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Molecular and morphometric identification of pistachio psyllids with niche modeling of Agonoscena pistaciae (Hemiptera: Aphalaridae)

Published online by Cambridge University Press:  27 September 2019

Mohammadreza Lashkari Open the ORCID record for Mohammadreza Lashkari [Opens in a new window] ,
Daniel Burckhardt Open the ORCID record for Daniel Burckhardt [Opens in a new window]  and
Roghayeh Shamsi Gushki
Mohammadreza Lashkari*
Affiliation:
Department of Biodiversity, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran
Daniel Burckhardt
Affiliation:
Naturhistorisches Museum, Augustinergasse 2, 4001Basel, Switzerland
Roghayeh Shamsi Gushki
Affiliation:
Department of Biodiversity, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran
*
Author for correspondence: Mohammadreza Lashkari, Email: [email protected]; [email protected]
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Abstract

Species of Agonoscena (Hemiptera: Aphalaridae) are key pests of pistachio in all of the most important pistachio producing countries in the Old World. The efficiency and accuracy of DNA barcoding for the identification of Agonoscena species were tested using mitochondrial cytochrome c oxidase subunit 1 (mtCO1) and cytochrome b (cytb) gene sequences. Moreover, morphometric sexual dimorphism was studied. Finally, the potential geographical distribution of Agonoscena pistaciae, the most important pistachio pest, was calculated using the MaxEnt model. Similar relationships of clustering were found in the morphometric analysis and the molecular analyses with mtCO1 and cytb genes, with A. bimaculata and A. pistaciae being closely related, and A. pegani constituting their sister group. Although the results showed that the cytb gene is a better marker for barcoding in this group, the mtCO1 gene clearly separates the three psyllid species making mtCO1 suitable for diagnostic purposes. A geometric morphometric analysis showed that the distance between landmark number 7 (bifurcation of vein M) to the fore margin of the forewing, and the distance between landmarks number 6 (apex of vein Cu1b) and 11 (wing base), are the most important geometric characters for diagnosing the studied species. Moreover, the forewing shape of males vs females is similar in A. pistaciae and A. bimaculata but differs significantly in A. pegani. In the ecological niche modeling of the distribution of A. pistaciae, the most important contribution was made by the variable ‘minimum temperature of coldest period’. The most suitable areas for A. pistaciae are restricted to Eastern, Southern and some parts of Central Iran.

Keywords

Cytochrome bCytochrome c oxidaseDNA Barcodinggeometric morphometricMaxEnt
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 110 , Issue 2 , April 2020 , pp. 259 - 269
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Copyright
Copyright © Cambridge University Press 2019

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References

Aghagoli, MN, Mozaffarian, F and Vafaei, SR (2013) Using wing geometric morphometric in identification of three species of grape cicads (Hem., Cicadidae) in Iran. Journal of Entomological Research 5, 1–10.Google Scholar
Alizadeh, A, Kharrazi Pakdel, A, Talebi Jahromi, K and Samih, MA (2011) Effect of some Beauveria bassiana (Bals.) viull isolates on common pistachio psylla Agonoscena pistaciae Burckh. and Laut. International Journal of Agriculture and Biology 9, 76–79.Google Scholar
