Few weeks ago our paper on spatial indicators for critical transitions was published in PloS One. It is a follow up paper from our previous work on methods for timeseries. The methods of the paper are now summarized in the spatial indicators section of the EWS toolbox website. The actual R code soon will be part of the update R earlywarnings package.
An interactive visualization version of the earlywarnings R package for critical transitions in the Data Challenge competition organised by the Waterloo Institute for Complexity and Innovation got into the 4 finalists. Although not reaching the first place, the reviews were flattering and Leo Lahti and myself got the kick into developing the package further. You can read more on it here and soon there will be more to follow.
The current issue of Theoretical Ecology is dedicated on Early Warnings and Tipping Points in Ecology. This special issue was co-edited by Vasilis Dakos and Alan Hastings and contains 11 original research papers from key contributors of the topic. You can find a complete list of content here. We hope it will have a strong impact in the further development of anticipating regime shifts in complex systems. It will be highlighted in the upcoming ESA conference in Minneapolis.
Two interesting papers on empirically demonstrating the detection of critical transitions using the generic early warnings have been recently published in high profile journals. Dai et al showed experimentally that a disturbance in connected yeast populations affects longer spatial scales close to a critical transition. The authors introduced this effect as the analogue of ‘recovery time‘ in space: namely ‘recovery length’ to show that it increases prior to a critical transition. Streeter and Dugmore used transects to substitute time for space and measured early warnings for land surface transitions. They found signatures of variance and autocorrelation in tephra deposits along transects that cut across 6 types of landscape thresholds. This is the first study that early warning have been used for critical transitions across space in field observations for such types of transitions. Also in this study the authors have used our recently developed earlywarnings package for R. These two studies are brilliant examples of applying early warning research in creative ways performing experiments in the lab, or looking for experiments conducted by nature.
After working hard, we are happy to announce that our earlywarning package is ready to use directly from R! No need to download and install locally, as from R you can find it and install it using your selected CRAN repository. Also, we keep a live update of the toolbox in github, as we have created an organization earlywarningstoolbox that aims to host the further development of the project.