Hierarchical Bayesian statistics: merging experimental and modeling approaches in ecology

Ecological Applications

Volumn 19, Issue 3, 2009, Pages 577-781

  Ogle, Kiona ^a  

^a University of Wyoming Laramie   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN ANALYSIS; ECOSYSTEM MODELING; HIERARCHICAL SYSTEM;

ARTICLE; BAYES THEOREM; ECOLOGY; EDUCATION; METHODOLOGY; STATISTICAL MODEL;

BAYES THEOREM; ECOLOGY; MODELS, STATISTICAL;

EID: 65349145830     PISSN: 10510761     EISSN: None     Source Type: Journal    
DOI: 10.1890/08-0560.1     Document Type: Article

References (32)

1. Clark, J. S., and A. E. Gelfand. 2006a. A future for models and data in environmental science. Trends in Ecology and Evolution 21:375-380.
2. Clark, J. S., and A. E. Gelfand. 2006è. Hierarchical modelling for the environmental sciences: statistical methods and applications. Oxford University Press, Oxford, UK.
3. Clark, J. S., S. LaDeau, and I. Ibanez. 2004. Fecundity of trees and the colonization-competition hypothesis. Ecological Monographs 74:415-442.
4. Cottingham, K. L., J. T. Lennon, and B. L. Brown. 2005. Knowing when to draw the line: designing more informative ecological experiments. Frontiers in Ecology and the Environment 3:145-152.
5. Cressie, N. A. C, C. A. Calder, J. S. Clark, J. M. Ver Hoef, and C. K. Wikle. 2009. Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. Ecological Applications 19:553-570.
6. Davidian, M., and D. M. Giltinan. 1995. Nonlinear models for repeated measurement data. Chapman and Hall/CRC Press, Boca Raton, Florida, USA.
7. Diggle, P. J., P. Heagerty, K.-Y. Liange, and S. L. Zeger. 2002. Analysis of longitudinal data. Oxford University Press, New York, New York, USA.
8. Gelman, A., and J. Hill. 2006. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press, New York, New York, USA.
9. Gertsev, V. I., and V. V. Gertseva. 2004. Classification of mathematical models in ecology. Ecological Modelling 178: 329-334.
10. Getz, W. M. 1998. An introspection on the art of modeling in population ecology. BioScience 48:540-552.
11. Goldstein, H. 2002. Multilevel statistical models. Hodder Arnold, London, UK.
12. Grimm, V. 1994. Mathematical models and understanding in ecology. Ecological Modelling 75:641-651.
13. Herendeen, R. A. 1988. Role of models in ecology. Ecological Modelling 43:133-136.
14. Hobbs, N. T., and R. Hilborn. 2006. Alternatives to statistical hypothesis testing in ecology: a guide to self teaching. Ecological Applications 16:5-19.
15. Hobbs, N. T., S. Twombly, and D. S. Schimel. 2006. Deepening ecological insights using contemporary statistics. Ecological Applications 16:3-4.
16. Hurtt, G C, P. R. Moorcroft, S. W. Pacala, and S. A. Levin. 1998. Terrestrial models and global change: challenges for the future. Global Change Biology 4:581-590.
17. Jackson, L. J., A. S. Trebitz, and K. L. Cottingham. 2000. An introduction to the practice of ecological modeling. Bio- Science 50:694-706.
18. Jørgensen, S. E. 1986. Fundamentals of ecological modelling. Elsevier, Amsterdam, The Netherlands.
19. Lindsey, J. K. 1993. Models for repeated measurements. Oxford University Press, New York, New York, USA.
20. Little, R. J. 2006. Calibrated Bayes: a Bayes/frequentist roadmap. American Statistician 60:213-223.
21. Ogle, K, and J. J. Barber. 2008. Bayesian data-model integration in plant physiological and ecosystem ecology. Progress in Botany 69:281-311.
22. Patten, B. C. 1971. Systems analysis and simulation in ecology. Volume I. Academic Press, New York, New York, USA.
23. Peek, M. S., E. Russek-Cohen, D. A. Wait, and I. N. Forseth. 2002. Physiological response curve analysis using nonlinear mixed models. Oecologia 132:175-180.
24. Pielou, E. C. 1981. The usefulness of ecological models: a stock- taking. Quarterly Review of Biology 56:17-31.
25. Potvin, C, M. J. Lechowicz, and S. Tardif. 1990. The statistical analysis of ecophysiological response curves obtained from experiments involving repeated measures. Ecology 71:1389- 1400.
26. Rastetter, E. B., J. D. Aber, D. P. C. Peters, D. S. Ojima, and I. C. Burke. 2003. Using mechanistic models to scale ecological processes across space and time. BioScience 53: 68-76.
27. Schneider, M. K., R. Law, and J. B. Illian. 2006. Quantification of neighbourhood-dependent plant growth by Bayesian hierarchical modelling. Journal of Ecology 94:310-321.
28. Searle, S. R., G. Casella, and C. E. McCulloch. 1992. Variance components. Wiley, New York, New York, USA.
29. Stephens, P. A., S. W. Buskirk, and C. Martinez del Rio. 2007. Inference in ecology and evolution. Trends in Ecology and Evolution 22:192-197.
30. Ulanowicz, R. E. 1988. On the importance of higher-level models in ecology. Ecological Modelling 43:45-56.
31. Wikle, C. K. 2003. Hierarchical Bayesian models for predicting the spread of ecological processes. Ecology 84:1382-1394.
32. Wikle, C. K., L. M. Berliner, and N. Cressie. 1998. Hierarchical Bayesian space-time models. Environmental and Ecological Statistics 5:117-154.