I studied why animals behave the way they do. Animals respond to their environment and to their own physiology. My PhD research explored how interactions between the two drive animal foraging behavior. I focused on changes in prey foraging in response to predator threats across diverse environmental conditions and prey animals.
The field of metabolic ecology changed the way I think about the world.
The bodies of all living organisms must do work to stay alive (e.g., breathe to transport oxygen, convert food to usable energy). Our metabolism is the rate at which our bodies do work. Animal metabolism scales with animal size, caloric requirements, growth, reproduction, even behavior. The most mind-blowing to me… the density of mitochondria (energy producing organelles) within each cell and the whole body, scales with metabolism.
So, based on an animal’s metabolic rate, we can predict so many things about that animal from its cellular structure to its eating behavior. And we can do this across diverse animals from insects to fish to mammals (including humans). The scaling is the same.
I think about what this means (and has meant) for evolution. There is unbelievable animal diversity in the natural world. Perhaps it all came about within very tight physiological constraints because of these relationships between body size and function and behavior. A change in one likely means predictable changes in others. The data suggest that deviation from some of these relationships (breaking from the constraints) is physiologically and evolutionarily impossible. It seems, incredible diversity emerged from very strict rules of metabolic ecology.
Photo Credit: Daryl L. Hunter
Broad ecological patterns (such as metabolic ecology) allow us to predict aspects of animal physiology, behavior and evolution across diverse types of animals. These predictions across diversity flesh out the broad brush strokes of how the world generally works. Identifying differences among diverse animals allows us to account for deviations from these broad patterns and better appreciate the details of the diversity around us.
Different animals have unique sensory systems through which they experience their environment. Humans rely heavily on sight. Dogs rely mostly on smell. Flying bats use sound (echolocation) to navigate through the air, and some insects (e.g., leaf hoppers) interpret vibrations of the plants underneath them. When we walk outside, we can see that many different types of animals exist in close proximity to one another. They share the same environment, but they experience that environment very differently. An animal’s perceptual environment is its Umwelt (oomvelt). Our human-centric perception of the world can be a handicap when studying how other animals interact with their environment. It’s useful and a lot of fun to think about what it’s like to be something else, to experience as something else.
Prey animals must eat without being eaten. For prey, foraging often requires using risky areas where they are more vulnerable to predators and foraging often reduces their awareness of their surroundings. Prey can’t have their head down foraging and up watching for predators at the same time. So, when prey detect a predator threat, they often reduce foraging.
For given prey animals, the extent to which prey reduce foraging under risk is influenced by environmental conditions (food availability, predator threat severity) and prey traits (hunger, experience). But, it remains unclear, whether these patterns hold across diverse types of animals. For example:
Metabolism drives energy requirements. Do higher energy requirements limit the extent to which prey reduce foraging under risk?
Animals farther from the equator generally have less food available to them. Do animals farther from the equator limit the extent to which they reduce foraging under risk?
To address questions like these I conducted a meta analysis of over 100 experiments that quantified changes in prey foraging in response to cues of predation risk in animals from mayflies to mule deer.
Humans generally eat at predictable times during the day and make dining choices based upon food quality, cost, proximity and ease of travel. Animals are similar. When and where animals forage can depend upon levels of predation risk, food availability and the animal’s energy requirements. However, many details remain unclear. For example:
Do skinnier animals forage more at the start of the day and if so, how do levels of food and risk influence their choices?
Do skinnier animals expose themselves to more risk to forage and if so, are they more likely to be eaten? Does reduced food availability exacerbate this pattern?
How low do the costs of travel (exposure to predators and energy expenditure) need to be to for prey to travel farther for more food?
Nuanced questions such as these can be challenging to address in the natural world. I chose a modeling approach. I first generated optimization models that identified optimal foraging choices in myriad foraging contexts (including combinations of predation risk, food availability and prey energy requirements). I then generated simulation models that assessed the survival consequences for animals that made optimal foraging decisions. I chose to model insectivorous prey (e.g., many birds, frogs, lizards). Some of my model assumptions could be relaxed to expand the model’s application to different types of animals.
My master’s research focused on the effects of drought on female pheasant body condition and stress hormones. In the Midwest, droughts are becoming more frequent and more severe with the changing climate. It’s not clear how these droughts influence wildlife. Pheasants are a popular upland game bird in Nebraska. We assessed how drought influenced pheasant physiology. We conducted a two-year, multi-site study in which we measured female pheasant body condition (bird BMI) and stress hormone levels before and after a severe drought. We found that after the drought birds were thinner and thinner birds had higher stress hormone levels. Our results suggest that droughts, which are intensifying with climate change, reduce pheasant body condition and increase pheasant stress hormone levels, both of which likely limit reproduction and consequently pheasant abundance in the Midwest.
Brown, J. H., J. F. Gillooly, A. P. Allen, V. M. Savage and G. B. West. 2004. Toward a metabolic theory of ecology. Ecology 85: 1771 - 1789.
Sibly, R. M., J. H. Brown and A. Kodric-Brown. 2012. Metabolic ecology: a scaling approach. Wiley-Blackwell, Hoboken, New Jersey, USA.
West, G. B., W. H. Woodruff and J. H. Brown. 2002. Allometric scaling of metabolic rate from molecules and mitochondria to cell and mammals. PNAS 99: 2473 - 2478.
Van Dyke, H. 2011. Changing organisms in rapidly changing anthropogenic landscapes: the significance of the ‘Umwelt’-concept and functional habitat for animal conservation. Evolutionary Applications 5: 144 - 153.
von Uexkull, J and J. D. O’Neil. 2010. A foray into the worlds of animals and humans: with a theory of meaning. University of Minnesota Press, Minneapolis, Minnesota, USA.