scholarly journals Testing the Accuracy of Growth and Yield Models for Southern Hardwood Forests

2000 ◽  
Vol 24 (3) ◽  
pp. 176-185 ◽  
Author(s):  
H. Michael Rauscher ◽  
Michael J. Young ◽  
Charles D. Webb ◽  
Daniel J. Robison
Keyword(s):  
Test Data ◽  
Basal Area ◽  
Hardwood Forests ◽  
Growth And Yield ◽  
Bottomland Hardwoods ◽  
Average Error ◽  
Yellow Poplar ◽  
Data Set ◽  
Southern Appalachian ◽  
Growth And Yield Models

Abstract The accuracy of ten growth and yield models for Southern Appalachian upland hardwood forests and southern bottomland forests was evaluated. In technical applications, accuracy is the composite of both bias (average error) and precision. Results indicate that GHAT, NATPIS, and a locally calibrated version of NETWIGS may be regarded as being operationally valid growth and yield models for Southern Appalachian yellow-poplar (Liriodendron tulipifera) and mixed oak (Quercus spp.) forests that fall within the range of characteristics of the test data set. No publicly available growth and yield models specifically developed for southern bottomland hardwood forests exist. Four general models that contain most of the applicable species to predict growth of these forests were tested. SETWIGS was found to be the most accurate of the four models tested and is recommended for use if the reported level of accuracy is acceptable and the target stand characteristics fall within the range of our test data set. Results indicate that the growth and density dynamics of dense, young stands of both upland and bottomland hardwoods were poorly predicted by the models. Models predicted basal area and density changes in yellow-poplar stands more accurately than mixed hardwoods. Predictions for upland hardwoods were more accurate than those for bottomland hardwoods. Model accuracy uniformly decreases with increasing length of the projection period. South. J. Appl. For. 24(3):176-185.

scholarly journals The SOHARC Model System for Growth and Yield of Southern Hardwoods

2008 ◽  
Vol 32 (4) ◽  
pp. 173-183 ◽  
Author(s):  
John Paul McTague ◽  
David O'Loughlin ◽  
Joseph P. Roise ◽  
Daniel J. Robison ◽  
Robert C. Kellison
Keyword(s):  
Tree Growth ◽  
Growth Models ◽  
Basal Area ◽  
Tree Height ◽  
Growth And Yield ◽  
Permanent Plots ◽  
Red Maple ◽  
Yellow Poplar ◽  
Individual Tree ◽  
Individual Tree Growth

Abstract A system of stand level and individual tree growth-and-yield models are presented for southern hardwoods. These models were developed from numerous permanent growth-and-yield plots established across 13 states in the US South on 9 site types, in even-aged (age classes from 20 to 60 years), fully stocked, naturally regenerated mixed hardwood and mixed hardwood-pine stands. Nested plots (⅕ and ac) were remeasured at 5-year intervals. The system of permanent plots was established and maintained by private and public members in the North Carolina State University Hardwood Research Cooperative. Stand level models are presented for dominant height, survival, basal area prediction and projection, and the ingrowth component. Individual tree diameter growth and tree height models were constructed for the most common species: sweetgum, tupelo, yellow-poplar, blackgum, and red maple. All other species were grouped according to growth dynamics into four species groups using cluster analysis. A ranking variable was incorporated into the individual tree growth models to account for competition.

scholarly journals Development of height to crown base models for thirteen tree species of the North American Acadian Region

2012 ◽  
Vol 88 (1) ◽  
pp. 60-73 ◽  
Author(s):  
Baburam Rijal ◽  
Aaron R. Weiskittel ◽  
John A. Kershaw
Keyword(s):  
Tree Species ◽  
Basal Area ◽  
Logistic Equation ◽  
Growth And Yield ◽  
Suitable Model ◽  
Breast Height ◽  
The North ◽  
Model Predictions ◽  
Important Input ◽  
Growth And Yield Models