Ashfaq, M, Hebert, PD, Mirza, JH, Khan, AM, Zafar, Y and Mirza, MS (2014 a) Analyzing mosquito (Diptera: Culicidae) diversity in Pakistan by DNA barcoding. PLoS One 9, e97268.CrossRefGoogle ScholarPubMed
Ashfaq, M, Hebert, PD, Mirza, MS, Khan, AM, Mansoor, S, Shah, GS and Zafar, Y (2014 b) DNA barcoding of Bemisia tabaci complex (Hemiptera: Aleyrodidae) reveals southerly expansion of the dominant whitefly species on cotton in Pakistan. PLoS One 9, e104485.CrossRefGoogle Scholar
Ashfaq, M, Prosser, S, Nasir, S, Masood, M, Ratnasingham, S and Hebert, PD (2015) High diversity and rapid diversification in the head louse, Pediculus humanus (Pediculidae: Phthiraptera). Scientific Reports 5, 14188.CrossRefGoogle Scholar
Bai, Y, Dong, JJ, Guan, dl, Xie, JY and Xu, S (2016) Geographic variation in wing size and shape of the grasshopper Trilophidia annulata (Orthoptera: Oedipodidae): Morphological trait variations follow an ecogeographical rule. Scientific Reports 6, 32680.CrossRefGoogle ScholarPubMed
Betts, CR and Wootton, RJ (1988) Wing shape and flight behaviour in butterflies (lepidoptera: papilionoidea and hesperioidea): a preliminary analysis. Journal of Experimental Biology 138, 271–228.Google Scholar
Bolu, H (2002) Investigations on the fauna of insects and mites in pistachio areas in south Eastern Anatolia Region of Turkey. Türkiye Entomoloji Dergisi 26, 197–208.Google Scholar
Bosso, L, Febbraro, M, Cristinzio, G, Zoina, A and Russo, D (2016) Shedding light on the effects of climate change on the potential distribution of Xylella fastidiosa. Biological Invasions 18, 1759–1768.CrossRefGoogle Scholar
Burckhardt, D and Basset, Y (2000) The jumping plant-lice (Hemiptera, Psylloidea) associated with Schinus (Anacardiaceae): systematics, biogeography and host plant relationships. Journal of Natural History 34, 57–155.CrossRefGoogle Scholar
Burckhardt, D and Lauterer, P (1989) Systematics and biology of the Rhinocolinae (Homoptera: Psylloidea). Journal of Natural History 23, 643–712.CrossRefGoogle Scholar
Burckhardt, D and Lauterer, P (1993) The jumping plant-lice of Iran (Homoptera, Psylloidea). Revue Suisse de Zoologie 100, 829–898.CrossRefGoogle Scholar
Burckhardt, D and Ouvrard, D (2012) A revised classification of the jumping plant-lice (Hemiptera: Psylloidea). Zootaxa 3509, 1–34.CrossRefGoogle Scholar
Corsi, F, Duprè, E and Boitani, L (1999) A large-scale model of wolf distribution in Italy for conservation planning. Conservation Biology 13, 150–159.CrossRefGoogle Scholar
Darriba, D, Taboada, GL, Doallo, R and Posada, D (2012) Jmodeltest 2: more models, new heuristics and parallel computing. Nature Methods 9, 772.CrossRefGoogle ScholarPubMed
Eldred, T, Meloro, C, Scholtz, C, Murphy, D, Fincken, K and Hayward, M (2016) Does size matter for horny beetles? A geometric morphometric analysis of interspecific and intersexual size and shape variation in Colophon haughtoni Barnard, 1929, and C. kawaii Mizukami, 1997 (Coleoptera: Lucanidae). Organisms Diversity & Evolution 6, 821.CrossRefGoogle Scholar
Erfanfar, D, Sarafrazi, A, Ghanbalani, GN, Ostovan, H and Shojaei, M (2014) Claims of potential expansion and future climatic scenarios for Orius species (Hemiptera: Anthocoridae) throughout Iran. European Journal of Zoological Research 3, 43–55.Google Scholar
Esmail-pour, A (1998) Distribution, use and conservation of pistachio in Iran. In Padulosi, S and Hadj-Hassan, A (eds), Towards A Comprehensive Documentation of Distribution and use of Pistacia Genetic Diversity in Central & West Asia, North Africa and Europe. Report of the IPGRI work shop on Pistacia, Italy: International Plant Genetic Resources Institute (IPGRI). pp. 16–27.Google Scholar
