scholarly journals A Mixed-Effects Model for the dbh–Height Relationship of Shortleaf Pine (Pinus echinata Mill.)

2008 ◽  
Vol 32 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Chakra B. Budhathoki ◽  
Thomas B. Lynch ◽  
James M. Guldin
Keyword(s):  
Tree Height ◽  
Ordinary Least Squares ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Tree Level ◽  
Permanent Plots ◽  
Pinus Echinata ◽  
Shortleaf Pine ◽  
Individual Tree ◽  
Total Height

Abstract Individual tree measurements were available from over 200 permanent plots established during 1985–1987 and later remeasured in naturally regenerated even-aged stands of shortleaf pine (Pinus echinata Mill.) in western Arkansas and eastern Oklahoma. The objective of this study was to model shortleaf pine growth in natural stands for the region. As a major component of the shortleaf modeling effort, an individual tree-level dbh–total height model was developed in which plot-specific random parameters were fitted using maximum-likelihood methods. The model predicts tree height on the basis of dbh and dominant stand height (which could be obtained from a site-index model). The mixed-effects model approach was found to predict the total height better than the similar models developed previously for this species using ordinary least-squares methods. Moreover, such a model has the appeal of generalization of the results over a region from which the plots were sampled; and also of calibration of parameters for newly sampled stands with minimal measurements.

scholarly journals Modelling the Tree Height, Crown Base Height, and Effective Crown Height of Pinus koraiensis Plantations Based on Knot Analysis

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1778
Author(s):  
Wancai Zhu ◽  
Zhaogang Liu ◽  
Weiwei Jia ◽  
Dandan Li
Keyword(s):  
Tree Height ◽  
Information Criterion ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Pinus Koraiensis ◽  
Tree Level ◽  
Model Parameters ◽  
Crown Height ◽  
Crown Base Height ◽  
Pruning Intensity

Taking 1735 Pinus koraiensis knots in Mengjiagang Forest Farm plantations in Jiamusi City, Heilongjiang Province as the research object, a dynamic tree height, effective crown height, and crown base height growth model was developed using 349 screened knots. The Richards equation was selected as the basic model to develop a crown base height and effective crown height nonlinear mixed-effects model considering random tree-level effects. Model parameters were estimated with the non-liner mixed effect model (NLMIXED) Statistical Analysis System (SAS) module. The akaike information criterion (AIC), bayesian information criterion (BIC), −2 Log likelihood (−2LL), adjusted coefficient (Ra2), root mean square error (RMSE), and residual squared sum (RSS) values were used for the optimal model selection and performance evaluation. When tested with independent sample data, the mixed-effects model tree effects-considering outperformed the traditional model regarding their goodness of fit and validation; the two-parameter mixed-effects model outperformed the one-parameter model. Pinus koraiensis pruning times and intensities were calculated using the developed model. The difference between the effective crown and crown base heights was 1.01 m at the 15th year; thus, artificial pruning could occur. Initial pruning was performed with a 1.01 m intensity in the 15th year. Five pruning were required throughout the young forest period; the average pruning intensity was 1.46 m. The pruning interval did not differ extensively in the half-mature forest period, while the intensity decreased significantly. The final pruning intensity was only 0.34 m.

Predictive Ability of Mixed-Effects Height–Diameter Models Fit Using One Species but Calibrated for Another Species

2019 ◽  
Author(s):  
Curtis L Vanderschaaf
Keyword(s):  
South Carolina ◽  
Predictive Ability ◽  
Pinus Palustris ◽  
Tree Height ◽  
Pinus Elliottii ◽  
Mixed Effects ◽  
Pinus Echinata ◽  
Individual Tree ◽  
Height Estimates ◽  
Model Form

Abstract Mixed-effects individual tree height–diameter models are presented for important pines in the Western Gulf, USA. Equations are presented for plantations of loblolly (Pinus taeda L.), longleaf (Pinus palustris P. Mill.), shortleaf (Pinus echinata Mill.), and slash (Pinus elliottii Engelm.) pine. To produce localized individual tree height estimates, these models can be calibrated after obtaining height–diameter measurements from a plot/stand of interest. These equations can help answer an interesting question of whether a model fit for one species can be calibrated to produce reasonable height estimates of another species. In situations where mixed-effects models have not been developed for a particular species, perhaps an equation from another species can be used. This question was addressed by calibrating these models using independent data of loblolly, longleaf, and slash pine plantations located in South Carolina. For each calibration species, in addition to the models developed described above, previously published models, but of the same model form, fit using other species from across the USA were examined. Results show that models of a variety of species can be calibrated to provide reasonable predictions for a particular species. Predictions using this particular model form indicate that model calibration is more important than species-specific height–diameter relations.

