Estimation of spatial-temporal dynamic evolution of potential reforestation lands and their carbon sequestration capacity
DOI:
https://doi.org/10.37135/ns.01.17.04Keywords:
Spatial analysis, Carbon capture, Climate change, Reforestation, Optimal zonesAbstract
Reforestation is established as a key strategy for mitigating climate change, due to the capacity of forest ecosystems to act as carbon sinks by storing this element in their above-ground biomass. This study aimed to estimate the spatial-temporal evolution of reforestation potential and carbon capture capacity in the province of El Oro by identifying optimal areas based on their climatic quality, biophysical conditioning factors, and projected carbon reserves. The methodology integrated climate data on temperature, precipitation, trend analysis, and variables such as vegetation succession and resilience, slope, and distance to roads. These variables were weighted using the weighted hierarchy approach (WHA) method, using the Random Forest (RF) model to assign relative weights, and subsequently modeled the biomass and carbon captured. The results show a climate productivity of 1780 (g/m2. a-1) in higher altitude cantons such as Piñas, Portovelo, Zaruma, Chilla, Atahualpa, and Balsas, identifying a total of 16529.85 ha with high reforestation potential. By 2090, the accumulated biomass is estimated to reach 848458.79 Mg, equivalent to 424229 Mg C. In conclusion, there is evidence of sustained growth in biomass and carbon accumulation until 2090, with greater fixation in the intermediate phases of the forest cycle and stability in density per hectare. The results highlight the importance of promoting reforestation policies that enhance carbon capture and strengthen climate adaptation strategies.
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