Predictions of individual-tree and whole-stand attributes for loblolly pine plantations

Quang V. Cao

doi:10.1016/j.foreco.2006.09.019

Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurements of height and crown dimensions

Forest Ecology and Management ◽

10.1016/j.foreco.2005.03.025 ◽

2005 ◽

Vol 213 (1-3) ◽

pp. 54-70 ◽

Cited By ~ 81

Author(s):

Scott D. Roberts ◽

Thomas J. Dean ◽

David L. Evans ◽

John W. McCombs ◽

Richard L. Harrington ◽

...

Keyword(s):

Leaf Area ◽

Loblolly Pine ◽

Pine Plantations ◽

Individual Tree ◽

Tree Leaf ◽

Crown Dimensions

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Individual tree and stand-level carbon and nutrient contents across one rotation of loblolly pine plantations on a reclaimed surface mine

New Forests ◽

10.1007/s11056-018-09696-4 ◽

2018 ◽

Vol 50 (5) ◽

pp. 733-753 ◽

Cited By ~ 1

Author(s):

Hannah Z. Angel ◽

Jeremy S. Priest ◽

Jeremy P. Stovall ◽

Brian P. Oswald ◽

Yuhui Weng ◽

...

Keyword(s):

Loblolly Pine ◽

Pine Plantations ◽

Individual Tree ◽

Surface Mine ◽

Nutrient Contents

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

Southern Journal of Applied Forestry ◽

10.1093/sjaf/20.4.188 ◽

1996 ◽

Vol 20 (4) ◽

pp. 188-193 ◽

Cited By ~ 8

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.

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Modeling individual tree growth for juvenile loblolly pine plantations

Forest Ecology and Management ◽

10.1016/s0378-1127(96)03851-0 ◽

1996 ◽

Vol 89 (1-3) ◽

pp. 157-172 ◽

Cited By ~ 17

Author(s):

Shaoang Zhang ◽

Harold E. Burkhart ◽

Ralph L. Amateis

Keyword(s):

Loblolly Pine ◽

Tree Growth ◽

Pine Plantations ◽

Individual Tree ◽

Individual Tree Growth

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Using disaggregation to link individual-tree and whole-stand growth models

Canadian Journal of Forest Research ◽

10.1139/x05-284 ◽

2006 ◽

Vol 36 (4) ◽

pp. 953-960 ◽

Cited By ~ 22

Author(s):

Jianhua Qin ◽

Quang V Cao

Keyword(s):

Loblolly Pine ◽

Growth Models ◽

Basal Area ◽

Tree Model ◽

Individual Tree ◽

Stand Growth ◽

Individual Tree Model ◽

Stand Attributes ◽

Pinus Taeda L ◽

The Individual

Data from 200 plots randomly selected from the Southwide Pine Seed Source Study of loblolly pine (Pinus taeda L.) were used to fit whole-stand and individual-tree equations. Another 100 plots, also randomly selected, were used for validation. Outputs from the individual-tree model were then adjusted to match observed stand attributes (number of trees, basal area, and volume per hectare) by four disaggregation methods: proportional yield, proportional growth, constrained least squares, and coefficient adjustment. The first three are existing methods, and the fourth is new. The four methods produced similar results, and the coefficient adjustment was then selected as the method to disaggregate predicted stand growth among trees in the tree list. Results showed that, compared to the unadjusted individual tree model, the adjusted tree model performed much better in predicting stand attributes, while providing comparable predictions of tree diameter, height, and survival probability. The proposed approach showed promise in the ongoing effort to link growth models having different resolutions.

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A comparison of competition measures for predicting growth of loblolly pine trees

Canadian Journal of Forest Research ◽

10.1139/x86-218 ◽

1986 ◽

Vol 16 (6) ◽

pp. 1230-1237 ◽

Cited By ~ 126

Author(s):

Richard F. Daniels ◽

Harold E. Burkhart ◽

Terry R. Clason

Keyword(s):

Loblolly Pine ◽

Relative Size ◽

Stand Density ◽

Tree Size ◽

Size Ratio ◽

Multiple Correlation ◽

Individual Tree ◽

Growth Prediction ◽

Point Density ◽

Stand Attributes

Five families of competition indices were evaluated and compared on the basis of simple correlation with loblolly pine individual tree growth and multiple correlation with growth in the presence of other tree and stand attributes. The family of distance-independent indices included various relative size measures in the form of tree size to mean size ratios. Crown ratio was also included as a distance-independent measure. The four families of distance-dependent indices included various influence area overlap indices, distance-weighted size ratio indices, Spurr's point density, and Brown's point density or area potentially available (APA). All indices were significantly correlated with dbh and basal area growth. The relative size ratio indices, crown ratio, Spurr's point density, and several APA variations were judged best in simple correlations after accounting for tree size and stand density. The best distance-dependent indices had little if any advantage, either in simple or multiple correlation, over the best distance-independent indices. However, the point density index of Spurr and especially APA contributed significantly to growth prediction even in the presence of tree size, stand density, and the distance-independent size ratio and crown ratio indices. Further, APA had the highest partial correlation when all variables were included in this multiple correlation. It was concluded the APA would be a good index for growth prediction models when other tree and stand attributes are already known.

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