Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data

Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is est...
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Autor*in:	Andréfouët, Serge [verfasserIn] Zubia, Mayalen Payri, Claude

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2004

Schlagwörter:	Macrophyte Seagrass Biotechnology Moorea Tahiti French Polynesia Remote sensing

Anmerkung:	© Springer-Verlag 2004

Übergeordnetes Werk:	Enthalten in: Coral reefs - Berlin : Springer, 1982, 23(2004), 1 vom: 17. Feb., Seite 26-38
Übergeordnetes Werk:	volume:23 ; year:2004 ; number:1 ; day:17 ; month:02 ; pages:26-38

Links:	Volltext

DOI / URN:	10.1007/s00338-003-0367-5

Katalog-ID:	SPR004530748

Internformat


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100	1		\|a Andréfouët, Serge \|e verfasserin \|4 aut
245	1	0	\|a Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data
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520			\|a Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima.
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650		4	\|a French Polynesia \|7 (dpeaa)DE-He213
650		4	\|a Remote sensing \|7 (dpeaa)DE-He213
700	1		\|a Zubia, Mayalen \|4 aut
700	1		\|a Payri, Claude \|4 aut
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856	4	0	\|u https://dx.doi.org/10.1007/s00338-003-0367-5 \|z lizenzpflichtig \|3 Volltext
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912			\|a GBV_ILN_31
912			\|a GBV_ILN_32
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912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
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
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_267
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_381
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_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
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
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
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2070
912			\|a GBV_ILN_2086
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
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2144
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2188
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2472
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4046
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4246
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 23 \|j 2004 \|e 1 \|b 17 \|c 02 \|h 26-38

