Critical Slowing down as Early Warning for the Onset of Collapse in Mutualistic Communities. Dakos, V. & Bascompte, J. Proceedings of the National Academy of Sciences, 111(49):17546–17551, December, 2014. doi abstract bibtex [Significance] Little is known on whether structurally diverse ecological networks may respond abruptly to anthropogenic stress and even less on our ability to detect such responses in advance. By simulating mutualistic communities en route to a tipping point, we show how critical slowing-down indicators may be used as early warnings for the collapse of ecological networks. Our findings not only confirm the existence of the generic dynamical signatures of tipping points in ecological networks but also suggest a promising way for identifying most vulnerable components in a broad class of networks at the brink of collapse. [Abstract] Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.
@article{dakosCriticalSlowingEarly2014,
title = {Critical Slowing down as Early Warning for the Onset of Collapse in Mutualistic Communities},
author = {Dakos, Vasilis and Bascompte, Jordi},
year = {2014},
month = dec,
volume = {111},
pages = {17546--17551},
issn = {1091-6490},
doi = {10.1073/pnas.1406326111},
abstract = {[Significance]
Little is known on whether structurally diverse ecological networks may respond abruptly to anthropogenic stress and even less on our ability to detect such responses in advance. By simulating mutualistic communities en route to a tipping point, we show how critical slowing-down indicators may be used as early warnings for the collapse of ecological networks. Our findings not only confirm the existence of the generic dynamical signatures of tipping points in ecological networks but also suggest a promising way for identifying most vulnerable components in a broad class of networks at the brink of collapse.
[Abstract]
Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.},
journal = {Proceedings of the National Academy of Sciences},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13459637,anthropogenic-impacts,ecological-networks,ecology,indicators,non-linearity,risk-assessment,system-catastrophe,tipping-point},
lccn = {INRMM-MiD:c-13459637},
number = {49}
}
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