Monday, September 21, 2015
Pest Management in Commercial Forestry
Friday, September 18, 2015
Species Selection in Commercial Forestry
Friday, November 7, 2014
Maho Plantations: Establishment of a Mahogany Plantation
By realising the timber value of Mahogany, Maho Plantations Ltd. has also started creating mahogany plantations in Sri Lanka. The company head office is at Narahenpita. The mahogany plantations are mainly concentrated in Kurunegala area. The company provides variety of investment benefits to their investors.
Maho Plantations Ltd. has a competent team of consultants who has experience and knowledge in the field of plantation management and they take care of the mahogany plantations. This company does not only plant mahogany trees on the land acquired, but also has taken steps to intercrop banana as a value addition to the existing mahogany lands. This practice enables the company to provide returns ranging from short-term to long-term, and everything in between. Plus, as a result of unparalleled planning and forest management practices, the harvest yields consistently forecast returns that are above the industry average.
The company is looking forward to expand the land area and the variety of species used, to identify new business opportunities, such as Carbon fixation value of the plantation and achieving ISO 14001 and ISO 9001 standards.
Thursday, September 19, 2013
Establishment of hypothetical forest Plantation Company for (Swietenia macropylla) AirForest Plantation Limited
Though AirForest entered into forestry and agricultural plantation industry only 15 years ago (1998), the management of AirForest has decades of experience and knowledge in the field of plantation management. Currently, the company is managing plantations at Kurunegala, Monaragala, Galle, Udawalawa, Badulla, Kegalle and Beragala. (over 250 ha, island wide). AirForest is one of the forestry management companies which use Drip Irrigation System. This ensures a higher and rapid growth and a maximum harvest as each and every tree gets sufficient nutrition by drippers.
AirForest Plantations ensures continuous monitoring and improvements by forestry consultants and experts in the industry and over 15,000 delighted clients in Sri Lanka. It provides harvest-purchase back guarantee, with many additional offers with exclusive premier membership benefits
This value addition is also a very important aspect in the plantation sector because it is eventually a business, and the increasing of profit becomes underlying target. The value addition to a plantation can be done in several aspects. It can be either by increasing the quantity of the timber produced from the plantation or by improving the quality of the mahogany produced and also especially by increasing the utility of the plantation land. Company exporting the Mahogany fruit (Sky Fruit) as a byproduct obtains from the plantation.
Currently company is planning to expand the land area of the plantations and the plantation species verities. And Carbon fixing value is identified as a new business opportunity.
Monday, December 21, 2009
Establishment of relationships of growth at 7-year old mahogany trees with selected site factors
Change of crown diameter with dbh of mahogany
Due to the lack of research studies on mahogany, the objective of the present study was to establish an empirical model to predict crown diameter accurately using dbh. For this purpose, data were collected from 16 mahogany monocultures in Kalutara, Ratnapura and Matale districts. In order to represent the whole plantation, sixty trees were selected from good, moderate and poor areas from each plantation.
In order to build a reliable model, theoretical basic structures were developed assuming the crown diameter is a function of tree dbh. This basic structure was fitted to the data as linear, exponential, and logistic form separately for different growth types. In addition to the untransformed variables, transformations were also made whenever possible. Suitable candidate models were preliminary selected by R2 and residual distributions. After further analysis, it was proven that the best results were given by the logistic model structure for good, moderate and poor site types (R2 = 92.0%, 71.4%, 65.9% respectively). In order to eliminate the difficulty of using separate models for different growth types, the possibility of using a common model for all growth types were tested. For this reason, one way ANOVA was used for residuals of different growth types generated after fitting respective models. Results indicated that it was possible to use a common model and therefore the logistic form was re-fitted to pooled data.
The final model was “crown diameter = 0.645 + 2.682 / (1+exp (-0.356 (dbh –7.749)))” and it had a R2 of 60.9%.
