442 results on '"Donges, Jonathan F."'
Search Results
52. Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package
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Donges, Jonathan F., Heitzig, Jobst, Beronov, Boyan, Wiedermann, Marc, Runge, Jakob, Feng, Qing Yi, Tupikina, Liubov, Stolbova, Veronika, Donner, Reik V., Marwan, Norbert, Dijkstra, Henk A., and Kurths, Jürgen
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Physics - Data Analysis, Statistics and Probability ,Physics - Atmospheric and Oceanic Physics - Abstract
We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. \texttt{pyunicorn} is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, \texttt{pyunicorn} provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology., Comment: 28 pages, 17 figures
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- 2015
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53. Hierarchical structures in Northern Hemispheric extratropical winter ocean-atmosphere interactions
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Wiedermann, Marc, Donges, Jonathan F., Handorf, Dörthe, Kurths, Jürgen, and Donner, Reik V.
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Physics - Atmospheric and Oceanic Physics ,Physics - Data Analysis, Statistics and Probability - Abstract
In recent years extensive studies on the Earth's climate system have been carried out by means of advanced complex network statistics. The great majority of these studies, however, have been focusing on investigating correlation structures within single climatic fields directly on or parallel to the Earth's surface. Here, we develop a novel approach of node weighted coupled network measures to study correlations between ocean and atmosphere in the Northern Hemisphere extratropics and construct 18 coupled climate networks, each consisting of two subnetworks. In all cases, one subnetwork represents monthly sea-surface temperature (SST) anomalies, while the other is based on the monthly geopotential height (HGT) of isobaric surfaces at different pressure levels covering the troposphere as well as the lower stratosphere. The weighted cross-degree density proves to be consistent with the leading coupled pattern obtained from maximum covariance analysis. Network measures of higher order allow for a further analysis of the correlation structure between the two fields and consistently indicate that in the Northern Hemisphere extratropics the ocean is correlated with the atmosphere in a hierarchical fashion such that large areas of the ocean surface correlate with multiple statistically dissimilar regions in the atmosphere. Ultimately we show that, this observed hierarchy is linked to large-scale atmospheric variability patterns, such as the Pacific North American pattern, forcing the ocean on monthly time scales.
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- 2015
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54. Macroscopic description of complex adaptive networks co-evolving with dynamic node states
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Wiedermann, Marc, Donges, Jonathan F., Heitzig, Jobst, Lucht, Wolfgang, and Kurths, Jürgen
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Physics - Physics and Society - Abstract
In many real-world complex systems, the time-evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here, we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the co-evolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we show that in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability play a crucial role for the sustainability of the system's equilibrium state. We derive a macroscopic description of the system which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network and is applicable to many fields of study, such as epidemic spreading or social modeling.
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- 2015
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55. Multi-method evidence for when and how climate-related disasters contribute to armed conflict risk
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Ide, Tobias, Brzoska, Michael, Donges, Jonathan F., and Schleussner, Carl-Friedrich
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- 2020
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56. Human agency in the Anthropocene
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Otto, Ilona M., Wiedermann, Marc, Cremades, Roger, Donges, Jonathan F., Auer, Cornelia, and Lucht, Wolfgang
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- 2020
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57. Tipping points in ocean and atmosphere circulations
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Loriani, Sina, primary, Aksenov, Yevgeny, additional, Armstrong McKay, David, additional, Bala, Govindasamy, additional, Born, Andreas, additional, Chiessi, Cristiano M., additional, Dijkstra, Henk, additional, Donges, Jonathan F., additional, Drijfhout, Sybren, additional, England, Matthew H., additional, Fedorov, Alexey V., additional, Jackson, Laura, additional, Kornhuber, Kai, additional, Messori, Gabriele, additional, Pausata, Francesco, additional, Rynders, Stefanie, additional, Salée, Jean-Baptiste, additional, Sinha, Bablu, additional, Sherwood, Steven, additional, Swingedouw, Didier, additional, and Tharammal, Thejna, additional
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- 2023
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58. Supplementary material to "Tipping points in ocean and atmosphere circulations"
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Loriani, Sina, primary, Aksenov, Yevgeny, additional, Armstrong McKay, David, additional, Bala, Govindasamy, additional, Born, Andreas, additional, Chiessi, Cristiano M., additional, Dijkstra, Henk, additional, Donges, Jonathan F., additional, Drijfhout, Sybren, additional, England, Matthew H., additional, Fedorov, Alexey V., additional, Jackson, Laura, additional, Kornhuber, Kai, additional, Messori, Gabriele, additional, Pausata, Francesco, additional, Rynders, Stefanie, additional, Salée, Jean-Baptiste, additional, Sinha, Bablu, additional, Sherwood, Steven, additional, Swingedouw, Didier, additional, and Tharammal, Thejna, additional
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- 2023
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59. Evolution of the polycrisis: Anthropocene traps that challenge global sustainability
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Søgaard Jørgensen, Peter, primary, Jansen, Raf E. V., additional, Avila Ortega, Daniel I., additional, Wang-Erlandsson, Lan, additional, Donges, Jonathan F., additional, Österblom, Henrik, additional, Olsson, Per, additional, Nyström, Magnus, additional, Lade, Steven J., additional, Hahn, Thomas, additional, Folke, Carl, additional, Peterson, Garry D., additional, and Crépin, Anne-Sophie, additional
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- 2023
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60. Disentangling different types of El Ni\~no episodes by evolving climate network analysis
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Radebach, Alexander, Donner, Reik V., Runge, Jakob, Donges, Jonathan F., and Kurths, Jürgen
