Moving forward
In a recent review, Sheriff et al. (2020) emphasized the need to better
understand how ecological and environmental context interact with prey
responses to predation risk. Focusing on anti-predator behavior, we
address this knowledge gap in two ways. First, our review sheds new
light on NCEs by showing when and how contingency can arise from
properties of the prey, the predator, and the setting as these effects
unfold across three phases (prey risk perception; prey responses to
perceived risk; impacts of these responses on other species). Second,
our synthesis of the ‘hunting mode-habitat domain’ and ‘evasion
landscape’ concepts offers a unified framework for predicting the form
and magnitude of anti-predator behavior during phase two. Looking ahead,
we highlight two knowledge deficiencies that require attention if we are
to develop a coherent framework for predicting how NCEs propagate
through ecosystems. First, there is insufficient exploration of
context-dependent indirect NCEs during phase three. Second, there is
need for research focused on the ways in which direct and indirect NCEs
are shaped simultaneously, or even interactively, by multiple drivers of
context dependence.
Drawing from a broad literature spanning diverse taxa and ecosystems,
our review reveals how contingencies in NCEs can arise as a result of
many factors. It is hardly surprising, then, that studies have revealed
so much variation with respect to whether, and in what way, NCEs
manifest in communities (Moll et al . 2016; Gaynor et al .
2019; Prugh et al . 2019). We clarify these factors by grouping
them into three broad categories: (1) prey properties influencing
detection of and responses to risk; (2) predator properties shaping
their detectability and lethality; and (3) properties of the setting
influencing the prey’s scope for predator detection and countermeasures.
We also emphasize that there is great potential for interplay among
them. For example, divergent responses to predators with disparate
hunting modes could disappear if declining food supply limits prey
capacity for defensive investment. Similarly, because prey often have
multiple defenses whose efficacies are context-specific (Brittonet al . 2007; Wirsing et al . 2010; Creel 2018), sympatric
prey may respond divergently to a shared predator in one setting but
similarly in another, depending on the availability of landscape
features facilitating particular responses (i.e., the evasion
landscape). Moreover, the latter two give rise to an emergent fourth
driver, (4) the timing of predation risk, and prey properties then
determine how individuals respond to this temporal dimension of danger
(Box 3 ). By implication, predictions based on one driver of
contingency, or a single NCE pathway (Preisser & Bolnick 2008), may
provide an incomplete picture of the impacts of predation risk on prey
populations and communities. Rather, examination of NCEs requires
thorough consideration of the functional properties of interacting
predator and prey species, as well as the circumstances under which
these interactions occur (Heithaus et al . 2009; Creel 2011;
Schmitz 2017). Fortunately, many of these natural history or
environmental details are attainable (Wirsing et al . 2010),
especially given new approaches (e.g., animal-borne video, camera traps,
drones) that facilitate placing behavioral data in context (Mollet al . 2007; Wirsing & Heithaus 2014).
Our review also highlights the staged manner in which NCE contingencies
can manifest. Namely, prey anti-predator investment may vary intra- and
inter-specifically as a function of differences in sensory perception
(phase one) and the form of any deployed countermeasures (phase two);
contingent outcomes during either of the first two phases then determine
if, and how, indirect NCEs emerge during phase three. Across taxa, then,
prey with greater sensory ability should experience and transmit larger
NCEs. Furthermore, the phase in which context dependence arises shapes
how the outcome of non-consumptive predator-prey interactions will
respond to perturbation. For example, landscape changes that reduce prey
sensory ability are likely to diminish NCEs, whereas those raising the
frequency of encounters with predators by restricting prey habitat
domains may elicit increased anti-predator defense during phase two
(Schmitz et al . 2004) and elevate the potential for indirect NCEs
in phase three. Thus, studies exploring phase-specific mechanisms by
which prey, predator, and landscape properties shape anti-predator
investment are crucial to forecasting NCEs in a changing world.
By synthesizing the work and concepts of Heithaus et al . (2009)
and Schmitz et al . (2017a), we present a new framework that
integrates prey, predator, and landscape traits to anticipate the form
and magnitude of anti-predator behavior. This framework is broadly
applicable, as evidenced by its ability to retrospectively explain
differences in behavioral countermeasures that have been observed in the
field across a range of taxa. Consistent with scenario one (Fig.
