Re: [SwarmFest2004] abstract

[Rick Riolo]

Thanks for your submission!

Could you please include a project title, and your
name and affiliation?

Thanks!
 - r

Rick Riolo                           address@hidden
Center for the Study of Complex Systems (CSCS)
4477 Randall Lab
University of Michigan         Ann Arbor MI 48109-1120
Phone: 734 763 3323                  Fax: 734 763 9267
http://cscs.umich.edu/~rlr

On Thu, 25 Mar 2004 address@hidden wrote:

> Date: Thu, 25 Mar 2004 06:55:59 EST
> From: address@hidden
> To: address@hidden
> Subject: [SwarmFest2004] abstract
>
> I developed a StarLogo project with crayfish data from my work in northern
> Minnesota that I acquired while attending graduate school at the University of
> Minnesota in fisheries.  I started working on it while attending a Starlogo
> workshop for teachers at the Santa Fe Institute, and I find it useful in my
> current job teaching biology to inner city students in Camden, NJ.  The 
> abstract
> follows:
>
> Teaching how organisms interact with habitat is different from researching
> the problem.  Research often paints a complex picture.  Multivariate 
> statistics
> are commonly used to describe the influence of several habitat variables on
> distribution.  At the high school level, textbooks often paint a simpler,
> sometimes oversimplified, picture.  I attempted a third approach by 
> developing a
> Starlogo model.  It uses actual field data on crayfish distribution and 
> several
> microhabitat variables to illustrate habitat use in an intuitive, visual, and
> accessible manner.  The model uses a population of artificial crayfish,
> reacting to habitat variables in parallel, as instructed by the student.  The 
> goal is
> to develop habitat selection criteria for these artificial crayfish that will
> place them in habitat on the computer screen corresponding to real habitat
> used by real crayfish at the study site.  Students determine whether 
> individual
> variables affect young-of-the-year crayfish numbers at the study site
> positively or negatively.  Then they estimate the degree of crayfish response 
> to each
> variable, and combine the variables to produce their best multivariate model.
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