Introduction

The difficulty of aphid taxonomy and identification has been recognized as far back as the 18^th Century by Carl Linnaeus (Walsh 1863) and is driven by multiple, often interconnected factors, including morphology and life history traits. Many aphids are heteroecious (Blackman and Eastop 2000) and host-specific morphology can vary enough that taxonomists have described the same species multiple times based on different host-associated life stages (Stern et al. 1997). Furthermore, aphid morphology can change substantially with abiotic factors such as temperature (e.g. Blackman and Spence 1994) and number of daylight hours (e.g. Hille Ris Lambers 1966), and biotic factors such as colony size (e.g. Watt and Dixon 1981), all of which cloud species delimitation. Lastly, most species diagnoses require measurements of body parts. Rarely are there one or more discrete characters that can separate species. Therefore, given the plasticity in aphid morphology and the paucity of discrete characters, aphid taxonomy desperately needs better ways to diagnose species.

Challenges in aphid taxonomy have resulted in different tools and methods to discern species. For example, Foottit et al. (2008) used mitochondrial DNA barcodes to distinguish among aphid species with high success. This high rate of success of DNA barcoding has led to the formation of regional barcoding databases to aid in the identification of aphid species (e.g. Coeur d'Acier et al. 2014). However, DNA barcoding is limited to freshly collected or alcohol-preserved specimens and cannot be used with cleared and slide-mounted specimens, which negates its use when comparing historic specimens.

Both statistical and non-statistical morphological tools have been developed for use with slide-mounted specimens. For example, online interactive keys have been developed to distinguish among large numbers of aphid species, but they lack statistical grounds for identification (e.g., Favret and Miller 2012). Multivariate statistics, specifically linear discriminant analysis (LDA), which requires taxonomic designation a priori and can use multivariate analysis of variance (MANOVA) with discrete and continuous characters to test whether the group centroids differ (see Henderson 2006 for multivariate statistics introduction applied to taxonomy), have been applied to aphids to distinguish among aphid species and ecotypes, (e.g. Favret and Voegtlin (2004) for three species of Cinara, Lozier et al. (2008) for three species of Hyalopterus, Valenzuela et al. (2009) for three species of Rhopalosiphum and Bašilova (2010) for two species of Cryptomyzus). However, such studies have been limited to just a few species and have not been used to evaluate historic synonymies.

In this paper, we expand upon previous examples using discriminant analysis in aphid taxonomy to test whether multivariate statistics support currently recognized Rhopalosiphum species and their synonymies. Specifically, we use LDA to statistically compare 34 valid and synonymized Rhopalosiphum species to test the validity of historic synonomies. Valid species and synonymies were tested using iterative LDA analyses in which we removed the most distinct species clusters and reanalyzed the remaining species. We used LDA analyses with only valid species and applied the resulting discriminant functions to synonymized species to determine whether the synonymies are statistically correct using species specific LDA functions. The methods and analyses presented here are unique and repeatable with respect to previous aphid studies. No previous studies have tested taxonomic hypotheses in this manner. We use open source software and describe the analyses with sufficient detail to make them repeatable, which has been lacking from the literature. Lastly, our analyses are statistically robust with respect to LDA model assumptions as we thoroughly describe character transformations and missing data and their relationship to model assumptions.

Our example genus of aphids in need of comprehensive review and revision is Rhopalosiphum Koch, 1857 (Aphididae: Aphidinae: Aphidini: Rhopalosiphina) (Koch 1857). Rhopalosiphum currently comprises 17 recognized species, including some of the earliest named aphids (i.e. R. padi (Linnaeus, 1758) and R. nymphaeae (Linnaeus, 1761)) (Fig. 1, Table 1). Most Rhopalosiphum species are heteroecious and typically overwinter on rosaceous trees (Rosaceae: Crataegus Tourn. ex L., Malus Mill., Prunus L.) and feed on grasses, sedges, and related plants (Poales) throughout the summer (Table 2). A number are important grain (e.g. R. maidis (Fitch, 1856) and R. padi) and apple (R. oxyacanthae) pests that transmit more than 25 aphid-transmitted plant viruses (Chan et al. 1991) and are often intercepted at ports of entry and in aphid-monitoring suction traps (Strażyński 2010, Favret and Miller 2012, Skvarla et al. 2017). Those species that are not economically important have received comparatively little study. For example, R. nigrum Richards, 1960 and R. padiformis Richards, 1962 have not been discussed in scientific literature outside of their original descriptions and catalog entries. Examples like this complicate the identification of alates collected without host data (e.g., in suction traps) because the majority of taxonomic resources focus on apterae and not alates.

Table 1.

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Rhopalosiphum species, associated original descriptions, type depositories, and number of specimens examined. Bold names are currently recognized as valid species with synonymized species listed immediately after. Citations marked with an asterisk (*) are not included in the literature cited as the authors were unable to locate them.