scholarly journals An individual-tree linear mixed-effects model for predicting the basal area increment of major forest species in Southern Europe

2020 ◽  
Vol 29 (3) ◽  
pp. e019
Author(s):  
Lucio Di Cosmo ◽  
Diego Giuliani ◽  
Maria Michela Dickson ◽  
Patrizia Gasparini
Keyword(s):  
Forest Inventory ◽  
Basal Area ◽  
Ordinary Least Squares ◽  
Mixed Effects ◽  
Forest Growth ◽  
Mixed Effects Model ◽  
Basal Area Increment ◽  
Individual Tree ◽  
Diameter At Breast Height ◽  
Breast Height

Aims of the study. Assessment of growth is essential to support sustainability of forest management and forest policies. The objective of the study was to develop a species-specific model to predict the annual increment of tree basal area through variables recorded by forest surveys, to assess forest growth directly or in the context of more complex forest growth and yield simulation models.Area of the study. Italy.Material and methods. Data on 34638 trees of 31 different forest species collected in 5162 plots of the Italian National Forest Inventory were used; the data were recorded between 2004 and 2006. To account for the hierarchical structure of the data due to trees nested within plots, a two-level mixed-effects modelling approach was used.Main results. The final result is an individual-tree linear mixed-effects model with species as dummy variables. Tree size is the main predictor, but the model also integrates geographical and topographic predictors and includes competition. The model fitting is good (McFadden’s Pseudo-R2 0.536), and the variance of the random effect at the plot level is significant (intra-class correlation coefficient 0.512). Compared to the ordinary least squares regression, the mixed-effects model allowed reducing the mean absolute error of estimates in the plots by 64.5% in average.Research highlights. A single tree-level model for predicting the basal area increment of different species was developed using forest inventory data. The data used for the modelling cover 31 species and a great variety of growing conditions, and the model seems suitable to be applied in the wider context of Southern Europe.   Keywords: Tree growth; forest growth modelling; forest inventory; hierarchical data structure; Italy.Abbreviations used: BA - basal area; BAI – five-year periodic basal area increment; BALT - basal area of trees larger than the subject tree; BASPratio - ratio of subject tree species basal area to stand basal area; BASTratio - ratio of subject tree basal area to stand basal area; CRATIO - crown ratio; DBH – diameter at breast height ; DBH0– diameter at breast height corresponding to five years before the survey year; DBHt– diameter at breast height measured in the survey year; DI5 - five-year, inside bark, DBH increment; HDOM - dominant height; LULUCF - Land Use, Land Use Changes and Forestry; ME - mean error; MAE - mean absolute error; MPD - mean percent deviation; MPSE - mean percent standard error; NFI(s) - National Forest Inventory/ies; OLS - ordinary least squares regression; RMSE - root mean squared error; UNFCCC - United Nation Framework Convention on Climate Change.

Estimating a system of nonlinear simultaneous individual tree models for white spruce in boreal mixed-species stands

1999 ◽  
Vol 29 (11) ◽  
pp. 1805-1811 ◽  
Author(s):  
Shongming Huang ◽  
Stephen J Titus
Keyword(s):  
Picea Glauca ◽  
Tree Height ◽  
White Spruce ◽  
Ordinary Least Squares ◽  
Tree Level ◽  
Parameter Estimates ◽  
Mixed Species ◽  
Individual Tree ◽  
Left Hand ◽  
Diameter Increment

A system of three interdependent, tree-level nonlinear equations was fitted. The system was used in an individual tree simulator to predict total tree height, periodic tree diameter increment, and height increment for white spruce (Picea glauca (Moench) Voss) grown in boreal mixed-species stands in Alberta. Because the variables appeared on the left-hand side of the equations also appeared on the right-hand side of the equations in the system, the system was estimated using nonlinear simultaneous techniques. Testing of cross-equation correlations using the Breusch and Pagan statistic indicated that the error terms of the related equations in the system are significantly correlated, suggesting that the parameter estimates obtained from simultaneous techniques are consistent and asymptotically more efficient than those obtained from ordinary least squares procedures applied to individual equations of the system.

scholarly journals Evaluation of Long-Term Shortleaf Pine Progeny Tests in the Ouachita and Ozark National Forests, USA

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 953
Author(s):  
Shaik M. Hossain ◽  
Don C. Bragg ◽  
Virginia L. McDaniel ◽  
Carolyn C. Pike ◽  
Barbara S. Crane ◽  
...  
Keyword(s):  
Tree Height ◽  
Seed Orchard ◽  
The United States ◽  
National Forests ◽  
Pinus Echinata ◽  
Shortleaf Pine ◽  
Individual Tree ◽  
Full Sibling ◽  
Seed Sources ◽  
Progeny Tests

