Seminars and Workshops

Upcoming conference sponsored by NCSE International Statistical Ecology Conference (ISEC) The ISEC will be held 9-11 July 2008 at the University of St. Andrews, Scotland

Seminars NCSE seminars are transmitted by video conference to all three sites, and are often broadcast by a remote speaker from a fourth site. All are welcome to attend. 19 Oct 2007 11:30am BST. (Broadcast from Kent.) Jon Barry, CEFAS, UK. How many benthic species are there and how bad is dredging for them? In this talk, I will cover a number of things: 1. A brief introduction to what goes on at the Centre for Environment, Fisheries and Aquacultural Science and how this might link into the work of the National Centre for Statistical Ecology. 2. A description of a dredging experiment that looks at the impact of the dredging on number of species and abundance of individuals. By modelling species as Matern spatial point processes and then estimating the parameters of these processes by a simulated maximum likelihood, we can examine how much the reduction in species numbers is due to dredging and how much is due to the fact that the thinned species are harder to find. 3. A look at the (in)famous "how many species are there problem" (i.e. how many have we missed in our survey?) and how we might specifically model spatial clustering to help with a solution. 4. Some nice pictures and an idea of the sorts of projects that will need statistical input in future. 14 Nov 2007 4pm GMT (Broadcast from Ann Arbor.) Ed Ionides, University of Michigan, USA. Inference for nonlinear dynamical systems, with applications to the ecology of infectious diseases. (slides) Nonlinear stochastic dynamical models are used to study ecological systems and many other systems occuring across the sciences and engineering. Such models are natural to formulate and can be analyzed mathematically and numerically. However, difficulties associated with inference from time-series data about unknown parameters in these models have been a constraint on their application. We present a new method that makes maximum likelihood estimation feasible for partially-observed nonlinear stochastic dynamical systems (also known as state-space models) where this was not previously the case. The method is based on a sequence of filtering operations which are shown to converge to a maximum likelihood parameter estimate. We make use of recent advances in nonlinear filtering in the implementation of the algorithm. We apply the method to the study of cholera in Bangladesh. We construct confidence intervals, perform residual analysis, and apply other diagnostics. Our analysis, based upon a model capturing the intrinsic nonlinear dynamics of the system, reveals some effects overlooked by previous studies. 27 Nov 2007 12:30pm GMT (Broadcast from St Andrews.) Geir Storvik, University of Oslo, Norway. Modelling Pollock egg counts from the western Gulf of Alaska by a zero-inflated Bayesian hierarchical space-time model Data from egg sampling surveys often contain a mixture of zero observations and large count or density values, often with a high proportion of zeros. We will consider a particular dataset giving walleye Pollock egg counts from the western Gulf of Alaska, from Kodiak Island to Unimah Pass, in the years 1978-2000. The main interest will be to predict the intensity of eggs as a process varying in space and time (both within and between years). In this talk I will discuss a Bayesian approach for the analysis of such data. The excessive number of zeros in the data is taken into account by the use of a two stage modelling approach, resulting in a zero-inflated hierarchical space-time model. An underlying intensity process is assumed to both influence the probabilities of zeros and the amount of eggs in non-zero observations. Dependence of covariates and spatio-temporal correlations are taken into account through the modelling of the underlying intensity process. Fitting is performed through Markov Chain Monte Carlo simulations. Results for the walley Pollock egg counts will be presented. This talk will be based on joint work with Ingunn Tvete and Bent Natvig at the University of Oslo and Lorenzo Ciannelli at Oregon State University.

Past seminars 24 May 2007 Jean-Michel Gaillard, University of Lyon, France. How does individual heterogeneity influence detection of senescence and trade-offs: ungulates as case studies. 16 May 2007 Paul Conn, Colorado State University, USA. Bayesian analysis of wildlife age-at-harvest data 5 February 2007 William Browne, University of Nottingham, UK. Using complex random effect models in epidemiology and ecology 29 November 2006 Carmen Fernandez, Spanish Oceanographic Institute. Inference for state space models of wild animal populations 30 August 2006 David Fletcher, University of Otago, Dunedin, New Zealand. Mark-Recapture Models and Population Dynamics 19 June 2006 Mark Maunder and Rick Deriso, Inter American Tropical Tuna Commission, San Diego, USA. Including covariates in population dynamics models 12 June 2006 Dave Thomson, Max Planck Institute for Demographic Research, Rostock, Germany. Statistical Analyses in Biodemography

Workshops Distance sampling - provisional dates 15 - 25 August 2007. St Andrews: Buckland, Borchers, Thomas, Burt, Rexstad, Marques, Marshall

Past Workshops Distance sampling 23 August - 1 September 2006 St Andrews: Buckland, Borchers, Thomas, Burt, Rexstad, Marques, Marshall Introduction to Distance sampling 28-30 June 2006 Auckland: Buckland, Borchers, Fewster Counting Critters 16-21 October 2005 Orlando: Thomas, Buckland, Borchers, Marques and Bishop Estimating Animal Abundance 23-27 August 2005 St Andrews: Borchers, Buckland, Morgan, Rexstad and Bishop Distance Sampling 31st August - 7th September 2005 St Andrews: Borchers, Buckland, Burt, Marques and Thomas Bayesian Computation for Population Ecology 4-8 September 2005 Cambridge: Brooks, King and Morgan Distance Sampling for Ornithologists. 11-14 January 2005 Flagstaff: Buckland, Burt, Marques, Bishop and Thomas

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