Small Mammal Responses to Intensively Established Pine Plantations in Coastal Plain Mississippi

2013 ◽  
Vol 37 (1) ◽  
pp. 53-58 ◽  
Author(s):  
Brice B. Hanberry ◽  
Scott L. Edwards ◽  
Stephen Demarais ◽  
Jeanne Jones
Keyword(s):  
Small Mammal ◽  
Coastal Plain ◽  
Pine Plantations

Small Mammal Responses to Site Preparation Techniques in North Carolina Coastal Plain Pine Plantations

2013 ◽  
Vol 37 (4) ◽  
pp. 226-232 ◽  
Author(s):  
Vanessa R. Lane ◽  
Karl V. Miller ◽  
Steven B. Castleberry ◽  
Darren A. Miller ◽  
T. Bently Wigley ◽  
...  
Keyword(s):  
North Carolina ◽  
Small Mammal ◽  
Coastal Plain ◽  
Site Preparation ◽  
Pine Plantations ◽  
Preparation Techniques

Water Quality Effects of Clearcutting Upper Coastal Plain Loblolly Pine Plantations

1985 ◽  
Vol 14 (3) ◽  
pp. 329-332 ◽  
Author(s):  
D. C. Mc Clurkin ◽  
P. D. Duffy ◽  
S. J. Ursic ◽  
N. S. Nelson
Keyword(s):  
Water Quality ◽  
Loblolly Pine ◽  
Coastal Plain ◽  
Pine Plantations

Influences of pine plantations on small mammal assemblages of the Patagonian forest-steppe ecotone

Mammalia ◽  
2011 ◽  
Vol 75 (3) ◽  
Author(s):  
María Victoria Lantschner ◽  
Verónica Rusch ◽  
John P. Hayes
Keyword(s):  
Small Mammal ◽  
Pine Plantations ◽  
Forest Steppe ◽  
Mammal Assemblages ◽  
Patagonian Forest

Wintering Birds in Intensively Established Pine Plantations of Coastal Plain Mississippi

2013 ◽  
Vol 37 (2) ◽  
pp. 91-96 ◽  
Author(s):  
Brice B. Hanberry ◽  
Phillip Hanberry ◽  
Samuel K. Riffell ◽  
Stephen Demarais ◽  
Jeanne C. Jones
Keyword(s):  
Coastal Plain ◽  
Pine Plantations ◽  
Wintering Birds

Predicting Stand Attributes of Loblolly Pine in West Gulf Coastal Plain Using Gradient Boosting and Random Forests

2020 ◽  
Author(s):  
Xiongwei Lou ◽  
Yuhui Weng ◽  
Luming Fang ◽  
HL Gao ◽  
Jason Grogan ◽  
...  
Keyword(s):  
Loblolly Pine ◽  
Random Forests ◽  
Coastal Plain ◽  
Mean Squared Error ◽  
Pine Plantations ◽  
Machine Learning Techniques ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Gulf Coastal Plain ◽  
Intensively Managed

Two machine-learning techniques, gradient boosting (GB) and random forests (RF), were used to predict stand mean height (HT), trees per hectare (Tree ha-1) and basal area per hectare (BA ha-1) based on datasets collected from extensively- and intensively-managed loblolly pine plantations in the West Gulf Coastal Plain region. Models were evaluated using coefficient of determination (R2), bias and root mean squared error (RMSE) by applying models to independent dataset and then compared to the model (Coble et al. 2017) currently being used in the region. For extensively-managed plantations, the GB models had less bias, larger R2 and smaller RMSE than RF and HT model was the best, followed by those of Tree ha-1 and BA ha-1. Even for BA ha-1, the GB model had R2 over 0.83. GB and RF models outperformed the Coble et al. (2017); differences were notable for HT and Tree ha-1, but significant for BA ha-1. For intensively-managed plantations, GB and RF were similarly great in predicting HT and Tree ha-1, but GB outperformed RF in predicting BA ha-1. We recommend the use of GB models to predict quantitative information required for managing loblolly pine plantations in the region.

Influence of Oak Control and Pine Growth on Fusiform Rust Incidence in Young Slash and Loblolly Pine Plantations

1995 ◽  
Vol 19 (4) ◽  
pp. 151-156 ◽  
Author(s):  
Robert A. Schmidt ◽  
James E. Allen ◽  
Roger P. Belanger ◽  
Thomas Miller
Keyword(s):  
Loblolly Pine ◽  
Coastal Plain ◽  
Pine Plantations ◽  
Border Zone ◽  
Fusiform Rust ◽  
Loblolly Pines

Abstract The influence of oak control and pine growth on fusiform rust incidence (percentage trees infected) on rust-susceptible slash and loblolly pines was evaluated at age 5 yr at seven potentially high-rust-incidence locations in the Coastal Plain of FL, GA, and MS. Rust-susceptible oaks were reduced or eliminated in a 9 ac treatment block and the surrounding 500 ft border zone of an oak-free (OF) area; oaks were not controlled in an adjacent oak-present (OP) area. At four of seven locations, rust incidence was significantly greater on the OF areas compared with the OP areas, and among all locations, average rust incidence on pine was greater (Pr > F = 0.06) on the OF areas (51.4%) than on the OP areas (40.0%). Greatly reducing rust-susceptible oak stems in the treatment blocks and in a surrounding 500 ft border did not reduce rust incidence on rust-susceptible slash or loblolly pine. Inoculum to infect pine came from beyond the 500 ft border zone. Greater pine height, associated with reduced competition from oaks, likely contributed to the greater rust incidence on pine in the OF areas. South. J. Appl. For. 19(4):151-156.

Removal of Competing Vegetation from Established Loblolly Pine Plantations Increases Growth on Piedmont and Upper Coastal Plain Sites

1996 ◽  
Vol 20 (4) ◽  
pp. 188-193 ◽  
Author(s):  
James C. Fortson ◽  
Barry D. Shiver ◽  
Lois Shackelford
Keyword(s):  
Loblolly Pine ◽  
Coastal Plain ◽  
Basal Area ◽  
Pine Plantations ◽  
Slope Position ◽  
Age Classes ◽  
Individual Tree ◽  
Competing Vegetation ◽  
Positive Treatment ◽  
The Individual

Abstract A series of paired plots was installed in loblolly pine plantations at 42 locations in Georgia's Piedmont and Alabama's Piedmont and Coastal Plain. One plot of each pair had all competing vegetation eliminated. The other plot was left as an uncontrolled check. Locations were stratified over two age classes (5-9 and 12-16 yr old) and three slope positions (top, midslope, and bottom). Analysis of 33 surviving locations 8 yr after treatment revealed a positive treatment effect for both individual tree (dbh and total height) and stand characteristics (basal area per acre, total volume per acre, and merchantable volume per acre). There was no difference in volume response between age classes. Slope position was not significant for the individual tree variables, but was significant for the stand variables, with midslopes responding most positively followed by bottom and then top slope positions. Over all locations, the average treatment response was approximately ½ cord/ac/yr. Economic analyses indicate that the magnitude of the response will be economical for many stumpage prices, particularly on midslope and bottom slope positions, in plantations where access and species composition make herbicide spraying possible. South J. Appl. For. 20(4):188-192.

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

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