Attractor landscapes: a unifying conceptual model for understanding behaviour change across scales of observation

References

• Allen, L. J. S. (2011). An introduction to stochastic processes with applications to biology (2nd ed.). Chapman & Hall/CRC.
   Google Scholar
• Antoniadou, K. I., & Libert, A.-S. (2019). Spatial resonant periodic orbits in the restricted three-body problem. Monthly Notices of the Royal Astronomical Society, 483(3), 2923–2940. https://doi.org/10.1093/mnras/sty3195
   Web of Science ®Google Scholar
• Ashwin, P., Wieczorek, S., Vitolo, R., & Cox, P. (2012). Tipping points in open systems: Bifurcation, noise-induced and rate-dependent examples in the climate system. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 370(1962), 1166–1184. https://doi.org/10.1098/rsta.2011.0306
   PubMed Web of Science ®Google Scholar
• Ashwin, P., & Zaikin, A. (2015). Pattern selection: The importance of “how you get there”. Biophysical Journal, 108(6), 1307–1308. https://doi.org/10.1016/j.bpj.2015.01.036
   PubMed Web of Science ®Google Scholar
• Astley, C. M., Tuli, G., Mc Cord, K. A., Cohn, E. L., Rader, B., Varrelman, T. J., Chiu, S. L., Deng, X., Stewart, K., Farag, T. H., Barkume, K. M., LaRocca, S., Morris, K. A., Kreuter, F., & Brownstein, J. S. (2021). Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base. Proceedings of the National Academy of Sciences, 118(51), e2111455118. https://doi.org/10.1073/pnas.2111455118
   PubMed Web of Science ®Google Scholar
• Barkay, N., Cobb, C., Eilat, R., Galili, T., Haimovich, D., LaRocca, S., Morris, K., & Sarig, T. (2020). Weights and Methodology Brief for the COVID-19 Symptom Survey by University of Maryland and Carnegie Mellon University, in Partnership with Facebook. ArXiv:2009.14675 [Cs]. http://arxiv.org/abs/2009.14675.
   Google Scholar
• Bar-Yam, Y. (1997). Dynamics of complex systems. Addison-Wesley. https://necsi.edu/dynamics-of-complex-systems.
   Google Scholar
• Berglund, N., & Gentz, B. (2006). Noise-induced phenomena in slow-fast dynamical systems. Springer-Verlag. https://doi.org/10.1007/1-84628-186-5
   Google Scholar
• Boeing, G. (2016). Visual analysis of nonlinear dynamical systems: Chaos, fractals, self-similarity and the limits of prediction. Systems, 4(4), 37. https://doi.org/10.3390/systems4040037
   Web of Science ®Google Scholar
• Bolger, N., & Zee, K. S. (2019). Heterogeneity in temporal processes: Implications for theories in health psychology. Applied Psychology: Health and Well-Being, 11(2), 198–201. https://doi.org/10.1111/aphw.12159
   PubMed Web of Science ®Google Scholar
• Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5–13. https://doi.org/10.1002/wps.20375
   PubMed Web of Science ®Google Scholar
• Cane, J., O’Connor, D., & Michie, S. (2012). Validation of the theoretical domains framework for use in behaviour change and implementation research. Implementation Science, 7(1), 37. https://doi.org/10.1186/1748-5908-7-37
   PubMed Web of Science ®Google Scholar
• Centola, D. (2021). Complex contagions. In Research handbook on analytical sociology (1st ed., pp. 321–335). Edward Elgar Publishing. https://www.elgaronline.com/view/edcoll/9781789906844/9781789906844.00025.xml.
