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Structural sensitivity of ecological models: state of the art and challenges Morozov, Andrew
Description
When we construct mathematical models to represent a given real-world system, there is always a degree of uncertainty with regards to the model specification - whether with respect to the choice of parameters or to the choice of formulation of model functions. This can become a real problem in some cases, where choosing two different functions with close shapes in a model can result in substantially different model predictions. This phenomenon is known as structural sensitivity, and is a significant obstacle to improving the predictive power of models - particularly in fields where it is not possible to derive the functions suitable for representing system processes from theory or physical laws, such as the biological sciences. In this talk, I shall revisit the notion of structural sensitivity and propose a general approach to reveal structural sensitivity which is a far more powerful technique than the conventional approach consisting of fixing a particular functional form and varying its parameters. I will demonstrate that conventional methods based on variation of parameters alone will often miss structural sensitivity. I shall discuss the consequences that structural sensitivity and the resulting model uncertainty may have for the modelling of biological systems. In particular, it will be shown the concept of a 'concrete' bifurcation structure may no longer be relevant in the case of structural sensitivity, thus we can only describe bifurcations of completely deterministic systems with a certain probability. Finally, I will show that structural sensitivity can be a possible explanation of the observed irregularity of oscillations of population densities in nature. At the end, we will discuss the current challenges related to structural sensitivity in models and data.
Item Metadata
| Title |
Structural sensitivity of ecological models: state of the art and challenges
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| Creator | |
| Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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| Date Issued |
2019-07-29T09:45
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| Description |
When we construct mathematical models to represent a given real-world system, there is always a degree of uncertainty with regards to the model specification - whether with respect to the choice of parameters or to the choice of formulation of model functions. This can become a real problem in some cases, where choosing two different functions with close shapes in a model can result in substantially different model predictions. This phenomenon is known as structural sensitivity, and is a significant obstacle to improving the predictive power of models - particularly in fields where it is not possible to derive the functions suitable for representing system processes from theory or physical laws, such as the biological sciences. In this talk, I shall revisit the notion of structural sensitivity and propose a general approach to reveal structural sensitivity which is a far more powerful technique than the conventional approach consisting of fixing a particular functional form and varying its parameters. I will demonstrate that conventional methods based on variation of parameters alone will often miss structural sensitivity. I shall discuss the consequences that structural sensitivity and the resulting model uncertainty may have for the modelling of biological systems. In particular, it will be shown the concept of a 'concrete' bifurcation structure may no longer be relevant in the case of structural sensitivity, thus we can only describe bifurcations of completely deterministic systems with a certain probability. Finally, I will show that structural sensitivity can be a possible explanation of the observed irregularity of oscillations of population densities in nature. At the end, we will discuss the current challenges related to structural sensitivity in models and data.
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| Extent |
37.0 minutes
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| Subject | |
| Type | |
| File Format |
video/mp4
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| Language |
eng
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| Notes |
Author affiliation: University of Leicester
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| Series | |
| Date Available |
2020-09-09
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0394270
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| URI | |
| Affiliation | |
| Peer Review Status |
Unreviewed
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| Scholarly Level |
Researcher
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Item Media
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International