Species	Original description	Primary type depository	Secondary type depositories	Number of apterae measured	Number of alatae measured	Notes
R. albigubernum	Zhang and Qiao (1997)			-	-	Unable to locate types.
R. arundinariae	Tissot (1933a)	USNM	NHMUK	3	5	Moved to Melanaphis.
R. cerasifoliae	Fitch (1855)	NHMUK	USNM	0	10
= Aphis furcata	Patch (1914)	CNC	CNC	0	6	Lectotype and paralectotypes on one slide.
= Aphis tahasa	Hottes and Frison (1931)	USNM	NHMUK	27	10
R. chusqueae	Pérez-Hidalgo et al. (2012)	CZULE		2	0
R. dryopterae	Kan (1986)			-	-	Unable to locate types.
R. enigmae	Hottes and Frison (1931)	INHS	NHMUK, USNM	120	32
= R. laconae	Taber (1993)	USNM	NCSU	54	5	Unable to locate holotype, apparently lost or never deposited. Neotype designated from NCSU paratypes.
R. esculentum	Raychaudhuri and Roychoudhuri (1978)			-	-	Unable to locate types; syn. possible de Aphis craccivora (Remaudiere & Remaudiere 1997)
R. maidis	Fitch (1856)	USNM		93	51
= Aphis adusta	Zehntner (1897a)			-	-	Unable to locate types.
= Aphis africana	Theobald (1914)	NHMUK	NHMUK	11	3
= Aphis cookii	Essig (1911)	EMEC		0	13
= Stenaphis monticellii	del Guercio (1914a)			-	-	Unable to locate types.
= Aphis obnoxia	Mordvilko (1916)*			-	-	Unable to locate types.
= Schizaphis setariae	Rusanova (1962)*			-	-	Unable to locate types.
= Aphis vulpiae	del Guercio (1914b)			-	-	Unable to locate types.
= R. zeae	Rusanova (1960)*			-	-	Unable to locate types.
R. musae	Schouteden (1906)	NHMUK	NHMUK	27	7	Lecto- and paralectotypes.
= R. scirpifolii	Gillette and Palmer (1932)	USNM	NHMUK, USNM	6	15
R. nigrum	Richards (1960)	CNC	CNC, NHMUK, USNM	10	8
R. nymphaeae	Linnaeus (1761)			58	14
= Aphis aquatica	Jackson (1908)	OSUC (?)		-	-	Unable to locate types. Type depository not given in original description. Jackson worked at The Ohio State and likely deposited his types there, however a search for the specimens did not locate them.
= Aphis butomi	von Schrank (1801)			-	-	Unable to locate types.
= Aphis infuscata	Koch (1854a)			-	-	Unable to locate types.
= R. najadum	Koch (1854b)			-	-	Unable to locate types.
= R. momo	Shinji (1922)			-	-	Unable to locate types, apparently lost.
= Aphis prunaria	Walker (1848)	NHMUK		0	2
= Aphis prunorum	Dobrowljansky (1913)	Kiev Entomological Station (defunct)		-	-	Unable to locate types, apparently lost.
= Hyadaphis sparganii	Theobald (1927)	NHMUK	NHMUK	6	0
= R. yoksumi	Ghosh et al. (1971)	Entomology laboratory, Calcutta University		-	-	Types not examined.
R. oxyacanthae	von Schrank (1801)	NHMUK		0	9
= Aphis crataegella	Theobald (1912)	NHMUK		-	-
= Aphis edentula	Buckton (1879)	NHMUK	NHMUK	-	-	Holotypes and 2 paratypes on one slide, holotype indicated. Ovipara.
= Aphis fitchii	Sanderson (1902)	USNM	NHMUK	0	3
= Aphis insertum	Walker (1849)	USNM		0	54
