A biologically-consistent stand growth model for loblolly pine in the Piedmont physiographic region, USA

2011 ◽  
Vol 262 (11) ◽  
pp. 2035-2041 ◽  
Author(s):  
Oscar García ◽  
Harold E. Burkhart ◽  
Ralph L. Amateis
Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 556
Author(s):  
Mauricio Zapata-Cuartas ◽  
Bronson P. Bullock ◽  
Cristian R. Montes ◽  
Michael B. Kane

Intensive loblolly pine (Pinus taeda L.) plantation management in the southeastern United States includes mid-rotation silvicultural practices (MRSP) like thinning, fertilization, competitive vegetation control, and their combinations. Consistent and well-designed long-term studies considering interactions of MRSP are required to produce accurate projections and evaluate management decisions. Here we use longitudinal data from the regional Mid-Rotation Treatment study established by the Plantation Management Research Cooperative (PMRC) at the University of Georgia across the southeast U.S. to fit and validate a new dynamic model system rooted in theoretical and biological principles. A Weibull pdf was used as a modifier function coupled with the basal area growth model. The growth model system and error projection functions were estimated simultaneously. The new formulation results in a compatible and consistent growth and yield system and provides temporal responses to treatment. The results indicated that the model projections reproduce the observed behavior of stand characteristics. The model has high predictive accuracy (the cross-validation variance explained was 96.2%, 99.7%, and 98.6%; and the prediction root mean square distance was 0.704 m, 19.1 trees ha−1, and 1.03 m2ha−1 for dominant height (DH), trees per hectare (N), and basal area (BA), respectively), and can be used to project the current stand attributes following combinations of MRSP and with different thinning intensities. Simulations across southern physiographic regions allow us to conclude that the most overall ranking of MRSP after thinning is fertilization + competitive vegetation control (Fert + CVC) > fertilization only (Fert) > competitive vegetation control only (CVC), and Fert + CVC show less than additive effect. Because of the model structure, the response to treatment changes with location, age of application, and dominant height growth as indicators of site quality. Therefore, the proposed model adequately represents regional growth conditions.


1994 ◽  
Vol 8 (2) ◽  
pp. 139-161 ◽  
Author(s):  
Rodrigo H. Bustamante ◽  
Wayne M. Getz ◽  
George M. Branch
Keyword(s):  

1991 ◽  
Vol 15 (1) ◽  
pp. 22-27
Author(s):  
Terry R. Clason

Abstract A hardwood suppression treatment applied to a 7-year-old, loblolly pine (Pinus taeda L.) plantation enhanced projected productivity through a 35-year rotation that included three commercial thinnings. By age 22, growth data showed that hardwood removal treatments had larger pines and smaller hardwoods than check treatments. Fifteen-year pine basal area and merchantable volume growth on hardwood removal plots exceeded the check plots by 25 and 27%. Projected growth between ages 22 and 35 indicated that 28 years after early hardwood removal thinned plantation merchantable volume yields improved by 840 ft³ per acre. South. J. Appl. For. 15(1):22-27.


1986 ◽  
Vol 16 (2) ◽  
pp. 330-334 ◽  
Author(s):  
N. J. Smith ◽  
D. W. Hann

A two-staged stand growth model is developed to describe the relationship between biomass or volume and numbers of stems in even-aged, monospecific plant populations undergoing self-thinning. The model is tested on red alder (Alnusrubra Bong.) seedlings and red pine (Pinusresinosa Ait.) stands grown over a range of site qualities and initial spacings. First, survival rate is modelled as a Weibull distribution. This is then fit to an analytical size–density model to give growth estimates. Crown closure is estimated to occur at a relative density of 0.09 for red alder, while initial mortality is estimated to occur at a relative density of 0.12 for red pine. Net stand growth rates peaked at a relative density of 0.54 for red alder biomass and from relative densities from 0.40 (widest initial spacing) to 0.55 (densest initial spacing) for red pine total stem volume. Site quality merely shifted the magnitude of these relationships. The model adds a dynamic component to the self-thinning rule and also generalizes and extends the rule to stand development between crown closure and the self-thinning asymptote.


1993 ◽  
Vol 23 (9) ◽  
pp. 1837-1851 ◽  
Author(s):  
Risto Sievänen ◽  
Thomas E. Burk

The problem of estimating the parameters of a process-based growth model using typical stand growth measurements (of tree dimensions) is studied. The data consist of measurements of diameter, height, number of trees, and live crown ratio obtained from plots representing different site qualities. An analysis of the identifiability of model parameters is made which shows (i) that the structure of the model makes certain parameter combinations unidentifiable and (ii) that the data at hand do not support all the parameters. It is not possible to reduce the number of parameters in the model without losing its biological significance. Therefore, as a remedy for identifiability problems, the model has been modified slightly on the basis of identifiability analysis and initial estimations and the set of parameters to be estimated has been restricted. A division of the parameters into two groups is sought: those estimated with all plots combined and those that are allowed to vary from plot to plot. The estimated parameters have biologically reasonable values, and the variation in accordance with plot site quality is logical. Data-based analysis shows that apart from some unidentifiable parameter combinations, the parameters of the present model are estimated rather consistently. Analysis of the loss function components indicates that measurements of diameter, height, density, and live crown ratio are needed for reliable fitting of the model.


2013 ◽  
Vol 59 (3) ◽  
pp. 335-344 ◽  
Author(s):  
Thomas J. Dean ◽  
Mauricio Jerez ◽  
Quang V. Cao

Author(s):  
Lingxia Hong ◽  
Shouzheng Tang ◽  
Haikui Li ◽  
Yongci Li ◽  
Francois de Coligny
Keyword(s):  

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