Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa
Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource m...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Vezi, Madonna [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Novel and emerging treatments for major depression - Marwaha, Steven ELSEVIER, 2023, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:185 ; year:2020 ; day:1 ; month:03 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.ocecoaman.2019.105035 |
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ELV04907251X |
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| 245 | 1 | 0 | |a Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa |
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| 520 | |a Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... | ||
| 520 | |a Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... | ||
| 650 | 7 | |a Estuaries |2 Elsevier | |
| 650 | 7 | |a Land use activities |2 Elsevier | |
| 650 | 7 | |a Stressors |2 Elsevier | |
| 650 | 7 | |a Regional ecological risk assessment |2 Elsevier | |
| 700 | 1 | |a Downs, Colleen |4 oth | |
| 700 | 1 | |a Wepener, Victor |4 oth | |
| 700 | 1 | |a O'Brien, Gordon |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier Science |a Marwaha, Steven ELSEVIER |t Novel and emerging treatments for major depression |d 2023 |g Amsterdam [u.a.] |w (DE-627)ELV010017429 |
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10.1016/j.ocecoaman.2019.105035 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001392.pica (DE-627)ELV04907251X (ELSEVIER)S0964-5691(19)30905-6 DE-627 ger DE-627 rakwb eng Vezi, Madonna verfasserin aut Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Estuaries Elsevier Land use activities Elsevier Stressors Elsevier Regional ecological risk assessment Elsevier Downs, Colleen oth Wepener, Victor oth O'Brien, Gordon oth Enthalten in Elsevier Science Marwaha, Steven ELSEVIER Novel and emerging treatments for major depression 2023 Amsterdam [u.a.] (DE-627)ELV010017429 volume:185 year:2020 day:1 month:03 pages:0 https://doi.org/10.1016/j.ocecoaman.2019.105035 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_30 GBV_ILN_40 GBV_ILN_70 AR 185 2020 1 0301 0 |
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10.1016/j.ocecoaman.2019.105035 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001392.pica (DE-627)ELV04907251X (ELSEVIER)S0964-5691(19)30905-6 DE-627 ger DE-627 rakwb eng Vezi, Madonna verfasserin aut Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Estuaries Elsevier Land use activities Elsevier Stressors Elsevier Regional ecological risk assessment Elsevier Downs, Colleen oth Wepener, Victor oth O'Brien, Gordon oth Enthalten in Elsevier Science Marwaha, Steven ELSEVIER Novel and emerging treatments for major depression 2023 Amsterdam [u.a.] (DE-627)ELV010017429 volume:185 year:2020 day:1 month:03 pages:0 https://doi.org/10.1016/j.ocecoaman.2019.105035 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_30 GBV_ILN_40 GBV_ILN_70 AR 185 2020 1 0301 0 |
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10.1016/j.ocecoaman.2019.105035 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001392.pica (DE-627)ELV04907251X (ELSEVIER)S0964-5691(19)30905-6 DE-627 ger DE-627 rakwb eng Vezi, Madonna verfasserin aut Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Estuaries Elsevier Land use activities Elsevier Stressors Elsevier Regional ecological risk assessment Elsevier Downs, Colleen oth Wepener, Victor oth O'Brien, Gordon oth Enthalten in Elsevier Science Marwaha, Steven ELSEVIER Novel and emerging treatments for major depression 2023 Amsterdam [u.a.] (DE-627)ELV010017429 volume:185 year:2020 day:1 month:03 pages:0 https://doi.org/10.1016/j.ocecoaman.2019.105035 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_30 GBV_ILN_40 GBV_ILN_70 AR 185 2020 1 0301 0 |
| allfieldsGer |
10.1016/j.ocecoaman.2019.105035 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001392.pica (DE-627)ELV04907251X (ELSEVIER)S0964-5691(19)30905-6 DE-627 ger DE-627 rakwb eng Vezi, Madonna verfasserin aut Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Estuaries Elsevier Land use activities Elsevier Stressors Elsevier Regional ecological risk assessment Elsevier Downs, Colleen oth Wepener, Victor oth O'Brien, Gordon oth Enthalten in Elsevier Science Marwaha, Steven ELSEVIER Novel and emerging treatments for major depression 2023 Amsterdam [u.a.] (DE-627)ELV010017429 volume:185 year:2020 day:1 month:03 pages:0 https://doi.org/10.1016/j.ocecoaman.2019.105035 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_30 GBV_ILN_40 GBV_ILN_70 AR 185 2020 1 0301 0 |
| allfieldsSound |
10.1016/j.ocecoaman.2019.105035 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001392.pica (DE-627)ELV04907251X (ELSEVIER)S0964-5691(19)30905-6 DE-627 ger DE-627 rakwb eng Vezi, Madonna verfasserin aut Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... 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Application of the relative risk model for evaluation of ecological risk in selected river dominated estuaries in KwaZulu-Natal, South Africa |
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Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... |
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Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... |
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Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m... |
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Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m...</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Effective environmental management and restoration of impacted estuaries in South Africa necessitates a holistic understanding of the contribution of various stressor-related impacts throughout the catchment. Ecological risk assessment for aquatic ecosystems is an important tool for water resource management. In this study, we describe results of a preliminary assessment that was conducted to evaluate the relative risks of multiple anthropogenic stressors currently acting within the catchments of uMvoti, Thukela and aMatikulu/Nyoni estuaries using Bayesian Network Relative Risk Model (BN-RRM) framework. Four socio-ecological endpoints selected for the present study included biodiversity habitat, safe environment, fisheries and productivity. We constructed a conceptual model which depicted potential and effect pathways from the source, to the stressor, to the habitat and to the endpoint. We also developed five scenarios (including historical and future scenarios) to predict the potential risk distributions in different proposed scenarios. Results revealed that productivity was the endpoint at the lower risk in all the estuaries and all scenarios except for scenario 5. Results also showed that scenario 3 which is a scenario before major resource development had the lowest risk scores for all the endpoints. Scenario 4 (year 2025 if no laws and management measures are implemented) had the highest risk scores for all the endpoints. Overall endpoints generally displayed low to medium risk throughout all scenarios (except scenario 3) and different flows. All endpoints generally displayed zero risk in scenario 3. All endpoints were at a highest risk in the uMvoti Estuary followed by aMatikulu/Nyoni and then Thukela Estuary. Results highlighted that in the uMvoti and Thukela estuaries, people were at a higher risk when compared with the ecological components of these systems as social endpoints displayed higher risk scores than the ecological endpoints, however the opposite was observed in the aMatikulu/Nyoni Estuary. This study provided the foundation for evaluating the risks of multiple stressors in the catchments of these estuaries to a variety of endpoints. Management options and research should focus on collecting necessary data and information to refine the developed RRM. By establishing such framework, we believe that stakeholders within the catchments of these systems together with government organisations will be able to make more informed and risk-based m...</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Estuaries</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Land use activities</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Stressors</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Regional ecological risk assessment</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Downs, Colleen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wepener, Victor</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">O'Brien, Gordon</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="a">Marwaha, Steven ELSEVIER</subfield><subfield code="t">Novel and emerging treatments for major depression</subfield><subfield code="d">2023</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV010017429</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:185</subfield><subfield code="g">year:2020</subfield><subfield code="g">day:1</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:0</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.ocecoaman.2019.105035</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_30</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">185</subfield><subfield code="j">2020</subfield><subfield code="b">1</subfield><subfield code="c">0301</subfield><subfield code="h">0</subfield></datafield></record></collection>
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