Partial Differential Equations in Ecology 80 Years and Counting
Partial differential equations (PDEs) have been used in theoretical ecology research for more than eighty years. Nowadays, along with a variety of different mathematical techniques, they remain as an efficient, widely used modelling framework; as a matter of fact, the range of PDE applications has e...
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| Format: | Electronic Book Chapter |
| Language: | English |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 100 | 1 | |a Petrovskii, Sergei |4 edt | |
| 700 | 1 | |a Petrovskii, Sergei |4 oth | |
| 245 | 1 | 0 | |a Partial Differential Equations in Ecology |b 80 Years and Counting |
| 260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
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| 520 | |a Partial differential equations (PDEs) have been used in theoretical ecology research for more than eighty years. Nowadays, along with a variety of different mathematical techniques, they remain as an efficient, widely used modelling framework; as a matter of fact, the range of PDE applications has even become broader. This volume presents a collection of case studies where applications range from bacterial systems to population dynamics of human riots. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Research & information: general |2 bicssc | |
| 650 | 7 | |a Mathematics & science |2 bicssc | |
| 653 | |a cross diffusion | ||
| 653 | |a Turing patterns | ||
| 653 | |a non-constant positive solution | ||
| 653 | |a animal movement | ||
| 653 | |a correlated random walk | ||
| 653 | |a movement ecology | ||
| 653 | |a population dynamics | ||
| 653 | |a taxis | ||
| 653 | |a telegrapher's equation | ||
| 653 | |a invasive species | ||
| 653 | |a linear determinacy | ||
| 653 | |a population growth | ||
| 653 | |a mutation | ||
| 653 | |a spreading speeds | ||
| 653 | |a travelling waves | ||
| 653 | |a optimal control | ||
| 653 | |a partial differential equation | ||
| 653 | |a invasive species in a river | ||
| 653 | |a continuum models | ||
| 653 | |a partial differential equations | ||
| 653 | |a individual based models | ||
| 653 | |a plant populations | ||
| 653 | |a phenotypic plasticity | ||
| 653 | |a vegetation pattern formation | ||
| 653 | |a desertification | ||
| 653 | |a homoclinic snaking | ||
| 653 | |a front instabilities | ||
| 653 | |a Evolutionary dynamics | ||
| 653 | |a G-function | ||
| 653 | |a Quorum Sensing | ||
| 653 | |a Public Goods | ||
| 653 | |a semi-linear parabolic system of equations | ||
| 653 | |a generalist predator | ||
| 653 | |a pattern formation | ||
| 653 | |a Turing instability | ||
| 653 | |a Turing-Hopf bifurcation | ||
| 653 | |a bistability | ||
| 653 | |a regime shift | ||
| 653 | |a carrying capacity | ||
| 653 | |a spatial heterogeneity | ||
| 653 | |a Pearl-Verhulst logistic model | ||
| 653 | |a reaction-diffusion model | ||
| 653 | |a energy constraints | ||
| 653 | |a total realized asymptotic population abundance | ||
| 653 | |a chemostat model | ||
| 653 | |a social dynamics | ||
| 653 | |a wave of protests | ||
| 653 | |a long transients | ||
| 653 | |a ghost attractor | ||
| 653 | |a prey-predator | ||
| 653 | |a diffusion | ||
| 653 | |a nonlocal interaction | ||
| 653 | |a spatiotemporal pattern | ||
| 653 | |a Allen-Cahn model | ||
| 653 | |a Cahn-Hilliard model | ||
| 653 | |a spatial patterns | ||
| 653 | |a spatial fluctuation | ||
| 653 | |a dynamic behaviors | ||
| 653 | |a reaction-diffusion | ||
| 653 | |a spatial ecology | ||
| 653 | |a stage structure | ||
| 653 | |a dispersal | ||
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| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/68481 |7 0 |z DOAB: description of the publication |