Comparison and Prediction of the above Ground Carbon Storage in Croplands on the Inhabited Slopes on Mount Kilimanjaro (Tanzania) and the Taita Hills (Kenya) — Oak Academic Publishing
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Comparison and Prediction of the above Ground Carbon Storage in Croplands on the Inhabited Slopes on Mount Kilimanjaro (Tanzania) and the Taita Hills (Kenya)
Center of Biodiversity, National Museums of Keny, Nairobi, Kenya
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Department of Geospatial and Space Technology, The University of Nairobi, Nairobi, Kenya
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Center of Biodiversity, National Museums of Keny, Nairobi, Kenya
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Earth Change Observation Laboratory, Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
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York Institute for Tropical Ecosystems (KITE), Environment Department, University of York, York, UK
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Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, Finland
1 Center of Biodiversity, National Museums of Keny, Nairobi, Kenya
2 Department of Geospatial and Space Technology, The University of Nairobi, Nairobi, Kenya
3 Center of Biodiversity, National Museums of Keny, Nairobi, Kenya
4 Earth Change Observation Laboratory, Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
5 York Institute for Tropical Ecosystems (KITE), Environment Department, University of York, York, UK
6 Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, Finland
Mount Kilimanjaro and the Taita Hills are adjacent montane areas that experience similar climate and agricultural activity, but which differ in their geologic history, nature of elevation gradients and cultures. We assessed differences in cropland above ground carbon (AGC) between the two sites and against environmental variables. One hectare sampling plots were randomly distributed along elevational gradients stratified by cropland type; AGC was derived from all trees with diameter ≥ 10 cm at breast height in each plot. Predictor variables were physical and edaphic variables and human population. A generalized linear model was used for predicting AGC with AIC used for ranking models. AGC was spatially upscaled in 2 km buffer and visually compared. Kilimanjaro has higher AGC in cropped and agroforestry areas than the Taita Hills, but only significant difference in AGC variation in agroforestry areas (F = 9.36, p = 0.03). AGC in cropped land and agroforestry in Kilimanjaro has significant difference on mean (t = 4.62, p = 0.001) and variation (F = 17.41, p = 0.007). In the Taita Hills, significant difference is observed only on the mean AGC (t = 4.86, p = 0.001). Common tree species that contribute the most to AGC in Kilimanjaro are Albizia gummifera and Persea americana , and in the Taita Hills Grevillea robusta and Mangifera indica . Significant and univariate predictors of AGC in Mount Kilimanjaro are pH (R 2 = 0.80, p = 0.00) and EVI (R 2 = 0.68, p = 0.00). On Mount Kilimanjaro, the top multivariate model contained SOC, CEC, pH and BLD (R 2 = 0.90, p = 0.00), whereas in the Taita Hills, the top multivariate model contained elevation, slope and population (R 2 = 0.89, p = 0.00). Despite of the difference in land management history of Mount Kilimanjaro and the Taita Hills, mean of AGC in croplands does not differ significantly. Difference occurs on variation of AGC, type of trees contributing AGC, and environmental variables that explain AGC distribution. The research results provide reference for management of carbon sequestration on inhabited montane areas.
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