult and nymphal ticks were identified to species using characteristics (scutum, basis capituli, spurs, etc.) as shown in 2 pictorial keys (Keirans and Durden 1998, Keirans and Litwak 1989). We did not morphologically identify the larval ticks to species as few keys exist for larvae, and Northeastern Naturalist 644 L.R. Card, et al. 2019 Vol. 26, No. 3 identification is difficult and prone to error. Preliminary species identification was checked by taxonomist R. Robbins (Air Forces Pest Management Board, US Army Garrison-Forest Glen, Silver Spring, MD). Pathogen screening and tick molecular identification As we were unable to test all collected ticks due to time and budget constraints, we selected a subsample (n = 250) of collected ticks, including both attached and questing, for genetic testing. Attached ticks were selected randomly but stratified by host and tick species across the study period. We randomly selected questing ticks from each dragging location across the study period. This subsample was genetically tested to verify tick species identification and screen for tick-borne pathogen groups including Anaplasma phagocytophilum (Foggie) Dumler et al., Ehrlichia spp., Theileria microti (França) (= Babesia microti), Borrelia burgdorferi, Coxiella burnetii Derrick, Rickettsia spp., and Hepatozoon spp. We chose these pathogens because they have been reported in the region (CDC 2017) and have had well-tested protocols designed for their detection using PCR-based methods (Campana et al. 2016). We refer to genera that include pathogenic and non-pathogenic species, such as Rickettsia spp., as pathogen groups with the understanding that the group may include pathogenic and/or non-pathogenic species. We homogenized whole ticks using 1.0-mm silica beads in a BeadBeater (BioSpec Products, Inc., Bartlesville, OK). Each individual tick was processed (Appendix 1). We identified morphologically unidentified ticks, mostly larvae, and pathogens by previously published conventional PCR assays (primer pairs listed in Appendix 1; detailed methodology listed in the appendix of Campana et al. 2016). Rarefaction curves for community composition We computed rarefaction-type curves, based on the Shannon–Weaver diversity index (Dumas et al. 2011, Gauthier et al. 2010) to assess whether the sizes of our subsamples of identified ticks were sufficient to characterize the tick communities we sampled. We first divided our identified ticks into 4 groups: (1) attached adults, (2) attached nymphs, (3) questing adults, and (4) questing nymphs. For each of these groups with at least 2 species identified, we then randomly resampled (without replacement) 15,000 times, and computed the Shannon–Weaver index, as a function of sample size, for each re-sampling. For each sample size (from 1 individual to the total number of individuals in each group), we then averaged over the 15,000 re-samplings to obtain the rarefaction curve and its standard deviation. Finally, we plotted the rarefaction curve for each group, together with ± 1 SD error bars, against the full-data Shannon–Weaver diversity estimate for the focal group. This latter value is simply the Shannon–Weaver estimate computed from all of the data for a given group. We developed a small R package, shannonRarefy (https://github. com/jmcalabrese/shannonRarefy), to automate these calculations. The package can be installed using the devtools package via: devtools::install.github(“jmcalabrese/ shannonRarefy”). These rarefaction curves allowed us to assess the extent to which species diversity in each of the above-defined groups could be expected to change as sample sizes Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 645 decreased. A small decrease in expected diversity produced by a large decrease in sample size would suggest that the actual sample size of the focal group was sufficient to characterize diversity. At the other extreme, a large decrease in expected diversity produced by a small decrease in sample size would suggest