MINERÍA la mejor puerta de acceso al sector minero MINERÍA / SEPTIEMBRE 2023 / EDICIÓN 552 104 mente, para 1/D fue de 16.69 (DE 33.87). Igualmente la misma muestra que presentó una alta riqueza, SNC1-2, también presentó los valores más altos para el resto de los índices de diversidad estudiados. En cuanto al análisis multivariante con los índices de alfa diversidad respecto a las condiciones de estudio, primero, se comprobó la normalidad de los datos, al no cumplir este requisito, se aplicaron técnicas no paramétricas como Kruskal-Wallis y Wilcoxon para evaluar posibles asociaciones entre estos índices biológicos y las condiciones experimentales, corrigiendo por múltiples comparaciones. Se evaluaron si existían diferencias estadísticamente significativas entre las muestras contaminadas (AC+SC) frente a las muestras no contaminadas (ANC+SNC) independientemente del material de soporte de la muestra (agua o suelo), no hallándose ningún índice significativo. Por lo que se procedió a comparar dentro del mismo soporte, buscando diferencias respecto a la contaminación, no hallándose tampoco diferencias ni en riqueza ni en diversidad entre AC vs ANC y entre SC vs SNC. Aparte de los índices de diversidad alfa, existen otros indicadores ecológicos, llamados índices de diversidad beta que evalúan la biodiversidad entre grupos de muestras definidos por las variables experimentales (Gotelli & Colwell, 2001). En este caso, se estudió la posible asociación entre los microorganismos detectados y el tipo de muestra (AC/ANC/SC/SNC), con el fin de detectar diferencias en cuanto al perfil microbiano usando el índice de Figura 5. Abundancia relativa observada (%) de los órdenes de procariotas. Cada barra vertical representa una muestra (N=13). Se presentan los órdenes más abundantes en todas las muestras y los taxones con una abundancia global inferior al 1% fueron colapsados en una sola categoría nombrada como “Otros” (en gris). Figure 5. Observed relative abundance (%) of prokaryote orders. Each vertical bar represents one sample (N = 13). The most abundant orders in all samples are shown and taxa with an overall abundance of less than 1% were collapsed into a single category named "Other" (in gray). 10, 10 and 14 ZOTU, respectively. The rest of indices represent the diversity in the sample, for these indices the following mean values were obtained for the set of samples: Shannon index (H) was 2.70 (SD 1.00); for the PD index, which also takes into account the phylogenetic distances between ZOTU, it was 12.36 (SD 11.95); finally, for 1/D it was 16.69 (SD 33.87). Also the same sample that presented a high richness, SNC1-2, also presented the highest values for the rest of the diversity indices studied. As for the multivariate analysis with the alpha diversity indices with respect to the study conditions, first, the normality of data was checked, and when this requirement was not met, non-parametric techniques such as Kruskal-Wallis and Wilcoxon were applied to evaluate possible associations between these biological indices and the experimental conditions, correcting for multiple comparisons. Statistically significant differences between contaminated samples (AC+SC) and noncontaminated samples (ANC+SNC) were evaluated independently of the sample support material (water or soil), and no significant index was found. Therefore, we proceeded to compare within the same support, looking for differences with respect to contamination, finding no differences either in richness or diversity between AC vs ANC and between SC vs SNC. Apart from alpha diversity indices, there are other ecological indices, called beta diversity indices, which evaluate biodiversity among groups of samples defined by experimental variables (Gotelli & Colwell, 2001). In this case, the possible association between the microorganisms detected and the type of sample (AC/ ANC/SC/SNC) was studied in order to detect differences in terms of microbial profile using the weighted UniFrac phylogenetic dissimilarity index. With the distance matrix, the Permanova test was performed, carrying out 999 permutations and correction for multiple comparisons by FDR (p<0.05). Likewise, the homoscedasticity of variances was tested multivariate and, once the distance matrix was obtained, the ordination method known as principal coordinate analysis or PCoA was applied. The groups were homogeneous (p = 0.340), however, no differences were detected between the microbial communities of the four conditions evaluated (p = 0.550), as corroborated in Figure 2, which shows the arrangement of the samples in the PCoA ordination system (Figure 4), no groups of samples are observed according to their characteristics, as can be seen the SC samples are far from each other showing that they have diverse microbial profiles, as for the water samples (AC and ANC) except for one duplicate, they are grouped together but together with non-contaminated soil samples (SNC). The maximum explained variability was 60%. Although the variability explained by the first two components was high, this does not generate clear sample groupings. In conclusion, the richness
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