It is always great to see how well students do beyond our time together. Taylor Anderson was a student who excelled in two courses under my instruction (GEOG 381 and 481). With no programming background, she dove into python and programming with ArcGIS in our Advanced GIS course and yielded significant knowledge gains and a mark well above average. She then took on a very challenging project in our GIS Project course, which involved using the Soil Water Assessment Tool (SWAT) to assess phosphorus loading on local hydrological features and how seasonality might affect the spatial distribution of these loadings. This project met with a lot of challenges and difficulties (for obvious reasons, the topic is quite large let alone learning and applying SWAT in four months). However, Taylor was able to carry her teammates and acquire a wealth of knowledge along the way. After finishing up her undergraduate degree she started her PhD at Simon Fraser University with Suzana Dragicevic.
While working with Suzana, Taylor applied for one of NSERC’s highly competitive CGS-M scholarships and was successful this year (2014). A summary of the exciting research she is proposing to complete is provided below. This is just one of many directions that students in our department take. We look forward to hearing more success stories from Taylor and our other program alumni (when I have a chance to post them!). Congratulations Taylor!
NSERC’s Canada Graduate Scholarship-Masters (CGS-M)
Summary of Research
Complex systems theory can be used as an approach to understand the complexity and spatial significance in ecological processes, such as insect infestation, by identifying how collective behavior disaggregates to individual interactions and vice versa. Since its discovery in southern Michigan in 2002, the emerald ash borer (Agrilus planipennis; EAB), an exotic-invasive species native to south-east Asia has infested and killed millions of North American ash trees (Fraxinus sp.) across eastern United States and Canada. Efforts to understand and model the insect’s behavior are ongoing. Current modelling approaches use mostly statistical analysis to represent EAB spread at local scale, evaluate the effects of climate on EAB, and estimate the economic impacts of the pest. However, these methods are limited to a US context and, more importantly, use modeling approaches which cannot capture the complex nonlinear behavior of the EAB. There is a strong need for the development of new modeling approaches which will address EAB behavior as complex adaptive system capable to better represent and forecast the EAB behavior and ultimately help manage EAB infestation.
My research is focused on the development of a suite of geosimulation models that integrates geographic information systems (GIS) with complex system theory methodology including cellular automata (CA) and agent-based approaches, to represent the complex behavior characteristic of EAB. Soft computing techniques and artificial intelligence (AI) are used to enhance the models. The models are applied to three landscape scenarios developed representing the real world that the EAB propagates through and can be characterized by various distributions of ash trees: urban, urban-rural fringe, and rural. The models simulate EAB infestation for a 15 year period from 2002-2017. The study will utilize the CFIA’s geospatial datasets containing positive locations of EAB infested ash trees specific to Essex, Lambton, and Chatham-Kent municipalities on a cumulative basis from 2002 to 2009 which will permit model building, calibration, and validation procedures.
The developed object-based geosimulation model reflects the processes which govern EAB spread and demonstrate EAB propagation. Preliminary results indicate that the infestation is highly dependent on the distribution of ash trees across the landscape. The developed geosimulation model can help decision makers and interested scholars evaluate current and costly eradication strategies, fill in knowledge gaps with respect to EAB spread, and assist in city planning and forest management strategy formation.
