Biology subjects

Donnelly, R.

Publications and source records attributed to Donnelly, R..

3 recordsLinked to original sources

bioRxiv2025

Optimizing crop varietal mixtures for viral disease management: A case study on cassava virus epidemics

Cassava viral diseases, including Cassava Mosaic Disease (CMD) and Cassava Brown Streak Disease (CBSD), pose significant threats to global food security, particularly in sub-Saharan Africa. This study explores the potential of varietal mixtures as a sustainable disease management strategy by introducing CropMix, a novel web-based application. The application encodes a flexible insect-borne plant pathogen transmission model to predict and optimize yields under scenarios of varietal mixtures. For instance, we use the application to evaluate the ability of virus-resistant cassava varieties to protect more susceptible varieties against CMD and CBSD, and we also consider mixtures involving tolerant varieties and non-host crops. For CMD, the high transmission rates of cassava mosaic begomoviruses limits the efficacy of mixtures, with susceptible monocultures emerging as better than susceptible-resistant mixtures whatever the whitefly pressure. In contrast, for CBSD, varietal mixtures demonstrate substantial benefits, with resistant varieties shielding susceptible ones and mitigating severe yield losses under moderate or high insect pressure. Management strategies involving non-host crops and complementary control measures, such as roguing, can further enhance outcomes. The models simplicity and adaptability make it suitable for tailoring recommendations to diverse insect-borne crop viral diseases and agroecological contexts. The study emphasizes the need for integrating real-world data and participatory frameworks to refine and implement disease management strategies. We discuss the critical balance between agronomic potential and farmer acceptability, underscoring the importance of collaborative efforts to ensure sustainable cassava production.

ecology↗

bioRxiv2020

DNA metabarcoding shows strong potential for investigating diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison)

In the UK, the native European otter (Lutra lutra) and invasive American mink (Neovison vison) have experienced concurrent declines and expansions. Currently, the otter is recovering from persecution and waterway pollution, whereas the mink is in decline due to population control and probable interspecific interaction with the otter. We explored the potential of DNA metabarcoding for investigating diet and niche partitioning between these mustelids. Otter spraints (n = 171) and mink scats (n = 19) collected from three sites (Malham Tarn, River Hull, and River Glaven) in northern and eastern England were screened for vertebrates using high-throughput sequencing. Otter diet mainly comprised aquatic fishes (81.0%) and amphibians (12.7%), whereas mink diet predominantly consisted of terrestrial birds (55.9%) and mammals (39.6%). The mink used a lower proportion (20%) of available prey (n = 40 taxa) than the otter, and low niche overlap (0.267) was observed between these mustelids. Prey taxon richness of mink scats was lower than otter spraints, and beta diversity of prey communities was driven by taxon turnover (i.e. the otter and mink consumed different prey taxa). Considering otter diet only, prey taxon richness was higher in spraints from the River Hull catchment, and beta diversity of prey communities was driven by taxon turnover (i.e. the otter consumed different prey taxa at each site). Studies using morphological faecal analysis may misidentify the predator as well as prey items. Faecal DNA metabarcoding can resolve these issues and provide more accurate and detailed dietary information. When upscaled across multiple habitat types, DNA metabarcoding should greatly improve future understanding of resource use and niche overlap between the otter and mink.

ecology↗

bioRxiv2018

Temporal and spatial variation in distribution of fish environmental DNA in England’s largest lake

Environmental DNA offers great potential as a biodiversity monitoring tool. Previous work has demonstrated that eDNA metabarcoding provides reliable information for lake fish monitoring, but important questions remain about temporal and spatial repeatability, which is critical for understanding the ecology of eDNA and developing effective sampling strategies. Here, we carried out comprehensive spatial sampling of Englands largest lake, Windermere, during summer and winter to 1) examine repeatability of the method, 2) compare eDNA results with contemporary gill-net survey data, 3) test the hypothesis of greater spatial structure of eDNA in summer compared to winter due to differences in water mixing between seasons, and 4) compare the effectiveness of shore and offshore sampling for species detection. We find broad consistency between results from three sampling events in terms of species detection and abundance, with eDNA detecting more species than established methods and being significantly correlated to rank abundance determined by long-term data. As predicted, spatial structure was much greater in the summer, reflecting less mixing of eDNA than in the winter. For example Arctic charr, a deep-water species, was only detected in deep, mid-lake samples in the summer, while littoral or benthic species such as minnow and stickleback were more frequently detected in shore samples. By contrast in winter, the eDNA of these species was more uniformly distributed. This has important implications for design of sampling campaigns, for example, deep-water species could be missed and littoral/benthic species overrepresented by focusing exclusively on shoreline samples collected in the summer.

ecology↗