   Google Scholar
• Chen, S., O’Dea, E. B., Drake, J. M., & Epureanu, B. I. (2019). Eigenvalues of the covariance matrix as early warning signals for critical transitions in ecological systems. Scientific Reports, 9(1), 2572. https://doi.org/10.1038/s41598-019-38961-5
   PubMedGoogle Scholar
• Chen, X., & Chen, D.-G. (2019). Cognitive theories, paradigm of quantum behavior change, and cusp catastrophe modeling in social behavioral research. Journal of the Society for Social Work and Research, 10(1), 127–159. https://doi.org/10.1086/701837
   Web of Science ®Google Scholar
• Chevance, G., Baretta, D., Heino, M. T. J., Perski, O., Olthof, M., Klasnja, P., Hekler, E., & Godino, J. (2021). Characterizing and predicting person-specific, day-to-day, fluctuations in walking behavior. PLOS ONE, 16(5), e0251659. https://doi.org/10.1371/journal.pone.0251659
   PubMed Web of Science ®Google Scholar
• Craig, P., Di Ruggiero, E., Frolich, K. L., Mykhalovskiy, E., White, M., Campbell, R., Cummins, S., Edwards, N., Hunt, K., & Kee, F. (2018). Taking account of context in population health intervention research: Guidance for producers, users and funders of research.
   Google Scholar
• Cummings, S., Bridgman, T., & Brown, K. G. (2016). Unfreezing change as three steps: Rethinking Kurt Lewin’s legacy for change management. Human Relations, 69(1), 33–60. https://doi.org/10.1177/0018726715577707
   Web of Science ®Google Scholar
• Dablander, F., Pichler, A., Cika, A., & Bacilieri, A. (2022). Anticipating critical transitions in psychological systems using early warning signals: Theoretical and practical considerations. Psychological Methods. https://doi.org/10.1037/met0000450
   Web of Science ®Google Scholar
• Dalege, J., Borsboom, D., Harreveld, F. v., & Maas, H. L. J. v. d. (2018). The attitudinal entropy (AE) framework as a general theory of individual attitudes. Psychological Inquiry, 29(4), 175–193. https://doi.org/10.1080/1047840X.2018.1537246
   Web of Science ®Google Scholar
• Eldredge, B., Markham, L. K., Ruiter, C. M., Fernández, R. A., Kok, M. E., & Parcel, G., & S, G. (2016). Planning health promotion programs: An intervention mapping approach. John Wiley & Sons.
   Google Scholar
• Erdi, P. (2008). History of complex systems research. In Complexity explained (pp. 25–55). Springer. https://doi.org/10.1007/978-3-540-35778-0_2
   Google Scholar
• Érdi, P. (2008). Complexity Explained. Springer-Verlag. https://doi.org/10.1007/978-3-540-35778-0
   Google Scholar
• Fan, J., Li, Y., Stewart, K., Kommareddy, A. R., Garcia, A., O’Brien, J., Bradford, A., Deng, X., Chiu, S., Kreuter, F., Barkay, N., Bilinski, A., Kim, B., Galili, T., Haimovich, D., LaRocca, S., Presser, S., Morris, K., Salomon, J. A., … Vannette, D. (2020). The University of Maryland Social Data Science Center Global COVID-19 Trends and Impact Survey, in partnership with Facebook. The Global COVID-19 Trends and Impact Survey Open Data API. https://covidmap.umd.edu/api.html.
   Google Scholar
• Feder, T. (2007). Statistical physics is for the birds. Physics Today, 60(10), 28–30. https://doi.org/10.1063/1.2800090
   Web of Science ®Google Scholar
• Fisher, A. J., Medaglia, J. D., & Jeronimus, B. F. (2018). Lack of group-to-individual generalizability is a threat to human subjects research. Proceedings of the National Academy of Sciences, 201711978. https://doi.org/10.1073/pnas.1711978115
   Google Scholar
• Gardiner, C. W. (2002). Handbook of stochastic methods: For physics, chemistry and the natural sciences (Study ed., 2. ed., 6. print). Springer.
   Google Scholar
• Goldenfeld, N. (2019). Lectures on phase transitions and the renormalization group. CRC Press. https://doi.org/10.1201/9780429493492
   Google Scholar
• Gomersall, T. (2018). Complex adaptive systems: A new approach for understanding health practices. Health Psychology Review, 12(4), 405–418. https://doi.org/10.1080/17437199.2018.1488603
   PubMed Web of Science ®Google Scholar
• Guastello, S. J., Koopmans, M., & Pincus, D. (2008). Chaos and Complexity in Psychology: The Theory of Nonlinear Dynamical Systems. Cambridge University Press. https://doi.org/10.1017/CBO9781139058544
   Google Scholar
• Gunderson, L. H., & Pritchard, L. (2012). Resilience and the Behavior of Large-Scale Systems. Island Press. https://catalogue.solent.ac.uk/openurl/44SSU_INST/44SSU_INST:VU1?u.ignore_date_coverage=true&rft.mms_id=9997124103604796.