Indexfelder

author_variant	s a sa m z mz c p cp
matchkey_str	article:14320975:2004----::apnadimsetmtootenaierwageubnraraaunraadadagsumnaeesguosthlohtrgnosaiin
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publishDate	2004
allfields	10.1007/s00338-003-0367-5 doi (DE-627)SPR004530748 (SPR)s00338-003-0367-5-e DE-627 ger DE-627 rakwb eng Andréfouët, Serge verfasserin aut Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. Macrophyte (dpeaa)DE-He213 Seagrass (dpeaa)DE-He213 Biotechnology (dpeaa)DE-He213 Moorea (dpeaa)DE-He213 Tahiti (dpeaa)DE-He213 French Polynesia (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Zubia, Mayalen aut Payri, Claude aut Enthalten in Coral reefs Berlin : Springer, 1982 23(2004), 1 vom: 17. Feb., Seite 26-38 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:23 year:2004 number:1 day:17 month:02 pages:26-38 https://dx.doi.org/10.1007/s00338-003-0367-5 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_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_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_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 AR 23 2004 1 17 02 26-38
spelling	10.1007/s00338-003-0367-5 doi (DE-627)SPR004530748 (SPR)s00338-003-0367-5-e DE-627 ger DE-627 rakwb eng Andréfouët, Serge verfasserin aut Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. Macrophyte (dpeaa)DE-He213 Seagrass (dpeaa)DE-He213 Biotechnology (dpeaa)DE-He213 Moorea (dpeaa)DE-He213 Tahiti (dpeaa)DE-He213 French Polynesia (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Zubia, Mayalen aut Payri, Claude aut Enthalten in Coral reefs Berlin : Springer, 1982 23(2004), 1 vom: 17. Feb., Seite 26-38 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:23 year:2004 number:1 day:17 month:02 pages:26-38 https://dx.doi.org/10.1007/s00338-003-0367-5 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_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_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_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 AR 23 2004 1 17 02 26-38
allfields_unstemmed	10.1007/s00338-003-0367-5 doi (DE-627)SPR004530748 (SPR)s00338-003-0367-5-e DE-627 ger DE-627 rakwb eng Andréfouët, Serge verfasserin aut Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. Macrophyte (dpeaa)DE-He213 Seagrass (dpeaa)DE-He213 Biotechnology (dpeaa)DE-He213 Moorea (dpeaa)DE-He213 Tahiti (dpeaa)DE-He213 French Polynesia (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Zubia, Mayalen aut Payri, Claude aut Enthalten in Coral reefs Berlin : Springer, 1982 23(2004), 1 vom: 17. Feb., Seite 26-38 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:23 year:2004 number:1 day:17 month:02 pages:26-38 https://dx.doi.org/10.1007/s00338-003-0367-5 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_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_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_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 AR 23 2004 1 17 02 26-38
allfieldsGer	10.1007/s00338-003-0367-5 doi (DE-627)SPR004530748 (SPR)s00338-003-0367-5-e DE-627 ger DE-627 rakwb eng Andréfouët, Serge verfasserin aut Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. Macrophyte (dpeaa)DE-He213 Seagrass (dpeaa)DE-He213 Biotechnology (dpeaa)DE-He213 Moorea (dpeaa)DE-He213 Tahiti (dpeaa)DE-He213 French Polynesia (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Zubia, Mayalen aut Payri, Claude aut Enthalten in Coral reefs Berlin : Springer, 1982 23(2004), 1 vom: 17. Feb., Seite 26-38 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:23 year:2004 number:1 day:17 month:02 pages:26-38 https://dx.doi.org/10.1007/s00338-003-0367-5 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_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_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_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 AR 23 2004 1 17 02 26-38
allfieldsSound	10.1007/s00338-003-0367-5 doi (DE-627)SPR004530748 (SPR)s00338-003-0367-5-e DE-627 ger DE-627 rakwb eng Andréfouët, Serge verfasserin aut Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data 2004 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag 2004 Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. Macrophyte (dpeaa)DE-He213 Seagrass (dpeaa)DE-He213 Biotechnology (dpeaa)DE-He213 Moorea (dpeaa)DE-He213 Tahiti (dpeaa)DE-He213 French Polynesia (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Zubia, Mayalen aut Payri, Claude aut Enthalten in Coral reefs Berlin : Springer, 1982 23(2004), 1 vom: 17. Feb., Seite 26-38 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:23 year:2004 number:1 day:17 month:02 pages:26-38 https://dx.doi.org/10.1007/s00338-003-0367-5 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_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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_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_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_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 AR 23 2004 1 17 02 26-38
language	English
source	Enthalten in Coral reefs 23(2004), 1 vom: 17. Feb., Seite 26-38 volume:23 year:2004 number:1 day:17 month:02 pages:26-38
sourceStr	Enthalten in Coral reefs 23(2004), 1 vom: 17. Feb., Seite 26-38 volume:23 year:2004 number:1 day:17 month:02 pages:26-38
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Macrophyte Seagrass Biotechnology Moorea Tahiti French Polynesia Remote sensing
isfreeaccess_bool	false
container_title	Coral reefs
authorswithroles_txt_mv	Andréfouët, Serge @@aut@@ Zubia, Mayalen @@aut@@ Payri, Claude @@aut@@
publishDateDaySort_date	2004-02-17T00:00:00Z
hierarchy_top_id	268756112
id	SPR004530748
language_de	englisch
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author	Andréfouët, Serge
spellingShingle	Andréfouët, Serge misc Macrophyte misc Seagrass misc Biotechnology misc Moorea misc Tahiti misc French Polynesia misc Remote sensing Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data
authorStr	Andréfouët, Serge
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topic_title	Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data Macrophyte (dpeaa)DE-He213 Seagrass (dpeaa)DE-He213 Biotechnology (dpeaa)DE-He213 Moorea (dpeaa)DE-He213 Tahiti (dpeaa)DE-He213 French Polynesia (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213
topic	misc Macrophyte misc Seagrass misc Biotechnology misc Moorea misc Tahiti misc French Polynesia misc Remote sensing
topic_unstemmed	misc Macrophyte misc Seagrass misc Biotechnology misc Moorea misc Tahiti misc French Polynesia misc Remote sensing
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title	Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data
ctrlnum	(DE-627)SPR004530748 (SPR)s00338-003-0367-5-e
title_full	Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data
author_sort	Andréfouët, Serge
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author_browse	Andréfouët, Serge Zubia, Mayalen Payri, Claude
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author-letter	Andréfouët, Serge
doi_str_mv	10.1007/s00338-003-0367-5
title_sort	mapping and biomass estimation of the invasive brown algae turbinaria ornata (turner) j. agardh and sargassum mangarevense (grunow) setchell on heterogeneous tahitian coral reefs using 4-meter resolution ikonos satellite data
title_auth	Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data
abstract	Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. © Springer-Verlag 2004
abstractGer	Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. © Springer-Verlag 2004
abstract_unstemmed	Abstract Turbinaria ornata and Sargassum mangarevense (Halophyte, Sargassaceae) are two Fucales that have strong biotechnological potential for the cosmetic industries. To plan for the harvesting of these two species on Tahiti (French Polynesia, South Pacific Ocean) reefs, their total biomass is estimated for three morphologically different reefs using a combination of field data and three 4-m resolution IKONOS satellite images. Fieldwork provided mean algal cover for each of the main habitats of the reefs and a ubiquitous relationship linking percent cover and biomass. Images were used to map the spatial extent of the habitats. Image classification resulted in an overall habitat map accuracy of 70%. For the three reefs, the total biomass was 153,565 ± 73,441, 561,718 ± 192,956, and 215,203 ± 75,012 tons of dry matter, which yielded a mean areal biomass of 0.173 ± 0.083 kg.$ m^{−2} $,0.133 ± 0.046 kg.$ m^{−2} $, and 0.193 ± 0.067 kg.$ m^{−2 } $(dry matter). The different total and areal biomass reflect different reef structures and the abundance of suitable substratum for algal settlement. Images reveal the spatial distribution of the algae, mostly located on the outer edges (crest and dense back-reef) of the reefs. Since percent cover data were collected during the cool season when algal densities are at their highest, the computed biomasses are maxima. © Springer-Verlag 2004
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container_issue	1
title_short	Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data
url	https://dx.doi.org/10.1007/s00338-003-0367-5
remote_bool	true
author2	Zubia, Mayalen Payri, Claude
author2Str	Zubia, Mayalen Payri, Claude
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doi_str	10.1007/s00338-003-0367-5
up_date	2024-07-04T01:29:03.927Z
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Mapping and biomass estimation of the invasive brown algae Turbinaria ornata (Turner) J. Agardh and Sargassum mangarevense (Grunow) Setchell on heterogeneous Tahitian coral reefs using 4-meter resolution IKONOS satellite data

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