A review of global-local-global linkages in economic land-use/cover change models

T.W. Hertel, T.A.P. West, J. Börner, N.B. Villoria

Research output: Contribution to JournalReview articleAcademicpeer-review

Abstract

© 2019 The Author(s). Published by IOP Publishing Ltd.Global change drivers of land-use/cover change (LUCC) like population dynamics, economic development, and climate change are increasingly important to local sustainability studies, and can only be properly analyzed at fine-scales that capture local biophysical and socio-economic conditions. When sufficiently widespread, local feedback to stresses originating from global drivers can have regional, national, and even global impacts. A multiscale, global-to-local-to-global (GLG) framework is thus needed for comprehensive analyses of LUCC and leakage. The number of GLG-LUCC studies has grown substantially over the past years, but no reviews of this literature and their contributions have been completed so far. In fact, the largest body of literature pertains to global-to-local impacts exclusively, whereas research on local feedback to regional, national, and global spheres remain scarce, and are almost solely undertaken within large modeling institutes. As such, those are rarely readily accessible for modification and extension by outside contributors. This review of the recent GLG-LUCC studies calls for more open-source modeling and availability of data, arguing that the latter is the real constraint to more widespread analyses of GLG-LUCC impacts. Progress in this field will require contributions from hundreds of researchers around the world and from a wide variety of disciplines.
Original languageEnglish
Article number053003
JournalEnvironmental Research Letters
Volume14
Issue number5
DOIs
Publication statusPublished - 3 May 2019
Externally publishedYes

Funding

FundersFunder number
National Science Foundation1739253, 1463644

    Fingerprint

    Dive into the research topics of 'A review of global-local-global linkages in economic land-use/cover change models'. Together they form a unique fingerprint.

    Cite this