= Aphis macatata	Walker (1849)	NHMUK		0	1
= R. viridis	Richards (1960)	CNC	CNC, NHMUK	0	14
= R. mali bivincta	Fitch (1855)	USNM		-	-	Unable to locate types, apparently lost. See also Favret et al. (2008)
= R. mali fulviventris	Fitch (1855)	USNM		-	-
= R. mali immaculata	Fitch (1855)	USNM		-	-	Unable to locate types, apparently lost. See also Favret et al. (2008)
= R. mali nigricollis	Fitch (1855)	USNM		-	-
= R. mali nigriventris	Fitch (1855)	USNM		-	-
= R. mali obsoleta	Fitch (1855)	USNM		0	1
= R. mali pallidicornis	Fitch (1855)	USNM		0	1
= R. mali tergata	Fitch (1855)	USNM		0	1
= R. mali thoracica	Fitch (1855)	USNM		0	1
= R. mali triseriata	Fitch (1855)	USNM		0	1
R. padi	Linnaeus (1758)	NHMUK		49	44	Holotype not examined.
= Siphocoryne acericola	Matsumura (1917)			-	-	Unable to locate types.
= Siphonaphis padi americana	Mordvilko (1921)			-	-	Unable to locate types.
= Aphis avenaestivae	von Schrank (1801)			-	-	Unable to locate types.
= Siphocoryne donarium	Matsumura (1918)			-	-	Unable to locate types.
= Siphocoryne fraxinicola	Matsumura 1917			-	-	Unable to locate types.
= Aphis holci	Ferrari (1872)			-	-	Unable to locate types.
= Aphis prunifoliae	Fitch (1855)	USNM		24	24
= Aphis pseudoavenae	Patch (1917)	CNC		2	11
= Aphis tritici	Lawson (1866)*			-	-	Unable to locate types.
= Aphis uwamizuskurae	Monzen (1929)			-	-	Unable to locate types.
R. padiformis	Richards (1962)	CNC	CNC, NHMUK, USNM	4	0
R. parvae	Hottes and Frison (1931)	USNM		3	0
R. rufiabdominale	Sasaki (1899)	USNM	USNM	24	28
= Cerosipha californica	Essig (1944)	EMEC	US Bureau of Entomology and Plant Quarantine (defunct)	0	1	Unable to locate paratypes, apparently lost.
= R. fucanoi	Moritsu (1947)*	Entomology Laboratory, Kyusyu Imperial University		-	-	Types not examined.
= R. gnaphalii	Tissot (1933b)	USNM		4	1
= Anuraphis mume	Hori (1927)			-	-	Unable to locate types.
= Yamataphis oryzae	Matsumura (1917)			-	-	Unable to locate types.
= Yamataphis papaveri	Takahashi (1921)*	Taihoku agricultural experiment station (defunct)		-	-	Unable to locate types.
= Pseudocerosipha pruni	Shinji (1932)*			-	-	Unable to locate types.
= Aresha setigera	Blanchard (1939)			-	-	Unable to locate types.
= Aresha shelkovnikovi	Mordvilko (1921)			-	-	Unable to locate types.
= Siphocoryne splendens	Theobald (1915)	NHMUK		40	3
= R. subterraneum	Mason (1937)	USNM		17	19
R. rufulum	Richards (1960)	CNC	CNC, NHMUK	10	10
R. sanguinarium	Baker (1934)		NHMUK (cotype)	0	1
sp. nov. "ex. Arisaema"	undescribed	USNM		34	1
R. sp. T	undescribed, proposed by Bulman et al. (2005)	Crop and Food Research, Lincoln, New Zealand		-	-
R. near insertum	undescribed, proposed by Bulman et al. (2005)	Crop and Food Research, Lincoln, New Zealand		-	-
R. sp. x	undescribed, proposed by Valenzuela et al. (2009)			-	-

