DOI: 10.5061/dryad.rv15dv49r
title: No net effect of host density on tick-borne disease hazard due to opposing roles of vector amplification and pathogen dilution

description: To better understand vector-borne disease dynamics, knowledge of the
 ecological interactions between animal hosts, vectors and pathogens is
 needed. The effects of hosts on disease hazard depends on their role in
 driving vector abundance and their ability to transmit pathogens.
 Theoretically, a host that cannot transmit a pathogen could dilute
 pathogen prevalence but increase disease hazard if it increases vector
 population size. In the case of Lyme disease, caused by Borrelia
 burgdorferi s.l. and vectored by Ixodid ticks, deer may have dual opposing
 effects on vectors and pathogen: deer drive tick population densities but
 do not transmit B. burgdorferi s.l. and could thus decrease or increase
 disease hazard. We aimed to test for the role of deer in shaping Lyme
 disease hazard by using a wide range of deer densities while taking
 transmission host abundance into account. We predicted that deer increase
 nymphal tick abundance while reducing pathogen prevalence. The resulting
 impact of deer on disease hazard will depend on the relative strengths of
 these opposing effects. We conducted a cross-sectional survey across 24
 woodlands in Scotland between 2017 and 2019, estimating host (deer,
 rodents) abundance, questing Ixodes ricinus nymph density and B.
 burgdorferi s.l. prevalence at each site. As predicted, deer density was
 positively associated with nymph density and negatively with nymphal
 infection prevalence. Overall, these two opposite effects cancelled each
 other out: Lyme disease hazard did not vary with increasing deer density.
 This demonstrates that, across a wide range of deer and rodent densities,
 the role of deer in amplifying tick densities cancels their effect of
 reducing pathogen prevalence. We demonstrate how non-competent host
 density has little effect on disease hazard even though they reduce
 pathogen prevalence, because of their role in increasing vector
 populations. These results have implications for informing disease
 mitigation strategies, especially through host management.
description: We used 24 sites located in Aberdeenshire,
 Northeast Scotland. An index for deer density was estimated the first year
 of data collection using the standing crop plot count method (Mayle et
 al., 1999). Rodent abundance was estimated at each site during the first
 year of data collection (2017 for 15 sites and 2018 for nine sites) using
 two methods. First, rodent abundance was quantified at each site by
 live-trapping using non-selective Sherman traps. The second method used to
 assess rodent abundance was by recording vole signs (tunnels and holes) at
 each site. We then created a simple index of rodent abundance which
 combined data from both methods. First, we classified each site as having
 either low or high rodent abundance from each method. The data from each
 method exhibited a bimodal distribution with a clear gap between low and
 high density . If a site scored a high category for at least one index, it
 was defined as a high rodent abundance site whereas sites which scored low
 categories for both indexes were identified as low rodent
 abundance.  Questing nymphs were
 collected three times a year (May, July and September) for each year
 following host density estimation (2018 and 2019) using a standard blanket
 dragging method . A white 1 m x 1 m square of fleece blanket material was
 dragged over vegetation along 10 m long transects. At each site, twenty
 transects were randomly surveyed and separated from each other by at least
 20 m. Nymph ticks on the blanket were counted, collected and kept at -20°C
 for pathogen analysis. Woodland type (coniferous, deciduous or mixed
 woodland) was recorded at the site level while ground vegetation was
 classified into four categories: (1) grasses and herbaceous species, (2)
 <em>Ericaceous </em>species (<em>Calluna </em>and
 <em>Vaccinium</em>), (3) moss species and (4) bracken and
 ferns. The dominant vegetation category (that with the most cover) over
 each transect was recorded. Vegetation height was measured at the
 beginning (1 m), middle (5 m) and end (10 m) of each transect, and the
 mean for each transect was included as a continuous variable in analysis
 of tick density as it can affect dragging efficiency. Tick surveys were
 conducted between 0900 hours and 1800 hours and air temperature, relative
 humidity and time were also recorded for each transect, as these may
 affect the proportion of nymphs questing. For analysis we also used the
 rainfall recorded the day before ticks were collected from the nearest
 weather station at Aberdeen Airport
 (http://rp5.co.uk/Weather_archive_in_Aberdeen_(airport),_UK).
 Nymphs were extracted individually using
 an ammonia extraction method. Borrelia burgdorferi s.l. was detected from
 samples using a qPCR protocol on fragments of OspA genes based on the
 protocol described by Heylen et al., 2013. All statistical analyses were performed in the
 software R version 3.5.1 (R core team, 2013) using the glmmTMB, lme4 and
 MuMIn packages. 
description: The data files can be open using Microsoft Excel.