   Google Scholar
• Hagger, M. S., Cameron, L. D., Hamilton, K., Hankonen, N., & Lintunen, T. (2020). The handbook of behavior change. Cambridge University Press.
   Google Scholar
• Hagger, M. S., Hankonen, N., Chatzisarantis, N. L. D., & Ryan, R. M. (2020). Changing Behavior Using Self-Determination Theory. In M. S. Hagger, L. D. Cameron, K. Hamilton, N. Hankonen, & T. Lintunen (Eds.), The handbook of behavior change (1st ed., pp. 104–119). Cambridge University Press. https://doi.org/10.1017/9781108677318.008
   Google Scholar
• Hasselman, F. (2020). casnet: A toolbox for studying Complex Adaptive Systems and NETworks (0.1.4) [R]. https://github.com/FredHasselman/casnet.
   Google Scholar
• Hasselman, F. (2022). Early warning signals in phase space: geometric resilience loss indicators from multiplex cumulative recurrence networks. Frontiers in Physiology, 13, 859127. https://doi.org/10.3389/fphys.2022.859127
   PubMed Web of Science ®Google Scholar
• Heino, M. T. J., Knittle, K., Noone, C., Hasselman, F., & Hankonen, N. (2021). Studying behaviour change mechanisms under complexity. Behavioral Sciences, 11(5), 77. https://doi.org/10.3390/bs11050077
   Web of Science ®Google Scholar
• Hekler, E., Tiro, J. A., Hunter, C. M., & Nebeker, C. (2020). Precision health: The role of the social and behavioral sciences in advancing the vision. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine, 54(11), 805–826. https://doi.org/10.1093/abm/kaaa018
   PubMed Web of Science ®Google Scholar
• Helmich, M. A., Wichers, M., Olthof, M., Strunk, G., Aas, B., Aichhorn, W., Schiepek, G., & Snippe, E. (2020). Sudden gains in day-to-day change: Revealing nonlinear patterns of individual improvement in depression. Journal of Consulting and Clinical Psychology, 88(2), 119–127. https://doi.org/10.1037/ccp0000469
   PubMed Web of Science ®Google Scholar
• Hooker, C. A. (2011). Philosophy of complex systems. North Holland.
   Google Scholar
• Intergovernmental Panel on Climate Change (IPCC). (2022, April 4). Sixth Assessment Report—IPCC. https://www.ipcc.ch/assessment-report/ar6/.
   Google Scholar
• Kok, G., Gottlieb, N. H., Peters, G.-J. Y., Mullen, P. D., Parcel, G. S., Ruiter, R. A. C., Fernández, M. E., Markham, C., & Bartholomew, L. K. (2016). A taxonomy of behaviour change methods: An Intervention Mapping approach. Health Psychology Review, 10(3), 297–312. https://doi.org/10.1080/17437199.2015.1077155
   PubMed Web of Science ®Google Scholar
• Kreuter, F., Barkay, N., Bilinski, A., Bradford, A., Chiu, S., Eliat, R., Fan, J., Galili, T., Haimovich, D., Kim, B., LaRocca, S., Li, Y., Morris, K., Presser, S., Sarig, T., Salomon, J. A., Stewart, K., Stuart, E. A., & Tibshirani, R. (2020). Partnering with a global platform to inform research and public policy making. Survey Research Methods, 14(2), 159–163. https://doi.org/10.18148/SRM/2020.V14I2.7761.
   Google Scholar
• Kricheldorf, H. R. (2016). Getting it right in science and medicine: Can science progress through errors? Fallacies and facts. Springer.
