Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations
A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle fo...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Felton, Adam [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Schlagwörter: |
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| Umfang: |
11 |
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| Übergeordnetes Werk: |
Enthalten in: Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality - Ren, Chunhui ELSEVIER, 2022, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:197 ; year:2017 ; day:15 ; month:07 ; pages:404-414 ; extent:11 |
| Links: |
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| DOI / URN: |
10.1016/j.jenvman.2017.04.001 |
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ELV020209932 |
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| 520 | |a A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. | ||
| 520 | |a A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. | ||
| 650 | 7 | |a Natural resource management |2 Elsevier | |
| 650 | 7 | |a Discounting |2 Elsevier | |
| 650 | 7 | |a Sensitivity analysis |2 Elsevier | |
| 650 | 7 | |a Forest dynamics |2 Elsevier | |
| 650 | 7 | |a Population models |2 Elsevier | |
| 650 | 7 | |a Virtual species |2 Elsevier | |
| 700 | 1 | |a Ranius, Thomas |4 oth | |
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| 700 | 1 | |a Hynynen, Jari |4 oth | |
| 700 | 1 | |a Juutinen, Artti |4 oth | |
| 700 | 1 | |a Mönkkönen, Mikko |4 oth | |
| 700 | 1 | |a Nilsson, Urban |4 oth | |
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| 700 | 1 | |a Nordin, Annika |4 oth | |
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10.1016/j.jenvman.2017.04.001 doi GBV00000000000076A.pica (DE-627)ELV020209932 (ELSEVIER)S0301-4797(17)30326-2 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Felton, Adam verfasserin aut Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. Natural resource management Elsevier Discounting Elsevier Sensitivity analysis Elsevier Forest dynamics Elsevier Population models Elsevier Virtual species Elsevier Ranius, Thomas oth Roberge, Jean-Michel oth Öhman, Karin oth Lämås, Tomas oth Hynynen, Jari oth Juutinen, Artti oth Mönkkönen, Mikko oth Nilsson, Urban oth Lundmark, Tomas oth Nordin, Annika oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:197 year:2017 day:15 month:07 pages:404-414 extent:11 https://doi.org/10.1016/j.jenvman.2017.04.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 197 2017 15 0715 404-414 11 045F 333.7 |
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10.1016/j.jenvman.2017.04.001 doi GBV00000000000076A.pica (DE-627)ELV020209932 (ELSEVIER)S0301-4797(17)30326-2 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Felton, Adam verfasserin aut Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. Natural resource management Elsevier Discounting Elsevier Sensitivity analysis Elsevier Forest dynamics Elsevier Population models Elsevier Virtual species Elsevier Ranius, Thomas oth Roberge, Jean-Michel oth Öhman, Karin oth Lämås, Tomas oth Hynynen, Jari oth Juutinen, Artti oth Mönkkönen, Mikko oth Nilsson, Urban oth Lundmark, Tomas oth Nordin, Annika oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:197 year:2017 day:15 month:07 pages:404-414 extent:11 https://doi.org/10.1016/j.jenvman.2017.04.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 197 2017 15 0715 404-414 11 045F 333.7 |
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10.1016/j.jenvman.2017.04.001 doi GBV00000000000076A.pica (DE-627)ELV020209932 (ELSEVIER)S0301-4797(17)30326-2 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Felton, Adam verfasserin aut Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. Natural resource management Elsevier Discounting Elsevier Sensitivity analysis Elsevier Forest dynamics Elsevier Population models Elsevier Virtual species Elsevier Ranius, Thomas oth Roberge, Jean-Michel oth Öhman, Karin oth Lämås, Tomas oth Hynynen, Jari oth Juutinen, Artti oth Mönkkönen, Mikko oth Nilsson, Urban oth Lundmark, Tomas oth Nordin, Annika oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:197 year:2017 day:15 month:07 pages:404-414 extent:11 https://doi.org/10.1016/j.jenvman.2017.04.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 197 2017 15 0715 404-414 11 045F 333.7 |
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10.1016/j.jenvman.2017.04.001 doi GBV00000000000076A.pica (DE-627)ELV020209932 (ELSEVIER)S0301-4797(17)30326-2 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Felton, Adam verfasserin aut Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. Natural resource management Elsevier Discounting Elsevier Sensitivity analysis Elsevier Forest dynamics Elsevier Population models Elsevier Virtual species Elsevier Ranius, Thomas oth Roberge, Jean-Michel oth Öhman, Karin oth Lämås, Tomas oth Hynynen, Jari oth Juutinen, Artti oth Mönkkönen, Mikko oth Nilsson, Urban oth Lundmark, Tomas oth Nordin, Annika oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:197 year:2017 day:15 month:07 pages:404-414 extent:11 https://doi.org/10.1016/j.jenvman.2017.04.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 197 2017 15 0715 404-414 11 045F 333.7 |
