Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use

Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered i...
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Autor*in:	Antonino Marvuglia [verfasserIn] Tomás Navarrete Gutiérrez [verfasserIn] Paul Baustert [verfasserIn] Enrico Benetto [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling

Übergeordnetes Werk:	In: AIMS Agriculture and Food - AIMS Press, 2016, 3(2018), 4, Seite 535-560
Übergeordnetes Werk:	volume:3 ; year:2018 ; number:4 ; pages:535-560

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3934/agrfood.2018.4.535

Katalog-ID:	DOAJ035544155

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allfields	10.3934/agrfood.2018.4.535 doi (DE-627)DOAJ035544155 (DE-599)DOAJ0c66981f9fc14009a04b3a0039666127 DE-627 ger DE-627 rakwb eng S1-972 TP368-456 Antonino Marvuglia verfasserin aut Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling Agriculture (General) Food processing and manufacture Tomás Navarrete Gutiérrez verfasserin aut Paul Baustert verfasserin aut Enrico Benetto verfasserin aut In AIMS Agriculture and Food AIMS Press, 2016 3(2018), 4, Seite 535-560 (DE-627)862916631 (DE-600)2861488-4 24712086 nnns volume:3 year:2018 number:4 pages:535-560 https://doi.org/10.3934/agrfood.2018.4.535 kostenfrei https://doaj.org/article/0c66981f9fc14009a04b3a0039666127 kostenfrei http://www.aimspress.com/article/10.3934/agrfood.2018.4.535/fulltext.html kostenfrei https://doaj.org/toc/2471-2086 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 3 2018 4 535-560
spelling	10.3934/agrfood.2018.4.535 doi (DE-627)DOAJ035544155 (DE-599)DOAJ0c66981f9fc14009a04b3a0039666127 DE-627 ger DE-627 rakwb eng S1-972 TP368-456 Antonino Marvuglia verfasserin aut Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling Agriculture (General) Food processing and manufacture Tomás Navarrete Gutiérrez verfasserin aut Paul Baustert verfasserin aut Enrico Benetto verfasserin aut In AIMS Agriculture and Food AIMS Press, 2016 3(2018), 4, Seite 535-560 (DE-627)862916631 (DE-600)2861488-4 24712086 nnns volume:3 year:2018 number:4 pages:535-560 https://doi.org/10.3934/agrfood.2018.4.535 kostenfrei https://doaj.org/article/0c66981f9fc14009a04b3a0039666127 kostenfrei http://www.aimspress.com/article/10.3934/agrfood.2018.4.535/fulltext.html kostenfrei https://doaj.org/toc/2471-2086 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 3 2018 4 535-560
allfields_unstemmed	10.3934/agrfood.2018.4.535 doi (DE-627)DOAJ035544155 (DE-599)DOAJ0c66981f9fc14009a04b3a0039666127 DE-627 ger DE-627 rakwb eng S1-972 TP368-456 Antonino Marvuglia verfasserin aut Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling Agriculture (General) Food processing and manufacture Tomás Navarrete Gutiérrez verfasserin aut Paul Baustert verfasserin aut Enrico Benetto verfasserin aut In AIMS Agriculture and Food AIMS Press, 2016 3(2018), 4, Seite 535-560 (DE-627)862916631 (DE-600)2861488-4 24712086 nnns volume:3 year:2018 number:4 pages:535-560 https://doi.org/10.3934/agrfood.2018.4.535 kostenfrei https://doaj.org/article/0c66981f9fc14009a04b3a0039666127 kostenfrei http://www.aimspress.com/article/10.3934/agrfood.2018.4.535/fulltext.html kostenfrei https://doaj.org/toc/2471-2086 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 3 2018 4 535-560
allfieldsGer	10.3934/agrfood.2018.4.535 doi (DE-627)DOAJ035544155 (DE-599)DOAJ0c66981f9fc14009a04b3a0039666127 DE-627 ger DE-627 rakwb eng S1-972 TP368-456 Antonino Marvuglia verfasserin aut Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling Agriculture (General) Food processing and manufacture Tomás Navarrete Gutiérrez verfasserin aut Paul Baustert verfasserin aut Enrico Benetto verfasserin aut In AIMS Agriculture and Food AIMS Press, 2016 3(2018), 4, Seite 535-560 (DE-627)862916631 (DE-600)2861488-4 24712086 nnns volume:3 year:2018 number:4 pages:535-560 https://doi.org/10.3934/agrfood.2018.4.535 kostenfrei https://doaj.org/article/0c66981f9fc14009a04b3a0039666127 kostenfrei http://www.aimspress.com/article/10.3934/agrfood.2018.4.535/fulltext.html kostenfrei https://doaj.org/toc/2471-2086 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 3 2018 4 535-560
allfieldsSound	10.3934/agrfood.2018.4.535 doi (DE-627)DOAJ035544155 (DE-599)DOAJ0c66981f9fc14009a04b3a0039666127 DE-627 ger DE-627 rakwb eng S1-972 TP368-456 Antonino Marvuglia verfasserin aut Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling Agriculture (General) Food processing and manufacture Tomás Navarrete Gutiérrez verfasserin aut Paul Baustert verfasserin aut Enrico Benetto verfasserin aut In AIMS Agriculture and Food AIMS Press, 2016 3(2018), 4, Seite 535-560 (DE-627)862916631 (DE-600)2861488-4 24712086 nnns volume:3 year:2018 number:4 pages:535-560 https://doi.org/10.3934/agrfood.2018.4.535 kostenfrei https://doaj.org/article/0c66981f9fc14009a04b3a0039666127 kostenfrei http://www.aimspress.com/article/10.3934/agrfood.2018.4.535/fulltext.html kostenfrei https://doaj.org/toc/2471-2086 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4367 GBV_ILN_4700 AR 3 2018 4 535-560
language	English
source	In AIMS Agriculture and Food 3(2018), 4, Seite 535-560 volume:3 year:2018 number:4 pages:535-560
sourceStr	In AIMS Agriculture and Food 3(2018), 4, Seite 535-560 volume:3 year:2018 number:4 pages:535-560
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling Agriculture (General) Food processing and manufacture
isfreeaccess_bool	true
container_title	AIMS Agriculture and Food
authorswithroles_txt_mv	Antonino Marvuglia @@aut@@ Tomás Navarrete Gutiérrez @@aut@@ Paul Baustert @@aut@@ Enrico Benetto @@aut@@
publishDateDaySort_date	2018-01-01T00:00:00Z
hierarchy_top_id	862916631
id	DOAJ035544155
language_de	englisch
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callnumber-first	S - Agriculture
author	Antonino Marvuglia
spellingShingle	Antonino Marvuglia misc S1-972 misc TP368-456 misc from biological systems to complex coupled human-natural systems. In particular misc when used to simulate man-managed systems misc they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM misc dealing with general issues that must be considered regardless of the domain of application (such as validity misc uncertainty misc parameter sensitivity misc agent definition misc data provision) misc and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks misc and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion misc we can observe that solutions based on complex systems simulations are starting misc to some extent misc to be influential in policymaking; however misc practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. misc Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling misc Agriculture (General) misc Food processing and manufacture Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use