Between the late 1970s and the early 1990s, the USDA Forest Service installed 155 shortleaf pine (Pinus echinata Mill.) progeny tests in national forests across the Southern Region of the United States. Using control-pollinated crosses from the Mount Ida Seed Orchard, 84 of these progeny tests were established in the Ouachita and Ozark-St. Francis National Forests in Arkansas and Oklahoma. Each of these 84 test locations had, on average, 33 full-sibling families representing three local geographic seed sources (East Ouachita, West Ouachita, and Ozark). Though largely abandoned years ago, the progeny tests that remain provided an opportunity to determine if significant genetic and genetic × environment variance exists for performance traits (d.b.h., tree height, and survival) decades after installation. In 2018 and 2019, we remeasured d.b.h. and height and determined survival in 15 fully stocked progeny tests. Family variances were significant (p < 0.01) for both d.b.h. and height but not for survival (p > 0.05). Seed sources differed significantly (p < 0.05) for d.b.h., with more pronounced latitudinal differences. Additionally, we determined that individual tree and full-sibling family mean heritabilities were moderate (0.15 and 0.72, respectively, for d.b.h and 0.09 and 0.41, for height), suggesting relatively high genetic to environmental variation and good potential for genetic improvement. We also found that shortleaf pine families were broadly adapted in this region since family-by-test variances were non-significant (p > 0.05).

scholarly journals A Mixed-Effects Height—Diameter Model for Individual Loblolly and Slash Pine Trees in East Texas

2011 ◽  
Vol 35 (1) ◽  
pp. 12-17 ◽  
Author(s):  
Dean W. Coble ◽  
Young-Jin Lee
Keyword(s):  
Loblolly Pine ◽  
Model Fitting ◽  
Pinus Elliottii ◽  
Ordinary Least Squares ◽  
Mixed Effects ◽  
Slash Pine ◽  
Permanent Plots ◽  
East Texas ◽  
Individual Tree ◽  
Pine Trees

Abstract A new mixed-effects model was developed that predicts individual-tree total height for loblolly (Pinus taeda) and slash pine (Pinus elliottii) as a function of individual-tree diameter (in.), dominant height (ft), quadratic mean diameter (in.), and maximum stand diameter (in.). Data from 119,983 loblolly pine and 42,697 slash pine height–diameter observations collected on 185 loblolly pine and 84 slash pine permanent plots located in plantations throughout East Texas were used for model fitting. This new model is an improvement over earlier models fit with ordinary least squares, in that it can be calibrated to a new stand with observed height–diameter pairs, thus improving height prediction. An example is provided that describes how to calibrate the model to a new stand with observed data.

scholarly journals Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications

2020 ◽  
Vol 13 (1) ◽  
pp. 77
Author(s):  
Tianyu Hu ◽  
Xiliang Sun ◽  
Yanjun Su ◽  
Hongcan Guan ◽  
Qianhui Sun ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Low Cost ◽  
Canopy Cover ◽  
Tree Height ◽  
Flying Height ◽  
Tree Level ◽  
Forest Site ◽  
Lidar System ◽  
Individual Tree ◽  
Gap Fraction

Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them from being used in large-scale forest applications. Here, we developed a very low-cost UAV lidar system that integrates a recently emerged DJI Livox MID40 laser scanner (~$600 USD) and evaluated its capability in estimating both individual tree-level (i.e., tree height) and plot-level forest inventory attributes (i.e., canopy cover, gap fraction, and leaf area index (LAI)). Moreover, a comprehensive comparison was conducted between the developed DJI Livox system and four other UAV lidar systems equipped with high-end laser scanners (i.e., RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE). Using these instruments, we surveyed a coniferous forest site and a broadleaved forest site, with tree densities ranging from 500 trees/ha to 3000 trees/ha, with 52 UAV flights at different flying height and speed combinations. The developed DJI Livox MID40 system effectively captured the upper canopy structure and terrain surface information at both forest sites. The estimated individual tree height was highly correlated with field measurements (coniferous site: R2 = 0.96, root mean squared error/RMSE = 0.59 m; broadleaved site: R2 = 0.70, RMSE = 1.63 m). The plot-level estimates of canopy cover, gap fraction, and LAI corresponded well with those derived from the high-end RIEGL VUX-1 UAV system but tended to have systematic biases in areas with medium to high canopy densities. Overall, the DJI Livox MID40 system performed comparably to the RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE systems in the coniferous site and to the Velodyne Puck LITE system in the broadleaved forest. Despite its apparent weaknesses of limited sensitivity to low-intensity returns and narrow field of view, we believe that the very low-cost system developed by this study can largely broaden the potential use of UAV lidar in forest inventory applications. This study also provides guidance for the selection of the appropriate UAV lidar system and flight specifications for forest research and management.

