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Closing the loop: Reconnecting social-technologial dynamics to Earth System science

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and the and the and year given wallop allow us to adopt don't to not and Dong Yu this a cone leaves the flexion project called on at the Potsdam Institute for Climate Impact region and all information about it he would provide that you introduce a about more information for you yeah it thanks so I'm I'm an elected position that my colleagues in In 2 talks already gave quite a nice introduction to climate change and tandem texts and what can be done about it maybe vegan becoming vegan and and so on so I can I can build on that and talk a bit about the um what we see as as a bit of the front shelf of system modeling and that has some of the key challenges and try to create connections to things that are may be of interest for people here at different places
so well again to to to to emphasize this again this challenge of uh of global warming here from a pile you can perspective so this starts 20 thousand years ago in the late step in the maximum uh of the last glaciation where we had about um for degree cooler climate than today of between 3 and 4 and the members were around there right and then there was the sole warming of about 3 degrees which took 10 thousand years it's actually quite slow then we have there would have thousand years nearly firms often nearly very steady climate that's the holocene the blue curve right that's where human civilization prospered developed humans developed agriculture technologies the industrial revolution took place and then suddenly we this this kink as a very comparably very fast warming there that's the that's the revolution driven by human anthropogenic emissions of greenhouse gasses and land use change mainly and this is all from pile you can the data from ice cores and other sources now these had true data these are measurements and they they confirm the earlier sources here this is this quick warming and and really want to mention that it's not only the amplitude of forming that's important he we have about 1 degree of warming in this in this red curve already compared to these 3 degrees of warming since the maximum of the last ice age but what is also very important the rate of warming you know it's me it's a 100 times faster than the what happened from the last Ice Age to the Holocene designed wouldn't warming 100 times faster and that's actually what creates a lot of problems for adaptation then if we go further into the future this gets even more extreme right this is 1 of the uh and um quite extreme pronounced as emissions in areas which is actually uh where a business-as-usual as usual scenario so that's what that is projected to happen when we just continue with business as usual and and this goes up to 3 degrees all 4 degrees so we've seen that before as well so again a 100 times faster very extreme so what is this doing this is actually
bringing us to a new logically age which has been from the Anthropocene and where social dynamics socio-technological-economic sexually has become a dominant process and system the system is very complex and lots of different processes and acting on global scales onlookers gives region is given different temporal scales but humans have created these these networks which we call also globalization and networks of and information flows in networks of trade networks of resource lots and and it's actually the technological systems these technological networks that have created that if enabled this global warming this these huge greenhouse-gas emissions so this is really a social technological dynamics that this 1 has been driving the so that that's kind of relating to the title but that's the
Anthropocene there some challenges and again this curve here the pile you Clement view on global warming the last 20 thousand years but this also brings the in some more information 1 is the tubing elements in our own is so go tubing elements in the climate system these are the parts of the climate system that have a non-linear response to global warming so they they can't they can't tip like like something that is standing on the set they can is the set threshold is exceeded and this threshold is indicated by this uncertainty ranges staff from yellow to red so um if some ends a lot of them actually lower these thresholds they they cluster in a range between 1 . 5 and the 2 2 degrees this this this uh class of tipping elements possibly switch within the Paris France and these include important but I see on the Earth which could create huge sea level rise but also um it engages in coral reefs and that's actually with the Paris Agreements and temperature range comes from 1 . 5 to 2 degrees has been agreed as limit to global warming and the persistent agreement 2 years ago and so but if you look at this curve that shows that really most of the scenarios the in areas that have been studies they they they would shoot beyond that and they would hit even these upper class of tipping elements which are for example Amazon rainforest boreal forest so high incubation of the oceans and only if you have very nice sustainability transformation this acid the 2 . 6 scenario you might avoid these tipping elements to tip so that that's the picture of of content uh science and sound these
might even attacked that created because skates so this is some from a paper that is just impressive but now
they are now not only gamma changes issue but as many as pointed out and others as well also other sustainability dimensions that humans have had an impact on and they are summarized in the planetary boundaries concept and term just important to mention that not only can the changes a problem that all of these are problem and this different dimensions like biosphere and integrity destruction climate change but also chemical pollution or deforestation they all interacting and they're taking the system away from something that has been put a safe operating space for humanity that people like you involves with Stefan and some the challenge for sustainability transformation is to basically returned to the safe operating space which is the only the state of your system that is known to be a good state for you societies to prosper and sound you
