Abstract
Rhyzopertha dominica and Tribolium castaneum are key pests of stored grains globally. These two species often occur together in infestations, and are seldom found outside the agricultural environment. Understanding the movement of these beetle pests is crucial for the development of management strategies, in particular to prevent the spread of phosphine resistance, which is a serious issue in many countries. We sampled both of these beetle species from farm silos across Australia, and used microsatellite markers to assess whether these two pests sharing the same resource show similar patterns of genetic diversity and genetic structure. Both species had high levels of genetic diversity, and showed some evidence of genetic structure across Australia, but the patterns of genetic structure differed across the two species. Specifically, our results suggest that there is significant gene flow in T. castaneum across Australia, with the clear isolation-by-distance pattern indicating that active flight may play an important role in determining genetic structure in this species. The significant movement of T. castaneum beetles across Australia will likely result in the continued spread of phosphine resistance alleles across Australia, leading to increased incidence of strongly resistance populations. Less gene flow was evident in R. dominica, suggesting movement of these beetles among localities is more restricted. Our results demonstrate that pests mostly sharing the same resources can significantly differ in their genetic structure and genetic diversity, suggesting species-specific management practices are essential.
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References
Ahmad F, Walter GH, Raghu S (2012) Comparative performance of Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) across populations, resource types and structural forms of those resources. J Stored Prod Res 48:73–80. https://doi.org/10.1016/j.jspr.2011.09.005
Campbell J, Toews MD, Arthur FH, Arbogast RT (2010) Long-term monitoring of Tribolium castaneum in two flour mills: seasonal patterns and impact of fumigation. J Econ Entomol 103:991–1001. https://doi.org/10.1603/EC09347
Chapuis MP, Estoup A (2007) Microsatellite null alleles and estimation of population differentiation. Mol Biol Evol 24:621–631. https://doi.org/10.1093/molbev/msl191
Collins PJ, Daglish GJ, Pavic H, Kopittke RA (2005) Response of mixed-age cultures of phosphine-resistant and susceptible strains of lesser grain borer, Rhyzopertha dominica, to phosphine at a range of concentrations and exposure periods. J Stored Prod Res 41:373–385. https://doi.org/10.1016/j.jspr.2004.05.002
Collins PJ, Falk MG, Nayak MK, Emery RN, Holloway JC (2017) Monitoring resistance to phosphine in the lesser grain borer, Rhyzopertha dominica, in Australia: a national analysis of trends, storage types and geography in relation to resistance detections. J Stored Prod Res 70:25–36. https://doi.org/10.1016/j.jspr.2016.10.006
Cordeiro EM, Campbell JF, Phillips T, Akhunov E. (2019) Isolation by distance, source-sink population dynamics and dispersal facilitation by trade routes: impact on population genetic structure of a stored grain pest. G3 Genes Genomes Genet https://doi.org/10.1534/g3.118.200892
Daglish GJ, Nayak MK, Pavic H, Smith LW (2015) Prevalence and potential fitness cost of weak phosphine resistance in Tribolium castaneum (Herbst) in eastern Australia. J Stored Prod Res 61:54–58. https://doi.org/10.1016/j.jspr.2014.11.005
Daglish GJ, Ridley AW, Reid R, Walter GH (2017) Testing the consistency of spatio-temporal patterns of flight activity in the stored grain beetles Tribolium castaneum (Herbst) and Rhyzopertha dominica (F.). J Stored Prod Res 72:68–74. https://doi.org/10.1016/j.jspr.2017.03.005
Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B (Statistical Methodology) 39:1–38
Drury DW, Siniard AL, Wade MJ (2009) Genetic differentiation among wild populations of Tribolium castaneum estimated using microsatellite markers. J Hered 100:732–741. https://doi.org/10.1093/jhered/esp077
Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x
Guedes RNC, Roditakis E, Campos MR, Haddi K, Bielza P, Siqueira HAA, Tsagkarakou A, Vontas J, Nauen R (2019) Insecticide resistance in the tomato pinworm Tuta absoluta: patterns, spread, mechanisms, management and outlook. J Pest Sci 92:1–14. https://doi.org/10.1007/s10340-019-01086-9
Hernandez Nopsa JF, Daglish GJ, Hagstrum DW, Leslie JF, Phillips TW, Scoglio C, Thomas-Sharma S, Walter GH, Garrett KA (2015) Ecological networks in stored grain: Key postharvest nodes for emerging pests, pathogens, and mycotoxins. Bioscience 65:985–1002. https://doi.org/10.1093/biosci/biv122