Fazeli Salmani, A, Davarynejad, GH and Sadeghi, H (2012) Influence of geographical direction and pistachio cultivar on the capture of adult pistachio psylla by yellow sticky card. Acta Horticulture 933, 523–527.CrossRefGoogle Scholar
Gómez, GF, Márquez, EJ, Gutiérrez, LA, Conn, JE and Correa, MM (2014) Geometric morphometric analysis of Colombian Anopheles albimanus (Diptera: Culicidae) reveals significant effect of environmental factors on wing traits and presence of a metapopulation. Acta Tropica 135, 75–85.CrossRefGoogle ScholarPubMed
Gordon, H, Rotstayn, L, McGregor, J, Dix, M, Kowalczyk, E, O'Farrell, S, Waterman, LJ, Hirst, AC, Wilson, SG, Collier, MA, Watterson, IG and Elliott, TI (2002) The CSIRO Mk3 climate system model. CSIRO Atmospheric Research technical paper.Google Scholar
Graham, CH and Hijmans, RJ (2006) A comparison of methods for mapping species ranges and species richness. Global Ecology and Biogeography 15, 578–587.CrossRefGoogle Scholar
Hajibabaei, M, Janzen, DH, Burns, JM, Hallwachs, W and Hebert, PD (2006) DNA barcodes distinguish species of tropical Lepidoptera. Proceedings of the National Academy of Sciences of the United States of America 103, 968–971.CrossRefGoogle ScholarPubMed
Hebert, PDN, Cywinska, A, Ball, SL and deWaard, JR (2003 a) Biological identifications through DNA barcodes. Proceedings of the Royal Society of London B: Biological Sciences 270 (1512), 313–321.CrossRefGoogle ScholarPubMed
Hebert, PDN, Ratnasingham, S and deWaard, JR (2003 b) Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London B: Biological Sciences 270(suppl. 1), S96–S99.CrossRefGoogle ScholarPubMed
Hebert, PD, Stoeckle, MY, Zemlak, TS and Francis, CM (2004 a) Identification of birds through DNA barcodes. PLoS Biology 2, e312.CrossRefGoogle ScholarPubMed
Hebert, PDN, Penton, EH, Burns, JM, Janzen, DH and Hallwachs, W (2004 b) Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. Proceedings of the National Academy of Sciences of the United States of America 101, 14812–14817.CrossRefGoogle ScholarPubMed
Hijmans, R, Cameron, S, Parra, J, Jones, P and Jarvis, A (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 1965–1978.CrossRefGoogle Scholar
Hodkinson, I and Hollis, D (1981) The psyllids (Homoptera: Psylloidea) of Mallorca. Insect Systematics & Evolution 12, 65–77.Google Scholar
Ivanova, NV, Zemlak, TS, Hanner, RH and Hebert, PD (2007) Universal primer cocktails for fish DNA barcoding. Molecular Ecology Resources 7, 544–548.Google Scholar
Karimi Darabi, S, Hosseini, R, Farahpour, A and Aalami, A (2014) Application of RAPD in comparison of diversity of common pistachio psylla (Agonoscena pistaciae Burckhardt & Lauterer) populations in some northern and southern regions of Kerman province. Journal of Plant Pests Research 4, 21–34.Google Scholar
Khatamsaz, M (1989) Flora of Iran No. 3: Anacardiaceae. Research Institute of Forests & Rangelands (in Farsi).Google Scholar
Kumar, S, Neven, LG and Yee, WL (2014) Assessing the potential for establishment of western cherry fruit fly using ecological niche modeling. Journal of Economic Entomology 107, 1032–1044.CrossRefGoogle ScholarPubMed
Kumar, S, Stecher, G, Li, M, Knyaz, C and Tamura, K (2018) MEGA x: molecular evolutionary genetics analysis across computing platforms. Molecular Biology and Evolution 35, 1547–1549.CrossRefGoogle ScholarPubMed
Lashkari, MR, Sahragard, A, Manzari, S, Hosseini, R and Erfanfar, D (2013) Niche modeling of asian citrus psyllid, Diaphorina citri Kuwayama (Hem.: Psyllidae), in Iran. Plant Pests Research 3, 45–58.Google Scholar