you can then bring the you where the social dimension and ask well for what system states of these planetary boundaries not violated but we are also certain social foundations summits so their basic basic um needs of humans like food water income but also jobs voice gender equality so and this safe and just operating space proposed by Cape Roberts is hypothetical space of system states that allow for these 2 things the mark environmental ceiling and the social foundation to be met at the same time and that's of course uh in
what some people tall called both resilience so the question is in which somewhat of future trajectories of the a system where the assistant and you societies in that are resilient and and and we are currently under this is its future trajectory which takes us out of such resilience state clearly and might to take us even tool hothouse states similar to those with the dinosaurs lived that's why the T. rex was there and earlier slide but then the question is are there actually to the nonlinear social transformations that can maintain the a system in a manageable states in a state of higher resilience so that would be the current that goes down right or other intrinsic feedback center because kids that take the the system up them to such a hot ice-free state and turn it now that the problem is really that current models of global change cannot really answer such questions in in a in a satisfactory d of degree and why this is so I would try to explain and in the next slide so
this and this is the challenge of of funding integrated Earth system modeling that's as true matches colds of computer simulations that then is already talked about and then the the jealous that channel but has has already outlined in a 1999 and even before that and so the the idea is to look at few systematic coevolution space of uh where they environment the dimensions of the by physically climate system but also social dimensions of human societies and you can look at trajectories and off the a system in this space they are there might be catastrophic domains for you don't wanna go with the tubing elements a tipping they are inaccessible demand for you cannot go because they violate for example basic physical laws energy conservation or something like that and then but then there might also be and parts of that space that that are something like a safe operating space in the sense of the planetary boundaries or even a safer just operating space in the sense of the key problems in the sense of the so called off and on and and the challenge for such an integrated whole of system analysis is really to ask for example they even if they even something like a safe operating space in this sense what is the size of it what is the shape what is the resilience of society the states with in this in this space under which conditions does it exist and these are really system questions will you need a complex systems analysis to answer them so you have to run use ensembles of of complex models gifted uncertainty analysis probabilistic things and so on and so forth
and and it even becomes a bit more complex so they are different and dimensions of such an analysis which which are very important and just to to mention them very briefly such new uh such a kind of integrated system analysis we think needs to take into account really on the dimension of human agency so models have to represent agents and and they cannot determine them are called dynamics that emerges from agent behavior for example people making decisions uh sharing information on social networks what macroscopic dynamics emerges from that that might be relevant for example for climate policy and then actually taking these networks into account global what that make up globalization um they taking modeling them explicitly that is there what's where complex networks theory provides a lot of Twitter for doing that that's the 2nd point is representing these networks and now under the microscope and the 3rd point is not really to capture the co-evolution off of nature and societies in these models and to really go beyond what uh just doing optimization take culations like economists often do with was actually good reasons but if you wanna look at resilience if you want to look at these questions like does a safe operating space exist at all you cannot do it was optimization model so another type of models is
needed for doing this type of analysis which we call would us models such models currently don't exist and terms so we are doing some modest efforts and the coupon project them to create such models and and for example again these models should allow to represent social network dynamics of information social tipping point to the actions to address questions like how do actually these climate tipping elements like the green and I should add that the guy should interact with potential social tipping elements what are potential social tipping elements for example opinion formation is known to and has the potential to be a tipping element and climate policy can be a tipping element and divestment movement a social movement on the vessel from fossil fuels can be a tipping element that can be taken cascades in this network and term this is something we have to so we have to talk about and
this is just showing me around the um types of global Change models that are out there that the types of the tool dominant types of models that out there right now also put a system models and integrated assessment models both art there focusing focusing respectively on uh the by physical dimensions of the user-system these other system models they focus on the climate system and 1 day um integrated assessment models that focus mainly on the social metabolic or economic dimensions of the assistance and then these these new types of models that the inventory envisioned should focus on and a process the separate presentation of things going on in the social cultural domain really again what is social cultural this is again open information creation of institutions dynamics of organizations and in such things yeah the term why it why do we
