People

Lincoln University staff

Dr. Hamish Rennie
Senior Lecturer, Environmental Management and Planning
Dr. Clare Churcher
Senior Lecturer in Software and Information Technology
Dr.
Professor, Resource Economics
Dr. Grant Cushman
Professor of Parks, Recreation and Tourism
Dr. Crile Doscher
Lecturer in Engineering
Dr. Stephen Espiner
Lecturer, Park and Recreation Management
Bob Gidlow
Senior Lecturer, Environment Society and Design Division
Dr. Ken Hughey
Professor, Director Postgraduate Studies
Dr. Geoff Kerr
Associate Professor, Environmental Economics
Hirini Matunga
Assistant Vice-Chancellor (Maori), Associate Professor
Dr. 
Professor of Software and Information Technology
Dr.
Professor of Environmental Management
Dr. Roy Montgomery
Lecturer
Dr. Harvey Perkins
Professor of Human Geography
Dr. Stefanie Rixecker
Dean, Faculty of Environment, Society & Design
Dr. Greg Ryan
Senior Lecturer, Faculty of Environment, Society and Design
Dr. Simon Swaffield
Professor of Landscape Architecture

Research Fellows

Dr. Lars Brabyn, Waikato University, New Zealand
Dr. Roger White, Professor, Memorial University of Newfoundland, Canada
Dr. Janet Brown, Institute of Aquaculture, Stirling University, Scotland
 

Students

Stephen Beville (MSc, London School of Economics)
Stephen’s PhD is centred on employing discrete choice methods to investigate how angler’s fishery site choices are affected by factors such as Didymo infestation, riparian margin erosion due to stock, changes in water visibility, angler congestion,  fish size, catch rates, bag limits, travel times and cost.  Stephen is especially interested in linking recreational specialisation theory to choice methods in order to test some of theoretical assertions of recreational specialisation theory in addition to illustrating how extensions to the Random Parameters Logit model may be used to improve understanding of angler behaviour.

Mohammad Daradkeh (MSc,Yarmouk University, Jordan)
The goal of this doctoral research, “Interactive Visualisation Techniques for Exploring Model Sensitivity”, is to develop interactive visualization techniques to help decision makers explore model sensitivity to simultaneous variations of input variables taking into account the interaction between input variables as well as the impact of different sources of uncertainty on the overall uncertainty in model output. Models on which this will be tested include some from the fisheries and aquaculture theme.