   Google Scholar
• Kuehn, C., & Bick, C. (2021). A universal route to explosive phenomena. Science Advances, 7(16), eabe3824. https://doi.org/10.1126/sciadv.abe3824
   PubMed Web of Science ®Google Scholar
• Kuznetsov, Y. A. (1998). Elements of applied bifurcation theory (Vol. 112). Springer. https://doi.org/10.1007/b98848
   Google Scholar
• Kwasnicka, D., Dombrowski, S. U., White, M., & Sniehotta, F. (2016). Theoretical explanations for maintenance of behaviour change: A systematic review of behaviour theories. Health Psychology Review, 10(3), 277–296. https://doi.org/10.1080/17437199.2016.1151372
   PubMed Web of Science ®Google Scholar
• Kwasnicka, D., Inauen, J., Nieuwenboom, W., Nurmi, J., Schneider, A., Short, C. E., Dekkers, T., Williams, A. J., Bierbauer, W., Haukkala, A., Picariello, F., & Naughton, F. (2019). Challenges and solutions for N-of-1 design studies in health psychology. Health Psychology Review, 13(2), 163–178. https://doi.org/10.1080/17437199.2018.1564627
   PubMed Web of Science ®Google Scholar
• Lever, J. J., Leemput, I. A. v. d., Weinans, E., Quax, R., Dakos, V., Nes, E. H. v., Bascompte, J., & Scheffer, M. (2020). Foreseeing the future of mutualistic communities beyond collapse. Ecology Letters, 23(1), 2–15. https://doi.org/10.1111/ele.13401
   PubMed Web of Science ®Google Scholar
• Marchand, G. C., & Hilpert, J. C. (2020). Complex systems approaches to educational research: Introduction to the special issue. The Journal of Experimental Education, 88(3), 351–357. https://doi.org/10.1080/00220973.2020.1746625
   Web of Science ®Google Scholar
• Meijer, E., Vangeli, E., Gebhardt, W. A., & van Laar, C. (2020). Identity processes in smokers who want to quit smoking: A longitudinal interpretative phenomenological analysis. Health, 24(5), 493–517. https://doi.org/10.1177/1363459318817923
   PubMed Web of Science ®Google Scholar
• Michie, S., Atkins, L., & West, R. (2014). The behaviour change wheel—A guide to designing interventions.
   Google Scholar
• Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., Eccles, M. P., Cane, J., & Wood, C. E. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46(1), 81–95. https://doi.org/10.1007/s12160-013-9486-6
   PubMed Web of Science ®Google Scholar
• Michie, S., Stralen, M. M. van, & West, R. (2011). The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Science, 6(1), 42. https://doi.org/10.1186/1748-5908-6-42
   PubMed Web of Science ®Google Scholar
• Michie, S., West, R., Campbell, R., Brown, J., & Gainforth, H. (2014). ABC of behaviour change theories. http://discovery.ucl.ac.uk/1450988/.
   Google Scholar
• Mitchell, M. (2009). Complexity: A guided tour. Oxford University Press.
   Google Scholar
• Molenaar, P. C. M. (2007). Psychological methodology will change profoundly due to the necessity to focus on intra-individual variation. Integrative Psychological and Behavioral Science, 41(1), 35–40. https://doi.org/10.1007/s12124-007-9011-1
   PubMed Web of Science ®Google Scholar
• Molenaar, P. C. M. (2008). On the implications of the classical ergodic theorems: Analysis of developmental processes has to focus on intra-individual variation. Developmental Psychobiology, 50(1), 60–69. https://doi.org/10.1002/dev.20262
   PubMed Web of Science ®Google Scholar
• Nosek, B. A., Hardwicke, T. E., Moshontz, H., Allard, A., Corker, K. S., Dreber, A., Fidler, F., Hilgard, J., Kline Struhl, M., Nuijten, M. B., Rohrer, J. M., Romero, F., Scheel, A. M., Scherer, L. D., Schönbrodt, F. D., & Vazire, S. (2022). Replicability, robustness, and reproducibility in psychological science. Annual Review of Psychology, 73(1), 719–748. https://doi.org/10.1146/annurev-psych-020821-114157
   PubMed Web of Science ®Google Scholar
• Nowak, A., & Vallacher, R. R. (2019). Nonlinear societal change: The perspective of dynamical systems. British Journal of Social Psychology, 58(1), 105–128. https://doi.org/10.1111/bjso.12271
   PubMed Web of Science ®Google Scholar
• Olthof, M., Hasselman, F., & Lichtwarck-Aschoff, A. (2020). Complexity in psychological self-ratings: Implications for research and practice. BMC Medicine, 18(1), 317. https://doi.org/10.1186/s12916-020-01727-2
   PubMed Web of Science ®Google Scholar
• Olthof, M., Hasselman, F., Maatman, F. O., Bosman, A., & Lichtwarck-Aschoff, A. (2020). Complexity Theory of Psychopathology. PsyArXiv. https://doi.org/10.31234/osf.io/f68ej
   Google Scholar
• Olthof, M., Hasselman, F., Strunk, G., van Rooij, M. M. J. W., Aas, B., Helmich, M. A., Schiepek, G., & Lichtwarck-Aschoff, A. (2019). Critical fluctuations as an early-warning signal for sudden gains and losses in patients receiving psychotherapy for mood disorders. Clinical Psychological Science, 8(1), 25–35. https://doi.org/10.1177/2167702619865969.