a group-level sample size that was likely too small to adequately characterize diversity. Results Small-mammal captures We captured 471 small mammals representing 5 species, including Blarina brevicauda (Say) (Short-Tailed Shrew), White-Footed Mice, Zapus hudsonius (Zimmermann) (Meadow Jumping Mouse), Microtus pennsylvanicus (Ord) (Meadow Vole), and Tamias striatus (L.) (Eastern Chipmunk) (Table 1), all of which were identified, measured, and examined for ticks. Most mammals (75%) were White- Footed Mice. A total of 87 White-Footed Mice and 4 Eastern Chipmunks were recaptured and reexamined for ticks. Tick collection and identification We collected 1114 ticks attached to the mammals, the majority of which were larvae (Table 1). Most ticks were attached on ears (86%), with less on the face region (9%) and the torso (5%). Ticks were not observed on 36% of all small mammals, including the majority of Short-Tailed Shrews, a third of Eastern Chipmunks and White-Footed Mice, and 1 Meadow Vole (Table 1). We identified a total of 164 ticks (115 genetically, 49 morphologically) to the following 3 species: Amblyomma americanum (L.) (Lone Star Tick), Dermacentor variabilis (Say) (American Dog Tick), and Ixodes scapularis (Say) (Blacklegged Tick). Tick abundance varied over time for each life stage (Fig. 1), with peak abundance of adults in October (n = 12 ticks), nymphs in June (n = 66), and larvae in July (n = 234). Tick burdens were lowest in November (91%) and peaked in July (16%). In addition, we collected 2389 questing ticks (Table 2). A subsample of 428 was identified (25 genetically, 403 morphologically) to the same 3 species. Most (57%) were Blacklegged Ticks. Table 1. Small mammals captured in forests and fields in Virginia, and the ticks collected from them, by species and life stage: Adult (A), Nymph (N), and Larvae (L). Average tick burdens (± 1 SD) are given. Unidentified ticks are not listed except for those in Ixodes genus. A. a. = A. americanum (Lone Star Tick), D. v. = D. variabilis (American Dog Tick), and I. s. = I. scapularis (Blacklegged Tick). Average Unknown Total tick A. a. D. v. I. s. Ixodes Host species hosts burden N L A N L A N L Totals Blarina brevicauda 55 0.51 (± 2.04) 0 0 0 0 6 0 0 8 26 Microtus pennsylvanicus 7 1.71 (± 1.60) 0 2 2 0 1 0 0 0 11 Peromyscus leucopus 353 3.04 (± 4.24) 6 11 16 34 54 1 55 527 930 Tamias striatus 55 2.85 (± 4.05) 0 0 6 11 12 0 14 95 144 Zapus hudsonius 1 3 0 0 0 0 3 0 0 0 3 Total ticks 6 13 24 45 76 1 69 630 1114 Northeastern Naturalist 646 L.R. Card, et al. 2019 Vol. 26, No. 3 The density of questing ticks peaked in June for adults (0.05 individuals/m2) and for nymphs (0.14 individuals/m2), and in August for larvae (14.28 individuals/m2) (Fig. 1). We identified an additional 700 of the 1114 ticks collected from small mammals (Table 1) and an additional 663 of the 2389 questing ticks to the Ixodes genus (Table 2). Ten ticks were identified to the Ixodes genus using molecular techniques, Figure 1.Tick burdens (number of ticks collected) and questing tick density (ticks/m2) over time for: (A) larvae, (B) nymphs, and (C) adults. Sampling efforts across trapping and dragging sessions were constant over time. No trapping took place between December 2011 and March 2012. No dragging for questing ticks took place between January and March 2012. Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 647 while the remaining 1353 ticks were identified morphologically. We were unable to identify the remaining 1548 collected ticks (250 attached, 1298 questing) because these specimens were either too damaged or non-Ixodes larvae, which are difficult to identify due to their morphological traits being less conspicuous. Taxonomist R. Robbins verified samples of adult and nymphal ticks that we had identified morphologically. The ticks selected for genetic identification were those that had not been morphologically identified to species, the majority of which were larval ticks or too damaged to identify. We verified the