Dynamic growth model simulation for carbon stock management in dry forest

The model described in this article was simulated in order to provide the best recommendations related to the management of dry forest carbon stock. The methodology of this study is based to the dynamic growth model (CO2fix V3.1). The model was developed to calculate and estimate dry forest carbon fluxes and stocks. In this study the model was utilized for estimating how much carbon is sequestered in Diospyros celebica, Eucalyptus urophylla, Tectona grandis and mixed woods and soils. The results of this study show that in the 200 years simulated, total C stock had a tendency of increase. All of modules showed very similar patterns from 0 years to 40 years, except for bioenergy. Biomass had the highest value of carbon stock around 236.9 MGCHA–1, carbon soil around 292.7 MGCHA–1, product carbon storage around 226.8 MGCHA–1 and bioenergy carbon storage presented a sustained increase and reached 522.3 MGCHA–1 in the end of the simulated period. The contribution of the tree species component to total carbon stock was significantly positively correlated (R2 = 0.634–0.882, P < 0.05) with the time simulated in years, except foliage of Diospyros celebica (R2 = 0.301), foliage of Tectona grandis (R2 = 0.162) and foliage of Eucalipthus urophylla (R2 = 0.256). However, future studies should involve detailed examination on below-ground fraction and the effects of humans on global ecosystems.The model described in this article was simulated in order to provide the best recommendations related to the management of dry forest carbon stock. The methodology of this study is based to the dynamic growth model (CO2fix V3.1). The model was developed to calculate and estimate dry forest carbon fluxes and stocks. In this study the model was utilized for estimating how much carbon is sequestered in Diospyros celebica, Eucalyptus urophylla, Tectona grandis and mixed woods and soils. The results of this study show that in the 200 years simulated, total C stock had a tendency of increase. All of modules showed very similar patterns from 0 years to 40 years, except on bioenergy. Biomass had the highest value of carbon stock around 236.9 MGCHA–1, carbon soil around 292.7 MGCHA–1, product carbon storage around 226.8 MGCHA–1 and bioenergy carbon storage presented a sustained increase and reached 522.3 MGCHA–1 in the end of the simulated period. The contribution of the tree species component to total carbon stock was significantly positively correlated (R2 = 0.634–0.882, P < 0.05) with the time simulated in years, except foliage of Diospyros celebica (R2 = 0.301), foliage of Tectona grandis (R2 = 0.162) and foliage of Eucalipthus urophylla (R2 = 0.256). However, future studies should involve detailed examination on below-ground fraction and the effects of humans on global ecosystems.