Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions

Pope, Aloah; Gimblett, Randy

doi:10.3389/fenvs.2015.00055

Cited by 27 publications

(18 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The explicit management of uncertainty in this method makes it a suitable tool to study potential interactions of hazards accounting for their probability of occurrence. Applications mainly involved quantitative information, but as explained in Section 4.5, Pope and Gimblett (2015) engaged the population for a bottom-up network creation, showing their use in case of poor quantitative data and stakeholder engagement. However, integration of feedback loop, spatial and temporal dynamics represent the future challenge to be explored to enhance the effectiveness of this method for climate change adaptation.…”

Section: Future Challengesmentioning

confidence: 99%

“…Existing studies considered the combination of a probabilistic evaluation performed by BN with one deterministic approach, like SDMs or ABM (Bertone et al, 2016a;Phan et al, 2016;Wang et al, 2016;Pope and Gimblett, 2015;Kocabas and Dragicevic, 2013). Advantages of this "hybridization" include the capacity of dealing with a high degree of uncertainty, the use of feedback loops and the integration of quantitative and qualitative data.…”

Section: Multi-risk Criteria Fulfilmentmentioning

confidence: 99%

“…Qualitative-data driven BN involving a participatory approach through stakeholder involvement allows a quick creation of a model and the inclusion of local information to better characterise people's perception on risk areas and legitimate risk reduction measures (Phan et al, 2016;Pope and Gimblett, 2015).…”

Section: Multi-risk Criteria Fulfilmentmentioning

confidence: 99%

“…Moreover, Wang et al (2016), Pope and Gimblett (2015) and Kocabas and Dragicevic (2013) performed a spatial analysis together with discrete temporal representation, looking at changes of systems variables and creating output maps. In addition to that, Pope and Gimblett (2015) also extended the analysis to future scenarios of climate change, assessing water scarcity impacts across different sectors (i.e. social, ecological and biophysical).…”

Section: Multi-risk Criteria Fulfilmentmentioning

confidence: 99%

See 3 more Smart Citations

Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation

Terzi

Torresan

Schneiderbauer

et al. 2019

Journal of Environmental Management

143

View full text Add to dashboard Cite

Climate change has already led to a wide range of impacts on our society, the economy and the environment. According to future scenarios, mountain regions are highly vulnerable to climate impacts, including changes in the water cycle (e.g. rainfall extremes, melting of glaciers, river runoff), loss of biodiversity and ecosystems services, damages to local economy (drinking water supply, hydropower generation, agricultural suitability) and human safety (risks of natural hazards). This is due to their exposure to recent climate warming (e.g. temperature regime changes, thawing of permafrost) and the high degree of specialization of both natural and human systems (e.g. mountain species, valley population density, tourism-based economy). These characteristics call for the application of risk assessment methodologies able to describe the complex interactions among multiple hazards, biophysical and socioeconomic systems, towards climate change adaptation. Current approaches used to assess climate change risks often address individual risks separately and do not fulfil a comprehensive representation of cumulative effects associated to different hazards (i.e. compound events). Moreover, pioneering multi-layer single risk assessment (i.e. overlapping of single-risk assessments addressing different hazards) is still widely used, causing misleading evaluations of multi-risk processes. This raises key questions about the distinctive features of multi-risk assessments and the available tools and methods to address them. Here we present a review of five cutting-edge modelling approaches (Bayesian networks, agent-based models, system dynamic models, event and fault trees, and hybrid models), exploring their potential applications for multi-risk assessment and climate change adaptation in mountain regions. The comparative analysis sheds light on advantages and limitations of each approach, providing a roadmap for methodological and technical implementation of multi-risk assessment according to distinguished criteria (e.g. spatial and temporal dynamics, uncertainty management, cross-sectoral assessment, adaptation measures integration, data required and level of complexity). The results show limited applications of the selected methodologies in addressing the climate and risks challenge in mountain environments. In particular, system dynamic and hybrid models demonstrate higher potential for further applications to represent climate change effects on multi-risk processes for an effective implementation of climate adaptation strategies.

show abstract

Section: Future Challengesmentioning

confidence: 99%

Section: Multi-risk Criteria Fulfilmentmentioning

confidence: 99%

Section: Multi-risk Criteria Fulfilmentmentioning

confidence: 99%

Section: Multi-risk Criteria Fulfilmentmentioning

confidence: 99%

See 2 more Smart Citations

Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation

Terzi

Torresan

Schneiderbauer

et al. 2019

Journal of Environmental Management

143

View full text Add to dashboard Cite

show abstract

“…For example, BNs are effective at data-reduction and, as such, a BN could provide inputs for the ABM (Pope and Gimmlet 2015). Outputs from the ABM could be used to further refine inputs to the BN (Figure 3).…”

Section: Model Interaction (Abms Bns)mentioning

confidence: 99%

D4.2 - Model development and data protocol

Grainger

Stewart

Piras

et al. 2016

View full text Add to dashboard Cite

Agent-Based Modelling to Delineate Spatiotemporal Control Mechanisms of the Stem Cell Niche

Mines

Chen

Shen

2019

Computational Stem Cell Biology

View full text Add to dashboard Cite

Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions

Abstract: Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions. Front. Environ. Sci. 3:55.

Cited by 27 publications

References 16 publications

Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation

Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation

D4.2 - Model development and data protocol

Agent-Based Modelling to Delineate Spatiotemporal Control Mechanisms of the Stem Cell Niche

Contact Info

Product

Resources

About