A replicated paired fencing experiment allowed us to test three hypotheses (increased transmission potential, dilution and ecological cascades) for how high deer density may affect B. burgdorferi s.l. infection prevalence in questing ticks (NIP). Furthermore, we could test how these effects on NIP interact with the role of deer in supporting tick populations and shaping Lyme disease hazard. We found that nymphal infection prevalence was lower in high deer density plots along with evidence pointing to a combination of dilution and trophic cascading effects. Despite the lower NIP, Lyme disease hazard (DIN) was five times higher in high deer density plots compared to deer exclusion plots, due to a strong, positive association between deer and nymph density.
Our transmission potential hypothesis (H1) predicted that a high deer density would result in an increased tick density, causing higher tick burdens (and therefore increased transmission potential) on individual rodents. We did find a strong positive effect of high deer density on DON, highlighting the importance of deer in driving tick populations, as found in previous studies (Gray et al. 1992; Daniels et al. 1993; Gilbert et al. 2012; Pacilly et al. 2014; Mysterud et al. 2016). All else being equal, this would have predicted increased opportunities for pathogen transmission. In contrast however, we found high deer density plots had half the predicted NIP of exclusion plots, suggesting that increased tick densities and transmission were counter-acted by other factors driving NIP down.
Several studies have reported positive correlations between DON and tick burdens on rodents (Daniels and Fish 1995; Hofmeester et al. 2017a) and other hosts (Gilbert et al. 2017). This may also have been the case for rodents in our experiment but, as only two bank voles were captured in high deer density plots (as predicted by the ecological cascade hypothesis), we were not able to test for differences between deer treatments in individual rodent tick burdens. This dramatic reduction in rodent captures in high deer density plots is a key finding and invalidates H1’s assumption of similar rodent densities with deer density. Therefore, even if individual rodents had higher tick burdens in high deer density areas, rodent density was probably too low for maintaining effective pathogen transmission in this environment.
Our observation that B. burgdorferi s.l. prevalence was almost three times higher in deer exclusion plots, despite estimates being associated with considerable uncertainty, is consistent with predictions from both the dilution effect (H2) and ecological cascade (H3) hypotheses. The dilution effect predicts lower NIP at high deer densities due to a lower proportion of the larval tick population feeding on rodents, which are transmission hosts for B. burgdorferi s.l., than on deer that do not transmit the pathogens (Gray et al. 1992; Ostfeld and Keesing 2000; Vourc’h et al. 2016). This is challenging to test because, ideally, it requires density estimates and tick burdens of the key hosts. We could not obtain tick burden measurements on deer and we caught only two voles in high deer density plots, precluding statistical test. However, based on differences in vole abundance between deer treatments, we estimated that voles fed almost 10 times more larvae in deer exclusion plots compared to high deer density plots. This compares to no larvae feeding on deer in exclusion plots (as deer were absent), in contrast to the situation in high deer density plots where it is highly likely that most larvae fed on deer. This is due to the (i) very high deer density (32.5. km− 2) and (ii) high densities of questing nymphs (a result of high larval survival) in high deer density plots. We therefore suggest that a dilution effect was one of the mechanisms operating on NIP in response to high deer densities, as it has been previously suggested for B. burgdorferi s.l. (Gray et al. 1992; Ostfeld and Keesing 2000; Vourc’h et al. 2016) and predicted for other tick-borne pathogens that deer do not transmit, including tick-borne encephalitis virus (Bolzoni et al. 2012) and Louping ill virus (Gilbert et al. 2001).
While we did not survey other known hosts for larval ticks such as birds or shrews (Sorex spp.) (Klaus et al. 2016; Hofmeester et al. 2017b), previous studies suggest that the effect of high deer density on these groups is likely to be negative as well (Flowerdew and Ellwood 2001; Allombert et al. 2005; Herder et al. 2016). It is therefore likely that the populations of alternative hosts were low in high deer density plots and that the majority of larvae must have been feeding on red deer. In addition, the fact that almost all nymphs that tested positive (92%) were infected with the rodent associated pathogen, B. afzelii, suggests that other hosts (e.g. birds) did not contribute much to B. burgdorferi s.l. transmission in our system.
