scholarly journals Loblolly Pine Growth and Yield Prediction for Managed West Gulf Plantations

1987 ◽  
Author(s):  
V. Clark Baldwin ◽  
D.P. Feduccia
Keyword(s):  
Loblolly Pine ◽  
Growth And Yield ◽  
Yield Prediction

scholarly journals Loblolly and Slash Pine Growth and Yield Prediction for Regional Timber Supply Projection Algorithms

1999 ◽  
Vol 23 (4) ◽  
pp. 230-237
Author(s):  
Bruce E. Borders ◽  
Jeffrey B. Jordan
Keyword(s):  
Loblolly Pine ◽  
Analysis Data ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Projection Algorithms ◽  
Timber Supply ◽  
Usda Forest Service ◽  
Forest Inventory And Analysis ◽  
Pine Stands ◽  
Growth And Yield Models

Abstract Regional and national timber supply models require standing inventory update procedures. To date, most inventory update procedures used in regional timber supply algorithms have not made use of growth and yield methodology. We present growth and yield models to update standing inventories for natural and planted slash and loblolly pine stands in Georgia. These models were fitted to USDA Forest Service Forest Inventory and Analysis data obtained from the sixth survey of Georgia and should prove useful in regional timber supply projection algorithms. South. J. Appl. For. 23(4):230-237.

scholarly journals A New Diameter Distribution Model for Unmanaged Loblolly Pine Plantations in East Texas

2006 ◽  
Vol 30 (1) ◽  
pp. 13-20 ◽  
Author(s):  
Young-Jin Lee ◽  
Dean W. Coble
Keyword(s):  
Loblolly Pine ◽  
Pine Plantations ◽  
Growth And Yield ◽  
Distribution Model ◽  
Diameter Distribution ◽  
Yield Prediction ◽  
East Texas ◽  
Distribution Models ◽  
Parameter Recovery ◽  
Diameter Classes

Abstract A parameter recovery procedure for the Weibull distribution function based on four percentile equations was used to develop a diameter distribution yield prediction model for unmanaged loblolly pine (Pinus taeda L.) plantations in East Texas. This model was compared with the diameter distribution models of Lenhart and Knowe, which have been used in East Texas. All three models were evaluated with independent observed data. The model developed in this study performed better than the other two models in prediction of trees per acre and cubic-foot volume per acre (wood and bark, excluding stump) across diameter classes. Lenhart’s model consistently underestimated the larger-diameter classes because it was developed originally with data mostly collected in young plantations. Knowe’s model overestimated volume in sawtimber-sized trees, which could lead to overestimations of volume in older loblolly pine plantations found in East Texas. An example also is provided to show users how to use this new yield prediction system. These results support the recommendation that forest managers should use growth and yield models designed and/or calibrated for the region in which they are implemented.South. J. Appl.For. 30(1):13–20.

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.

Estimating Fusiform Rust Losses in Five Southeast States

1986 ◽  
Vol 10 (4) ◽  
pp. 237-240 ◽  
Author(s):  
Robert L. Anderson ◽  
Joe P. McClure ◽  
Noel Cost ◽  
Robert J. Uhler
Keyword(s):  
Loblolly Pine ◽  
Forest Inventory ◽  
Slash Pine ◽  
Growth And Yield ◽  
Quality Loss ◽  
Forest Inventory And Analysis ◽  
Fusiform Rust ◽  
State Area

Abstract Annual losses to fusiform rust are estimated at over $35 million in the five States from Virginia to Florida. Losses were estimated by taking Forest Inventory and Analysis (FIA) data on fusiform rust through a series of growth and yield equations and sawtimber quality loss projections. The result is a system that estimates cordwood and sawtimber losses by state for loblolly and slash pine in natural and planted stands. Each time a state is resurveyed by FIA, a new estimate of loss can be made. This system applied to a 5-state area also shows that about 8.8 million acres of the 24 million acres of slash and loblolly pine have at least 10 percent of the trees infected. South. J. Appl. For. 10:237-240, Nov. 1986.

Growth and yield drivers of loblolly pine in the southeastern U.S.: A meta-analysis

2019 ◽  
Vol 435 ◽  
pp. 205-218 ◽  
Author(s):  
Héctor I. Restrepo ◽  
Bronson P. Bullock ◽  
Cristian R. Montes
Keyword(s):  
Loblolly Pine ◽  
Meta Analysis ◽  
Growth And Yield

A Graphical Comparison of Loblolly Pine Growth-and-Yield Models

2013 ◽  
Vol 37 (3) ◽  
pp. 169-176 ◽  
Author(s):  
James E. Henderson ◽  
Scott D. Roberts ◽  
Donald L. Grebner ◽  
Ian A. Munn
Keyword(s):  
Loblolly Pine ◽  
Growth And Yield ◽  
Graphical Comparison ◽  
Growth And Yield Models

scholarly journals A Growth and Yield Model Incorporating Hardwood Competition for Natural Loblolly Pine Stands in the Georgia Piedmont