morphological identification of ticks to genus through genetic testing. All ticks that were genetically identified as Blacklegged Ticks, or at least to the Ixodes genus, were morphologically identified to the Ixodes genus. All larvae that were genetically identified as American Dog Ticks and a single Lone Star Tick were morphologically identified as non-Ixodes. These results indicates that visual identification was accurate . We computed Shannon–Weaver diversity-based rarefaction curves for attached nymphs (n = 51), questing adults (n = 105), and questing nymphs (n = 320) (Fig. 2). We were unable to compute a rarefaction curve for attached adults, as only 1 species (Blacklegged Tick) was identified in this group. For the 3 groups of identified ticks with ≥ 2 species per group, the rarefaction curves suggested that the estimated species diversity of each group was not sensitive to changes in sample size. Specifically, our analysis suggested that a 50% reduction in sample size of identified ticks would lead to reductions in Shannon diversity of only 5.0% for attached nymphs (Fig. 2A), 1.4% for questing adults (Fig. 2B), and 0.3% for questing nymphs (Fig. 2C). Pathogen detection Using molecular methods, we tested 250 ticks (218 from small mammals and 32 questing) for 7 pathogens (Table 3). We detected varying prevalence of 4 pathogen groups in tested ticks: A. phagocytophilum, B. burgdorferi, Hepatozoon spp., and Rickettsia sp. (Table 3). Overall, 26% of the larvae (n = 33), 22% of the nymphs (n = 19), and 26% of the adults (n = 9) tested positive for pathogens. Five Blacklegged Ticks tested positive for multiple pathogens. Discussion Virginia has seen significant increases in reported cases of tick-borne diseases over the past decade (CDC 2017), but basic knowledge on the community ecology of these tick-borne diseases is poor. We examined the tick species and tick-borne Table 2. Questing ticks captured in forests and field in Virginia, grouped by species and life stage. Unidentified ticks are not listed except for those in Ixodes genus. Amblyomma Dermacentor Ixodes Unknown americanum variabilis scapularis Ixodes Total Adult 45 20 40 1 106 Nymph 119 0 201 82 402 Larvae 1 0 2 580 583 Total 165 20 243 663 1091 Northeastern Naturalist 648 L.R. Card, et al. 2019 Vol. 26, No. 3 pathogens in questing ticks and within tick burdens of a small-mammal community in forests and fields from October 2011 to November 2012 in northwest Virginia, in order to generate valuable information regarding tick burdens and pathogen prevalence that can be used as a baseline for future studies. Among ticks collected from 5 small-mammal species, we found that Blacklegged Tick was the most abundant tick species and Ixodes the most abundant genus at each tick life stage. Lone Star Ticks and American Dog Ticks were present in the burdens at much lower levels of abundance. It is likely that the unidentified portion of attached larval ticks consisted of Lone Star Ticks and American Dog Ticks, but even with these additional ticks, the 2 species remain at low abundances when compared to Ixodes. These findings reflect that the range of Figure 2. Rarefaction-type curves representing Shannon-Weaver diversity vs sample size (black curves) for identified: (A) attached nymphs (n = 51), (B) questing adults (n = 105), and (C) questing nymphs (n = 320). The (vertical) error bars are ±1 SD, and the horizontal line is the Shannon-Weaver diversity estimate from the full dataset for the focal group. Notice that the full sample sizes noted above for each group are reflected in the maximum sample size value on the x-axis of each panel. In all cases, cutting the full sample size in half resulted in no more than a 5% decrease in Shannon diversity. Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 649 Table 3. Pathogen prevalence in ticks collected from 3 small mammal species—Peromyscus leucopus (PELE; n = 166 ticks tested), Tamias striatus (TAST; n = 38), Microtus pennsylvanicus (MIPE; n = 5)—and directly from the environment (q) in forests and fields in Virginia, grouped by species and life stage: Larvae (L), Nymph (N), and Adult (A). Tested ticks from Blarina brevicauda (BLBR; n = 6) and Zapus hudsonius (ZAHU; n = 3) were negative for all pathogens and are not listed below. Totals equal total number tested (number positive). Tick life Anaplasma phagocytophilum Borrelia burgdorferi Hepatozoon spp. Rickettsia spp. Tick species stage PELE TAST q PELE TAST MIPE q PELE q PELE q A. americanum L 0 (0) 0 (0) 1 (0) 0 (0) 0 (0) 0 (0) 1 (0) 0 (0) 1 (0) 0 (0) 1 (1) N 1 (0) 0 (0) 3 (0) 1 (0) 0 (0) 0 (0) 3 (0) 1 (0) 3 (1) 1 (0) 3 (2) A 0 (0) 0 (0) 1 (0) 0 (0) 0 (0) 0 (0) 1 (0) 0 (0) 1 (0) 0 (0) 1 (0) D. variabilis L 11 (1) 0 (0) 0 (0) 11 (0) 0 (0) 2 (0) 0 (0) 11 (0) 0 (0) 11 (0) 0 (0) A 0 (0) 0 (0) 2 (0) 0 (0) 0 (0) 0 (0) 2 (0) 0 (0) 2 (0) 0 (0) 2 (0) I. scapularis L 54 (4) 12 (0) 2 (0) 54 (11) 12 (6) 1 (1) 2 (0) 54 (0) 2 (0) 54 (4) 2 (0) N 34 (2) 11 (1) 13 (1) 34 (2) 11 (4) 0 (0) 13 (2) 34 (0) 13 (0) 34 (1) 13 (0) A 16 (0) 6 (0) 6 (1) 16 (0) 6 (0) 2 (0) 6 (3) 16 (0) 6 (0) 16 (0) 6 (3) Unknown Ixodes L 19 (0) 13 (0) 1 (0) 19 (4) 13 (0) 0 (0) 1 (0) 19 (1) 1 (0) 19 (0) 1 (0) N 24 (0) 1 (0) 0 (0) 24 (1) 1 (1) 0 (0) 0 (0) 24 (1) 0 (0) 24 (0) 0 (0) A 0 (0) 0 (0) 0 (0) 0 (0) 1 (1) 1 (1) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Totals 250 (10) 250 (37) 250 (3) 250 (11) % of ticks testing positive 4.0 14.8 1.2 4.4 Northeastern Naturalist 650 L.R. Card, et al. 2019 Vol. 26, No. 3 the Blacklegged Tick has been expanding geographically over the past 20 years, and is moving from the East Coast inland to the west (Brinkerhoff et al. 2014, Brownstein et al. 2003). Our findings confirm Brownstein et al. (2003), who modeled future distributions of Blacklegged Ticks, and predicted prominent increases in Virginia. We found that the Blacklegged Tick has become the dominant tick species in burdens in northwest Virginia. Blacklegged Ticks tested positive for Borrelia burgdorferi, Anaplasma phagocytophilum, and Rickettsia spp., and some specimens even tested positive for multiple pathogens. Given the major roles that Blacklegged Ticks and White-footed Mice have in the transmission and maintenance of Lyme disease (B. burgdorferi; Brunner and Ostfeld 2008, Schmidt et al. 1999), the dominance of Blacklegged Ticks in tick burdens can help explain the drastic increases in Lyme disease and other tickborne diseases in Virginia (Brinkerhoff et al. 2014). Monitoring of the expansion of Blacklegged Ticks across North America would be needed to track and predict increases in associated tick-borne pathogen prevalence and resulting disease risks to human health. Our survey of questing ticks showed high abundances of Blacklegged Ticks and Lone Star Ticks; however, many of the larvae could not be identified. In surveys in southeastern Virginia, Lone Star Ticks represented 95% of the questing ticks collected (Nadolny et al. 2014). As Lone Star Ticks do not use small mammals as primary hosts (Kollars et al. 2000), studies should include larger-sized hosts to better understand the interactions of this species. Our rarefaction analyses suggested that our sampling efforts were sufficient to characterize the tick assemblages we studied. For the specific samples we collected, these analyses demonstrated that halving the sample size would be expected to cause a negligible change in estimated species diversity for attached nymphs, questing adults, and questing nymphs. However, we caution that there is no guarantee employing such reduced sample sizes in future studies would sufficiently characterize diversity in these groups. We also caution that no method can “see” what was not in a sample. However, based on the data we do have, the rarefaction results lend some confidence that our results would not have changed much even if we had collected substantially smaller samples. We detected 4 tick-borne pathogens: Rickettsia spp., B. burgdorferi, A. phagocytophilum, and Hepatozoon spp., the agents of Rickettsia