Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters

Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using...
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Autor*in:	Ryu, Jongseong [verfasserIn] Kim, Hae-Cheol [verfasserIn] Khim, Jong Seong [verfasserIn] Kim, Yong Hoon [verfasserIn] Park, Jinsoon [verfasserIn] Kang, Daeseok [verfasserIn] Hwang, Jin Hwan [verfasserIn] Lee, Chang-Hee [verfasserIn] Koh, Chul-Hwan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2011

Schlagwörter:	Logistic regression Statistical modeling Benthic macrofauna Saemangeum Tidal flat

Übergeordnetes Werk:	Enthalten in: Ecological research - Bognor Regis : Wiley, 1986, 26(2011), 3 vom: 20. Apr., Seite 659-668
Übergeordnetes Werk:	volume:26 ; year:2011 ; number:3 ; day:20 ; month:04 ; pages:659-668

Links:	Volltext

DOI / URN:	10.1007/s11284-011-0826-3

Katalog-ID:	SPR018635016

Internformat


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245	1	0	\|a Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters
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520			\|a Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management.
650		4	\|a Logistic regression \|7 (dpeaa)DE-He213
650		4	\|a Statistical modeling \|7 (dpeaa)DE-He213
650		4	\|a Benthic macrofauna \|7 (dpeaa)DE-He213
650		4	\|a Saemangeum \|7 (dpeaa)DE-He213
650		4	\|a Tidal flat \|7 (dpeaa)DE-He213
700	1		\|a Kim, Hae-Cheol \|e verfasserin \|4 aut
700	1		\|a Khim, Jong Seong \|e verfasserin \|4 aut
700	1		\|a Kim, Yong Hoon \|e verfasserin \|4 aut
700	1		\|a Park, Jinsoon \|e verfasserin \|4 aut
700	1		\|a Kang, Daeseok \|e verfasserin \|4 aut
700	1		\|a Hwang, Jin Hwan \|e verfasserin \|4 aut
700	1		\|a Lee, Chang-Hee \|e verfasserin \|4 aut
700	1		\|a Koh, Chul-Hwan \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Ecological research \|d Bognor Regis : Wiley, 1986 \|g 26(2011), 3 vom: 20. Apr., Seite 659-668 \|w (DE-627)320630773 \|w (DE-600)2023900-2 \|x 1440-1703 \|7 nnns
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matchkey_str	article:14401703:2011----::rdcinfarzoetiseisitiuinnhkraseagutdlltaeoaoitcers
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publishDate	2011
allfields	10.1007/s11284-011-0826-3 doi (DE-627)SPR018635016 (SPR)s11284-011-0826-3-e DE-627 ger DE-627 rakwb eng 570 630 ASE 42.00 bkl Ryu, Jongseong verfasserin aut Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management. Logistic regression (dpeaa)DE-He213 Statistical modeling (dpeaa)DE-He213 Benthic macrofauna (dpeaa)DE-He213 Saemangeum (dpeaa)DE-He213 Tidal flat (dpeaa)DE-He213 Kim, Hae-Cheol verfasserin aut Khim, Jong Seong verfasserin aut Kim, Yong Hoon verfasserin aut Park, Jinsoon verfasserin aut Kang, Daeseok verfasserin aut Hwang, Jin Hwan verfasserin aut Lee, Chang-Hee verfasserin aut Koh, Chul-Hwan verfasserin aut Enthalten in Ecological research Bognor Regis : Wiley, 1986 26(2011), 3 vom: 20. Apr., Seite 659-668 (DE-627)320630773 (DE-600)2023900-2 1440-1703 nnns volume:26 year:2011 number:3 day:20 month:04 pages:659-668 https://dx.doi.org/10.1007/s11284-011-0826-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_101 GBV_ILN_105 GBV_ILN_110 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_2056 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_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_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 42.00 ASE AR 26 2011 3 20 04 659-668
spelling	10.1007/s11284-011-0826-3 doi (DE-627)SPR018635016 (SPR)s11284-011-0826-3-e DE-627 ger DE-627 rakwb eng 570 630 ASE 42.00 bkl Ryu, Jongseong verfasserin aut Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management. Logistic regression (dpeaa)DE-He213 Statistical modeling (dpeaa)DE-He213 Benthic macrofauna (dpeaa)DE-He213 Saemangeum (dpeaa)DE-He213 Tidal flat (dpeaa)DE-He213 Kim, Hae-Cheol verfasserin aut Khim, Jong Seong verfasserin aut Kim, Yong Hoon verfasserin aut Park, Jinsoon verfasserin aut Kang, Daeseok verfasserin aut Hwang, Jin Hwan verfasserin aut Lee, Chang-Hee verfasserin aut Koh, Chul-Hwan verfasserin aut Enthalten in Ecological research Bognor Regis : Wiley, 1986 26(2011), 3 vom: 20. Apr., Seite 659-668 (DE-627)320630773 (DE-600)2023900-2 1440-1703 nnns volume:26 year:2011 number:3 day:20 month:04 pages:659-668 https://dx.doi.org/10.1007/s11284-011-0826-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_101 GBV_ILN_105 GBV_ILN_110 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_2056 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_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_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 42.00 ASE AR 26 2011 3 20 04 659-668
