What explains variation in the strength of behavioral responses to predation risk? A standardized test with large carnivore and ungulate guilds in three ecosystems

Abstract

If access to food is affected by the risk of predation, then the number of individuals killed by predators is an incomplete measure of the limiting effect of predation. Nonetheless, it is often assumed that the costs of antipredator responses (risk effects) are either small enough to be ignored or positively correlated with direct predation, and thus unlikely to alter inferences based on predation rates. These assumptions are rarely tested. Here we studied five large carnivores and ten prey species in three Zambian ecosystems to test relationships between direct predation, antipredator vigilance and trade-offs with foraging. The presence of a predator caused vigilance to increase by a factor of 2.4, with substantial variation among prey species in the strength of this response. This was associated with a 28% decrease in the proportion of individuals foraging, a trade-off that was consistent across species. We detected no correlation between direct predation and the strength of antipredator responses, which undermines the gambit of ignoring risk effects. The strength of antipredator responses was uncorrelated with broad attributes of predators and environments, but was correlated with attributes of prey. Responses were stronger for small species and for browsers/mixed feeders relative to grazers. It has previously been noted that small ungulates face higher rates of direct predation. Building on this inference, our results suggest that carnivore loss/restoration will also have stronger behaviorally-mediated effects on small ungulates, particularly browsers and mixed feeders. If such species increase their representation where carnivores are depleted, then cascading effects on vegetation would be expected.

Fear of large carnivores is tied to ungulate habitat use: evidence from a bifactorial experiment

“…The growing emphasis on developing a better understanding of the interactions among multiple prey and predators within large carnivore—ungulate systems 15 , 26 , 57 is being driven, in part, by new methodologies to study behavior 10 . For example, using ABRs enabled us to test responses to playbacks during night and day on numerous species 38 .…”

Hidden Markov Models reveal a clear human footprint on the movements of highly mobile African wild dogs

“…Both variables describing human land use had strong effects on the probabilities of typical vs. fast movement. Outside the National Park in the GMAs (where prey density is known to be lower 63 , 66 ), wild dogs were significantly more likely to adopt the fast movements of State 3 (Figs. 6 and 7 C).…”

“…Faster movements in GMAs relative to the National Park probably have at least two causes. First, the densities of large herbivores are lower in the GMAs 62 , including impala and puku, which are most important prey of African wild dogs in the Luangwa Valley 66 . Lower prey density would be expected to translate into increased effort to locate and kill prey.…”

Reactive anti-predator behavioral strategy shaped by predator characteristics

“…Wildebeest, were less likely to flee from these threats, instead appearing to offset this response by increasing the amount of time spent monitoring the danger. The use of complementary anti-predator responses such as this would not have been detected if we had only examined a single behavioral metric (see [ 68 – 70 ]). Several authors have noted that anti-predatory behaviors should decrease levels of direct predation to the point that lethality becomes a poor proxy for predation threat [ 64 , 71 ], and studies in other large herbivore communities found that capture success fails to predict proactive anti-predator avoidance behaviors (e.g., [ 72 ]) and reactive levels of vigilance to predators within 0.5 km [ 59 , 69 ].…”

“…The physical and social environments may also shape anti-predator decision-making [ 57 , 68 , 70 ]. The distribution of resources across the landscape differs for browsers and grazers, forcing certain species to enter habitats of varying complexity [ 59 ] and/or that differ in underlying predation risk [ 57 ].…”