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Decision Support Systems in Forest Management: An Integrated Approach

F Bwagalilo
E Liwa
R Shemdoe


Decision making process - especially in natural resources management, encounters myriad of challenges to objective decisions, significant decision depends on amount of information and capability of decision makers to handle massive data. In forest management, these challenges such as lack of enough data and cost associated with obtaining insitu spatial data, have been minimised with the use Geospatial Decision Support System (GDSS). GDSS has shown great capability of capturing, storing, analysing, retrieving and manipulating data for aiding spatial decisions. This technology proliferates quickly and as a result decision makers overlook other systems for forest governing. Following this situation, people living adjacent to forests have found it difficult to accessing forest resources - and their livelihoods, which depends on forests have been compromised. The continuing degradation of forest resources despite existence of different management strategies - such as (community based forest management and joint forest management), has made it necessary to assess decisions on forest conservation. Focus Group Discussion (FGD) strategy was applied to capture extent of use of Indigenous and Local Knowledge (ILK) and GDSS in forest management decisions, observation was applied to implicitly relate the narration from FGD and the reality while interview method was applied to forest officials to capture use of ILK in forest decision making. The results revealed that ILK related to forest management; however the uncovered ILK has been insignificantly used together with GDSS in making decision for conservation. This paper establishes the ignorance on ILK as one among other factors behind the continued forest cover depletion despite existence of conventional conservation strategies. The developed framework integrates GDSS and ILK to aid forest decisions which will ensure sustainable forest conservation and serves for forest needs of the communities adjacent.

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eISSN: 0856-6739