Mart, C, Erkılıç, L, Bolu, H, Uygun, N and Altin, M (1995) Species and pest control methods used in pistachio orchards of Turkey. Acta Horticulturae 419, 379–386.CrossRefGoogle Scholar
Martoni, F, Bulman, S, Pitman, A, Taylor, G and Armstrong, K (2018) DNA barcoding highlights cryptic diversity in the New Zealand Psylloidea (Hemiptera: Sternorrhyncha). Diversity 10, 50.CrossRefGoogle Scholar
Malenovský, I, Lauterer, P, Labina, E and Burckhardt, D (2012) Jumping plant-lice (Hemiptera: Psylloidea) of Afghanistan. Acta Entomologica Musei Natioalis Pragae 52, 1–22.Google Scholar
Mehrnejad, MR (2000) A study on susceptibility and resistance of 10 pistachio cultivars and 2 wild pistachio species to the common pistachio psylla. Final report of a research projects. Pistachio Research Institute, Rafsanjan, Iran.Google Scholar
Mehrnejad, MR (2003) Pistachio psylla and other major psyllids of Iran. Tehran: Ministry of Jihad-e-Agriculture. p. 105.Google Scholar
Mitrovski-Bogdanović, A, Tomanović, Ž, Mitrović, M, Petrović, A, Ivanović, A, Žikić, V, Stary, P and Vorburger, C (2014) The Praon dorsale–yomenae s.str. complex (Hymenoptera, Braconidae, Aphidiinae): Species discrimination using geometric morphometrics and molecular markers with description of a new species. Zoologischer Anzeiger 253, 270–282.CrossRefGoogle Scholar
Nadi, H (2014) Genetic differentiation among the Iranian populations of Agonoscena pistaceae (Hom: Psyllidae) by using molecular markers. Master of Science Thesis: Sari University of Agricultural Science and Natural Resource, p. 92.Google Scholar
Nicolas, V, Schaeffer, B, Missoup, AD, Kennis, J, Colyn, M, Denys, C, Tatard, C, Cruaud, C and Laredo, C (2012) Assessment of three mitochondrial genes (16S, Cytb, CO1) for identifying species in the praomyini tribe (Rodentia: Muridae). PLoS One 7, e36586.CrossRefGoogle Scholar
Park, DS, Foottit, R, Maw, E and Hebert, PD (2011) Barcoding bugs: DNA-based identification of the true bugs (Insecta: Hemiptera: Heteroptera). PLoS One 6, e18749.CrossRefGoogle Scholar
Percy, DM (2017) Making the most of your host: the Metrosideros-feeding psyllids (Hemiptera, Psylloidea) of the Hawaiian Islands. ZooKeys 649, 1–163.CrossRefGoogle Scholar
Percy, DM, Butterill, PT and Malenovský, I (2016) Three new species of gall-forming psyllids (Hemiptera: Psylloidea) from Papua New Guinea, with new records and notes on related species. Journal of Natural History 50, 1073–1101.CrossRefGoogle Scholar
Peterson, AT and Cohoon, KP (1999) Sensitivity of distributional prediction algorithms to geographic data completeness. Ecological Modelling 117, 159–164.CrossRefGoogle Scholar
Peterson, AT and Holt, RD (2003) Niche differentiation in Mexican birds: using point occurrences to detect ecological innovation. Ecology Letters 6, 774–782.CrossRefGoogle Scholar
Peterson, AT and Shaw, J (2003) Lutzomyia vectors for cutaneous leishmaniasis in Southern Brazil: ecological niche models, predicted geographic distributions, and climate change effects. International Journal for Parasitology 33, 919–931.CrossRefGoogle ScholarPubMed
Phillips, SJ, Anderson, RP and Schapire, RE (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling 190, 231–259.CrossRefGoogle Scholar
Phillips, SJ, Dudík, D and Schapire, RE (2018) Maxent software for modeling species niches and distributions (Version 3.4.1). Available at http://biodiversityinformatics.amnh.org/open_source/maxent/ (Accessed 22 April 2018).Google Scholar
Queiroz, DL, Majer, J, Burckhardt, D, Zanetti, R, Fernandez, JIR, de Queiroz, EC, Garrastazu, M, Fernandes, BV and dos Anjos, N (2013) Predicting the geographical distribution of Glycaspis brimblecombei (Hemiptera: Psylloidea) in Brazil. Australian Journal of Entomology 52, 20–30.CrossRefGoogle Scholar