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Physics - Data Analysis, Statistics and Probability ,Physics - Atmospheric and Oceanic Physics - Abstract
Complex network theory provides a powerful toolbox for studying the structure of statistical interrelationships between multiple time series in various scientific disciplines. In this work, we apply the recently proposed climate network approach for characterizing the evolving correlation structure of the Earth's climate system based on reanalysis data of surface air temperatures. We provide a detailed study on the temporal variability of several global climate network characteristics. Based on a simple conceptual view on red climate networks (i.e., networks with a comparably low number of edges), we give a thorough interpretation of our evolving climate network characteristics, which allows a functional discrimination between recently recognized different types of El Ni\~no episodes. Our analysis provides deep insights into the Earth's climate system, particularly its global response to strong volcanic eruptions and large-scale impacts of different phases of the El Ni\~no Southern Oscillation (ENSO)., Comment: 20 pages, 12 figures
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- 2013
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61. The hysteresis of the Antarctic Ice Sheet
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Garbe, Julius, Albrecht, Torsten, Levermann, Anders, Donges, Jonathan F., and Winkelmann, Ricarda
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Hysteresis -- Analysis ,Surface-ice melting -- Forecasts and trends ,Global warming -- Environmental aspects ,Ice sheets -- Properties -- Models ,Market trend/market analysis ,Environmental issues ,Science and technology ,Zoology and wildlife conservation - Abstract
More than half of Earth's freshwater resources are held by the Antarctic Ice Sheet, which thus represents by far the largest potential source for global sea-level rise under future warming conditions.sup.1. Its long-term stability determines the fate of our coastal cities and cultural heritage. Feedbacks between ice, atmosphere, ocean, and the solid Earth give rise to potential nonlinearities in its response to temperature changes. So far, we are lacking a comprehensive stability analysis of the Antarctic Ice Sheet for different amounts of global warming. Here we show that the Antarctic Ice Sheet exhibits a multitude of temperature thresholds beyond which ice loss is irreversible. Consistent with palaeodata.sup.2 we find, using the Parallel Ice Sheet Model.sup.3-5, that at global warming levels around 2 degrees Celsius above pre-industrial levels, West Antarctica is committed to long-term partial collapse owing to the marine ice-sheet instability. Between 6 and 9 degrees of warming above pre-industrial levels, the loss of more than 70 per cent of the present-day ice volume is triggered, mainly caused by the surface elevation feedback. At more than 10 degrees of warming above pre-industrial levels, Antarctica is committed to become virtually ice-free. The ice sheet's temperature sensitivity is 1.3 metres of sea-level equivalent per degree of warming up to 2 degrees above pre-industrial levels, almost doubling to 2.4 metres per degree of warming between 2 and 6 degrees and increasing to about 10 metres per degree of warming between 6 and 9 degrees. Each of these thresholds gives rise to hysteresis behaviour: that is, the currently observed ice-sheet configuration is not regained even if temperatures are reversed to present-day levels. In particular, the West Antarctic Ice Sheet does not regrow to its modern extent until temperatures are at least one degree Celsius lower than pre-industrial levels. Our results show that if the Paris Agreement is not met, Antarctica's long-term sea-level contribution will dramatically increase and exceed that of all other sources. Modelling shows that the Antarctic Ice Sheet exhibits multiple temperature thresholds beyond which ice loss would become irreversible, and once melted, the ice sheet can regain its previous mass only if the climate cools well below pre-industrial temperatures., Author(s): Julius Garbe [sup.1] [sup.2] , Torsten Albrecht [sup.1] , Anders Levermann [sup.1] [sup.2] [sup.3] , Jonathan F. Donges [sup.1] [sup.4] , Ricarda Winkelmann [sup.1] [sup.2] Author Affiliations: (1) Potsdam [...]
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- 2020
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62. Human impacts on planetary boundaries amplified by Earth system interactions
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Lade, Steven J., Steffen, Will, de Vries, Wim, Carpenter, Stephen R., Donges, Jonathan F., Gerten, Dieter, Hoff, Holger, Newbold, Tim, Richardson, Katherine, and Rockström, Johan
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- 2020
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63. Amplified Rossby waves enhance risk of concurrent heatwaves in major breadbasket regions
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Kornhuber, Kai, Coumou, Dim, Vogel, Elisabeth, Lesk, Corey, Donges, Jonathan F., Lehmann, Jascha, and Horton, Radley M.
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- 2020
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64. How complex climate networks complement eigen techniques for the statistical analysis of climatological data
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Donges, Jonathan F., Petrova, Irina, Loew, Alexander, Marwan, Norbert, and Kurths, Jürgen
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Physics - Data Analysis, Statistics and Probability ,Physics - Atmospheric and Oceanic Physics ,Statistics - Methodology - Abstract
Eigen techniques such as empirical orthogonal function (EOF) or coupled pattern (CP) / maximum covariance analysis have been frequently used for detecting patterns in multivariate climatological data sets. Recently, statistical methods originating from the theory of complex networks have been employed for the very same purpose of spatio-temporal analysis. This climate network (CN) analysis is usually based on the same set of similarity matrices as is used in classical EOF or CP analysis, e.g., the correlation matrix of a single climatological field or the cross-correlation matrix between two distinct climatological fields. In this study, formal relationships as well as conceptual differences between both eigen and network approaches are derived and illustrated using exemplary global precipitation, evaporation and surface air temperature data sets. These results allow to pinpoint that CN analysis can complement classical eigen techniques and provides additional information on the higher-order structure of statistical interrelationships in climatological data. Hence, CNs are a valuable supplement to the statistical toolbox of the climatologist, particularly for making sense out of very large data sets such as those generated by satellite observations and climate model intercomparison exercises., Comment: 18 pages, 11 figures
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- 2013
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65. Geometric detection of coupling directions by means of inter-system recurrence networks
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Feldhoff, Jan H., Donner, Reik V., Donges, Jonathan F., Marwan, N., and Kurths, J.
