A Bayesian network approach to investigating climate change and commodity price change impacts on human well‐being

Lynam, Timothy

doi:10.1002/9781118529577.ch31

Cited by 1 publication

(1 citation statement)

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“…The higher the level of organisation dealing with adaptation planning, the greater the value of integrated large-scale assessments to support the coordination of policy measures (i.e., regulations, incentives) towards congruent outcomes. Approaches such as the Bayesian network approach can be useful to provide a broad integrated vulnerability assessments under climate change, while making prediction uncertainties explicit (see also Lynam et al, [72]). The large potential benefit of integrated assessment tools to help foster food security by providing a platform that brings modellers and stakeholders from different backgrounds together was also highlighted by Webber et al [73].…”

Section: The Value Of Model-based Information For Adaptation Planningmentioning

confidence: 99%

Adapting Agricultural Production Systems to Climate Change—What’s the Use of Models?

Holzkämper

2017

Agriculture

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Climate change poses a challenge to agricultural production and its impacts vary depending on regional focus and on the type of production system. To avoid production losses and make use of emerging potentials, adaptations in agricultural management will inevitably be required. Adaptation responses can broadly be distinguished into (1) short-term incremental responses that farmers often choose autonomously in response to observed changes and based on local knowledge and experiences, and (2) long-term transformative responses that require strategic planning, and which are usually implemented at a larger spatial scale. Models can be used to support decision making at both response levels; thereby, different features of models prove more or less valuable depending on the type of adaptation response. This paper presents a systematic literature review on the state-of-the-art in modelling for adaptation planning in agricultural production systems, investigating the question of which model types can be distinguished and how these types differ in the way they support decision making in agricultural adaptation planning. Five types of models are distinguished: (1) empirical crop models; (2) regional suitability models; (3) biophysical models; (4) meta-models; and (5) decision models. The potential and limitations of these model types for providing decision-support to short-and long-term adaptation planning are discussed. The risk of maladaptation-adaptation that implies negative consequences either in the long term or in a wider context-is identified as a key challenge of adaptation planning that needs more attention. Maladaptation is not only a risk of decision making in the face of incomplete knowledge of future climate impacts on the agricultural production system; but it can also be a threat if the connectedness of the agroecosystem is not sufficiently acknowledged when management adaptations are implemented. Future research supporting climate change adaptation efforts should thus be based on integrated assessments of risk and vulnerabilities (considering climate variability and uncertainty). To secure adaptation success in the long term, frameworks for monitoring management adaptations and their consequences should be institutionalised.

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Section: The Value Of Model-based Information For Adaptation Planningmentioning

confidence: 99%

Adapting Agricultural Production Systems to Climate Change—What’s the Use of Models?

Holzkämper

2017

Agriculture

View full text Add to dashboard Cite

show abstract

A Bayesian network approach to investigating climate change and commodity price change impacts on human well‐being

Cited by 1 publication

References 22 publications

Adapting Agricultural Production Systems to Climate Change—What’s the Use of Models?

Adapting Agricultural Production Systems to Climate Change—What’s the Use of Models?

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