1999 ◽  
Vol 23 (3) ◽  
pp. 179-185 ◽  
Author(s):  
Stacey W. Martin ◽  
Graham H. Brister
Keyword(s):  
Loblolly Pine ◽  
Basal Area ◽  
Growth And Yield ◽  
Parameter Estimates ◽  
Yield Model ◽  
Pinus Taeda L ◽  
Projection Equations ◽  
Georgia Piedmont ◽  
The Impact ◽  
Over Time

Abstract Using 5 yr remeasurement data from even-aged natural loblolly pine (Pinus taeda L.) stands in the Georgia Piedmont, a system of growth equations was developed to project pine yield over time that accounts for hardwood competition. In this system, the increase in the proportion of hardwood basal area over time is estimated, then the projected pine basal area and trees per acre are adjusted inversely to account for this increase. The parameter estimates for this system ensure compatibility between volume prediction and projection equations and the proportion of hardwood basal area, pine basal area, dominant height, and trees per acre projection equations. The whole-stand growth and yield system developed here coupled with published merchantable yield equations allow for the evaluation of the impact of hardwoods on future stand yield and product distributions. The results indicate that the impact of hardwood competition on pine yield is substantial and occurs mainly as a reduction in sawtimber volume. South. J. Appl. For. 16(3):179-185.

scholarly journals To Blend or Not to Blend? A Framework for Nationwide Landsat–MODIS Data Selection for Crop Yield Prediction

2020 ◽  
Vol 12 (10) ◽  
pp. 1653
Author(s):  
Yang Chen ◽  
Tim R. McVicar ◽  
Randall J. Donohue ◽  
Nikhil Garg ◽  
François Waldner ◽  
...  
Keyword(s):  
Crop Yield ◽  
Temporal Frequency ◽  
Management Strategies ◽  
Crop Growth ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Landsat Images ◽  
Yield Model ◽  
Pixel Resolution ◽  
Country Level

The onus for monitoring crop growth from space is its ability to be applied anytime and anywhere, to produce crop yield estimates that are consistent at both the subfield scale for farming management strategies and the country level for national crop yield assessment. Historically, the requirements for satellites to successfully monitor crop growth and yield differed depending on the extent of the area being monitored. Diverging imaging capabilities can be reconciled by blending images from high-temporal-frequency (HTF) and high-spatial-resolution (HSR) sensors to produce images that possess both HTF and HSR characteristics across large areas. We evaluated the relative performance of Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat, and blended imagery for crop yield estimates (2009–2015) using a carbon-turnover yield model deployed across the Australian cropping area. Based on the fraction of missing Landsat observations, we further developed a parsimonious framework to inform when and where blending is beneficial for nationwide crop yield prediction at a finer scale (i.e., the 25-m pixel resolution). Landsat provided the best yield predictions when no observations were missing, which occurred in 17% of the cropping area of Australia. Blending was preferred when <42% of Landsat observations were missing, which occurred in 33% of the cropping area of Australia. MODIS produced a lower prediction error when ≥42% of the Landsat images were missing (~50% of the cropping area). By identifying when and where blending outperforms predictions from either Landsat or MODIS, the proposed framework enables more accurate monitoring of biophysical processes and yields, while keeping computational costs low.

Relation of Nantucket Pine Tip Moth Attack and Fusiform Rust Infection in Loblolly Pine Families

1991 ◽  
Vol 15 (4) ◽  
pp. 204-208 ◽  
Author(s):  
Roy L. Hedden ◽  
Roger P. Belanger ◽  
Harry R. Powers ◽  
Thomas Miller
Keyword(s):  
Loblolly Pine ◽  
Cost Effective ◽  
Growth And Yield ◽  
Insecticide Treatment ◽  
Fusiform Rust ◽  
Rust Infection ◽  
Nantucket Pine Tip Moth ◽  
Combined Control ◽  
Economic Analyses ◽  
The Relationship

Abstract The relationship between pine tip moth attack and fusiform rust infection was studied in a 12-year-old loblolly pine stand in Houston County, GA. Four pine families were selected for study, and 24 trees of each family were felled for evaluation. The lower 8 ft of each tree was cut into two 4-ft sections and split to reveal the pith. Each section was examined for evidence of pine tip moth attack and the presence of fusiform rust galls. The analysis revealed 476 tip moth attacks and 99 fusiform rust galls. Forty-six of the rust galls occurred at the same place as a tip moth attack. These results, when combined with those of previous studies, suggest that the control of the pine tip moth may reduce the incidence of fusiform rust. Growth and yield simulations and economic analyses indicate that insecticide treatment of loblolly pine for the combined control of the pine tip moth and the associated reduction in levels of fusiform rust infection may be potentially cost effective in stands managed for sawtimber, but not for pulpwood. South. J. Appl. For. 15(4):204-208.

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