even think that we can do that because it seems to be you you would show a very difficult task and so our we've seen that even though we've come a long way since the limits to growth report 1970 to on uh I mean there have been a lot of developments since then 40 years then past or even more 45 and so it has been a huge progress in computing power since then of course so comprehensive but system modeling is advancing fast already and we can exploit this progress further advances in Complex Systems theory of social-ecological systems modeling social simulation and similar views that allow really computer simulations of certain aspects of social particle dynamics so for example again this opinion formation example we've done a study on how for smokers have been marginalized in social networks in the US through the past 40 years or so and we can do that at least on a qualitative level quite nice and projections of of of social network dynamics and we can understand why certain things are happening the way they are doing and this is actually possible through mostly agent-based modeling approaches where you simulate the dynamics of thousands of simpler agents and study the macro properties that emerge from that for example the fraction of people that have a certain opinion and how it changes over time then there's the point is that big data on social dynamics is increasingly available and terms in if you will in and of course this is valuable for science but you have to be of course very careful about them issues that that can happen when you have too much data like that and in most cases you don't have a that's 1 of our main problems I mean they are the data out there but we cannot get it as scientists and the 4th point is there are emerging research networks that aimed at fostering such In time transdisciplinary research so this is really about integrating natural and social sciences to a degree that is on much closer than has been done in the past and and this is of course very difficult because everyone speak different languages but there are these networks progress is slow but there's some hope and now
this is a bit more concrete on what we are doing in there in the global project we are developing a software framework for which is called quot coupon punk or because of our core activity at the moment so it doesn't really hasn't had a meeting as an acronym sold so far maybe it has at some point and then the hideous really to provide a framework to build such models that has the potential to represent these these different spheres of your system that it talked about before so this this the environmental and the in nature on which we call the by physical taxonomy which some where and then there's this metabolic sphere and the catchphrase here and there and the that different entities in the model so different things that are and M it the thing that is very simple it was easy to understand ourselves so disability good said where uh typically a lot of by physical dynamics are going on but also for example agents individuals which is a different type of entity lives can live in this said them and then there's another type of entity that we highlight here these are social systems he says things like and aggregates and systems of parts of society like a nation state for example or a city that I described more on the on the microscopic level by some every good variables for example at production harvesting where's the capital stocks and so on and so on these different entities of course interacting some are related to each other and they are different modeling approaches like agent-based modelling adaptive networks differential equations the stochastic uh the questions that we can use to model the dynamics of these entities so they are then this is only
and another type of another look at that which is Monican you and a diagram so this shows how all um the different entities in the model are represented by the by classes by objects and and how they are can be related to each other for example an individual can live on its head and or a social system and there are a number of individuals to individuals can belong to social systems and so on and the OK case of for
designed it so we have a reference implementation Tyson itself on its object-oriented so we have we put a lot of effort in in providing a good documentation uh test framework around and tools to allow for comparison relations and all cluster because that's super important and this of course also and all work in progress and in a way because we have relatively low resources for doing that but it's basically made in a way that people can really try a
plug and play and the what together so it's a role-based modularization that allows for different levels of involvement of people so they can be more users that just using models in in a scripting kind of way there can be component developers to develop different parts and uh to represent different types of a system processes for example um and they are can be framework developers the costs were really providing the sourcing and trying to make it more performance for example or to uh ported to a different programming language or something like that we will sit on the top the link is down there but unfortunately and we are not allowed it to put it open source because of all administration but it will be hopefully open-source sperm but he next year and so we we made the we designed this to be very very flexible and modular so we can then connected to other models for example like this land use and and vegetation models that Benny just talked about them and that we try to follow the standards for social science here and to enable people from these different networks but also maybe people earning from from the screen here to to contribute to
this and that this is an example how to because uh script looks like that's on runs the uh that's the model run so this is just an inner city lines of code here because we know it's there this this thing is highly modular and this is just showing how the how simple
this can be actually form of user and term this is this is solved it even more concrete this is illustrated for example model that we um that we put together to to show that this whole thing works and terms so the white white boxes here their model components that the model component developer would and would provide for example the global carbon cycle so this uh that determines how common this and for example diffusing between the atmosphere the ocean how come is going from the earth from the vegetation into the atmosphere for example as this for example the entities involved in this comes psychic component would be the words so the word planets which is 1 entity and then also say it's because of photosynthesis and uh in general biology happens onsets and uh entities are of for example also represented individual social systems are there and then also each of these entities is involved in different processes so just to give 1 example if you look into the Socialists social learning component this is showing how people and imitate each other so it's a very typical human behavior to 2 0 look what your friends are doing and then you want to do it as well as many times and if you think it makes sense and and then the individual has this learning environmentally friendly process that it's that participates and so this is if you see your friend is environmentally friendly maybe you want to be environmentally friendly to and then we put this all
