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Preparing for an uncertain future: Merging the strategic foresight toolkit with landscape modeling in northeast Minnesota's forests

  • Lynne M. Westphal
  • , Brian R. Sturtevant
  • , Gordon C. Reese
  • , Kathleen M. Quigley
  • , Jason Crabtree
  • , David N. Bengston
  • , Forrest D. Fleischman
  • , Joshua S. Plisinski

Research output: Contribution to journalArticlepeer-review

Abstract

“The Great Acceleration” poses serious challenges to land managers, policy makers, and all who are interested in the global sustainability of socioecological systems. Methods that can effectively address the uncertainty of the future to allow more robust and adaptive planning and management are urgently needed. We present a case study from northeastern Minnesota to highlight how strategic foresight methods and landscape modeling can serve as complementary tools to generate divergent yet plausible participatory scenarios to ultimately model the potential impacts of these scenarios on fundamental ecosystem services over 50 years. The landscape scenarios generated from the scenario process ranged widely, from optimistic futures to dire outcomes; these scenarios were far more divergent than outcomes explored in a traditional factorial landscape modeling study. This greater range in possible futures leads to more useful model outputs to guide the decisions of planners, managers, and policymakers. Our study illustrates advantages of blending the power of multiple strategic foresight tools with landscape modeling to generate alternative future storylines that are enlightening (i.e., expanding the scope of possibilities), useful (via strong contrasts), and yet plausible (i.e., grounded by robust science and stakeholder perspectives). Strategic foresight methods such as horizon scanning can also be useful in on-going monitoring of landscapes to support adaptive management aimed at fostering sustainable futures. Combining these approaches enhances creativity and wide-ranging plausibility (strategic foresight) with science-based assessments of outcomes and trajectories (landscape modeling), increasing the likelihood of creating resilient, preferred futures.

Original languageEnglish (US)
Article number104798
JournalLandscape and Urban Planning
Volume237
DOIs
StatePublished - Sep 2023

Bibliographical note

Publisher Copyright:
© 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land
  2. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Dinamica EGO
  • Forest landscape dynamics
  • Horizon scanning
  • LANDIS-II
  • Participatory scenarios
  • Socioecological systems

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