Mapping the Flow of Forest Migration through the City under Climate Change

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    Rapid climate change will create extreme problems for the biota of the planet. Much of it will have to migrate towards the poles at a rate far beyond normal speeds. In this context, the concept of assisted migration has been proposed to facilitate the migration of trees. Yet current practices of assisted migration focus on “where tree species should be in the future” and thus have many uncertainties. We suggest that more attention should be paid on the flow of forest migration. Therefore, this study develops a three-step methodology for mapping the flow of forest migration under climate change. Since the migration of trees depends on the activities of their seed dispersal agents, the accessibility of the landscape for dispersal agents is mainly considered in this study. The developed method combines a least-cost path model, a graph-based approach, and a circuit theory-based model. The least-cost path model is applied to map the movement of dispersal agents, based on which graph-based indices are used to evaluate landscape accessibility for dispersal agents, which in turn is used as the basis for circuit theory-based modelling to map the flow of forest migration. The proposed method is demonstrated by a case study in the Greater Manchester area, UK. The resulting maps identify the areas with high probability of the climate-driven migration of trees.

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    • Mapping the Flow of Forest Migration through the City under Climate Change

      Rights statement: © 2018 The Authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.

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    DOI

    Original languageEnglish
    Pages (from-to)139–151
    JournalUrban Planning
    Journal publication date21 Feb 2019
    Issue number1
    Volume4
    DOIs
    Publication statusPublished - 21 Feb 2019

    ID: 159343249