together and then it just gets a bit more complicated again this looks more and more like at the limits to growth models and and EI you can look into the paper for uh for for the dates here but I doubt that we have we have of course some some results here this is just 3 4 and for illustration so that these are not spend the summer predictions of any kind they are not even projections but they're just illustrations of of this space of possibilities of of the system dynamics if you assume or the things that we have assumed right so they are and this is a very legitimate thing that models have to do with where or that we think models are important for us where to explore the space of possibilities to really understand how the the word uh system works and you don't have to do predictions to have a good model and this this and for example we show here and trajectories of the systems in the next 100 years without social processes soul and where for example the environmental friendliness of individuals as fixed where in certain subsidies emission Texas and fossil fuel bands are fixed right so here we have then these things are not changing we put them into the social cultural dimension then they are we at on the social metabolic dimension the economic dimension these are the shares of different energy and sources that the society's use so in this example we have 5 social systems that are running at the same time has 100 individuals and in this example for example you have a strong increase of biomass in the beginning of a later it even later increase of renewable energy sources and the decrease of of some of fossil uh resources which is not very fast and then India system the on the by physical dimension Reese respond accordingly and then uh if you switch the social processes on so these are now really and Peter Kendall social learning so they can learn from and to be environmentally friendly from their peers that can be read the renewables subsidies can be implemented and under certain conditions emissions Texas can be implemented in a fossil fuel that can be implemented basically by a certain voting processes among the individuals so we emulate the democratic decision-making process here and then we see that all these things they are they are switched on quite fast and this leads to a rapid decrease here um all the and fossil energy sources and work faster increase of the renewables compared to 0 and the case without social dynamics right so we get a completely different dynamics which is of course would what you would expect because we change the model to a large degree but this is what this type of modeling is about to really understand what is happening when you make plausible assumptions and now OK
what's the status of this and work core it is already an operational use and is ready for community integration and so we have a description papers submitted actually today and so the open-source lounge of the software is planned for early 2018
now OK to I wanna give to Okabe slides for 4 types of research questions that I would find really interesting or important to look at so early in the context of this conference here so 1 is really to look at more into the competition trade so synergies between these really are the tool may be made the only transformations going on in the 21st century and and where 1 is that the detected reformation it's ongoing rapidly and sends just happening and the other 1 is this necessary maybe we think necessary social ecological sustainability transformation the parts that they can be that they can be competition even between them and for example we've seen that before this large and strongly increasing energy consumption of digital technology so the internet and generous consuming a huge amount of energy than the block chain and the con mining was becoming them is mentioned a lot as an example because bitcoin mining consumes uh the same amount of energy as a small country already and it's just increasing exponentially many at the mall on a more subtle level and the influence of digital communication and online social networks and public opinion formation and governance processes and that may be relevant for so that are relevant for sustainability transformation so this is really the issue was an debate about fake news and a echo chambers and what these things whether they are really there are not is of course have to debate and but this is this is really relevant to study the small so maybe using these types of models and then the last point is things that are that much more false maybe but that people are seriously concerned about like an emerging general artificial intelligence and then asking really what would be the uh system consequences of of such an event and the this system of course but yeah then
maybe a bit even more so and uh philosophical idea but this is interesting debate about it so could take here so this is the and um looking at basically the the complex of the global technological networks and connected to human societies and to what this actually and has to say about sustainability and sound they're Peter half has written a lot about that and we've made a small contribution to that debate and maybe some the tag the set of 1 thing that I talked about might also shed some light on how all human society sexually interrelated with these technological microstructures that we've created and and what this means for the the pop really the viability of sustainable development in the future and also this actually highlight some some the basic questions again about what sustainability actually is and on how work on how this depends on on a basic humanistic principles so that that sustainability is really mostly about humans and so what what is um what what do you do with that concept if it's true that on humans don't really have agency anymore as some people claim likely to have and to some degree right so these are all open questions and know
