Research Report No. 28, Tree Content and Taper Functions for Planted Loblolly and Slash Pine Trees in East Texas, Update: June 1993, Revised: September 1993

In 1987, tree content and tree taper functions for individual live standing planted loblolly and slash pine trees in East Texas were published 1. These equations were developed based on stem analyses of felled trees located adjacent to East Texas Pine Plantation Research Project (ETPPRP) permanent plots throughout East Texas. The 1987 report was based on 65 loblolly and 34 slash pine trees sampled during 1986. For both species, dbh (0) values ranged from about 2-12 inches and total height (H) values varied from about 10-60 feet

Research Report No. 27, Site Index Equations for Loblolly and Slash Pine Plantations in East Texas, Update: 1993

In 1986, equations to estimate site index in loblolly and slash pine plantations in East Texas were published. These equations were developed using data collected from East Texas Pine Plantation Research Project (ETPPRP) permanent plots distributed throughout East Texas. The site index prediction equations were designed to estimate tree height 25 years from planting, ie., index age = 25 years. In the 1986 study, only data recorded during the first measurement cycle of the ETPPRP (1982- 1984) were available for analysis. Pairs of observed plantation age and a\u27verage !otal height of the ten tallest trees values were accessible from 150 permanent plots in loblolly pine plantations and 75 sample plots in slash pine plantations. For both species, approximately 85% of the data pairs were 1 o years or younger. In this update, new versions of site index prediction equations are presented for these two pine species based on information from repeated measurements of the ETPPRP permanent plots during 1982-1992. To date, almost all the ETPPRP plots have been measured four times. The loblolly pine site index equation is based on the analysis of 608 age-height pairs, and the slash pine site index prediction equation is derived from 264 age-height pairs. Original data pairs from the 1986 study are included in this new expanded data set. which represents a 3 to 4 fold increase in data size. As a result, the updated equations should quantify the productivity of the East Texas planted areas in a more accurate and reliable manner

Modelling growth of swietenia macrophylla (mahogany) plantation in Gum-Gum Forest Reserve, Sabah.

Growth models can contribute to the forest management decision making process by providing stand development forecasts. Mahogany plantation in Gum-Gum Forest Reserve Sabah was planted in 1968 with spacing 2.74×2.74 m within an area of 0.52 hectare. Diameter at breast height (dbh) and tree height data were collected from year 1969 to 2006. This study aimed to determine the efficient regression equations for growth prediction of the mahogany plantation. Regression models were developed by search from literature as a basis references. Four diameter prediction models and six height prediction models were developed. Proc Reg in SAS was used to evaluate the regression equations. Performance of the model was measured by using root mean square error (RMSE), bias and coefficient of determination (R2). The chosen diameter prediction model is lnH=3.07-10.42D-1+0.1lnA with RMSE (0.31), bias (1.76) and R2 (0.68). The recommended prediction model slightly underestimated the actual diameter. The chosen height prediction model is lnD=354-3.98A-1 with RMSE (0.11), bias (0.01) and R2 (0.91). This recommended height prediction model gives very close height estimate to the actual height

Modelling survival and growth prediction of Swietenia macrophylla king (mahogany) plantation at Kolapis, Sabah.

This study was carried out to determine the appropriate growth model for Swietenia macrophylla plantation at Luang Manis, Kolapis, Sabah. It included exploratory data analysis, development of survival and growth prediction models, basal area estimation and model comparison to determine the most appropriate model to predict the optimum age for harvesting. The growth prediction models were evaluated using Proc Reg and Proc Nlin in SAS and Kaplan Meier estimation was adapted for survival estimation. The models were compared on the basis of bias, root mean square error (RMSE) and coefficient of determination (R2). The results were supported by the findings from the basal area prediction. Results showed that the most suitable diameter prediction models were; lnD̂=3.49-(5.45/A) with RMSE (0.40), bias (1.43) and R2 (0.56) and lnD̂=0.97+0.73 lnA with RMSE (0.40), bias (1.45) and R2 (0.55). While the recommended height prediction model was lnĤ=1.00+0.12D-0.0016D2 with RMSE (0.22), bias (-2.01) and R2 (0.86). The growth prediction models recommended that the optimum age that give maximum yield per hectare is at 25 years