TY - JOUR A1 - McCool, Weston C. A1 - Codding, Brian F. A1 - Vernon, Kenneth B. A1 - Wilson, Kurt M. A1 - Yaworsky, Peter M. A1 - Marwan, Norbert A1 - Kennett, Douglas J. T1 - Climate change-induced population pressure drives high rates of lethal violence in the Prehispanic central Andes JF - Proceedings of the National Academy of Sciences of the United States of America : PNAS N2 - Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of-and the interaction between-climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry C-14-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 C-14 dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity-whether driven by reduced resource abundance or increased competition-can lead to violence in subsistence societies when the outcome is lower per capita resource availability. KW - climate change KW - population pressure KW - warfare KW - lethal violence KW - Andes Y1 - 2022 U6 - https://doi.org/10.1073/pnas.2117556119 SN - 0027-8424 SN - 1091-6490 VL - 119 IS - 17 PB - National Acad. of Sciences CY - Washington ER - TY - JOUR A1 - Krämer, Hauke Kai A1 - Gelbrecht, Maximilian A1 - Pavithran, Induja A1 - Sujith, Ravindran A1 - Marwan, Norbert T1 - Optimal state space reconstruction via Monte Carlo decision tree search JF - Nonlinear Dynamics N2 - A novel idea for an optimal time delay state space reconstruction from uni- and multivariate time series is presented. The entire embedding process is considered as a game, in which each move corresponds to an embedding cycle and is subject to an evaluation through an objective function. This way the embedding procedure can be modeled as a tree, in which each leaf holds a specific value of the objective function. By using a Monte Carlo ansatz, the proposed algorithm populates the tree with many leafs by computing different possible embedding paths and the final embedding is chosen as that particular path, which ends at the leaf with the lowest achieved value of the objective function. The method aims to prevent getting stuck in a local minimum of the objective function and can be used in a modular way, enabling practitioners to choose a statistic for possible delays in each embedding cycle as well as a suitable objective function themselves. The proposed method guarantees the optimization of the chosen objective function over the parameter space of the delay embedding as long as the tree is sampled sufficiently. As a proof of concept, we demonstrate the superiority of the proposed method over the classical time delay embedding methods using a variety of application examples. We compare recurrence plot-based statistics inferred from reconstructions of a Lorenz-96 system and highlight an improved forecast accuracy for map-like model data as well as for palaeoclimate isotope time series. Finally, we utilize state space reconstruction for the detection of causality and its strength between observables of a gas turbine type thermoacoustic combustor. KW - State space reconstruction KW - Embedding KW - Optimization KW - Time series analysis KW - Causality KW - Prediction KW - Recurrence analysis Y1 - 2022 U6 - https://doi.org/10.1007/s11071-022-07280-2 SN - 0924-090X SN - 1573-269X VL - 108 IS - 2 SP - 1525 EP - 1545 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Marwan, Norbert T1 - Challenges and perspectives in recurrence analyses of event time series JF - Frontiers in applied mathematics and statistics N2 - The analysis of event time series is in general challenging. Most time series analysis tools are limited for the analysis of this kind of data. Recurrence analysis, a powerful concept from nonlinear time series analysis, provides several opportunities to work with event data and even for the most challenging task of comparing event time series with continuous time series. Here, the basic concept is introduced, the challenges are discussed, and the future perspectives are summarized. KW - event time series KW - extreme events KW - recurrence analysis KW - edit distance KW - synchronization Y1 - 2023 U6 - https://doi.org/10.3389/fams.2023.1129105 SN - 2297-4687 VL - 9 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Agarwal, Ankit A1 - Guntu, Ravikumar A1 - Banerjee, Abhirup A1 - Gadhawe, Mayuri Ashokrao A1 - Marwan, Norbert T1 - A complex network approach to study the extreme