Assessing differential land use impacts on soil quality: A method based on log-response ratios and polygonal projections.

Soil quality indices (SQI) used for assessing soil degradation are often developed using additive scoring functions. However, these SQI may lack reference values for interpreting their outputs and the capacity to differentiate changes in specific variables. To overcome these limitations, this study introduces SQI using Log Response Ratios (LRR) as measures of size effects caused by land use in physical, chemical, and microbiological soil quality indicators. LRR vectors projected 2D polygons with condensed change measures along their perimeters. This method was tested in andosols within the southeastern region of Antioquia, Colombia. These soils were subjected to contrasting stages of degradation determined by the extent of A-horizon removal due to land use practices. This study shows that mining and agriculture have detrimental effects on soil organic carbon and water contents, and that size effects vary significantly between land uses (p < 0.05). Microbiological features also exhibit distinct size effects, such as populations of culturable mesophilic bacteria and fungi, microbial basal respiration, spore density of arbuscular mycorrhizal fungi (AMF), their diversity, and total glomalin-related soil proteins (p < 0.05). The SQI proposed exhibited a negative correlation with SQI computed from scoring additive functions either considering the entire dataset (R2 = 0.87) or a minimum dataset (R2 = 0.90). This approach underscores the utility of using LRR geometrical analysis to assess global soil quality differences among land uses (p < 0.01), offering a visual, quantifiable representation of the effects of each land use over specific soil quality indicators.

Automated software for counting and measuring Hyalella genus using artificial intelligence.

Amphipods belonging to the Hyalella genus are macroinvertebrates that inhabit aquatic environments. They are of particular interest in areas such as limnology and ecotoxicology, where data on the number of Hyalella individuals and their allometric measurements are used to assess the environmental dynamics of aquatic ecosystems. In this study, we introduce HyACS, a software tool that uses a model developed with the YOLOv3's architecture to detect individuals, and digital image processing techniques to extract morphological metrics of the Hyalella genus. The software detects body metrics of length, arc length, maximum width, eccentricity, perimeter, and area of Hyalella individuals, using basic imaging capture equipment. The performance metrics indicate that the model developed can achieve high prediction levels, with an accuracy above 90% for the correct identification of individuals. It can perform up to four times faster than traditional visual counting methods and provide precise morphological measurements of Hyalella individuals, which may improve further studies of the species populations and enhance their use as bioindicators of water quality.

Metabarcoding Reveals Impact of Different Land Uses on Fungal Diversity in the South-Eastern Region of Antioquia, Colombia.

Changes in soil fungal communities caused by land use have not been sufficiently studied in South American Andosols, which are considered key food production areas. Since fungal communities play an important role in soil functionality, this study analysed 26 soil samples of Andosols collected from locations devoted to conservation, agriculture and mining activities in Antioquia, Colombia, to establish differences between fungal communities as indicators of soil biodiversity loss using Illumina MiSeq metabarcoding on nuclear ribosomal ITS2 region. A non-metric multidimensional scaling allowed to explore driver factors of changes in fungal communities, while the significance of these variations was assessed by PERMANOVA. Furthermore, the effect size of land use over relevant taxa was quantified. Our results suggest a good coverage of fungal diversity with a detection of 353,312 high-quality ITS2 sequences. We found strong correlations of Shannon and Fisher indexes with dissimilarities on fungal communities (r = 0.94). These correlations allow grouping soil samples according to land use. Variations in temperature, air humidity and organic matter content lead to changes in abundances of relevant orders (Wallemiales and Trichosporonales). The study highlights specific sensitivities of fungal biodiversity features in tropical Andosols, which may serve as a basis for robust assessments of soil quality in the region.