Publications

2024

  • Park, J., Sugihara, G., & Pao, G. (2024). Control of complex systems with generalized embedding and empirical dynamic modeling. PLOS ONE, 19(8), e0305408. https://doi.org/10.1371/journal.pone.0305408
  • Carpenter, D., Saberski, E. R., Deyle, E. R., Park, J., & Sugihara, G. (2024). Exploiting complexity to repair ecological time series (In Press). Methods in Ecology and Evolution, 14(3).
  • Saberski, E. R., Lorimer, T., Carpenter, D., Deyle, E. R., Mertz, E., Park, J., Pao, G., & Sugihara, G. (2024). The Impact of Data Resolution on Dynamic Causal Inference in Multiscale Ecological Networks (In press). Nature Communications, 14(1).

2023

  • Zhao, Q., Van Den Brink, P. J., Xu, C., Wang, S., Clark, A. T., Karakoç, C., Sugihara, G., Widdicombe, C. E., Atkinson, A., Matsuzaki, S. S., Shinohara, R., He, S., Wang, Yingying. X. G., & De Laender, F. (2023). Relationships of temperature and biodiversity with stability of natural aquatic food webs. Nature Communications, 14(1), 3507. https://doi.org/10.1038/s41467-023-38977-6
  • Gao, B., Yang, J., Chen, Z., Sugihara, G., Li, M., Stein, A., Kwan, M.-P., & Wang, J. (2023). Causal inference from cross-sectional earth system data with geographical convergent cross mapping. Nature Communications, 14(1), 5875. https://doi.org/10.1038/s41467-023-41619-6
  • Merz, E., Saberski, E., Gilarranz, L. J., Isles, P. D. F., Sugihara, G., Berger, C., & Pomati, F. (2023). Disruption of ecological networks in lakes by climate change and nutrient fluctuations. Nature Climate Change, 13(4), 389–396. https://doi.org/10.1038/s41558-023-01615-6

2022

  • Park, J., Pao, G. M., Sugihara, G., Stabenau, E., & Lorimer, T. (2022). Empirical mode modeling A data-driven approach to recover and forecast nonlinear dynamics from noisy data. Nonlinear Dynamics, 14. https://doi.org/10.1007/s11071-022-07311-y
  • Deyle, E. R., Bouffard, D., Frossard, V., Schwefel, R., Melack, J., & Sugihara, G. (2022). A hybrid empirical and parametric approach for managing ecosystem complexity: Water quality in Lake Geneva under nonstationary futures. Proceedings of the National Academy of Sciences, 119(26), e2102466119. https://doi.org/10.1073/pnas.2102466119
  • Munch, S. B., Rogers, T. L., & Sugihara, G. (2022). Recent developments in empirical dynamic modelling. Methods in Ecology and Evolution, 2041-210X.13983. https://doi.org/10.1111/2041-210X.13983
  • Saberski, E., Park, J., Hill, T., Stabenau, E., & Sugihara, G. (2022). Improved Prediction of Managed Water Flow into Everglades National Park Using Empirical Dynamic Modeling. Journal of Water Resources Planning and Management, 148(12), 10. https://doi.org/10.1061/(asce)wr.1943-5452.0001598
  • Chen, Z., Xu, M., Gao, B., Sugihara, G., Shen, F., Cai, Y., Li, A., Wu, Q., Yang, L., Yao, Q., Chen, X., Yang, J., Zhou, C., & Li, M. (2022). Causation inference in complicated atmospheric environment. Environmental Pollution, 303, 119057. https://doi.org/10.1016/j.envpol.2022.119057
  • Medeiros, L. P., Allesina, S., Dakos, V., Sugihara, G., & Saavedra, S. (2022). Ranking species based on sensitivity to perturbations under non‐equilibrium community dynamics. Ecology Letters, ele.14131. https://doi.org/10.1111/ele.14131

2021

  • Lorimer, T., Goodridge, R., Bock, A. K., Agarwal, V., Saberski, E., Sugihara, G., & Rifkin, S. A. (2021). Tracking changes in behavioural dynamics using prediction error. PLOSONE, 16(5).  https://doi.org/10.1371/journal.pone.0251053
  • Park, J., Saberski, E., Stabenau, E., & Sugihara, G. (2021). Dynamics of Florida milk production and total phosphate in Lake Okeechobee. PLOS ONE, 16(8), 10. https://doi.org/10.1371/journal.pone.0248910
  • Pao, G. M., Smith, C., Park, J., Takahashi, K., Watanakeesuntorn, W., Natsukawa, H., Chalasani, S. H., Lorimer, T., Takano, R., Rungratsameetaweemana, N., & Sugihara, G. (2021). Experimentally testable whole brain manifolds that recapitulate behavior. arXiv. https://doi.org/10.48550/ARXIV.2106.10627

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

  • Sala, E., & Sugihara, G. (2004). Food-web theory provides guidelines for marine conservation. Aquatic food webs: an ecosystem approach (pp. 170-183). Oxford: Oxford University Press.

2003

2001

  • Dixon, P., Milicich, M. J., & Sugihara, G. (2001). Noise and nonlinearity in an ecological system. Nonlinear dynamics and statistics (pp. 339-364). Boston: Birkhhauser.

2000

1999

1998

1997

1996

  • Sugihara, G., Allan, W., Sobel, D., & Allan, K. D. (1996). Nonlinear control of heart rate variability in human infants. Proceedings of the National Academy of Sciences of the United States of America, 93(6), 2608-2613. doi: 10.1073/pnas.93.6.2608
  • Bersier, L. F., & Sugihara, G. (1996). Scale invariance versus size dependence in food web properties. Rev. Suisse Zool., 103, 799.
  • Bersier, L. F., & Sugihara, G. (1996). A correspondence between two classical notions of community structure. Rev. Suisse Zool., 102, 855.

1995

1994

1993

1990

1989

1988

1987

1986

1984

1983

  • Siegel, A. F., & Sugihara, G. (1983). Moments of particle size distributions under sequential breakage with applications to species abundance. Journal of Applied Probability, 20(1), 158-164. doi: 10.2307/3213730
  • DeAngelis, D. L., Post, W. M., & G., S. (1983). Current trends in food web theory (Report on a food web workshop, October 25-27, 1982, Fontana Village Inn, North Carolina). , 137.
  • Sugihara, G. (1983). Holes in niche space: a derived assembly rule and its relation to intervality. Current trends in food web theory (Report on a food web workshop, October 25-27, 1982, Fontana Village Inn, North Carolina) (pp. 25-36). Oak Ridge, Tenn.: Oak Ridge National Laboratory.
  • Sugihara, G. (1983): Minimal community structure: an explanation of species abundance patterns. Reprinted in the series “Benchmark Papers in Ecology,” ed. Frank B. Golley
  • Sugihara, G. Peeling apart nature. Nature 304, 94 (1983). https://doi.org/10.1038/304094a0

1982

1981

1980