Date of Submission

Spring 2015

Academic Programs and Concentrations

Biology; Mathematics

Project Advisor 1

Bruce Robertson

Project Advisor 2

Csilla Szabo

Abstract/Artist's Statement

When the fitness detriment associated with a habitat becomes decoupled from the cues organisms associate with habitat quality, the habitat is deemed an ecological trap. These traps can pose severe threats to affected populations, and hold the potential to cause extinction events if not corrected. Here we characterize the evolutionary implications of stochastic ecological traps. That is, when a novel environment (generally anthropogenic in origin) is presented that is characterized by a severe fitness disadvantage at some time-points but not others, and when individuals in a population show a preference for that habitat overall, will selective pressures cause the population’s preference to evolve over time and thus allow escape from that trap? Even more important than asking if escape via evolution by natural selection is possible, is the question of what levels of severity and frequency of fitness detriment will lead to the escape or extinction of the population. To answer these questions we construct a discrete, probabilistic model based on the life-history of the Checkerspot Butterfly (E. editha), which may have been exposed to such a trap at General’s Highway in Sequoia National Park. Using a stochastic difference equation model that is built upon a Markov chain and arrival processes we are able to reconstruct checkerspot life history patterns and natural sources of uncertainty for these populations. We find (1) that moderate preference for a trap can, under certain circumstances, pose greater risk than high preference for the trap, (2) that high variability in preference does not always facilitate evolutionary escape, (3) that the severity of catastrophes is more important than their frequency in assessing extinction risk, and (4) that persistence is inversely related to the fitness detriment associated with a trap.

Open Access Agreement

On-Campus only

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.