EXPERIMENTAL METHOD 1 Material and tools

Bogor, 21-22 October 2015 507 1964; Davis and Johnson, 1987; Davis et al., 2001. Diameter dimensions is important in the management of forest stands because it has properties that is correlated with the growth of other dimensions eg, basic field and volume and can easily be measured in accurate ways Gertner et al., 1996. In recent years, delimitation of limit diameter cutting on natural forest production in Indonesia has been lowered. It will impact on the number of trees to be felled because trees in natural forests have a pattern of increasingly large diameter trees, the number the less, it can be seen from several studies that the diameter distribution of the natural forests have a pattern of inverted J is increasingly large diameter trees then the fewer number of trees Bettinger et al., 2009; Abdurachman 2011; Abdurachman, 2013; Susanty and Setiawan, 2013. Development modeling growth estimate since 200 years ago in support of the preparation of good forest management of natural forests forests are not lifetime and plantations forest lifetime is still underway recover Vanclay, 2003; Henning and Burk, 2004; Metcalf et al. , 2009. Determination of value increment individuals and forest stand is very important in setting efficient results to provide growth models as quantitative tools in forest planning Vanclay, 1989. This study aims to determine model of periodic increment for individual trees and stands in variuos dipterocarp forest condition to support forest management practices. 2. EXPERIMENTAL METHOD 2.1 Material and tools The research material in the form of logged forest and primary forest with repeated measurements of all kinds of trees with a diameter of 10 cm limit on permanent plots include data: name of tree species, around the trunk chest height 1.3 m or 20 cm above buttresses. Tools used are the compass, clinometers, measuring tape phi band and distribution maps of trees. 2.2 Data collection Observation plots measuring 200 mx 200 m 4 ha is divided into sub-plots of 100 mx 100 m 1 ha and 25 sub subplot measuring 20 mx 20 m. Plots consisted of a series of permanent plots with four variations of the condition of forest stands with a total of 12 plots 48 ha. Minutes of the plot in the form of primary forest in 1990 and carried out logging with different techniques, namely: environmentally friendly harvesting techniques reduced impact logging RIL diameter limit of 50 cm RIL50, RIL limit diameter of 60 cm RIL60, conventional logging limit diameter 60 cm CNV and the control primary forest. Measurements are periodically carried out every two years. 2.3 Data Analysis Increment is calculated periodically annual periodic increment PAI with a formula approach Loetsch et al. 1973 and Husch et al. 2003 as the following: PAI = Cumulative dimension as periodic for n years n years Bogor, 21-22 October 2015 508 Individual increment calculation based on the average diameter increment cm 2th-1 and increment by basal area of stands m 2 ha -1 2yr -1 . rd i = d o – d i where as: rd i = tree diameter increment cm 2yr -1 d o = tree diameter on initial measurement cm d i = tree diameter on next measurement after 2 years cm rBD i = bd o – bd i where as: rBD i = basal area increment of stand m 2 ha -1 2yr -1 bd o = basal area of stand on initial measurement m 2 ha -1 bd i = basal area of stand on next measurement 2 years m 2 ha -1 Increment calculation done by grouping Dipterocarpaceae, non Dipterocarpaceae and all species. Rate differences forest conditions against individual increment and increment of stands using analysis of variance ANOVA. The relationship between the period of the second increment value is carried out by regression analysis. Regression equations were tested are as follows: Y = + X Linear Eq.1 Y = + 1 X + 2 X 2 Polinomialkuadratik pangkat 2 Eq.2 Y = + 1 X + 2 X 2 + 3 X 3 Polinomialkuadratik pangkat 3 Eq.3 Y = е X Eksponensial Eq.4 Y = + logX Logaritma Eq.5 Selection of the most appropriate model is done with a scatter diagram technique is based on the value of the correlation coefficient r and coefficient of determination R2 and the highest value of the standard error SE, the smallest Steel and Torrie, 1995. 3. RESULT AND DISCUSSION 3.1 Tree individual increment