Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 550835
Title Spatial early warning signals for impending regime shifts : A practical framework for application in real-world landscapes
Author(s) Nijp, Jelmer J.; Temme, Arnaud J.A.M.; Voorn, George A.K. van; Kooistra, Lammert; Hengeveld, Geerten M.; Soons, Merel B.; Teuling, Adriaan J.; Wallinga, Jakob
Source Global Change Biology 25 (2019)6. - ISSN 1354-1013 - p. 1905 - 1921.
DOI https://doi.org/10.1111/gcb.14591
Department(s) Soil Geography and Landscape
Mathematical and Statistical Methods - Biometris
PE&RC
Laboratory of Geo-information Science and Remote Sensing
Biometris
Forest and Nature Conservation Policy
WIMEK
Hydrology and Quantitative Water Management
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) alternative stable states - critical slowing down - early warning signals - ecosystem resilience - environmental change - landscapes - regime shifts - remote sensing - spatial patterns - tipping points
Abstract

Prediction of ecosystem response to global environmental change is a pressing scientific challenge of major societal relevance. Many ecosystems display nonlinear responses to environmental change, and may even undergo practically irreversible ‘regime shifts’ that initiate ecosystem collapse. Recently, early warning signals based on spatiotemporal metrics have been proposed for the identification of impending regime shifts. The rapidly increasing availability of remotely sensed data provides excellent opportunities to apply such model-based spatial early warning signals in the real world, to assess ecosystem resilience and identify impending regime shifts induced by global change. Such information would allow land-managers and policy makers to interfere and avoid catastrophic shifts, but also to induce regime shifts that move ecosystems to a desired state. Here, we show that the application of spatial early warning signals in real-world landscapes presents unique and unexpected challenges, and may result in misleading conclusions when employed without careful consideration of the spatial data and processes at hand. We identify key practical and theoretical issues and provide guidelines for applying spatial early warning signals in heterogeneous, real-world landscapes based on literature review and examples from real-world data. Major identified issues include (1) spatial heterogeneity in real-world landscapes may enhance reversibility of regime shifts and boost landscape-level resilience to environmental change (2) ecosystem states are often difficult to define, while these definitions have great impact on spatial early warning signals and (3) spatial environmental variability and socio-economic factors may affect spatial patterns, spatial early warning signals and associated regime shift predictions. We propose a novel framework, shifting from an ecosystem perspective towards a landscape approach. The framework can be used to identify conditions under which resilience assessment with spatial remotely sensed data may be successful, to support well-informed application of spatial early warning signals, and to improve predictions of ecosystem responses to global environmental change.

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