Height to live crown base (HCB) is an important input variable for several growth and yield models. Since HCB is rarely measured in the field, it is often predicted using static models. Instead of predicting HCB, the Forest Vegetation Simulator Northeastern Variant (FVS-NE) uses an equation that predicts crown ratio (CR), which has not been well validated. The main goal of the present study was to construct a regional HCB model for thirteen selected tree species of the Acadian Region of North America. The specific objectives were to: 1) evaluate FVS-NE model predictions, 2) compare suitable model forms, and 3) assess influence of various covariates to improve predictions. We evaluated three model forms, namely Holdaway (1986), logistic, and exponential. The findings indicated that FVS-NE models were significantly biased for all species as the overall mean bias and root mean square error (RMSE) were 0.11 m and 1.80 m, respectively. A logistic equation with size (diameter at breast height [DBH], total height [HT] and ratio of DBH to HT), and competition (crown competition factor [CCF] and basal area larger than subject tree [BAL]) gave the best predictions for all species in this analysis. This model had an overall mean bias <0.01 m and an RMSE of 1.59 m, which represents a significant improvement in predictions compared to FVS-NE. Despite the range of species and observed variation in the data, the equations worked well and can be easily calibrated to new stands with a few local observations.

Regenerating Southern Appalachian Mixed Hardwood Stands with the Shelterwood Method

1983 ◽  
Vol 7 (4) ◽  
pp. 212-217 ◽  
Author(s):  
David L. Loftis
Keyword(s):  
Species Composition ◽  
Basal Area ◽  
Herbicide Application ◽  
Oak Regeneration ◽  
Yellow Poplar ◽  
Southern Appalachian ◽  
Prominent Component ◽  
Appalachian Hardwoods

Abstract Shelterwood cuts, with understory treatment by cutting or herbicide application, can be used to regenerate southern Appalachian hardwoods. Cuts with residual basal area ranging from 25 to 66 square feet per acre and overwood retained from 5 to 13 years established desirable, well-stocked stands. However, species composition was essentially the same as in clearcuts with intolerant species, especially yellow-poplar, dominating. Oak regeneration did not benefit from either higher residual basal area or longer periods of overstory retention, even though oaks were prominent in the overstories of all stands. Only where larger oak advance reproduction was numerous before the initial cut did oaks become a prominent component of the new stand.

scholarly journals A preliminary growth and yield model for Eucalyptus globoidea Blakely plantations in New Zealand

2020 ◽  
Vol 50 ◽  
Author(s):  
Serajis Salekin ◽  
Euan G. Mason ◽  
Justin Morgenroth ◽  
Dean F. Meason
Keyword(s):  
New Zealand ◽  
Basal Area ◽  
Growth And Yield ◽  
Maximum Diameter ◽  
Forest Industry ◽  
Eucalyptus Species ◽  
Plantation Forest ◽  
Yield Model ◽  
Growth And Yield Model ◽  
Growth And Yield Models

Background: New Zealand’s plantation forest industry is dominated by the exotic species radiata pine (Pinus radiata D.Don), which comprises approximately 90% of the net stocked area. However, there is interest in introducing new species to: (a) provide wood that is naturally decay-resistant as a substitute for wood treated with preservatives; (b) match species to the wide variety of environmental conditions in New Zealand; and (c) reduce reliance on P. radiata. Some Eucalyptus species are considered as potential alternatives to P. radiata, specifically those that can survive in resource-limited conditions and produce high quality wood. While Eucalyptus species are grown in plantations in many regions of the world, limited information is available on their growth in New Zealand. Eucalyptus globoidea Blakley is of particular interest and has been planted in trials throughout New Zealand. A complete set of preliminary growth and yield models for this species will satisfy the initial information requirements for diversifying New Zealand’s plantation forest industry. Methods: A set of growth and yield models was developed and validated, based on data from 29 E. globoidea permanent sample plots (PSPs) located mostly in North Island and a few in South Island of New Zealand. Trees were measured at different time intervals in these plots, with height and diameter at breast height (DBH) ranging from 0.1–39.8 m and 0.1–62.3 cm, respectively. An algebraic difference approach (ADA) was applied to model mean top height, basal area, maximum diameter, and standard deviation of DBH. Non-linear regression equations were used to project stand volume and height-diameter relationship, and Reineke’s stand density index (SDI) approach was employed to model mortality. Results: Mean top height, maximum diameter, and standard deviation of DBH were best fitted by Von Bertalanffy-Richards (SE=1.1 m), Hossfeld (SE=2.4 cm), and Schumacher polymorphic (SE=1.6 cm) difference equations, respectively. Basal area data were modelled with high precision (SE=6.9 m2 ha-1) by the Schumacher anamorphic difference equation. Reineke’s SDI approach was able to explain the self-thinning as a reduction in the number of stems per hectare. Stand-level volume per hectare and height-diameter relationship models were precise when including site-specific variables with standard errors of 40.5 m3 ha-1 and 3.1 m, respectively. Conclusion: This study presents a set of preliminary growth and yield models for E. globoidea to project plot-level growth attributes. The models were path invariant and satisfied basic traditional mensurational-statistical growth and yield model assumptions. These models will provide forest growers and managers with important fundamental information about the growth and yield of E. globoidea.

