Department of Natural Resources
Permanent URI for this collectionhttp://localhost:4000/handle/20.500.12092/1949
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Item Comparing Tree Heights among Montane Forest Blocks of Kenya Using LiDAR Data from GLAS(Scientific Research Publishing, 2015) Kinyanjui, Mwangi James; Kigomo, Ngugi John; Kamau, Miriam Wambui; Nderitu, Joel Kariuki; Nyanjui, Charles; Nganga, John Macharia; Ojijo, William Odidi; Ashiono, Fredrick; Owate, Augustine Omamo; Ndirangu, Monicah KatumbiThis study was designed to use LiDAR data to research tree heights in montane forest blocks of Kenya. It uses a completely randomised block design to asses if differences exist in forest heights: 1) among montane forest blocks, 2) among Agro ecological zones (AEZ) within each forest block and 3) between similar AEZ in different forest blocks. Forest height data from the Geoscience Laser Altimeter System (GLAS) on the Ice Cloud and Land Elevation Satellite (ICE- SAT) for the period 2003-2009 was used for 2146 circular plots, of 0.2 - 0.25 ha in size. Results indicate that, tree height is largely influenced by Agro ecological conditions and the wetter zones have taller trees in the upper, middle and lower highlands. In the upper highland zones of limited human activity, tree heights did not vary among forest blocks. Variations in height among forest blocks and within forest blocks were exaggerated in regions of active human intervention.Item Developing a Forest Management Plan (DFMP) for Gatsibo District in the Eastern Province of Rwanda(Scientific Research Publishing Inc., 2018) Kinyanjui, Mwangi James; Rurangwa, Felix; Bazimaziki, Frederick; Peeters, Jacques; Munyehirwe, Anicet; Musoke, Francis; Habiyaremye, Gaspard Nelson; Bakundukize, Dismas; Ngabonziza, Prime; Uwase, JostIn support of conservation of its fragile land resource, the government of Rwanda has proposed the management of all forests in the country under a specific management plan. This assignment sought to develop a management plan for the public productive forests of Gatsibo District in Eastern province of Rwanda. Data was collected from 1468 plots, proportionally allocated by size to the 375 forest stands. Information about the forest (qualitative data) was recorded and then forest measurements (inventory) done in a concentric cycle of 9.77 m and 3.99 m radius and all data recorded in a digital format using the survey CTO platform. The data was summarized and analyzed in a harmonized forest management tool for Rwanda comprising of six interlinked excel files based on Rwanda’s silvicultural regimes and treatments. This analysis resulted to planning for silvicultural activities in each forest up to the year 2070. Results show that the public plantation forests of Gatsibo are poorly stocked mainly due to poor management and the best stocked forest had a basal area of only 13.3 m2/ha. This implied low forest volumes for each of the wood requirements; timber wood, service wood and energy wood. Eucalyptus forests are the most common but are poorly stocked compared to the Pinus patula forests which are even aged by plantation. A projection of stocks shows that the forests can be sustained with an average wood volume of 73 m3/ha, to provide harvests yearly and reduce the wood supply and demand gap in the district. A viability analysis indicates that some forests are viable for leasingwith good profits in the short term (10 years) and full term planning (40 years). However, some forests may not be commercially viable due to their current stocks and agro bioclimatic conditions, and these would be rehabilitated for ecosystem services. This plan supports the restoration of the forests of Gatsibo district through provision of specific guidelines for the management of the forests.Item Biomass Energy Resource of the Highland Bamboo (Yushania alpina) and Its Potential for Sustainable Exploitation in Southern Aberdares Forest(Scientific Research Publishing Inc., 2017) Kinyanjui, Mwangi James; Katumbi, Ndirangu Monicah; Kimondo, JM; Mware, Mugo JosephYushania alpina is the only bamboo species native to Kenya and covers about 150,000 ha growing in pure or mixed stands in the montane forests. The Aberdare forest is one of the natural habitats for Y. alpine occupying an area of 6419 ha mainly in the water catchment areas. The growing human population and depletion of other forest resources have necessitated the exploration of Y. alpine as a source of energy. This paper assessed the quantity of Y. alpine available for biomass energy and its potential for sustainable exploitation. Plots were laid on area maps to cater for altitude and distance from farms. The study area was stratified into three altitudinal zones: A (2220 - 2330 m), B (2331 - 2440 m) and C (2441 - 2550 m). The initial sampling plot of 10 m × 10 m was located randomly 500 m from the edge of the forest while the subsequent plots were laid out systematically at intervals of 500 m. In each plot, a total enumeration and biomass estimation of bamboo clumps were done using Muchiri and Muga (2013) [1] method. Bamboo samples and those of commonly used biomass energy sources were analysed for calorific value using bomb calorimeter. In addition, data for quantities of biomass energy used by some local industries were used to estimate the amount of bamboo required. The mean stocking was 19,981 (20,000) culms ha−1, and varied significantly among altitude strata and distance from adjacent farms. The mean biomass density and energy content were 86 tons/ha and 380,893 Kca/ha respectively with the higher altitudinal stratum (zone C) having the highest means (114 tons/ha) while the lower stratum (zone A) had the lowest (65 tons/ha). Theenergy needed by sampled local industries was 