George Sugihara

George Sugihara
Sugihara in 2015
Born	Tokyo
Alma mater	Princeton University
Known for	Empirical dynamic modeling
Scientific career
Fields	Algebraic topology, network theory, nonlinear dynamics, chaotic systems, causality, ecology, medicine, genomics, finance, atmospheric and earth science, fisheries
Institutions	Scripps Institution of Oceanography, University of California San Diego Cornell University Imperial College London Kyoto University Tokyo Institute of Technology Oxford University
Doctoral advisor	Robert May
Doctoral students	Alistair Hobday, Chi-Hao Hsieh, Charles Perretti, Hao Ye, Ethan Deyle, Alfredo Giron-Nava
Other notable students	DJ Patil, Louis-Felix Bersier, Martin Casdagli, Franc Courchamp
Website	https://deepeco.ucsd.edu/

George Sugihara is a professor of biological oceanography and complex systems at the Scripps Institution of Oceanography where he is the inaugural holder of the McQuown Chair in Natural Science. ^[1]

His work involves inductive theoretical approaches to understanding nature from observational data. The general approach is different from most theory and involves minimalist inductive theory – Inductive data-driven explorations of nature using minimal assumptions. The aim is to avoid inevitable assumptions of deductive first-principle models and produce an understanding that passes the validation test of out-of-sample prediction. His initial work on fisheries as complex, chaotic systems led to work on financial networks and prediction of chaotic systems. ^[2]

Research interests

Research interests include complexity theory, nonlinear dynamics, ecology, cryptic pathology, food web structure, species abundance patterns, conservation biology, biological control, neuroscience, epidemiology, geoscience, empirical climate modelling, quantitative finance, economics, fisheries forecasting, and the design and implementation of derivatives markets for fisheries.

Education

Sugihara studied natural resources at the University of Michigan, where he received a BS in 1973. At Princeton University he studied mathematical ecology under Robert May earning a MS in biology in 1980 and PhD in mathematical biology in 1983.

While at Princeton he made important contributions to species abundance by identifying regularities in hierarchical community structure expressed by sequentially divided niches. The hierarchical structure, representing a minimal form of community structure, derives from evolutionary and ecological drivers generating species diversity accounting for observed abundance structures. ^[3]

Career

Sugihara began his career as the Wigner Prize Fellow ^[4] at Oak Ridge National Laboratory and concurrently associate professor of Mathematics at the University of Tennessee. A notable contribution was the topological / graph theoretical proof that increasing food web species specialization combined with the rigid circuit property leads to the rule that species enter communities by attaching within individual guilds or cliques rather than across multiple guilds. ^[5]

In 1986, he joined Scripps Institution of Oceanography (SIO), holding the UC San Diego John Dove Isaacs Chair in Natural Philosophy from 1990 to 1995. Since 2007 he has been the McQuown Professor of Natural Science at Scripps.

Sugihara has been a visiting professor at Cornell University, Imperial College London, Kyoto University and the Tokyo Institute of Technology, and was a visiting fellow at Merton College, Oxford University in 2002. He served as a member of the National Academy of Sciences Board on Mathematical Sciences and its Applications.

Contributions

Early work included topology and assembly in ecological and social systems ^[6] and generic early warning signs of critical transitions that apply across many apparently different classes of systems. ^[7]

One of his most interdisciplinary contributions involves the work he developed with Robert May concerning methods for forecasting nonlinear and chaotic systems. ^{[8] [9]} This took him into the arena of investment banking at Deutsche Bank, where he applied these theoretical methods to forecast erratic market behavior.

He helped found Prediction Company and Quantitative Advisors LLC, and has been a consultant to the Bank of England, the Federal Reserve Bank of New York, and to the Federal Reserve System on questions of international security regarding systemic risk in the financial sector. ^{[10] [11]}

He also contributed significantly to natural resource management and policy development. ^[12] He was commissioned by the Eastern Bering Sea and Aleutian Islands Alaskan Pollock Fleet, one of the most valuable fisheries in the world ^[13] to design a market-incentive plan, the Comprehensive Incentive Plan (CIP), for salmon by-catch avoidance. He developed the plan framework implemented in 2010 to protect the native salmon fisheries of western Alaska, resulting in a marked decrease in salmon bycatch. ^[14]

Other contributions address topology and assembly of ecological systems, and, social system dynamics ^[15] , as well as work on generic early warning signs of critical transitions across many apparently different classes of systems ^[16] .

