Mapping the abundance of riverine fish populations: Integrating hierarchical Bayesian models with a geographic information system (GIS)

Canadian Journal of Fisheries and Aquatic Sciences

Volumn 60, Issue 8, 2003, Pages 997-1006

  Wyatt, Robin J ^a  

^a ENVIRONMENT AGENCY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ABUNDANCE; BAYESIAN ANALYSIS; FISH; GIS; MAPPING;

CONWY; CONWY RIVER; EURASIA; EUROPE; UNITED KINGDOM; WALES; WESTERN EUROPE;

SALMO; SALMO TRUTTA; SALMONIDAE;

EID: 0344496628     PISSN: 0706652X     EISSN: None     Source Type: Journal    
DOI: 10.1139/f03-085     Document Type: Article

References (34)

1. Barnett, V. 1999. Comparative statistical inference. 3rd ed. John Wiley & Sons Ltd., Chichester, U.K.
2. Bohlin, T. 1981. Methods of estimating total stock, smolt output and survival of salmonids using electrofishing. Rep. Inst. Freshw. Res. Drottningholm, 59: 5-14.
3. Brooks, S.P. 1998. Markov chain Monte Carlo method and its application. Statistician, 47: 69-100.
4. Brooks S.P., and Gelman, A. 1998. Alternative methods for monitoring convergence of iterative simulations. J. Comput. Graph. Statist. 7: 434-455.
5. Burrough, P.A. 2001. GIS and geostatistics: essential partners for spatial analysis. Environ. Ecol. Stat. 8: 361-377.
6. Carle, F.L., and Strub, M.R. 1978. A new method for estimating population size from removal data. Biometrics, 34: 621-630.
7. Carlin, B., and Louis, T. 2000. Bayes and Empirical Bayes methods for data analysis. 2nd ed. Chapman and Hall, London.
8. Diggle, P.J., and Tawn, J.A. 1998. Model-based geostatistics. Appl. Stat. 47: 299-350.
9. Garbrecht, J., and Martz, L.W. 2000. Digital Elevation Model issues in water resource modelling. In Hydrologic and hydraulic modelling support with Geographic Information Systems. Edited by David Maidment and Jean Djokic. ESRI Press, Redlands, Calif.
10. Gelman, A., and Rubin, D.B. 1992. Inference from iterative simulation using multiple sequences (with discussion). Stat. Sci. 7: 457-511.
11. Gelman, A., Carlin, J., Stern, H., and Rubin, D. 1995. Bayesian data analysis. Chapman and Hall, London.
12. Gilks, W.R., Thomas, A., and Spiegelhalter, D.J. 1994. A language and program for complex Bayesian modelling. Statistician, 43: 169-178.
13. Gilks, W.R., Richardson, S., and Spiegelhalter, D.J. (Editors). 1996. Markov Chain Monte Carlo in practice. Chapman and Hall, London.
14. Handcock, M.S., and Stein, M.L. 1993. A Bayesian analysis of kriging. Technometrics, 35: 403-410.
15. Hankin, D.G. 1984. Multistage sampling designs in fisheries research: application in small streams. Can. J. Fish. Aquat. Sci. 41: 1575-1591.
16. Hogg, J., McCormack, J.E., Roberts, S.A., Gahegan, M.N., and Hoyle, B.S. 1993. Automated derivation of stream-channel networks and selected catchment characteristics from digital elevation models. In Geographical information handling - research and applications. Edited by Paul M. Mather. John Wiley & Sons Ltd., New York.
17. Isaak, D.J., and Hubert, W.A. 1997. Integrating new technologies into fisheries science: the application of geographic information systems. Fisheries, 22: 6-10.
18. Kapetsky, J.M. 2001. Recent applications of GIS in inland fisheries. In Proceedings of the First International Symposium on GIS in Fishery Science. Edited by Tom Nishida, Chuck E. Hollingworth, and Patricia J. Kailola. Fishery/Aquatic GIS Research Group, Kawagoe-City, Japan.
19. Le, N.D., and Zidek, J.V. 1992. Interpolation with uncertain spatial covariances: a Bayesian alternative to kriging. J. Multivariate Anal. 43: 351-374.
20. McAllister, M.K., and Kirkwood, G.P. 1998. Bayesian stock assessment: a review and example application using the logistic model. ICES J. Mar. Sci. 55: 1031-1060.
21. Meyer, R., and Millar, R. 1999. BUGS in Bayesian stock assessment. Can. J. Fish. Aquat. Sci. 56: 1078-1086.
22. Millar, R.B., and Meyer, R. 2000. Bayesian state-space modeling of age-structured data: fitting a model is just the beginning. Can. J. Fish. Aquat. Sci. 57: 43-50.
23. Moran, P.A.P. 1951. A mathematical theory of animal trapping. Biometrika, 38: 307-311.
24. O'Hagan, A. 1994. Kendall's advanced theory of statistics. Vol. 2b. Bayesian inference. Edward Arnold Publishers Ltd., London.
25. Olivera, F., Furnans, J., Maidment, D., Djokic, D., and Ye, Z. 2002. Drainage systems. In Arc Hydro: GIS for water resources. Edited by David Maidment. ESRI Press, Redlands, Calif.
26. Punt, A.E., and Hilborn, R. 1997. Fisheries stock assessment and decision analysis: the Bayesian approach. Rev. Fish Biol. Fish. 7: 35-63.
27. Rivoirard, J., Simmonds, J., Foote, K.G., Fernandes, P., and Bez, N. 2000. Geostatistics for estimating fish abundance. Blackwell Science Ltd., Oxford.
28. Rubin, D.B. 1988. Using the SIR algorithm to simulate posterior distributions. In Bayesian Statistics 3: Proceedings of the Third Valencia International Meeting, June 1-5, 1987. Edited by J.M. Bernardo, M.N. Degroot, D.V. Lindley, and A.M. Smith. Clarendon Press, Oxford, pp. 385-402.
29. Saunders, W. 2000. Preparation of DEMs for use in environmental modelling analysis. In Hydrologic and hydraulic modelling support with Geographic Information Systems. Edited by David Maidment and Jean Djokic. ESRI Press, Redlands, Calif.
30. Smith, A.F.M., and Gelfand, A.E. 1992. Bayesian statistics without tears: a sampling-resampling perspective. Am. Stat. 46: 84-88.
31. Spiegelhalter, D., Thomas, A., Best, N., and Lunn, D. 2003. WinBUGS user manual. Ver. 1.4. Medical Research Council Biostatistics Unit, Institute of Public Health, Cambridge, U.K. (http://www.mrc-bsu.cam.ac.uk/bugs).
32. Toepfer, C.S., Fisher, W.L., and Warde, W.D. 2000. A multistage approach to estimate fish abundance in streams using Geographic Information Systems. N. Am. J. Fish. Manag. 20: 634-645.
33. Wyatt, R.J. 2002. Estimating riverine fish population size from single-and multiple-pass removal sampling using a hierarchical model. Can. J. Fish. Aquat. Sci. 59: 695-706.
34. Zippin, C. 1956. An evaluation of the removal method of estimating animal populations. Biometrics, 12: 163-189.