Cuff, J. P. | bioRxiv Science

bioRxiv2024

Identifying the Fusarium species involved in foot rot disease of faba beans in the UK using a combined molecular and microbiological approach

Foot rot is a devastating disease of faba bean crops globally, including in the United Kingdom, the worlds third largest producer. To identify the causal agents, we have sampled foot rot-affected plants and soils from faba bean crops across England. We isolated organisms associated with foot rot disease in culture and assessed pathogenicity in vivo to evaluate the infectivity of the isolates on faba bean. We identified the pathogenic isolates using DNA barcoding of the Internal Transcribed Spacer (ITS) and Translation Elongation Factor one (TEF1 ) molecular markers. A total of 113 clonal isolates were obtained from infected plants and soil samples across England. Of these, 60 were pathogenic, inducing mild to severe symptoms on faba bean. Sequencing of the ITS and TEF1 loci and comparison against sequence databases (Genbank and Fusarium_ID) enabled the identification of pathogenic isolates, in decreasing order of frequency, as Fusarium oxysporum (26.6 %), F. vanettenii (25%), F. redolens (15 %), F. solani (11.6%), F. culmorum (8.3 %), F. avenaceum (6.7 %), F. equiseti (1.7 %), F. clavum (1.7 %), Clonostachys rosea (1.7%) and Alternaria alternata (1.7%). F. oxysporum, F. redolens and F. avenaceum induced the most severe symptoms, whilst F. solani induced the least severe symptoms. Determining the most prevalent causal agents of foot rot in UK faba beans will facilitate targeted disease monitoring and intervention for enhanced productivity.

microbiology↗

bioRxiv2023

Sources of prey availability data alter interpretation of outputs from prey choice null networks

O_LINull models provide an invaluable baseline against which to test fundamental ecological hypotheses and highlight patterns in foraging choices that cannot be explained by neutral processes or sampling artefacts. In this way, null models can advance our understanding beyond simplistic dietary descriptions to identify drivers of interactions. This method, however, requires estimates of resource availability, which are generally imperfect representations of highly dynamic systems. Optimising method selection is crucial for study design, but the precise effects of different resource availability data on the efficacy of null models are poorly understood. C_LIO_LIUsing spider-prey networks as a model, we used prey abundance (suction sample) and activity density (sticky trap) data, and combinations of the two, to simulate null networks. We compared null diet composition, network properties (e.g., connectance and nestedness) and deviations of simulations from metabarcoding-based spider dietary data (to ascertain how different prey availability data alter ecological interpretation. C_LIO_LIDifferent sampling methods produced different null networks and inferred distinct prey selectivity. Null networks based on prey abundance and combined frequency-of-occurrence data more closely resembled the observed diet composition, and those based on prey abundance, activity density and proportionally combined data generated network properties most like dietary metabarcoding networks. C_LIO_LIWe show that survey method choice impacts all aspects of null network analyses, the precise effects varying between methods but ultimately altering ecological interpretation by increasing disparity in network properties or trophic niches between null and directly constructed networks. Merging datasets can generate more complete prey availability data but is not a panacea because it introduces different biases. The choice of method should reflect the research hypotheses and study system being investigated. Ultimately, survey methods should emulate the foraging mode of the focal predator as closely as possible, informed by the known ecology, natural history and behaviour of the predator. C_LI

ecology↗