Soil erosion risk for farming futures: Novel model application and validation to an agricultural landscape in southern England

Assessment of the prevalence, serotype, and antibiotic resistance pattern of Salmonella enterica in integrated farming systems in the Maryland-DC area

Implementation of organic/pasture farming practices has been increasing in the USA regardless of official certification. These practices have created an increasingly growing demand for marketing safe products which are produced through these systems. Products from these farming systems have been reported to be at greater risk of transmitting foodborne pathogens because of current trends in their practices. Salmonella enterica (SE) is a ubiquitous foodborne pathogen that remains a public health issue given its prevalence in various food products, but also in the environment and as part of the microbial flora of many domestic animals. Monitoring antibiotic resistance and identifying potential sources contamination are increasingly important given the growing trend of organic/pasture markets. This study aimed to quantify prevalence of SE at the pre- and post-harvest levels of various integrated farms and sites in Maryland-Washington D.C. area, as well as identify the most prevalent serovars and antibiotic resistance patterns. Samples from various elements within the farm environment were collected and screened for SE through culture and molecular techniques, which served to identify and serotype SE, using species and serovar-specific primers, while antibiotic resistance was evaluated using an antibiogram assay. Results showed a prevalence of 7.80% of SE pre-harvest and 1.91% post-harvest. These results also showed the main sources of contamination to be soil (2.17%), grass (1.28%), feces (1.42%) and unprocessed produce (1.48%). The most commonly identified serovar was Typhimurium (11.32%) at the pre-harvest level, while the only identified serovar from post-harvest samples was Montevideo (4.35%). With respect to antibiotic resistance, out of the 13 clinically relevant antibiotics tested, gentamycin and kanamycin were the most effective, demonstrating 78.93 and 76.40% of isolates, respectively, to be susceptible. However, ampicillin, amoxicillin and cephradine had the lowest number of susceptible isolates with them being 10.95, 12.36, and 9.83%, respectively. These results help inform farms striving to implement organic practices on how to produce safer products by recognizing areas that pose greater risks as potential sources of contamination, in addition to identifying serotypes of interest, while also showcasing the current state of antibiotic efficacy and how this can influence antibiotic resistance trends in the future.

Multicriteria spatial model to prioritize degraded areas for landscape restoration through agroforestry

Reconciling the restoration of ecosystem services within agricultural landscapes is an effort that has been advancing within degraded areas restoration through agroforestry systems. However, to contribute to the effectiveness of these initiatives, it is essential to integrate landscape vulnerability and local demands to better highlight in which areas the implementation of agroforestry systems should be prioritized. Thus, we developed a spatial hierarchization methodology as a decision support tool as an active strategy for agroecosystem restoration. The proposed method constitutes a spatial indicator of priority areas to guide agroforestry interventions, including resource allocation and public policies for payment for environmental services. The methodology consists of Multicriteria Decision Analysis implemented in GIS software by combining input datasets based on biophysical conditions, environmental and socioeconomic aspects, that integrated promotes an assessment of the environment fragility, the pressures and responses to land use dynamic; a strategy for landscape restoration and conservation of the natural habitats, and multiple specific scenarios for decision making regarding the agricultural and the local actors demands. The output of the model provides the spatial distribution of areas suitable for the implementation of agroforestry systems, sorted into four priority levels (Low, Medium, High, and Extreme priority). The method is a promising tool proposal for territorial management and governance and subsidizes future research on the flows of ecosystem services.•Assessment of the environment fragility and the pressures and responses to land use dynamic.•Strategy for landscape restoration and conservation of remaining natural habitats.•Multiple specific scenarios for decision making regarding the agricultural and the local actors demands.