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topic_title	S1-972 TP368-456 Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use from biological systems to complex coupled human-natural systems. In particular when used to simulate man-managed systems they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM dealing with general issues that must be considered regardless of the domain of application (such as validity uncertainty parameter sensitivity agent definition data provision) and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion we can observe that solutions based on complex systems simulations are starting to some extent to be influential in policymaking; however practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling
topic	misc S1-972 misc TP368-456 misc from biological systems to complex coupled human-natural systems. In particular misc when used to simulate man-managed systems misc they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM misc dealing with general issues that must be considered regardless of the domain of application (such as validity misc uncertainty misc parameter sensitivity misc agent definition misc data provision) misc and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks misc and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion misc we can observe that solutions based on complex systems simulations are starting misc to some extent misc to be influential in policymaking; however misc practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. misc Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling misc Agriculture (General) misc Food processing and manufacture
topic_unstemmed	misc S1-972 misc TP368-456 misc from biological systems to complex coupled human-natural systems. In particular misc when used to simulate man-managed systems misc they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM misc dealing with general issues that must be considered regardless of the domain of application (such as validity misc uncertainty misc parameter sensitivity misc agent definition misc data provision) misc and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks misc and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion misc we can observe that solutions based on complex systems simulations are starting misc to some extent misc to be influential in policymaking; however misc practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. misc Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling misc Agriculture (General) misc Food processing and manufacture
topic_browse	misc S1-972 misc TP368-456 misc from biological systems to complex coupled human-natural systems. In particular misc when used to simulate man-managed systems misc they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM misc dealing with general issues that must be considered regardless of the domain of application (such as validity misc uncertainty misc parameter sensitivity misc agent definition misc data provision) misc and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks misc and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion misc we can observe that solutions based on complex systems simulations are starting misc to some extent misc to be influential in policymaking; however misc practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking. misc Agent-Based model\| quantitative sustainability assessment\| Life Cycle Assessment\| life cycle sustainability analysis\| agricultural modelling misc Agriculture (General) misc Food processing and manufacture
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title	Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use
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title_full	Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use
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title_sort	implementation of agent-based models to support life cycle assessment: a review focusing on agriculture and land use
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title_auth	Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use
abstract	Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking.
abstractGer	Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking.
abstract_unstemmed	Agent-Based Models (ABMs) have been adopted to simulate very different kinds of complex systems, from biological systems to complex coupled human-natural systems. In particular, when used to simulate man-managed systems, they have the advantage of allowing human behavioral aspects to be considered in the modelling framework. This paper provides a literature review of the application of ABMs for agricultural and land use modelling. One section is specifically devoted to the coupling of ABMs and Life Cycle Assessment (LCA) models. The aim of the paper is to give a perspective of the different “modelling blocks” one needs to take into account to build an ABM, dealing with general issues that must be considered regardless of the domain of application (such as validity, uncertainty, parameter sensitivity, agent definition, data provision), and providing concrete examples related specifically to ABMs applied to agricultural and land use modelling. The paper highlights the difficulties that the modelers can encounter in dealing with each of these modelling blocks, and presents the solutions that can be envisioned (mentioning those that have been applied in certain cases in the literature). As a general conclusion, we can observe that solutions based on complex systems simulations are starting, to some extent, to be influential in policymaking; however, practical user-friendly tools that allow scenario simulations also to non-expert users are clearly still lacking.
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title_short	Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use
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Implementation of Agent-Based Models to support Life Cycle Assessment: A review focusing on agriculture and land use

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