Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models

Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact...
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Autor*in:	Guirey, E. J. [verfasserIn] Bees, M. A. Martin, A. P. Srokosz, M. A. Fasham, M. J. R.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2007

Schlagwörter:	Plankton patchiness Synchronisation Metapopulation Biophysical modelling

Anmerkung:	© Springer Science+Business Media, Inc. 2007

Übergeordnetes Werk:	Enthalten in: Bulletin of mathematical biology - New York, NY : Springer, 1939, 69(2007), 4 vom: 15. März, Seite 1401-1422
Übergeordnetes Werk:	volume:69 ; year:2007 ; number:4 ; day:15 ; month:03 ; pages:1401-1422

Links:	Volltext

DOI / URN:	10.1007/s11538-006-9180-y

Katalog-ID:	SPR021177937

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520			\|a Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care.
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allfields	10.1007/s11538-006-9180-y doi (DE-627)SPR021177937 (SPR)s11538-006-9180-y-e DE-627 ger DE-627 rakwb eng Guirey, E. J. verfasserin aut Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, Inc. 2007 Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. Plankton patchiness (dpeaa)DE-He213 Synchronisation (dpeaa)DE-He213 Metapopulation (dpeaa)DE-He213 Biophysical modelling (dpeaa)DE-He213 Bees, M. A. aut Martin, A. P. aut Srokosz, M. A. aut Fasham, M. J. R. aut Enthalten in Bulletin of mathematical biology New York, NY : Springer, 1939 69(2007), 4 vom: 15. März, Seite 1401-1422 (DE-627)25463429X (DE-600)1462512-X 1522-9602 nnns volume:69 year:2007 number:4 day:15 month:03 pages:1401-1422 https://dx.doi.org/10.1007/s11538-006-9180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_266 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_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_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2153 GBV_ILN_2188 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2007 4 15 03 1401-1422
spelling	10.1007/s11538-006-9180-y doi (DE-627)SPR021177937 (SPR)s11538-006-9180-y-e DE-627 ger DE-627 rakwb eng Guirey, E. J. verfasserin aut Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, Inc. 2007 Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. Plankton patchiness (dpeaa)DE-He213 Synchronisation (dpeaa)DE-He213 Metapopulation (dpeaa)DE-He213 Biophysical modelling (dpeaa)DE-He213 Bees, M. A. aut Martin, A. P. aut Srokosz, M. A. aut Fasham, M. J. R. aut Enthalten in Bulletin of mathematical biology New York, NY : Springer, 1939 69(2007), 4 vom: 15. März, Seite 1401-1422 (DE-627)25463429X (DE-600)1462512-X 1522-9602 nnns volume:69 year:2007 number:4 day:15 month:03 pages:1401-1422 https://dx.doi.org/10.1007/s11538-006-9180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_266 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_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_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2153 GBV_ILN_2188 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2007 4 15 03 1401-1422
allfields_unstemmed	10.1007/s11538-006-9180-y doi (DE-627)SPR021177937 (SPR)s11538-006-9180-y-e DE-627 ger DE-627 rakwb eng Guirey, E. J. verfasserin aut Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, Inc. 2007 Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. Plankton patchiness (dpeaa)DE-He213 Synchronisation (dpeaa)DE-He213 Metapopulation (dpeaa)DE-He213 Biophysical modelling (dpeaa)DE-He213 Bees, M. A. aut Martin, A. P. aut Srokosz, M. A. aut Fasham, M. J. R. aut Enthalten in Bulletin of mathematical biology New York, NY : Springer, 1939 69(2007), 4 vom: 15. März, Seite 1401-1422 (DE-627)25463429X (DE-600)1462512-X 1522-9602 nnns volume:69 year:2007 number:4 day:15 month:03 pages:1401-1422 https://dx.doi.org/10.1007/s11538-006-9180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_266 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_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_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2153 GBV_ILN_2188 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2007 4 15 03 1401-1422
allfieldsGer	10.1007/s11538-006-9180-y doi (DE-627)SPR021177937 (SPR)s11538-006-9180-y-e DE-627 ger DE-627 rakwb eng Guirey, E. J. verfasserin aut Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, Inc. 2007 Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. Plankton patchiness (dpeaa)DE-He213 Synchronisation (dpeaa)DE-He213 Metapopulation (dpeaa)DE-He213 Biophysical modelling (dpeaa)DE-He213 Bees, M. A. aut Martin, A. P. aut Srokosz, M. A. aut Fasham, M. J. R. aut Enthalten in Bulletin of mathematical biology New York, NY : Springer, 1939 69(2007), 4 vom: 15. März, Seite 1401-1422 (DE-627)25463429X (DE-600)1462512-X 1522-9602 nnns volume:69 year:2007 number:4 day:15 month:03 pages:1401-1422 https://dx.doi.org/10.1007/s11538-006-9180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_266 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_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_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2153 GBV_ILN_2188 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2007 4 15 03 1401-1422