Table 2.

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Rhopalosiphum hosts and distributions. Host author names have been omitted for space. Unless otherwise noted, information is compiled from the original description (see Table 1), Holman (2009), and Blackman and Eastop (2017).

Taxon	Primary host	Secondary host	Distribution	Notes	Additional references
R. albigubernum	Citrus		Baidicheng, Fengjie, Sichuan, China	Known only from the type series, which consists of two alate vivipara.
R. arundinariae		Arundinaria tecta	Gainesville, FL	Known only from the type series, which were found as dense colonies on ventral side of younger A. tecta leaves that contained aptareae and alatae on 16 April 1930.
R. cerasifoliae	Prunus pennsylvanica, P. virginiana	Cyperaceae, including Schoenoplectus, Scirpus, and Eleocharis. Also Juncus (Juncaceae)	North America, wherever host plants occur	Can persist throughout summer on primary host.
R. chusqueae		Chusquea tomentosa	Costa Rica	Lives close to the nodes and well protected by leaves of C. tomentosa, so not easily detectable. Alatae and lifecycle unknown
R. dryopterae	Dryopteris filix-mas		Kyrgyzstan
R. enigmae		Typha, especially. T. latifolia; also recorded from Sparganium	North America, wherever host plants occur, though apparently most common in the East (A. Jensen, pers. comm.). "R. laconae" is morphology restricted to southeastern coastal plain.	Autoecious on cattails, no primary host known.
R. maidis	Prunus, including P. cornuta (Pakistan), P. mume and P. persica (Korea), and P. sargentii (Japan).	Zea, Sorghum, Hordeum,other Poaceae; occasionally Cyperaceae and Typhaceae.	Cosmopolitan, but cannot survive outdoors in regions with severe winter climates	Most lineages are autoecious anholocyclic, with males and ovipara occurring only rarely. Heteroecious, androcyclic populations are known from Asia, where the species originated. In the Northern Hemisphere, lineages with different chromosome counts are associated with different hosts: 2n = 10 colonize Hordeum and Echinochloa crus-galli, while 2n = 8 colonize Zea and Sorghum; lineages with 2n = 9 , 2n = 11, and heterozygous 2n = 8 are also known. In contrast, 2n = 8 and 2n = 9 lineages in Australia do not exhibit host preference. Morphological and early genetic investigations of North American lineages reported incomplete morphological separation and lack of genetic differences between the various parthenogenetic karyotype lineages of R. maidis, though future investigations may raise one or more lineages to species from within the complex.	Wildermuth and Walter (1932), Blackman (1954), Menon and Ghai (1969), Brown and Blackman (1988), Blackman et al. (1990), Blackman and Brown (1991), Barro (1992), Simon et al. (1995), Jauset et al. (2000)
R. musae	Prunus beseyi, P. subcordata, P. fasciculata	Scirpus; also Musa, Ensete, Sterlitzia	WA to CO, MD (native); Europe, Middle East, Africa, and Australia (adventive)	Adventive populations outside of the native range are presumed to be anholocyclic. Specimen vouchers reportedly sent to the USNM are not present in the collection and were presumably never sent.	Taber (2003)
R. nigrum	Crataegus	Avena sativa, Zizania aquatica, Alisma	ON, MB, AK; unconfirmed reports from OR, UT		Pantoja et al. (2006)
R. nymphaeae	Prunus	Aquatic and semi-aquatic plants, including Alisma, Juncus, Nelumbo, Nuphar, Sagittaria, Sparganium and Typha. Occasionally other hosts, including Canna, Glyceria, Lactuca, Triticum, and Tulipa	Cosmopolitan
R. oxyacanthae	Various Rosaceae including Malus, Pyrus, Cotoneaster, Crataegus, Sorbus, and Prunus	Various Poaceae, including Agropyron, Agrostis, Festuca, Poa; occasionally cyperaceae and Juncaceae.	North America (probable native range), Europe, North Africa, Japan	The name R. insertum Walker was used widely for the species in North America, but García Prieto et al. (2004) synonymized the species with R. oxyacanthae.
R. padi	Primarily Prunus virginiana (North America) and P. padus (Europe), occasionally other Prunus. One record on Syringa vulgaris.	Primarily Poaceae, occasionally Asteraceae, Brassicaceae, Cyperaceae, Iridaceae, Juncaceae, Lilaceae, Typhaceae and other taxa.	Cosmopolitan	Can persist throughout summer on primary host.
R. padiformis		Poa, Triticum	BC, MT	Primary host and associated morphs not known; alate males have been obtained in culture.
R. parvae		Carex (US), Scirpus lacustris (Italy)	Native to North America (IL); Italy (adventive)	Primary host not known.
R. rufiabdominale	Primarily Prunus; also recorded from Malus, Chaenomeles, Pyrus, Rhodotypos, and Sorbus.	Underground parts of Poaceae (including cereals) and Cyperaceae. Can infest some dicots (e.g. Asteraceae, Solanaceae), especially in greenhouse and hydroponic situations.	Native to East Asia. Currently pan-tropical/subtropical and restricted to greenhouses in colder climates.	Heteroecious holocyclic in East Asia and Italy; autoecious anholocyclic in majority of introduced range. Rakauskas et al. (2015) noted that if the heteroecious holocyclic forms recently reported from Italy spreads the species may persist in cold climates in Europe.	Etzel and Petitt (1992), Ciampolini et al. (1993), Zilahi-Balogh et al. (2005)
R. rufulum	Crataegus	Primarily Acorus, also recorded from Typha	North America and Europe, wherever hosts are found.
R. sanguinarium	Crataegus mexicana	Unknown, but reared on various Poaceae in lab conditions	Mexico
sp. nov. "ex. Arisaema"	Unknown	Arisaema	Maryland
R. sp. T	Unknown	Cereals	New Zealand
R. near insertum	Unknown	Cereals	New Zealand; Victoria, Australia
R. sp. x	Unknown	Zea mays	Victoria, Australia

a

b

Figure 1.

Rhopalosiphum live stereomicrographs.

a: R. padi.  
b: R. enigmae  

The taxonomic history of Rhopalosiphum is complicated. Many taxa with slightly-swollen siphunculi were historically included within Rhopalosiphum, but are now placed in a different tribe, Macrosiphini (e.g. Hyadaphis Börner, Lipaphis Mordvilko, Rhopalomyzus Mordvilko), or other aphidine genera (e.g. Melanaphis van der Goot, Schizaphis Börner) (Richards 1960, Blackman and Eastop 2017, Favret 2019). Börner (1952) was the first to restrict the definition of the genus as it is currently conceived.

