Looking forwards and backwards: dynamics and genealogies of locally regulated populations
<p>We introduce a broad class of mechanistic spatial models to describe how spatially heterogeneous populations live, die, and reproduce. Individuals are represented by points of a point measure, whose birth and death rates can depend both on spatial position and local population density, defi...
| Үндсэн зохиолчид: | , , , , |
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| Формат: | Journal article |
| Хэл сонгох: | English |
| Хэвлэсэн: |
Institute of Mathematical Statistics
2024
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| _version_ | 1826312474427654144 |
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| author | Etheridge, AM Kurtz, TG Letter, I Ralph, PL Tsui, THL |
| author_facet | Etheridge, AM Kurtz, TG Letter, I Ralph, PL Tsui, THL |
| author_sort | Etheridge, AM |
| collection | OXFORD |
| description | <p>We introduce a broad class of mechanistic spatial models to describe how spatially heterogeneous populations live, die, and reproduce. Individuals are represented by points of a point measure, whose birth and death rates can depend both on spatial position and local population density, defined at a location to be the convolution of the point measure with a suitable non-negative integrable kernel centred on that location. We pass to three different scaling limits: an interacting superprocess, a nonlocal partial differential equation (PDE), and a classical PDE. The classical PDE is obtained both by a two-step convergence argument, in which we first scale time and population size and pass to the nonlocal PDE, and then scale the kernel that determines local population density; and in the important special case in which the limit is a reaction-diffusion equation, directly by simultaneously scaling the kernel width, timescale and population size in our individual based model.</p>
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<p>A novelty of our model is that we explicitly model a juvenile phase. The number of juveniles produced by an individual depends on local population density at the location of the parent; these juvenile offspring are thrown off in a (possibly heterogeneous, anisotropic) Gaussian distribution around the location of the parent; they then reach (instant) maturity with a probability that can depend on the local population density at the location at which they land. Although we only record mature individuals, a trace of this two-step description remains in our population models, resulting in novel limits in which the spatial dynamics are governed by a nonlinear diffusion.</p>
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<p>Using a lookdown representation, we are able to retain information about genealogies relating individuals in our population and, in the case of deterministic limiting models, we use this to deduce the backwards in time motion of the ancestral lineage of an individual sampled from the population. We observe that knowing the history of the population density is not enough to determine the motion of ancestral lineages in our model. We also investigate (and contrast) the behaviour of lineages for three different deterministic models of a population expanding its range as a travelling wave: the Fisher-KPP equation, the Allen-Cahn equation, and a porous medium equation with logistic growth.</p> |
| first_indexed | 2024-03-07T08:29:32Z |
| format | Journal article |
| id | oxford-uuid:a6e69e9c-4e48-4346-a2b4-a47d38349e85 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T08:29:32Z |
| publishDate | 2024 |
| publisher | Institute of Mathematical Statistics |
| record_format | dspace |
| spelling | oxford-uuid:a6e69e9c-4e48-4346-a2b4-a47d38349e852024-03-06T10:17:06ZLooking forwards and backwards: dynamics and genealogies of locally regulated populationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:a6e69e9c-4e48-4346-a2b4-a47d38349e85EnglishSymplectic ElementsInstitute of Mathematical Statistics2024Etheridge, AMKurtz, TGLetter, IRalph, PLTsui, THL<p>We introduce a broad class of mechanistic spatial models to describe how spatially heterogeneous populations live, die, and reproduce. Individuals are represented by points of a point measure, whose birth and death rates can depend both on spatial position and local population density, defined at a location to be the convolution of the point measure with a suitable non-negative integrable kernel centred on that location. We pass to three different scaling limits: an interacting superprocess, a nonlocal partial differential equation (PDE), and a classical PDE. The classical PDE is obtained both by a two-step convergence argument, in which we first scale time and population size and pass to the nonlocal PDE, and then scale the kernel that determines local population density; and in the important special case in which the limit is a reaction-diffusion equation, directly by simultaneously scaling the kernel width, timescale and population size in our individual based model.</p> <br> <p>A novelty of our model is that we explicitly model a juvenile phase. The number of juveniles produced by an individual depends on local population density at the location of the parent; these juvenile offspring are thrown off in a (possibly heterogeneous, anisotropic) Gaussian distribution around the location of the parent; they then reach (instant) maturity with a probability that can depend on the local population density at the location at which they land. Although we only record mature individuals, a trace of this two-step description remains in our population models, resulting in novel limits in which the spatial dynamics are governed by a nonlinear diffusion.</p> <br> <p>Using a lookdown representation, we are able to retain information about genealogies relating individuals in our population and, in the case of deterministic limiting models, we use this to deduce the backwards in time motion of the ancestral lineage of an individual sampled from the population. We observe that knowing the history of the population density is not enough to determine the motion of ancestral lineages in our model. We also investigate (and contrast) the behaviour of lineages for three different deterministic models of a population expanding its range as a travelling wave: the Fisher-KPP equation, the Allen-Cahn equation, and a porous medium equation with logistic growth.</p> |
| spellingShingle | Etheridge, AM Kurtz, TG Letter, I Ralph, PL Tsui, THL Looking forwards and backwards: dynamics and genealogies of locally regulated populations |
| title | Looking forwards and backwards: dynamics and genealogies of locally regulated populations |
| title_full | Looking forwards and backwards: dynamics and genealogies of locally regulated populations |
| title_fullStr | Looking forwards and backwards: dynamics and genealogies of locally regulated populations |
| title_full_unstemmed | Looking forwards and backwards: dynamics and genealogies of locally regulated populations |
| title_short | Looking forwards and backwards: dynamics and genealogies of locally regulated populations |
| title_sort | looking forwards and backwards dynamics and genealogies of locally regulated populations |
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