Human actions commonly alter wildlife populations. A classic example of
an alteration is hunting, which often has density and demographic
effects on a population (Milner-Gulland et al. 2003; Whitmanet al. 2004; Packer et al. 2009; Treves 2009). However,
the consequences of these actions on pathogen transmission and evolution
are largely unknown, and the few available studies report contradictory
findings. Theory predicts that for density-dependent pathogens
hunting-induced changes to density should decrease transmission rates
yet make little difference to transmission dynamics for
frequency-dependent pathogens. However, in practice models suggest that
reducing host density can decrease (Lloyd-Smith et al. 2005;
Potapov et al. 2012) or even increase pathogen transmission and
prevalence (Choisy & Rohani 2006; Beeton & McCallum 2011). The complex
interplay between host density, demography and behavior also makes
predicting the impacts of hunting on pathogen dynamics complex. Limited
empirical work shows that population reduction can increase pathogen
prevalence via a ‘perturbation effect’ (Woodroffe et al. 2004,
2006; Carter et al. 2007; Carr et al. 2019). For example,
culling induced changes or ‘perturbations’ to badger (Meles
meles ) territorial behavior was considered a driver of increased bovine
tuberculosis transmission between badgers and cattle (e.g., Woodroffeet al. 2006). However, there is also evidence that population
reduction has little impact on canine rabies (Morters et al.2013) or Tasmanian devil facial tumor disease (Lachish et al.2010) dynamics. Recent advances in high-resolution pathogen sequencing
and analytic approaches can now elucidate patterns of pathogen
transmission and evolution (Smith et al. 2015; Didelot et
al. 2017; Grubaugh et al. 2019) that were previously out of
reach. Here we address the effects of hunting on pathogen dynamics by
capitalizing on pathogen sequences collected from a detailed study on
the demographic effects of hunting (Logan & Runge 2020b) as well as
from sequences obtained over the same time period in a region where
little hunting occurred. Our approach enables us to provide insights
into the cascading consequences of hunting on pathogen-host dynamics.
RNA viruses are ideal agents for examining the effect of hunting on
pathogen transmission and evolution. Genomic variation rapidly accrues
in RNA viruses, enabling estimation of fine-scale epidemiological
processes (such as transmission between hosts) and the basic
reproduction number R0 (the average number of secondary
cases per infection, Biek et al. 2015; Didelot et al.2017). Altered transmission dynamics and the arrival of new lineages can
imprint distinctive evolutionary signatures on RNA viruses as they adapt
quickly to changes in host populations they encounter (Woolhouseet al. 2014; Pybus et al. 2015). For example, if the
cessation of hunting led to a higher frequency of transmission events,
we expect that the transmission bottleneck would lead to high purifying
selection since within-host mutations are lost with transmission (e.g.,
Pybus & Rambaut 2009). Conversely, if new mutations entering the host
population allow the pathogen to escape immune detection, we may expect
an increase in diversifying selection. Altered transmission dynamics and
new lineages will also shape the phylogenetic diversity of the pathogen
(Fountain-Jones et al. 2018). For example, if novel pathogen
lineages are frequently arriving into a host population with limited
transmission, we would expect to see a pattern of phylogenetic
dispersion (i.e., higher phylogenetic diversity than expected by chance
(Webb 2000)). In contrast, phylogenetic clustering (i.e., lower
phylogenetic diversity than expected by chance (Webb 2000)), may be a
marker of increased transmission events within a population.
Here we leverage viral data collected from closely monitored puma
(Puma concolor ) in two areas in Colorado during the same time
period: a ‘treatment region’ in which hunting pressure changed over time
and a ‘stable management region’ acting as a control (hereafter ‘stable
region’). We sequenced viral genes sampled from captured puma for an
endemic RNA retrovirus, puma feline immunodeficiency virus
(FIVpco), which is a host-specific pathogen considered
relatively benign and not associated with overt disease outcomes (Bieket al. 2003). Even though FIVpco is endemic in
puma populations, novel infections can spread in susceptible and
previously infected individuals (Malmberg et al. 2019). Evidence
suggests FIVpco is transmitted via aggressive
interactions in most instances, although vertical transmission is also
possible (Biek et al. 2003; Fountain-Jones et al. 2017).
We analyzed these viral data in both regions using a transmission
network approach (Didelot et al. 2017; Fountain-Jones et
al. 2018) that incorporates a stochastic epidemiological model with
pathogen genomic data to trace transmission between individual puma. The
treatment region consisted of puma in a
~12000km2 area in western Colorado in
which hunting prior to our study was common practice (see Logan & Runge
2020a). Hunting was excluded for a five-year period (2004-2009,
“no-hunting period”) and reinstated for a further five years
afterwards (2009-2014, “hunting period”). During the no-hunting period
in the treatment region, the population of independent pumas (i.e.,
adults and sub-adults) increased from an estimated 23 (2005) to 57
(2009) individuals with much of this growth occurring 2007-2010 (Logan
& Runge 2020a, i.e., after a two year lag 2004-6 hereafter “Lag 1”).
Adult and sub-adult male survival was significantly higher in the
no-hunting period (Logan & Runge 2020a). When hunting resumed, the
overall population declined after a lag of two years (hereafter ‘Lag
2’). However, the decline in abundance and demographic effects on males
were severe and rapid with males > 6 years old apparently
eliminated from the population after two hunting seasons (Logan & Runge
2020b). In contrast, over the same period, the stable region in the
Front Range of Colorado experienced minimal hunting pressures and no
change in management practice. Nearly all the individuals sampled in
both regions were adults and both sexes were evenly represented. While
density was higher in the stable region (see Table S1), individual
survival probabilities in the stable region were unaltered across years
(Moss et al. 2016). By comparing the treatment and stable
regions, we were able to test how demographic changes caused by hunting
cessation and reinstatement perturb viral transmission networks and
epidemiological parameters (e.g., R0), and also alter
pathogen diversity and evolution. In doing so we begin to untangle the
complex interplay between wildlife management and pathogen transmission,
which is crucial for pathogen-orientated conservation and disease
management strategies.