Molecular studies (e.g. Kim and Lee 2008) suggest Rhopalosiphum is closely related to the rhopalosiphine genera Melanaphis and Schizaphis. However, no comprehensive molecular or morphological study has tested the monophyly of the genera and species contained therein (Valenzuela et al. 2009). Indeed, Halbert and Voegtlin (1998) suggested that Rhopalosiphum arundinariae (Tissot, 1933) is a North American representative of Melanaphis based on “wing venation [and] cuticular sculpturing”, though declined to officially move it to Melanaphis.

Rhopalosiphum species concepts are further complicated by the presence of cryptic species (Bulman et al. 2005, Valenzuela et al. 2009); holocyclic, heteroecious (alternating between sexual and asexual reproduction on primary and secondary hosts) and anholocyclic, autoecious (only asexual reproduction on secondary hosts) forms within the same species (e.g. R. padi); and morphological plasticity within species that often makes morphological species determinations, especially of alate specimens, difficult (personal observation).

Finally, while 17 species are currently recognized, at least 85 specific names (which includes misspellings of valid names) have been applied to Rhopalosiphum (Favret 2019). Many of the names were synonymized in species catalogues (e.g. Eastop and Hille Ris Lambers 1976, Remaudière and Remaudière 1997), where the authors gave little or no comment on their reasoning for the moves, and the moves have not been confirmed since they were proposed. Thus, there are potentially valid species that have been improperly synonymized.

Herein, we confirm many historic synonymies using LDA, propose two new synonymies, and report new distribution data for R. rufulum Richards, 1960, based on material examined for the analyses.

Materials and Methods

Most specimens examined are housed in the National Museum of Natural History Aphidomorpha Collection (USNM), which is currently housed at the USDA-ARS Beltsville Agricultural Research Center in Beltsville, Maryland, U.S.A. Additionally, types and other material were borrowed from the Essig Museum of Entomology (EMEC), Berkeley, California, U.S.A.; the Florida State Collection of Arthropods (FSCA), Gainesville, Florida, U.S.A.; the Illinois Natural History Survey Insect Collection (INHS), Champaign, Illinois, U.S.A.; the North Carolina State University Insect Museum (NCSU), Raleigh, North Carolina, U.S.A.; The Ohio State University Triplehorn Insect Collection (OSUC), Columbus, Ohio, U.S.A; the personal collection of Andrew Jensen (AJ), Lakeview, OR, U.S.A.; The Canadian National Collection of Insects, Arachinds, and Nematodes (CNC), Ottawa, Ontario, Canada; the Natural History Museum (NHMUK), London, United Kingdom; and the Aphidological Collection of the University of León (CZULE). For a list of types, species, and number of specimens examined, see Table 1. Museum abbreviations follow Evenhuis (2017).

Slides were labelled with individual, sequential numbers (MS 0001–0980) and specimens assigned a number that was appended to the slide number (e.g. MS 0001-1 for the first specimen on the first slide). Specimens were examined using a Zeiss Axio Imager M1 stereomicroscope; micrographs were taken and measurements of various morphological features of adult female apterous and alate specimens made using AxioVision 4.9.1 software (Carl Zeiss AG, Oberkochen, Germany) (Fig. 2, Table 3). Measurements were hand-written in a notebook, then later manually entered into an Excel spreadsheet.

Table 3.

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Descriptions of measurements.

Measurement number	Measurement description or ratio
1	Antenna segment (AS) 1, length
2	Antenna segment (AS) 2, length
3	Antenna segment (AS) 3, length
4	Antenna segment (AS) 4, length
5	Antenna segment (AS) 5, length
6	Antenna segment (AS) 6 base, length
7	Antenna segment (AS) 6, process terminalis (pt), length
8	Head width across eyes
9	Ultimate rostral segment (RIV+V), length
10	Ultimate rostral segment (RIV+V), width
11	Hind femur, length
12	Hind tibia, length
13	Hind distitarsus, length
14	Siphunculus, length
15	Cauda, length
16	Abdominal segment 8 submedian seta, length
17	Body length (BL)
18	Siphunculus, width
19	RIV+V length: RIV+V width
20	RIV+V length: hind distitarsus length
21	Pt length: AS 6 base length
22	Siphunculus length: siphunculus width
23	Siphunculus length: cauda length
24	Siphunculus length: AS 3 length
25	RIV+V length: cauda length
26	BL: head width
27	AS 3 and 4 fused (0 = no, 1 = yes)
28–33	Angle, A1–A6 (see Fig. 2b)
34–36	Area, S1–S3 (see Fig. 2c)
37–57	Wing length, L1–L21 (see Fig. 2d)
58	L1:L2 (37:38)
59	L1:L3 (37:39)
60	L1:L4 (37:40)
61	L1:L5 (37:41)
62	L1:L6 (37:42)
63	L1:L7 (37:43)
64	L2:L3 (38:39)
65	L2:L4 (38:40)
66	L2:L6 (38:41)
67	L2:L7 (38:42)
68	L3:L4 (39:40)
69	L6:L7 (42:43)

a

b

c

d

Figure 2.

