Factors affecting soil invertebrate biodiversity in agroecosystems of the Po Plain area (Italy)

Soil is a fundamental component of the biosphere, whose properties and quality are affected by human activities, such as agriculture. Soil health is fundamental for different ecosystem services and soil biota has a crucial role in maintaining it. Elucidating how different crops and agricultural practices affect soil invertebrates communities is of relevance. In the present study, a DNA metabarcoding approach was adopted to evaluate the effects of different biotic and abiotic factors, including agricultural practices, on the composition and diversity of soil invertebrate communities of different agro-ecosystems (Po Plain-Italy). At this aim, the DNA markers and the more effective primers in retrieving soil metazoan communities were established. Bulk soil samples from different agro-ecosystems (i.e., cornfield, alfalfa, paddy fields, vineyard, stable meadow, woodland) were collected and, processed for obtaining 18S rRNA and coi sequences (raw reads analyzed using QIIME2 and R). Soil physical and chemical parameters were measured for each soil sample (e.g., pH, carbon-nitrogen ratio, texture, porosity) and metadata on farms management were retrieved. The most efficient primer pairs in recovering soil metazoans were M620F/M1260R for 18S rRNA, and mlCOIintF/jgHCO2198R for coi gene. Soil communities resulted dominated by Nematoda, Arthropoda, Annelida, Rotifera and Tardigrada. The most diverse invertebrate communities have been found in the soil of stable meadows and woodlands, while cornfields showed the lowest level of diversity. The diversity of soil invertebrate communities (Hill numbers) was positively correlated with the level of porosity and carbon-nitrogen ratio, while it was negatively correlated with the phosphate abundance. This pattern probably reflects the negative effect of excessive fertilization with phosphates on soil fauna, while the abundance of organic matter and microhabitats were found to enhance the presence of more complex communities. Other soil properties were correlated only with specific taxa (e.g., pH was negatively correlated with the diversity of Annelida and Rotifera)

Sensitivity analysis of six soil organic matter models applied to the decomposition of animal manures and crop residues

Two features distinguishing soil organic matter simulation models are the type of kinetics used to calculate pool decomposition rates, and the algorithm used to handle the effects of nitrogen (N) shortage on carbon (C) decomposition. Compared to widely used first-order kinetics, Monod kinetics more realistically represent organic matter decomposition, because they relate decomposition to both substrate and decomposer size. Most models impose a fixed C to N ratio for microbial biomass. When N required by microbial biomass to decompose a given amount of substrate-C is larger than soil available N, carbon decomposition rates are limited proportionally to N deficit (N inhibition hypothesis). Alternatively, C-overflow was proposed as a way of getting rid of excess C, by allocating it to a storage pool of polysaccharides. We built six models to compare the combinations of three decomposition kinetics (first-order, Monod, and reverse Monod), and two ways to simulate the effect of N shortage on C decomposition (N inhibition and C-overflow). We conducted sensitivity analysis to identify model parameters that mostly affected CO2 emissions and soil mineral N during a simulated 189-day laboratory incubation assuming constant water content and temperature. We evaluated model outputs sensitivity at different stages of organic matter decomposition in a soil amended with three inputs of increasing C to N ratio: liquid manure, solid manure, and low-N crop residue. Only few model parameters and their interactions were responsible for consistent variations of CO2 and soil mineral N. These parameters were mostly related to microbial biomass and to the partitioning of applied C among input pools, as well as their decomposition constants. In addition, in models with Monod kinetics, CO2 was also sensitive to a variation of the half-saturation constants. C-overflow enhanced pool decomposition compared to N inhibition hypothesis when N shortage occurred. Accumulated C in the polysaccharides pool decomposed slowly; therefore model outputs were not sensitive to a variation of its decay constant. Six-month organic matter decomposition was generally higher for models implementing classical Monod kinetics, followed by models with first-order and reverse Monod kinetics, due to the effect of soil microbial biomass growth on decomposition rates. Moreover, models implementing Monod kinetics predicted positive priming effects of native organic matter after soil amendment, according to co-metabolism theory. Thus, priming was proportional to the increase of the microbial biomass and in turn to the decomposability of applied organic matter. We conclude that model calibration should focus only on the few important parameters

INFLUENCE OF GROUND COVER AND SOIL PROPERTIES ON BIOLOGICAL SOIL QUALITY IN ECOSYSTEMS OF THE PO VALLEY

The characterization of the soil physicochemical properties together with the knowledge of the biological diversity associated to this substrate are fundamental to assess the soil quality and to support political decision relative to agricultural and natural ecosystems. The soil is a complex environment in which different taxa (bacteria, fungi and metazoan) play a fundamental role in regulating the organic matter decomposition and nutrient recycling, influencing the ability to maintain the ecosystem services and agricultural production sustainability. In the early 2000s QBS-ar index (Qualità Biologica del Suolo – artropodi) was developed and arose as one of the most used indexes to assess soil biological quality. This index assigns a morphometric score, based on the level of adaptation to edaphic environment, to arthropods extracted through Berlese funnel from soil samples. In this project we collected soil samples from environments with different ground covers (grapevine, corn, rice, mixed forest, alfalfa, stable meadow), for each sample we measured physicochemical properties (i.e., texture, pH, organic carbon and nitrogen) and computed the QBS-ar index. The analysis of variance and a subsequent post-hoc comparison showed a subdivision of the crop into two different groups: the first containing corn, rice and alfalfa 1-3 years and the second with grapevine, mixed forest and alfalfa 4-5 years. The stable meadow is found in both groups. Among the different physicochemical properties analyzed, organic carbon and nitrogen positively correlate with the QBS-ar, while the percentage of sand in the soil correlates negatively with the index. These results support the conclusion that less disturbed soil can sustain higher biological diversity

A multi-element psychosocial intervention for early psychosis (GET UP PIANO TRIAL) conducted in a catchment area of 10 million inhabitants: study protocol for a pragmatic cluster randomized controlled trial

Multi-element interventions for first-episode psychosis (FEP) are promising, but have mostly been conducted in non-epidemiologically representative samples, thereby raising the risk of underestimating the complexities involved in treating FEP in 'real-world' services