A Review of Bayesian Networks as a Participatory Modeling Approach in Support of Sustainable Environmental Management

Duespohl, Meike; Frank, Sina; Doell, P.

doi:10.5539/jsd.v5n12p1

Cited by 39 publications

(29 citation statements)

References 54 publications

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“…The problem of model parameterization may be particularly challenging for large numbers of system variables (McCann et al., ). The reliability of BBNs is an additional challenge, because quantitative and probabilistic understanding of causal relationships within social–ecological systems is generally poor, regardless of whether it is based on empirical studies or expert knowledge (Duespohl et al., ). Furthermore, use of discrete variables to represent system states and impacts (e.g., low, medium, high) leads to low precision of results and outcomes that are vague and difficult to interpret.…”

Section: Inventory Of Methodsmentioning

confidence: 99%

Options for integrating ecological, economic, and social objectives in evaluation and management of fisheries

Benson

Stephenson

2017

Fish and Fisheries

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There has been growing international attention in recent years to the Ecosystem Approach to Fisheries, Ecologically Sustainable Development, and similar initiatives that demand a comprehensive evaluation of the social, economic, and ecological performance of fisheries. However, the practical integration and application of these aspects continue to present a significant challenge for management. Progress to date has been limited by gaps in governance, objectives, disciplinary breadth, and methods. In this study, we develop an inventory of the methods that have been proposed to be able to incorporate ecological, economic, and social objectives and to provide a more comprehensive evaluation of fisheries and management. Our inventory includes both a description of the range of methods, and an evaluation against a set of criteria related to their utility in an applied, decision support context.

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Section: Inventory Of Methodsmentioning

confidence: 99%

Options for integrating ecological, economic, and social objectives in evaluation and management of fisheries

Benson

Stephenson

2017

Fish and Fisheries

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“…In contrast, the popularity of graphical models (Düspohl, Frank, and Döll, 2012;Greenland and Brumback, 2002) indicates that researchers find it useful to harness visual means to communicate-to peers and endusers-the complexities of the underlying theory. The research questions then emerge from, and are tied to, this theory.…”

Section: Redefining What Quantitative Methods Ismentioning

confidence: 99%

Using Bayesian statistical modelling as a bridge between quantitative and qualitative analyses: illustrated via analysis of an online teaching tool

Low‐Choy

Riley

Alston-Knox

2017

Educational Media International

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Bayesian methods provide a more general approach to statistical analysis that mathematically includes Null Hypothesis Significance Testing (NHST) and classical statistical modelling as special cases. This expanded, Bayesian, approach provides several benefits, which we illustrate using a case study about decision-making by teachers. We focus on a relatively unexplored topic: the way in which a Bayesian approach provides a 'bridge' between qual/quant methods. We highlight five bridges, illustrated using the case study: (1) visualization of the conceptual framework, (2) generalization via randomization and alternatives, (3) stories for interpretation, (4) computation that is flexible, and (5) continual learning, through priors. This work illustrates these bridges using a case study on a digital tool that wove together: a behavioural study to investigate decision-making, with an inbuilt perceptual component to probe rationale for specific decisions, and an interview component. A mixed method was therefore a natural choice for integrating learnings across these data sources. This online tool inhabits the digital realm of education which enables 'virtual' assessment, and sits midway between theoretical, written pieces and the fully immersed practicums in the classroom. Adopting a similar tool for training in a virtual classroom could provide greater accessibility and privacy, and enhanced feedback through the in situ qual/quant analytics. Thus the digital learning sphere provides a context for raising awareness of the potential that Bayesian statistical paradigm offers researchers who wish to connect qual/quant methods.

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“…Bayesian Networks can be used in a top-down manner for scenario and impact analysis. Top-down means that it is possible to change the probability laws of one or several parent nodes and analyze how states of nodes situated in lower parts of the network's hierarchy have their state's distribution changed (Düspohl et al 2012). With each of the individual BN, we simulated five scenarios related to biological control and habitat management.…”

Section: Scenario Explorationmentioning

confidence: 99%

First use of participatory Bayesian modeling to study habitat management at multiple scales for biological pest control

Salliou

Vialatte

Monteil

et al. 2019

Agron. Sustain. Dev.

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Habitat management is increasingly considered as a promising approach to favor the ecosystem service of biological control by enhancing natural enemies. However, habitat management, whether at local or landscape scale, remains very uncertain for farmers. Interactions between ecological processes and agricultural practices are indeed uncertain and site-specific, which makes implementation difficult. Thus, prospecting innovations based on habitat management may benefit from integrating local stakeholders and their knowledge. Our objective is to explore with both local and scientific stakeholders how they perceive agricultural practices, ecological processes, and services related to biological pest control and habitat management. We conducted a participatory Bayesian Network modeling approach with five stakeholders in Southwest France around apple orchard cultivation. We co-constructed such Bayesian Networks based on participants' knowledge. We explored scenarios favoring natural enemies and habitat manipulation with each participant's Bayesian Network. We compared how different stakeholders perceive the impact of each scenario on the biological control ecosystem service. Our results indicate that a landscape with a high proportion of seminatural habitats does not translate into significant biological control for most participants even though some stakeholders perceive a significant impact on generalist predators' activity within orchards. For these local stakeholders, habitat management at the orchard level such as inter-row vegetation seems currently more promising than at the landscape scale. Here, we show for the first time that the use of Bayesian modeling in a participatory manner can give precious insights into the most promising perspectives on habitat management at different scales. These different local perspectives suggest in particular that further dialogue between ecologists and local stakeholders should be sought about inter-row habitat management as the most promising practice to foster biological pest control and other ecosystem services.

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A Review of Bayesian Networks as a Participatory Modeling Approach in Support of Sustainable Environmental Management

Cited by 39 publications

References 54 publications

Options for integrating ecological, economic, and social objectives in evaluation and management of fisheries

Options for integrating ecological, economic, and social objectives in evaluation and management of fisheries

Using Bayesian statistical modelling as a bridge between quantitative and qualitative analyses: illustrated via analysis of an online teaching tool

First use of participatory Bayesian modeling to study habitat management at multiple scales for biological pest control

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