Rohlf, FJ (2000) NTSYSpc, version 2.10e, Exter Software, Applied Biosystematics Inc.Google Scholar
Rohlf, FJ (2010) tpsRelw, version 1.49, Software, Department of Ecology and Evolution, State University of New York, Stony Brook, NY 11794-5245. Available at http://life.bio.sunysb.edu/morph.Google Scholar
Rohlf, FJ (2016 a) tpsDig2. version 2.28. Department of Ecology and Evolution, State University of New York, Stony Brook.Google Scholar
Rohlf, FJ (2016 b) tpsRegI, version 1.45. Software, Department of Ecology and Evolution, State University of New York, Stony Brook.Google Scholar
Ronquist, F, Teslenko, M, Van Der Mark, P, Ayres, DL, Darling, A, Höhna, S, Larget, B, Liu, L, Suchard, MA and Huelsenbeck, JP (2012) Mrbayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Systematic Biology 61, 539–542.CrossRefGoogle ScholarPubMed
Roura-Pascual, N, Brotons, L, Peterson, AT and Thuiller, W (2009) Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula. Biological Invasions 11, 1017–1031.CrossRefGoogle Scholar
Schwarz, G (1978) Estimating the dimension of a model. The Annals of Statistics 6, 461–464.CrossRefGoogle Scholar
Serbina, L, Burckhardt, D, Birkhofer, K, Syfert, MM and Halbert, SE (2015) The potato pest Russelliana solanicola Tuthill (Hemiptera: Psylloidea): taxonomy and host-plant patterns. Zootaxa 4021, 33–62.CrossRefGoogle ScholarPubMed
Shabani, M, Bertheau, C, Zeinalabedini, M, Sarafrazi, A, Mardi, M, Naraghi, SM, Rahimian, H and Shojaee, M (2013) Population genetic structure and ecological niche modelling of the leafhopper Hishimonus phycitis. Journal of Pest Science 86, 173–183.CrossRefGoogle Scholar
Shamsi Gushki, R, Lashkari, MR and Mirzaei, S (2018) Identification, sexual dimorphism, and allometric effects of three psyllid species of the genus Psyllopsis by geometric morphometric analysis (Hemiptera, Liviidae). ZooKeys 737, 57.CrossRefGoogle Scholar
Simon, C, Frati, F, Beckenbach, A, Crespi, B, Liu, H and Floors, P (1994) Evolution, weighting, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Annals of the Entomological Society of America 87, 651–701.CrossRefGoogle Scholar
Solhjouy-Fard, S, Sarafrazi, A, Minbashi Moeini, M and Ahadiyat, A (2013) Predicting habitat distribution of five heteropteran pest species in Iran. Journal of Insect Science 13, 116.CrossRefGoogle ScholarPubMed
Souliotis, C, Markoyiannaki-Printziou, D and Lefkaditis, F (2002) The problems and prospects of integrated control of Agonoscena pistaciae Burck. & Laut. (Hom., Sternorrhyncha) in Greece. Journal of Applied Entomology 126, 384–388.CrossRefGoogle Scholar
Taylor, G, Fagan-Jeffries, EP and Austin, AD (2016) A new genus and twenty new species of Australian jumping plant-lice (Psylloidea: Triozidae) from Eremophila and Myoporum (scrophulariaceae: Myoporeae). Zootaxa 4073, 1–84.CrossRefGoogle Scholar
Tobe, SS, Kitchener, AC and Linacre, AM (2010) Reconstructing mammalian phylogenies: a detailed comparison of the cytochrome b and cytochrome oxidase subunit I mitochondrial genes. PLoS One 5, e14156.CrossRefGoogle ScholarPubMed
Zelditch, ML, Lundrigan, BL and Garland, TJ (2004) Developmental regulation of skull morphology. I. Ontogenetic dynamics of variance. Evolution Development 6, 194–206.CrossRefGoogle Scholar
Zúñiga-Reinoso, A and Benítez, HA (2015) The overrated use of the morphological cryptic species concept: an example with Nyctelia darkbeetles (Coleoptera: Tenebrionidae) using geometric morphometrics. Zoologischer Anzeiger 255, 47–53.CrossRefGoogle Scholar