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Agent‐based modelling of alternative futures in the British land use system

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  • C Brown
  • B Seo
  • P Alexander
  • V Burton
  • EA Chacón‐Montalván
  • R Dunford
  • M Merkle
  • PA Harrison
  • R Prestele
  • EL Robinson
  • M Rounsevell
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Article numbere2022EF002905
<mark>Journal publication date</mark>30/11/2022
<mark>Journal</mark>Earth's Future
Issue number11
Volume10
Number of pages30
Publication StatusPublished
Early online date11/10/22
<mark>Original language</mark>English

Abstract

Socio-economic scenarios such as the Shared Socioeconomic Pathways (SSPs) have been widely used to analyse global change impacts, but representing their diversity is a challenge for the analytical tools applied to them. Taking Great Britain as an example, we represent a set of stakeholder-elaborated UK-SSP scenarios, linked to climate change scenarios (Representative Concentration Pathways), in a globally-embedded agent-based modelling framework. We find that distinct model components are required to account for divergent behavioural, social and societal conditions in the SSPs, and that these have dramatic impacts on land system outcomes. From strong social networks and environmental sustainability in SSP1 to land consolidation and technological intensification in SSP5, scenario-specific model designs vary widely from one another and from present-day conditions. Changes in social and human capitals reflecting social cohesion, equality, health and education can generate impacts larger than those of technological and economic change, and comparable to those of modelled climate change. We develop an open-access, transferrable model framework and provide UK-SSP projections to 2080 at 1km2 resolution, revealing large differences in land management intensities, provision of a range of ecosystem services, and the knowledge and motivations underlying land manager decision-making. These differences suggest the existence of large but underappreciated areas of scenario space, within which novel options for land system sustainability could occur.