Modeling Primary Productivity and Communities’ Perception for Climate Change Resilience Building in the Mount Kenya Landscape

Abstract

Climate change is arguably the greatest threat to ecosystem services, biodiversity and livelihood of communities in the Mount Kenya landscape. To guarantee an impartial understanding of the complex link between climate change ecosystem services and livelihoods; this study used Human Ecological Approach (HEA), and looked at dynamic interrelationships between human populations and the physical, biotic, cultural and social characteristics of the environment and the biosphere. In this study land users’ perception was used to anticipate human action in response to climate change using the available natural resources or ecosystem services estimated through net primary productivity (NPP). Human impact was assessed using human appropriation of net primary production (HANPP), which estimated biomass availability used as an indicator of resilience. The general goal was to integrate Communities’ perception and modeled primary productivity estimates for building resilience to climate change in the Mount Kenya landscape. In order to address the challenge of socioeconomic and unique regional geographical setting, a customized methodological framework was developed. This was for application in assessment of climate change vulnerability perception and adaptation options around the Mount Kenya landscape. Indicators of climate change and variability most appropriate for the region were derived from the IPCC.Focused discussions were held involving key informants in various sectors of the economy drawn from the Mount Kenya landscape used to pick relevant indicators. Using these indicators, a structured questionnaire was developed from which surveys and interviews were done on a selected sample of the target population of farming communities in the Mount Kenya landscape. The key highlights of the questionnaire were vulnerability and adaptation. Data obtained from respondents was standardized and subjected to multivariate and ANOVA analysis. Based on principle component analysis (PCA), two main vulnerability categories were identified, namely the social and the bio-physical vulnerability indicators. Analysis of variance using Kruskal-Wallis test showed significant statistical variation (P ≤ 0.05) in the perceived vulnerability across the spatial distribution of the 198 respondents. Ecosystem service analysis for carbon sequestration started by land cover and land use assessments. Landsat Thematic Mapper (TM) satellite imagery was used for land use and land cover classification. Existing land use and land cover information were also collected from the United Nations Environmental program (UNEP) geo-portals. The supervised classification approach was used to determine land cover. The Mount Kenya landscape was found to be in the subsistence state of land use transition. The subsistence small-scale farming constituted about 30%, while forest, shrub land, and grassland together were about 40% of the cover that was characterized by the frontier clearing of these wild lands. To determine the level and distribution of primary productivityand carbon stock in the Mount Kenya landscape CASA model was used. Land use and land cover maps were generated from Landsat 7 ETM sensor, and vegetation stress scalars of temperature and moisture derived from Thornthwaite water balance model. The aboveground net primary production results for 2002 ranged