Applied Time Series Analysis

for Fisheries and Environmental Sciences

Course Website
Lectures pdfs, lectures, course handouts and exercises.
2021 Lecture Playlist
Prior year versions of the course 2017 2019 2021
Book
Online book based on the course and computer labs.
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R Packages available on CRAN and GitHub

MARSS
Multivariate Autoregressive State-Space Modeling with R. Includes a book: Analysis of multivariate time series using the MARSS package.
atsar
Applied time series analysis in R with Stan. Fast fitting of Bayesian multivariate time-series models. See our ATSA book for applications.
mvdlm
Multivariate dynamic linear models with Stan. Extends DLM models in MARSS to be fit in a Bayesian framework with Stan.
tvvarss
Time-varying vector autoregressive state-space modeling of community interactions. Fit time-varying B matrices in a Bayesian framework.
varlasso
Bayesian VAR models with shrinkage on coefficient estimates Uses Stan to fit VAR state space models with optional shrinkage priors on B matrix elements.
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Please see our individual websites for our contact information

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Our publications related to multivariate time-series analysis

This is a selection of our papers using multivariate time-series modeling. See our individual websites for our publications on other topics.

  • Ward, E. J., K. Oken, K. A. Rose, S. Sable, K. Watkins, E. E. Holmes, and M. D. Scheuerell. 2018. Applying spatiotemporal models to monitoring data to quantify fish responses to the Deepwater Horizon oil spill in the Gulf of Mexico. Environmental Monitoring and Assessment 190:530. https://doi.org/10.1007/s10661-018-6912-z

  • Ward, E. J., M. Adkison, J. Couture, S. C. Dressel, M. A. Litzow, S. Moffitt, T. Hoem Neher, J. Trochta, and R. Brenner. 2017. Evaluating signals of oil spill impacts, climate, and species interactions in Pacific herring and Pacific salmon populations in Prince William Sound and Copper River, Alaska. PLOS ONE, 12(3): e0172898.

  • Holmes, E. E., M. D. Scheuerell, and E. J. Ward. 2017. Applied Time Series Analysis for Fisheries and Environmental Sciences. Online text for our course at University of Washington. Online

  • Tolimieri, N., E. E. Holmes, G. D. Williams, R. Pacunski, and D. Lowry. 2017. Population assessment using multivariate time-series analysis: A case study of rockfishes in Puget Sound. Ecology and Evolution 7(8): 2045-7758. PDF

  • Goertler, P. A. L., M. D. Scheuerell, C. A. Simenstad, D. L. Bottom. 2016. Estimating common growth patterns in juvenile Chinook salmon (Oncorhynchus tshawytscha) from diverse genetic stocks and a large spatial extent. PLoS ONE 11:e0162121 PDF

  • Ohlberger J., M. D. Scheuerell, and D. E. Schindler. 2016. Population coherence and environmental impacts across spatial scales: a case study of Chinook salmon. Ecosphere 7:e01333 PDF

  • Jorgensen J. C., E. J. Ward, M. D. Scheuerell, and R. W. Zabel. 2016. Assessing spatial covariance among time series of abundance. Ecology and Evolution 6:2472–2485 PDF

  • Scheuerell, M. D., E. R. Buhle, B. X. Semmens, M. J. Ford, T. Cooney, R. W. Carmichael. 2015. Analyzing large-scale conservation interventions with Bayesian hierarchical models: A case study of supplementing threatened Pacific salmon. Ecology and Evolution 5:2115–2125 PDF

  • Ford, M. J., K. Barnas, T. Cooney, L. G. Crozier, M. Diaz, J. J. Hard, E. E. Holmes, D. M. Holzer, R. G. Kope, P. W. Lawson, M. Liermann, J. M. Myers, M. Rowse, D. J. Teel, D. M. Van Doornik, T. C. Wainwright, L. A. Weitkamp, M. Williams. 2015. Status Review Update for Pacific Salmon and Steelhead Listed under the Endangered Species Act: Pacific Northwest. National Marine Fisheries Service, Northwest Fisheries Science Center. PDF

  • Ruhi, A., E. E. Holmes, J. N. Rinne, and J. L. Sabo. 2015. Anomalous droughts, not invasion, decrease persistence of native fishes in a desert river. Global Change Biology 21:1482-1496. html PDF

  • See, K. E. and E. E. Holmes. 2015. Reducing bias and improving precision in species extinction forecasts. Ecological Applications 25: 1157-1165.

  • Lisi P. J., D. E. Schindler, T. J. Cline, M. D. Scheuerell, P. B. Walsh. 2015. Topography and snowmelt control stream thermal sensitivity to air temperature. Geophysical Research Letters 42:3380-3388 PDF

  • Griffiths J. R, D. E. Schindler, J. B. Armstrong, M. D. Scheuerell, D. C. Whited, R. A. Clarke, R. Hilborn, C. A. Holt, S. T. Lindley, J. A. Stanford, and E. C. Volk. 2014. Performance of salmon fishery portfolios across western North America. Journal of Applied Ecology 51:1554–1563

  • Francis, T. B., E. M. Wolkovich, M. D. Scheuerell, S. L. Katz, E. E. Holmes, and S. E. Hampton. 2014. Shifting Regimes and Changing Interactions in the Lake Washington, USA, Plankton Community from 1962-1994. PlosOne e110363. PDF

