Stochastic Integrated Assessment of Ecosystem Tipping Risk
Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different...
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Gespeichert in:
| Autor*in: |
Lontzek, Thomas S. [verfasserIn] Narita, Daiju [verfasserIn] Wilms, Ole [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Environmental and resource economics - [S.l.] : Proquest, 1991, 65(2016), 3 vom: 04. Aug., Seite 573-598 |
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| Übergeordnetes Werk: |
volume:65 ; year:2016 ; number:3 ; day:04 ; month:08 ; pages:573-598 |
| Links: |
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| DOI / URN: |
10.1007/s10640-016-0054-y |
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SPR01205481X |
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| 520 | |a Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. | ||
| 650 | 4 | |a Climate change uncertainty |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Ecosystem services |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Forest dieback |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Tipping point |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Regime shift |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Epstein–Zin preferences |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Economic growth |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Narita, Daiju |e verfasserin |4 aut | |
| 700 | 1 | |a Wilms, Ole |e verfasserin |4 aut | |
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10.1007/s10640-016-0054-y doi (DE-627)SPR01205481X (SPR)s10640-016-0054-y-e DE-627 ger DE-627 rakwb eng 333.7 300 330 ASE 43.30 bkl 83.63 bkl Lontzek, Thomas S. verfasserin aut Stochastic Integrated Assessment of Ecosystem Tipping Risk 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. Climate change uncertainty (dpeaa)DE-He213 Ecosystem services (dpeaa)DE-He213 Forest dieback (dpeaa)DE-He213 Tipping point (dpeaa)DE-He213 Regime shift (dpeaa)DE-He213 Epstein–Zin preferences (dpeaa)DE-He213 Economic growth (dpeaa)DE-He213 Narita, Daiju verfasserin aut Wilms, Ole verfasserin aut Enthalten in Environmental and resource economics [S.l.] : Proquest, 1991 65(2016), 3 vom: 04. Aug., Seite 573-598 (DE-627)271349085 (DE-600)1479788-4 1573-1502 nnns volume:65 year:2016 number:3 day:04 month:08 pages:573-598 https://dx.doi.org/10.1007/s10640-016-0054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.30 ASE 83.63 ASE AR 65 2016 3 04 08 573-598 |
| spelling |
10.1007/s10640-016-0054-y doi (DE-627)SPR01205481X (SPR)s10640-016-0054-y-e DE-627 ger DE-627 rakwb eng 333.7 300 330 ASE 43.30 bkl 83.63 bkl Lontzek, Thomas S. verfasserin aut Stochastic Integrated Assessment of Ecosystem Tipping Risk 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. Climate change uncertainty (dpeaa)DE-He213 Ecosystem services (dpeaa)DE-He213 Forest dieback (dpeaa)DE-He213 Tipping point (dpeaa)DE-He213 Regime shift (dpeaa)DE-He213 Epstein–Zin preferences (dpeaa)DE-He213 Economic growth (dpeaa)DE-He213 Narita, Daiju verfasserin aut Wilms, Ole verfasserin aut Enthalten in Environmental and resource economics [S.l.] : Proquest, 1991 65(2016), 3 vom: 04. Aug., Seite 573-598 (DE-627)271349085 (DE-600)1479788-4 1573-1502 nnns volume:65 year:2016 number:3 day:04 month:08 pages:573-598 https://dx.doi.org/10.1007/s10640-016-0054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.30 ASE 83.63 ASE AR 65 2016 3 04 08 573-598 |
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10.1007/s10640-016-0054-y doi (DE-627)SPR01205481X (SPR)s10640-016-0054-y-e DE-627 ger DE-627 rakwb eng 333.7 300 330 ASE 43.30 bkl 83.63 bkl Lontzek, Thomas S. verfasserin aut Stochastic Integrated Assessment of Ecosystem Tipping Risk 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. Climate change uncertainty (dpeaa)DE-He213 Ecosystem services (dpeaa)DE-He213 Forest dieback (dpeaa)DE-He213 Tipping point (dpeaa)DE-He213 Regime shift (dpeaa)DE-He213 Epstein–Zin preferences (dpeaa)DE-He213 Economic growth (dpeaa)DE-He213 Narita, Daiju verfasserin aut Wilms, Ole verfasserin aut Enthalten in Environmental and resource economics [S.l.] : Proquest, 1991 65(2016), 3 vom: 04. Aug., Seite 573-598 (DE-627)271349085 (DE-600)1479788-4 1573-1502 nnns volume:65 year:2016 number:3 day:04 month:08 pages:573-598 https://dx.doi.org/10.1007/s10640-016-0054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.30 ASE 83.63 ASE AR 65 2016 3 04 08 573-598 |
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10.1007/s10640-016-0054-y doi (DE-627)SPR01205481X (SPR)s10640-016-0054-y-e DE-627 ger DE-627 rakwb eng 333.7 300 330 ASE 43.30 bkl 83.63 bkl Lontzek, Thomas S. verfasserin aut Stochastic Integrated Assessment of Ecosystem Tipping Risk 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. Climate change uncertainty (dpeaa)DE-He213 Ecosystem services (dpeaa)DE-He213 Forest dieback (dpeaa)DE-He213 Tipping point (dpeaa)DE-He213 Regime shift (dpeaa)DE-He213 Epstein–Zin preferences (dpeaa)DE-He213 Economic growth (dpeaa)DE-He213 Narita, Daiju verfasserin aut Wilms, Ole verfasserin aut Enthalten in Environmental and resource economics [S.l.] : Proquest, 1991 65(2016), 3 vom: 04. Aug., Seite 573-598 (DE-627)271349085 (DE-600)1479788-4 1573-1502 nnns volume:65 year:2016 number:3 day:04 month:08 pages:573-598 https://dx.doi.org/10.1007/s10640-016-0054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.30 ASE 83.63 ASE AR 65 2016 3 04 08 573-598 |