precipitation patterns in a river basin JF - Chaos : an interdisciplinary journal of nonlinear science N2 - The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes. Y1 - 2022 U6 - https://doi.org/10.1063/5.0072520 SN - 1054-1500 SN - 1089-7682 VL - 32 IS - 1 PB - American Institute of Physics CY - Woodbury, NY ER - TY - JOUR A1 - Trauth, Martin H. A1 - Marwan, Norbert T1 - Introduction-time series analysis for Earth, climate and life interactions JF - Quaternary science reviews : the international multidisciplinary research and review journal Y1 - 2022 U6 - https://doi.org/10.1016/j.quascirev.2022.107475 SN - 0277-3791 SN - 1873-457X VL - 284 PB - Elsevier CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Ladeira, Guenia A1 - Marwan, Norbert A1 - Destro-Filho, Joao-Batista A1 - Ramos, Camila Davi A1 - Lima, Gabriela T1 - Frequency spectrum recurrence analysis JF - Scientific reports N2 - In this paper, we present the new frequency spectrum recurrence analysis technique by means of electro-encephalon signals (EES) analyses. The technique is suitable for time series analysis with noise and disturbances. EES were collected, and alpha waves of the occipital region were analysed by comparing the signals from participants in two states, eyes open and eyes closed. Firstly, EES were characterized and analysed by means of techniques already known to compare with the results of the innovative technique that we present here. We verified that, standard recurrence quantification analysis by means of EES time series cannot statistically distinguish the two states. However, the new frequency spectrum recurrence quantification exhibit quantitatively whether the participants have their eyes open or closed. In sequence, new quantifiers are created for analysing the recurrence concentration on frequency bands. These analyses show that EES with similar frequency spectrum have different recurrence levels revealing different behaviours of the nervous system. The technique can be used to deepen the study on depression, stress, concentration level and other neurological issues and also can be used in any complex system. KW - Biomedical engineering KW - Brain injuries KW - Computational models KW - Computational neuroscience KW - Data acquisition KW - Data processing KW - Electrical and electronic engineering KW - Neural circuits KW - Visual system Y1 - 2020 U6 - https://doi.org/10.1038/s41598-020-77903-4 SN - 2045-2322 VL - 10 IS - 1 PB - Nature portfolio CY - Berlin ER - TY - JOUR A1 - Ramos, Antonio M. T. A1 - Builes-Jaramillo, Alejandro A1 - Poveda, German A1 - Goswami, Bedartha A1 - Macau, Elbert E. N. A1 - Kurths, Jürgen A1 - Marwan, Norbert T1 - Recurrence measure of conditional dependence and applications JF - Physical review : E, Statistical, nonlinear and soft matter physics N2 - Identifying causal relations from observational data sets has posed great challenges in data-driven causality inference studies. One of the successful approaches to detect direct coupling in the information theory framework is transfer entropy. However, the core of entropy-based tools lies on the probability estimation of the underlying variables. Herewe propose a data-driven approach for causality inference that incorporates recurrence plot features into the framework of information theory. We define it as the recurrence measure of conditional dependence (RMCD), and we present some applications. The RMCD quantifies the causal dependence between two processes based on joint recurrence patterns between the past of the possible driver and present of the potentially driven, excepting the contribution of the contemporaneous past of the driven variable. Finally, it can unveil the time scale of the influence of the sea-surface temperature of the Pacific Ocean on the precipitation in the Amazonia during recent major droughts. Y1 - 2017 U6 - https://doi.org/10.1103/PhysRevE.95.052206 SN - 2470-0045 SN - 2470-0053 VL - 95 PB - American Physical Society CY - College Park ER - TY - JOUR A1 - Wendi, Dadiyorto A1 - Marwan, Norbert A1 - Merz, Bruno T1 - In Search of Determinism-Sensitive Region to Avoid Artefacts in Recurrence Plots JF - International journal of bifurcation and chaos : in applied sciences and engineering N2 - As an effort to reduce parameter uncertainties in constructing recurrence plots, and