Forest Carbon Inventory: A Comprehensive Dataset on Tree Biomass and Carbon Sequestration Matrices using Dendrometric Analysis across Various Districts of Gujarat State, India

This abstract presents an analysis of a detailed dataset focusing on the biomass characteristics and carbon sequestration potential of various tree families across different districts of Gujarat State, India. It provides crucial insights into the ecological contributions of diverse tree species, offering valuable information for environmental assessment and climate change mitigation strategies. The data is meticulously structured to include information on each tree family, the number of trees (N) sampled within family, and specific district of origin. Key dendrometric parameters are quantified, such as radius (m), radius squared (m2), and height (H). These measurements enable the calculation of tree volume (m3), which is a primary indicator of tree size and growth. Based on the physical attributes, the dataset further derives essential biomass metrics: Above Ground Biomass (AGB), Below Ground Biomass (BGB), and Total Biomass. A central objective of this dataset is the precise quantification of carbon capture capabilities. It meticulously calculates the Carbon Weight, representing the actual carbon stored within the biomass. Furthermore, it provides the equivalent Carbon Dioxide (CO2) Weight, offering a direct measure of the greenhouse gas sequestration capacity of each tree family. The total carbon is also presented, providing a macro-level perspective on the carbon sink potential of the surveyed areas. Families such as Bombacaceae stand out with exceptionally high values for Total Biomass (e.g., 296,573 kg) and CO2 Weight (e.g., 694,645 kg), underscoring their substantial role in atmospheric carbon reduction. Conversely, other families, like Oleaceae, exhibit considerably lower values (e.g., Total Biomass of 2,789 kg and CO2 Weight of 5,118 kg). This disparity highlights the diverse ecological functions and varied capacities for carbon storage inherent in different tree species, emphasizing the importance of species-specific characteristics in determining overall carbon sequestration efficiency. For climate change mitigation efforts, the data facilitates the identification of high-performing tree species and families that are ideal candidates for targeted afforestation and reforestation initiatives. Moreover, the district-wise breakdown allows for localized environmental assessments, empowering policymakers, and conservationists to develop precise and effective interventions for sustainable forestry management and regional carbon footprint reduction strategies. The detailed metrics provided can inform strategic land-use planning, optimize the implementation of carbon credit projects, and significantly contribute to global efforts in combating climate change by enhancing natural carbon sinks. The dataset's granularity offers a robust foundation for developing predictive models of carbon sequestration rates under various environmental conditions and management practices, thereby supporting proactive environmental management.