Review on detection of critical transition in ecosystems |
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| Affiliation: | Center for Human-Environment System Sustainability, State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China |
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| Abstract: | Ecosystem with alternative stable states would respond abruptly to minor changes in the external conditions and switch into an alternative stable state with different ecosystem structures and functions when the system approaches the transition threshold. This phenomenon is called critical transition. It is often the case that such transition can result in marked changes in ecosystem services, which are much likely to impact the sustainable development of human being. It is difficult to predict the critical transitions in ecosystems, but the large amount of research in this field show that by monitoring some generic properties (i.e. early-warning signals) relating to ecosystem status, we are able to discern if the system approaches the transition threshold; this can be used to predict the critical transitions in ecosystems. This paper summarizes the major findings and achievements in the field of detecting critical transitions in ecosystems. It first discusses the mechanism and consequence of critical transitions, and then introduces the basic theory behind the early-warning signals. We sum up the methods used to extract early-warning signals both from temporal and spatial dimensions. Finally, challenges confronting the contemporary research are summarized. In future, the application of early-warning signals should make full use of both temporal and spatial data and combine different indicators to improve our ability to forecast unfavorable environmental events. Also, special attention needs to be paid to the relationship between critical transitions and ecosystem structures so that we can strengthen the ability to predict critical transitions in ecosystems. |
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| Keywords: | critical slowing down critical transition early-warning signal ecological resilience stable state |
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