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Detection rates of aphid DNA in the guts of larval hoverflies and potential links to the provision of floral resources

Published online by Cambridge University Press:  24 February 2022

Dylan Hodgkiss ,
Mark J. F. Brown ,
Michelle T. Fountain Open the ORCID record for Michelle T. Fountain [Opens in a new window]  and
Elizabeth L. Clare
Dylan Hodgkiss
Affiliation:
Centre for Ecology, Evolution & Behaviour, Department of Biological Sciences, School of Life Sciences and the Environment, Royal Holloway University of London, London TW20 0EX, UK NIAB EMR, New Road, East Malling, Kent ME19 6RN, UK
Mark J. F. Brown
Affiliation:
Centre for Ecology, Evolution & Behaviour, Department of Biological Sciences, School of Life Sciences and the Environment, Royal Holloway University of London, London TW20 0EX, UK
Michelle T. Fountain*
Affiliation:
NIAB EMR, New Road, East Malling, Kent ME19 6RN, UK
Elizabeth L. Clare
Affiliation:
School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, UK Department of Biology, York University, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada
*
Author for correspondence: Michelle T. Fountain, Email: michelle.fountain@niab.com
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Abstract

Aphidophagous hoverflies (Diptera, Syrphidae, Syrphinae) are common flower visitors and aphid predators in a range of flowering plants, including fruit crops. Here, we investigate whether aphid prey DNA can be detected in the gut contents of hoverfly larvae from a commercial strawberry field as a proof of concept that a molecular approach can be used to measure agricultural biocontrol. We used high-throughput sequencing (HTS) to target insect DNA and compared the resulting data to reference databases containing aphid and hoverfly DNA sequences. We explored what impact incorporating wildflowers within polythene-clad tunnels may have on aphid DNA detection rates in hoverfly larvae. In a randomized block experiment, coriander (Coriandrum sativum), field forget-me-not (Myosotis arvensis) and corn mint (Mentha arvensis) plants were inserted in rows of strawberries. Their effect on aphid DNA detection rates was assessed. Aphid DNA was found in 55 of 149 specimens (37%) validating the method in principle for measuring agricultural services provided by hoverflies. Interestingly, detection rates were higher near plots with forget-me-not than plots with coriander, though detection rates in control plots did not differ significantly from either wildflower species. These findings confirm that hoverflies predate aphids in UK strawberry fields, and that HTS is a viable method of identifying aphid DNA in predatory hoverflies. We comment on the need for further method development to narrow down identifications of both predator and prey. We furthermore provide some evidence that there is an effect of intercropping strawberry crops with wildflowers which may affect aphid consumption in hoverfly larvae.

