SMS scnews item created by Ian Lizarraga at Sat 1 Apr 2023 1426
Type: Seminar
Modified: Mon 3 Apr 2023 0916; Mon 3 Apr 2023 1159
Distribution: World
Expiry: 1 Oct 2023
Calendar1: 6 Apr 2023 1100-1200
CalLoc1: AGR Carslaw 829
CalTitle1: AM Seminar: Using Field Data to Inform Agent-Based and Continuous Models of Locust Hopper Bands (Bernoff)
Auth: [email protected] (iliz4074) in SMS-SAML

Applied Maths Seminar: Bernoff -- (THURSDAY @ 11am) Using Field Data to Inform Agent-Based and Continuous Models of Locust Hopper Bands

(PLEASE NOTE TEMPORARY SCHEDULE AND LOCATION CHANGE FOR THE AM SEMINAR THIS WEEK:) 

Dear all, 

Our upcoming AM seminar is held this Thursday 6 April at 11am in the AGR (Carslaw 829).
Our speaker is Andrew Bernoff (Harvey Mudd).  Talk details follow below: 

-----------------------------------------------------------------------------------------
Title: Using Field Data to Inform Agent-Based and Continuous Models of Locust Hopper
Bands 

Abstract: An outstanding problem in mathematical biology is using laboratory and field
observations to tune a model’s functional form and parameter values.  In this talk I
will discuss an ongoing project developing models of the Australian plague locust for
which excellent field and experimental data is available.  Under favorable environmental
conditions flightless locust juveniles may aggregate into coherent, aligned swarms
referred to as hopper bands.  We will develop two models of hopper bands in tandem; an
agent-based model that tracks the position of individuals and a partial differential
equation model that describes locust and resource density.  By examining 4.4 million
parameter combinations, we identify a set of the problem’s ten parameters that reproduce
field observations.  

I will then discuss two ongoing efforts to improve this model.  The first uses ideas
from dynamical systems and continuum mechanics to extend this model into two dimensions
by modeling the known tendency of locusts to align using ideas from the Kuramoto model
of oscillator synchronization.  The second, firmly based in data science, uses motion
tracking of tens of thousands of locusts to shed light on how locust movement is
informed by interactions with other individuals.
----------------------------------------------------------------------------------------- 

An ongoing list of AM seminars is posted here:
https://www.maths.usyd.edu.au/u/SemConf/Applied.html 

See you there, 

Ian


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