Emergent patterns in nature and society

Mapping regime shifts

The regime shifts database (RSDB) is to my knowledge the largest repository of information about regime shifts in the world. It synthesises scientific literature about known social-ecological regime shifts that can have impacts on ecosystem services. I always think of it as a Wikipedia of regime shifts: a public online repository where people can go and learn what are they about, but also contribute content and cases.

Lead by Oonsie Biggs and Garry Peterson at the Stockholm Resilience Centre, the database started as an internship I did as master student in 2009. Later it became my master thesis and soon after the core of my doctoral studies. Several master thesis have been published using the database and it has also been useful for international assessments of regime shifts. It contributed to Global Biodiversity Outlook 3 (2010), the Arctic Resilience Assessment (2016), and more recently I was asked to contribute a short synthesis for IPBES – the International Panel for Biodiversity and Ecosystem Services.

Despite its importance, at least on my eyes, the regime shift database is largely unknown to the scientific community. There is no published peer reviewed paper describing how it was done and how can it be used. As a result, few groups have been publishing work suggesting that a framework for comparing regime shifts is needed, in other words: reinventing the wheel. The first public available draft of that paper is included on my Licenciate thesis (2013), and a later edited pre-print was posted on bioRxive (2015) that was included on my PhD thesis. I needed to graduate. Unfortunately, it has never been submitted for peer-review and people keep using the database without knowing how to give proper recognition to our work. The draft has been sitting on Oonsie’s desk for literally years waiting for the submit button to be pressed.

To date the database describes 30 generic types of regime shifts and 324 case studies, plus a few experimental cases that if included add up to 35 regime shift types. A generic type is for example the coral reefs transitions from coral dominated reefs to macro-algae or other alternative stable states; while a case study would be the coral transitions in Jamaica. A generic type is a collection of all drivers and mechanisms that can produce a particular regime shift, while a case is an instance of its occurrence. An analogy that often helps me distinguish them is the one of a disease (generic type) and the patient (case). Such was my enthusiasm with this project that out of the 30 regime shifts currently available, 16 were contributed by me during the first year of my PhD. Most case studies were contributed by my friend and colleague Johanna Yletyinen (@jo_yletyinen) who spent a lot of time digitalising the Hypoxia database made available by the study of Diaz and Rosenberg in Science (2008). The rest of the contributions have been developed in the class room with master students or researchers who have been generous to share their work with us by filling up a data template. Roughly 1000 scientific publications have been reviewed to build the database.

Last week writing the synthesis for IPBES made me think that we need better visualisations of the RSDB. I created a map where large dots represent generic types or regime shifts. The are located on the kind of ecosystem where they would be expected to occur. So for example, fisheries collapse is located on the southern ocean close to Antarctica (a place where many fish stocks have been reported on be in decline), but a case study about salmon appears on the other side of the planet in Alaska. Case studies are the small dots on the same colour as their generic types. You can see all the hypoxia cases that Johanna coded especially on the coasts of Europe, North America and Japan. Creating the map brought memories of my days writing regime shifts reviews for the database. It also made me realise that it has been few years I have not contributed besides my teaching duty. Disappointed by the lack of commitment with the paper, my PhD student enthusiasm almost disappeared. The last draft I worked on was on desertification (2014?), it was never reviewed nor published online. Each contribution to the RSDB has been peer reviewed by an expert on the topic to make sure we do a fair assessment of the literature.  Here is the map:RSDB_map.png

Currently I live in the United States, Princeton to be precise. It’s not a secret for anyone who follow the news -or try to avoid them like me- that the political situation here is concerning, to say the least. The kind of situation when you ask yourself what can I do? How do I contribute to make this a better place. Scientist being censored, immigration policies that not only contradict the USadian heritage of immigrants but also remind us of a one of the darkest moments of human history. Whatever I could think of seems insignificant.

Then I looked the map again and tried to remember what was my driver when contributing to RSDB. It was making knowledge free for others to be used, the kind of thing that doesn’t contribute to your career but hopefully is doing some good somewhere. If you come from a place such as the one I come from, you know that scientific knowledge is locked behind paywalls and most of people do not have access to scientific literature. Documenting change in ecosystems and making available to a broader public was important to me. It was like sending wealth to someone else, no on the form of money but knowledge, making sure it’s available when is needed, for free. A lot of people is marching for life and standing up for science. My way of contributing will be by putting dots on the map, making scientific facts count and visible when needed. From now on every week I will contribute a case to RSDB. Let’s make science count. If you want to contribute just drop me a line.

 

 

 

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