Recolonization of predators to their former ranges is becoming increasingly prevalent. Such recolonization places predators among their prey once again; the latter having lived without predation (from such predators) for a considerable time. This renewed coexistence creates opportunities to explore predation ecology at both fundamental and applied levels. We used a paired experimental design to investigate white‐tailed deer risk allocation in the Upper and Lower Peninsulas (UP and LP) in Michigan, USA. Wolves are functionally absent in the LP, while deer in the UP coexist with a re‐established wolf population. We treated 15 sites each in UP and LP with wolf olfactory cues and observed deer vigilance, activity, and visitation rates at the interface of habitat covariates using remote cameras. Such a paired design across wolf versus no‐wolf areas allowed us to examine indirect predation effects while accounting for confounding parameters such as the presence of other predators and human activity. While wolf urine had no effect across most metrics in both UP and LP, we observed differences in deer activity in areas with versus without wolves. Sites treated with wolf urine in the UP showed a reduction in crepuscular deer activity, compared to control/novel‐scent treated sites. Furthermore, we observed a strong positive effect of vegetation cover on deer vigilance in these sites. This indicates that simulated predator cues likely affect deer vigilance more acutely in denser habitats, which presumably facilitates predation success. Such responses were however absent among deer in the LP that are presumably naïve toward wolf predation. Where human and non‐human predators hunt shared prey, such as in Michigan, predators may constrain human hunting success by increasing deer vigilance. Hunters may avoid such exploitative competition by choosing hunting/bait sites located in open areas. Our results pertaining to fundamental predation ecology have strong applied implications that can promote human–predator coexistence.
- Award ID(s):
- 1810586
- NSF-PAR ID:
- 10298981
- Editor(s):
- Yue, Bi-Song
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 16
- Issue:
- 8
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0256147
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract -
Introduction: Predators can affect prey not only by killing them, but also by causing them to alter their behavior, including patterns of habitat selection. Prey can reduce the risk of predation by moving to habitats where predators are less likely to detect them, less likely to attack, or less likely to succeed. The interaction of such responses to risk with other ecological processes remains relatively unstudied, but in some cases, changes in habitat use to avoid predation may be constrained by competition: larger, dominant competitors should respond freely to predation risk, but the responses of smaller, subordinate competitors may be constrained by the responses of dominant competitors. For large grazing herbivores, an alternative hypothesis proposes that smaller prey species are vulnerable to more predators, and thus should respond more strongly to predation risk. Methods: Here, we tested these two hypotheses with 775 observations of habitat selection by four species of obligate grazers (zebra, wildebeest, puku and oribi) in the immediate presence or absence of four large carnivores (lion, spotted hyena, African wild dog and cheetah) in three ecosystems (Greater Liuwa, Greater Kafue and Luangwa Valley). Patterns of predation within this set were described by observation of 1,105 kills. Results:Our results support the hypothesis that responses to predation risk are strongest for larger, dominant competitors. Even though zebras were killed least often, they showed the strongest shift into cover when carnivores were present. Wildebeest, puku and oribi showed weaker habitat shifts, even though they were more frequently killed. These patterns remained consistent in models that controlled for differences in the hunting mode of the predator (stalking, coursing, or intermediate) and for differences among ecosystems. There was no evidence that smaller species were subject to predation by a broader set of predators. Instead, smaller prey were killed often by smaller predators, and larger prey were killed often by larger predators. Discussion: Broadly, our results show that responses to predation risk interact with interspecific competition. Accounting for such interactions should help to explain the considerable variation in the strength of responses to predation risk that has been observed.more » « less
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Abstract Landscapes of fear describe a spatial representation of an animal's perceived risk of predation and the associated foraging costs, while energy landscapes describe the spatial representation of their energetic cost of moving and foraging. Fear landscapes are often dynamic and change based on predator presence and behaviour, and variation in abiotic conditions that modify risk. Energy landscapes are also dynamic and can change across diel, seasonal, and climatic timescales based on variability in temperature, snowfall, wind/current speeds, etc.
Recently, it was suggested that fear and energy landscapes should be integrated. In this paradigm, the interaction between landscapes relates to prey being forced to use areas of the energy landscape they would avoid if risk were not a factor. However, dynamic energy landscapes experienced by predators must also be considered since they can affect their ability to forage, irrespective of variation in prey behaviour. We propose an additional component to the fear and dynamic energy landscape paradigm that integrates landscapes of both prey and predators, where predator foraging behaviour is modulated by changes in their energyscape.
Specifically, we integrate the predator's energy landscape into foraging theory that predicts prey patch‐leaving decisions under the threat of predation. We predict that as a predator's energetic cost of foraging increases in a habitat, then the prey's foraging cost of predation and patch quitting harvest rate, will decrease. Prey may also decrease their vigilance in response to increased energetic foraging costs for predators, which will lower giving‐up densities of prey.
We then provide examples in terrestrial, aerial, and marine ecosystems where we might expect to see these effects. These include birds and sharks which use updrafts that vary based on wind and current speeds, tidal state, or temperature, and terrestrial predators (e.g. wolves) whose landscapes vary seasonally with snow depth or ice cover which may influence their foraging success and even diet selection.
A predator perspective is critical to considering the combination of these landscapes and their ecological consequences. Dynamic predator energy landscapes could add an additional spatiotemporal component to risk effects, which may cascade through food webs.
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0256147
