Development of molecular diagnostic test to quantify Rhizobium leguminosarum bv. viciae (rhizobia group E/F) in soil - Stephen Barnett; Ross A. Ballard; Danièle Giblot-Ducray; Kelly Hill; Alan McKay; Herdina; Elizabeth A. Farquharson (Plant and Soil, 2026)
Aims Rhizobia are essential for nitrogen fixation in legumes. The current method for enumerating rhizobia in soil by the Most Probable Number (MPN) method is costly and time consuming. This paper describes the development of a qPCR test to quantify Rhizobium leguminosarum bv. viciae (Rlv) in soil. Methods TaqMan probe and primers were developed . Specificity of qPCR was confirmed against Rlv and non-target rhizobia and compared to vetch nodulation. Relationship between qPCR results and Rlv numbers was assessed by comparing qPCR of Rlv strains added into sand at known cell density to plate counts on agar. The reliability of the test was assessed on 41 field soils and compared to quantification by MPN on vetch and symbiotic performance of rhizobia in soil extracts was examined on field pea and faba bean. Results The developed test was specific for Rlv, with 42 strains testing positive for both qPCR and nodulation of vetch and 42 other rhizobia negative for both qPCR and nodulation. A dilution series of two Rlv strains inoculated into sand produced a tight correlation (R 2 = 0.92) between qPCR data and plate counts. Assessment of field soils indicated a significant relationship ( P < 0.001, R 2 = 0.85) between qPCR and MPN and between qPCR and nitrogen fixation capacity with field pea (R 2 = 0.82) and faba bean (R 2 = 0.51). Conclusion The qPCR test developed is specific for Rlv strains and shows high correlation with plate counts, MPN population estimates and symbiotic performance. This test is now delivered as a commercial service to growers and researchers as “PREDICTA® rNod”.

Passive acoustic monitoring (PAM) to assess benthic communities associated with offshore wind farms: insights and future directions - Laurence H. De Clippele; Ross J. Barnett; Marta Bolgan; Flora Kent; Kirsty Wright; Kate Brookes; Alexander Gilliland (Environmental Monitoring and Assessment, 2026)
Understanding biodiversity in offshore benthic ecosystems is crucial as anthropogenic pressures like offshore wind development increasingly alter marine environments. Passive acoustic monitoring (PAM), widely used for marine mammal research, offers a promising yet underexplored tool for assessing broader faunal communities. Here, we investigate whether PAM data, collected initially for marine mammal monitoring, can reveal spatial variation in benthic biodiversity along Scotland’s east coast. We analysed passive acoustic data from eight offshore sedimentary habitats, identifying 16 distinct biological sound types likely produced by fish and invertebrates. Acoustic indices were also calculated and compared with environmental variables and infaunal benthic richness derived from open-source biodiversity databases. Our results show that key habitat variables, including substrate type, current velocity, and spawning suitability, drive variation in acoustic communities. The findings of this pilot study demonstrate that PAM can be used to detect biologically meaningful patterns in benthic assemblages, and with future work focusing on investigating longer-term datasets, it could offer a cost-effective tool for biodiversity monitoring across space and time. While several acoustic indices correlated with phonic richness and benthic diversity, we currently do not recommend their use in biodiversity monitoring. This study highlights the ecological value of existing acoustic datasets and advances our understanding of soundscape ecology and species-habitat relationships in changing marine environments.