  • Holmes, E. E. 2014. Computation of standardized residuals for (MARSS) models. Technical Report. arXiv:1411.0045 PDF

  • Ward, E. J., E. E. Holmes, J. T. Thorson, and B. Collen. 2014. Complexity is costly: a meta-analysis of parametric and non-parametric methods for short-term population forecasting. Oikos, 123(6): 652-661. PDF

  • Hampton, S. E., E. E. Holmes, D. E. Pendleton, L. P. Scheef, M. D. Scheuerell, and E. J. Ward. 2013. Quantifying effects of abiotic and biotic drivers on community dynamics with multivariate autoregressive (MAR) models. Ecology 94(12): 2663-2669. PDF

  • Holmes, E. E. 2013. Derivation of the EM algorithm for constrained and unconstrained multivariate autoregressive state-space (MARSS) models. Technical Report. arXiv:1302.3919 PDF

  • Holmes, E. E., E. J. Ward, and K. Wills. 2012. MARSS: multivariate autoregressive state-space models for analyzing time series data. R Journal 4(1): 11-19. PDF

  • Scheef, L. P., D. E. Pendleton, S. E. Hampton, S. L. Katz, E. E. Holmes, M. D. Scheuerell, and D. G. Johns. 2012. Assessing marine plankton community structure from long-term monitoring data with multivariate autoregressive (MAR) models: a comparison of fixed station vs. spatially distributed sampling data. Limnology & Oceanography: Methods 10: 54-64. PDF

  • Francis T. B., M. D. Scheuerell, R. Brodeur, P. S. Levin, J. J. Ruzicka, N. Tolimieri, and W. T. Peterson. 2012. Climate shifts the interaction web of a marine plankton community. Global Change Biology 18:2498–2508

  • Crozier L. G., M. D. Scheuerell, and R. W. Zabel. 2011. Using time series analysis to characterize evolutionary and plastic responses to environmental change: a case study of a shift toward earlier migration date in sockeye salmon. The American Naturalist 178:755-773

  • Pattengill-Semmens, C. V., Semmens, B. X., E. E. Holmes, E. J. Ward, and B. I. Ruttenberg. 2011. Integrating time-series of community monitoring data. Proceedings of the Gulf and Caribbean Fisheries Institute 63: 214-216. PDF

  • Drake, J., E. A. Berntson, J. M. Cope, R. G. Gustafson, E. E. Holmes, P. S. Levin, N. Tolimieri, R. S. Waples, S. Sogard, and G. D. Williams. 2010. Status review of five rockfish species in Puget Sound, Washington: Bocaccio (Sebastes paucispinis), canary rockfish (S. pinniger), yelloweye rockfish (S. ruberrimus), greenstriped rockfish (S. elongatus), and redstripe rockfish (S. proriger). U.S. Dept. of Commerce, NOAA Tech. Memo., NMFS-NWFSC-108. PDF

  • Ward, E. J., H. Chirrakal, M. Gonzalez-Suarez, D. Aurioles-Gamboa, E. E. Holmes, and L. Gerber. 2010. Inferring spatial structure from time-series data: using multivariate state-space models to detect metapopulation structure of California sea lions in the Gulf of California, Mexico. Journal of Applied Ecology 47: 47-56. PDF

  • Holmes, E. E. and E. J. Ward. 2010. Analysis of multivariate time series using the MARSS package PDF. User Guide for the MARSS R package

  • Viscido, S. V. and E. E. Holmes. 2010. Statistical modelling of communities and ecosystems using the LAMDA software tool. Environmental Modelling and Software 25(12): 1905-1908. PDF

  • Holmes, E. E., J. L. Sabo, S. V. Viscido, and W. Fagan. 2007. A statistical approach to quasi-extinction forecasting. Ecology Letters 10:1182-1198

  • Hampton S. E., M. D. Scheuerell, and D. E. Schindler. 2006. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnology and Oceanography 51:2042-2051

  • Holmes, E. E., W. F. Fagan, J. J. Rango, A. Folarin, J. A. Sorensen, J. E. Lippe, and N. E. McIntyre. 2005. Cross-validation of quasi-extinction risks from real time series: an examination of diffusion approximation methods. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-67, 37 p.

  • Holmes, E. E. 2004. Beyond theory to application and evaluation: diffusion approximations for population viability analysis. Ecological Applications 14: 1272-1293.

  • Holmes, E. E. and B. Semmens. 2004. Population viability analysis for metapopulations: a diffusion approximation approach. Pp. 565-598 in Ecology, Genetics, and Evolution of Metapopulations, editors Illka Hanski and Oscar E. Gaggiotti. Elsevier Press.

  • McClure, M. M., E. E. Holmes, B. L. Sanderson, and C. E. Jordan. 2003. A large-scale, multi-species risk assessment: anadromous salmonids in the Columbia River Basin. Ecological Applications 13(4):964-989.

  • Holmes, E. E. and W. F. Fagan. 2002. Validating population viability analysis for corrupted data sets. Ecology 83: 2379-2386.

  • Holmes, E. E. 2001. Estimating risks in declining populations with poor data. Proceedings of the National Academy of Science 98: 5072-5077.

The material on this website was produced by E Holmes, M Scheuerell and E Ward working as a US Federal employees. Content on this website is a government work in the public domain in the U.S. and under the CC0 1.0 internationally.
The website design is based on the SinglePaged Theme by Tim O’Brien