Wing structures measured in Rhopalosiphum alatae.

a: Wing schematic.  
b: Vein angles.  
c: Cell areas.  
d: Vein and point-to-point lengths. See Table 3 for explanation of alphanumeric codes.  

Morphological terms and structures were adapted from Foottit and Richards (1993). Throughout the text, the term aptera (pl. apterae) refers to wingless adult vivipara (pl. viviparae) and alata (pl. alatae) refers to winged adult vivipara (pl. viviparae). Body measurements were adapted from Foottit et al. (2010). Wing measurements (Fig. 2) were adapted from Favret (2009). All measurements are in micrometers (μm) and were taken from the right side of the body when possible. Species names and statuses follow Favret (2019). Measurement data are available as supplementary files (Suppl. materials 1, 2, 3, 4).

Statistical analyses

We used linear discriminant analysis (LDA) in R (R Core Team 2017) using the MASS package (Venables and Ripley 2002) to test the synonymized and valid species names designations. The code we used to analyze the apterae datasets is available in Suppl. material 5

The analysis proceeded in several steps, which were similar for apterae and alatae, the first of which was data cleaning, described below. LDA is one of the most commonly employed discriminant function analyses, used both to identify useful characters distinguishing specimens of valid species and groups of species, and to form discriminant functions that could then be applied to specimens of uncertain taxonomic status to determine if they cluster with valid species or cluster separately, which would suggest a new species. This LDA approach was applied in a systematic iterative manner; the initial linear discriminant functions separated the most distinctive species, leaving a large amorphous cluster of the other known species. In the next step, the distinctive valid species were removed in that iteration, and the method applied to the remaining valid species. This could be followed by another iteration, until all valid species were separated to the extent possible using available morphological characters.

Prior to the analyses, the dataset was checked for incorrectly entered data. This was performed for both the valid and synonymized by constructing boxplots for each trait, broken down by species (e.g. Fig. 3). This allowed us to identify outlier measurements in the Excel database, which were compared against the hand-recorded measurements and in most cases were the result of inaccurately entered data (e.g. 10002 instead of 100.02 or 278 instead of 728). Incorrectly entered data that were discovered in this manner were corrected before additional analyses. The boxplots also gave a general picture of which species were more variable for which traits.

Figure 3.  

Example of box plots created for a character (length of antennal segment I here) that were used to identify outlier measurements that should be doublechecked before further analyses. Note the outliers for R. enigmae and R. padi, which were the result of miskeyed data.

‘Size’: as a trait and as an adjustment

We standardized the size measurements of each specimen, based on a ‘size’ variable (but also kept ‘size’ as a variable in the LDA, explained below). There are several reasons for this. One is that some species are more variable in size than others. If measures are not size adjusted, the LDA does not work as well; in fact, we implemented the size adjustments because size affected the usefulness of many of the measures, especially for taxa with a lot of size variability. Second, if one doesn't adjust for size, many of the measures are correlated through size, so less useful. Third, we wanted measures which made sense morphometrically, and these are often 'relative' measures, (e.g. antenna are relatively long for species A (in relation to its size) versus species B). If not adjusted for size, we would have to use ratios for more variables. Standardizing on size was very helpful for many traits and might be useful when developing criteria to separate species in other groups. Given that it is desirable to adjust for size, how does one best estimate 'size'? There is not a one-size-fits-all solution for this and, while we found one that seems to work well for these taxa, it may be improved upon or altered for other taxa. This variable was constructed by combining the body length, head width, and femur length using principal components (PC); head width and femur length were chosen as, among all measured characters, these were most highly correlated with body length. This is a dimension reduction technique, the idea being to create a single variable (the first PC) that best captures the variation in these three correlated measures. In cases where one or two of these measures were missing, the derived principal component measure (henceforth labelled ‘relative size’) for the specimen was imputed using linear regression based on the rest of the data set. Another method employed for developing a size measure is the use the geometric mean of the characters. We calculated the geometric means for data where we had all three characters and found the correlation between the geometric mean and first PC to be 0.9963; for this data set the two methods would yield essentially identical results.

Our relative size measure was retained as a character in the LDA analysis. It was also used to adjust all other size measures using linear regression, i.e. adjusted measures were residuals from regressing each of the size measures (dependent variable) on the relative size (independent variable). This resulted in smaller and larger individuals of the same species having similar adjusted measurements. Non-size measures (such as wing angles or ratios) were not adjusted using relative size, instead they were transformed by taking logs; this created measures that were closer to being normally distributed. All measures were then individually standardized (using all samples) to mean zero, standard deviation one (this helps one to interpret the coefficients of the linear discriminant analysis results). Missing values were then imputed by randomly sampling from the corresponding adjusted measure of other individuals of that same species. In the unusual case where this could not be done (e.g. all specimens were incomplete for this trait), the trait value was set to zero (which is the overall mean for each measure), removing its influence on the calculated discriminant functions. If all specimens of a species were naturally lacking a trait, a new character column was created for that trait, with either 0 (not missing) or 1 (missing). The end result was that a naturally missing trait could be used as a character when creating the linear discriminant function and that incomplete or aberrant individuals were not dropped from the analysis because of missing data.