allfields_unstemmed	10.1007/s11284-011-0826-3 doi (DE-627)SPR018635016 (SPR)s11284-011-0826-3-e DE-627 ger DE-627 rakwb eng 570 630 ASE 42.00 bkl Ryu, Jongseong verfasserin aut Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management. Logistic regression (dpeaa)DE-He213 Statistical modeling (dpeaa)DE-He213 Benthic macrofauna (dpeaa)DE-He213 Saemangeum (dpeaa)DE-He213 Tidal flat (dpeaa)DE-He213 Kim, Hae-Cheol verfasserin aut Khim, Jong Seong verfasserin aut Kim, Yong Hoon verfasserin aut Park, Jinsoon verfasserin aut Kang, Daeseok verfasserin aut Hwang, Jin Hwan verfasserin aut Lee, Chang-Hee verfasserin aut Koh, Chul-Hwan verfasserin aut Enthalten in Ecological research Bognor Regis : Wiley, 1986 26(2011), 3 vom: 20. Apr., Seite 659-668 (DE-627)320630773 (DE-600)2023900-2 1440-1703 nnns volume:26 year:2011 number:3 day:20 month:04 pages:659-668 https://dx.doi.org/10.1007/s11284-011-0826-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_101 GBV_ILN_105 GBV_ILN_110 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_2056 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_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_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 42.00 ASE AR 26 2011 3 20 04 659-668
allfieldsGer	10.1007/s11284-011-0826-3 doi (DE-627)SPR018635016 (SPR)s11284-011-0826-3-e DE-627 ger DE-627 rakwb eng 570 630 ASE 42.00 bkl Ryu, Jongseong verfasserin aut Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management. Logistic regression (dpeaa)DE-He213 Statistical modeling (dpeaa)DE-He213 Benthic macrofauna (dpeaa)DE-He213 Saemangeum (dpeaa)DE-He213 Tidal flat (dpeaa)DE-He213 Kim, Hae-Cheol verfasserin aut Khim, Jong Seong verfasserin aut Kim, Yong Hoon verfasserin aut Park, Jinsoon verfasserin aut Kang, Daeseok verfasserin aut Hwang, Jin Hwan verfasserin aut Lee, Chang-Hee verfasserin aut Koh, Chul-Hwan verfasserin aut Enthalten in Ecological research Bognor Regis : Wiley, 1986 26(2011), 3 vom: 20. Apr., Seite 659-668 (DE-627)320630773 (DE-600)2023900-2 1440-1703 nnns volume:26 year:2011 number:3 day:20 month:04 pages:659-668 https://dx.doi.org/10.1007/s11284-011-0826-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_101 GBV_ILN_105 GBV_ILN_110 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_2056 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_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_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 42.00 ASE AR 26 2011 3 20 04 659-668
allfieldsSound	10.1007/s11284-011-0826-3 doi (DE-627)SPR018635016 (SPR)s11284-011-0826-3-e DE-627 ger DE-627 rakwb eng 570 630 ASE 42.00 bkl Ryu, Jongseong verfasserin aut Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management. Logistic regression (dpeaa)DE-He213 Statistical modeling (dpeaa)DE-He213 Benthic macrofauna (dpeaa)DE-He213 Saemangeum (dpeaa)DE-He213 Tidal flat (dpeaa)DE-He213 Kim, Hae-Cheol verfasserin aut Khim, Jong Seong verfasserin aut Kim, Yong Hoon verfasserin aut Park, Jinsoon verfasserin aut Kang, Daeseok verfasserin aut Hwang, Jin Hwan verfasserin aut Lee, Chang-Hee verfasserin aut Koh, Chul-Hwan verfasserin aut Enthalten in Ecological research Bognor Regis : Wiley, 1986 26(2011), 3 vom: 20. Apr., Seite 659-668 (DE-627)320630773 (DE-600)2023900-2 1440-1703 nnns volume:26 year:2011 number:3 day:20 month:04 pages:659-668 https://dx.doi.org/10.1007/s11284-011-0826-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA 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_101 GBV_ILN_105 GBV_ILN_110 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_266 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_2056 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_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_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 42.00 ASE AR 26 2011 3 20 04 659-668
language	English
source	Enthalten in Ecological research 26(2011), 3 vom: 20. Apr., Seite 659-668 volume:26 year:2011 number:3 day:20 month:04 pages:659-668
sourceStr	Enthalten in Ecological research 26(2011), 3 vom: 20. Apr., Seite 659-668 volume:26 year:2011 number:3 day:20 month:04 pages:659-668
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Logistic regression Statistical modeling Benthic macrofauna Saemangeum Tidal flat
dewey-raw	570
isfreeaccess_bool	false
container_title	Ecological research
