Sensing and Decision-Making in Animal Search

Start: 02/08/2017 - 4:15pm
End  : 02/08/2017 - 5:15pm


Scott McKinley (Tulane)

Due to the rapid growth of animal movement data obtained by GPS, radio tracking collars and other means, there is a growing recognition that classical models of encounter rates among animal populations should be revisited. Recent theoretical investigations have demonstrated that biologically relevant modifications to classical assumptions about individual behavior can bring about non-trivial changes in the formulation of population-scale dynamical systems. Put more simply: a panther does not move around like a Brownian motion, but PDEs used in Mathematical Ecology pretend like they do!
The first paradigm shift in describing animal movement was to move towards “Levy Flight” models that take into account the tendency of searching animals to make long excursions. The problem with this theory is that animal decisions are hypothesized to be divorced from stimuli in their environment. In this talk, I will review some of the conventional wisdom that supports the Levy flight theory, but through a few examples, I will make the case that animal movement patterns should not be separated from the spatial environmental features that shape them. In fact, animal sensing and decision-making are “leading-order” effects in observed data, and their study gives rise to new ecological observations and novel mathematical challenges.
Shanahan B460, Harvey Mudd

Claremont Graduate University | Claremont McKenna | Harvey Mudd | Pitzer | Pomona | Scripps
Proudly Serving Math Community at the Claremont Colleges Since 2007
Copyright © 2018 Claremont Center for the Mathematical Sciences