Figure Legends
Fig. 1 . Flow chart, adapted from Figure 1 in Lima & Dill
(1990), conceptualizing the process by which direct and indirect
non-consumptive predator effects (NCEs) may manifest. (a ) Phase
one. Each point in space and time is characterized by some value of
intrinsic predation risk, or danger, defined after Lank & Ydenberg
(2003) as the inherent probability that an individual will become a prey
item given no, or a standard amount of, anti-predator investment. Danger
may or may not be perceived; in the latter case, no NCE will precipitate
from the danger cue in question. (b ) Phase two. Given that the
forager perceives risk cues, does it respond? Danger that is perceived
may nevertheless fail to elicit a response of sufficient magnitude to
trigger a NCE. Though not the focus of this review, prey individuals
that do respond to perceived danger may experience stress, which may in
turn affect fitness and consequently lead to risk effects. Furthermore,
prey individuals that perceive danger may seek to manage their risk of
predation through behavioral modifications, whose costs in terms of time
and energy determine the magnitude of any associated risk effects.
(c ) Phase three. Given that the forager responds to the cues,
does the response induce an indirect interaction? Risk effects flowing
from predator-induced stress and risk management can reduce prey
population size and, in turn, trigger indirect interactions if changes
to prey abundance affect other members of the community. The nature and
strength of predator-induced risk management by prey can also determine
whether and how other species in the community are affected indirectly;
namely, if additional species are impacted by prey risk management, then
NCEs can propagate through communities in the form of indirect
interactions that are transmitted by prey behavior.
Fig. 2 . Observed (solid arrows) and hypothesized (dashed
arrows) relationships between gray wolves (Canis lupus ) and two
sympatric ungulates – mule deer (Odocoileus hemionus ) and
white-tailed deer (O. virginianus ) – in areas of eastern
Washington, USA, located outside (a , c ) and inside
(b , d ) wolf pack territories. Non-consumptive effects of
wolves on prey behavior (relative to wolf-free sites; a ) are
depicted in b , whereas c and d display baseline and
wolf-influenced trophic relationships between the herbivores and the
plants they target, respectively. Increasing effect size corresponds
with arrow thickness. Mule and white-tailed deer are morphologically
similar but have different running gaits (Lingle 1993). When threatened,
mule deer flee by stotting, a bounding gait that limits speed on flat
ground but facilitates navigation of uneven terrain and obstacles.
White-tailed deer flee danger by galloping, a swift means of moving over
gentle terrain that is less effective where the ground is more sloped or
broken. This disparity explains differences in the space use of these
two deer species that emerge when they are exposed to the risk from wolf
predation during phase two (b versus a ). Working in a
system in eastern Washington, USA, Dellinger et al . (2019) found
that wolf presence elicited elevated use of sloped terrain by mule deer
(b ; heavy arrow), presumably because the uneven ground
characterizing these uplands confers an advantage to bounding prey
seeking to escape coursing wolves. White-tailed deer space use differed
comparatively little as a function of wolf presence, with individuals
exposed to wolf risk manifesting small-scale shifts within their home
ranges toward flat ground and roads that actually led to increased
overlap with wolves (b ; thin arrow). By inference, white-tailed
deer were able to manage risk ‘in place’ because of spatial synchrony
between the effectiveness of their galloping means of escape and the
space use pattern of their coursing predator. Notably, this form of risk
management is expected whenever the safety benefits of matching predator
distribution that accrue from escape facilitation outweigh the costs
associated with elevated encounter probability (Lima 1992). These
divergent anti-predator responses raise the possibility of recolonizing
wolves triggering prey-specific indirect NCEs on plants during phase
three (c versus d ). In this ecosystem, mule and
white-tailed deer exhibit considerable dietary overlap, though mule deer
rely more heavily on upland shrubs (e.g., serviceberry;Amelanchier spp), and white-tailed deer exploit lowland riparian
vegetation (e.g., willow; Salix spp.) to a greater degree (A.
Craig, unpublished data ). Given that they elicit broad-scale
spatial shifts by mule deer, wolves may dampen the impact of mule deer
on lowland plant species (d ; thin dashed arrow) while
strengthening this species’ effects on upland plants growing in areas
with steeper slopes (d ; thick dashed arrow). By contrast, the
absence of a strong spatial response by white-tailed deer in areas
occupied by wolf packs suggests that wolves may have modest and
localized (i.e., within existing home ranges) indirect effects on the
plants exploited by this deer species (similarity in the thickness of
the solid and dashed arrows in c and d ).