   Web of Science ®Google Scholar
• Proverbio, D. (2020, October 19). Daniele Proverbio: Smooth or abrupt? How dynamical systems change their state. https://www.youtube.com/watch?v=4tW6No-u0Ag&feature=youtu.be.
   Google Scholar
• Proverbio, D., Kemp, F., Magni, S., & Gonçalves, J. (2022). Performance of early warning signals for disease re-emergence: A case study on COVID-19 data. PLOS Computational Biology, 18(3), e1009958. https://doi.org/10.1371/journal.pcbi.1009958
   PubMed Web of Science ®Google Scholar
• Resnicow, K., & Vaughan, R. (2006). A chaotic view of behavior change: A quantum leap for health promotion. International Journal of Behavioral Nutrition and Physical Activity, 3(1), 25. https://doi.org/10.1186/1479-5868-3-25
   PubMedGoogle Scholar
• Rikkert, O., Dakos, M. G. M., Buchman, V., Boer, T. G., de, R., Glass, L., Cramer, A. O. J., Levin, S., van Nes, E., Sugihara, G., Ferrari, M. D., Tolner, E. A., van de Leemput, I., Lagro, J., Melis, R., & Scheffer, M. (2016). Slowing down of recovery as generic risk marker for acute severity transitions in chronic diseases. Critical Care Medicine, 44(3), 601–606. https://doi.org/10.1097/CCM.0000000000001564
   PubMed Web of Science ®Google Scholar
• Ruissen, G. R., Zumbo, B. D., Rhodes, R. E., Puterman, E., & Beauchamp, M. R. (2021). Analysis of dynamic psychological processes to understand and promote physical activity behaviour using intensive longitudinal methods: A primer. Health Psychology Review, 0(0), 1–34. https://doi.org/10.1080/17437199.2021.1987953
   PubMedGoogle Scholar
• Salmon, J., Hesketh, K. D., Arundell, L., Downing, K. L., & Biddle, S. J. H. (2020). Changing Behavior Using Ecological Models. In K. Hamilton, L. D. Cameron, M. S. Hagger, N. Hankonen, & T. Lintunen (Eds.), The Handbook of Behavior Change (pp. 237–250). Cambridge University Press. https://doi.org/10.1017/9781108677318.017
   Google Scholar
• Scholz, U., Berli, C., Lüscher, J., & Knoll, N. (2020). Dyadic Behavior Change Interventions. In K. Hamilton, L. D. Cameron, M. S. Hagger, N. Hankonen, & T. Lintunen (Eds.), The Handbook of Behavior Change (pp. 632–648). Cambridge University Press. https://doi.org/10.1017/9781108677318.043
   Google Scholar
• Siegenfeld, A. F., & Bar-Yam, Y. (2020). An introduction to complex systems science and its applications. Complexity, 2020, 6105872. https://doi.org/10.1155/2020/6105872
   Web of Science ®Google Scholar
• Skivington, K., Matthews, L., Simpson, S. A., Craig, P., Baird, J., Blazeby, J. M., Boyd, K. A., Craig, N., French, D. P., McIntosh, E., Petticrew, M., Rycroft-Malone, J., White, M., & Moore, L. (2021). A new framework for developing and evaluating complex interventions: Update of Medical Research Council guidance. BMJ, 374, n2061. https://doi.org/10.1136/bmj.n2061
   PubMed Web of Science ®Google Scholar
• Stapelberg, N. J. C., Pratt, R., Neumann, D. L., Shum, D. H. K., Brandis, S., Muthukkumarasamy, V., Stantic, B., Blumenstein, M., & Headrick, J. P. (2018). From feedback loop transitions to biomarkers in the psycho-immune-neuroendocrine network: Detecting the critical transition from health to major depression. Neuroscience and Biobehavioral Reviews, 90, 1–15. https://doi.org/10.1016/j.neubiorev.2018.03.005
   PubMed Web of Science ®Google Scholar
• Sugihara, G., May, R., Ye, H., Hsieh, C., Deyle, E., Fogarty, M., & Munch, S. (2012). Detecting causality in complex ecosystems. Science, 338(6106), 496–500. https://doi.org/10.1126/science.1227079
   PubMed Web of Science ®Google Scholar
• Sutton, S. (2000). A critical review of the transtheoretical model applied to smoking cessation. In Understanding and changing health behaviour: From health beliefs to self-regulation (pp. 207–225). Harwood Academic Publishers.
