It was a really short visit, but we all really enjoyed how they used elegant mathematical and data-driven approaches to understand socio-ecological systems.
I am super delighted to share this — somewhat belated — news that Sumithra Sankaran has defended her PhD thesis on 7th December 2018. Sumithra’s thesis was on understanding how local interactions, spatial patterns and ecosystem stability are related. Needless to say, Sumithra gave a fabulous presentation and the examiners (including external examiner Prof Partha Sarathi Dutta from IIT Ropar, Department of Mathematics) were super impressed.
It is worth noting – especially for prospective students to our lab – that Sumithra was formally trained in zoology and wildlife biology. Because of her exceptional interest in theory, she did a thesis in theoretical ecology involving fairly involved mathematical calculations, e.g., mean-field models, stochastic differential equations and their analyses via Fokker-Planck equations, cellular automata models. Finally, testing her predictions of theory with empirical data – which required another suite of skills in analysing remotely-sensed data, statistics, and making sense of results in light of theory!
Congratulations to Sumithra – its been so much fun collaboratingworking with you – which I hope we will continue!
Our friends from France, Sonia Kefi and two of her group members Miguel Berdugo (currently a student of Prof Fernando Maestre in Spain and soon moving as a postdoc with Sonia) and Angeles Mayor (a postdoc with Sonia) visited Bengaluru for about a week. They enjoyed the tree festival Neralu and other small fun events in the town.
Of course, we all met them to have exciting discussions and how to take our collaboration forward. Here is a group picture at a cafetaria.
We are happy to announce that our new paper on testing theory of spatial indicators of critical slowing down and ecological transitions has appeared in the online early version of the journal Global Ecology and Biogeography. The paper was highlighted via a cover image (left) taken by Stephanie.
Congratulations to Amit Agrawal (former project assistant of our lab) and Sabiha Majumder (PhD student) for their first research publication! This project began during conversations between Stephanie Eby, Andrew P. Dobson and myself. That was back in 2010, when I was a post-doc at Princeton. They had this excellent high resolution data that made sense in the context of a theory paper from my thesis in 2009.
So what is this paper about?
Ecosystems like clear lakes or forests can abruptly collapse to ‘unhealthy’ states like toxic-turbid lakes or deserts with low vegetation. Our lab uses ideas from physics of phase transitions (e.g., water boiling to become vapour) to develop statistical tools of early warnings of such abrupt transitions. For example, two papers of my PhD thesis (Guttal and Jayaprakash 2008 and 2009) were on developing such tools to analyse time series and spatial data from ecosystems. The underlying theory is now popularly known as ‘Early warning signals of critical transitions’, “Theory of Critical slowing down”, etc.
In this paper, we were testing such tools using spatial data of large scale ecosystems. There were earlier efforts to test these quantitative tools, but mostly in simple laboratory conditions or controlled lake experiments.
Specifically, we test the prediction that the following metrics show stronger signatures of transitions ‘before a collapse of an ecosystem’
(A) Spatial variance (proposed in Guttal and Jayaprakash, 2009)
(B) Spatial skewness (proposed in Guttal and Jayaprakash, 2009)
(C) Spatial autocorrelation (proposed in Dakos et al 2010)
(D) Spatial spectra (proposed in Carpenter and Brock 2010).
This graph below shows how theoretical predictions and real data match.
There were a few subtle and insightful aspects related to analysing this dataset. First, we didn’t have an ideal dataset, so we had to make an approximation called ‘space-for-time substitution’ to compare theory with real data. We justified this approach using a model. Second, the data were discrete-state (occupied/unoccupied), unlike what the models typically assumes continuous variables (like biomass density) in each of the above papers. We developed a data preprocessing method called coarse-graining, inspired from the physics literature. We thought the method to be sufficiently important and hence the details of the method will be published separately. Analysing this dataset has motivated various thesis chapters in our lab’s PhD student Sabiha Majumder, who is from Physics department and works jointly with me and Prof. Sriram Ramaswamy.
I should add that reviewers gave detailed comments that helped the manuscript a lot. This was also our first manuscript where we used services of Axios.
All codes and some data associated with this manuscript are available on our Github page: https://github.com/tee-lab/spacetime-csd
Our new paper showing “Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk” is out in PLoS ONE!
Nature India carried out a very nice article on our work, written by Mr Varma. National University of Ireland, Galway issued a press-release (an initial draft of which was written by Rajashree of Science Media Centre, IISc). and featured it on their website. Here is a media article at Deccan Herald, but whats written there just does not make sense.