Fig. 3 . Observed (solid arrows) and hypothesized (dashed
arrows) relationships between tiger sharks (Galeocerdo cuvier ),
their air-breathing prey – dugongs (Dugong dugon ), dolphins
(Tursiops cf. aduncus ), green turtles (Chelonia
mydas ), sea snakes (Disteria major ; not pictured), pied
cormorants (Phalacrocorax varius ) – omnivorous fish
(Pelates octolineatus ), and seagrasses within shallow
(<4.5m water depth) habitats in Shark Bay, Western Australia.
Species interactions are depicted during times when tiger sharks are
present and absent from the bay, and interaction effect sizes correspond
with arrow thickness. When tiger sharks are present, they preferentially
spend time over shallow banks (Heithaus et al . 2002). Within
these shallow habitats, they spend more time over bank edges compared to
interior areas of banks (Heithaus et al . 2006). Non-consumptive
direct effects of sharks on prey behavior (phase two) are black lines,
whereas indirect relationships between tiger shark prey and lower
trophic levels are gray lines (phase three). Dugongs (Wirsing et
al . 2007), cormorants (Heithaus et al . 2009), dolphins (Heithaus
& Dill 2006), and sea snakes (Wirsing & Heithaus 2009) distribute
themselves between edge and interior portions (microhabitats) of shallow
banks roughly proportional to food abundance when tiger sharks are
absent. When sharks are present, by contrast, these species, along with
green turtles (Heithaus et al . 2007), shift among the two
microhabitats to enhance safety. Their spatial shifts during phase two,
however, are based on species-specific escape tactics. Green turtles,
dugongs, and dolphins escape through sub-surface flight and rely on
maneuverability that is constrained over interior portions of banks.
Accordingly, these species move into bank edges when tiger sharks are
present to facilitate escape even at the cost of higher encounter rates
with sharks (Heithaus et al . 2009). Conversely, sea snakes, which
are unlikely to escape a tiger shark, and cormorants, which escape by
flying away, shift toward interior areas of banks where shark encounters
are minimized. For green turtles, habitat use is state-dependent with
turtles in better condition selecting safer areas of banks with less
food (Heithaus et al . 2007). Experimental studies of herbivory
(Burkholder et al . 2013; Bessey et al . 2016) show that
these spatial shifts cascade to seagrass communities during phase three.
Fig. 4. Framework integrating the ‘hunting mode-habitat domain’
and ‘evasion landscape’ concepts to predict the nature and strength of
direct NCEs on prey populations. Once predation risk is perceived (phase
two), four different patterns of anti-predator behavior can emerge
depending on the overlap between predator ( ) and prey ( ) domains
across the landscape ( ) and spatial variability in the effectiveness of
the evasion tactic used by the prey species (i.e., the evasion landscape
, with darker interior colors representing higher evasion efficacy). For
each combination of domain overlap and evasion landscape
(a -d ), magnitudes of different anti-predator responses –
vigilance only ( ), vigilance plus evasive behavior ( ), spatial shifts
( ), and resistance or responses of individuals in compromised or naïve
states, ) as a function of the immediacy of perceived predation risk
(from low to high with intermediate values representing an encounter
situation) are depicted under ‘Anti-predator Response’. (a ) When
predator and prey habitat domains are narrow and overlapping, and the
probability of predator encounter is high, two scenarios are possible:
if a prey’s evasion landscape is heterogeneous, allowing it to spatially
modify the efficacy of its evasion tactic, then it should exhibit
chronic vigilance coupled with evasion facilitation by moving to space
where its tactic is most effective; if its evasion landscape is
homogenous, then the prey individual should be vigilant when risk
immediacy is low and only engage in vigilance plus evasive behavior when
perceived risk is immediate (i.e., when a predator has been encountered
because the efficacy of evasion does not depend on the prey individual’s
location at the time of the encounter). (b ) Prey with broad
domains should seek refuge by shifting space use (dashed intermediate
gray line) when facing predators with a narrow domain, irrespective of
the type of evasion landscape. (c ) Prey individuals with narrow
domains that fall within a broad predator domain should behave similarly
to those in (a ), given the absence of a spatial refuge and that
the predator is likely to converge on the prey, leading to high
encounter rates. (d ) When predator and prey share broad,
overlapping domains, low encounter rates lead prey to jointly invest in
vigilance and evasive behavior only when the immediacy of perceived risk
is elevated (a predator has been encountered), irrespective of the
evasion landscape. In all cases, prey individuals that 1) rely
exclusively on resistance to repel predators, 2) are constitutively
defended, 3) are in a compromised energetic state, or 4) are naïve with
respect to predators are expected to invest minimally in anti-predator
behavior ( ), save perhaps when perceived risk is acute (during an
attack; ).