Abstract
This paper proposes a new statistical spatial model to analyze and predict the coverage percentage of the upland ground flora in the Missouri Ozark Forest Ecosystem Project (MOFEP). The flora coverage percentages are collected from clustered locations, which requires a new spatial model other than the traditional kriging method. The proposed model handles this special data structure by treating the flora coverage percentages collected from the clustered locations as repeated measurements in a Bayesian hierarchical setting. The correlation among the observations from the clustered locations are considered as well. The total vegetation coverage data in MOFEP is analyzed in this study. An Markov chain Monte Carlo algorithm based on the shrinkage slice sampler is developed for simulation from the posterior densities. The total vegetation coverage is modeled by three components, including the covariates, random spatial effect and correlated random errors. Prediction of the total vegetation coverage at unmeasured locations is developed.
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References
Banerjee S, Carlin BP, Gelfand AE (2004) Hierarchical moddeling and analysis for spatial data. Chapman & Hall/CRC, London/Boca Raton
Brookshire B, Shifley S (eds) (1997) Proceedings of the Missouri Ozark Forest Ecosystem Project Symposium: An Experimental Approach to Landscape Research. General Technical Report NC-193, St. Paul, MN, The United States Department of Agriculture, Forest Service, North Central Experiment Station
Chib S, Carlin BP (1999) On MCMC sampling in hierarchical longitudinal models. Stat Comput 9(1): 17–26
Cressie NAC (1993) Statistics for spatial data, Revised edition. Wiley-Interscience, New York
Cressie N (2004) Block kriging for lognormal spatial processes. Technical Report 739, Department of Statistics, The Ohio State University
Grabner J (2000) Ground layer vegetation in Missouri Ozark Forest Ecosystem Project:pre-treatment species composition, richness, and diversity. In: Shifley S, Brookshire B (eds) Missouri Ozark Forest Ecosystem Project: Site history, Soils, Landform, Woody and Herbaceous Vegetation, Down Wood, and Inventory Methods for Landscape Experiment, vol NC-208, pp 107–131
Grabner J (2002) Patterns in upland forest vegetation in relation to geology, to pography, and soils: an approach to ecological land classification in the Southeast Missouri Ozarks. Master’s thesis, University of Missouri-Columbia
Host GE, Pregitzer KS (1991) Ecological species groups for upland forest ecosystems of northwestern lower Michigan. For Ecol Manage 43: 87–102
Kabrick J, Meinert D, Nigh T, Gorlinsky BJ (2000) Physical environment of the Missouri Ozark Forest Ecosystem Project Sites. In: Missouri Ozark Forest Ecosystem Project Site History, Soils, Landforms, Woodys and Herbaceous Vegetation, Down Wood, and Inventory Methods for Landscape Experiment, vol NC-208, pp 41–70
Neal RM (2003) Slice sampling. Ann Stat 31(3):705–767 (with discussions and a rejoinder by the author)
Shifley S, Kabrick J (eds) (2002) Proceedings of the Missouri Ozark Forest Ecosystem Project Symposium: post-treatment results of the landscape experiment. General Technical Report NC-227, St. Paul, MN, US Department of Agriculture, Forest Service, North Central Research Station
Stein ML (1999) Interpolation of spatial data: some theory for kriging. Springer, New York
Webster R, McBratney AB (1987) Mapping soil fertility at broom’s barn by simple kriging. J Sci Food Agric 38: 97–115
Whittaker R (1967) Gradient analysis of vegetation. Biol Rev 49: 207–264
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Sun, X., He, Z., Zhang, J. et al. Bayesian spatial models with repeated measurements: with application to the herbaceous data analysis. Stat Methods Appl 18, 585–601 (2009). https://doi.org/10.1007/s10260-009-0114-3
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DOI: https://doi.org/10.1007/s10260-009-0114-3