Survival Functions for Site-Prepared Slash Pine Plantations in the Flatwoods of Georgia and Northern Florida

1981 ◽  
Vol 5 (2) ◽  
pp. 59-62 ◽  
Author(s):  
Leon V. Pienaar ◽  
Barry D. Shiver
Keyword(s):  
Management Strategies ◽  
Slash Pine ◽  
Pine Plantations ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Survival Functions ◽  
Inventory Data ◽  
The Difference ◽  
Prediction Systems ◽  
Future Growth

Abstract Survival functions are derived for site-prepared slash pine plantations in the flatwoods of Georgia and northern Florida. Two functions are presented. The first is a function which may be used with any planting-survival count or estimate. This function is probably most useful in conjunction with available yield-prediction systems (with stems/acre as an input) to evaluate alternative management strategies. The second function, the difference equation form of the first function, is most useful in predicting future growth and yield based on inventory data.

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 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.

scholarly journals A New Whole-Stand Model for Unmanaged Loblolly and Slash Pine Plantations in East Texas

2009 ◽  
Vol 33 (2) ◽  
pp. 69-76 ◽  
Author(s):  
Dean W. Coble
Keyword(s):  
Loblolly Pine ◽  
Basal Area ◽  
Pinus Elliottii ◽  
Current Data ◽  
Slash Pine ◽  
Pine Plantations ◽  
Growth And Yield ◽  
East Texas ◽  
Age Classes ◽  
Yield Model

Abstract A new compatible whole-stand growth-and-yield model to predict total tree cubic-foot volume per acre yield (outside and inside bark) was developed for unmanaged loblolly pine (Pinus taeda) and slash pine (Pinus elliottii) plantations in East Texas. This model was compared with the noncompatible whole-stand model of Lenhart (<xref ref-type="bibr" rid="B15-2127">Lenhart, 1996</xref>, Total and partial stand-level yield prediction for loblolly and slash pine plantations in east Texas, South. J. Appl. For. 20(1):36–41) and the <xref ref-type="bibr" rid="B15-2127">Lenhart (1996)</xref> model refit to current data. For the two species, all three models were evaluated with independent observed data. The model developed in this study outperformed both Lenhart models in prediction of future yield and basal area per acre for all age classes combined and by 5-year age classes. The Lenhart models consistently overestimated yield and basal area per acre. All three models predicted surviving trees per acre similarly. An example is also provided to show users how to use the new whole-stand model.

Postthinning growth and yield of row-thinned and selectively thinned loblolly and slash pine plantations

1989 ◽  
Vol 19 (2) ◽  
pp. 247-256 ◽  
Author(s):  
V. C. Baldwin Jr. ◽  
D. P. Feduccia ◽  
J. D. Haywood
Keyword(s):  
Loblolly Pine ◽  
Unit Area ◽  
Basal Area ◽  
Site Index ◽  
Slash Pine ◽  
Pine Plantations ◽  
Growth And Yield ◽  
Growth Responses ◽  
Diameter Increment ◽  
Study Results

This study compared growth responses in planted loblolly pine (Pinustaeda L.) and slash pine (P. elliottii Engelm.) stands thinned by using three row-felling methods and at the same density levels, three selective felling methods. The study plots were in six plantations, aged 15–22 years, located in central Louisiana. Growth was measured 5 and 10 years after plot installation. Site index varied from 19.5 to 31.7 m (base age 50) and initial planting densities ranged from 1993 to 2989 trees/ha. Study results show there will likely be less diameter increment and less net basal area and cubic-metre volume per unit area growth and yield, and the growth will be in smaller-sized trees, if row thinning is used rather than selective thinning from below. These differences will probably be greater in slash pine plantations than in loblolly pine plantations.

A Density-Management Diagram for Slash Pine Plantations in the Lower Coastal Plain

1992 ◽  
Vol 16 (4) ◽  
pp. 178-185 ◽  
Author(s):  
Thomas J. Dean ◽  
Eric J. Jokela
Keyword(s):  
Coastal Plain ◽  
Pinus Elliottii ◽  
Slash Pine ◽  
Pine Plantations ◽  
Growth And Yield ◽  
Graphical Form ◽  
Annual Increment ◽  
Growing Stock ◽  
Management Regimes ◽  
Lower Coastal Plain

Abstract Data from 92 regional, midrotation-fertilizer trials were used to develop a density-management diagram for site-prepared slash pine (Pinus elliottii var. elliottii) plantations. The density-management diagram shows the interrelationships of five important stand variables (i.e., quadraticmean diameter (Dq), trees/ac, site height, standing volume/ac, and relative current annual increment) in a graphical form. The diagram can aid foresters in designing and comparing alternative density-management regimes for slash pine. In doing so, foresters can evaluate individualtree and stand level performances in relation to growing stock levels and make field approximations of growth and yield for various density-management regimes. Results indicated that fertilization and soil type had minimal effects on the diagram's isolines. This suggests broad applicabilityof the diagram for fertilized or unfertilized plantations found in the lower Coastal Plain. The use of the diagram is illustrated with three alternative density-management regimes, and a method is presented for estimating midrotation fertilization responses. South. J. Appl. For. 16(4):178-185

Effect of Soil Type and Site-Preparation Method on Growth and Yield of Flatwoods Slash Pine Plantations

1979 ◽  
Vol 3 (3) ◽  
pp. 95-100 ◽  
Author(s):  
Barry D. Shiver ◽  
James C. Fortson
Keyword(s):  
South Carolina ◽  
Soil Type ◽  
Preparation Method ◽  
Pinus Elliottii ◽  
Site Preparation ◽  
Slash Pine ◽  
Pine Plantations ◽  
Growth And Yield ◽  
Percent Survival ◽  
Lower Site

Abstract Analysis of measurements from slash pine (Pinus elliottii Engelm.) plantations in the flatwoods of Georgia, Florida, and South Carolina showed that plantations located on areas where debris had been moved (KG, bulldozed, rootraked, etc.) had significantly higher site indices than plantations located on comparable areas where debris had not been moved. Plantations located on spodic soils had significantly lower site indices than plantations located on nonspodic soils. While these differences were statistically significant, they were generally less than 2 feet at age 25. Neither volume nor percent survival was significantly affected by site-preparation classes or soils groups.

Yield Prediction for Mechanically Site-Prepared Slash Pine Plantations

1990 ◽  
Vol 14 (3) ◽  
pp. 104-109 ◽  
Author(s):  
Leon V. Pienaar ◽  
Henry H. Page ◽  
John W. Rheney
Keyword(s):  
Coastal Plain ◽  
Solid Wood ◽  
Slash Pine ◽  
Pine Plantations ◽  
Yield Prediction ◽  
Management Regimes ◽  
Solid Wood Product ◽  
Permanent Sample Plot ◽  
Projection Equations ◽  
Lower Coastal Plain

Abstract Simultaneous yield prediction and projection equations are presented for both unthinned and thinned site-prepared slash pine plantations in the lower coastal plain of Georgia and north Florida. These equations were developed from permanent sample plot data representing different planting densities and thinning intensities, replicated at 29 locations throughout the region. An equation is also provided to estimate different solid wood product yields, thus providing information for a realistic evaluation of management regimes with different planting densities, with or without thinning. South. J. Appl. For. 14(3):104-109.

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