A Validation of TWIGS for Illinois Forests

1989 ◽  
Vol 6 (4) ◽  
pp. 154-156 ◽  
Author(s):  
David G. Kowalski ◽  
George Z. Gertner
Keyword(s):  
Basal Area ◽  
Predictive Ability ◽  
Hardwood Forests ◽  
Growth And Yield ◽  
Permanent Plots ◽  
Timber Species ◽  
Prediction Errors ◽  
Tree Survival ◽  
Species Characteristics ◽  
Growth Projection

Abstract The predictive ability of the Central States growth and yield system TWIGS 3.0 was evaluated for Illinois forests. The data used to validate the system were collected from permanent plots that had been established throughout the state and maintained for up to 30 years. TWIGS growth predictions were analyzed through the differences between observed and predicted stand and species characteristics. TWIGS consistently overpredicted mean stand diameter and underpredicted tree survival over a 30-year growth projection. The combined result of prediction errors in diameter growth and tree survival was a consistent underprediction of basal area per acre. Percent error at the twentieth year of projection was -6% for mean stand diameter, 18% for tree survival, and 6% for basal area. TWIGS, with its simulation features and small relative prediction errors for some major timber species, is an adequate growth and yield system for Illinois' mixed hardwood forests. North. J. Appl. For. 6:154-156, December 1989.

How to Assess Prognostic Models for Survival Data: A Case Study in Oncology

2003 ◽  
Vol 42 (05) ◽  
pp. 564-571 ◽  
Author(s):  
M. Schumacher ◽  
E. Graf ◽  
T. Gerds
Keyword(s):  
Test Data ◽  
Survival Data ◽  
Prediction Error ◽  
Classification Scheme ◽  
Neural Nets ◽  
Brier Score ◽  
Data Set ◽  
Independent Test ◽  
Artificial Neural

Summary Objectives: A lack of generally applicable tools for the assessment of predictions for survival data has to be recognized. Prediction error curves based on the Brier score that have been suggested as a sensible approach are illustrated by means of a case study. Methods: The concept of predictions made in terms of conditional survival probabilities given the patient’s covariates is introduced. Such predictions are derived from various statistical models for survival data including artificial neural networks. The idea of how the prediction error of a prognostic classification scheme can be followed over time is illustrated with the data of two studies on the prognosis of node positive breast cancer patients, one of them serving as an independent test data set. Results and Conclusions: The Brier score as a function of time is shown to be a valuable tool for assessing the predictive performance of prognostic classification schemes for survival data incorporating censored observations. Comparison with the prediction based on the pooled Kaplan Meier estimator yields a benchmark value for any classification scheme incorporating patient’s covariate measurements. The problem of an overoptimistic assessment of prediction error caused by data-driven modelling as it is, for example, done with artificial neural nets can be circumvented by an assessment in an independent test data set.

scholarly journals A Dynamic Stand Growth Model System for Loblolly Pine Responding to Mid-Rotation Treatments

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 556
Author(s):  
Mauricio Zapata-Cuartas ◽  
Bronson P. Bullock ◽  
Cristian R. Montes ◽  
Michael B. Kane
Keyword(s):  
Growth Model ◽  
Loblolly Pine ◽  
Basal Area ◽  
Model System ◽  
Growth And Yield ◽  
Site Quality ◽  
Response To Treatment ◽  
Plantation Management ◽  
Vegetation Control ◽  
Dominant Height

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.