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Physics - Data Analysis, Statistics and Probability ,Nonlinear Sciences - Chaotic Dynamics - Abstract
We introduce a geometric method for identifying the coupling direction between two dynamical systems based on a bivariate extension of recurrence network analysis. Global characteristics of the resulting inter-system recurrence networks provide a correct discrimination for weakly coupled R\"ossler oscillators not yet displaying generalised synchronisation. Investigating two real-world palaeoclimate time series representing the variability of the Asian monsoon over the last 10,000 years, we observe indications for a considerable influence of the Indian summer monsoon on climate in Eastern China rather than vice versa. The proposed approach can be directly extended to studying $K>2$ coupled subsystems., Comment: 13 pages, 10 figures, 2 tables
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- 2013
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66. Node-weighted interacting network measures improve the representation of real-world complex systems
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Wiedermann, Marc, Donges, Jonathan F., Heitzig, Jobst, and Kurths, Jürgen
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Physics - Physics and Society ,Computer Science - Social and Information Networks ,Physics - Data Analysis, Statistics and Probability - Abstract
Network theory provides a rich toolbox consisting of methods, measures, and models for studying the structure and dynamics of complex systems found in nature, society, or technology. Recently, it has been pointed out that many real-world complex systems are more adequately mapped by networks of interacting or interdependent networks, e.g., a power grid showing interdependency with a communication network. Additionally, in many real-world situations it is reasonable to include node weights into complex network statistics to reflect the varying size or importance of subsystems that are represented by nodes in the network of interest. E.g., nodes can represent vastly different surface area in climate networks, volume in brain networks or economic capacity in trade networks. In this letter, combining both ideas, we derive a novel class of statistical measures for analysing the structure of networks of interacting networks with heterogeneous node weights. Using a prototypical spatial network model, we show that the newly introduced node-weighted interacting network measures indeed provide an improved representation of the underlying system's properties as compared to their unweighted analogues. We apply our method to study the complex network structure of cross-boundary trade between European Union (EU) and non-EU countries finding that it provides important information on trade balance and economic robustness., Comment: 7 pages, 5 figures
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- 2013
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67. Geometric signature of complex synchronisation scenarios
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Feldhoff, Jan F., Donner, Reik V., Donges, Jonathan F., Marwan, Norbert, and Kurths, Jürgen
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Nonlinear Sciences - Chaotic Dynamics ,Physics - Data Analysis, Statistics and Probability - Abstract
Synchronisation between coupled oscillatory systems is a common phenomenon in many natural as well as technical systems. Varying the strength of coupling often leads to qualitative changes in the complex dynamics of the mutually coupled systems including different types of synchronisation such as phase, lag, generalised, or even complete synchronisation. Here, we study the geometric signatures of coupling along with the onset of generalised synchronisation between two coupled chaotic oscillators by mapping the systems' individual as well as joint recurrences in phase space to a complex network. For a paradigmatic continuous-time model system, the transitivity properties of the resulting joint recurrence networks display distinct variations associated with changes in the structural similarity between different parts of the considered trajectories. They therefore provide a useful indicator for the emergence of generalised synchronisation. This paper is dedicated to the 25th anniversary of the introduction of recurrence plots by Eckmann et al. (Europhys. Lett. 4 (1987), 973)., Comment: 7 pages, 3 figures
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- 2013
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68. Testing time series irreversibility using complex network methods
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Donges, Jonathan F., Donner, Reik V., and Kurths, Jürgen
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Physics - Data Analysis, Statistics and Probability ,Nonlinear Sciences - Chaotic Dynamics ,Physics - Medical Physics - Abstract
The absence of time-reversal symmetry is a fundamental property of many nonlinear time series. Here, we propose a new set of statistical tests for time series irreversibility based on standard and horizontal visibility graphs. Specifically, we statistically compare the distributions of time-directed variants of the common complex network measures degree and local clustering coefficient. Our approach does not involve surrogate data and is applicable to relatively short time series. We demonstrate its performance for paradigmatic model systems with known time-reversal properties as well as for picking up signatures of nonlinearity in neuro-physiological data., Comment: 6 pages, 5 figures
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- 2012
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69. Can Intensification of Cattle Ranching Reduce Deforestation in the Amazon? Insights From an Agent-based Social-Ecological Model
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Müller-Hansen, Finn, Heitzig, Jobst, Donges, Jonathan F., Cardoso, Manoel F., Dalla-Nora, Eloi L., Andrade, Pedro, Kurths, Jürgen, and Thonicke, Kirsten
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- 2019
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70. Complex network approaches to nonlinear time series analysis
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Zou, Yong, Donner, Reik V., Marwan, Norbert, Donges, Jonathan F., and Kurths, Jürgen
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- 2019
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71. Analytical framework for recurrence-network analysis of time series
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Donges, Jonathan F., Heitzig, Jobst, Donner, Reik V., and Kurths, Jürgen
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Physics - Data Analysis, Statistics and Probability ,Nonlinear Sciences - Chaotic Dynamics - Abstract
Recurrence networks are a powerful nonlinear tool for time series analysis of complex dynamical systems. {While there are already many successful applications ranging from medicine to paleoclimatology, a solid theoretical foundation of the method has still been missing so far. Here, we interpret an $\varepsilon$-recurrence network as a discrete subnetwork of a "continuous" graph with uncountably many vertices and edges corresponding to the system's attractor. This step allows us to show that various statistical measures commonly used in complex network analysis can be seen as discrete estimators of newly defined continuous measures of certain complex geometric properties of the attractor on the scale given by $\varepsilon$.} In particular, we introduce local measures such as the $\varepsilon$-clustering coefficient, mesoscopic measures such as $\varepsilon$-motif density, path-based measures such as $\varepsilon$-betweennesses, and global measures such as $\varepsilon$-efficiency. This new analytical basis for the so far heuristically motivated network measures also provides an objective criterion for the choice of $\varepsilon$ via a percolation threshold, and it shows that estimation can be improved by so-called node splitting invariant versions of the measures. We finally illustrate the framework for a number of archetypical chaotic attractors such as those of the Bernoulli and logistic maps, periodic and two-dimensional quasi-periodic motions, and for hyperballs and hypercubes, by deriving analytical expressions for the novel measures and comparing them with data from numerical experiments. More generally, the theoretical framework put forward in this work describes random geometric graphs and other networks with spatial constraints which appear frequently in disciplines ranging from biology to climate science.
