pubs via zotero

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.
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.
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.
Munch, S. B., Rogers, T. L., & Sugihara, G. (2022). Recent developments in empirical dynamic modelling. Methods in Ecology and Evolution, 2041-210X.13983.
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.
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.
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.
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.
Giron-Nava, A., Ezcurra, E., Brias, A., Velarde, E., Deyle, E., Cisneros-Montemayor, A. M., Munch, S. B., Sugihara, G., & Aburto-Oropeza, O. (2021). Environmental variability and fishing effects on the Pacific sardine fisheries in the Gulf of California. Canadian Journal of Fisheries and Aquatic Sciences, 78(5), 623–630.
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. PLOS ONE, 16(5).
Li, J. J., Zyphur, M. J., Sugihara, G., & Laub, P. J. (2021). Beyond linearity, stability, and equilibrium: The edm package for empirical dynamic modeling and convergent cross-mapping in Stata. Stata Journal, 21(1), 220–258.
Natsukawa, H., Deyle, E. R., Pao, G. M., Koyamada, K., & Sugihara, G. (2021). A visual analytics approach for ecosystem dynamics based on empirical dynamic modeling. Ieee Transactions on Visualization and Computer Graphics, 27(2), 506–516.
Choi, E. S., Saberski, E., Lorimer, T., Smith, C., Kandage-don, U., Burton, R. S., & Sugihara, G. (2020). The importance of making testable predictions: A cautionary tale. PLOS ONE, 15(12).
Nova, N., Deyle, E. R., Shocket, M. S., MacDonald, A. J., Childs, M. L., Rypdal, M., Sugihara, G., & Mordecai, E. A. (2020). Susceptible host availability modulates climate effects on dengue dynamics. Ecology Letters.
Kuriyama, P. T., Sugihara, G., Thompson, A. R., & Semmens, B. X. (2020). Identification of shared spatial dynamics in temperature, salinity, and ichthyoplankton community diversity in the California Current system with empirical dynamic modeling. Frontiers in Marine Science, 7.
Chang, C. W., Ye, H., Miki, T., Deyle, E. R., Souissi, S., Anneville, O., Adrian, R., Chiang, Y. R., Ichise, S., Kumagai, M., Matsuzaki, S. S., Shiah, F. K., Wu, J. T., Hsieh, C. H., & Sugihara, G. (2020). Long-term warming destabilizes aquatic ecosystems through weakening biodiversity-mediated causal networks. Global Change Biology.
Munch, S. B., Brias, A., Sugihara, G., & Rogers, T. L. (2020). Frequently asked questions about nonlinear dynamics and empirical dynamic modelling. ICES Journal of Marine Science, 77(4), 1463–1479.
Giron-Nava, A., Munch, S. B., Johnson, A. F., Deyle, E., James, C. C., Saberski, E., Pao, G. M., Aburto-Oropeza, O., & Sugihara, G. (2020). Circularity in fisheries data weakens real world prediction. Scientific Reports, 10(1).
Cenci, S., Medeiros, L. P., Sugihara, G., & Saavedra, S. (2020). Assessing the predictability of nonlinear dynamics under smooth parameter changes. Journal of The Royal Society Interface, 17(162), 20190627.
Lee, S. W., Yon, D. K., James, C. C., Lee, S., Koh, H. Y., Sheen, Y. H., Oh, J. W., Han, M. Y., & Sugihara, G. (2019). Short-term effects of multiple outdoor environmental factors on risk of asthma exacerbations: Age-stratified time-series analysis. Journal of Allergy and Clinical Immunology, 144(6), 1542-+.
Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E., Glymour, C., Kretschmer, M., Mahecha, M. D., Munoz-Mari, J., van Nes, E. H., Peters, J., Quax, R., Reichstein, M., Scheffer, M., Scholkopf, B., Spirtes, P., Sugihara, G., Sun, J., … Zscheischler, J. (2019). Inferring causation from time series in Earth system sciences. Nature Communications, 10.
Cenci, S., Sugihara, G., & Saavedra, S. (2019). Regularized S-map for inference and forecasting with noisy ecological time series. Methods in Ecology and Evolution, 10(5), 650–660.
Rypdal, M., & Sugihara, G. (2019). Inter-outbreak stability reflects the size of the susceptible pool and forecasts magnitudes of seasonal epidemics. Nature Communications, 10.
Munch, S. B., Giron-Nava, A., & Sugihara, G. (2018). Nonlinear dynamics and noise in fisheries recruitment: A global meta-analysis. Fish and Fisheries, 19(6), 964–973.
Deyle, E., Schueller, A. M., Ye, H., Pao, G. M., & Sugihara, G. (2018). Ecosystem-based forecasts of recruitment in two menhaden species. Fish and Fisheries, 19(5), 769–781.
Sugihara, G., Criddle, K. R., McQuown, M., Giron-Nava, A., Deyle, E., James, C., Lee, A., Pao, G., Saberski, E., & Ye, H. (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.
Ushio, M., Hsieh, C. H., Masuda, R., Deyle, E. R., Ye, H., Chang, C. W., Sugihara, G., & Kondoh, M. (2018). Fluctuating interaction network and time-varying stability of a natural fish community. Nature, 554(7692), 360-+.
