期刊
PLOS COMPUTATIONAL BIOLOGY
卷 8, 期 2, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1002360
关键词
-
资金
- Max Planck Society
Critical transitions are sudden, often irreversible, changes that can occur in a large variety of complex systems; signals that warn of critical transitions are therefore highly desirable. We propose a new method for early warning signals that integrates multiple sources of information and data about the system through the framework of a generalized model. We demonstrate our proposed approach through several examples, including a previously published fisheries model. We regard our method as complementary to existing early warning signals, taking an approach of intermediate complexity between model-free approaches and fully parameterized simulations. One potential advantage of our approach is that, under appropriate conditions, it may reduce the amount of time series data required for a robust early warning signal.
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