Stochastic Modelling in Ecosystems

Predicting ecosystems responses under changing environment conditions is one of the major challenges in ecology. It is rendered more complex by the non-linear dynamics which characterise ecosystems and the partially stochastic nature of key drivers. Environmental drivers (including climate, nutrients, fire, and herbivores) change in time and space, sometimes gradually and smoothly, sometimes less gradually, even abruptly. Ecosystems may respond to changes in their environmental drivers in an orderly and continuous way, but they may be quite unresponsive over certain ranges of environmental conditions and then react rapidly with strong changes, or shifts, when conditions approach a critical level or threshold.

It is due to these complex features of Ecosystems, stochastic modelling has become more and more popular, not only because it is useful in the study of ecosystems, but also presents many challenges to mathematical research as well as provides ecologists, biologists and mathematicians with a great opportunity to collaborate together. Although stochastic modelling in ecosystems has been very hot for the past several years, there is a significant gap between ecologists, biologists and mathematicians.

Professor Xuerong Mao or Dr Andrew Wade from the University of Strathclyde, Glasgow, Scotland UK are organizing a 2-day workshop to bring researchers (mainly from UK/EU) and their research assistants and students together to promote, encourage, and influence more cooperation, and to bring together various disciplines e.g. ecology, biology, mathematics, engineering, computer science. As well as talks  and a poster section given by research students, there will also be spaces in the programme designed to encourage interaction between the attendees with the aim of promoting further collaborative research work.

More information about the workshop is available at http://www.mathstat.strath.ac.uk/seminars/stochastic .