## 3 Results
### Principal Component Analysis (PCA)  
The PCA began with the development of a nonparametric Spearman correlation matrix with a Mantel test, as shown in Figure 8. This test was performed to reduce the number of variables without losing important information by calculating the relationships between the indicators evaluated. It was observed that, of the 19 indicators analyzed during the C and N mineralization dynamics experiments, TOC, TN, N-NO\({}_{3}\)\({}^{-}\), N-NH\({}_{4}\)\({}^{+}\), N\({}_{\text{min}}\), UA, DHA, SEI, MBC, C-CO\({}_{2}\), and qMIC were those that presented at least one significant interaction--either positive or negative--with another indicator (\(r^{2}\geq\pm 0.6\)). The indicators that presented a negative correlation were UA with C-CO\({}_{2}\) and qCO\({}_{2}\), indicators related to the biological phase of the soil. Also, the TN indicator presented a negative correlation with the C/N ratio, indicators that are inversely related. On the other hand, indicators with positive correlations were N\({}_{\rm min}\) with N-NH\({}_{4}\)+ and N-NO\({}_{3}\)-, all directly related to the N cycle and mineralization. In addition, the DHA indicator presented a positive interaction with the SEI indicator, both involved in the enzymatic activities of soil. A positive interaction related to OM and the microbial community in the soil was MBC with qMIC. Finally, there was a positive interaction between C-CO\({}_{2}\) and qCO\({}_{2}\), both related to the activities of aerobic microorganisms and--directly or indirectly--to the C and N cycles, respectively.  
Only one principal component (PC) was obtained from the PCA analysis, which met the eigenvalue > 1 criterion according to the methodology described in Section 2.8. This PC accounted for 83.2% of the variability of the indicators analyzed during the C and N mineralization dynamics experiments over time. The variability was distributed as shown in Figure 9.  
The analyzed indicators showed a significant correlation only with respect to PC1, as shown in Figure 10.  
It is worth highlighting the importance and innovation of simultaneously using different types of physicochemical, enzymatic, and electrophysiological indicators to develop an _SQI_ for soils with MPs, since these indicators evaluate soil quality by addressing different bioprocesses that are linked in the soil matrix. In the case of this study, there were  
Figure 8: Nonparametric Spearman correlation matrix with Mantel test. pH, hydrogen potential; EC, electrical conductivity; TOC, total organic carbon; OM, organic matter; TN, total nitrogen; C/N, carbon–nitrogen ratio; NO\({}_{2}\)–, nitrites; NO\({}_{3}\)–, nitrates; NH\({}_{4}\)+, ammonium; N\({}_{\rm min}\), mineralizable nitrogen; NI, nitrification index; UA, urease activity; DHA, dehydrogenase activity; FDA, fluorescein diacetate activity; SEI, synthetic enzymatic index; MBC, microbial biomass carbon; CO\({}_{2}\), carbon dioxide; qCO\({}_{2}\), metabolic quotient, and qMIC, microbial quotient. Significance level of \(p\leq\) 0.05, where a significant linear correlation is considered at values of \(r^{2}\geq\pm\)0.6. Levels of significant differences, * significant under of \(p\leq\) 0.05, ** very significant under of \(p\leq\) 0.01, ** and highly significant under a significance level of \(p\leq\) 0.001. Positive correlations are shown in blue, negative correlations are shown in red.**  
two physicochemical indicators directly related to N (N-NH4+ and Nmin) and one ecophysiological indicator (C-CO2) that impacted PC1.