Individual Tree Diameter, Height, and Volume Functions for Longleaf Pine

Gonzalez‐Benecke, Carlos A.; Gezan, Salvador A.; Martin, Timothy A.; Cropper, Wendell P.; Samuelson, Lisa J.; Leduc, Daniel J.

doi:10.5849/forsci.12-074

Cited by 25 publications

(15 citation statements)

References 25 publications

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“…To simplify and to improve the access and application of the crown profile models, other variables must be considered for estimation. Among these values, HT and DBH are easily measured in a stand, and many models have already been established for these values (Martin & Ek 1984;Biging & Dobbertin 1995;Temesgen & Gadow 2004;Gonzalez-Benecke et al 2014). …”

Section: Other Variable Modelsmentioning

confidence: 99%

Study on crown profile models for Chinese fir (Cunninghamia lanceolata) in Fujian Province and its visualization simulation

Chen

Wang

et al. 2015

Scandinavian Journal of Forest Research

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Crown profile models were developed for Chinese fir (Cunninghamia lanceolata) in Shunchang County, Fujian Province. We used data from 360 trees located in 65 pure, even-aged, and unthinned temporary plots. The data was divided into three groups according to site index. Nine models, including models for upper crown, lower crown, and entire crown, were fit; the optimal ones in each group were validated and chosen to estimate crown shape. The optimal models explained at least 70% variability in crown radius. In addition, models for crown width, height above ground to crown base, and height above ground to largest crown radius were also developed to facilitate the convenient simulation of crown profile models. These three models explained 85.4%, 85.1%, and 86.9%variability. All models also passed the F-test and residual test. The 3D images of a single tree and stands were presented by OpenGL technology on visual c++ platform based on the proposed models. Tree growth was compared and analyzed using crown profile curves under constrained conditions. The analysis results accorded with plant growth.

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Section: Other Variable Modelsmentioning

confidence: 99%

Study on crown profile models for Chinese fir (Cunninghamia lanceolata) in Fujian Province and its visualization simulation

Chen

Wang

et al. 2015

Scandinavian Journal of Forest Research

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“…At each age, stand biomass was calculated by multiplying Nha, estimated by the growth and yield model, by the individual-tree biomass estimated with the fitted functions, using QMD as a surrogate of dbh and the mean height estimated using the model shown in Table 1 (reported by Gonzalez-Benecke et al, 2014).…”

Section: Modelsmentioning

confidence: 99%

“…The goal of this study was to develop a model that can be used to analyze the effects of silviculture on C budgets in longleaf pine plantations in the southeastern U.S. To simulate in situ C pools, we developed a hybrid model that integrates a growth and yield model for longleaf pine (Gonzalez-Benecke et al, 2012) with allometric and biometric equations determined for the species (Baldwin and Saucier, 1983;Gonzalez-Benecke et al, 2014;Samuelson et al, 2014). To estimate ex situ C pool dynamics, the model used the outputs of merchantable products from the growth and yield model and current values of forest product conversion efficiencies and forest product decay rates (Gonzalez-Benecke et al, 2010a, 2011.…”

Section: Introductionmentioning

confidence: 99%

Modeling the effects of forest management on in situ and ex situ longleaf pine forest carbon stocks

Gonzalez‐Benecke

Samuelson

Martin

et al. 2015

Forest Ecology and Management

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a b s t r a c tAssessment of forest carbon storage dynamics requires a variety of techniques including simulation models. We developed a hybrid model to assess the effects of silvicultural management systems on carbon (C) budgets in longleaf pine (Pinus palustris Mill.) plantations in the southeastern U.S. To simulate in situ C pools, the model integrates a growth and yield model with species-specific allometric and biometric equations and explicitly accounts for the impacts of both thinning and prescribed fire. To estimate the ex situ C pool, the model used the outputs of merchantable products from the growth and yield model with current values of forest product conversion efficiencies and forest product decay rates. The model also accounts for C emissions due to transportation and silvicultural activities. Site productivity (site quality) was the major factor controlling stand C density followed by rotation length. Thinning reduced C sequestration, as the slow growth rate of longleaf pine reduced the potential of C sequestration in forest products. Prescribed burning reduced average C stock by about 16-19%, with the majority of the reduction in the forest floor. In a comparison of longleaf pine C dynamics with slash pine (Pinus elliottii Engelm.), both species reached a similar average C stock at age 75 years, but when averaged across the whole rotation, slash pine sequestered more C. Nevertheless, for medium quality sites, C sequestration was similar between thinned 75-year rotation longleaf pine and unthinned 25-year rotation slash pine. This longleaf pine plantation C sequestration model, based on empirical and biological relationships, provides an important new tool for developing testable research hypotheses, estimating C stocks for regional assessments or C credit verification, and for guiding future longleaf pine management.

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“…The equations reported by Gonzalez-Benecke et al [19], which depend on the individual dbh and stand parameters N, H dom and SI, were used to estimate individual tree volume outside and inside bark for each living tree in the dataset. After aggregating all individual tree volumes within each plot, stand volume outside and inside bark was determined for each plot.…”

Section: Survival and Yield Models For Unthinned Standsmentioning

confidence: 99%

“…For each tree in the fitting dataset, merchantable stem volume (both outside and inside bark), from the stump to any top diameter, was estimated using the equations reported by Gonzalez-Benecke et al [19] for a range of combinations of threshold dbh values (d, from 5.08 to 40.64 cm) and top diameter limit values (t, from 5.08 to 45.72 cm) that incremented at steps of 5.08 cm. Finally, for each plot, merchantable stem volume per hectare for each combination of d and t was calculated based on all living trees within each plot.…”

Section: Merchantable Volumementioning

confidence: 99%

Modeling Survival, Yield, Volume Partitioning and Their Response to Thinning for Longleaf Pine Plantations

Gonzalez‐Benecke

Gezan

Leduc

et al. 2012

Forests

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Longleaf pine (Pinus palustris Mill.) is an important tree species of the southeast U.S. Currently there is no comprehensive stand-level growth and yield model for the species. The model system described here estimates site index (SI) if dominant height (H dom ) and stand age are known (inversely, the model can project H dom at any given age if SI is known). The survival (N) equation was dependent on stand age and H dom , predicting greater mortality on stands with larger H dom . The function that predicts stand basal area (BA) for unthinned stands was dependent on N and H dom . For thinned stands BA was predicted with a competition index that was dependent on stand age. The function that best predicted stand stem volume (outside or inside bark) was dependent on BA and H dom . All functions performed well for a wide range of stand ages and productivity, with coefficients of determination ranging between 0.946 (BA) and 0.998 (N). We also developed equations to estimate merchantable volume yield consisting of different combinations of threshold diameter at breast height and top diameter for longleaf pine stands. The equations presented in this study performed similarly or slightly better than other reported models to estimate future N, H dom and BA. The system presented here provides important new tools for supporting future longleaf pine management and research.

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Individual Tree Diameter, Height, and Volume Functions for Longleaf Pine

Cited by 25 publications

References 25 publications

Study on crown profile models for Chinese fir (Cunninghamia lanceolata) in Fujian Province and its visualization simulation

Study on crown profile models for Chinese fir (Cunninghamia lanceolata) in Fujian Province and its visualization simulation

Modeling the effects of forest management on in situ and ex situ longleaf pine forest carbon stocks

Modeling Survival, Yield, Volume Partitioning and Their Response to Thinning for Longleaf Pine Plantations

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