Holloway JC, Daglish GJ, Mayer DG (2020) Spatial distribution and flight patterns of two grain storage insect pests, Rhyzopertha dominica (Bostrichidae) and Tribolium castaneum (Tenebrionidae): implications for pest management. Insects 11:715. https://doi.org/10.3390/insects11100715
Horowitz AR, Ghanim M, Roditakis E, Nauen R, Ishaaya I (2020) Insecticide resistance and its management in Bemisia tabaci species. J Pest Sci 93:893–910. https://doi.org/10.1007/s10340-020-01210-0
Jombart T (2008) adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24:1403–1405. https://doi.org/10.1093/bioinformatics/btn129
Kearse M, Moir R, Wilson A, Stones-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S, Duran C (2012) Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28:1647–1649. https://doi.org/10.1093/bioinformatics/bts199
Kopelman NM, Mayzel J, Jakobsson M, Rosenberg NA, Mayrose I (2015) Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour 15:1179–1191. https://doi.org/10.1111/1755-0998.12387
Mahroof RM, Edde PA, Robertson B, Puckette JA, Phillips TW (2010) Dispersal of Rhyzopertha dominica (Coleoptera: Bostrichidae) in different habitats. Environ Entomol 39:930–938. https://doi.org/10.1603/EN09243
Malekpour R, Rafter MA, Daglish GJ, Walter GH (2016) Influence of phosphine resistance genes on flight propensity and resource location in Tribolium castaneum (Herbst)(Coleoptera: Tenebrionidae): the landscape for selection. Biol J Lin Soc 119:348–358. https://doi.org/10.1111/bij.12817
Malekpour R, Rafter MA, Daglish GJ, Walter GH (2017) The movement abilities and resource location behaviour of Tribolium castaneum: phosphine resistance and its genetic influences. J Pest Sci 1–11. https://doi.org/10.1007/s10340-017-0935-z
Mazzi D, Dorn S (2012) Movement of insect pests in agricultural landscapes. Ann Appl Biol 160:97–113. https://doi.org/10.1111/j.1744-7348.2012.00533.x
McCulloch GA, Mohankumar S, Subramaniam S, Sonai Rajan T, Rahul C, Surendran R, Gaurav R, Chandrasekaran S, Daglish GJ, Walter GH (2019) Contrasting patterns of phylogeographic structuring in two key beetle pests of stored grain in India and Australia. J Pest Sci 92:1248–1259. https://doi.org/10.1007/s10340-019-01121-9
McCulloch GA, Gurdasani K, Kocak E, Daglish GJ, Walter GH (2020) Significant population genetic structuring in Rhyzopertha dominica across Turkey: biogeographic and practical implications. J Stored Prod Res 85: 101536. https://doi.org/10.1016/j.jspr.2019.101536
McFarlane D, Aitken E, Ridley A, Walter G (2021) The dietary relationships of Tribolium castaneum (Herbst) with microfungi. J Appl Entomol 145:158–169. https://doi.org/10.1111/jen.12830
Nayak MK, Falk MG, Emery RN, Collins PJ, Holloway JC (2017) An analysis of trends, frequencies and factors influencing the development of resistance to phosphine in the red flour beetle Tribolium castaneum (Herbst) in Australia. J Stored Prod Res 72:35–48. https://doi.org/10.1016/j.jspr.2017.03.004
Nayak MK, Daglish GJ, Phillips TW, Ebert PR (2020) Resistance to the fumigant phosphine and its management in insect pests of stored products: a global perspective. Annu Rev Entomol 65:333–350. https://doi.org/10.1146/annurev-ento-011019-025047
Nayak MK, Jagadeesan R, Singarayan VT, Nath NS, Pavic H, Dembowski B, Daglish GJ, Schlipalius DI, Ebert PR (2021) First report of strong phosphine resistance in stored grain insects in a far northern tropical region of Australia, combining conventional and genetic diagnostics. J Stored Prod Res 92: 101813. https://doi.org/10.1146/annurev-ento-011019-025047
Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28:2537–2539. https://doi.org/10.1093/bioinformatics/bts460
Perez-Mendoza J, Flinn PW, Campbell JF, Hagstrum DW, Throne JE (2004) Detection of stored-grain insect infestation in wheat transported in railroad hopper-cars. J Econ Entomol 97:1474–1483. https://doi.org/10.1093/jee/97.4.1474
Perez-Mendoza J, Throne JE, Maghirang EB, Dowell FE, Baker JE (2005) Insect fragments in flour: relationship to lesser grain borer (Coleoptera : Bostrichidae) infestation level in wheat and rapid detection using near-infrared spectroscopy. J Econ Entomol 98:2282–2291. https://doi.org/10.1093/jee/98.6.2282
Piry S, Luikart G, Cornuet J (1999) BOTTLENECK: a computer program for detecting recent reductions in the effective population size using allele frequency data. J Hered 90:502–503. https://doi.org/10.1093/jhered/90.4.502
Porretta D, Canestrelli D, Bellini R, Celli G, Urbanelli S (2007) Improving insect pest management through population genetic data: a case study of the mosquito Ochlerotatus caspius (Pallas). J Appl Ecol 44:682–691. https://doi.org/10.1111/j.1365-2664.2007.01301.x
Potter C (1935) The biology and distribution of Rhizopertha dominica (Fab.). Trans R Entomol Soc Lond 83:449–482. https://doi.org/10.1111/j.1365-2311.1935.tb02995.x