416,276,266 Kcal per year against 2.4 billion Kcal available in the bamboo forest. This implies that the bamboo forest in its present stocking can provide biomass energy for these local industries for more than five years. With bamboo maturing with less than five years, the forest can sustainably provide the required energy while still providing its environmental services.Item Allometric Equations for Estimating Silk Oak (Grevillea robusta) Biomass in Agricultural Landscapes of Maragua Subcounty, Kenya(Hindawi International Journal of Forestry Research, 2018) Mugo, Joseph Mware; Kinyanjui, Mwangi James; Owate, Omamo AugustineGrevillea robusta is widely interplanted with crops in Maragua subcounty, a practice that enhances biomass quantities in farmlands. However, quick tools for estimating biomass of such trees are lacking resulting in undervaluation of the farm product. This study sought to develop allometric equations for estimating tree biomass using diameter at breast height (DBH) and tree height as predictor variables. Tree biomass was computed using thirty-three (33) trees randomly selected from 12 one hectare plots established in each of the four agroecological zones (AEZs). DBH of all Grevillea robusta trees per plot was measured and three trees were selected for destructive sampling to cover the variety of tree sizes. Regression analysis was used to develop equations relating DBH/tree height to biomass based on linear, exponential, power, and polynomial functions. Te polynomial and the power equations had the highest R2 , lowest SEE, and MRE values, while DBH was the most suitable parameter for estimating tree biomass. Te tree stem, branches, foliage, and roots biomass comprised 56.89%, 14.11%, 6.67%, and 22.32% of the total tree biomass, respectively. Te mean tree biomass density (12.430±1.84 ton ha−1) showed no signifcant diference (p=0.09) across AEZs implying no diference in G. robusta agroforestry stocks across the AEZ. Te allometric equations will support marketing of tree products by farmers and therefore better conservation and management of the tree resource.Item Estimation of Above Ground Biomass in Forests Using Alos Palsar Data in Kericho and Aberdare Ranges(Scientific Research Publishing, 2017) Kinyanjui, Mwangi James; Odera, Patroba Achola; Maina, Eunice WamuyuAbove Ground Biomass is one of the six pools identified in the inventory of forest resources and estimation of greenhouse gas emissions and sinks from the forestry sector. The pool varies by management practices in different agro- ecological or agro-climatic zones in forests. The quantification of above ground biomass (AGB) hence carbon sequestration in forests has been very difficult due to the immense costs required. This research was done to estimate AGB using ALOS PALSAR L band data (HH, HV polarisation) acquired in 2009 in relation with ground measurements data in Kericho and Aberdares ranges in Kenya. Tree data information was obtained from ground measurement of DBH and tree heights in 100 circular plots of 15 m radius, by use of random sampling technique. ALOS PALSAR image is advantageous for its active microwave sensor using L-band frequency to achieve cloud free imageries, and the ability of long wavelength cross-polarization to estimate AGB accurately for tro- pical forests. The variations result between Natural and plantation forest for measured and estimated biomass in Kericho HV band regression value was 0.880 and HH band was 0.520. In Aberdare ranges HV regression value of 0.708 and HH band regression value of 0.511 for measured and estimated biomass respectively. The variations can be explained by the influence of different management regimes induced human disturbances, forest stand age, density, species composition, and trees diameter distribution. However, further research is required to investigate how strong these factors affect relationship between AGB and Alos Palsar backscatters.Item Estimation of Above Ground Biomass in Forests Using Alos Palsar Data in Kericho and Aberdare Ranges(Scientific Research Publishing, 2017) Kinyanjui, Mwangi James; Odera, Patroba Achola; Maina, Eunice WamuyuAbove Ground Biomass is one of the six pools identified in the inventory of forest resources and estimation of greenhouse gas emissions and sinks from the forestry sector. The pool varies by management practices in different agro- ecological or agro-climatic zones in forests. The quantification of above ground biomass (AGB) hence carbon sequestration in forests has been very difficult due to the immense costs required. This research was done to estimate AGB using ALOS PALSAR L band data (HH, HV polarisation) acquired in 2009 in relation with ground measurements data in Kericho and Aberdares ranges in Kenya. Tree data information was obtained from ground measurement of DBH and tree heights in 100 circular plots of 15 m radius, by use of random sampling technique. ALOS PALSAR image is advantageous for its active microwave sensor using L-band frequency to achieve cloud free imageries, and the ability of long wavelength cross-polarization to estimate AGB accurately for tro- pical forests. The variations result between Natural and plantation forest for measured and estimated biomass in Kericho HV band regression value was 0.880 and HH band was 0.520. In Aberdare ranges HV regression value of 0.708 and HH band regression value of 0.511 for measured and estimated biomass respectively. The variations can be explained by the influence of different management regimes induced human disturbances, forest stand age, density, species composition, and trees diameter distribution. However, further research is required to investigate how strong these factors affect relationship between AGB and Alos Palsar backscatters.