Data Exploration

This section outlines the initial steps taken to explore the dataset prior to formal analysis. It includes examining data distributions, applying necessary transformations, identifying and excluding outliers or incorrect entries, and presenting visual summaries to better understand the dataset's structure and characteristics.

Data Tables

Table 1. Cumulative GHG (CO2, N2O and CH4 ) efflux rates

Table 2. Chemical properties of the soils

Cumulative CO2, N2O and CH4 Efflux Rates

The boxplots visualize the distributions of cumulative CO2, N2O and CH4 efflux rates across the various soil treatments. the data shows considerable variance present within many of the boxplots, particularly for CO2 and N2O in the Control (CK) and CKD treatments, indicated by their large interquartile ranges (the size of the boxes) and long whiskers. Conversely, treatments involving the three main components (CKD, DG, and HA), such as CKD-HF-HA and CKD-HF-DG, exhibit tighter data concentration with smaller interquartile ranges for both CO2 and N2O, suggesting a more consistent and reliable reduction in gas efflux compared to the high variability of the CK and CKD groups. The presence of outliers (individual dots) across several treatments confirms the necessity of outlier detection to check for potential errors or uncharacteristic flux events.