diseases (i.e., Rocky Mountain Spotted Fever), Lyme disease, human granulocytic anaplasmosis, and hepatozoonosis, respectively (CDC 2017). While pathogen presence in ticks collected from mammalian hosts does not necessarily imply that the mammal is infected, it does provide information regarding the infection risk to the host species. With at least a quarter of the tested ticks having one or more pathogen, these data demonstrate the high risk for tick-borne disease in the study area. Our study provides a snapshot of the tick burdens and tick-borne disease risk in Virginia, and can provide a baseline for future research. Given the range expansion of various tick species across the Mid-Atlantic region and the possible consequences for human health, we recommend further monitoring of the changes in both the tick community and variation in prevalence and disease risk over time. Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 651 Acknowledgments We thank Justin Lock for initial testing of ticks at the Center for Conservation Genomics lab; Caitlin Kupferman and Giulia Manno for assisting with the trapping and tick collection; Richard Robbins of the Armed Forces Pest Management Board and Hillary Young for assistance with tick identification; Rick Ostfeld and Kelly Oggenfuss for advice regarding tick collection; Holly Gaff and Jory Brinkerhoff for advice regarding the use of PCR for testing ticks; and Lorenza Beati of the US National Tick Collection for advice regarding tick identification. This study was funded by a Smithsonian Institution Grand Challenges Award to W.J. McShea and P.A. Jansen. The collection of mammals was done under the approval of the Smithsonian Institutional Animal Care and Use Committee (#11-30). No competing financial interests exist. Literature Cited Bourg, N.A., W.J. McShea, J.R. Thompson, J.C. McGarvey, and X. Shen. 2013. Initial census, woody seedling, seed rain, and stand-structure data for the SCBI SIGEO Large Forest Dynamics Plot. Ecology 94:2111–2112. Brinkerhoff, R.J., W.F. Gilliam, and D. Gaines. 2014. Lyme Disease, Virginia, USA, 2000– 2011. Emerging Infectious Diseases 20:1661–1668. Brownstein, J.S., T.R. Holford, and D. Fish. 2003. A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States. Environmental Health Perspectives 111:1152–1157. Brunner, J.L., and R.S. Ostfeld. 2008. Multiple causes of variable tick burdens on smallmammal hosts. Ecology 89:2259–2272. Campana, M.G., M.T.R. Hawkins, L.H. Henson, K. Stewardson, H.S. Young, L.R. Card, J. Lock, B. Agwanda, J. Brinkerhoff, H.D. Gaff, K.M. Helgen, J.E. Maldonado, W.J. McShea, and R.C. Fleischer. 2016. Simultaneous identification of host, ectoparasite, and pathogen DNA via in-solution capture. Molecular Ecology Resources 16:1224–1239. Centers for Disease Control and Prevention (CDC). 2017. Tickborne diseases of the United States. Available online at https://www.cdc.gov/ticks/diseases/index.html. Accessed 12 December 2017. CDC. 2018. Lyme Disease: Data and statistics. Available online at https://www.cdc.gov/ lyme/stats/index.html. Accessed 18 January 2018. Criado-Fornelio, A., A. Martinez-Marcos, A. Buling-Saraña, and J.C. Barba-Carretero. 2003. Molecular studies on Babesis, Theileria, and Hepatozoon in southern Europe. Part I. Epizootiological aspects. Veterinary Parasitology 113:189–201. Dallas, T.A., S.A. Foré, and H.-J. Kim. 2012. Modeling the influence of Peromyscus leucopus body mass, sex, and habitat on immature Dermacentor variabilis burden. Journal of Vector Ecology 37:338–341. Dantas-Torres, F., B.B. Chommel, and D. Otranto. 2012. Ticks and tick-borne diseases: A One Health perspective. Trends in Parasitology 28:437–446. Dumas, M.D., S.W. Polson, D. Ritter, J. Ravel, J. Gelb Jr., R. Morgan, and K.E. Wommack. 2011. Impacts of poultry-house environment on poultry-litter bacterial community composition. PLoS ONE 6:1–12 (e24785). Eremeeva, M., X. Yu, and D. Raoult. 