SMS scnews item created by Ben Goldys at Sun 9 Jun 2019 0858
Type: Seminar
Distribution: World
Expiry: 2 Jul 2019
Calendar1: 24 Jun 2019 1405-1500
CalLoc1: AGR
CalTitle1: Stochastic Population Dynamics: coexistence, extinction and long term behaviour, part 1
Calendar2: 25 Jun 2019 1405-1500
CalLoc2: AGR
CalTitle2: Stochastic Population Dynamics: coexistence, extinction and long term behaviour, part 2
Calendar3: 2 Jul 2019 1405-1500
CalLoc3: AGR
CalTitle3: Stochastic Population Dynamics: coexistence, extinction and long term behaviour, part 3
Auth: beng@d49-191-144-157.mas2.nsw.optusnet.com.au (bgoldys) in SMS-WASM

3 Lectures on Stochastic Population Dynamics: Alexandru Hening -- Stochastic population dynamics

Dear Colleagues, 

Dr Alexandru Hening (Tufts University) will be visiting Mathematical Research Institute
from June 17 till August 1.  He will deliver three lectures and two research seminars on
stochastic population dynamics; the title and description of lectures is provided
below.  More information about the seminars will be sent as a separate message.  All
lectures and seminars will be held in AGR at 2PM.  

Lecture 1: 24/06, Lecture 2: 25/06, Lecture 3: 2/07

Seminar 1: 4/07, Seminar 2: 9/07 

TITLE OF LECTURES: Stochastic Population Dynamics: coexistence, extinction and long
term behaviour 

ABSTRACT: One of the major tasks of mathematical ecology is to describe
the dynamics of populations.  In most ecosystems multiple different species interact in
complex ways.  Even a system with two species can exhibit complicated dynamics due to
dispersion, seasonal differences, and other factors.  The dynamics of species is
inherently stochastic due to the random fluctuations of environmental factors.  The
combined effects of biotic interactions (competition, predation, mutualism) and
environmental fluctuations (precipitation, temperature, sunlight) are key when trying to
determine species richness.  A successful way of studying this interplay is modeling the
populations as discrete or continuous time Markov processes, and looking at the
long-term behavior of these processes.  We will start by looking at deterministic models
of population dynamics in discrete and continuous time.  Consequently, we will add
environmental noise to these systems and analyze how this changes the long term
behavior.  We will look in depth at stochastic Lotka-Volterra systems (both for
competition and predator-prey interactions), the dynamics of populations living in
patchy environments, evolutionary stable strategies (ESS) and other examples.


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