Linear discriminant analyses

A first LDA was performed on the cleaned dataset for only the valid species (this included the three variables used to create relative size, as well as the adjusted size measure) using 49 measured values and 20 ratios calculated from those values. The first three latent axes were sufficient to explain 80% or more of the variability. We looked at which variables loaded most heavily on each axis and compared that to the boxplots created at an earlier step as a check that the methodology was working as expected. The linear discriminant functions derived from the valid species were then applied to all specimens (valid and synonymized) so the specimens could be mapped to the two dimensional space created from pairs of the latent axes. Species were suitably coded so they could be distinguished on the plots. Since there was only one individual of R. sanguinarium Baker, 1934 for both apterae and alatae, it was analyzed with the synonymized, rather than the valid, species.

We then identified clusters of specimens comprising a valid species. Sometimes a valid species was well separated from other valid species and sometimes not. For those well-separated valid species, we looked to see if any of the synonymized species occupied the same space and manually outlined the group. When this happened, we concluded that the synonymized species and valid species were likely the same and we removed them from further analyses. If a synonymized species formed a distinct cluster, we concluded that it was not synonymized with any of the valid (or other synonymized) species and considered it a separate species and also removed it from further analyses.

With the remaining species, we repeated the previously described procedure, producing another LDA using only the valid species that did not separate well in the previous analysis, and using the same independent variables. With fewer species and the same number of independent variables, the software sometimes had difficulty due to insufficient degrees of freedom. When this occurred, we reduced the number of independent variables by removing those that were highly correlated with others in a stepwise manner until there were no independent variables that were highly correlated with other independent variables, and then produced an LDA with the reduced set of independent variables. For alatae, this methodology needed to be repeated a third time to finish separating all the known species.

Notes on Rhopalosiphum species not included in linear discriminant analyses

Rhopalosiphum dryopterae Kan, 1986. Halbert and Voegtlin (1998) and Jenson and Holman (2000) suggested R. dryopterae is a species of Dysaphis. The authors have been unable to locate the type specimens or a copy of the original description by Kan (1986), though Holman, now deceased, based his suggestion on it (Jensen, pers. comm). We hesitate to move R. dryopterae without having seen specimens or the description, although concede that it is likely not a species of Rhopalosiphum given the weight of expert opinion and do not treat it further herein.

Rhopalosiphum esculentum Raychaudhuri and Roychoudhuri, 1978. Remaudière and Remaudière (1997) suggested R. esculentum may be a synonym of Aphis craccivora Koch, 1854. Unfortunately, the description of R. esculentum does not include characters that would definitively place the species in either Aphidina or Rhopalosiphina (i.e. lateral tubercles I and VII dorsal to adjacent spiracles). Raychaudhuri and Roychoudhuri (1978) report the presence of “rhopalosiphine reticulations” on the thorax and abdomen. However, A. craccivora also has reticulations and the lack of accompanying illustrations in the description of R. esculentum leaves it ambiguous as to whether the reticulations are composed of solid lines as in A. craccivora (similar to Fig. 4a, b) or spicules as in Rhopalosiphum (Fig. 4c). Certain characters in the description agree with A. craccivora (e.g. segments I, II, apex of V, and VI dark or dusky, the shape of and imbrications on the siphunculi). Finally, A craccivora is the only aphid species reported to feed on Manihot esculenta Crantz, the reported host plant (Blackman and Eastop 2017), which is native to South America and grown as a food crop in India, where R. esculentum was described. We, therefore, agree that R. esculentum is likely to be a synonym of A. craccivora and do not include it in subsequent analyses. However, as we have not examined the holotype of R. esculentum to confirm our suspicions, we decline to formally synonymize the two species herein.

a

b

c

Figure 4.

Dorsal cuticle.

a: M. pyraria (Passerini, 1861).  
b: R. arundinariae (Tissott, 1933).  
c: R. enigmae Hottes and Frison, 1931.  

Rhopalosiphum momo Shinji, 1922. Halbert and Voegtlin (1998) reported that the description of Rhopaloiphum momo “is suggestive of” R. nymphaeae, but did not formally synonymize the two species. An undated, unattributed translation of the original description is available in the USDA-ARS Systematic Entomology Laboratory library and is reproduced here in full:

(40) Rhopalosiphum momo SHINJI, n. sp. / pp. 791

Characteristics: Body green or pale. Antennae somewhat longer than body, III shorter than IV and V taken together, with 16–18 subcircular sensorial, IV and V subequal in length, the former with one sensorium in the middle and the latter with a subapical one; flagellum of VI about 3 times as long as the base. Antennae as a whole infuscated and each segment has a few hairs. Cornicles with a basal 2/3 part green or pale, the remaining 1/3 part swollen and infuscated.