1994. Differentiation among spotted fever group rickettsiae species by analysis of restriction fragment length polymorphism of PCRamplified DNA. Journal of Clinical Microbiology 32:803–810. Northeastern Naturalist 652 L.R. Card, et al. 2019 Vol. 26, No. 3 Folmer, O., M. Black, W. Hoeh, R. Lutz, and R. Vrijenhoek. 1994. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Molecular Marine Biology and Biotechnology 3:294–299. Gatewood, A.G., K.A. Liebman, G. Vourc’h, J. Bunikis, S.A. Hamer, R. Cortinas, F. Melton, P. Cislo, U. Kitron, J. Tsao, A.G. Barbour, D. Fish, and M.A. Diuk-Wasser. 2009. Climate and tick seasonality are predictors of Borrelia burgdorferi genotype distribution. Applied and Environmental Microbiology 75:2476–2483. Gauthier, O., J. Sarrazin, and D. Desbruyères. 2010. Measure and mis-measure of species diversity in deep-sea chemosynthetic communities. Marine Ecology Progress Series 402:285–302. Ghafar, M.W. and N.A. Eltablawy. 2011. Molecular survey of five tick-borne pathogens (Ehrlichia chaffeensis, Ehrlichia ewingii, Anaplasma phagocytophilum, Borrelia burgdorferi sensu lato, and Babesia microti) in Egyptian farmers. Global Veterinaria 7:249–255. Goddard, J. 1993. Ecological studies of Ixodes scapularis (Acari: Ixodidae) in central Mississippi: Lateral movement of adult ticks. Journal of Medical Entomology 30:824–826. Gubler, D.J., P. Reiter, K.L. Ebi, W. Yap, R. Nasci, and J.A. Patz. 2001. Climate variability and change in the United States: Potential impacts on vector- and rodent-borne diseases. Environmental Health Perspectives 109:223–233. Hebert, P.D.N., E.H. Penton, J.M. Burns, D.H. Janzen, and W. Hallwachs. 2004. Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. Proceedings of the National Academy of Sciences of the United States of America 101:14812–14817. Henning, T.C., J.M. Orr, J.D. Smith, J.R. Arias, and D.E. Norris. 2014. Spotted fever group rickettsiae in multiple hard tick species from Fairfax County, Virginia. Vector borne and zoonotic diseases 14:482–485. Herrin, B., A.M. Zajac, and S.E. Little. 2014. Confirmation of Borrelia burgdorferi sensu stricto and Anaplasma phagocytophilum in Ixodes scapularis, Southwestern Virginia. Vector-Borne and Zoonotic Diseases 14:821–823. Hersh, M.H., S.L. LaDeau, M.A. Previtali, and R.S. Ostfeld. 2014. When is a parasite not a parasite? Effects of larval tick burdens on White-footed Mouse survival. Ecology 95:1360–1369. Ivanova, N., and C. Grainger. 2006. Primer sets comprising major analytical pipelines at CCDB. Canadian Center for DNA Barcoding Advances: Methods Release Dec 1. Guelph, ON, Canada. Available online at http://ccdb.ca/site/wp-content/uploads/2016/09/ CCDB_PrimerSets.pdf. Keirans, J.E., and L.A. Durden. 1998. Illustrated key to nymphs of the tick genus Amblyomma (Acari: Ixodidae) found in the United States. Journal of Medical Entomology 35:489–495. Keirans, J.E., and T.R. Litwak. 1989. Pictorial key to the adults of hard ticks, Family Ixodidae (Ixodida: Ixodoidea), East of the Mississippi River. Journal of Medical Entomology 26:435–448. Kollars, T.M., J.H. Oliver, L.A. Durden, and P.G. Kollars. 2000. Host associations and seasonal activity of Amblyomma americanum (Acari: Ixodidae) in Missouri. Journal of Parasitology 86:1156–1159. Levin, M.L., and D. Fish. 2000. Immunity reduces reservoir host competence of Peroymscus leucopus for Ehrlichia phagocytophila. Infection and Immunity 68:1514–1518. Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 653 Levine, J.F., D.E. Sonenshine, W.L. Nicholson, and R.T. Turner. 1991. Borrelia burgdorferi in ticks (Acari: Ixodidae) from coastal Virginia. Journal of Medical Entomology 28:668–674. LoGiudice, K., R.S. Ostfeld, K.A. Schmidt, and F. Keesing. 2003 The ecology of infectious disease: Effects of host diversity and community composition on Lyme disease risk. Proceedings of the National Academy of Sciences 100:567–571. Mediannikov, O., F. Fenollar, C. Socolovschi, G. Diatta, H. Bassene, J.-F. Molez, C. Sokhna, J.-F. Trape, and D. Raoult. 