Urbanization alters predator‐avoidance behaviours

Urbanisation is changing the natural landscape at a global scale. This obviously alters habitat structures, but what is the influence on predator-prey dynamics? A recent paper in the Journal of Animal Ecology studied two urban prey species to examine whether urbanisation changed their predator-avoidance behaviour. Lead author Dr Travis Gallo, an Urban Wildlife Postdoctoral Researcher at the Urban Wildlife Institute, Lincoln Park Zoo, tells us more. 

It’s easy to recognize that urban environments are quite different from the rural or natural landscapes ecologists have historically studied. Thus, urban ecologist have long stated that traditional ecological principles should be adjusted or fine-tuned to better fit urban ecosystems. For example, continuously maintained landscapes in cities stabilize primary productivity and reduce the ‘dynamic’ part of the well-studied principles of top-down and bottom-up trophic dynamics. Along those same lines, we became interested in the role that cities and their unique characteristics play in predator-prey dynamics.

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A coyote out in the open in Chicago (Photo: Julie Fuller)

In a study recently published in the Journal of Animal Ecology, we explored predator-avoidance behaviors of two common mammal species – eastern cottontail (Sylvilagus floridanus) and white-tailed deer (Odocoileus virginianus) in the highly urbanized landscape of Chicago, IL USA. Contrary to what one might expect, we found that coyotes (Canis latrans) – a natural predator – had little influence on predator-avoidance behaviors of either species in the more urbanized areas of Chicago.

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White-tailed deer doe and fawn (Photo: Urban Wildlife Institute)

But first let’s step back and offer a little context. Typically, the presence of a predator influences the distribution and behavior of prey species. One might expect that prey, if able, would first and foremost avoid habitat patches that contain predators. But our expectations for this outcome were derived from more natural systems — so how might this relationship change in a city? Habitat patches in urban environments are typically spaced far apart and embedded in a matrix of houses, businesses, and roads. The roads and buildings between habitat patches could restrict an animal’s ability to move between them. As a result, it may be all the more difficult for prey to ‘pack up and move’ if they so happen to encounter a predator. Therefore, we predicted that urban prey might be forced to occupy the same habitat patches as predators. If this were the case, we predicted that prey would change their daily activity schedules or increase their vigilance to avoid interactions with predators. But again, human development and human activity in and around an urban habitat patch might alter a species ability to perform such predator-avoidance behaviors.

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Remotely-triggered wildlife cameras around Chicago allowed a sneak peek into predator-prey dynamics of local wildlife (Photo: Urban Wildlife Institute)

Using photos collected from over 100 remotely triggered wildlife cameras placed across the greater Chicago region, we first assessed whether deer and cottontails were more likely to occupy the same habitat patches as coyotes – or were they avoiding them across the landscape? Additionally, we used the time of day each picture was taken to explore whether deer and cottontails changed their daily activity patterns when coyotes were present within a habitat patch. And finally, in each picture of deer and cottontail we identified whether the individual animal had their head up in a vigilance posture or down in foraging posture, and used that information to assess whether the presence of coyotes increased their rate of vigilance.

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An eastern cottontail displaying vigilance (Photo: Urban Wildlife Institute)

 

Contrary to our prediction – that prey species would likely be constrained to the same habitat patch as coyotes – we found no evidence of spatial aggregation, nor did we find any evidence of spatial avoidance. Both deer and cottontails were spatially distributed independent of where coyotes were present. Additionally, we found that neither species changed their daily activity schedules when coyotes were present. Our most interesting finding was that cottontails had their highest rates of vigilance when coyotes were absent from the most urban sites. Even when coyotes had a low probability of being at a site, cottontails were still on their toes! In Chicago, these highly urban habitat patches (e.g., city parks, golf courses, cemeteries) are often visited by people and in many cases people with their pets (sometimes untethered). While these urban green spaces may provide a refuge from coyote (i.e. a human-shield effect), they likely come with tradeoffs in the form of increased interactions with humans and their pets. As a result, their vigilance rates are high in urban areas even when coyotes are not around. Conversely, as sites became less urban we began to see a shift back to expected vigilance behaviors, and rabbits were more vigilant when coyotes were present in the less urban areas.

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Cemetaries are highly-urban habitat patches, regularly visited by people (Photo: Urban Wildlife Institute)

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As well as people, wildlife also come across pets (Photo: Urban Wildlife Institute)

These results indicate that urban ecosystems are still fear driven systems, but perhaps, the fear inducing agents are now anthropogenic in nature. Traditionally we think of predator-prey dynamics in the context of two interactions – predators and prey. But in urban ecosystems we must begin to think of it as a three-player game – predators, prey, and people. Thus, we should begin to explicitly consider people in our ecological equations – especially in urban ecosystems. Doing so will improve our predictions, advance our understanding of urban ecology, and increase our ability to conserve biodiversity on an urbanizing planet.

More Info:

Gallo et al. (2019) Urbanization alters predator‐avoidance behaviours. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.12967

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