Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region
Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to sim...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Guerra, A. [verfasserIn] Azevedo, A. [verfasserIn] Amorim, F. [verfasserIn] Soares, J. [verfasserIn] Neuparth, T. [verfasserIn] Santos, M.M. [verfasserIn] Martins, I. [verfasserIn] Colaço, A. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Marine pollution bulletin - Amsterdam [u.a.] : Elsevier Science, 1970, 199 |
|---|---|
| Übergeordnetes Werk: |
volume:199 |
| DOI / URN: |
10.1016/j.marpolbul.2023.115974 |
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| Katalog-ID: |
ELV066843073 |
|---|
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| 245 | 1 | 0 | |a Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region |
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| 520 | |a Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. | ||
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| 700 | 1 | |a Azevedo, A. |e verfasserin |4 aut | |
| 700 | 1 | |a Amorim, F. |e verfasserin |4 aut | |
| 700 | 1 | |a Soares, J. |e verfasserin |4 aut | |
| 700 | 1 | |a Neuparth, T. |e verfasserin |4 aut | |
| 700 | 1 | |a Santos, M.M. |e verfasserin |4 aut | |
| 700 | 1 | |a Martins, I. |e verfasserin |4 aut | |
| 700 | 1 | |a Colaço, A. |e verfasserin |4 aut | |
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10.1016/j.marpolbul.2023.115974 doi (DE-627)ELV066843073 (ELSEVIER)S0025-326X(23)01409-1 DE-627 ger DE-627 rda eng 550 333.7 VZ BIODIV DE-30 fid 38.90 bkl 43.50 bkl Guerra, A. verfasserin aut Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. SPCC Deep-sea Maritime traffic Contaminants Chemosynthesis Azevedo, A. verfasserin aut Amorim, F. verfasserin aut Soares, J. verfasserin aut Neuparth, T. verfasserin aut Santos, M.M. verfasserin aut Martins, I. verfasserin aut Colaço, A. verfasserin aut Enthalten in Marine pollution bulletin Amsterdam [u.a.] : Elsevier Science, 1970 199 Online-Ressource (DE-627)320410897 (DE-600)2001296-2 (DE-576)259484415 1879-3363 nnns volume:199 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 43.50 Umweltbelastungen VZ AR 199 |
| spelling |
10.1016/j.marpolbul.2023.115974 doi (DE-627)ELV066843073 (ELSEVIER)S0025-326X(23)01409-1 DE-627 ger DE-627 rda eng 550 333.7 VZ BIODIV DE-30 fid 38.90 bkl 43.50 bkl Guerra, A. verfasserin aut Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. SPCC Deep-sea Maritime traffic Contaminants Chemosynthesis Azevedo, A. verfasserin aut Amorim, F. verfasserin aut Soares, J. verfasserin aut Neuparth, T. verfasserin aut Santos, M.M. verfasserin aut Martins, I. verfasserin aut Colaço, A. verfasserin aut Enthalten in Marine pollution bulletin Amsterdam [u.a.] : Elsevier Science, 1970 199 Online-Ressource (DE-627)320410897 (DE-600)2001296-2 (DE-576)259484415 1879-3363 nnns volume:199 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 43.50 Umweltbelastungen VZ AR 199 |
| allfields_unstemmed |
10.1016/j.marpolbul.2023.115974 doi (DE-627)ELV066843073 (ELSEVIER)S0025-326X(23)01409-1 DE-627 ger DE-627 rda eng 550 333.7 VZ BIODIV DE-30 fid 38.90 bkl 43.50 bkl Guerra, A. verfasserin aut Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. SPCC Deep-sea Maritime traffic Contaminants Chemosynthesis Azevedo, A. verfasserin aut Amorim, F. verfasserin aut Soares, J. verfasserin aut Neuparth, T. verfasserin aut Santos, M.M. verfasserin aut Martins, I. verfasserin aut Colaço, A. verfasserin aut Enthalten in Marine pollution bulletin Amsterdam [u.a.] : Elsevier Science, 1970 199 Online-Ressource (DE-627)320410897 (DE-600)2001296-2 (DE-576)259484415 1879-3363 nnns volume:199 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 43.50 Umweltbelastungen VZ AR 199 |
