Passing the Point of No Return. Seekell, D. 354(6316):1109. ![Passing the Point of No Return [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex [Excerpt] In the field of ecology, regime shifts are massive changes in function and character that occur when an ecosystem passes a tipping point. Regime shifts sometimes have severe consequences for human well-being through losses of ecosystem services, including desertification in arid regions and marine fisheries collapses. These changes are difficult to predict and sometimes impossible to reverse. For these reasons, understanding how to anticipate and prevent regime shifts is one of the most important challenges faced by environmental scientists. [] Theoretical analyses have identified statistical anomalies, such as increased autocorrelation and variance in time series before regime shifts. These patterns are a manifestation of ” critical slowing down” – when return rate from perturbation to equilibrium progressively declines before a tipping point [...] [] [...] [] A specific contribution of my dissertation was to evaluate the efficacy of tests for conditional heteroskedasticity (clustered variability in time series) as early warning indicators. Conditional heteroskedasticity is widely studied by economists but almost never examined by ecologists. A key observation in my dissertation was the presence of conditional heteroskedasticity in time series from ecosystems approaching tipping points but not from stable ecosystems. [] This observation has great practical importance. Most early warning indicators are interpreted by comparison with indicators from a pristine reference system. Such pristine systems are in short supply given the global nature of many environmental changes, such as climate warming. Conditional heteroskedasticity tests have thresholds that make clear distinctions between ” warning” and ” no warning” conditions, reducing the need for pristine reference systems [...]
@article{seekellPassingPointNo2016,
title = {Passing the Point of No Return},
author = {Seekell, David},
date = {2016-12},
journaltitle = {Science},
volume = {354},
pages = {1109},
issn = {1095-9203},
doi = {10.1126/science.aal2188},
url = {https://doi.org/10.1126/science.aal2188},
abstract = {[Excerpt] In the field of ecology, regime shifts are massive changes in function and character that occur when an ecosystem passes a tipping point. Regime shifts sometimes have severe consequences for human well-being through losses of ecosystem services, including desertification in arid regions and marine fisheries collapses. These changes are difficult to predict and sometimes impossible to reverse. For these reasons, understanding how to anticipate and prevent regime shifts is one of the most important challenges faced by environmental scientists.
[] Theoretical analyses have identified statistical anomalies, such as increased autocorrelation and variance in time series before regime shifts. These patterns are a manifestation of ” critical slowing down” -- when return rate from perturbation to equilibrium progressively declines before a tipping point [...]
[] [...]
[] A specific contribution of my dissertation was to evaluate the efficacy of tests for conditional heteroskedasticity (clustered variability in time series) as early warning indicators. Conditional heteroskedasticity is widely studied by economists but almost never examined by ecologists. A key observation in my dissertation was the presence of conditional heteroskedasticity in time series from ecosystems approaching tipping points but not from stable ecosystems.
[] This observation has great practical importance. Most early warning indicators are interpreted by comparison with indicators from a pristine reference system. Such pristine systems are in short supply given the global nature of many environmental changes, such as climate warming. Conditional heteroskedasticity tests have thresholds that make clear distinctions between ” warning” and ” no warning” conditions, reducing the need for pristine reference systems [...]},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14218613,~to-add-doi-URL,desertification,ecology,ecosystem-services,fish-resources,heteroskedasticity,irreversibility,lepomis-gibbosus,micropterus-salmoides,regime-shift,statistics,system-catastrophe,tipping-point,water-resources},
number = {6316}
}
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For these reasons, understanding how to anticipate and prevent regime shifts is one of the most important challenges faced by environmental scientists. [] Theoretical analyses have identified statistical anomalies, such as increased autocorrelation and variance in time series before regime shifts. These patterns are a manifestation of ” critical slowing down” – when return rate from perturbation to equilibrium progressively declines before a tipping point [...] [] [...] [] A specific contribution of my dissertation was to evaluate the efficacy of tests for conditional heteroskedasticity (clustered variability in time series) as early warning indicators. Conditional heteroskedasticity is widely studied by economists but almost never examined by ecologists. A key observation in my dissertation was the presence of conditional heteroskedasticity in time series from ecosystems approaching tipping points but not from stable ecosystems. [] This observation has great practical importance. 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