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10.1016/j.jenvman.2017.04.001 doi GBV00000000000076A.pica (DE-627)ELV020209932 (ELSEVIER)S0301-4797(17)30326-2 DE-627 ger DE-627 rakwb eng 333.7 690 333.7 DNB 690 DNB 300 VZ 70.00 bkl 71.00 bkl Felton, Adam verfasserin aut Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations 2017transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. Natural resource management Elsevier Discounting Elsevier Sensitivity analysis Elsevier Forest dynamics Elsevier Population models Elsevier Virtual species Elsevier Ranius, Thomas oth Roberge, Jean-Michel oth Öhman, Karin oth Lämås, Tomas oth Hynynen, Jari oth Juutinen, Artti oth Mönkkönen, Mikko oth Nilsson, Urban oth Lundmark, Tomas oth Nordin, Annika oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:197 year:2017 day:15 month:07 pages:404-414 extent:11 https://doi.org/10.1016/j.jenvman.2017.04.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 197 2017 15 0715 404-414 11 045F 333.7 |
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projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations |
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Projecting biodiversity and wood production in future forest landscapes: 15 key modeling considerations |
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A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. |
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A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. |
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A variety of modeling approaches can be used to project the future development of forest systems, and help to assess the implications of different management alternatives for biodiversity and ecosystem services. This diversity of approaches does however present both an opportunity and an obstacle for those trying to decide which modeling technique to apply, and interpreting the management implications of model output. Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources. |
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Furthermore, the breadth of issues relevant to addressing key questions related to forest ecology, conservation biology, silviculture, economics, requires insights stemming from a number of distinct scientific disciplines. As forest planners, conservation ecologists, ecological economists and silviculturalists, experienced with modeling trade-offs and synergies between biodiversity and wood biomass production, we identified fifteen key considerations relevant to assessing the pros and cons of alternative modeling approaches. Specifically we identified key considerations linked to study question formulation, modeling forest dynamics, forest processes, study landscapes, spatial and temporal aspects, and the key response metrics – biodiversity and wood biomass production, as well as dealing with trade-offs and uncertainties. We also provide illustrative examples from the modeling literature stemming from the key considerations assessed. We use our findings to reiterate the need for explicitly addressing and conveying the limitations and uncertainties of any modeling approach taken, and the need for interdisciplinary research efforts when addressing the conservation of biodiversity and sustainable use of environmental resources.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Natural resource management</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Discounting</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Sensitivity analysis</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Forest dynamics</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Population models</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Virtual species</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ranius, Thomas</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Roberge, Jean-Michel</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Öhman, Karin</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lämås, Tomas</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hynynen, Jari</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Juutinen, Artti</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mönkkönen, Mikko</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Nilsson, Urban</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lundmark, Tomas</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Nordin, Annika</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Ren, Chunhui ELSEVIER</subfield><subfield code="t">Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality</subfield><subfield code="d">2022</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV008002754</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:197</subfield><subfield code="g">year:2017</subfield><subfield code="g">day:15</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:404-414</subfield><subfield code="g">extent:11</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.jenvman.2017.04.001</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="936" ind1="b" ind2="k"><subfield code="a">70.00</subfield><subfield code="j">Sozialwissenschaften allgemein: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">71.00</subfield><subfield code="j">Soziologie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">197</subfield><subfield code="j">2017</subfield><subfield code="b">15</subfield><subfield code="c">0715</subfield><subfield code="h">404-414</subfield><subfield code="g">11</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">333.7</subfield></datafield></record></collection>
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