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David J. Lieske, Ph.D.
David J. Lieske is an Associate Professor in the Department of Geography and Environment, and is the Director of the Mount Allison University Geospatial Modelling Lab (GML).

His research expertise encompasses spatial statistical modelling, geographic information systems (GIS), and geovisualization. David is particularly interested in the application of these methods to assist environmental monitoring, mapping and conservation planning.

David is also the author of the Tantramar Community Adaptation Viewer (TCAV), a web-based decision support toolkit for viewing community flood risk vulnerability.

Link to David's Workshop on the R Statistical Package: click here

His contact information is as follows:

  David J. Lieske
  Assoc. Professor
  Dept. of Geography
  and Environment,
  Mount Allison
  University
  144 Main Street,
  Sackville, NB,
  Canada
  Tel: 506-364-2315
  Fax: 506-364-2625
  dlieske@mta.ca


Blacklegged Ticks



Project Summary:

The Blacklegged Tick (Ixodes scapularis) is an arthropod currently undergoing range expansion, and is of concern as a vector for the transmission of Lyme Disease (caused by the bacterium Borrelia burgdorferi). However, not much is known about the factors controlling the tick's geographic distribution in New Brunswick.

Objectives:

This research will develop a geodatabase to bring together tick distribution data for the province of New Brunswick, current and projected climatic conditions, and forest land cover. Current information about the distribution of the Blacklegged Tick, obtained from passive surveillance, will be combined with current climate data. Using a cutting-edge modelling framework, the climatic response of the tick will be quantified and an ensemble prediction (derived from a number of flexible modelling methods) used to map the future climate-suitability envelope for the species.

Anticipated Outcomes:

This project will help identify "source" areas - or colonizing points for expanding black tick populations - that will have bearing on land use planning and sustainable development.

Furthermore, It is expected that communication of the projectís findings will enhance public awareness and help reduce the number of human cases of tick-borne lyme disease.

This research will also develop general techniques for constructing climate-habitat distribution models that can be used to measure habitat suitability for any species. It is expected that future work will apply these tools and innovations to study other species considered at-risk for extinction, or of concern as an invasive.

Project Funders:



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