Deriving Tree Diameter Growth and Probability of Survival Equations from Successive Diameter Distributions

2008 ◽  
Vol 54 (1) ◽  
pp. 31-35
Author(s):  
Thomas G. Matney ◽  
Emily B. Schultz
Keyword(s):  
General Procedure ◽  
Growth And Yield ◽  
Diameter Distribution ◽  
Diameter Growth ◽  
Individual Tree ◽  
Statistical Probability ◽  
Growth And Survival ◽  
Tree Diameter ◽  
Growth And Yield Models ◽  
Diameter Distributions

Abstract Many growth and yield models have used statistical probability distributions to estimate the diameter distribution of a stand at any age. Equations for approximating individual tree diameter growth and survival probabilities from dbh can be derived from these models. A general procedure for determining the functions is discussed and illustrated using a loblolly pine spacing study. The results from the spacing study show that it is possible to define tree diameter growth and survival probability functions from diameter distributions with an accuracy sufficient to obtain a link between the individual tree and diameter growth and yield models.

A Growth and Yield Model for Improved Eastern Cottonwood Plantations in the Lower Mississippi Delta

1991 ◽  
Vol 15 (4) ◽  
pp. 213-216 ◽  
Author(s):  
Quang V. Cao ◽  
Kenneth M. Durand
Keyword(s):  
Populus Deltoides ◽  
Mississippi Delta ◽  
Basal Area ◽  
Site Index ◽  
Growth And Yield ◽  
Annual Increment ◽  
Yield Model ◽  
Eastern Cottonwood ◽  
Volume Yield ◽  
Growth And Yield Model

Abstract A compatible growth and yield model was developed based on remeasurement data collected from 183 plots on unthinned improved eastern cottonwood (Populus deltoides Bartr.) plantations in the lower Mississippi Delta. The Sullivan and Clutter (1972) equation form was selected for predicting cubic-foot volume yield and projecting volume from site index and initial age and basal area. Yield equations explained 97% and 94%, respectively, of the variations in total outside bark and merchantable inside bark volumes. Mean annual increment of merchantable volume culminated between 8 and 15 years, depending on site index and initial basal area. South. J. Appl. For. 15(4):213-216.

Demographic Characterization of Anonymous Trace Travel Data

2015 ◽  
Vol 2526 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Joshua Auld ◽  
Abolfazl (Kouros) Mohammadian ◽  
Marcelo Simas Oliveira ◽  
Jean Wolf ◽  
William Bachman
Keyword(s):  
Test Data ◽  
Large Scale ◽  
Travel Demand ◽  
Null Model ◽  
Demographic Characteristics ◽  
Travel Pattern ◽  
Data Set ◽  
Trace Data ◽  
Demographic Models ◽  
Pattern Information

Research was undertaken to determine whether demographic characteristics of individual travelers could be derived from travel pattern information when no information about the individual was available. This question is relevant in the context of anonymously collected travel information, such as cell phone traces, when used for travel demand modeling. Determining the demographics of a traveler from such data could partially obviate the need for large-scale collection of travel survey data, depending on the purpose for which the data were to be used. This research complements methodologies used to identify activity stops, purposes, and mode types from raw trace data and presumes that such methods exist and are available. The paper documents the development of procedures for taking raw activity streams estimated from GPS trace data and converting these into activity travel pattern characteristics that are then combined with basic land use information and used to estimate various models of demographic characteristics. The work status, education level, age, and license possession of individuals and the presence of children in their households were all estimated successfully with substantial increases in performance versus null model expectations for both training and test data sets. The gender, household size, and number of vehicles proved more difficult to estimate, and performance was lower on the test data set; these aspects indicate overfitting in these models. Overall, the demographic models appear to have potential for characterizing anonymous data streams, which could extend the usability and applicability of such data sources to the travel demand context.

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