Abstract:
By sinking and storing carbon from the atmosphere via photosynthesis, forests play a significant
role in combating climate change. Global warming is currently the most pressing global issue.
Forests play an important role in the global carbon cycle, covering 30% of the world's terrestrial
land area and conserving 81% of the earth's terrestrial carbon biomass. The aim of the study was
to quantify and map the Carbon Sink and Stock Values of the Yeraba state forest ecosystem.
Primary and secondary data sources were used in this study. Primary data such as plot length and
width, DBH (diameter at breast height), soil data, and ground control point (GCP) were obtained
in the field using a Garmin 72 GPS, a clinometer, and a diameter tape. Diameter tape, caliper and
Soil ogre materials. Beside from this sentimental 2 satellite image, there was also another
important primary data. In addition to the primary data source, secondary data sources were used.
It includes published books, journals and studies, reports, website sources, and other materials
that are publicly available. The systematic sampling technique for identifying each intersection
point in the area at regular intervals was the most appropriate sampling design for this study. The
study used data from four forest carbon pools, including AGB, BGB, soil, and litter, to calculate
the carbon sink and stock values of the Yeraba state forest ecosystem. A total of 17 quadrats, each
measuring 20m x 20m and spaced 428 m apart, were used to collect vegetation data. For litter
and soil sample collection, five 1 m x 1 m sub-quadrats were established at each quadrat's four
corners and center. This data was correlated with five Sentinel 2A level 1c imagery data derived
vegetation indices of 2023 to obtain a model and estimate of AGB and AGC at the study site. The
total mean carbon stock density of Yeraba state Forest was 404.895 t/ha, with 223.656t/ha,
58.15t/ha, 3.41t/ha, and 119.679 t/ha in the above ground carbon, below ground carbon, litter
carbon, and soil carbon pools, respectively. The three environmental factors that influence the
distribution of different carbon pools in the forest are altitudinal gradient, slope, and aspect.
Standing from the result and inputs the researcher recommended that, Future research may find
that using LiDAR and Radar imageries, which can address the saturation and canopy penetration
issues, will increase the accuracy of carbon stock estimation.