Project Title:
Optimal Foraging in a Generalist Snake Predator, Nerodia sipedon

Project Description (short):
Optimal foraging theory predicts that an organism should prey upon that food source that maximizes the net energy gained and minimizes the fitness costs associated with each foraging bout. Generalist predators increase prey availability, and theoretically energy availability, by increasing the diversity of prey species on which they will forage. We will model optimal foraging using Agent-Based Modeling (ABM). The objective of the study is to determine the net energy gain of N. sipedon feeding on different prey types (Longer description here.)

Skills needed:

Biology:

We expect a biology student to have had STAT 190 and BIOL 315 Physiology. We prefer a student who also has experience handling and caring for reptiles and amphibians.

Mathematics:

We expect a mathematics student to have had STAT 290, CS 170 or 180, and displays an eagerness to learn about Agent-Based Modeling. We prefer a student who has CS 171 or 181 or 185 or experience with a programming language suitable for running simulations (e.g. Java, Python, C++, Matlab, Octave).

Start Date:
January 2009

End Date:
December 2009

Mentors:
Prof. Chad Montgomery (Biology) chadmont@truman.edu
Prof. Phil Ryan (Mathematics), pryan@truman.edu

About Prof. Montgomery:

Dr. Montgomery received his B.S. in Biology from Truman State University and has recently returned as an assistant professor in Biology. Dr. Montgomery received his M.A. thesis degree from the University of Northern Colorado, where he studied clinal variation in Texas horned lizards. After receiving his M.A., he attended the University of Arkansas to study the effects of foraging mode on life history in copperheads and timber rattlesnakes for his PhD. Dr. Montgomery then moved to Panama as part of his postdoctoral work examining the effects of amphibian decline on snake communities. Dr. Montgomery still conducts research in Central America, including a project examining body size variation in boa constrictors on islands off of the north coast of Honduras. Dr. Montgomery travels extensively throughout Central America and when back in the U.S. enjoys spending time with his family in St. Louis.

About Prof. Ryan:

Dr. Ryan was born and raised in Canberra, Australia where he received his B.Sc. and M.Sc. in Mathematics from the Australian National University. In 1991 he moved to the U.S. where he completed his PhD (1997) in Mathematics at the University of California at Berkeley. In 1999, he started teaching at Truman in 1999 and his research interests has evolved to using Mathematics in interdisciplinary projects, particularly with Biology, Art, and/or History. He has a six year old son, Donal, who loves animals.  He loves good books and movies.

Project Description (long):

Optimal foraging theory predicts that an organism should prey upon that food source that maximizes the net energy gained and minimizes the fitness costs associated with each foraging bout. The net energy gained from a given meal is a function of energy consumed minus the cost of prey handling and digestion. Energy ingested may vary due to differences in body composition and body size, with endotherms typically having higher energy content per gram than ectotherms. Ultimately however, all of the energy ingested is not absorbed by the predator. Digestibility of a particular prey item, or digestive efficiency of that prey item, may vary based on predator size, prey size, and prey type. Prey type effects DE due to differences in prey shape and body covering. The digestive efficiency (DE) of a predator consuming a particular prey item is the proportion of energy ingested that is absorbed by the predator ((E_in – E_out)/E_in). Therefore, gross energy available to a predator from any given meal is a function of energy content of the prey item and the digestive efficiency of the predator feeding on that prey item.

The energetic costs of foraging include prey handling and digestion. Prey handling is the process of capturing and consuming a prey item. Prey handling can be energetically expensive and may result in large fitness costs. Prey handling costs vary based on prey type due to differences in body structure, locomotion, defense mechanisms, prey size, and habitat. The energetic cost of digestion, which is known as specific dynamic action, can account for up to 25% of the annual energy budget of an organism. SDA is affected by predator size, prey size, prey quality, and potentially temperature.

Generalist predators increase prey availability, and theoretically energy availability, by increasing the diversity of prey species on which they will forage. However, not all prey are created equally. Prey species differ in abundance, catchability, energy content, digestibility, and energetic cost of digestion. Therefore, understanding these aspects of prey species available to a generalist predator will allow us to better understand foraging and optimal foraging theory. Water snakes, Nerodia sipedon, are locally abundant, medium sized (~ 1.0 m), semi-aquatic snakes that prey on a wide variety of prey, including fish, rodents, frogs, tadpoles, and lizards. N. sipedon make a good model organism for examining optimal foraging because they are easily maintained and easily manipulated in the laboratory.

We will model optimal foraging using Agent-Based Modeling (ABM). ABM, a relatively new computational paradigm, uses autonomous individuals, called agents. Each agent individually assesses its situation ands makes decisions to interact with each other and with its environment on the basis of a set of simple local rules. These local rules incorporate physiological and behavioral decisions and are capable of incorporating a great deal of complexity. The model should provide us with insights into the physiological and evolutionary mechanisms that underlie foraging.

The objective of the study is to determine the net energy gain of N. sipedon feeding on different prey types. Using this information we will be able to model foraging to determine the optimal prey type for N. sipedon under conditions of variable prey abundance in the environment. Previous work in our lab indicates that DE is high for water snakes feeding on fish, however fish are low in energy content relative to other prey types.

Methods: We will determine net energy gain by assessing energy content, prey handling costs, digestive efficiency, and specific dynamic action of N. sipedon feeding on three different prey types (fish, tadpoles, frogs). Energy content of prey will be determined using bomb calorimetry. Prey handling costs will be determined by timing feeding trials to determine duration of foraging bouts as a caveat for energetic cost. Digestive efficiency will be determined through feeding trials, where a known mass of prey is fed to a snake and the undigested material is collected and analyzed. Specific dynamic action will be assessed by feeding a known mass of prey to a snake and measuring the O2 consumption during digestion.

References:

• Grimm, V., and S. F. Railsback. 2005. Individual-based modeling and ecology. Princeton University Press, Princeton, New Jersey.
• Grimm, V., E. Revilla, U. Berger, F. Jeltsch, W. M. Mooij, S. F. Railsback, H.-H. Thulke, J. Weiner, T. Wiegand, and D. L. DeAngelis. 2005. Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310:987-991.