Evaluating the influence of stem form and damage on individual-tree diameter increment and survival in the Acadian Region: implications for predicting future value of northern commercial hardwood stands

2018 ◽  
Vol 48 (9) ◽  
pp. 1007-1019 ◽  
Author(s):  
Mark Castle ◽  
Aaron Weiskittel ◽  
Robert Wagner ◽  
Mark Ducey ◽  
Jereme Frank ◽  
...  
Keyword(s):  
Growth And Yield ◽  
Tree Level ◽  
Permanent Plots ◽  
Stem Form ◽  
Individual Tree ◽  
Tree Diameter ◽  
Diameter Increment ◽  
Hardwood Species ◽  
Future Value

Northern hardwood species display a variety of forms and defects that can reduce stem quality and complicate their timber management. However, for the most part, growth and yield models do not account for the influence of stem form and damage. This study determined the influence of stem form and damage on growth, survival, and projected future sawlog value among several northern commercial hardwood species. To accomplish this, hardwood trees on 112 permanent plots across three long-term research sites in Maine were assigned stem form and risk classes using a tree classification system developed in New Brunswick. A highly significant influence of stem form and risk on annualized individual-tree diameter increment and survival was found. Inclusion of these equations into a regional growth and yield model highlighted the importance of stem form and defects on long-term simulations as projected stand-level future value was significantly reduced by over 17%, on average (range of 13% to 28%), when compared with projections that did not include that tree-level information. The results highlight the importance of stem form and defects, as well as the need to account for them, in growth and yield applications that assess the forecasted value of commercially important hardwood stands.

scholarly journals Tree Biomass Equations for Naturally Regenerated Shortleaf Pine

2008 ◽  
Vol 32 (4) ◽  
pp. 163-167 ◽  
Author(s):  
Charles O. Sabatia ◽  
Thomas B. Lynch ◽  
Rodney E. Will
Keyword(s):  
Stand Density ◽  
Seemingly Unrelated Regression ◽  
Tree Level ◽  
Parameter Estimates ◽  
Pinus Echinata ◽  
Shortleaf Pine ◽  
Tree Biomass ◽  
Biomass Component ◽  
Tree Component ◽  
Old Trees

Abstract Aboveground tree-level and branch-level biomass component equations were fitted by nonlinear seemingly unrelated regression, for even-aged naturally regenerated shortleaf pine (Pinus echinata Mill.) in southeastern Oklahoma. Data were obtained from 46- to 53-year-old trees growing in stands that had previously been thinned to densities ranging from 50% of full stocking to overstocked unthinned stands. Stand density affected some of the parameter estimates for trees growing in thinned stands versus unthinned stands. Equations based on dbh alone gave biomass estimates that were not significantly different from those obtained with equations based on dbh, height, and/or crown width. The fitted tree-level biomass component equations were additive in the sense that predictions for biomass components were constrained by the estimation process to sum to total tree biomass. These equations can be used to estimate aboveground tree or tree component biomass for naturally regenerated shortleaf pine in the dbh range of 7–40 cm in southeastern Oklahoma and have potential for application in other shortleaf pine growing areas.

scholarly journals An Individual-Tree Growth and Yield Prediction System for Uneven-Aged Shortleaf Pine Stands

2000 ◽  
Vol 24 (2) ◽  
pp. 112-120 ◽  
Author(s):  
Michael M. Huebschmann ◽  
Lawrence R. Gering ◽  
Thomas B. Lynch ◽  
Onesphore Bitoki ◽  
Paul A. Murphy
Keyword(s):  
Basal Area ◽  
Growth Patterns ◽  
Growth And Yield ◽  
Prediction System ◽  
Pinus Echinata ◽  
Shortleaf Pine ◽  
Individual Tree ◽  
Basal Area Growth ◽  
Area Growth ◽  
Pine Stands

Abstract A system of equations modeling the growth and development of uneven-aged shortleaf pine (Pinus echinata Mill.) stands is described. The prediction system consists of two main components: (1) a distance-independent, individual-tree simulator containing equations that forecast ingrowth, basal-area growth, probability of survival, total and merchantable heights, and total and merchantable volumes and weights of shortleaf pine trees; and (2) stand-level equations that predict hardwood ingrowth, basal-area growth, and mortality. These equations were combined into a computer simulation program that forecasts future states of uneven-aged shortleaf pine stands. Based on comparisons of observed and predicted stand conditions in shortleaf pine permanent forest inventory plots and examination of the growth patterns of hypothetical stands, the simulator makes acceptable forecasts of stand attributes. South. J. Appl. For. 24(2):112-120.

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