the take-home messages and computer simulation models the far that our system microscopes and and and the big social-ecological data analytics various tools for understanding of sustainable development in the Anthropocene and we think a new class of were those models is really needed to capture key aspects of this dynamics and and uh uh really 1 central challenge of of the century I think it's really how to reconcile the sustainability in digital transformations and so on yes please contact us maybe
contributes and to lunch the the and thank you use your time plus the lead which means that we have just 2 minutes for 2 questions if there are any please go to the microphone all the Internet I see 1 question you and 1 to have failed so we have 2 questions amazing were really interesting talk thanks a lot and so are I'm working on the 1st system of a monarch community and there we also have we have a tendency to member models more and more complex and more before observed is that as we make the more complex the last we understand that reason that we do less understand what's going on and that seen that a lot of your work you try to do the same right you try to integrate all the processes that you're interested in and then we observe that a lot of judgment which is we know that we have are coming from from the parameters so each time you integrate new um module into Europe injury or model you at some time at some point you you need to parameterize some values you don't know and for us it's been very hard to measure some of 2 quantities and my question would be just a guess for you it's even harder right you what are your parameters and how do you try to estimate and thanks a lot the right so now of course this is the system would always a tennis was modelling and so on they out yeah for example and some some parameters that our um uh typical for these types of social dynamics modeling they are concerning rates for example what is the rate of of imitation uh off of behaviors or opinions between people and compared to the rate of some of the network dynamics or how fast the network changes due to processes like or more for the for example which is the process that you would let you are typically people are more likely to interact with other people that are similar to that um then then with people that are different and and the at the so these these different timescales they can be parameters and of course and you you can address that by doing some but doing simulations was on 1 of parameter space 1 robustness tests and 1 thing that's uh that we do a lot of the coupon project is actually to work to do these and huge agent-based simulations that that I've shown you today but we also do and and conceptual modeling and a careful theoretical work where we try to really on understand what the models are doing in a more simplified way actually most of all work so far has been uh working on various simplified models of such things that that we can still understand mathematically sometimes even derive analytical mathematically approximations and and this works quite well but of course this is this is always a challenge lies that there is 1 question from the internet so I ask you please go after world since people with whom we don't have time because of the next speaker sold Internet what is your question it's some are connected by some care how does the group especially in your scientific community in general validate models and how do you convince people that predictions using this model actually have some validity the but so I am I try to be I try to address securing the talk already about and very briefly I think the 1 thing is that we are on in this social dynamics modeling particularly it's very difficult to do quantitative predictions and that's also why it this what would we try to do more as to as so we validate the monads doing on reproducing qualitatively what's on past developments for example in this study on on the smoking and change in smoking behavior and how people were marginalized in social networks we were able to do that quite well so these types of of and if you can then look at different and properties of a social network at the same time and you see that OK my model can reproduce that change uh the decrease and eigenvector centrality and decreasing clustering and of all the increase of clustering of smokers and they decrease of centrality at the same time and a lot of different parameter settings and this is a good and validation in a quantitative sense for that model and 7 uh and then again I would what would like to highlight that we really don't try to predict the things that we we want to explore the space of possibilities for the the at the bookie OK them the bigger also fall of the dollar and got a loan and landed on you if they've was
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Titel Closing the loop: Reconnecting social-technologial dynamics to Earth System science
Serientitel 34th Chaos Communication Congress
Autor Donges, Jonathan
Lizenz CC-Namensnennung 4.0 International:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen.
DOI 10.5446/34876
Herausgeber Chaos Computer Club e.V.
Erscheinungsjahr 2017
Sprache Englisch

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Fachgebiet Informatik
Abstract International commitment to the appropriately ambitious Paris climate agreement and the United Nations Sustainable Development Goals in 2015 has pulled into the limelight the urgent need for major scientific progress in understanding and modelling the Anthropocene, the tightly intertwined social-techno-ecological planetary system that humanity now inhabits. The Anthropocene qualitatively differs from previous eras in Earth’s history in three key characteristics: (1) There is planetary-scale human agency. (2) There are social and economic networks of teleconnections spanning the globe. (3) It is dominated by planetary-scale social-ecological feedbacks. Bolting together old concepts and methodologies cannot be an adequate approach to describing this new geological era. Instead, we need a new paradigm in Earth System science that is founded equally on a deep understanding of the physical and biological Earth System – and of the economic, technological, social and cultural forces that are now an intrinsic part of it. It is time to close the loop and bring socially mediated dynamics and the technosphere explicitly into theory, analysis and computer models that let us study the whole Earth System.
Schlagwörter Science

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