Empirical Dynamic Modeling

Focusing on data-driven, practical solutions to analysis and forecasting he developed empirical dynamic modeling, a set of tools and techniques widely applicable to analysis and prediction of complex, nonlinear systems ^{[17] [18]} . A particularly important and widely-used tool is convergent cross mapping, a method to quantify cause-and-effect relationships as expressed in the underlying dynamics of the data ^[19] rather than on statistical estimates such as a correlation coefficient that may not be justifiable or informative on nonlinear (state-dependent) complex systems. ^[17]

References

1. "UC Announcement of McQuown Chair". Archived from the original on 2009-01-12. Retrieved 2008-11-22.
2. Sugihara, G.; May, R. M. (1990). "Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series". Nature. 344 (6268): 734–741. Bibcode:1990Natur.344..734S. doi:10.1038/344734a0. PMID   2330029. S2CID   4370167.
3. Sugihara, G. (1980). "Minimal Community Structure: An Explanation of Species Abundance Patterns". The American Naturalist. 116 (6): 770–787. doi:10.1086/283669.
4. "Eugene Wigner Fellowship". www.ornl.gov. Oak Ridge National Laboratory. Retrieved 2023-08-24.
5. Sugihara, G. (1983). "Graph theory, homology, and food webs". Proc. Symp. Appl. Math. 30: 83–101. doi:10.1090/psapm/030/73864.
6. Sugihara, G., and H. Ye. Cooperative Network Dynamics. Nature458, 979-980
7. Scheffer, M; Bascompte, J; Brock, WA; Brovkin, V; Carpenter, S R; Dakos, V; Held, H; Rietkerk, M; Sugihara, G; et al. (2009). "Early-warning signals for critical transitions". Nature. 461 (7260): 53–59. Bibcode:2009Natur.461...53S. doi:10.1038/nature08227. PMID   19727193. S2CID   4001553.
8. Sugihara, G.; May, R. M. (1990). "Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series". Nature. 344 (6268): 734–741. Bibcode:1990Natur.344..734S. doi:10.1038/344734a0. PMID   2330029. S2CID   4370167.
9. Sugihara, G. (1994). "Nonlinear forecasting for the classification of natural time series". Philosophical Transactions: Physical Sciences and Engineering. 348: 477–495. doi:10.1098/rsta.1994.0106.
10. Sugihara, G. 2006. Observations on new directions for understanding systemic risk in the financial sector. Federal Reserve Bank of New York and the National Academy of Science.
11. May, R.M.; Levin, S.A.; Sugihara, G. (2008). "Complex systems: Ecology for bankers". Nature. 451 (7181): 893–895. Bibcode:2008Natur.451..893M. doi: 10.1038/451893a . PMID   18288170.
12. Dalton, Rex (2005). "Conservation policy: Fishy futures". Nature. 437 (7058): 473–474. Bibcode:2005Natur.437..473D. doi: 10.1038/437473a . PMID   16177759.
13. "Alaska Pollock". www.fisheries.noaa.gov. National Oceanic and Atmospheric Administration. Retrieved 2023-08-24.
14. Sugihara, G.; Criddle, K.R.; McQuown, M. (2018). "Comprehensive incentives for reducing Chinook salmon bycatch in the Bering Sea walleye Pollock fishery: Individual tradable encounter credits". Regional Studies in Marine Science. 22: 70–81. doi:10.1016/j.rsma.2018.06.002.
15. Sugihara, G., and H. Ye. (2009). Cooperative Network Dynamics. Nature458, 979-980. https://doi.org/10.1038/458979a
16. Scheffer, M; Bascompte, J; Brock, WA; Brovkin, V; Carpenter, S R; Dakos, V; Held, H; Rietkerk, M; Sugihara, G; et al. (2009). "Early-warning signals for critical transitions". Nature. 461 (7260): 53–59. Bibcode:2009Natur.461...53S. doi:10.1038/nature08227. PMID   19727193. S2CID   4001553.
17. DeAngelis, Donald L.; Yurek, Simeon (2015). "Equation-free modeling unravels the behavior of complex ecological systems". Proceedings of the National Academy of Sciences. 112 (13): 3856–3857. doi:10.1073/pnas.1503154112.
18. Chang, C; Ushio, M (2017). "Empirical dynamic modeling for beginners". Ecol Res. 32 (6): 785–796. doi:10.1007/s11284-017-1469-9.
19. Sugihara, G.; May, R. (2012). "Detecting Causality in Complex Ecosystems". Science. 338: 496–500. doi:10.1126/science.1227079.