Modelling and analysis of spatio-temporal dynamics of a marine ecosystem

Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton in...
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Gespeichert in:

Autor*in:	Chakraborty, Kunal [verfasserIn] Manthena, Vamsi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Reaction–diffusion equations Marine ecosystem Diffusion-driven instability Spatio-temporal dynamics Patchiness

Übergeordnetes Werk:	Enthalten in: Nonlinear dynamics - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990, 81(2015), 4 vom: 01. Mai, Seite 1895-1906
Übergeordnetes Werk:	volume:81 ; year:2015 ; number:4 ; day:01 ; month:05 ; pages:1895-1906

Links:	Volltext

DOI / URN:	10.1007/s11071-015-2114-1

Katalog-ID:	SPR016380177

Internformat


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520			\|a Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments.
650		4	\|a Reaction–diffusion equations \|7 (dpeaa)DE-He213
650		4	\|a Marine ecosystem \|7 (dpeaa)DE-He213
650		4	\|a Diffusion-driven instability \|7 (dpeaa)DE-He213
650		4	\|a Spatio-temporal dynamics \|7 (dpeaa)DE-He213
650		4	\|a Patchiness \|7 (dpeaa)DE-He213
700	1		\|a Manthena, Vamsi \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Nonlinear dynamics \|d Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 \|g 81(2015), 4 vom: 01. Mai, Seite 1895-1906 \|w (DE-627)315297034 \|w (DE-600)2012600-1 \|x 1573-269X \|7 nnns
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912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
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912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
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912			\|a GBV_ILN_2025
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912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2057
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912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2070
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912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2116
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2119
912			\|a GBV_ILN_2122
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912			\|a GBV_ILN_2143
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912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
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author_variant	k c kc v m vm
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publishDate	2015
allfields	10.1007/s11071-015-2114-1 doi (DE-627)SPR016380177 (SPR)s11071-015-2114-1-e DE-627 ger DE-627 rakwb eng 510 ASE 30.20 bkl Chakraborty, Kunal verfasserin aut Modelling and analysis of spatio-temporal dynamics of a marine ecosystem 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments. Reaction–diffusion equations (dpeaa)DE-He213 Marine ecosystem (dpeaa)DE-He213 Diffusion-driven instability (dpeaa)DE-He213 Spatio-temporal dynamics (dpeaa)DE-He213 Patchiness (dpeaa)DE-He213 Manthena, Vamsi verfasserin aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 81(2015), 4 vom: 01. Mai, Seite 1895-1906 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:81 year:2015 number:4 day:01 month:05 pages:1895-1906 https://dx.doi.org/10.1007/s11071-015-2114-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 30.20 ASE AR 81 2015 4 01 05 1895-1906
spelling	10.1007/s11071-015-2114-1 doi (DE-627)SPR016380177 (SPR)s11071-015-2114-1-e DE-627 ger DE-627 rakwb eng 510 ASE 30.20 bkl Chakraborty, Kunal verfasserin aut Modelling and analysis of spatio-temporal dynamics of a marine ecosystem 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments. Reaction–diffusion equations (dpeaa)DE-He213 Marine ecosystem (dpeaa)DE-He213 Diffusion-driven instability (dpeaa)DE-He213 Spatio-temporal dynamics (dpeaa)DE-He213 Patchiness (dpeaa)DE-He213 Manthena, Vamsi verfasserin aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 81(2015), 4 vom: 01. Mai, Seite 1895-1906 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:81 year:2015 number:4 day:01 month:05 pages:1895-1906 https://dx.doi.org/10.1007/s11071-015-2114-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 30.20 ASE AR 81 2015 4 01 05 1895-1906
allfields_unstemmed	10.1007/s11071-015-2114-1 doi (DE-627)SPR016380177 (SPR)s11071-015-2114-1-e DE-627 ger DE-627 rakwb eng 510 ASE 30.20 bkl Chakraborty, Kunal verfasserin aut Modelling and analysis of spatio-temporal dynamics of a marine ecosystem 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments. Reaction–diffusion equations (dpeaa)DE-He213 Marine ecosystem (dpeaa)DE-He213 Diffusion-driven instability (dpeaa)DE-He213 Spatio-temporal dynamics (dpeaa)DE-He213 Patchiness (dpeaa)DE-He213 Manthena, Vamsi verfasserin aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 81(2015), 4 vom: 01. Mai, Seite 1895-1906 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:81 year:2015 number:4 day:01 month:05 pages:1895-1906 https://dx.doi.org/10.1007/s11071-015-2114-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 30.20 ASE AR 81 2015 4 01 05 1895-1906
