An agent-based modelling approach to evaluate factors influencing bioenergy crop adoption in north-east Scotland

Chris Brown*, Innocent Bakam, Pete Smith, Robin Matthews

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)
19 Downloads (Pure)

Abstract

An agent-based modelling (ABM) framework was adapted to assess bioenergy crop uptake and integrate social and economic processes with biophysical elements. Survey results indicated that economic rationalisation was intrinsic to farmers' decision-making, but was not the only consideration. This study presents an approach, set within an established resource management framework, to incorporate a number of key socio-economic factors, which we call Mitigation Willingness Factors (MWFs), using survey data collected from farmers and land managers, into the ABM. The MWFs represent farmers' willingness to compromise revenue in order to reduce GHG emissions, derived from their attitudes to climate change and the ability of different economic mechanisms to stimulate energy crop uptake. Adoption of bioenergy crops of different farmer types and farming enterprises was also assessed. Adoption rates and scenarios that take into account noneconomic factors are presented, and particular farming enterprises that may respond more positively to policy initiatives are identified.

Original languageEnglish
Pages (from-to)226-244
Number of pages19
JournalGlobal Change Biology. Bioenergy
Volume8
Issue number1
Early online date14 Mar 2015
DOIs
Publication statusPublished - 1 Jan 2016

Bibliographical note

Acknowledgements

This work was funded through a NERC-CASE studentship with the University of Aberdeen and the James Hutton Institute (JHI). The authors wish to thank those farmers who participated in the survey and provided data for the research, and BioSS (JHI – Aberdeen) for advising on statistical analysis.

Keywords

  • agent-based models
  • bioenergy crops
  • decision-making
  • greenhouse gases
  • land use
  • socio-economic factors
  • survey

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