The attributes of nematodes are presented as valuable tools for determining the quality of soil, especially that of mining companies. The aim of this study was to evaluate the behavior of nematodes against a stress gradient in a rainy season and a dry season in soils influenced by mining. Thus, field sampling was carried out over 100 m2 in triplicate for four types of soils classified according to their uses (pasture, maize cultivation, fig cultivation, and eucalyptus cultivation), and these areas were located on the periphery (500 to 1500 m) of the Ollachea mining community of Puno in Peru; subsequently, the samples were processed in the laboratory to determine edaphic, agrochemical, heavy metal, and microbiological parameters and identify the nematodes. The abiotic stress gradient was determined by a principal component analysis; and through a canonical correlation analysis, the relationships between the abiotic stress gradient and the nematodes were determined. Canonical correlation analysis showed that there were significant correlations: in the rainy season, Helicotylenchus and vanadium (r = 0.99), Globodera and titanium (r = 0.97), and Tylenchus and lead (r = 0.96); in the dry season: Meloidogyne and vanadium (r = 0.99), and Hemicycliophora and lead (r = 0.91). In conclusion, the abiotic stress gradient had a high correlation with bacterivorous, fungivorous, and phytoparasitic nematodes and a low correlation with omnivorous and predatory nematodes, showing the bioindicator capacity of nematodes in relation to stress parameters that impact soil quality.

The physicochemical and biological indices have been used in isolation; if the parameters of these indices were applied in an integrated manner, they would bring together in a single measure the functional and structural variability of the biotic and abiotic components of water quality. The aim of this study was to build a comprehensive water quality index. Eleven sampling points were selected considering different degrees of agro-industrial intervention. 21 abiotic variables and 27 biological metrics were measured. Macroinvertebrates were quantitatively collected and identified to family taxonomic level. Using Principal Component Analysis, after standardization and exclusion of uncorrelated variables (VIF ≤ 10), the abiotic gradient was determined, which represented the abiotic variables that explained the disturbances in the water; with the abiotic gradient and the biological metrics, a Pearson correlation was performed, and those biological metrics that presented a high and non-redundant correlation were selected (Pearson 0.6 ≤ r ≤ 0.8); with the selected biological metrics, we proceeded to formulate and categorize the index; finally, by means of simple linear regression, the proposed index was compared with five other indexes (ICA, ICOMO, EPT, BMWP/col. and ASPT). The results showed that the abiotic gradient was defined by CP 1 which explained 65.5% of the accumulated variance, represented by altitude (r = 0.411), iron (r = 0.345) and dissolved oxygen (r = 0.329). The biological metrics used for the index design were: % scrapers, % swimmers, NEF of order 2, Ephemeroptera and Trichoptera tolerance. It was concluded that the integral index presents a higher predictive level (R2 = 0.87) of water quality, compared to the other indices: ASPT (R2 = 0.79), BMWP/col. (R2 = 0.68), EPT (R2 = 0.61), ICOMO (R2 = 0.35) and ICA (R2 = 0.27).

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