allfieldsGer	10.1007/s11071-015-2114-1 doi (DE-627)SPR016380177 (SPR)s11071-015-2114-1-e DE-627 ger DE-627 rakwb eng 510 ASE 30.20 bkl Chakraborty, Kunal verfasserin aut Modelling and analysis of spatio-temporal dynamics of a marine ecosystem 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments. Reaction–diffusion equations (dpeaa)DE-He213 Marine ecosystem (dpeaa)DE-He213 Diffusion-driven instability (dpeaa)DE-He213 Spatio-temporal dynamics (dpeaa)DE-He213 Patchiness (dpeaa)DE-He213 Manthena, Vamsi verfasserin aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 81(2015), 4 vom: 01. Mai, Seite 1895-1906 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:81 year:2015 number:4 day:01 month:05 pages:1895-1906 https://dx.doi.org/10.1007/s11071-015-2114-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 30.20 ASE AR 81 2015 4 01 05 1895-1906
allfieldsSound	10.1007/s11071-015-2114-1 doi (DE-627)SPR016380177 (SPR)s11071-015-2114-1-e DE-627 ger DE-627 rakwb eng 510 ASE 30.20 bkl Chakraborty, Kunal verfasserin aut Modelling and analysis of spatio-temporal dynamics of a marine ecosystem 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments. Reaction–diffusion equations (dpeaa)DE-He213 Marine ecosystem (dpeaa)DE-He213 Diffusion-driven instability (dpeaa)DE-He213 Spatio-temporal dynamics (dpeaa)DE-He213 Patchiness (dpeaa)DE-He213 Manthena, Vamsi verfasserin aut Enthalten in Nonlinear dynamics Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 81(2015), 4 vom: 01. Mai, Seite 1895-1906 (DE-627)315297034 (DE-600)2012600-1 1573-269X nnns volume:81 year:2015 number:4 day:01 month:05 pages:1895-1906 https://dx.doi.org/10.1007/s11071-015-2114-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 30.20 ASE AR 81 2015 4 01 05 1895-1906
language	English
source	Enthalten in Nonlinear dynamics 81(2015), 4 vom: 01. Mai, Seite 1895-1906 volume:81 year:2015 number:4 day:01 month:05 pages:1895-1906
sourceStr	Enthalten in Nonlinear dynamics 81(2015), 4 vom: 01. Mai, Seite 1895-1906 volume:81 year:2015 number:4 day:01 month:05 pages:1895-1906
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Reaction–diffusion equations Marine ecosystem Diffusion-driven instability Spatio-temporal dynamics Patchiness
dewey-raw	510
isfreeaccess_bool	false
container_title	Nonlinear dynamics
authorswithroles_txt_mv	Chakraborty, Kunal @@aut@@ Manthena, Vamsi @@aut@@
publishDateDaySort_date	2015-05-01T00:00:00Z
hierarchy_top_id	315297034
dewey-sort	3510
id	SPR016380177
language_de	englisch
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author	Chakraborty, Kunal
spellingShingle	Chakraborty, Kunal ddc 510 bkl 30.20 misc Reaction–diffusion equations misc Marine ecosystem misc Diffusion-driven instability misc Spatio-temporal dynamics misc Patchiness Modelling and analysis of spatio-temporal dynamics of a marine ecosystem
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topic_title	510 ASE 30.20 bkl Modelling and analysis of spatio-temporal dynamics of a marine ecosystem Reaction–diffusion equations (dpeaa)DE-He213 Marine ecosystem (dpeaa)DE-He213 Diffusion-driven instability (dpeaa)DE-He213 Spatio-temporal dynamics (dpeaa)DE-He213 Patchiness (dpeaa)DE-He213
topic	ddc 510 bkl 30.20 misc Reaction–diffusion equations misc Marine ecosystem misc Diffusion-driven instability misc Spatio-temporal dynamics misc Patchiness
topic_unstemmed	ddc 510 bkl 30.20 misc Reaction–diffusion equations misc Marine ecosystem misc Diffusion-driven instability misc Spatio-temporal dynamics misc Patchiness
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title	Modelling and analysis of spatio-temporal dynamics of a marine ecosystem
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title_full	Modelling and analysis of spatio-temporal dynamics of a marine ecosystem
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title_sort	modelling and analysis of spatio-temporal dynamics of a marine ecosystem
title_auth	Modelling and analysis of spatio-temporal dynamics of a marine ecosystem
abstract	Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments.
abstractGer	Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments.
abstract_unstemmed	Abstract This paper examines the spatio-temporal dynamics of a marine ecosystem. The system is described by two reaction–diffusion equations. We consider a phytoplankton–zooplankton system with Ivlev-type grazing function. The dynamics of the reaction–diffusion system of phytoplankton–zooplankton interaction has been studied with both constant and variable diffusion coefficients. Periodic oscillations of the phytoplankton and zooplankton populations are shown with constant and variable diffusion coefficients. In order to obtain spatio-temporal patterns, we perform numerical simulations of the coupled system describing phytoplankton–zooplankton dynamics in the presence of diffusive forces. We explain how the concentration of species changes due to local reactions and diffusion. Our results suggest that patchiness is one of the basic characteristics of the functioning of an ecological system. Two-dimensional spatial patterns of phytoplankton–zooplankton dynamics are self-organized and, therefore, can be considered to provide a theoretical framework to understand patchiness in marine environments.
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container_issue	4
title_short	Modelling and analysis of spatio-temporal dynamics of a marine ecosystem
url	https://dx.doi.org/10.1007/s11071-015-2114-1
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author2	Manthena, Vamsi
author2Str	Manthena, Vamsi
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doi_str	10.1007/s11071-015-2114-1
up_date	2024-07-03T22:44:04.015Z
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Modelling and analysis of spatio-temporal dynamics of a marine ecosystem

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