Dataset Information

Global assessment of early warning signs that temperature could undergo regime shifts.

ABSTRACT: Climate change metrics have been used to quantify the exposure of geographic areas to different facets of change and relate these facets to different threats and opportunities for biodiversity at a global scale. In parallel, a suite of indicators have been developed to detect approaching transitions between alternative stable states in ecological systems at a local scale. Here, we explore whether particular geographic areas over the world display evidence for upcoming critical transitions in the temperature regime using five Early Warning Indicators (EWIs) commonly used in the literature. Although all EWIs revealed strong spatial variations regarding the likelihood of approaching transitions we found differences regarding the strength and the distribution of trends across the world, suggesting either that different mechanisms might be at play or that EWIs differ in their ability to detect approaching transitions. Nonetheless, a composite EWI, constructed from individual EWIs, showed congruent trends in several areas and highlighted variations across latitudes, between marine and terrestrial systems and among ecoregions within systems. Although the underlying mechanisms are unclear, our results suggest that some areas over the world might change toward an alternative temperature regime in the future with potential implications for the organisms inhabiting these areas.

SUBMITTER: Chevalier M

PROVIDER: S-EPMC6030089 | biostudies-other | 2018 Jul

REPOSITORIES: biostudies-other

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Global assessment of early warning signs that temperature could undergo regime shifts.

Chevalier Mathieu M Grenouillet Gaël G

Scientific reports 20180703 1

Climate change metrics have been used to quantify the exposure of geographic areas to different facets of change and relate these facets to different threats and opportunities for biodiversity at a global scale. In parallel, a suite of indicators have been developed to detect approaching transitions between alternative stable states in ecological systems at a local scale. Here, we explore whether particular geographic areas over the world display evidence for upcoming critical transitions in the ...[more]

PMID: 29968797

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Project description: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.

Dataset Information

Global assessment of early warning signs that temperature could undergo regime shifts.

Publications

Global assessment of early warning signs that temperature could undergo regime shifts.

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