Host plant: Prumus [sic] persica L.

Date of collection: 2 June 1920

Locality: Miyakonojo, Nakajo (Nagano Pref.)

Rhopalosiphum arundinariae (Tissot, 1933). Halbert and Voegtlin (1998) suggested that R. arundinariae belongs within Melanaphis based on “wing venation [and] cuticular sculpturing” (they also suggested bamboo as a host plant is a Melanaphis but not a Rhopalosiphum characteristic; however, R. chusqueae Pérez Hidalgo and Villalobos Muller, 2012, which feeds on bamboo, was subsequently described and placed unambiguously within Rhopalosiphum based on morphological and molecular characters, thus establishing bamboo-feeding as a Rhopalosiphum characteristic). We agree with Halbert and Voegtlin (1998) and did not include it in the linear discriminant analyses (see Results for additional details).

We were unable to locate apterae of R. cerasifoliae (Fitch, 1855) to include in the analyses. However, we included specimens of the junior synonym R. tahasa Hottes, 1950 in order to understand what might happen when synonymized species do not have a presumed conspecific valid species for comparison.

Results

Morphometric analyses

In the first LDA of apterae, R. maidis and its synonom R. africana (Theobald, 1914) formed a distinct cluster in the plots of LD1 x LD2 and LD1 x LD3 (Fig. 5). Rhopalosiphum nymphaeae L., 1761) and its synonym R. sparganii (Theobald, 1925) formed a distinct cluster in the LD1 x LD2 plot (Fig. 4a) and R. sp. nov. “ex. Arisaema” formed a distinct cluster in the plot of LD1 x LD3 (Fig. 4b). These five species were removed prior to performing the second LDA.

Figure 5.  

Graphs of the first linear discriminant analysis of apterae.

In the second linear discriminant analysis of apterae, R. padi and its synonyms R. prunifoliae (Fitch, 1855) and R. pseudoavenae (Patch, 1917) formed distinct clusters in both the LD1 x LD2 and LD1 x LD3 plots (Fig. 6); Rhopalosiphum tahasa (Hottes, 1950) also clustered with R. padi, although this may be an artifact of the fact that the species with which it is currently synonymized, R. cerasifoliae, was not included in the analyses. In the LD1 x LD2 plot, Rhopalosiphum enigmae and its synonym R. laconae (+ R. chusqueae), R. musae (Schouteden, 1906) and its synonym R. scirpifolii Gillette & Palmer, 1932 and R. nigrum Richards, 1960 all formed distinct clusters. In the LD1 x LD3 plot, Rhopalosiphum rufiabdominale (Sasaki, 1899) and its three synonyms R. gnaphalii Tissot, 1933, R. subterraneum Mason, 1937 and R. splendens (Theobald, 1915) clustered together although there was some overlap of R. splendens with R. enigmae + R. laconae. Rhopalosiphum chusqueae formed a distinct cluster in the LD1 x LD4 plot. Rhopalosiphum parvae Hottes and Frison, 1931 and R. rufulum clustered together in all plots, not forming separate clusters in any plot.

Figure 6.  

Graphs of the second linear discriminant analysis of apterae.

In the first linear discriminant analysis of alatae, R. maidis formed a cluster with its synonyms R. cookii (Essig, 1911) and R. africana and R. nymphaeae clustered with its synonym R. prunaria (Walker, 1848) in the plots of LD1 x LD2 and LD1 x LD3 (Fig. 7). These five species were removed prior to performing the second LDA except for the three most outlying R. africana, which were paratypes.

Figure 7.  

Graphs of the first linear discriminant analysis of alatae.

In the second linear discriminant analysis of alatae, R. rufulum (along with one of the outlier R. africana not removed from the analyses) formed a distinct cluster in the LD1 x LD2 plot (Fig. 8). Rhopalosiphum enigmae and its synonym R. laconae formed a distinct cluster in the LD1 x LD3 plot and were removed prior to performing the third LDA. Rhopalosiphum rufiabdominale and its synonyms R. californica (Essig, 1944), R. splendens (Theobald, 1915), and R. subterraneum Mason, 1937 formed a distinct cluster in the LD1 x LD3 plot with minimal overlap with R. oxyacanthae synonyms and so were also removed prior to the third LDA.

Figure 8.  

Graphs of the second linear discriminant analysis of alatae.

None of the remaining species formed distinct clusters in the third linear discriminant analysis (Fig. 9).

Figure 9.  

Graphs of the third linear discriminant analysis of alatae.

Discussion

Summary

Acknowledgements

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