Information theory in wildlife science: Critique and viewpoint

Journal of Wildlife Management

Volumn 69, Issue 2, 2005, Pages 457-465

  Guthery, Fred S ^a   Brennan, Leonard A ^b   Peterson, Markus J ^c   Lusk, Jeffrey J ^d  

^a OKLAHOMA STATE UNIVERSITY   (United States)

^b TEXAS A AND M UNIVERSITY KINGSVILLE   (United States)

^c TEXAS A AND M UNIVERSITY   (United States)

^d PURDUE UNIVERSITY   (United States)

Author keywords

AIC; Hypothetico deductive methods; Inference; Information theoretic models; Model selection; Philosophy of wildlife science

Indexed keywords

ALGORITHM; ECOLOGICAL MODELING; STATISTICAL ANALYSIS; WILDLIFE MANAGEMENT;

EID: 23744463463     PISSN: 0022541X     EISSN: None     Source Type: Journal    
DOI: 10.2193/0022-541X(2005)069[0457:ITIWSC]2.0.CO;2     Document Type: Article

References (57)

1. ANDERSON, D. R. 2001. The need to get the basics right in wildlife field studies. Wildlife Society Bulletin 29:1294-1297.
2. _. 2003. Response to Engeman: index values rarely constitute reliable information. Wildlife Society Bulletin 31:288-291.
3. _, AND K. P. BURNHAM. 2002. Avoiding pitfalls when using information-theoretic methods. Journal of Wildlife Management 66:912-918.
4. _, _, W. R. GOULD, AND S. CHERRY. 2001. Concerns about finding effects that are actually spurious. Wildlife Society Bulletin 29:311-316.
5. _, _, AND W. L. THOMPSON. 2000. Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64:912-923.
6. BRENNAN, L. A., W. M. BLOCK, AND R. J. GUTIÉRREZ. 1987. Habitat use by mountain quail in northern California. Condor 89:66-74.
7. BRODERS, H. G., AND G. J. FORBES. 2004. Interspecific and intersexual variation in roost-site selection of northern long-eared and little brown bats in the Greater Fundy National Park Ecosystem. Journal of Wildlife Management 68:602-610.
8. BROTHERS, L. 1997. Friday's footprint: how society shapes the human mind. Oxford University Press, New York, USA.
9. BURNHAM, K. P., AND D. R. ANDERSON. 1998. Model selection and inference. Springer, New York, USA.
10. _, AND _. 2002. Model selection and multimodel inference. Springer, New York, USA.
11. CHAMBERLIN, T. C. 1890. The method of multiple working hypotheses. Science 148:754-759.
12. CHERRY, S. 1998. Statistical tests in publications of The Wildlife Society. Wildlife Society Bulletin 26:947-953.
13. CLAESKENS, G., AND N. L. HJORT. 2003. The focused information criterion. Journal of the American Statistical Association 98:900-916.
14. CURTIS, P. D., AND P. G. JENSEN. 2004. Habitat features affecting beaver occupancy along roadsides in New York state. Journal of Wildlife Management 68:278-287.
15. EBERHARDT, L. L. 2003. What should we do about hypothesis testing? Journal of Wildlife Management 67:241-247.
16. EDWARDS, A. W. F. 1992. Likelihood. Johns Hopkins University Press, Baltimore, Maryland, USA.
17. ELLISON, A. M. 2004. Bayesian inference in ecology. Ecology Letters 7:509-520.
18. FRANKLIN, A. B., D. R. ANDERSON, R. J. GUTIÉRREZ, AND K. B. BURNHAM. 2000. Climate, habitat quality, and fitness in northern spotted owl populations in north-western California. Ecological Monographs 70:539-590.
19. _, R. J. GUTIĖRREZ, J. D. NICHOLS, M. E. SEAMANS, G. C. WHITE, G. S. ZIMMERMAN, J. E. HINES, T. E. MUNTON, W. S. LAHAYE, J. A. BLAKESLEY, G. N. STEIGER, B. R. NOON, D. W. H. SHAW, J. J. KEANE, T. L. MCDONALD, AND S. BRITTING. 2004. Population dynamics of the California spotted owl (Strix occidentalis occidentalis): a meta-analysis. Ornithological Monographs 54:1-54.
20. GINZBURG, L. R., AND C. X. J. JENSEN. 2004. Rules of thumb for judging ecological theories. Trends in Ecology and Evolution 19:121-126.
21. GRIFFIN, P. C., L. BIENEN, C. M. GILLIN, AND L. S. MILLS. 2003. Estimating pregnancy rates and litter size in snowshoe hares using ultrasound. Wildlife Society Bulletin 31:1066-1072.
22. GUTHERY, F. S. 2004. Commentary: the flavors and colors of facts in wildlife science. Wildlife Society Bulletin 32:288-297.
23. _, J. J. LUSK, AND M. J. PETERSON. 2001. The fall of the null hypothesis: liabilities and opportunities. Journal of Wildlife Management 65:379-384.
24. _, _, AND _. 2004. In my opinion: hypotheses in wildlife science. Wildlife Society Bulletin 32:1325-1332.
25. HALL, J. R. 1990. Epistemology and sociohistorical inquiry. Annual Review of Sociology 16:329-351.
26. HOWSON, C. 2000. Induction and the uniformity of nature. Pages 181-183 in W. H. Newton-Smith, editor. A companion to the philosophy of science. Blackwell Publishers, Malden, Massachusetts, USA.
27. HURLBERT, S. H. 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:187-211.