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10.1007/s10640-016-0054-y doi (DE-627)SPR01205481X (SPR)s10640-016-0054-y-e DE-627 ger DE-627 rakwb eng 333.7 300 330 ASE 43.30 bkl 83.63 bkl Lontzek, Thomas S. verfasserin aut Stochastic Integrated Assessment of Ecosystem Tipping Risk 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. Climate change uncertainty (dpeaa)DE-He213 Ecosystem services (dpeaa)DE-He213 Forest dieback (dpeaa)DE-He213 Tipping point (dpeaa)DE-He213 Regime shift (dpeaa)DE-He213 Epstein–Zin preferences (dpeaa)DE-He213 Economic growth (dpeaa)DE-He213 Narita, Daiju verfasserin aut Wilms, Ole verfasserin aut Enthalten in Environmental and resource economics [S.l.] : Proquest, 1991 65(2016), 3 vom: 04. Aug., Seite 573-598 (DE-627)271349085 (DE-600)1479788-4 1573-1502 nnns volume:65 year:2016 number:3 day:04 month:08 pages:573-598 https://dx.doi.org/10.1007/s10640-016-0054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_26 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.30 ASE 83.63 ASE AR 65 2016 3 04 08 573-598 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR01205481X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220110231717.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201005s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10640-016-0054-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR01205481X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s10640-016-0054-y-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">333.7</subfield><subfield code="a">300</subfield><subfield code="a">330</subfield><subfield code="q">ASE</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">43.30</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">83.63</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Lontzek, Thomas S.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Stochastic Integrated Assessment of Ecosystem Tipping Risk</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. 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Lontzek, Thomas S. |
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Lontzek, Thomas S. ddc 333.7 bkl 43.30 bkl 83.63 misc Climate change uncertainty misc Ecosystem services misc Forest dieback misc Tipping point misc Regime shift misc Epstein–Zin preferences misc Economic growth Stochastic Integrated Assessment of Ecosystem Tipping Risk |
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333.7 300 330 ASE 43.30 bkl 83.63 bkl Stochastic Integrated Assessment of Ecosystem Tipping Risk Climate change uncertainty (dpeaa)DE-He213 Ecosystem services (dpeaa)DE-He213 Forest dieback (dpeaa)DE-He213 Tipping point (dpeaa)DE-He213 Regime shift (dpeaa)DE-He213 Epstein–Zin preferences (dpeaa)DE-He213 Economic growth (dpeaa)DE-He213 |
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stochastic integrated assessment of ecosystem tipping risk |
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Stochastic Integrated Assessment of Ecosystem Tipping Risk |
| abstract |
Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. |
| abstractGer |
Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. |
| abstract_unstemmed |
Abstract One of the major potential consequences of climate change is damage to earth’s ecosystems, damage which could manifest itself in the form of tipping risks. We establish an economic growth model of ecosystem tipping risks, set in the context of possible forest dieback. We consider different specifications of impacts arising from the forest dieback tipping point, specifications such as changes in the system dynamics of the forests, changes in the forest mass, and impacts on economic output. We also consider endogenous and exogenous tipping point probabilities. For each specification we compute the optimal policies for forest management and emission control. Our results show qualitative differences in patterns of post-tipping event, optimal forest harvest, and either precautionary or aggressive pre-tipping event harvest patterns, a feature consistent with the findings of the existing literature. Optimal control of deforestation and carbon dioxide emission reduction also exhibits varied patterns of post- and pre-tipping levels depending on the nature of the tipping risk. Still, today’s optimal policy is one of more stringent emissions control in presence of a potential forest dieback tipping point. |
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Stochastic Integrated Assessment of Ecosystem Tipping Risk |
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| score |
7.401515 |