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- 66Biological Sciences, Department of/Journal Articles (Biological Sciences)
- 46Mathematical and Statistical Sciences, Department of
- 46Mathematical and Statistical Sciences, Department of/Research Publications (Mathematical and Statistical Sciences)
- 11The NSERC TRIA Network (TRIA-Net)
- 11The NSERC TRIA Network (TRIA-Net)/Journal Articles (TRIA-Net)
- 6animal movement
- 4Animal movement
- 4population dynamics
- 3Advection-diffusion
- 3Integrodifference equations
- 3Machine learning
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2023-12-10
Harrison DE, Diluvio MS, Matveev E, Corrêa PVF, De Leo FC, Leys SP
Supplementary files associated with the Journal Article
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2022-03-10
Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah, Mark Lewis
Accurate prediction of the number of daily or weekly confirmed cases of COVID-19 is critical to the control of the pandemic. Existing mechanistic models nicely capture the disease dynamics. However, to forecast the future, they require the transmission rate to be known, limiting their prediction...
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Beyond resource selection: emergent spatio-temporal distributions from animal movements and stigmergent interactions
Download2022-03-30
Jonathan R. Potts, Valeria Giunta, Mark A. Lewis
A principal concern of ecological research is to unveil the causes behind observed spatio-temporal distributions of species. A key tactic is to correlate observed locations with environmental features, in the form of resource selection functions or other correlative species distribution models....
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Simulating how animals learn: a new modelling framework applied to the process of optimal foraging
Download2022-01-01
Peter R. Thompson, Melodie Kunegel-Lion, Mark A. Lewis
Animal learning has interested ecologists and psychologists for over a century. Mathematical models that explain how animals store and recall information have gained attention recently. Central to this work is statistical decision theory (SDT), which relates information uptake in animals to...
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Beyond resource selection: emergent spatio-temporal distributions from animal movements and stigmergent interactions
Download2022-01-01
Jonathan R. Potts, Valeria Giunta, Mark A. Lewis
A principal concern of ecological research is to unveil the causes behind observed spatiotemporal distributions of species. A key tactic is to correlate observed locations with environmental features, in the form of resource selection functions or other correlative species distribution models. In...
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Detecting seasonal episodic-like spatiotemporal memory patterns using animal movement modelling
Download2021-01-01
Peter R. Thompson, Andrew E. Derocher, Mark A. Edwards, Mark A. Lewis
Spatial memory plays a role in the way animals perceive their environments, resulting in memory-informed movement patterns that are observable to ecologists. Developing mathematical techniques to understand how animals use memory in their environments allows for an increased understanding of...
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2021-01-01
Valeria Giunta, Thomas Hillen, Mark A. Lewis, Jonathan R. Potts
Non-local advection is a key process in a range of biological systems, from cells within individuals to the movement of whole organisms. Consequently, in recent years, there has been increasing attention on modelling non-local advection mathematically. These often take the form of partial...
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2021-05-01
Dean Koch, Mark A. Lewis, Subhash Lele
The mountain pine beetle (MPB) is among the most destructive eruptive forest pests in North America. A recent increase in the frequency and severity of outbreaks, combined with an eastward range expansion towards untouched boreal pine forests, has spurred a great interest by government, industry...
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2021-10-01
Pouria Ramazi, Mélodie Kunegel-Lion, Russell Greiner, Mark A. Lewis
Planning forest management relies on predicting insect outbreaks such as mountain pine beetle, particularly in the intermediate‐term future, e.g., 5‐year. Machine‐learning algorithms are potential solutions to this challenging problem due to their many successes across a variety of prediction...
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2021-01-05
Pouria Ramazi, Mélodie Kunegel-Lion, Russell Greiner, Mark A. Lewis
Although ecological models used to make predictions from underlying covariates have a record of success, they also suffer from limitations. They are typically unable to make predictions when the value of one or more covariates is missing during the testing. Missing values can be estimated but...