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- 2012
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72. Investigating the topology of interacting networks - Theory and application to coupled climate subnetworks
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Donges, Jonathan F., Schultz, Hanna C. H., Marwan, Norbert, Zou, Yong, and Kurths, Juergen
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Physics - Data Analysis, Statistics and Probability ,Computer Science - Social and Information Networks ,Physics - Atmospheric and Oceanic Physics ,Physics - Physics and Society - Abstract
Network theory provides various tools for investigating the structural or functional topology of many complex systems found in nature, technology and society. Nevertheless, it has recently been realised that a considerable number of systems of interest should be treated, more appropriately, as interacting networks or networks of networks. Here we introduce a novel graph-theoretical framework for studying the interaction structure between subnetworks embedded within a complex network of networks. This framework allows us to quantify the structural role of single vertices or whole subnetworks with respect to the interaction of a pair of subnetworks on local, mesoscopic and global topological scales. Climate networks have recently been shown to be a powerful tool for the analysis of climatological data. Applying the general framework for studying interacting networks, we introduce coupled climate subnetworks to represent and investigate the topology of statistical relationships between the fields of distinct climatological variables. Using coupled climate subnetworks to investigate the terrestrial atmosphere's three-dimensional geopotential height field uncovers known as well as interesting novel features of the atmosphere's vertical stratification and general circulation. Specifically, the new measure "cross-betweenness" identifies regions which are particularly important for mediating vertical wind field interactions. The promising results obtained by following the coupled climate subnetwork approach present a first step towards an improved understanding of the Earth system and its complex interacting components from a network perspective.
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- 2011
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73. The Geometry of Chaotic Dynamics -- A Complex Network Perspective
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Donner, Reik V., Heitzig, Jobst, Donges, Jonathan F., Zou, Yong, Marwan, Norbert, and Kurths, Jürgen
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Nonlinear Sciences - Chaotic Dynamics - Abstract
Recently, several complex network approaches to time series analysis have been developed and applied to study a wide range of model systems as well as real-world data, e.g., geophysical or financial time series. Among these techniques, recurrence-based concepts and prominently $\epsilon$-recurrence networks, most faithfully represent the geometrical fine structure of the attractors underlying chaotic (and less interestingly non-chaotic) time series. In this paper we demonstrate that the well known graph theoretical properties local clustering coefficient and global (network) transitivity can meaningfully be exploited to define two new local and two new global measures of dimension in phase space: local upper and lower clustering dimension as well as global upper and lower transitivity dimension. Rigorous analytical as well as numerical results for self-similar sets and simple chaotic model systems suggest that these measures are well-behaved in most non-pathological situations and that they can be estimated reasonably well using $\epsilon$-recurrence networks constructed from relatively short time series. Moreover, we study the relationship between clustering and transitivity dimensions on the one hand, and traditional measures like pointwise dimension or local Lyapunov dimension on the other hand. We also provide further evidence that the local clustering coefficients, or equivalently the local clustering dimensions, are useful for identifying unstable periodic orbits and other dynamically invariant objects from time series. Our results demonstrate that $\epsilon$-recurrence networks exhibit an important link between dynamical systems and graph theory., Comment: 21 pages, 12 figures
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- 2011
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74. Node-weighted measures for complex networks with spatially embedded, sampled, or differently sized nodes
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Heitzig, Jobst, Donges, Jonathan F., Zou, Yong, Marwan, Norbert, and Kurths, Jürgen
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Physics - Data Analysis, Statistics and Probability ,Condensed Matter - Disordered Systems and Neural Networks ,Condensed Matter - Statistical Mechanics ,05C82, 05C81, 05C75, 90B15, 91D30 ,G.2.2 ,F.2.2 ,G.3 - Abstract
When network and graph theory are used in the study of complex systems, a typically finite set of nodes of the network under consideration is frequently either explicitly or implicitly considered representative of a much larger finite or infinite region or set of objects of interest. The selection procedure, e.g., formation of a subset or some kind of discretization or aggregation, typically results in individual nodes of the studied network representing quite differently sized parts of the domain of interest. This heterogeneity may induce substantial bias and artifacts in derived network statistics. To avoid this bias, we propose an axiomatic scheme based on the idea of node splitting invariance to derive consistently weighted variants of various commonly used statistical network measures. The practical relevance and applicability of our approach is demonstrated for a number of example networks from different fields of research, and is shown to be of fundamental importance in particular in the study of spatially embedded functional networks derived from time series as studied in, e.g., neuroscience and climatology., Comment: 21 pages, 13 figures
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- 2011
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75. Identifying complex periodic windows in continuous-time dynamical systems using recurrence-based methods
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Zou, Yong, Donner, Reik V., Donges, Jonathan F., Marwan, Norbert, and Kurths, Jürgen
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Nonlinear Sciences - Chaotic Dynamics - Abstract