Keywords

Aphidoideabiocontrolfloral resourcesFragariagut content analysishoverfly
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 112 , Issue 4 , August 2022 , pp. 451 - 457
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Afgan, E, Baker, D, Batut, B, Van Den Beek, M, Bouvier, D, Čech, M, Chilton, J, Clements, D, Coraor, N, Grüning, BA, Guerler, A, Hillman-Jackson, J, Hiltemann, S, Jalili, V, Rasche, H, Soranzo, N, Goecks, J, Taylor, J, Nekrutenko, A and Blankenberg, D (2018) The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Research 46, W537–W544.CrossRefGoogle ScholarPubMed
Albano, S, Salvado, E, Duarte, S, Mexia, A and Borges, PAV (2009) Pollination effectiveness of different strawberry floral visitors in Ribatejo, Portugal: selection of potential pollinators. Part 2. Advances in Horticultural Sciences 23, 246–253.Google Scholar
Alford, DV (2011) Plant Pests: A Natural History of Pests of Farms and Gardens. London: Harper Collins.Google Scholar
Assaf, G (2010) FASTQ/A short-reads pre-processing tools. http://hannonlab.cshl.edu/fastx_toolkit/.Google Scholar
Ball, S and Morris, R (2015) Britain's Hoverflies: A Field Guide, 2nd Edn. Princeton: Princeton UP.CrossRefGoogle Scholar
Bates, D, Maechler, M, Bolker, B and Walker, S (2015) Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67, 1–48.CrossRefGoogle Scholar
Bowie, MH, Gurr, GM, Hossain, Z, Baggen, LR and Frampton, CM (1999) Effects of distance from field edge on aphidophagous insects in a wheat crop and observations on trap design and placement. International Journal of Pest Management 45, 69–73.CrossRefGoogle Scholar
Chacoff, NP and Aizen, MA (2006) Edge effects on flower-visiting insects in grapefruit plantations bordering premontane subtropical forest. Journal of Applied Ecology 43, 18–27.CrossRefGoogle Scholar
Clare, EL (2014) Molecular detection of trophic interactions: emerging trends, distinct advantages, significant considerations and conservation applications. Evolutionary Applications 7, 1144–1157.CrossRefGoogle ScholarPubMed
Colares, F, Michaud, JP, Bain, CL and Torres, JB (2015) Recruitment of aphidophagous arthropods to sorghum plants infested with Melanaphis sacchari and Schizaphis graminum (Hemiptera: Aphididae). Biological Control 90, 16–24.CrossRefGoogle Scholar
Colley, MR and Luna, JM (2000) Relative attractiveness of potential beneficial insectary plants to aphidophagous hoverflies (Diptera: Syrphidae). Environmental Entomology 29, 1054–1059.CrossRefGoogle Scholar
Crowder, DW and Harwood, JD (2014) Promoting biological control in a rapidly changing world. Biological Control 75, 8–17.CrossRefGoogle Scholar
Dedryver, C-A, Le Ralec, A and Fabre, F (2010) The conflicting relationships between aphids and men: a review of aphid damage and control strategies. Comptes Rendus Biologies 333, 539–553.CrossRefGoogle Scholar
Dent, D (1995) Integrated Pest Management. London: Chapman and Hall.Google Scholar
Dib, H, Jamont, M, Sauphanor, B and Capowiez, Y (2016) Individual and combined effects of the generalist Forficula auricularia and the specialist Episyrphus balteatus on Dysaphis plantaginea – are two predators better than one? Entomologia Experimentalis et Applicata 161, 1–10.CrossRefGoogle Scholar
Gariepy, TD, Haye, T and Zhang, J (2014) A molecular diagnostic tool for the preliminary assessment of host-parasitoid associations in biological control programmes for a new invasive pest. Molecular Ecology 23, 3912–3924.CrossRefGoogle ScholarPubMed
Gilbert, F (2005) Syrphid aphidophagous predators in a food-web context. European Journal of Entomology 102, 325–333.CrossRefGoogle Scholar
Gojković, N, Francuski, L, Ludoški, J and Milankov, V (2020) DNA barcode assessment and population structure of aphidophagous hoverfly Sphaerophoria scripta: implications for conservation biological control. Ecology and Evolution 10, 9428–9443.CrossRefGoogle ScholarPubMed
Gomez-Polo, P, Alomar, O, Castañé, C, Lundgren, JG, Piñol, J and Agustí, N (2015) Molecular assessment of predation by hoverflies (Diptera: Syrphidae) in Mediterranean lettuce crops. Pest Management Science 71, 1219–1227.CrossRefGoogle ScholarPubMed
Gomez-Polo, P, Alomar, O, Castañé, C and Agustí, N (2016) Molecular tracking of arthropod predator-prey interactions in Mediterranean lettuce crops. Food Webs 9, 18–24.CrossRefGoogle Scholar
Haenke, S, Scheid, B, Schaefer, M, Tscharntke, T and Thies, C (2009) Increasing syrphid fly diversity and density in sown flower strips within simple vs. complex landscapes. Journal of Applied Ecology 46, 1106–1114.CrossRefGoogle Scholar
Hassan, MA, Mahmood, K, Nazir, K, Fatima, N and Aslam, MA (2017) Faunistic work on the hover flies (Diptera: Syrphidae) of district Narowal, Pakistan. Journal of Entomological and Zoological Studies 5, 626–630.Google Scholar
Hebert, PDN, Cywinska, A, Ball, SL and de Waard, JR (2003) Biological identifications through DNA barcodes. Proceedings of the Royal Society B 270, 313–321.CrossRefGoogle ScholarPubMed
Hodgkiss, D, Brown, MJF and Fountain, MT (2018) Syrphine hoverflies are effective pollinators of commercial strawberry. Journal of Pollination Ecology 22, 55–66.CrossRefGoogle Scholar
Hogg, BN, Nelson, EH, Mills, NJ and Daane, KM (2011) Floral resources enhance aphid suppression by a hoverfly. Entomologia Experimentalis et Applicata 141, 138–144.CrossRefGoogle Scholar
