A decision support model for estimating above-ground carbon stock changes in Mabira forest reserve

Abstract

Forests are major contributors to the carbon cycle, sustainable forest management is key for stabilising carbon emissions, global warming and climate change. Mabira forest is one of the tropical high forests in Uganda but reports indicate that the forest is increasingly suffering from deforestation and forest degradation. This has led to continuous carbon emissions thus the need to constantly perform carbon estimations. Literature has recorded the spatial and temporal limitations during ground inventory of above-ground carbon estimations in Mabira. This study’s goal was to come up with a decision support model for estimating above-ground carbon changes for Mabira forest. This was achieved through using design science methodology in which we identified requirements for model development, the iterative model development and evaluation process, and validation with stakeholders. Ground inventory data, tool evaluation and model validation data was analysed using excel and SPSS for respective results. Ground inventory results showed higher amounts (55%) of above-ground carbon in the strict nature reserve compared to buffer zone (23 %) and production zone (22%). The regression model evaluation results presented that the NDVI based regression model performed better (R²=0.96, RMSE=1.04%, P-value<0.04 and Bias=0.001) than RVI and MSAVI. The Decision support system (DSS) functionality evaluation showed a strong association between the functionality stakeholder responses and the perceived level of agreement (χ2= 56.21, df = 16, p<0.001). Additionally, the experts agreed with the model design (Chi-square χ2= 1, df =5, p<0.001). The major achievement of this research project included the development of a decision support model for estimating above-ground carbon stock changes and DSS development for monitoring above-ground carbon stock. Based on the results similarity between ground inventory and remotely sensed finding, we recommend that the developed decision support model be adopted, further evaluated and implemented by National Forestry Authority for estimating above-ground carbon stock changes in Mabira forest for sustainable forest management.