allfieldsSound	10.1007/s11538-006-9180-y doi (DE-627)SPR021177937 (SPR)s11538-006-9180-y-e DE-627 ger DE-627 rakwb eng Guirey, E. J. verfasserin aut Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media, Inc. 2007 Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. Plankton patchiness (dpeaa)DE-He213 Synchronisation (dpeaa)DE-He213 Metapopulation (dpeaa)DE-He213 Biophysical modelling (dpeaa)DE-He213 Bees, M. A. aut Martin, A. P. aut Srokosz, M. A. aut Fasham, M. J. R. aut Enthalten in Bulletin of mathematical biology New York, NY : Springer, 1939 69(2007), 4 vom: 15. März, Seite 1401-1422 (DE-627)25463429X (DE-600)1462512-X 1522-9602 nnns volume:69 year:2007 number:4 day:15 month:03 pages:1401-1422 https://dx.doi.org/10.1007/s11538-006-9180-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_266 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_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_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2110 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2153 GBV_ILN_2188 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 69 2007 4 15 03 1401-1422
language	English
source	Enthalten in Bulletin of mathematical biology 69(2007), 4 vom: 15. März, Seite 1401-1422 volume:69 year:2007 number:4 day:15 month:03 pages:1401-1422
sourceStr	Enthalten in Bulletin of mathematical biology 69(2007), 4 vom: 15. März, Seite 1401-1422 volume:69 year:2007 number:4 day:15 month:03 pages:1401-1422
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Plankton patchiness Synchronisation Metapopulation Biophysical modelling
isfreeaccess_bool	false
container_title	Bulletin of mathematical biology
authorswithroles_txt_mv	Guirey, E. J. @@aut@@ Bees, M. A. @@aut@@ Martin, A. P. @@aut@@ Srokosz, M. A. @@aut@@ Fasham, M. J. R. @@aut@@
publishDateDaySort_date	2007-03-15T00:00:00Z
hierarchy_top_id	25463429X
id	SPR021177937
language_de	englisch
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author	Guirey, E. J.
spellingShingle	Guirey, E. J. misc Plankton patchiness misc Synchronisation misc Metapopulation misc Biophysical modelling Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models
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topic_title	Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models Plankton patchiness (dpeaa)DE-He213 Synchronisation (dpeaa)DE-He213 Metapopulation (dpeaa)DE-He213 Biophysical modelling (dpeaa)DE-He213
topic	misc Plankton patchiness misc Synchronisation misc Metapopulation misc Biophysical modelling
topic_unstemmed	misc Plankton patchiness misc Synchronisation misc Metapopulation misc Biophysical modelling
topic_browse	misc Plankton patchiness misc Synchronisation misc Metapopulation misc Biophysical modelling
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title	Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models
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title_full	Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models
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author_browse	Guirey, E. J. Bees, M. A. Martin, A. P. Srokosz, M. A. Fasham, M. J. R.
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title_sort	emergent features due to grid-cell biology: synchronisation in biophysical models
title_auth	Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models
abstract	Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. © Springer Science+Business Media, Inc. 2007
abstractGer	Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. © Springer Science+Business Media, Inc. 2007
abstract_unstemmed	Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. It is shown that chaotic ecosystem dynamics, in particular, should be used with care. © Springer Science+Business Media, Inc. 2007
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title_short	Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models
url	https://dx.doi.org/10.1007/s11538-006-9180-y
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J.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Emergent Features Due to Grid-Cell Biology: Synchronisation in Biophysical Models</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2007</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, Inc. 2007</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Modelling studies of upper ocean phenomena, such as that of the spatial and temporal patchiness in plankton distributions, typically employ coupled biophysical models, with biology in each grid-cell represented by a plankton ecosystem model. It has not generally been considered what impact the choice of grid-cell ecosystem model, from the many developed in the literature, might have upon the results of such a study. We use the methods of synchronisation theory, which is concerned with ensembles of interacting oscillators, to address this question, considering the simplest possible case of a chain of identically represented interacting plankton grid-cells. It is shown that the ability of the system to exhibit stably homogeneous (fully synchronised) dynamics depends crucially upon the choice of biological model and number of grid-cells, with dynamics changing dramatically at a threshold strength of mixing between grid-cells. Consequently, for modelling studies of the ocean the resolution chosen, and therefore number of grid-cells used, could drastically alter the emergent features of the model. 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