Hopper, JV, Nelson, EH, Daane, KM and Mills, NJ (2011) Growth, development and consumption by four syrphid species associated with the lettuce aphid, Nasonovia ribisnigri, in California. Biological Control 58, 271–276.CrossRefGoogle Scholar
Kovanci, OB, Kovanci, B and Gencer, NS (2007) Species composition, seasonal dynamics and numerical responses of arthropod predators in organic strawberry fields. Biocontrol Science and Technology 17, 457–472.CrossRefGoogle Scholar
McClenaghan, B, Gibson, JF, Shokralla, S and Hajibabaei, M (2015) Discrimination of grasshopper (Orthoptera: Acrididae) diet niche overlap using next-generation sequencing of gut contents. Ecology and Evolution 5, 3046–3055.CrossRefGoogle ScholarPubMed
Mollot, G, Duyck, P-F, Lefeuvre, P, Lescourret, F, Martin, J-F, Piry, S, Canard, E and Tixier, P (2014) Cover cropping alters the diet of arthropods in a banana plantation: a metabarcoding approach. PLoS ONE 9, e93740.CrossRefGoogle Scholar
Morris, MC and Li, FY (2000) Coriander (Coriandrum sativum) “companion plants” can attract hoverflies, and may reduce pest infestation in cabbages. New Zealand Journal of Crop Horticultural Science 28, 213–217.CrossRefGoogle Scholar
New, TR (2005) Invertebrate Conservation and Agricultural Ecosystems. Cambridge: Cambridge UP.CrossRefGoogle Scholar
Pekas, A, De Craecker, I, Boonen, S, Wäckers, FL and Moerkens, R (2020) One stone; two birds: concurrent pest control and pollination services provided by aphidophagous hoverflies. Biological Control 149, 104328.CrossRefGoogle Scholar
Piñol, J, San Andrés, V, Clare, EL, Mir, G and Symondson, WOC (2014) A pragmatic approach to the analysis of diets of generalist predators: the use of next-generation sequencing with no blocking probes. Molecular Ecology Resources 14, 18–26.CrossRefGoogle Scholar
Pompanon, F, Deagle, BE, Symondson, WOC, Brown, DS, Jarman, SN and Taberlet, P (2012) Who is eating what: diet assessment using next generation sequencing. Molecular Ecology 21, 1931–1950.CrossRefGoogle ScholarPubMed
Prasad, RP, Kabaluk, JT, Meberg, HP, Bevon, DA and Henderson, DE (2009) Seasonal and spatial occurrence of aphid natural enemies in organic Brassica fields: diversity, phenology, and reproduction. Journal of Sustainable Agriculture 33, 336–348.CrossRefGoogle Scholar
R Core Team, (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Rodríguez-Gasol, N, Alins, G, Veronesi, ER and Wratten, S (2020) The ecology of predatory hoverflies as ecosystem-service providers in agricultural systems. Biological Control 151, 104405.CrossRefGoogle Scholar
Rotheray, GE (1993) Colour Guide to Hoverfly Larvae (Diptera, Syrphidae) in Britain and Europe. Sheffield: Derek Whiteley.Google Scholar
Rotheray, GE and Gilbert, F (2011) The Natural History of Hoverflies. Cardigan, UK: Forrest Text.Google Scholar
Schloss, PD, Westcott, SL, Ryabin, T, Hall, JR, Hartmann, M, Hollister, EB, Lesniewski, RA, Oakley, BB, Parks, DH, Robinson, CJ, Sahl, JW, Stres, B, Thallinger, DJ, Van Horn, DJ and Weber, CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied Environmental Microbiology 75, 7537–7541.CrossRefGoogle ScholarPubMed
Smith, HA, Chaney, WE and Bensen, TA (2008) Role of syprhid larvae and other predators in suppressing aphid infestations in organic lettuce on California's Central Coast. Journal of Economic Entomology 101, 1526–1532.CrossRefGoogle Scholar
Solomon, MG, Jay, CN, Innocenzi, PJ, Fitzgerald, JD, Crook, D, Crook, AM, Easterbrook, MA and Cross, JV (2001) Review: natural enemies and biocontrol of pests of strawberry in Northern and Central Europe. Biocontrol Sciences and Technology 11, 165–216.CrossRefGoogle Scholar
Symondson, WOC (2002) Molecular identification of prey in predator diets. Molecular Ecology 11, 627–641.CrossRefGoogle ScholarPubMed
Tenhumberg, B and Poehling, H-M (1995) Syrphids as natural enemies of cereal aphids in Germany: aspects of their biology and efficacy in different years and regions. Agriculture, Ecosystems and Environment 52, 39–43.CrossRefGoogle Scholar
Tinkeu, LN and Hance, T (1998) Functional morphology of the mandibles of the larvae of Episyrphus balteatus (De Geer, 1776) (Diptera: Syrphidae). International Journal of Insect Morphology and Embryology 27, 135–142.CrossRefGoogle Scholar
van Rijn, PCJ, Kooijman, J and Wackers, FL (2006) The impact of floral resources on syrphid performance and cabbage aphid biological control. IOBC/WPRS Bulletin 29, 149–152.Google Scholar
Wang, W, Liu, Y, Chen, J, Ji, X, Zhou, H and Wang, G (2009) Impact of intercropping aphid-resistant wheat cultivars with oilseed rape on wheat aphid (Sitobion avenae) and its natural enemies. Acta Ecologica Sinica 29, 186–191.CrossRefGoogle Scholar
Weber, DC and Lundgren, JG (2009) Assessing the trophic ecology of the Coccinellidae: their roles as predators and as prey. Biological Control 51, 199–214.CrossRefGoogle Scholar
Wulff, JA, Kjeldgaard, MK, Eubanks, MD and Sword, GA (2021) From the bellies of babes: a larval-based approach to ant molecular gut content analysis. Insectes Sociaux 68, 245–253.CrossRefGoogle Scholar
Zeale, MRK, Butlin, RK, Barker, GLA, Lees, DC and Jones, G (2011) Taxon-specific PCR for DNA barcoding arthropod prey in bat faeces. Molecular Ecology Resources 11, 236–244.CrossRefGoogle ScholarPubMed
Zhong, W, Tan, Z, Wang, B and Yan, H (2019) Next-generation sequencing analysis of Pardosa pseudoannulata's diet composition in different habitats. Saudi Journal of Biological Sciences 26, 165–172.CrossRefGoogle ScholarPubMed