Abstract
This paper uses Generalized Additive Models to evaluate model-based designs for wildlife abundance surveys where substantial pre-existing data are available. This is often the case in fisheries with historical catch and effort data. Compared to conventional stratified design or design-based designs, our model-based designs can be both efficient and flexible, for example in allowing uneven sampling due to survey logistics, and providing a general framework to answer specific design questions. As an example, we describe the design and preliminary implementation of a trawl survey for eleven fish species along the continental slope off South-East Australia.
Similar content being viewed by others
References
Arbia, G., and Lafratta, G. (2002), “Anisotropic Spatial Sampling Designs for Urban Pollution,” Journal of the Royal Statistical Society Series C, 51, 223–234.
Breslow, N., and Clayton, D. (1993), “Approximate Inference in Generalized Linear Mixed Models,” Journal of the American Statistical Association, 88, 9–25.
Britt, L., and Martin, M. (2001), “Data Report: 1999 Gulf of Alaska Bottom Trawl Survey. US Department of Commerce,” NOAA Technical Memorandum NMFS-AFSC-121.
Brus, D. J., and deGruijter, J. J. (1997), “Random Sampling or Geostatistical Modelling? Choosing Between Design-Based and Model-Based Sampling Strategies for Soil (with Discussion),” Geoderma, 80, 1–44.
Brus, D. J., and Heuvelink, G. (2007), “Optimization of Sample Patterns for Universal Kriging of Environmental Variables,” Geoderma, 138, 86–95.
Candy, S. G. (2004), “Modelling Catch and Effort Data Using Generalised Linear Models, the Tweedie Distribution, Random Vessel Effects and Random Stratum-by-Year Effects,” CCAMLR Science, 11, 59–80.
Cotter, A. (2001), “Intercalibration of North Sea International Bottom Trawl Surveys by Fitting Year-Class Curves,” ICES Journal of Marine Science, 58, 622–632.
Curtis, A. (1999), “Optimal Design of Focused Experiments and Surveys,” Geophysical Journal International, 139, 205–215.
Diggle, P., and Lophaven, S. (2006), “Bayesian Geostatistical Design,” Scandinavian Journal of Statistics, 33, 53–64.
Doubleday, W. (1981), Manual on Groundfish Surveys in the Northwest Atlantic. Northwest Atlantic Fisheries Organization.
Dunn, P. K. (2009), “Improving Comparisons Between Models for CPUE,” Fisheries Research, 97, 148–149.
Dunn, P. K., and Smyth, G. K. (1996), “Randomized Quantile Residuals,” Journal of Computational and Graphical Statistics, 5, 236–244.
— (2001), “Tweedie Family Densities: Methods of Evaluation,” in Proceedings of the 16th International Workshop on Statistical Modelling, Odense, Denmark, pp. 155–162.
— (2005), “Series Evaluation of Tweedie Exponential Dispersion Model Densities,” Statistics and Computing, 15, 267–280.
Gao, H. Y., Wang, J. H., and Zhao, P. D. (1996), “The Updated Kriging Variance and Optimal Sample Design,” Mathematical Geology, 28, 295–313.
Hastie, T., and Tibshirani, R. (1986), “Generalized Additive Models (with Discussion),” Statistical Science, 1, 297–318.
— (1990), Generalized Additive Models, London: Chapman and Hall.
Jolly, G., and Hampton, I. (1990), “A Stratified Random Transect Design for Acoustic Surveys of Fish Stocks,” Canadian Journal of Fisheries and Aquatic Sciences, 47, 1282–1291.
Jørgensen, B. (1987), “Exponential Dispersion Models,” Journal of the Royal Statistical Society Series B, 49, 127–162.
— (1997), Theory of Dispersion Models, London: Chapman and Hall.
Michaelsen, J., Schimel, D. S., Friedl, M. A., Davis, F. W., and Dubayah, R. C. (1994), “Regression Tree Analysis of Satellite and Terrain Data to Guide Vegetation Sampling and Surveys,” Journal of Vegetation Science, 5, 673–686.
Minami, M., Lennert-Cody, C. E., Gao, W., and Roman-Verdesoto, M. (2007), “Modeling Shark Bycatch: The Zero-Inflated Negative Binomial Regression Model with Smoothing,” Fisheries Research, 84, 210–221.
Oehlert, G. (1992), “A Note on the Delta Method,” The American Statistician, 46, 27–29.
Pennington, M. (1986), “Some Statistical Techniques for Estimating Abundance Indices from Trawl Surveys,” Fishery Bulletin, 84, 519–525.
Petitgas, P. (2001), “Geostatistics in Fisheries Survey Design and Stock Assessment: Models, Variance and Applications,” Fish and Fisheries, 2, 231–249.
R Core Development Team (2007), “R: A Language and Environment for Statistical Computing,” Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org.
Rivoirard, J., Simmonds, J., Foote, K., Fernandes, P., and Bez, N. (2000), Geostatistics for Estimating Fish Abundance, Oxford: Blackwell Science.
Schnute, J., and Haigh, R. (2003), “A Simulation Model for Designing Groundfish Trawl Surveys,” Canadian Journal of Fisheries and Aquatic Sciences, 60, 640–656.
Shono, H. (2008), “Application of the Tweedie Distribution to Zero-Catch Data in CPUE Analysis,” Fisheries Research, 93, 154–162.
Silverman, B. (1985), “Some Aspects of the Spline Smoothing Approach to Non-parametric Regression Curve Fitting,” Journal of the Royal Statistical Society. Series B, 47, 1–52.
Smith, A., and Smith, D. (2001), “A Complex Quota-managed Fishery: Science and Management in Australia’s South-East Fishery. Introduction and Overview,” Marine and Freshwater Research, 52, 353–360.
Smyth, G. K., and Verbyla, A. P. (1999), “Adjusted Likelihood Methods for Modelling Dispersion in Generalized Linear Models,” Environmetrics, 10, 695–709.
van den Berg, J., Curtis, A., and Trampert, J. (2003), “Optimal Nonlinear Bayesian Experimental Design: An Application to Amplitude Versus Offset Experiments,” Geophysical Journal International, 155, 411–421.
van Groenigen, J. W., and Stein, A. (1998), “Constrained Optimization of Spatial Sampling Using Continuous Simulated Annealing,” Journal of Environmental Quality, 27, 1078–1086.
Williams, A., Kloser, R., Barker, B., Bax, N., and Butler, A. (2005), “A Seascape Perspective for Managing Deep Sea Habitats,” in “Deep Sea”: Conference on the Governance and Management of Deep-Sea Fisheries, Vol. FAO Fisheries Proceedings of 3, Rome: FAO, pp. 89–97.
Wood, S. (2006), Generalized Additive Models: An Introduction with R, London/Boca Raton: Chapman and Hall/CRC Press.
— (2011), “Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models,” Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73, 3–36. doi:10.1111/j.1467-9868.2010.00749.x
Xiao, Y. (2004), “Use of Individual Types of Fishing Effort in Analyzing Catch and Effort Data by Use of a Generalized Linear Model,” Fisheries Research, 70, 311–318.
Zhu, Z. Y., and Stein, M. L. (2006), “Spatial Sampling Design for Prediction with Estimated Parameters,” Journal of Agricultural Biological and Environmental Statistics, 11, 24–44.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Peel, D., Bravington, M.V., Kelly, N. et al. A Model-Based Approach to Designing a Fishery-Independent Survey. JABES 18, 1–21 (2013). https://doi.org/10.1007/s13253-012-0114-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13253-012-0114-x