duncanobrien Goto Github PK
Name: Duncan O'Brien
Type: User
Company: University of Bristol
Location: United Kingdom
Name: Duncan O'Brien
Type: User
Company: University of Bristol
Location: United Kingdom
Data, code and results from O'Brien D.A. and Clements C.F., 2021, Early warning signal reliability varies with COVID-19 waves, Biology Letters, 17:20210487, https://doi.org/10.1098/rsbl.2021.0487.
critical transitions, early warning signals, dynamical systems, theoretical ecology, machine learning
Data, code and results from O'Brien D.A., Deb S., Gal G., Thackeray S.J., Dutta P.S., Matsuzaki S.S., May L. & Clements C.F. 2023. Early warning signals have limited applicability to empirical lake data.
EWSmethods: an R package to forecast tipping points at the community level using early warning signals and machine learning models
Repository to store data produced by Duncan O'Brien (Twitter - @duncanobrienn) and collaborators.
Data, code and results from O'Brien D.A., Gal G., Thackeray S.J., Matsuzaki S.S & Clements C.F. 2022. Planktonic functional diversity changes in synchrony with lake ecosystem state.
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