28. JASANOFF, S. 1996. Beyond epistemology: relativism and engagement in the politics of science. Social Studies of Science 26:393-418.
29. JOHNSON, D. H. 1999. The insignificance of statistical significance testing. Journal of Wildlife Management 63:763-772.
30. _. 2002a. The importance of replication in wildlife research. Journal of Wildlife Management 66:919-932.
31. _. 2002b. The role of hypothesis testing in wildlife science. Journal of Wildlife Management 66:272-276.
32. JOHNSON, J. B., AND K. S. OMLAND. 2004. Model selection in ecology and evolution. Trends in Ecology and Evolution 19:101-108.
33. KADANE, J. B., AND N. A. LAZAR. 2004. Methods and criteria for model selection. Journal of the American Statistical Association 99:279-290.
34. LAHAYE, W. S., G. S. ZIMMERMAN, AND R. J. GUTIÉRREZ. 2004. Temporal variation in vital rates of an insular population of spotted owls (Strix occidentalis occidentalis): contrasting effects of weather. Auk 121:1056-1069.
35. MAURER, B. A. 2004. Models of scientific inquiry and statistical practice: implications for the structure of scientific knowledge. Pages 17-50 in M. L. Taper and S. R. Lele, editors. The nature of scientific evidence: statistical, philosophical, and empirical considerations. University of Chicago Press, Chicago, Illinois, USA.
36. MURATA, N., S. YOSHIZAWA, AND S. AMARI. 1994. Network information criterion - determining the number of hidden units for artificial neural network models. IEEE Transactions on Neural Networks 5:865-872.
37. NOON, B. R., AND A. B. FRANKLIN. 2002. Scientific research and the spotted owl: opportunities for major contributions to avian population demography. Auk 119:311-320.
38. NORMAN, G. W., M. M. CONNER, J. C. PACK, AND G. C. WHITE. 2004. Effects of fall hunting on survival of male wild turkeys in Virginia and West Virginia. Journal of Wildlife Management 68:393-404.
39. PEARCE, W. B. 1989. Communication and the human condition. Southern Illinois University Press, Carbondale, USA.
40. PEAT, D. F. 2002. From certainty to uncertainty: the story of science and ideas in the twentieth century. Joseph Henry Press, Washington, D.C., USA.
41. PETERSON, M. N., S. A. ALLISON, M. J. PETERSON, T. R. PETERSON, AND R. R. LOPEZ. 2004. A tale of two species: habitat conservation plans as bounded conflict. Journal of Wildlife Management 68:743-761.
42. _, T. R. PETERSON, M. J. PETERSON, R. R. LOPEZ, AND N. J. SILVY. 2002. Cultural conflict and the endangered Florida Key deer. Journal of Wildlife Management 66:947-968.
43. POINCARÉ, H. 1952. Science and hypothesis. Dover Publications, New York, USA.
44. POPPER, K. R. 1959. The logic of scientific discovery. Hutchinson, United Kingdom.
45. _. 1962. Conjectures and refutations: the growth of scientific knowledge. Basic Books, New York, USA.
46. RIPLEY, B. D. 1996. Pattern recognition and neural networks. Cambridge University Press, New York, USA.
47. ROMESBURG, H. C. 1981. Wildlife science: gaining reliable knowledge. Journal of Wildlife Management 45:293-313.
48. SACKETT, D. L., S. E. STRATUS, W. S. RICHARDSON, W. ROSENBERG, AND R. B. HAYNES. 2000. Evidence-based medicine. Churchill Livingston, New York, USA.
49. SCHWANDT, T. A. 1998. Constructivist, interpretivist approaches to human inquiry. Pages 221-259 in N. K. Denzin and Y. S. Lincoln, editors. The landscape of qualitative research: theories and issues. Sage Publications, Thousand Oaks, California, USA.
50. SCHWARZ, G. 1978. Estimating the dimension of a model. Annals of Statistics 6:461-464.
51. SILVER, B. L. 1998. The ascent of science. Oxford University Press, Oxford, United Kingdom.
52. SPIEGELHALTER, D. J., N. G. BEST, B. P. CARLIN, AND A. VAN DER LINDE. 2002. Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society Series B-Statistical Methodology 64:583-639.
53. STUMP, D. 1992. Naturalized philosophy of science with a plurality of methods. Philosophy of Science 59:456-460.
54. TAKEUCHI, K. 1976. Distribution of informational statistics and a criterion for model fitting. Suri-Kagaku 153:12-18. [In Japanese.]
55. TAPER, M. L. 2004. Model identification from many candidates. Pages 488-501 in M. L. Taper and S. R. Lele, editors. The nature of scientific evidence: statistical, philosophical, and empirical considerations. University of Chicago Press, Chicago, Illinois, USA.
56. WELLENDORF, S. D., W. E. PALMER, AND P. T. BROMLEY. 2004. Estimating calling rates of northern bobwhite coveys and measuring abundance. Journal of Wildlife Management 68:672-682.
57. WILSON, E. O. 1998. Consilience: the unity of knowledge. Alfred A. Knopf, New York, USA.