in particular to avoid potential artefacts, this paper presents a technique to derive artefact-safe region of parameter sets. This technique exploits both deterministic (incl. chaos) and stochastic signal characteristics of recurrence quantification (i.e. diagonal structures). It is useful when the evaluated signal is known to be deterministic. This study focuses on the recurrence plot generated from the reconstructed phase space in order to represent many real application scenarios when not all variables to describe a system are available (data scarcity). The technique involves random shuffling of the original signal to destroy its original deterministic characteristics. Its purpose is to evaluate whether the determinism values of the original and the shuffled signal remain closely together, and therefore suggesting that the recurrence plot might comprise artefacts. The use of such determinism-sensitive region shall be accompanied by standard embedding optimization approaches, e.g. using indices like false nearest neighbor and mutual information, to result in a more reliable recurrence plot parameterization. KW - Recurrence plot KW - phase space time delay embedding reconstruction KW - artefact avoidance Y1 - 2017 U6 - https://doi.org/10.1142/S0218127418500074 SN - 0218-1274 SN - 1793-6551 VL - 28 IS - 1 PB - World Scientific CY - Singapore ER - TY - JOUR A1 - Goswami, Bedartha A1 - Boers, Niklas A1 - Rheinwalt, Aljoscha A1 - Marwan, Norbert A1 - Heitzig, Jobst A1 - Breitenbach, Sebastian Franz Martin A1 - Kurths, Jürgen T1 - Abrupt transitions in time series with uncertainties JF - Nature Communications N2 - Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an ‘uncertainty-aware’ framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon. Y1 - 2018 U6 - https://doi.org/10.1038/s41467-017-02456-6 SN - 2041-1723 VL - 9 PB - Nature Publ. Group CY - London ER - TY - JOUR A1 - Mishra, Praveen Kumar A1 - Prasad, Sushma A1 - Marwan, Norbert A1 - Anoop, A. A1 - Krishnan, R. A1 - Gaye, Birgit A1 - Basavaiah, N. A1 - Stebich, Martina A1 - Menzel, Philip A1 - Riedel, Nils T1 - Contrasting pattern of hydrological changes during the past two millennia from central and northern India BT - regional climate difference or anthropogenic impact? JF - Global and planetary change N2 - High resolution reconstructions of the India Summer Monsoon (ISM) are essential to identify regionally different patterns of climate change and refine predictive models. We find opposing trends of hydrological proxies between northern (Sahiya cave stalagmite) and central India (Lonar Lake) between 100 and 1300 CE with the strongest anti-correlation between 810 and 1300 CE. The apparently contradictory data raise the question if these are related to widely different regional precipitation patterns or reflect human influence in/around the Lonar Lake. By comparing multiproxy data with historical records, we demonstrate that only the organic proxies in the Lonar Lake show evidence of anthropogenic impact. However, evaporite data (mineralogy and delta O-18) are indicative of precipitation/evaporation (P/E) into the Lonar Lake. Back-trajectories of air-mass circulation over northern and central India show that the relative contribution of the Bay of Bengal (BoB) branch of the ISM is crucial for determining the delta O-18 of carbonate proxies only in north India, whereas central India is affected significantly by the Arabian Sea (AS) branch of the ISM. We conclude that the delta O-18 of evaporative carbonates in the Lonar Lake reflects P/E and, in the interval under consideration, is not influenced by source water changes. The opposing trend between central and northern India can be explained by (i) persistent multidecadal droughts over central India between 810 and 1300 CE that provided an effective mechanism for strengthening sub-tropical westerly winds resulting in enhancement of wintertime (non-monsoonal) rainfall over northern parts of the Indian subcontinent, and/or (ii) increased moisture influx to northern India from the depleted BoB source waters. KW - ENSO KW - Isotopes KW - Indian summer monsoon KW - Lonar Lake KW - Stalagmites KW - Westerlies Y1 - 2017 U6 - https://doi.org/10.1016/j.gloplacha.2017.12.005 SN - 0921-8181 SN - 1872-6364 VL - 161 SP - 97 EP - 107 PB - Elsevier CY - Amsterdam ER -