Forest Carbon Inventory: A Comprehensive Dataset on Tree Biomass and Carbon Sequestration Matrices using Dendrometric Analysis across Various Districts of Gujarat State, India
Description
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.
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Define Study Area and Sampling Design: Identify the specific districts or regions to be surveyed and establish a robust sampling methodology (e.g., systematic plots, random plots) to ensure representative data collection; Tree Species Identification and Family Classification: Accurately identify each tree species encountered within the sample plots and classify them into their respective botanical families; Dendrometric Measurements: For each sampled tree, measure key parameters such as Diameter at Breast Height (DBH) (from which radius can be derived) and total tree height (H); Volume Estimation: Utilize established allometric equations or volume tables specific to the tree species or regional forest types to estimate the individual tree volume (m3) based on measured DBH and height; Above Ground Biomass (AGB) Estimation: Apply appropriate allometric equations (often incorporating DBH, height, and wood density) to calculate the Above Ground Biomass (kg) for each tree. This typically includes stems, branches, and foliage, Below Ground Biomass (BGB) Estimation: Estimate Below Ground Biomass (kg) (roots) using allometric equations or root-to-shoot ratios derived from AGB, considering species-specific or regional factors; Total Biomass Calculation: Sum the AGB and BGB for each tree to determine its Total Biomass (kg); Carbon Weight Calculation: Convert total biomass to carbon weight (kg) by applying a carbon fraction (typically assumed to be 0.47 to 0.50, or species-specific values (if available) to the total biomass; CO2 Equivalent Weight Calculation: Convert the carbon weight (kg) to CO2 equivalent weight (kg) by multiplying by the ratio of the molecular weight of CO2 to carbon (44/12 or approximately 3.67); Data Aggregation and Quality Control: Aggregate the individual tree data by family and district, perform calculations for sums or averages as needed, and conduct thorough quality control checks to ensure data accuracy, consistency, and completeness.