2010. Coxiella burnetii in humans and ticks in rural Senegal. PLoS Neglected Tropical Diseases 4:1–8. Nadolny, R.M., C.L. Wright, W.L. Hynes, D.E. Sonenshine, and H.D. Gaff. 2011. Ixodes affinis (Acari: Ixodidae) in southeastern Virginia and implications for the spread of Borrelia burgdorferi, the agent of Lyme disease. Journal of Vector Ecology 36:464–467. Nadolny, R.M., C.L. Wright, D.E. Sonenshine, W.L. Hynes, and H.D. Gaff. 2014. Ticks and spotted fever group rickettsiae of southeastern Virginia. Ticks and Tick-borne Diseases 5:53–57. Ostfeld, R.S., and F. Keesing. 2012. Effects of host diversity on infectious disease. Annual Review of Ecology, Evolution, and Systematics 43:157–182. Reid, F.A. 2006. White-footed Mouse. Pp. 278–279, In A Field Guide to Mammals of North America North of Mexico. 4th Edition. The Peterson Field Guide Series. Houghton Mifflin Company, New York, NY. 579 pp. Rich, S.M., C.W. Kilpatrick, J.L. Shippee, and K.L. Crowell. 1996. Morphological differentiation and identification of Peromyscus leucopus and P. maniculatus in northeastern North America. Journal of Mammalogy 77: 985–991. Schmidt, K.A., R.S. Ostfeld, and E.M. Schauber. 1999. Infestation of Peromyscus leucopus and Tamias striatus by Ixodes scapularis (Acari: Ixodidae) in relation to the abundance of hosts and parasites. Journal of Medical Entomology 36:749–757. Shih, C.-M., and L.-L. Chao. 2002. An OspA-based genospecies identification of Lyme disease spirochetes (Borrelia burgdorferi) isolated in Taiwan. American Journal of Tropical Medicine and Hygiene 66:611–615. Smart, D.L., and D.F. Caccamise. 1988. Population dynamics of the American Dog Tick (Acari: Ixodidae) in relation to small-mammal hosts. Journal of Medical Entomology 25:515–522. Sonenshine, D.E., and G. Haines. 1985. A convenient method for controlling populations of the American Dog Tick, Dermacentor variabilis (Acari: Ixodidae), in the natural environment. Journal of Medical Entomology 22:577–583. Sonenshine, D.E., and J. Stout. 1968, Tick burdens in relation to spacing and range of hosts in Dermacentor variabilis. Journal of Medical Entomology 5:49–52. Tilly, K., P.A. Rosa, and P.E. Stewart. 2008. Biology of infection with Borrelia burgdorferi. Infectious disease clinics of North America 22:217–234. Ujvari, B., T. Madsen, and M. Olsson. 2004. High prevalence of Hepatozoon spp. (Apicomplexa, Hepatozoidae) infection in Water Pythons (Liasis fuscus) from tropical Australia. Journal of Parasitology 90:670-672. Zhang, Z., S. Schwartz, L. Wagner, and W. Miller. 2000. A greedy algorithm for aligning DNA sequences. Journal of Computational Biology 7:203–214. Zimmerman, R.H., G.R. McWherter, and S.R. Bloemer. 1987. Role of small mammals in population dynamics and dissemination of Amblyomma americanum and Dermacentor variabilis (Acari: Ixodidae) at Land Between the Lakes, Tennessee. Journal of Medical Entomology 24:370–375. Northeastern Naturalist 654 L.R. Card, et al. 2019 Vol. 26, No. 3 Appendix 1. We genetically identified ticks to species using the cytochrome c oxidase subunit 1 (cox1) barcode region and the 16S rRNA gene (Folmer et al. 1994, Hebert et al. 2004, Ivanova and Grainger 2006, Nadolny et al. 2011). The Apicomplexan primer pair BT-1F/BT-1R (Criado-Fornelio et al. 2003) sometimes amplified the tick 18S rRNA gene, permitting identification of ticks to genus. We identified pathogens by previously published diagnostic regions (Criado-Fornelio et al. 2003, Ghafar and Eltablawy 2011, Levin and Fish 2000, Mediannikov et al. 2010, Shih and Chao 2002, Ujvari et al. 2004). All PCR set-ups included an extraction negative control and a PCR negative control (containing water rather than DNA). Positive controls were obtained for the 8 pathogens from known infected animals. Therefore, all non- Apicomplexan PCR set-ups included positive controls. PCRs were conducted in 25- μl volumes containing 1× AmpliTaq Gold PCR buffer (Life Technologies, Carlsbad, CA), 2 mM of MgCl2, 1 mM of dNTPs, 0.4 μM of each primer, 20 μg of BSA, 1U of AmpliTaq Gold (Life Technologies) and 2‒3 μl of DNA. Thermocycling for