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Designing biology informed anthropogenically driven invasive forest pests risk models

University of British Columbia

Forest invasive species (FIS) pose significant threats to the economic and ecological stability of our forests. Given the potential impact of invasive species, tools are needed that will help prevent invasions, or enable effective early responses through robust interception and surveillance frameworks. Spatial models aim at identifying meaningful spatial relationships between different geographical features. Climate based spatial models have the ability to provide information on current and future potential for invasion and spread. Species distribution modelling (SDM) is a valuable tool for predicting the potential distribution of invasive species across space and time. While recent developments in modeling approaches and wider availability of environmental datasets have create advanced and more accurate SDM, in many cases the developed models ignore the associated underlying ecological processes. Moreover, bioclimatic variables usually included in the SDMs do not account for anthropogenic impacts on the response variable and the methods to integrate species traits as predicted by genetics into projections of species distributions are not generally used. In this PhD dissertation I address these key issues in particular reference to two pests and two pathogens that represent urgent threats. I explored the sensitivity of SDM modelling in two of the major ports in Canada and produced dispersal restricted projections of individual FIS distributions in various climate change scenarios. I also analyzed the methodology of determining climatic niches and compared the native and post-invasion niches of chosen FIS. I found that if I ignored the underlying FIS biology such as use of biologically relevant predictors, appropriate feature selection and inclusion of dispersal and biotic interactions when I developed SDMs, I obtained complex SDMs that provided an incomplete picture of the potential FIS invasion. Most of the representative invasives were far away from reaching niche equilibrium. In this thesis throughout I discuss the potential of spatial models in risk analysis of FIS. I provide an improved framework for invasive species risk mapping using spatial models. The methodology presented in this dissertation to develop pest risk maps is robust and easy and the presented results can guide monitoring and help inform management of these and other invasive species.

Text

2020-07-28

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/75304

Forestry

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/