Monday, November 30, 2009
Establishment of relationships of growth with site factors and some selected soil parameters of a selected 7 years old mahogany plantation in Eheliyag
Establishment of relationships of growth with site factors and some selected soil parameters of a selected 7 years old mahogany plantation in Eheliyagoda DS, using GIS as a tool
B.Sc. Dissertation
Himesha Randeni and Upul Subasinghe
Mahogany (Swietenia macrophylla) is an exotic tree, which is heavily adapted to the climatic conditions of wet and intermediate zones of Sri Lanka. Although the state sector manages mahogany with longer rotations, private sector expects to achieve the maximum timber yield within a shorter period. Due to the land scarcity, many of these mahogany plantations have been established in barren and rubber uprooted lands which were heavily degraded. Therefore the soil conditions and site factors directly affect the growth of the mahogany within short rotations.
The present study was carried out in a 7 years old mahogany monoculture plantation established in Gomaragala, in low country wet zone of Sri Lanka to find out the effect of soil and site factors to the mahogany tree growth. Extent of this forest is 20.7 ha and it is managed by a private plantation company. This forest has been divided into 2 lots for the purpose of administration. However, for the sales purposes it has been divided into 240 plots.
In order to identify the relationships, tree dbh and tree height as growth parameters; slope and terrain were selected as geographical factors as well as soil texture, soil organic carbon level and soil pH levels were selected as soil parameters. The growth parameters (i.e.dbh and height) were measured of all the trees in plantation. Slope and terrain as geographical parameters were measured of all 240 plots in the entire plantation. Soil parameters namely soil pH, soil organic carbon and soil texture were measured for systematically selected 50 plots out of 240 plots to represent the entire plantation. There are some qualitative parameters namely tree growth, terrain, presence of bedrock, included into the present study. These were usually assessed to give a single value for each plot.
Since the regression based methods was not adequate for both qualitative as well as quantitative parameter analysis, GIS based analysis was decided to use for the present study, because it serves as an analytical and decision supporting tool. ArcView 3.3 was used for this purpose. In order to create digital maps, the survey plan of the selected forest was digitized and georeferanced by main 10 ground control points collected by a GPS data receptor. Then the georeferanced base map was digitized to demarcate all the plots and other land marks. After that different maps were prepared in vector form separately for each parameter. However, for the analysis, all these vector layers were converted to raster layers. Raster layers were then reclassified and overlaid two or three layers at a time with the growth parameters to identify the effects. Then map analysis was completed to make decisions regarding tree growth in different site factors and soil conditions with similar other environmental conditions. Since the soil pH, soil organic carbon level and soil texture were measured in selected 50 plots out of 240 plots, the raster layers were interpolated for entire area.
Changes of branch and crown characteristics with stem parameters and age of Swietenia macrophylla even-aged monocultures
Changes of branch and crown characteristics with stem parameters and age of Swietenia macrophylla (mahogany) even-aged monocultures
B.Sc. Dissertation
Shyanika Lakmali and Upul Subasinghe
Growth predictions in the plantation forestry play a vital role in order to maximize the future gains specially in the field of economy. Plantations of mahogany monocultures in private sector directly focus in the timber production and thereby the financial gain. Tree growth is accompanied with the photosynthesis process and it increases the stem parameters of the trees. Therefore there is a close relationship between crown development and tree growth. In addition to that, crown growth causes a competition after the canopy closure in the forest plantations.
The main objective of the present study was to establish a series of empirical models for predicting the relationships between stem, crown and branch parameters. In addition to that an attempt was taken to predict the above parameters with age. It was expected to use those relationships to prepare a pruning schedule for mahogany monoculture plantations in
In order to achieve the objectives, data were collected from 16 mahogany monocultures in Kalutara, Ratnapura and Matale districts. In order to represent the whole plantation, due to growth differences, sixty trees were selected from each of plantation as twenty trees from each good, moderate, and poor growing areas. The measurements were taken including dbh, total tree height, crown diameter, height to the first branch, height to the second branch, branch lengths and base diameters up to two branches.
Regression analysis was employed to build the suitable relationships between related variables. Both linear and non-linear regression equations were tested for each relationship using MINITAB and GENSTAT statistical software. In order to obtain the best equations, both qualitative (R2 ) and quantitative (residual distribution and fitted line plots) were used. Initially, the data were grouped as good, moderate and poor growth types. Then different theoretical model structures (linear with untransformed and transformed variables, exponential and logistic) were separately fitted to those data. After that the best model was selected for each relationship for each growth type. At this point, it was a must to select the similar model structure (with different regression parameter sets) for each relationship in each growth type.