Computational models of spider activity patterns integrated with behavioral experiments hypothesize adaptive benefits of the circadian clock (thesis)
Mah, Andrew V.
Washington and Lee University -- Honors in Neuroscience
Spiders -- Behavior
Circadian rhythms -- Mathematical models
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Thesis; [FULL-TEXT FREELY AVAILABLE ONLINE]Andrew V. Mah is a member of the Class of 2018 of Washington and Lee University.The purpose of this study is to combine behavioral and computational analyses to describe the circadian systems of C. turbinata and P. tepidariorum in order to hypothesize adaptive benefits of the observed behaviors. In the first chapter, I will present a series of numerical experiments performed on models that recreate C. turbinata’s short period circadian clock. The results from these numerical experiments will be used to give us greater understanding about the nature of C. turbinata’s molecular oscillators and generate testable hypotheses about the adaptive nature of circadian clocks. In the second chapter, in addition to P. tepidariorum, I will also describe the circadian systems of two other theridiid species as a point of comparison: the subsocial spider, Anelosimus studiosus; and the southern black widow, Latrodectus mactans. The goal of these experiments is to understand the mechanisms underlying the observed variability in spider circadian systems (e.g., FRP, distribution, and affect of light). More generally, understanding how this variability arises can improve mechanistic explanations of adaptive benefits. Examining the free-running behavior, including the FRP and its distribution within a species, of the three Theridiidae spiders will reveal the behavior of their circadian systems in the absence of any external cues, because without the influence of external cues, more endogenous traits about the underlying system become apparent. For example, C. turbinata can entrain its circadian period to LD 12:12. It is only when the specimens are removed from light that their 19-hour endogenous period becomes apparent. [From Introduction]Andrew Mah