   Google Scholar
• Sutton, S. (2005). Another nail in the coffin of the transtheoretical model? A comment on west. Addiction, 100(8), 1043–1046. https://doi.org/10.1111/j.1360-0443.2005.01172.x
   PubMed Web of Science ®Google Scholar
• Tan, J., Zhao, L., & Chen, H. (2019). A meta-analysis of the effectiveness of gradual versus abrupt smoking cessation. Tobacco Induced Diseases, 17. https://doi.org/10.18332/tid/100557
   PubMed Web of Science ®Google Scholar
• The Visual Representation of Complexity. (2018, June 7). CECAN. https://www.cecan.ac.uk/news/the-visual-representation-of-complexity/.
   Google Scholar
• Trickett, E., & Paterson, S. (2020). Behavior change in community contexts. In K. Hamilton, L. D. Cameron, M. S. Hagger, N. Hankonen, & T. Lintunen (Eds.), The handbook of behavior change (pp. 401–415). Cambridge University Press. https://doi.org/10.1017/9781108677318.028
   Google Scholar
• Vallacher, R. R., & Nowak, A. (2008). The dynamics of human experience: Fundamentals of dynamical social psychology. In S. J. Guastello, M. Koopmans, & D. Pincus (Eds.), Chaos and complexity in psychology (pp. 370–401). Cambridge University Press. http://ebooks.cambridge.org/ref/id/CBO9781139058544A119.
   Google Scholar
• Vallacher, R. R., Read, S. J., & Nowak, A. (2017). Computational social psychology. Routledge. https://www.taylorfrancis.com/books/e/9781315173726.
   Google Scholar
• Wallot, S., & Kelty-Stephen, D. G. (2017). Interaction-dominant causation in mind and brain, and its implication for questions of generalization and replication. Minds and Machines, 28, 1–22. https://doi.org/10.1007/s11023-017-9455-0
   Google Scholar
• Weinans, E., Lever, J. J., Bathiany, S., Quax, R., Bascompte, J., van Nes, E. H., Scheffer, M., & van de Leemput, I. A. (2019). Finding the direction of lowest resilience in multivariate complex systems. Journal of The Royal Society Interface, 16(159), 20190629. https://doi.org/10.1098/rsif.2019.0629
   PubMed Web of Science ®Google Scholar
• West, R., & Sohal, T. (2006). “Catastrophic” pathways to smoking cessation: Findings from national survey. BMJ : British Medical Journal, 332(7539), 458–460. https://doi.org/10.1136/bmj.38723.573866.AE
   Google Scholar
• Wijnants, M. L. (2014). A review of theoretical perspectives in cognitive science on the presence of 1 / f scaling in coordinated physiological and cognitive processes. Journal of Nonlinear Dynamics, 2014, 1–17. https://doi.org/10.1155/2014/962043
   Google Scholar
• Williams, B., & Hummelbrunner, R. (2011). Systems concepts in action: A practitioner’s toolkit. Stanford Business Books.
   Google Scholar
• Zhang, X., Kuehn, C., & Hallerberg, S. (2015). Predictability of critical transitions. Physical Review E, 92(5), 052905. https://doi.org/10.1103/PhysRevE.92.052905
   Web of Science ®Google Scholar