To the best of our knowledge, this is the first test of the ecological trophic cascade hypothesis of B. burgdorferi s.l. prevalence, predicting that grazing pressure from high deer densities will reduce the vegetation, resulting in fewer rodents and therefore lower NIP. We found support for most of the expected trophic links: high deer density resulted in shorter vegetation, highlighting the effects of deer grazing on vegetation structure (Flowerdew and Ellwood 2001; Buesching et al. 2011). Lower ground vegetation was associated with fewer bank voles in support of denser and higher ground vegetation providing better food, shelter and protection from predators (Flowerdew and Ellwood 2001; Eccard et al. 2008). We captured 13 times fewer bank voles in high deer density plots, consistent with our predictions and with previous work that showed higher densities of bank voles (Buesching et al. 2011) and wood mice (Buesching et al. 2011; Smit et al. 2011) in plots excluding deer. It is possible that direct disturbance from deer (which we did not quantify) could also be contributing in addition to the effect of reduced vegetation cover (Flowerdew and Ellwood 2001). However, we could not confirm the last link for the trophic cascade hypothesis (i.e. a strong link between rodent activity and NIP), as bank vole abundance the previous year was only a weak positive predictor of NIP for B. afzelii (Fig. 4D). The weak association between vole abundance and NIP in this experiment could be due to several factors, including low prevalence of B. burgdorferi s.l. overall, providing insufficient signal for detecting unequivocal statistical effects. Another contributing factor might have been the small spatial scale of our experiment plots (0.23 ha), facilitating likely movements of rodents between fenced and unfenced plots, which were 30–100 m apart.
The small spatial scale of our plots, while a potential issue for confirming a link between rodent abundance and NIP, proved sufficient to confirm strong effects of high deer density with DON, NIP, Lyme disease hazard, vegetation height and rodent activity. While a previous meta-analysis of deer exclusion effects on tick abundance (Perkins et al. 2006) suggested that deer exclusion areas of at least 2.5 ha may be necessary to have an effect, our results show smaller plots sizes to be sufficient for testing impacts of deer on ticks, consistent with other more recent studies (Gilbert et al. 2012 - plots of 0.2–0.25 ha; Mysterud et al. 2016 - plots of 0.04 ha)
Irrespective of the mechanisms driving NIP, the most critical parameter governing public health and policy importance for Lyme disease is the density of infected nymphs (DIN = NIP x DON), which is the key proxy for Lyme disease hazard in the environment. DIN was five times higher in high deer density plots compared to exclosures due to deer having a strong positive effect on DON. Similarly, other studies have found a positive correlation between deer density and Lyme disease hazard (Vourc’h et al. 2016; Takumi et al. 2019) or Lyme disease incidence in humans (Mysterud et al. 2016). Using an experimental system with high deer densities (32.5. km− 2), we were able to demonstrate that this role of deer as tick reproduction hosts is, at least at high deer densities, more important than their role in lowering NIP through dilution and trophic cascade effects in shaping Lyme disease hazard.
In contrast to our experiment, previous studies have shown Lyme disease hazard to be associated with higher densities of transmission hosts (van Duijvendijk 2016; Takumi et al. 2019). However, such an association requires enough vectors in the environment to transmit the pathogen effectively (Logiudice et al. 2008), whereas in our experimental situation, the plots with high densities of transmission hosts did not have deer, and therefore had few ticks to aid transmission. Thus, we might expect Lyme disease hazard to be highest in an environment supporting both high numbers of transmission hosts and tick reproduction hosts. However, based on our findings and previous research showing that high deer densities have strong negative effects on rodent abundance (Flowerdew and Ellwood 2001; van Wieren and Bakker 2008), such a combination may not commonly occur in nature. This demonstrates the importance of taking a systems approach, including considering potential ecological cascades when predicting disease risk. While our experiment used extreme contrasts in deer densities (zero vs 32.5. km− 2) it is notable that we were able to detect effects on infection dynamics even on very small spatial scales (0.23 ha plots).
Our results highlight the need for taking a systems approach to such a complex disease system where different host types might affect each other’s densities through habitat modification, or other means such as predation (Levi et al. 2012). Gaps in knowledge that can now be addressed include testing for cascading effects from deer on B. burgdorferi s.l. prevalence at landscape scales, and including a full range of intermediate deer densities, to investigate non-linearities and thresholds of effects of deer and to test whether the mechanisms supported here operate in a non-experimental setting.
In conclusion, we found that high deer density could lower Lyme disease pathogen prevalence by a combination of dilution and trophic cascading effects. Despite this, Lyme disease hazard was five times higher in high deer density plots due to a strong positive effect of deer on tick density. This study is, to our knowledge, the first to test for cascading effects of deer on B. burgdorferi s.l. prevalence via grazing and suppressing rodent abundance. This study highlights the need for a systems approach to understand disease dynamics and risks that could arise from complex ecological interactions between host types and habitat.