4c ), for example, prey species whose habitat domains are nested within
those of tiger sharks manifest chronic vigilance and space use that
facilitates their escape strategies (Heithaus et al . 2012), save
when in depressed energetic states (Heithaus et al . 2007).
Similarly, white-tailed deer whose domains fall within the larger
movements of gray wolves exhibit space use changes within their home
ranges facilitating their means of predator evasion (Dellinger et
al . 2019). By contrast, sympatric mule deer practice chronic predator
avoidance by shifting to refugia within their domains that are little
used by wolves (scenario three; Fig. 4b ). For both ungulates,
the consumptive effects of wolves appear to be limited (Dellingeret al . 2018). In the Greater Yellowstone Ecosystem, USA, elk
(Cervus canadensis ) and wolves have large, overlapping domains,
leading to low encounter rates (Cusack et al . 2020). Thus,
consistent with scenario four (Fig. 4d ), elk in this system
appear to predominantly experience the consumptive effects of wolves
(Peterson et al . 2014) and typically exhibit evasive behavior
only during risky times (e.g., Cusack et al . 2020). Larger elk
survive many encounters with wolves via resistance (Mech et al .
2015), further contributing to their tendency to experience consumptive
rather than non-consumptive wolf impacts. In an African system with
multiple sympatric predators, prey consistently select for habitats
offering a lower probability of lethal predator encounters, suggesting
that chronic evasive behavior (under scenarios one and three) may be
common where overlapping predator domains preclude outright avoidance
(Thaker et al . 2011). Accordingly, it underscores
characterization of habitat domains and evasion landscapes as a critical
first step in forecasting the extent to which, and how, prey should
respond behaviorally to perceived risk during phase two and transmit
indirect NCEs in phase three. Our framework also highlights the need to
discriminate among prey individuals relying principally on evasion
versus resistance, given that prey expressing the latter group of
behaviors are less likely to respond to the threat of predation unless
the cue is acute and, consequently, to experience and transmit NCEs.
Finally, it gives rise to new hypotheses. For example, in any scenario
where predators cannot be avoided spatially and encounters are high
enough to warrant anti-predator investment, we might nevertheless expect
vigilance and space use that facilitates evasion to relax in prey
species that are instead able to avoid the predator(s) temporally (Kohlet al . 2019).
Our survey revealed two knowledge gaps that represent fruitful
directions for future research. First, whereas there is ample evidence
for context dependence during phases one and two, few studies have
rigorously examined contingency in the propagation of indirect NCEs.
There are notable examples, including the role of predator hunting mode
in shaping indirect NCEs of spiders on plant and soil properties
(Schmitz et al . 2017b), and the impact of prey refugia on
indirect non-consumptive relationships between crabs and barnacles
(Trussell et al . 2006). These studies offer a template for
expanded scrutiny of contingencies in NCEs during phase three, which
will improve our understanding of when and how predators initiate
indirect effects by altering prey traits.
Second, a growing literature underscores the importance of
simultaneously considering multiple drivers of contingency in NCEs. For
example, anti-predator investment by mud crabs varied with their
personality (bold versus shy) and predator hunting mode (actively
hunting blue crabs versus sit-and-wait toadfish, Opsanus tau )
(Belgrad & Griffen 2016). Thaker et al . (2011) showed that small
members of an African ungulate guild avoided all predators whereas their
larger counterparts avoided sit-and-pursue but not active hunters. More
work is needed, however, particularly on the importance of three-way
interactions among factors drawn from the aforementioned groups.
There are also studies suggesting that interactive impacts of multiple
contingent drivers may act collectively to shape indirect NCEs during
phase three. For example, Murie & Bourdeau (2019) speculated that,
compared to the strong effects initiated by slow-moving sea stars, the
absence of direct and indirect non-consumptive effects of crabs and
octopuses on snail grazing and kelp, respectively, might owe to the
inability of snails to escape these vagile predators. Thus, more mobile
prey species with greater scope for avoidance may have responded
equivalently to all three predators, yielding similar rather than
predator-specific cascades of NCEs. The possibility that interactions
between context dependent factors might modify cascading NCEs has not
been tested empirically, however, and thus remains as an exciting
research frontier.