authorswithroles_txt_mv	Ryu, Jongseong @@aut@@ Kim, Hae-Cheol @@aut@@ Khim, Jong Seong @@aut@@ Kim, Yong Hoon @@aut@@ Park, Jinsoon @@aut@@ Kang, Daeseok @@aut@@ Hwang, Jin Hwan @@aut@@ Lee, Chang-Hee @@aut@@ Koh, Chul-Hwan @@aut@@
publishDateDaySort_date	2011-04-20T00:00:00Z
hierarchy_top_id	320630773
dewey-sort	3570
id	SPR018635016
language_de	englisch
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author	Ryu, Jongseong
spellingShingle	Ryu, Jongseong ddc 570 bkl 42.00 misc Logistic regression misc Statistical modeling misc Benthic macrofauna misc Saemangeum misc Tidal flat Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters
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topic_title	570 630 ASE 42.00 bkl Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters Logistic regression (dpeaa)DE-He213 Statistical modeling (dpeaa)DE-He213 Benthic macrofauna (dpeaa)DE-He213 Saemangeum (dpeaa)DE-He213 Tidal flat (dpeaa)DE-He213
topic	ddc 570 bkl 42.00 misc Logistic regression misc Statistical modeling misc Benthic macrofauna misc Saemangeum misc Tidal flat
topic_unstemmed	ddc 570 bkl 42.00 misc Logistic regression misc Statistical modeling misc Benthic macrofauna misc Saemangeum misc Tidal flat
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title	Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters
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title_full	Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters
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author_browse	Ryu, Jongseong Kim, Hae-Cheol Khim, Jong Seong Kim, Yong Hoon Park, Jinsoon Kang, Daeseok Hwang, Jin Hwan Lee, Chang-Hee Koh, Chul-Hwan
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title_sort	prediction of macrozoobenthic species distribution in the korean saemangeum tidal flat based on a logistic regression model of environmental parameters
title_auth	Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters
abstract	Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management.
abstractGer	Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management.
abstract_unstemmed	Abstract This study aims to contribute to the development of heuristic statistical models, which are able to predict benthic macrofaunal responses to environmental gradients in coastal areas, such as tidal flats. Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. Our modeling approach was capable of predicting macrobenthic species distributions with a relatively high degree of accuracy, although the ecological processes controlling intertidal macrobenthic distribution could not be fully determined. Overall, good agreement between modeling results and field observations, with relatively high concordance regardless of target species, emphasized that such an approach would be of practical use in terms of ecosystem approach to tidal flat management.
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title_short	Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters
url	https://dx.doi.org/10.1007/s11284-011-0826-3
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author2	Kim, Hae-Cheol Khim, Jong Seong Kim, Yong Hoon Park, Jinsoon Kang, Daeseok Hwang, Jin Hwan Lee, Chang-Hee Koh, Chul-Hwan
author2Str	Kim, Hae-Cheol Khim, Jong Seong Kim, Yong Hoon Park, Jinsoon Kang, Daeseok Hwang, Jin Hwan Lee, Chang-Hee Koh, Chul-Hwan
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doi_str	10.1007/s11284-011-0826-3
up_date	2024-07-03T21:07:18.047Z
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Ecological response surfaces were derived for 15 intertidal macrobenthic species, using logistic regression based on three separate environmental parameters (shore level, mud content, and organic content) measured on the tidal flats of the Saemangeum estuary, Korea. The presence/absence of the 15 intertidal macrofauna was accurately predicted from each separate environmental factor in the environmental models, with a prediction accuracy of ~65–92%. Subsequently, geographical comparison was made between the mapped probability surfaces and maps of observed species occurrence. The results indicated that the models developed for different species exhibited a wide variety of functional forms, highlighting potential variability in species response to changes in habitat conditions, even for closely associated species with a similar trophic type. 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Prediction of macrozoobenthic species distribution in the Korean Saemangeum tidal flat based on a logistic regression model of environmental parameters

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