# The Carbon Dynamics of Dry Tropical Afromontane Forest Ecosystems in the Amhara Region of Ethiopia
## 5 Discussion  
Biogeochemical-mechanistic modeling is a powerful diagnostic tool to assess the carbon and nitrogen fluxes within our study areas. Although the species composition of the natural Afromontane forests in Ethiopia is very rich and diverse, the eco-physiological parameter settings suggested by [66] are applicable within the area. After adjusting for the length of the growing season (on the site with predominant deciduous vegetation cover) and addressing harvesting impacts, the above ground biomass, as well as soil carbon and NPP predictions derived with Biome-BGC revealed consistent estimates versus field observations (Figures 4 and 5). This suggests that our chosen approach mimics the ecosystem fluxes (i.e., carbon, nitrogen and water) as well as potential harvesting impacts correctly for Afromontane ecosystems of the Amhara region of Northwestern Ethiopia. This is an important finding because forests cover about 251,000 ha or 2% of the total land area (15.7 million. ha) in Amhara region [38], but no systematic forest monitoring or empirically driven forest growth and yield model for ensuring sustainable forest management is in place. Considering the enormous pressure of a fast-growing population on the remaining forest resources, this lack of information is one of the key obstacles for sustainable forest management in the region. The option we tested in this study to circumvent this lack of information is the application of biogeochemical-mechanistic modeling theories. Although the model results fit with the observed data (Figures 4 and 5), the limitations of the modeling approach versus growth and yield models is the level of abstraction in the general modeling approach. This makes forest stand specific predictions, including single tree mortality or specific harvesting operations, difficult [67]. This may be one of the reasons that the model predicted  
Figure 5: Soil carbon (first row) and vegetation carbon trend (second row) attained on degraded sites after afforestation, without human intervention (left) and with human intervention (2.5% thinning, center and 5% annual thinning, right). higher vegetation carbon versus the observations in Taragedam (Figure 4), as the study sites in Taragedam experienced stronger human interventions and cattle grazing versus the other study sites [71; 72]. The key problem within the highlands of the Amhara region is land use change (the conversion of forests into agricultural area) to feed a fast growing population [4; 73; 74]. An enormous loss in soil fertility due to erosion is associated with this reduction in forest area. We observed that 40 to 50 years after converting forests into agricultural land, the carbon and nitrogen content in the soil declined by 40% to 85% of the remaining neighboring forested areas (Table 3). The dramatic deterioration of the soils within this short period of time is also reported by other studies showing similar trends [75; 76]. The underlying parent material in Amhara is granite with an extremely low release of nutrients from weathering. Removal of the forest cover leads to enormous soil erosion during the heavy and intensive rainy season [34], associated with a removal of the top soil layer. Once the forest vegetation and the top soil layer are gone, the key source for nutrients is gone [32]. Future productivity is therefore jeopardized by two effects, i.e., loss in nutrients through vegetation clearing and erosion, and the low rates of replenishing of the lost nutrients from weathering of the rock and from nitrogen deposition and fixation [77]. One option to stabilize and eventually ameliorate productivity is to replant forests on such degraded sites. Any permanent land cover will decrease further erosion and will lead to nitrogen and litter input due to litterfall and consequently to a recovery of the carbon and nutrient stocks, and the water retention capacity. The rate of carbon pool accumulation varied by harvesting intensity (Figure 5).