Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms

Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Han, Yaoyao [verfasserIn] Zhang, Ke [verfasserIn] Lin, Qi [verfasserIn] Huang, Shixin [verfasserIn] Yang, Xiangdong [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Socio-ecological system Ecosystem health index Sustainability Bayesian Hierarchy Model Freshwater ecosystems

Übergeordnetes Werk:	Enthalten in: Ecological indicators - Amsterdam [u.a.] : Elsevier Science, 2001, 147
Übergeordnetes Werk:	volume:147

DOI / URN:	10.1016/j.ecolind.2023.110007

Katalog-ID:	ELV009290729

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520			\|a Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems.
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700	1		\|a Yang, Xiangdong \|e verfasserin \|4 aut
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allfields	10.1016/j.ecolind.2023.110007 doi (DE-627)ELV009290729 (ELSEVIER)S1470-160X(23)00149-8 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Han, Yaoyao verfasserin (orcid)0000-0003-4150-7855 aut Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems. Socio-ecological system Ecosystem health index Sustainability Bayesian Hierarchy Model Freshwater ecosystems Zhang, Ke verfasserin aut Lin, Qi verfasserin aut Huang, Shixin verfasserin aut Yang, Xiangdong verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 147 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:147 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 147
spelling	10.1016/j.ecolind.2023.110007 doi (DE-627)ELV009290729 (ELSEVIER)S1470-160X(23)00149-8 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Han, Yaoyao verfasserin (orcid)0000-0003-4150-7855 aut Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems. Socio-ecological system Ecosystem health index Sustainability Bayesian Hierarchy Model Freshwater ecosystems Zhang, Ke verfasserin aut Lin, Qi verfasserin aut Huang, Shixin verfasserin aut Yang, Xiangdong verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 147 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:147 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 147
allfields_unstemmed	10.1016/j.ecolind.2023.110007 doi (DE-627)ELV009290729 (ELSEVIER)S1470-160X(23)00149-8 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Han, Yaoyao verfasserin (orcid)0000-0003-4150-7855 aut Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems. Socio-ecological system Ecosystem health index Sustainability Bayesian Hierarchy Model Freshwater ecosystems Zhang, Ke verfasserin aut Lin, Qi verfasserin aut Huang, Shixin verfasserin aut Yang, Xiangdong verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 147 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:147 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 147
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allfieldsSound	10.1016/j.ecolind.2023.110007 doi (DE-627)ELV009290729 (ELSEVIER)S1470-160X(23)00149-8 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Han, Yaoyao verfasserin (orcid)0000-0003-4150-7855 aut Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems. Socio-ecological system Ecosystem health index Sustainability Bayesian Hierarchy Model Freshwater ecosystems Zhang, Ke verfasserin aut Lin, Qi verfasserin aut Huang, Shixin verfasserin aut Yang, Xiangdong verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 147 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:147 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 147
language	English
source	Enthalten in Ecological indicators 147 volume:147
sourceStr	Enthalten in Ecological indicators 147 volume:147
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topic_facet	Socio-ecological system Ecosystem health index Sustainability Bayesian Hierarchy Model Freshwater ecosystems
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container_title	Ecological indicators
authorswithroles_txt_mv	Han, Yaoyao @@aut@@ Zhang, Ke @@aut@@ Lin, Qi @@aut@@ Huang, Shixin @@aut@@ Yang, Xiangdong @@aut@@
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author	Han, Yaoyao
spellingShingle	Han, Yaoyao ddc 570 fid BIODIV misc Socio-ecological system misc Ecosystem health index misc Sustainability misc Bayesian Hierarchy Model misc Freshwater ecosystems Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms
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title	Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms
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title_full	Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms
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title_sort	assessing lake ecosystem health from disturbed anthropogenic landscapes: spatial patterns and driving mechanisms
title_auth	Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms
abstract	Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems.
abstractGer	Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems.
abstract_unstemmed	Freshwater lake ecosystems face unprecedented challenges with escalating anthropogenic pressure worldwide. An improved understanding of how environmental and socioeconomic factors impact lake health is crucial for strategic conservation and management. Here, we compiled data from 85 lakes from China’s most densely populated regions and proposed an integrated index to examine spatial patterns of lake ecosystem health. We further evaluated how 16 socioeconomic drivers and environmental conditions drive these changes by using the Bayesian hierarchical model and Gradient boosting decision tree models. Our results suggest the integrated index can provide a comprehensive picture of lake ecosystem quality from a systems perspective combining water bodies and lakeshore zones. We find that lake degradation shows clear spatial heterogeneity patterns given the common forcings associated with climate factors and land-use practices within this region. We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. This study contributes to the understanding of the differences and driving mechanisms of lake ecological degradation in areas of high human activity as a basis for further identifying environmental conflicts and recommendations to improve the state of lake ecosystems.
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title_short	Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms
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up_date	2024-07-06T22:39:37.979Z
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We further reveal the non-linear relationships between the social and economic factors (distance, population, food production, gross domestic product [GDP], etc.) and lake ecology, and find that distance of the lake from the city center was the predominant factor that influenced the lake system health among these multiple drivers. 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Assessing lake ecosystem health from disturbed anthropogenic landscapes: Spatial patterns and driving mechanisms

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