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10.1016/j.marpolbul.2023.115974 doi (DE-627)ELV066843073 (ELSEVIER)S0025-326X(23)01409-1 DE-627 ger DE-627 rda eng 550 333.7 VZ BIODIV DE-30 fid 38.90 bkl 43.50 bkl Guerra, A. verfasserin aut Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. SPCC Deep-sea Maritime traffic Contaminants Chemosynthesis Azevedo, A. verfasserin aut Amorim, F. verfasserin aut Soares, J. verfasserin aut Neuparth, T. verfasserin aut Santos, M.M. verfasserin aut Martins, I. verfasserin aut Colaço, A. verfasserin aut Enthalten in Marine pollution bulletin Amsterdam [u.a.] : Elsevier Science, 1970 199 Online-Ressource (DE-627)320410897 (DE-600)2001296-2 (DE-576)259484415 1879-3363 nnns volume:199 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 43.50 Umweltbelastungen VZ AR 199 |
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10.1016/j.marpolbul.2023.115974 doi (DE-627)ELV066843073 (ELSEVIER)S0025-326X(23)01409-1 DE-627 ger DE-627 rda eng 550 333.7 VZ BIODIV DE-30 fid 38.90 bkl 43.50 bkl Guerra, A. verfasserin aut Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. SPCC Deep-sea Maritime traffic Contaminants Chemosynthesis Azevedo, A. verfasserin aut Amorim, F. verfasserin aut Soares, J. verfasserin aut Neuparth, T. verfasserin aut Santos, M.M. verfasserin aut Martins, I. verfasserin aut Colaço, A. verfasserin aut Enthalten in Marine pollution bulletin Amsterdam [u.a.] : Elsevier Science, 1970 199 Online-Ressource (DE-627)320410897 (DE-600)2001296-2 (DE-576)259484415 1879-3363 nnns volume:199 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.90 Ozeanologie Ozeanographie VZ 43.50 Umweltbelastungen VZ AR 199 |
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Guerra, A. @@aut@@ Azevedo, A. @@aut@@ Amorim, F. @@aut@@ Soares, J. @@aut@@ Neuparth, T. @@aut@@ Santos, M.M. @@aut@@ Martins, I. @@aut@@ Colaço, A. @@aut@@ |
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550 333.7 VZ BIODIV DE-30 fid 38.90 bkl 43.50 bkl Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region SPCC Deep-sea Maritime traffic Contaminants Chemosynthesis |
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using a food web model to predict the effects of hazardous and noxious substances (hns) accidental spills on deep-sea hydrothermal vents from the mid-atlantic ridge (mar) region |
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Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region |
| abstract |
Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. |
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Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. |
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Deep-sea hydrothermal vents host unique ecosystems but face risks of incidents with Hazardous and Noxious Substances (HNS) along busy shipping lanes such as the transatlantic route. We developed an Ecopath with Ecosim (EwE) model of the Menez Gwen (MG) vent field (MG-EwE) (Mid-Atlantic Ridge) to simulate ecosystem effects of potential accidental spills of four different HNS, using a semi-Lagrangian Dispersion Model (sLDM) coupled with the Regional Ocean Modelling System (ROMS) calibrated for the study area. Food web modelling revealed a simplified trophic structure with low energy efficiency. The MG ecosystem was vulnerable to disruptions caused by all tested HNS, yet it revealed some long-term resilience. Understanding these impacts is vital for enhancing Spill Prevention, Control, and Countermeasure plans (SPCC) in remote marine areas and developing tools to assess stressors effects on these invaluable habitats. |
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Using a food web model to predict the effects of Hazardous and Noxious Substances (HNS) accidental spills on deep-sea hydrothermal vents from the Mid-Atlantic Ridge (MAR) region |
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| score |
7.3999033 |