Class
Article
College
College of Science
Faculty Mentor
Noelle Beckman
Presentation Type
Oral Presentation
Abstract
Current models predict that up to 60% of species are at a greater risk of extinction due to climate change. This increased risk is largely due to the challenge of adapting to a new climate or tracking existing climate conditions to a new location. Existing habitats are expected to shift at a rate of 0.08 to 1.26 kilometers per year due to changes in temperature, precipitation, and other climatic variables. Most models currently used to predict species responses to climate change rely on unrealistic dispersal assumptions and statistical instead of mechanistic structures. With improved access to applicable datasets and modeling capabilities, we generate predictions as to which types of species will be able to track their environment. We will use statistical approximations of trait data to generate virtual plant species with dispersal, demography, and functional traits, and an analytical integrodifference model that includes realistic dispersal kernels and demographic information to inform the potential for each species to follow climatic shifts based on their unique characteristics. While the ecological data has become more available, virtual species are essential to this approach, as these data tend to be sparse. From these models, a rate of spread based on dispersal and demography for each species can be generated and compared to the expected velocity of climate change globally and for each biome. This will provide an estimate of how many species could go extinct as a result of their inability to track their environments, allowing responsible parties to prioritize efforts to anticipate and mitigate the potentially disastrous consequences of large scale extinction. Preliminary results indicate that approximately 80% of plant species will be unable to track their current habitat conditions, meaning that a large majority of species will be required to adapt to their new habitats in order to survive.
Location
Room 101
Start Date
4-12-2018 3:00 PM
End Date
4-12-2018 4:15 PM
Novel Approaches to Predicting Plant Species’ Movement under Climate Change
Room 101
Current models predict that up to 60% of species are at a greater risk of extinction due to climate change. This increased risk is largely due to the challenge of adapting to a new climate or tracking existing climate conditions to a new location. Existing habitats are expected to shift at a rate of 0.08 to 1.26 kilometers per year due to changes in temperature, precipitation, and other climatic variables. Most models currently used to predict species responses to climate change rely on unrealistic dispersal assumptions and statistical instead of mechanistic structures. With improved access to applicable datasets and modeling capabilities, we generate predictions as to which types of species will be able to track their environment. We will use statistical approximations of trait data to generate virtual plant species with dispersal, demography, and functional traits, and an analytical integrodifference model that includes realistic dispersal kernels and demographic information to inform the potential for each species to follow climatic shifts based on their unique characteristics. While the ecological data has become more available, virtual species are essential to this approach, as these data tend to be sparse. From these models, a rate of spread based on dispersal and demography for each species can be generated and compared to the expected velocity of climate change globally and for each biome. This will provide an estimate of how many species could go extinct as a result of their inability to track their environments, allowing responsible parties to prioritize efforts to anticipate and mitigate the potentially disastrous consequences of large scale extinction. Preliminary results indicate that approximately 80% of plant species will be unable to track their current habitat conditions, meaning that a large majority of species will be required to adapt to their new habitats in order to survive.