Agent-based modelling of land use dynamics and residential quality of life for future scenarios

Murray-Rust, Dave; Rieser, Verena; Robinson, Derek T.; Miličić, Vesna; Rounsevell, Mark

doi:10.1016/j.envsoft.2013.02.011

Cited by 61 publications

(29 citation statements)

References 44 publications

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“…This is beneficial as it allows for open cross-validation of the model as well as the exploration of land-use-change futures under various climate and socio-economic change scenarios (e.g. Murray-Rust et al 2013), making RULEX a potentially powerful policy analysis tool. Before such explorations can be made, a sensitivity analysis of RULEX to a range of model parameters and input variables is needed, which will be the topic of a forthcoming paper.…”

Section: Discussionmentioning

confidence: 99%

Land-use change arising from rural land exchange: an agent-based simulation model

et al. 2014

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Introduction Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing farmers, nature organizations, and estate owners. Methods The RULEX model (Rural Land EXchange) was calibrated and applied to a 300 km 2 case study area in the east of the Netherlands. Decision rules about which actor will sell and buy land, as well as which specific land to buy or sell are based on historical observations, interviews, and choice experiments.Results A reconstruction of land-use change for the period 2001-2009 demonstrates that RULEX reproduces most observed land-use trends and patterns. Given that RULEX simulates only one mechanism of land-use change, i.e. land exchange, it is conservative in simulating change. Conclusions With this model, we demonstrate the potential of incorporating land market processes in an agent-based, land-use change model. This supports understanding of land-use change that is brought about by ownership change, which is an important process in areas where pressure on land is high. The soundness of the process representation was corroborated by stakeholders within the study area. Land exchange models can be used to assess the impact of changes in climate, markets, and policy on land use change, and help to increase effectiveness of alternative land purchasing strategies by stakeholders or spatial planning policy.

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Section: Discussionmentioning

confidence: 99%

Land-use change arising from rural land exchange: an agent-based simulation model

et al. 2014

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“…For example, to explore the trade-offs between different stakeholders under scenarios of fisheries management in coastal Mombasa, outputs from ecological models were linked to a rule-based model describing the interactions between different groups of fishers, fish traders, and their well-being (Daw et al 2015). Other modeling approaches such as agent-based modeling (Murray-Rust et al 2013) also offer potential for disaggregating individual Shares and Well-being Contribution.…”

Section: Policy Relevance Of Analysing Chains and Elasticitymentioning

confidence: 99%

Elasticity in ecosystem services: exploring the variable relationship between ecosystems and human well-being

Daw¹,

Hicks²,

Brown³

et al. 2016

E&S

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ABSTRACT. Although ecosystem services are increasingly recognized as benefits people obtain from nature, we still have a poor understanding of how they actually enhance multidimensional human well-being, and how well-being is affected by ecosystem change. We develop a concept of "ecosystem service elasticity" (ES elasticity) that describes the sensitivity of human well-being to changes in ecosystems. ES Elasticity is a result of complex social and ecological dynamics and is context dependent, individually variable, and likely to demonstrate nonlinear dynamics such as thresholds and hysteresis. We present a conceptual framework that unpacks the chain of causality from ecosystem stocks through flows, goods, value, and shares to contribute to the well-being of different people. This framework builds on previous conceptualizations, but places multidimensional well-being of different people as the final element. This ultimately disaggregated approach emphasizes how different people access benefits and how benefits match their needs or aspirations.Applying this framework to case studies of individual coastal ecosystem services in East Africa illustrates a wide range of social and ecological factors that can affect ES elasticity. For example, food web and habitat dynamics affect the sensitivity of different fisheries ecosystem services to ecological change. Meanwhile high cultural significance, or lack of alternatives enhance ES elasticity, while social mechanisms that prevent access can reduce elasticity.Mapping out how chains are interlinked illustrates how different types of value and the well-being of different people are linked to each other and to common ecological stocks. We suggest that examining chains for individual ecosystem services can suggest potential interventions aimed at poverty alleviation and sustainable ecosystems while mapping out of interlinkages between chains can help to identify possible ecosystem service trade-offs and winners and losers. We discuss conceptual and practical challenges of applying such a framework and conclude on its utility as a heuristic for structuring interdisciplinary analysis of ecosystem services and human wellbeing.

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“…The fifth category of models was those representing feedbacks between land use and social institutions. These demonstrated how land use changes can give rise to policy change (via formal institutions such as government or nongovernmental institutions, e.g., [67]) and behavioural change (via informal institutions such as social networks [12], altered financial conditions [76], or perceived quality of life [69]), which could result in land use changes in turn. In the reviewed articles, no models were found to represent feedbacks between land use and technological systems.…”

Section: Feedback Processes Between Land Use Systems and Related Systemsmentioning

confidence: 99%

“…This review covers a few examples of such models. Agents' financial conditions [76], requirements on certain type of land use [67], behavioural strategies [12] and perceived quality of life due to land use changes [69] have been explored by agent-based models.…”

Section: How Are Land Changes Represented?mentioning

confidence: 99%

How Are Feedbacks Represented in Land Models?

Chen

Bakker

Ligtenberg

et al. 2016

Land

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Land systems are characterised by many feedbacks that can result in complex system behaviour. We defined feedbacks as the two-way influences between the land use system and a related system (e.g., climate, soils and markets), both of which are encompassed by the land system. Land models that include feedbacks thus probably more accurately mimic how land systems respond to, e.g., policy or climate change. However, representing feedbacks in land models is a challenge. We reviewed articles incorporating feedbacks into land models and analysed each with predefined indicators. We found that (1) most modelled feedbacks couple land use systems with transport, soil and market systems, while only a few include feedbacks between land use and social systems or climate systems; (2) equation-based land use models that follow a top-down approach prevail; and (3) feedbacks' effects on system behaviour remain relatively unexplored. We recommend that land system modellers (1) consider feedbacks between land use systems and social systems; (2) adopt (bottom-up) approaches suited to incorporating spatial heterogeneity and better representing land use decision-making; and (3) pay more attention to nonlinear system behaviour and its implications for land system management and policy.

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Agent-based modelling of land use dynamics and residential quality of life for future scenarios

Cited by 61 publications

References 44 publications

Land-use change arising from rural land exchange: an agent-based simulation model

Land-use change arising from rural land exchange: an agent-based simulation model

Elasticity in ecosystem services: exploring the variable relationship between ecosystems and human well-being

How Are Feedbacks Represented in Land Models?

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