The identification of complex periodic windows in the two-dimensional parameter space of certain dynamical systems has recently attracted considerable interest. While for discrete systems, a discrimination between periodic and chaotic windows can be easily made based on the maximum Lyapunov exponent of the system, this remains a challenging task for continuous systems, especially if only short time series are available (e.g., in case of experimental data). In this work, we demonstrate that nonlinear measures based on recurrence plots obtained from such trajectories provide a practicable alternative for numerically detecting shrimps. Traditional diagonal line-based measures of recurrence quantification analysis (RQA) as well as measures from complex network theory are shown to allow an excellent classification of periodic and chaotic behavior in parameter space. Using the well-studied R\"ossler system as a benchmark example, we find that the average path length and the clustering coefficient of the resulting recurrence networks (RNs) are particularly powerful discriminatory statistics for the identification of complex periodic windows.
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- 2010
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76. Recurrence-based time series analysis by means of complex network methods
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Donner, Reik V., Small, Michael, Donges, Jonathan F., Marwan, Norbert, Zou, Yong, Xiang, Ruoxi, and Kurths, Jürgen
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Nonlinear Sciences - Chaotic Dynamics ,Computer Science - Social and Information Networks ,Physics - Data Analysis, Statistics and Probability ,Physics - Physics and Society - Abstract
Complex networks are an important paradigm of modern complex systems sciences which allows quantitatively assessing the structural properties of systems composed of different interacting entities. During the last years, intensive efforts have been spent on applying network-based concepts also for the analysis of dynamically relevant higher-order statistical properties of time series. Notably, many corresponding approaches are closely related with the concept of recurrence in phase space. In this paper, we review recent methodological advances in time series analysis based on complex networks, with a special emphasis on methods founded on recurrence plots. The potentials and limitations of the individual methods are discussed and illustrated for paradigmatic examples of dynamical systems as well as for real-world time series. Complex network measures are shown to provide information about structural features of dynamical systems that are complementary to those characterized by other methods of time series analysis and, hence, substantially enrich the knowledge gathered from other existing (linear as well as nonlinear) approaches., Comment: To be published in International Journal of Bifurcation and Chaos (2011)
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- 2010
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77. The backbone of the climate network
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Donges, Jonathan F., Zou, Yong, Marwan, Norbert, and Kurths, Juergen
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Physics - Atmospheric and Oceanic Physics ,Physics - Data Analysis, Statistics and Probability - Abstract
We propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system, relying on the nonlinear mutual information of time series analysis and betweenness centrality of complex network theory. We show, that this approach reveals a rich internal structure in complex climate networks constructed from reanalysis and model surface air temperature data. Our novel method uncovers peculiar wave-like structures of high energy flow, that we relate to global surface ocean currents. This points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). We find that these results cannot be obtained using classical linear methods of multivariate data analysis, and have ensured their robustness by intensive significance testing., Comment: 6 pages, 5 figures
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- 2010
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78. Ambiguities in recurrence-based complex network representations of time series
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Donner, Reik V., Zou, Yong, Donges, Jonathan F., Marwan, Norbert, and Kurths, Juergen
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Nonlinear Sciences - Chaotic Dynamics - Abstract
Recently, different approaches have been proposed for studying basic properties of time series from a complex network perspective. In this work, the corresponding potentials and limitations of networks based on recurrences in phase space are investigated in some detail. We discuss the main requirements that permit a feasible system-theoretic interpretation of network topology in terms of dynamically invariant phase-space properties. Possible artifacts induced by disregarding these requirements are pointed out and systematically studied. Finally, a rigorous interpretation of the clustering coefficient and the betweenness centrality in terms of invariant objects is proposed.
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- 2010
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79. Recurrence networks - A novel paradigm for nonlinear time series analysis
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Donner, Reik V., Zou, Y., Donges, Jonathan F., Marwan, Norbert, and Kurths, Juergen
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Nonlinear Sciences - Chaotic Dynamics - Abstract
This paper presents a new approach for analysing structural properties of time series from complex systems. Starting from the concept of recurrences in phase space, the recurrence matrix of a time series is interpreted as the adjacency matrix of an associated complex network which links different points in time if the evolution of the considered states is very similar. A critical comparison of these recurrence networks with similar existing techniques is presented, revealing strong conceptual benefits of the new approach which can be considered as a unifying framework for transforming time series into complex networks that also includes other methods as special cases. It is demonstrated that there are fundamental relationships between the topological properties of recurrence networks and the statistical properties of the phase space density of the underlying dynamical system. Hence, the network description yields new quantitative characteristics of the dynamical complexity of a time series, which substantially complement existing measures of recurrence quantification analysis.