Arndt, T., Florian, G., Philip, C., Takeshi, M., James, W. M., George, S., Stephen, L. D., & Chih-hao, H. (2017). Infections of Wolbachia may destabilize mosquito population dynamics. Journal of Theoretical Biology, 428(Supplement C), 98–105.
Giron-Nava, A., James, C. C., Johnson, A. F., Dannecker, D., Kolody, B., Lee, A., Nagarkar, M., Pao, G. M., Ye, H., Johns, D. G., & Sugihara, G. (2017). Quantitative argument for long-term ecological monitoring. Marine Ecology Progress Series, 572, 269–274.
McGowan, J. A., Deyle, E. R., Ye, H., Carter, M. L., Perretti, C. T., Seger, K. D., de Verneil, A., & Sugihara, G. (2017). Predicting coastal algal blooms in Southern California. Ecology.
Dakos, V., Glaser, S. M., Hsieh, C. H., & Sugihara, G. (2017). Elevated nonlinearity as an indicator of shifts in the dynamics of populations under stress. Journal of the Royal Society Interface, 14(128).
Sugihara, G. (2017). Niche hierarchy: Structure, organization, and assembly in natural systems. J. Ross Publishing.
Deyle, E. R., Maher, M. C., Hernandez, R. D., Basu, S., & Sugihara, G. (2016). Global environmental drivers of influenza. Proceedings of the National Academy of Sciences of the United States of America, 113(46), 13081–13086.
Ye, H., & Sugihara, G. (2016). Information leverage in interconnected ecosystems: Overcoming the curse of dimensionality. Science, 353(6302), 922–925.
Rikkert, M., Dakos, V., Buchman, T. G., de Boer, 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.
Deyle, E. R., May, R. M., Munch, S. B., & Sugihara, G. (2016). Tracking and forecasting ecosystem interactions in real time. Proceedings of the Royal Society B-Biological Sciences, 283(1822).
Ye, H., Deyle, E. R., Gilarranz, L. J., & Sugihara, G. (2015). Distinguishing time-delayed causal interactions using convergent cross mapping. Scientific Reports, 5.
Clark, A. T., Ye, H., Isbell, F., Deyle, E. R., Cowles, J., Tilman, G. D., & Sugihara, G. (2015). Spatial convergent cross mapping to detect causal relationships from short time series. Ecology, 96(5), 1174–1181.
van Nes, E. H., Scheffer, M., Brovkin, V., Lenton, T. M., Ye, H., Deyle, E., & Sugihara, G. (2015). Causal feedbacks in climate change. Nature Climate Change, 5(5), 445–448.
Ye, H., Beamish, R. J., Glaser, S. M., Grant, S. C. H., Hsieh, C. H., Richards, L. J., Schnute, J. T., & Sugihara, G. (2015). Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling. Proceedings of the National Academy of Sciences of the United States of America, 112(13), E1569–E1576.
Tsonis, A. A., Deyle, E. R., May, R. M., Sugihara, G., Swanson, K., Verbeten, J. D., & Wang, G. L. (2015). Dynamical evidence for causality between galactic cosmic rays and interannual variation in global temperature. Proceedings of the National Academy of Sciences of the United States of America, 112(11), 3253–3256.
Liu, H., Fogarty, M. J., Hare, J. A., Hsieh, C. H., Glaser, S. M., Ye, H., Deyle, E., & Sugihara, G. (2014). Modeling dynamic interactions and coherence between marine zooplankton and fishes linked to environmental variability. Journal of Marine Systems, 131, 120–129.
Glaser, S. M., Ye, H., & Sugihara, G. (2014). A nonlinear, low data requirement model for producing spatially explicit fishery forecasts. Fisheries Oceanography, 23(1), 45–53.
National Research Council (Ed.). (2014). Evaluating the Effectiveness of Fish Stock Rebuilding Plans in the United States. The National Academies Press.
Deyle, E. R., Fogarty, M., Hsieh, C. H., Kaufman, L., MacCall, A. D., Munch, S. B., Perretti, C. T., Ye, H., & Sugihara, G. (2013). Predicting climate effects on Pacific sardine. Proceedings of the National Academy of Sciences of the United States of America, 110(16), 6430–6435.
Perretti, C. T., Sugihara, G., & Munch, S. B. (2013). Nonparametric forecasting outperforms parametric methods for a simulated multispecies system. Ecology, 94(4), 794–800.
Glaser, S. M., Fogarty, M. J., Liu, H., Altman, I., Hsieh, C.-H., Kaufman, L., MacCall, A. D., Rosenberg, A. A., Ye, H., & Sugihara, G. (2013). Complex dynamics may limit prediction in marine fisheries. Fish and Fisheries, n/a-n/a.
Perretti, C. T., Munch, S. B., & Sugihara, G. (2013). Model-free forecasting outperforms the correct mechanistic model for simulated and experimental data. Proceedings of the National Academy of Sciences of the United States of America, 110(13), 5253–5257.
National Research Council. (2013). Abrupt Impacts of Climate Change: Anticipating Surprises (978-0-309-28773–9; p. 250). The National Academies Press.
Sugihara, G., May, R., Ye, H., Hsieh, C. H., Deyle, E., Fogarty, M., & Munch, S. (2012). Detecting causality in complex ecosystems. Science, 338(6106), 496–500.