Special issue on early-warning research in journal of Theoretical Ecology

After an invitation by Alan Hastings (editor-in-chief) and a year of preparation, the current issue of Theoretical Ecology is dedicated on Early Warnings and Regime Shifts.
The issue contains 11 original research papers from key contributors of the topic ranging from data analysis, to theoretical considerations, lake ecosystems to disease epidemics. We hope it will have a strong impact in the further development of anticipating regime shifts in complex systems.

Are Warning Signals specific to Catastrophic Transitions?

There is a lot of interest on the limits of resilience indicators and on whether they are uniquely associated with catastrophic transitions. We tried to shed light on that question in a short piece that just appeared in Oikos. There, we show that the same early warnings may signal non catastrophic transitions, but the same transitions are as well bifurcation points. Thus, it is not surprising that the same expectations for signals of deteriorating resilience are universal prior to any (local) bifurcation. The challenge remains in finding signals that would be specific to the catastrophic, unexpected, and irreversible shifts.

highlighted in Editor’s choice in Oikos

earlywarnings package in R libraries

logoEWS Together with Leo Lahti, we fixed bugs and moved the earlywarnings toolbox in R. It is now a library ready to be installed from your preferable CRAN repository. In the process, we also migrated the earlywarnings toolbox to github for shifitng towards open-source, community-based project development. We hope this will facilitate the use of the toolbox both for research and education. More details on the Early Warning Signals Toolbox webpage.

Passing slowly tipping points: opportunities and challenges

In a short conceptual paper that appeared this month in TREE, we play around with the idea that depending on the scale and the rate of change of ecological systems, responses to crossing tipping points may differ widely. Ecosystems without tipping points may appear hysteretic, whereas hysteretic systems may offer a window of opportunity for averting a regime shift even after having passed their tipping point. Such insights may change the way ecosystem managers and policy makers view common practices in a changing world.

Flickering before a shift to eutrophication

Together with colleagues from China and the UK we just published work on a paleo limnological record in a big chinese lake that shows a transition to eutrophication during the last 30 years. Interestingly, the data offer the possibility to show that the system exhibits bimodality and that approaching to the permanent shift ‘flickering’ between the oligotrophic and eutrophic state may be observed. We compared these results to model simulations and we conclude that flickering may be more possible to detect in the most common ecological records at hand.

Review on anticipating critical transitions in last week´s issue in Science

Our review paper on Anticipating Critical Transitions summarizes the advancement and popularity in estimating early-warning signals for approaching transitions in a variety of disciplines together with some ground-breaking experimental demonstrations that followed the earlier review on early-warnings. In addition, new ideas are mapped out and the challenge of merging network perspectives on stability and collapse with early-warnign research is pioneered.

7 principles for enhancing the resilience of ecosystem services

Our long lasting project with the RAYS cohort just got appeared in a review/synthesis paper where we try to summarize basic principles that so far have been widely proposed to be fundamental for supporting the resilience of ecosystem services. Important part of this work is that we try to identify gaps in the existing research on resilience factors based on literature and expert opinion. This effort received quite some enthusiasm so that we decided to extent it into a book.

KNAW colloquium, masterclass and SparcS

Our colloquium and masterclass on ‘Early-warning signals for critical transitions: bridging the gap between theory and practice’ will be hosted by the Dutch Royal Science and Arts Society (KNAW) from 10 to 12 of October 2012 in Amsterdam. This is also going to be the official kick-off of SparcS – the Synergy Program for Analyzing Resilience and Critical transitionS: an initiative on getting people to work on issues of critical transitions and resilience in a broad range of scientific fields.

PLoS One paper out!

The methodological paper that we worked on during the Santa Fe Institute workshop last October became available few weeks ago. It presents a suite of most developed methods for identifying early-warnings and provides clear step-by-step examples on how to apply them, in an attempt to offer a protocol to the uninitiated into the field. Most of the content of the paper is presented in simple form- together with more supporting material- on the newly launched Early Warning Signals Toolbox. This website accompanies the paper and aims to be a source of existing methods, newly developed methods, and a repository of case studies. Have a look and if you are interested to contribute, don’t hesitate to contact me!

Model-based leading indicators for critical transitions

In a recent work with Tony Ives, we showed how modified linear models with time-varying parameters can be used to extract an indicator of instability for a time series that may be drifting towards a regime shift. The paper is available online in Ecosphere. The idea is simply that instead of fitting an autoregressive model and finding a fixed value for its parameters, to fit an autoregressive model with parameters that change based on the point one is along the time series. This is possible due to a Kalman filter fitting proceedure and seems to not require a too much long time series. We also show that fitting threshold autoregressive models can distinguish alternative attractors in a flickering time series. The code to execute all this is currently in Matlab, but we aim in converting it to an easy to use routine in the R environment.