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- 2009
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80. Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods
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Donges, Jonathan F., Zou, Yong, Marwan, Norbert, and Kurths, Jürgen
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Physics - Data Analysis, Statistics and Probability ,Physics - Atmospheric and Oceanic Physics - Abstract
Complex network theory provides a powerful framework to statistically investigate the topology of local and non-local statistical interrelationships, i.e. teleconnections, in the climate system. Climate networks constructed from the same global climatological data set using the linear Pearson correlation coefficient or the nonlinear mutual information as a measure of dynamical similarity between regions, are compared systematically on local, mesoscopic and global topological scales. A high degree of similarity is observed on the local and mesoscopic topological scales for surface air temperature fields taken from AOGCM and reanalysis data sets. We find larger differences on the global scale, particularly in the betweenness centrality field. The global scale view on climate networks obtained using mutual information offers promising new perspectives for detecting network structures based on nonlinear physical processes in the climate system., Comment: 24 pages, 10 figures
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- 2009
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81. Evolution of the polycrisis: Anthropocene traps that challenge global sustainability.
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Søgaard Jørgensen, Peter, Jansen, Raf E. V., Avila Ortega, Daniel I., Wang-Erlandsson, Lan, Donges, Jonathan F., Österblom, Henrik, Olsson, Per, Nyström, Magnus, Lade, Steven J., Hahn, Thomas, Folke, Carl, Peterson, Garry D., and Crépin, Anne-Sophie
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SUSTAINABILITY ,WELL-being ,SOCIAL evolution ,ANIMAL navigation ,CONCEPT mapping - Abstract
The Anthropocene is characterized by accelerating change and global challenges of increasing complexity. Inspired by what some have called a polycrisis, we explore whether the human trajectory of increasing complexity and influence on the Earth system could become a form of trap for humanity. Based on an adaptation of the evolutionary traps concept to a global human context, we present results from a participatory mapping. We identify 14 traps and categorize them as either global, technology or structural traps. An assessment reveals that 12 traps (86%) could be in an advanced phase of trapping with high risk of hard-to-reverse lock-ins and growing risks of negative impacts on human well-being. Ten traps (71%) currently see growing trends in their indicators. Revealing the systemic nature of the polycrisis, we assess that Anthropocene traps often interact reinforcingly (45% of pairwise interactions), and rarely in a dampening fashion (3%). We end by discussing capacities that will be important for navigating these systemic challenges in pursuit of global sustainability. Doing so, we introduce evolvability as a unifying concept for such research between the sustainability and evolutionary sciences. This article is part of the theme issue 'Evolution and sustainability: gathering the strands for an Anthropocene synthesis'. [ABSTRACT FROM AUTHOR]
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- 2024
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82. Earth beyond six of nine planetary boundaries
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Richardson, Katherine, primary, Steffen, Will, additional, Lucht, Wolfgang, additional, Bendtsen, Jørgen, additional, Cornell, Sarah E., additional, Donges, Jonathan F., additional, Drüke, Markus, additional, Fetzer, Ingo, additional, Bala, Govindasamy, additional, von Bloh, Werner, additional, Feulner, Georg, additional, Fiedler, Stephanie, additional, Gerten, Dieter, additional, Gleeson, Tom, additional, Hofmann, Matthias, additional, Huiskamp, Willem, additional, Kummu, Matti, additional, Mohan, Chinchu, additional, Nogués-Bravo, David, additional, Petri, Stefan, additional, Porkka, Miina, additional, Rahmstorf, Stefan, additional, Schaphoff, Sibyll, additional, Thonicke, Kirsten, additional, Tobian, Arne, additional, Virkki, Vili, additional, Wang-Erlandsson, Lan, additional, Weber, Lisa, additional, and Rockström, Johan, additional
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- 2023
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83. Negative Social Tipping Dynamics Resulting from and Reinforcing Earth System Destabilisation
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Spaiser, Viktoria, primary, Juhola, Sirkku, additional, Constantino, Sara M., additional, Guo, Weisi, additional, Watson, Tabitha, additional, Sillmann, Jana, additional, Craparo, Alessandro, additional, Basel, Ashleigh, additional, Bruun, John T., additional, Krishnamurthy, Krishna, additional, Scheffran, Jürgen, additional, Pinho, Patricia, additional, Okpara, Uche T., additional, Donges, Jonathan F., additional, Bhowmik, Avit, additional, Yasseri, Taha, additional, Safra de Campos, Ricardo, additional, Cumming, Graeme S., additional, Chenet, Hugues, additional, Krampe, Florian, additional, and Abrams, Jesse F., additional
- Published
- 2023
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84. Climate tipping point interactions and cascades: A review
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Wunderling, Nico, primary, von der Heydt, Anna, additional, Aksenov, Yevgeny, additional, Barker, Stephen, additional, Bastiaansen, Robbin, additional, Brovkin, Victor, additional, Brunetti, Maura, additional, Couplet, Victor, additional, Kleinen, Thomas, additional, Lear, Caroline H., additional, Lohmann, Johannes, additional, Roman-Cuesta, Rosa Maria, additional, Sinet, Sacha, additional, Swingedouw, Didier, additional, Winkelmann, Ricarda, additional, Anand, Pallavi, additional, Barichivich, Jonathan, additional, Bathiany, Sebastian, additional, Baudena, Mara, additional, Bruun, John T., additional, Chiessi, Christiano M., additional, Coxall, Helen K., additional, Docquier, David, additional, Donges, Jonathan F., additional, Falkena, Swinda K. J., additional, Klose, Ann Kristin, additional, Obura, David, additional, Rocha, Juan, additional, Rynders, Stefanie, additional, Steinert, Norman Julius, additional, and Willeit, Matteo, additional
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- 2023
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85. A global social activation model of enabling conditions for positive social tipping – the role of sea-level rise anticipation and climate change concern
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Smith, E. Keith, primary, Wiedermann, Marc, additional, Donges, Jonathan F., additional, Heitzig, Jobst, additional, and Winkelmann, Ricarda, additional
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- 2023
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86. Trajectories of the Earth System in the Anthropocene
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Steffen, Will, Rockström, Johan, Richardson, Katherine, Lentond, Timothy M., Folke, Carl, Liverman, Diana, Summerhayes, Colin P., Barnosky, Anthony D., Cornell, Sarah E., Crucifix, Michel, Donges, Jonathan F., Fetzer, Ingo, Lade, Steven J., Scheffer, Marten, Winkelmann, Ricarda, and Schellnhuber, Hans Joachim
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- 2018
87. A network-based microfoundation of Granovetter’s threshold model for social tipping
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Wiedermann, Marc, Smith, E. Keith, Heitzig, Jobst, and Donges, Jonathan F.
