Nonlinear Mixed Effects Modeling for Slash Pine Dominant Height Growth Following Intensive Silvicultural Treatments
Abstract:A modified Richard's growth model with nonlinear mixed effects is developed for modeling slash pine (Pinus elliottii Engelm.) dominant height growth in conjunction with different silvicultural treatments. All three parameters in the model turn out to have both fixed and random individual plot or silvicultural treatments effects. Moving average correlation with 2° was identified as within-plot error structure. The advantages of the mixed effects model in prediction for new responses are demonstrated in detail by formulations and examples. The modified Richards model has a form that combines dominant height growth and site index into one model form, so the incompatibility between height growth and site index model can be avoided. The general methodologies of nonlinear mixed effects model building, such as which parameters in the model should be considered to be random and which should be purely fixed, how to determine appropriate within-plot variance covariance structure, and how to specify between-plot variation via appropriate covariate modeling, are addressed in detail. Likelihood ratio test and Akaike information criterion (AIC) are used in model performance evaluation. Some useful graphical model diagnosis tools are also presented. FOR. SCI. 47(3):287–300.
Keywords: Random effects; base age invariant; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; natural resource management; natural resources; prediction variance; repeated measurements; site index model
Document Type: Miscellaneous
Affiliations: 1: Biometrician Division of Biostatistics, Department of Community Medicine and Health Care, University of Connecticut School of Medicine, 270 Farmington Ave., Exchange Suite 260, MC 6325, Farmington, CT, 06030, Phone: (860) 679-5477; Fax: (860) 679- 2: Professor D. B. Warnell School of Forest Resources, The University of Georgia, Athens, Georgia, 30605, email@example.com
Publication date: 2001-08-01
- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
Also published by SAF:
Journal of Forestry
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