Beyond single mechanism studies
Each of the individual mechanisms for predator-spreading described above
requires substantial additional study to understand both their relative
importance across natural systems and the factors that contribute to the
strength of the effect. While much can be learned by studying a single
mechanism in a single predator-prey-parasite system, a broad
understanding of the importance of predator-spreading to disease
dynamics in wildlife requires inference that spans mechanisms and study
systems (Duffy et al. 2021). This type of inference necessitates
both the study of multiple predator-spreading mechanisms within a single
system and the comparison of predator-spreading across a wide range of
biological systems.
Although we have noted the characteristics of systems that may make them
especially suited to studying a particular type of predator spreading,
it is vital that a variety of predator spreading mechanisms are tested
in a single system. It is natural for a particular system to be used
repeatedly to investigate a particular mechanism of predator spreading
due to demonstrated feasibility. For example, behavioral predator
spreading has been well studied in aquatic frog tadpole prey because
tadpoles can readily be exposed to caged predators or predator
kairomones to provoke behavioral responses, and because methods are
well-established (Han et al. 2011; Szuroczki & Richardson 2012;
Koprivnikar & Urichuk 2017; Buss & Hua 2018). It is, however,
plausible that other predator-spreading mechanisms such as
sloppy-predation, selective predation, and parasites passing through
predators could prove important in some tadpole-parasite systems. By
comparing the relative magnitude of effect sizes across multiple
predator-spreader mechanisms or by manipulating multiple mechanisms
within a single experiment (e.g., by manipulating predator kairomone
presence and the presence of shredded infected tadpoles), we can come to
understand whether predator-spreading is important to disease dynamics;
this would also allow us to understand which mechanisms are key to
driving this phenomenon in a particular system and whether or not there
are synergistic effects between mechanisms.
In addition to studying multiple mechanisms in a single system, we must
study the same mechanism in multiple systems – an approach known as
“horizontal integration” (Travis 2006). Horizontal integration
requires a range of systems that are amenable to study (Duffy et
al. 2021); even without considering predation, dominant model systems
in the study of disease ecology and evolution have major gaps that
likely impede our understanding (Wale & Duffy 2021). Despite these
challenges, a comprehensive understanding of the factors that promote
predator spreading will require studies that use prey from a range of
taxa, predators that differ in key traits (e.g., related to how prey are
detected and captured), with a variety of parasites (including
microparasites, macroparasites, and ectoparasites), and in a variety of
habitats (including terrestrial and aquatic).
Comparative analyses of predator-spreading mechanisms across taxa and
study systems will require substantial scientific coordination. At
present, quite a few labs across the world have conducted or regularly
conduct experiments or observational studies of predator-prey-parasite
interactions. Some of these labs have a primary focus on predator-prey
or parasite-host ecology and use a study system as a way of asking
fundamental ecological questions. However, many predator-prey-parasite
experiments are conducted with an aim towards better pest management in
agriculture or other applied outcomes (e.g., Chacón et al. 2008;
Chailleux et al. 2017; de Lourdes Ramírez-Ahuja et al.2017). Unfortunately few of these studies share common reporting
standards and many suffer from similar experimental design limitations.
In addition to placing all data in a publicly accessible repository, we
encourage future researchers measuring predator spreader effects to
follow these general guidelines:
- Report all measurable parasitism outcomes; ideally at least prevalence
and prey population density, and intensity if feasible
- Measure as many proximate predator effects as is practical (e.g., prey
demography, prey physiology, prey immunity, prey space-use or grouping
behavior)
- Test a range of predation pressures instead of presence/absence of
predators
Most studies of predator-parasite interactions report only a single
parasite outcome and rarely report prey population density (though
studies on agricultural pests are a notable exception to the latter
(Kaneko 2006; Agboton et al. 2013; Chailleux et al.2017)). The choice of parasite outcome, typically prevalence or
intensity, is at times motivated by underlying theory or parasite
biology, but frequently the reasons for the choice are unclear.
Measuring intensity is more common in studies of macroparasites, but we
suggest that it could be interesting to measure this for microparasites
as well (since, for example, predators may shift age or size structure
in a way that alters the average burden of infection). We also note that
the term “intensity” can denote different types of parasite
quantification in different systems (similar to the case for the term
“virulence”), so it will be important to clearly define how intensity
is being quantified when reporting the results. Mechanisms of predator
spreading affect prevalence and intensity in different ways (Richardset al. 2022). For example, if predators have the largest
physiological effect on prey already susceptible to infection then
individuals who are likely to be infected may become more heavily
infected at a higher rate than healthy individuals become newly
infected. The combination of effects on prevalence and intensity may
also help to identify the specifics of predator spreading mechanisms. We
also suggest the reporting of prey population density as an outcome
because of the important role it plays in the original healthy herds
hypothesis and our general understanding of the predator-prey-parasite
interaction, and because this metric can be of particular interest
(e.g., when the prey is of conservation concern) (Packer et al.2003; Duffy et al. 2019). If predators increase parasitism but
fail to have persistent effects on prey population densities or prey
fitness, the predator-spreader interaction would be of limited use for
understanding prey population dynamics. Studies on agricultural
arthropod pests which manipulate both predators and parasites typically
focus on prey density as the key outcome of interest (Kaneko 2006;
Vance-Chalcraft et al. 2007; Agboton et al. 2013; Linet al. 2019); these studies often focus on whether predator and
parasite effects on pest species are additive, substitutive,
antagonistic, or synergistic in order to best accomplish biological
control of pest species (Roy et al. 2001; Zhang et al.2015; Lin et al. 2019). Measuring effects on population density
does generally require longer-term studies than those simply reporting
parasite outcomes, but the amount of additional time required varies
substantially with prey life history. The reporting of all three of
these outcome variables (prevalence, intensity, and density) will both
improve understanding of mechanisms in individual studies and facilitate
future synthetic and meta-analytic work on the subject.
In addition to measuring and reporting multiple parasitism outcome
variables, we also encourage researchers to measure and report as many
proximate predator effects as feasible. These proximate predator effects
include many of the intermediary mechanistic steps we detail above: prey
demography, prey immune function, and prey space-use behavior. Very few
predator-parasite studies report any proximate predator effects but
those that do are able to tell the clearest and most convincing stories
of predator-spreading mechanisms (e.g., Navarro et al. 2004;
Cáceres et al. 2009; Szuroczki & Richardson 2012). If
investigating a particular mechanism of predator-spreading, we hold it
is essential to measure the proximate predator effects that mediate that
mechanism. Moreover, because multiple predator-spreading mechanisms are
likely at play in any given system, future research would greatly
benefit from casting a wide net of measured proximate predator effects
when logistically feasible.
Nearly all predator-parasite studies include just two levels of
predation, typically presence/absence or high/low (Richards et
al. 2022), but it is well known that reducing a continuous spectrum of
a predictor variable to a binary is dangerous for inference (Inouye
2001). What may appear to be a clear positive or negative effect when
considered at just two levels may in fact be a complex non-monotonic
relationship. Predator-parasite studies that consider a broader range of
predation pressure levels have, in fact, found hump-shaped relationships
between predation and parasitism (Hawlena et al. 2010), as has
been predicted by theory (Holt & Roy 2007). It is also likely that some
predator-spreading mechanisms may operate most strongly at different
points on the predator-pressure spectrum. For example, behavioral
effects may respond strongly to the introduction of predators but weakly
to increases in predation pressure thereafter, whereas consumptive
effects may respond more linearly with increasing predation pressure. In
such a situation, multiple interacting predator-spreader effects may
produce unexpectedly non-linear relationships between predation pressure
and parasitism over the full spectrum of predation.