This work was done in collaboration with Dr Srinivas Raghavendra, an economist at the National University of Ireland, Galway. We started the work sometime in mid-2012. Nikunj Goel, a Physics undergraduate student at IISc, joined this work in early 2014 and did enormous contributions to the manuscript. Quentin Hoarau, an undergraduate itern from CNS, France, was also a co-author on the manuscript.
We are delighted that our school got a coverage from Deccan Herald, an important newspaper in southern India. My colleague Srinivas Raghavendra and a student participating in the conference are quoted in the article.
In this school, I will be teaching techniques related to our collaborative work on testing predictions of early warning signals of critical transitions in financial markets. This work was done with Srinivas Raghavendra and my former UG students Nikunj Goel and Quentin Hoarau.
And Happy new year to all!
Dr Sonia Kefi, a researcher from the CNRS Montpellier and two of her students, Alex Genin and Miguel Berdugo, are visiting our lab for two weeks from 27th Nov to 10th Dec 2015. Our labs are collaborating on developing mathematical models of patterned ecosystems, especially the vegetation of semi-arid ecosystems.
The three visitors from France and the three folks from our lab (me, Sumithra and Sabiha) went to a tea estate resort near Conoor in Tamil Nadu, away from the distraction of Bengaluru, to assess the progress we have made so far on our projects. We also had a guest – Krishnapriya Tamma, a PhD student from NCBS (Dr Uma Ramakrishnan’s student) who gave a fantastic talk on her superb phd thesis. It was a great scientific meeting discussing a number of ideas.
Sonia also gave a departmental seminar at CES on 7th Dec 2015 on ‘Identifying the building blocks of ecological networks‘
Visit by Sonia and her students is part of travel grant we were awarded early this year by the Indo-French Centre for Applied Mathematics. In the first visit, we visited Montpellier in June this year.
We are delighted that we have been awarded a grant from Indo-French Centre for Applied Mathematics. This is a collaborative grant with Dr. Sonia Kefi, a researcher at the CNRS based Institut des Sciences de l’Evolution de Montpellier (ISEM), France. This will help us continue our collaborations on the topic of mathematical and computational models of self-organization in semi-arid ecosystems.
The grant is awarded for a duration of two years. It allows for visits of both of our labs working on this problem to travel to each other labs. The total funds for the first year is around 12,000 Euros.
For those interested in knowing more, see Kefi, Guttal, et cl 2014, Plos ONE for our previous work where, together with various leading researchers in the field, we developed a systematic methodology to detect early warning signals of ecological transitions.
I am giving a talk at a workshop on Environmental Statistics at ISI Kolkata. This is jointly organized by SAMSI, am NSF funded institute in the USA on mathematics and statistics and ISI Kolkata. The workshop has various talks on using statistical models in studying environmental data. There are many talks on analyzing data related to climate and a few on spatial data as well.
I presented our own on devising early warning signals of critical transitions. My talk was a bit different compared to others in using dynamical systems models that helps us devise statistical measures for studying ecology. I also used our recent analysis of financial markets to illustrate statistical aspects of detecting early warning signals.
Our new collaborative paper (with researchers from five different countries) summarizing methods to detect early warning signals of ecological transitions using spatial patterns has been published in Plos ONE this March. Click here to read the paper.
The paper also comes with an R package to use the methods. Its available from the github: https://github.com/earlywarningtoolbox/spatial_warnings
If you would like to use this toolbox and face any problems, please feel free to contact me:
Story behind the paper: Vasilis Dakos, Marten Scheffer and Stephen R Carpenter organized a fantastic workshop in Santa Fe Institute (New Mexico, USA) and invited a bunch of people who had worked on developing early warning signals. It was two and a half days of extremely interesting discussion and we decided to summarize the methods of early warning signals in two papers.
One paper was to focus exclusively on methods to detect early warning signals in time series data. Vasilis Dakos took the lead and we published a paper in Plos ONE that can be found here. Together with the paper, we also provided an R package so that researchers can use the methods without having to develop their own code. The methods and package can be obtained from the website: www.early-warning-signals.org
A second paper was to focus on the methods for analyzing spatial patterns to detect early warning signals. Sonia Kefi and myself took the lead, and we had to face the challenge of summarizing results for analyzing spatial patterns where the methods have not been not so well developed. Finally, the second paper has also been now published! We now need to make the codes more easily accessible to users.