duncanobrien

EWSmethods

EWSmethods: an R package to forecast tipping points at the community level using early warning signals and machine learning models

COVID-EWS

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.

deep-early-warnings-pnas

critical transitions, early warning signals, dynamical systems, theoretical ecology, machine learning

duncanobrien.github.io

ews-assessments

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.

lpi-multivariate-res

open-datasets

Repository to store data produced by Duncan O'Brien (Twitter - @duncanobrienn) and collaborators.

plankton-FD

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.