The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin
Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pi...
Ausführliche Beschreibung
Autor*in: |
Wang, Hongxiang [verfasserIn] |
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E-Artikel |
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Englisch |
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2024 |
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Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Übergeordnetes Werk: |
Enthalten in: Environmental science and pollution research - Berlin : Springer, 1994, 31(2024), 6 vom: 05. Jan., Seite 8483-8498 |
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Übergeordnetes Werk: |
volume:31 ; year:2024 ; number:6 ; day:05 ; month:01 ; pages:8483-8498 |
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DOI / URN: |
10.1007/s11356-023-31673-4 |
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Katalog-ID: |
SPR054563569 |
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245 | 1 | 4 | |a The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin |
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520 | |a Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. | ||
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650 | 4 | |a Hydrological variability |7 (dpeaa)DE-He213 | |
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700 | 1 | |a Bai, Xiangyu |4 aut | |
700 | 1 | |a Huang, Lintong |4 aut | |
700 | 1 | |a Hong, Fengtian |4 aut | |
700 | 1 | |a Yuan, Weiqi |4 aut | |
700 | 1 | |a Guo, Wenxian |4 aut | |
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10.1007/s11356-023-31673-4 doi (DE-627)SPR054563569 (SPR)s11356-023-31673-4-e DE-627 ger DE-627 rakwb eng Wang, Hongxiang verfasserin aut The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. Connectivity floodplain wetlands (dpeaa)DE-He213 Hydrological variability (dpeaa)DE-He213 Vegetation succession (dpeaa)DE-He213 Ecological effect (dpeaa)DE-He213 Bai, Xiangyu aut Huang, Lintong aut Hong, Fengtian aut Yuan, Weiqi aut Guo, Wenxian aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 31(2024), 6 vom: 05. Jan., Seite 8483-8498 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:31 year:2024 number:6 day:05 month:01 pages:8483-8498 https://dx.doi.org/10.1007/s11356-023-31673-4 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2024 6 05 01 8483-8498 |
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10.1007/s11356-023-31673-4 doi (DE-627)SPR054563569 (SPR)s11356-023-31673-4-e DE-627 ger DE-627 rakwb eng Wang, Hongxiang verfasserin aut The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. Connectivity floodplain wetlands (dpeaa)DE-He213 Hydrological variability (dpeaa)DE-He213 Vegetation succession (dpeaa)DE-He213 Ecological effect (dpeaa)DE-He213 Bai, Xiangyu aut Huang, Lintong aut Hong, Fengtian aut Yuan, Weiqi aut Guo, Wenxian aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 31(2024), 6 vom: 05. Jan., Seite 8483-8498 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:31 year:2024 number:6 day:05 month:01 pages:8483-8498 https://dx.doi.org/10.1007/s11356-023-31673-4 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2024 6 05 01 8483-8498 |
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10.1007/s11356-023-31673-4 doi (DE-627)SPR054563569 (SPR)s11356-023-31673-4-e DE-627 ger DE-627 rakwb eng Wang, Hongxiang verfasserin aut The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. Connectivity floodplain wetlands (dpeaa)DE-He213 Hydrological variability (dpeaa)DE-He213 Vegetation succession (dpeaa)DE-He213 Ecological effect (dpeaa)DE-He213 Bai, Xiangyu aut Huang, Lintong aut Hong, Fengtian aut Yuan, Weiqi aut Guo, Wenxian aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 31(2024), 6 vom: 05. Jan., Seite 8483-8498 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:31 year:2024 number:6 day:05 month:01 pages:8483-8498 https://dx.doi.org/10.1007/s11356-023-31673-4 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2024 6 05 01 8483-8498 |
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10.1007/s11356-023-31673-4 doi (DE-627)SPR054563569 (SPR)s11356-023-31673-4-e DE-627 ger DE-627 rakwb eng Wang, Hongxiang verfasserin aut The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. Connectivity floodplain wetlands (dpeaa)DE-He213 Hydrological variability (dpeaa)DE-He213 Vegetation succession (dpeaa)DE-He213 Ecological effect (dpeaa)DE-He213 Bai, Xiangyu aut Huang, Lintong aut Hong, Fengtian aut Yuan, Weiqi aut Guo, Wenxian aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 31(2024), 6 vom: 05. Jan., Seite 8483-8498 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:31 year:2024 number:6 day:05 month:01 pages:8483-8498 https://dx.doi.org/10.1007/s11356-023-31673-4 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2024 6 05 01 8483-8498 |
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10.1007/s11356-023-31673-4 doi (DE-627)SPR054563569 (SPR)s11356-023-31673-4-e DE-627 ger DE-627 rakwb eng Wang, Hongxiang verfasserin aut The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. Connectivity floodplain wetlands (dpeaa)DE-He213 Hydrological variability (dpeaa)DE-He213 Vegetation succession (dpeaa)DE-He213 Ecological effect (dpeaa)DE-He213 Bai, Xiangyu aut Huang, Lintong aut Hong, Fengtian aut Yuan, Weiqi aut Guo, Wenxian aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 31(2024), 6 vom: 05. Jan., Seite 8483-8498 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:31 year:2024 number:6 day:05 month:01 pages:8483-8498 https://dx.doi.org/10.1007/s11356-023-31673-4 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_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_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 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_2118 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_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 31 2024 6 05 01 8483-8498 |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. 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Wang, Hongxiang |
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Wang, Hongxiang misc Connectivity floodplain wetlands misc Hydrological variability misc Vegetation succession misc Ecological effect The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin |
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The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin Connectivity floodplain wetlands (dpeaa)DE-He213 Hydrological variability (dpeaa)DE-He213 Vegetation succession (dpeaa)DE-He213 Ecological effect (dpeaa)DE-He213 |
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misc Connectivity floodplain wetlands misc Hydrological variability misc Vegetation succession misc Ecological effect |
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The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin |
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The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin |
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Wang, Hongxiang |
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Environmental science and pollution research |
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Wang, Hongxiang Bai, Xiangyu Huang, Lintong Hong, Fengtian Yuan, Weiqi Guo, Wenxian |
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spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: dongting lake basin |
title_auth |
The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin |
abstract |
Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstractGer |
Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstract_unstemmed |
Abstract Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) — hydrological status (S) — vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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container_issue |
6 |
title_short |
The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin |
url |
https://dx.doi.org/10.1007/s11356-023-31673-4 |
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Bai, Xiangyu Huang, Lintong Hong, Fengtian Yuan, Weiqi Guo, Wenxian |
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doi_str |
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up_date |
2024-07-04T02:11:55.988Z |
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score |
7.403078 |