SARS-CoV-2 is responsible for the COVID-19 pandemic. Airflows sustain the infection spread, and in densely urbanized areas airborne particulate matters (PMs) are deemed to aggravate the viral transmission. Apis mellifera colonies are used as bioindicators as they allow environmental sampling of different nature, PMs included. This experiment demonstrates for the first time the possible use of honey bee colonies in the SARS-CoV-2 monitoring. The trial was conducted in Bologna on 18 March 2021, when the third wave of the Italian pandemic was at its peak and environmental conditions allowed high PM concentrations in the air. Sterile swabs were lined up at the hive entrance to sample the dusty material on the body of returning foragers. All of them resulted positive for the target genes of viral SARS-CoV-2 RNA. Likewise, internal samples were taken, but they resulted in no amplification of the target sequences. This experiment does not support speculations about the role of honey bees or their products in SARS-CoV-2 transmission. However, it indicates a novel use of A. mellifera colonies in the environmental detection of airborne human pathogens, at least in a densely urbanized area, deserving better understanding and possible integration with data from automatic air samplers.

The pollination ecology in agroecosystems tackles a landscape in which plants and pollinators need to adjust, or be adjusted, to human intervention. A valid, widely applied approach is to regard pollination as a link between specific plants and their pollinators. However, recent evidence has added landscape features for a wider ecological perspective. Are we going in the right direction? Are existing methods providing pollinator monitoring tools suitable for understanding agroecosystems? In Italy, we needed to address these questions to respond to government pressure to implement pollinator monitoring in agroecosystems. We therefore surveyed the literature, grouped methods and findings, and evaluated approaches. We selected studies that may contain directions and tools directly linked to pollinators and agroecosystems. Our analysis revealed four main paths that must come together at some point: (i) the research question perspective, (ii) the advances of landscape analysis, (iii) the role of vegetation, and (iv) the gaps in our knowledge of pollinators taxonomy and behavior. An important conclusion is that the pollinator scale is alarmingly disregarded. Debate continues about what features to include in pollinator monitoring and the appropriate level of detail: we suggest that the pollinator scale should be the main driver.

Agriculture has both direct and indirect effects on quality of surface water and is one of the key activities causing water quality degradation. Its environmental impact can be evaluated by the determination of indicators of the quality of water bodies that collect drainage and runoff waters from agricultural watersheds. For this research, the water quality draining from three watersheds, totally or partially cultivated, all within the Po river valley (Italy), was determined, using chemical indicators (N-NO3 and N-NH4 concentration, N balance), trophic status (chlorophyll-a concentration) and benthic population indexes. Together, they should provide an overview of the water status, which is supposed to be strictly related to the land use and the management. Results show that the chemical parameters are well related to land use and farming management: intensive agricultural activity leads to high N-NO3 concentration in water and N surplus and vice versa. The chlorophyll-a concentration follows the same trend, being linked to nitrogen loads and land use. Not always there is accordance between chemical and biological indicators: no direct correspondence is evident between the N-NO3 concentration in waters and benthic community. Its presence and abundance seems to be mostly correlated with the geomorphology, hydrology, riparian strips, etc. of the habitat than to the land use. Only the integration of chemical and biological parameters allows a correct understanding of the state of health of water body and benthic communities

The microsporidian fungus Nosema ceranae represents one of the primary bee infection threats worldwide and the antibiotic fumagillin is the only registered product for nosemosis disease control, while few alternatives are, at present, available. Natural bioactive compounds deriving from the glucosinolate–myrosinase system (GSL–MYR) in Brassicaceae plants, mainly isothiocyanates (ITCs), are known for their antimicrobial activity against numerous pathogens and for their health-protective effects in humans. This work explored the use of Brassica nigra and Eruca sativa defatted seed meal (DSM) GSL-containing diets against natural Nosema infection in Apis mellifera colonies. DSM patties from each plant species were obtained by adding DSMs to sugar candy at the concentration of 4% (w/w). The feeding was administered in May to mildly N. ceranae-infected honey bee colonies for four weeks at the dose of 250 g/week. In the treated groups, no significant effects on colony development and bee mortality were observed compared to the negative controls. The N. ceranae abundance showed a slight but significant decrease. Furthermore, the GSL metabolism in bees was investigated, and MYR hydrolytic activity was qualitatively searched in isolated bee midgut and hindgut. Interestingly, MYR activity was detected both in the bees fed DSMs and in the control group where the bees did not receive DSMs. In parallel, ITCs were found in gut tissues from the bees treated with DSMs, corroborating the presence of a MYR-like enzyme capable of hydrolyzing ingested GSLs. On the other hand, GSLs and other GSL hydrolysis products other than ITCs, such as nitriles, were found in honey produced by the treated bees, potentially increasing the health value of the final product for human consumption. The results are indicative of a specific effect on the N. ceranae infection in managed honey bee colonies depending on the GSL activation within the target organ.

Although describing the primary sector of a given country is a common institutional practice, such studies usually offer aggregated information on holding rather than supplying the information required for farm-level simulations. The present study aimed to identify the main typologies of Italian farms from the 2007 database of RICA (the Italian section of the European Union's Farm Accountancy Data Network). Using a hierarchical strategy driven by climates (5) and slopes (3), farms have been grouped by super-structure, described in terms of the presence and extent of primary activities (livestock, farmland use). The resulting picture of Italian farms is based on 35 farm types, the most common of which grow low-input orchards (e.g., olive trees). On the plains in warm climatic areas, low-input orchards and arable crops dominate; in hilly and mountainous areas, mixed farms with forage crops, meadows, ovines, and cattle prevail. In more temperate areas, the most common farm type is based on intensive and field crops (e.g., durum and bread wheat). In temperate hilly and mountain areas, mixed farms combining meadows, woods, and cattle become predominant.