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- 2020
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88. Global warming due to loss of large ice masses and Arctic summer sea ice
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Wunderling, Nico, Willeit, Matteo, Donges, Jonathan F., and Winkelmann, Ricarda
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- 2020
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89. Resilience basins of complex systems: An application to prosumer impacts on power grids
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Bien, Samuel, primary, Schultz, Paul, additional, Heitzig, Jobst, additional, and Donges, Jonathan F., additional
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- 2023
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90. Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest
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Wunderling, Nico, primary, Staal, Arie, additional, Wolf, Frederik, additional, Sakschewski, Boris, additional, Hirota, Marina, additional, Tuinenburg, Obbe A., additional, Donges, Jonathan F., additional, Barbosa, Henrique M.J., additional, and Winkelmann, Ricarda, additional
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- 2023
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91. Coherent response of the Indian Monsoon Rainfall to Atlantic Multi-decadal Variability over the last 2000 years
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Naidu, Pothuri Divakar, Ganeshram, Raja, Bollasina, Massimo A., Panmei, Champoungam, Nürnberg, Dirk, and Donges, Jonathan F.
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- 2020
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92. Tipping points in ocean and atmosphere circulations.
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Loriani, Sina, Aksenov, Yevgeny, McKay, David Armstrong, Bala, Govindasamy, Born, Andreas, Chiessi, Cristiano M., Dijkstra, Henk, Donges, Jonathan F., Drijfhout, Sybren, England, Matthew H., Fedorov, Alexey V., Jackson, Laura, Kornhuber, Kai, Messori, Gabriele, Pausata, Francesco, Rynders, Stefanie, Salée, Jean-Baptiste, Sinha, Bablu, Sherwood, Steven, and Swingedouw, Didier
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OCEAN circulation ,ATLANTIC meridional overturning circulation ,EL Nino ,ATMOSPHERIC circulation ,OCEAN ,ICE shelves ,MONSOONS ,AIR pollution - Abstract
In this review, we assess scientific evidence for tipping points in ocean and atmosphere circulations. The warming of oceans, modified wind patterns and increasing freshwater influx from melting ice hold the potential to disrupt established circulation patterns. The literature provides evidence for oceanic tipping points in the Atlantic Meridional Overturning Circulation (AMOC), the North Atlantic Subpolar Gyre (SPG), and the Antarctic Overturning Circulation, which may collapse under warmer and 'fresher' (i.e. less salty) conditions. A slowdown or collapse of these oceanic circulations would have far-reaching consequences for the rest of the climate system and could lead to strong impacts on human societies and the biosphere. Among the atmospheric circulation systems considered, we classify the West African monsoon as a tipping system. Its abrupt changes in the past have led to vastly different vegetation states of the Sahara (e.g. "green Sahara" states). Evidence about tipping of the monsoon systems over South America and Asia is limited however, there are multiple potential sources of destabilisation, including large-scale deforestation, air pollution, and shifts in other circulation patterns (in particular the AMOC). Although theoretically possible, there is currently little indication for tipping points in tropical clouds or mid-latitude atmospheric circulations. Similarly, tipping towards a more extreme or persistent state of the El Niño-Southern Oscillation (ENSO) is currently not fully supported by models and observations. While the tipping thresholds for many of these systems are uncertain, tipping could have severe socio-environmental consequences. Stabilising Earth's climate (along with minimising other environmental pressures, like aerosol pollution and ecosystem degradation) is critical for reducing the likelihood of reaching tipping points in the ocean-atmosphere system. [ABSTRACT FROM AUTHOR]
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- 2023
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93. The Pareto effect in tipping social networks: from minority to majority.
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Everall, Jordan Paul, Donges, Jonathan F., and Otto, Ilona M.
