Population assessment using multivariate time‐series analysis: A case study of rockfishes in Puget Sound
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Gregory D. Williams | Robert E. Pacunski | Gregory D Williams | N. Tolimieri | Nick Tolimieri | Elizabeth E Holmes | Robert Pacunski | Dayv Lowry | D. Lowry | E. Holmes
[1] Brian Dennis,et al. A better way to estimate population trends , 2009 .
[2] Brian Dennis,et al. Replicated sampling increases efficiency in monitoring biological populations. , 2010, Ecology.
[3] D. Brito,et al. Unraveling the conservation status of Data Deficient species , 2013 .
[4] Ben Lomond Wallflower. 5-Year Review: Summary and Evaluation , 2008 .
[5] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[6] Jonas Knape,et al. ESTIMABILITY OF DENSITY DEPENDENCE IN MODELS OF TIME SERIES DATA. , 2008, Ecology.
[7] Sean R Connolly,et al. Diversity and stability of herbivorous fishes on coral reefs. , 2012, Ecology.
[8] Mark Hebblewhite,et al. The importance of observation versus process error in analyses of global ungulate populations , 2013, Scientific Reports.
[9] Steven V. Viscido,et al. A statistical approach to quasi-extinction forecasting. , 2007, Ecology letters.
[10] Eric J Ward,et al. Quantifying effects of abiotic and biotic drivers on community dynamics with multivariate autoregressive (MAR) models. , 2013, Ecology.
[11] E. E. Holmes,et al. Viability Analysis for Endangered Metapopulations: A Diffusion Approximation Approach , 2004 .
[12] Elizabeth E. Holmes,et al. MARSS: Multivariate Autoregressive State-space Models for Analyzing Time-series Data , 2012, R J..
[13] P. Macreadie,et al. Assessing the risk of carbon dioxide emissions from blue carbon ecosystems , 2017 .
[14] A. Zuur,et al. Dynamic factor analysis to estimate common trends in fisheries time series , 2003 .
[15] David R. Anderson,et al. Model Selection and Inference: A Practical Information-Theoretic Approach , 2001 .
[16] E. E. Holmes,et al. Estimating risks in declining populations with poor data , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[17] Jeremy P. Bird,et al. Data Deficient birds on the IUCN Red List: What don’t we know and why does it matter? , 2010 .
[18] S. Andelman,et al. A review of protocols for selecting species at risk in the context of US Forest Service viability assessments , 2004 .
[19] S. Carpenter,et al. ESTIMATING COMMUNITY STABILITY AND ECOLOGICAL INTERACTIONS FROM TIME‐SERIES DATA , 2003 .
[20] Robert H. Shumway,et al. Time series analysis and its applications : with R examples , 2017 .
[21] Gregory D. Williams,et al. Rockfish in Puget Sound: An ecological history of exploitation , 2010 .
[22] D. Doak,et al. Book Review: Quantitative Conservation biology: Theory and Practice of Population Viability analysis , 2004, Landscape Ecology.
[23] P. Levin,et al. Costs of Delaying Conservation: Regulations and the Recreational Values of Exploited and Co-occurring Species , 2013, Land Economics.
[24] Elizabeth E. Holmes,et al. Using multivariate state-space models to study spatial structure and dynamics , 2008 .
[25] S. T. Bucklanda,et al. State-space models for the dynamics of wild animal populations , 2003 .
[26] Jonas Knape,et al. Estimating environmental effects on population dynamics: consequences of observation error , 2009 .
[27] Andrew Harvey,et al. Forecasting, Structural Time Series Models and the Kalman Filter , 1990 .
[28] Elizabeth E. Holmes,et al. BEYOND THEORY TO APPLICATION AND EVALUATION: DIFFUSION APPROXIMATIONS FOR POPULATION VIABILITY ANALYSIS , 2004 .
[29] André E. Punt,et al. Reconciling Approaches to the Assessment and Management of Data-Poor Species and Fisheries with Australia's Harvest Strategy Policy , 2009 .
[30] Emily J. Whitney,et al. Historical Patterns and Drivers of Spatial Changes in Recreational Fishing Activity in Puget Sound, Washington , 2016, PloS one.
[31] Elizabeth E. Holmes,et al. 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 , 2010 .
[32] Helen M. Regan,et al. Combined Influences of Model Choice, Data Quality, and Data Quantity When Estimating Population Trends , 2015, PloS one.
[33] Brian Dennis,et al. Estimation of Growth and Extinction Parameters for Endangered Species , 1991 .
[34] T. Pietsch,et al. Fishes of the Salish Sea : a compilation and distributional analysis , 2015 .
[35] M. Love,et al. The Rockfishes of the Northeast Pacific , 2002 .
[36] Perry de Valpine,et al. Using uncertainty estimates in analyses of population time series. , 2013, Ecology.
[37] Daniel E. Schindler,et al. The portfolio concept in ecology and evolution , 2015 .
[38] A. Agresti,et al. Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions , 1998 .
[39] R. Hilborn,et al. Biocomplexity and fisheries sustainability , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[40] S. Lele,et al. ESTIMATING DENSITY DEPENDENCE, PROCESS NOISE, AND OBSERVATION ERROR , 2006 .