the ectoparasite cytochrome c oxidase subunit I (cox1) reactions included the following: an initial 5-min denaturation step at 95 °C; 5 cycles of 30 s at 95 °C, 40 s at 45 °C, and 1 min at 72 °C; 35 cycles of 30 s at 95 °C, 40 s at 51 °C, and 1 min at 72 °C; and a final 10-min extension step at 72 °C. Thermocycling for B. burgdorferi, C. burnetii, Rickettsia sp., and ectoparasite 16S rRNA assay programs consisted of an initial 5-min denaturation of 95 °C; 40 (B. burgdorferi, Rickettsia sp.) or 35 (C. burnetii, ectoparasite) cycles of 1 min at 94–95 °C, 1 min at annealing temperature (60 °C for B. burgdorferi and C. burnetii, 55 °C for Rickettsia sp., 50 °C for ectoparasites), and 1 min at 72 °C; and a final 5-min extension step of 72 °C. For the A. phagocytophilum and Ehrlichia sp. assays, thermocycling consisted of an initial 5-min denaturation of 95 °C; 35 cycles of 30 s at 94 °C, 30 s at annealing temperature (55 °C for Ehrlichia sp., 58 °C for A. phagocytophilum), and 30 s at 72 °C; and a final 5-min extension step of 72 °C. Thermocycling for the apicomplexan assays consisted of an initial 5-min denaturation of 95 °C; 40 (BTH- 1F/BTH-1R primer pair) or 35 (HepF300/HepR900 primer pair) cycles of 30 s at 94 °C, 30 s at 60 °C, and 60 s (BTH-1F/BTH-1R) or 45 s (HepF300/Hep4900) at 72 °C; and a final 5-min extension step of 72 °C. Sequencing was done on an ABI 3130 (Life Technologies) for representative subsamples of positive PCR products following standard protocols. PCR products were visualized on a 1.5% agarose gel stained with GelRed (Biotium Inc., Freemont, CA). We purified and sequenced representative samples of positive PCR products on an ABI 3130 sequencer (Life Technologies) following standard protocols (sequences available in FASTA format upon request from the authors). Sequences were edited using Sequencher® 5 (Gene Codes Corporation, Ann Arbor, MI) and then aligned against the GenBank non-redundant nucleotide database using Megablast to determine tick and pathogen identities (Zhang et al. 2000). We identified pathogen and tick species by their best Megablast matches. In the case of multiple best (or near-best) matches, we conservatively identified sequences to genus. All pathogens identified to species were at least 97% identical with publicly available reference sequences. Northeastern Naturalist Vol. 26, No. 3 L.R. Card, et al. 2019 655 The following table provides the primer pairs used to identify tick and pathogen species by polymerase chain reaction. Published primer names are given with the marker in parentheses. Organism Marker Forward (5′→3′) Reverse (5′→3′) Reference Tick cox1 TAA CTT CAG GGT CAA CAA Folmer et al. 1994 (HC02198/LC01490) GGT GAC CAA ATC ATA AAG AAA TCA ATA TTG G Tick cox1 ATT CAA CCA TAA ACT TCT Hebert et al. 2004 (LEPF1/LEPR1) ATC ATA AAG GGA TGT CCA ATA TTG G AAA ATC A Tick cox1 AYT CAA CYA CCW GTY CCA Ivanova and Grainger (dgLEPF1/dgMLEPR1) ATC AYA AAG GCW CCA KWT 2006 AYM TTG G TC Tick 16S rRNA CTG CTC AAT GTC TGA ACT Nadolny et al. 2011 (16s + 1/16s - 1) GAT TTT TTA CAG ATC AAG AAT TGC TGT T Anaplasma 16S rRNA GGC ATG TAG CCC CCA CAT Ghafar and Eltablawy (E1/E2) GCG GTT CGG TCA GCA CTC 2011 TAA GTT ATC GTT TA Apicomplexa 18S rRNA GTT TCT GAC CAA ATC AAG Ujvari et al. 2004 (HepF300/HepR900) CTA TCA GCT AAT TTC ACC TTC GAC G TCT GAC Apicomplexa 18S rRNA GGT TGA TCC GCC TGC TGC Criado-Fornelio et al. (BT-1F/BT-1R) TGCC AGT CTT CCT TA 2003 AGT Borrelia ospA AAT AGG TCT CTA GTG TTT Shih and Chao 2002 (SL_F/SL_R) AAT AAT AGC TGC CAT CTT CTT AAT AGC CTT TGA AAA Borrelia Flagellin CGG CAC ATA CCT GTT GAA Levin and Fish 2000 (FLA297/FLA652) TTC AGA TGC CAC CCT CTT AGA CAG GAA CC Coxiella IS1111 CAA GAA ACG CAC AGA GCC Mediannikov et al. (CbISF/CbISR) TAT CGC TGT ACC GTA TGA 2010 GGC ATC Ehrlichia 16S rRNA CAA TTG CTT TAT AGG TAC Ghafar and Eltablawy (HE1F/HE3R) ATA ACC TTT CGT CAT TAT 2011 TGG TTA TAA CTT CCC TAT AT Rickettsia ompB GGC AAT TAA GCA TCT GCA Eremeeva et al. 1994 (BG1-21/BG2-20) TAT CGC TGA CTA GCA CTT CGG TC