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SOCIAL networks ,CONTAGION (Social psychology) ,LITERATURE reviews ,SOCIAL systems ,SOCIAL norms - Abstract
How do social networks tip? A popular theory is that a small minority can affect network, or population wide change. This effect is roughly consistent with the properties of the Pareto principle, a semi-quantitative law which suggests that in many systems, 80 % of effects are produced by only 20 % of the causes. In the context of the transition to net-zero emissions, this vital 20 % can be a critical instigator of social tipping, a process which can rapidly accelerate social norm change. In this work, we ask whether the Pareto effect can be observed in social systems by conducting a literature review with a focus on social norm diffusion and complex contagion on social networks. By collecting simulation and empirical results of social tipping events over a wide disciplinary, and parametric space, we are able to see the existence of shared behaviour across studies. Based on a compiled dataset, we show general support for the existence of a tipping point which occurs at around 25 % of the total population in susceptible social systems. Around this critical mass, there is a high likelihood of a social tipping event, where a large minority is then quickly "tipped". Additionally, we were able to show a range of critical masses where social tipping is possible, these values lie roughly between 10 % and 45 %. Finally, we also provide practical advice for facilitating norm changes under uncertainty, difficult social norm transitions, and social groups resistant to change. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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94. Complex Network Analysis of Recurrences
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Donner, Reik V., Donges, Jonathan F., Zou, Yong, Feldhoff, Jan H., Abarbanel, Henry, Series editor, Braha, Dan, Series editor, Érdi, Péter, Series editor, Friston, Karl, Series editor, Haken, Hermann, Series editor, Jirsa, Viktor, Series editor, Kacprzyk, Janusz, Series editor, Kaneko, Kunihiko, Series editor, Kelso, Scott, Series editor, Kirkilionis, Markus, Series editor, Kurths, Jürgen, Series editor, Nowak, Andrzej, Series editor, Reichl, Linda, Series editor, Schuster, Peter, Series editor, Schweitzer, Frank, Series editor, Sornette, Didier, Series editor, Thurner, Stefan, Series editor, Webber, Jr., Charles L., editor, and Marwan, Norbert, editor
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- 2015
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95. Climate tipping risks under policy-relevant overshoot temperature pathways
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Möller, Tessa, primary, Högner, Ernest Annika, additional, Bien, Samuel, additional, Schleussner, Carl-Friedrich, additional, Rockström, Johan, additional, Donges, Jonathan F., additional, and Wunderling, Nico, additional
- Published
- 2023
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96. Robustness of critical slowing down indicators to power-law extremes in an Amazon rainforest model
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Benson, Vitus, primary, Donges, Jonathan F., additional, Vollmer, Jürgen, additional, and Wunderling, Nico, additional
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- 2023
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97. Armed-conflict risks enhanced by climate-related disasters in ethnically fractionalized countries
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Schleussner, Carl-Friedrich, Donges, Jonathan F., Donner, Reik V., and Schellnhuber, Hans Joachim
- Published
- 2016
98. Using Causal Effect Networks to Analyze Different Arctic Drivers of Midlatitude Winter Circulation
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Kretschmer, Marlene, Coumou, Dim, Donges, Jonathan F., and Runge, Jakob
- Published
- 2016
99. Regenerative agriculture for food security and ecological resilience
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Breier, Jannes, Schwarz, Luana, Donges, Jonathan F., Gerten, Dieter, and Rockström, Johan
- Abstract
As part of the Earth4All project, collaborators have submitted this paper to delve further into the steps to be taken to widely transform our conventional agricultural system to provide food security and improve ecological resilience in a rapidly changing global climate. This article analyses the potential positive effects on soil ecology and crop yield of a global-scale transition to regenerative agriculture, while also considering social spreading dynamics that determine the adoption of such practices by farmers. The authors argue that the transition to a global regenerative agricultural system cannot be achieved without considering the deeper societal processes driving the effective dissemination and adoption of the change. Furthermore, the surrounding factors and conditions such as farmers’ political and institutional embeddedness, public opinion, the economic situation and the climate conditions they face within their region or community, as potential barriers hindering the transition, have to be taken into account. Therefore, it is not only the farmers’ responsibility to drive the change but also the politicians, institutions, companies and individual actors’ one which, all together, will support such transition processes.
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- 2023
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100. Rate-induced tipping cascades arising from interactions between the Greenland Ice Sheet and the Atlantic Meridional Overturning Circulation.
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Klose, Ann Kristin, Donges, Jonathan F., Feudel, Ulrike, and Winkelmann, Ricarda
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ATLANTIC meridional overturning circulation , *GREENLAND ice , *ICE sheets , *MELTWATER , *SUBGLACIAL lakes , *GLOBAL warming - Abstract
The Greenland Ice Sheet and Atlantic Meridional Overturning Circulation are considered tipping elements in the climate system, where global warming exceeding critical threshold levels in forcing can lead to large-scale and nonlinear reductions in ice volume and overturning strength, respectively. The positive-negative feedback loop governing their interaction (with a destabilizing effect on the AMOC due to ice loss and subsequent freshwater flux into the North Atlantic as well as a stabilizing effect of a net-cooling around Greenland with an AMOC weakening) may determine the long-term stability of both tipping elements. Here we explore the potential dynamic regimes arising from this positive-negative tipping feedback loop in a process-based conceptual model. Under idealized forcing scenarios we identify conditions under which different kinds of tipping cascades can occur: Herein, we distinguish between overshoot tipping cascades (leading to tipping of both GIS and AMOC) and rate-induced tipping cascades (where the AMOC despite not having crossed its own intrinsic tipping point tips nonetheless due to the fast rate of ice loss from Greenland). These different cascades occur within corridors of distinct tipping pathways that are affected by the GIS melting patterns and thus eventually by the imposed forcing and its time scales. Our results suggest that it is not only necessary to avoid breaching the respective critical levels of the environmental drivers for the Greenland Ice Sheet and Atlantic Meridional Overturning Circulation, but also to respect safe rates of environmental change to mitigate potential domino effects. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
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