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959. https://doi.org/10.1093/genetics/155.2.945
R Core Team (2019) R: A language and environment for statistical computing. R Foundation for Statistical Computing
Rafter MA, McCulloch GA, Daglish GJ, Walter GH (2017) Progression of phosphine resistance in susceptible Tribolium castaneum (Herbst) populations under different immigration regimes and selection pressures. Evol Appl 10:907–918. https://doi.org/10.1111/eva.12493
Rafter MA, McCulloch GA, Daglish GJ, Gurdasani K, Walter GH (2018) Polyandry, genetic diversity and fecundity of emigrating beetles: understanding new foci of infestation and selection. J Pest Sci 91:287–298. https://doi.org/10.1007/s10340-017-0902-8
Rajan TS, Muralitharan V, Daglish GJ, Mohankumar S, Rafter MA, Chandrasekaran S, Mohan S, Vimal D, Srivastava C, Loganathan M, Walter GH (2018) Flight of three major insect pests of stored grain in the monsoonal tropics of India, by latitude, season and habitat. J Stored Prod Res 76:43–50. https://doi.org/10.1016/j.jspr.2017.12.005
Ridley AW, Hereward JP, Daglish GJ, Raghu S, Collins PJ, Walter GH (2011) The spatiotemporal dynamics of Tribolium castaneum (Herbst): adult flight and gene flow. Mol Ecol 20:1635–1646. https://doi.org/10.1111/j.1365-294X.2011.05049.x
Ridley AW, Hereward JP, Daglish GJ, Raghu S, McCulloch GA, Walter GH (2016) Flight of Rhyzopertha dominica (Coleoptera: Bostrichidae)—a spatio-temporal analysis with pheromone trapping and population genetics. J Econ Entomol 109:2561–2571. https://doi.org/10.1093/jee/tow226
Rousset F (2008) GENEPOP’ 007: a complete re-implementation of the GENEPOP software for Windows and Linux. Mol Ecol Resour 8:103–106. https://doi.org/10.1111/j.1471-8286.2007.01931.x
Schlipalius DI, Tuck AG, Pavic H, Daglish GJ, Nayak MK, Ebert PR (2019) A high-throughput system used to determine frequency and distribution of phosphine resistance across large geographical regions. Pest Manag Sci 75:1091–1098. https://doi.org/10.1002/ps.5221
Semeao AA, Campbell JF, Beeman RW, Lorenzen MD, Whitworth RJ, Sloderbeck PE (2012) Genetic structure of Tribolium castaneum (Coleoptera: Tenebrionidae) populations in mills. Environ Entomol 41:188–199. https://doi.org/10.1603/EN11207
Sinclair ER, White GG (1980) Stored products insect pests in combine harvesters on the Darling Downs. Qld J Agric Anim Sci 37:93–99
Smith EH, Whitman RC (1992) Field guide to structural pests. National Pest Management Association, Dunn Loring, VA
Sokoloff A (1977) The biology of Tribolium with special emphasis on genetic aspects. Clarendon Press, Oxford
Toon A, Daglish GJ, Ridley AW, Emery RN, Holloway JC, Walter GH (2018) Significant population structure in Australian Cryptolestes ferrugineus and interpreting the potential spread of phosphine resistance. J Stored Prod Res 77:219–224. https://doi.org/10.1016/j.jspr.2018.05.004
Vela-Coiffier EL, Fargo WS, Bonjour EL, Cuperus GW, Warde WD (1997) Immigration of insects into on-farm stored wheat and relationships among trapping methods. J Stored Prod Res 33:157–166. https://doi.org/10.1016/S0022-474X(96)00043-4
Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370. https://doi.org/10.1111/j.1558-5646.1984.tb05657.x
White GG (1988) Field estimates of population growth rates of Tribolium castaneum (Herbst) and Rhyzopertha dominica (F) (Coleoptera: Tenebrionidae and Bostrychidae) in bulk wheat. J Stored Prod Pest Control 24:13–22. https://doi.org/10.1016/0022-474X(88)90004-5
White P, Carter C, Kingwell R (2018) Australia’s grain supply chains: costs, risks and opportunities. In: South Perth: Australian Export Grains Innovation Centre
Wright VF, Fleming EE, Post D (1990) Survival of Rhyzopertha dominica (Coleoptera, Bostrichidae) on friuts and seeds collected from Woodrat nests in Kansas. J Kansas Entomol Soc 63:344–347
Acknowledgements
We thank the farming enterprises across Australia for allowing access to their land, as well as Andrew Ridley, Jo Holloway, Rob Emery, and Philip Burrill, for providing samples.
Funding
This work was financially supported by the Australia–India Strategic Research Grand Challenge Funded (GCF010006) project entitled “Ensuring food security: harnessing science to protect our grain harvest from insect threats”, jointly sponsored by the Department of Science and Technology, New Delhi, India, and the Department of Innovation, Industry, Science and Research, Canberra, Australia.
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McCulloch, G.A., Daglish, G.J. & Walter, G.H. Two grain beetle species, one resource, different patterns of genetic structure: implications for management. J Pest Sci 95, 959–969 (2022). https://doi.org/10.1007/s10340-021-01430-y
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DOI: https://doi.org/10.1007/s10340-021-01430-y