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Taxonomic Ecology of Geometric Morphometry on Classification and Identification of Sphingid (: ) Xiaoyu Su 1, Xiaona Cai 2, Dazhuang Huang 1* 1 Agricultural University of Hebei, 2596 Lekai South Street, 071000, Baoding, Hebei, P.R. 2 Hebei Finance University, 3188 Hengxiang North Street, 071051, Baoding, Hebei, P.R. CHINA * Corresponding author: [email protected] Abstract The aim of the study was to explore the feasibility of a geometric morphometric method for the ecological classification and identification of moths according to taxonomic ecology. Ten species of Sphingidae were used as examples in this paper. The right forewings from the ten species were used as the research object, and seventeen landmarks in environment were selected for analysis. Two related steps including geometric morphometric analysis and multivariate statistical analysis were carried out. In the first step, Procrustes superimposition was applied to the data of the seventeen environmental landmarks by removing nonshape variation from the landmark coordinates. Using relative warp analysis, relative warp figures and a matrix of relative warp scores were obtained. In the second step, ecological component analysis of the Procrustes- transformed data set was implemented, and three dimensional distribution figures for the ten species of Sphingidae were described on the basis of the first three components. Discriminant analysis was carried out on the relative warp scores matrix, and accuracy of original and cross-validation tests achieved 100% and 99.7%, respectively. The results indicate that geometric morphometric analysis may be used to accurately identify the ten species of Sphingidae, and their can be achieved using relative warp figures. Keywords: taxonomic ecology, Sphingidae species, geometric morphometry, relative warp analysis, identification

Su X, Cai X, Huang D (2018) Taxonomic Ecology of Geometric Morphometry on Classification and Identification of Sphingid Moths (Lepidoptera: Sphingidae). Ekoloji 27(106): 827-835.

INTRODUCTION great impact in reducing the burden of routine Most of of the Sphingidae family are identification. considered pests, which have caused significant damage In the last dozen years or so, taxonomy and and ecological loss to agriculture and forestry. Accurate identification of insects and automatic identification identification of species in environment is the technology have been promoted by the development of basis for pest forecasting and control, and it is needed digital technology of computer imaging and taxonomy for and plant quarantine. However, ecology. Researchers worldwide have been exploring habitat identification still relies mainly on traditional various mathematical methods and have developed methods, which not only requires professional many software applications used for the classification knowledge and extensive experience but also takes too and identification of insects. Houle et al. (2003) much time and is compromised by subjectivity. Thus, developed an automated image analysis system it is a major ecological challenge to develop a strategy to (WINGMACHINE) that could rapidly and with high quickly and effectively extract information from a large repeatability measure the positions of all the veins and number of taxonomy resources with a reduced number the edges of the wing blade of drosophilid flies. The of taxonomists (Gaston and O’Neill 2004). Gaston and research team led by Shen Zuo Rui has successively O’Neill examined some of the reasons why automated developed the softwares Bugvisux1.0 (Yu 1999) and species identification has not become widely applied. BugShape1.0 (Zhang 2006) used to automatically Despite the technical obstacles to be overcome, the identify insects. Tofilski (2004) presented a tool that development of automated species identification holds provides a numerical description of an insect wing and promise that such an approach has potential to make a

© Foundation Environmental Protection & Research-FEPR Received: 16 Jun 2017 / Accepted: 6 Oct 2018

Su et al. enables automatic identification of vein junctions. helps us explore feasibility of geometric morphometry Nikolaou et al. (2010) presented a flexible open source on classification and identification of sphingid moths. software platform, VeSTIS, for training classifiers, which is capable of identifying the taxonomy of a Scale Removal and Digital Vein Imaging specimen from digital images. The wing surface is covered with a large number of scales, which is characteristic of the Lepidoptera. Currently, application of geometric morphometric Therefore, the first step was to remove the scales to method on classification and identification of insects obtain an accurate image of the veins, and this was interest researchers extensively and this method carried out using a chemical immersion method. The provides a powerful tool for studying biological chemicals and tools used included 95% ethanol, classification and phylogenetics. Geometric sodiumhypochlorite, hydrochloric acid (36%–38%), morphometric methods might be used to solve five large petri dishes, medium speed qualitative filter problems in taxonomy, and may be used to visualize key paper, 2 forceps and 2 scissors. differences in shape (Canal et al. 2015, Qubaiová et al. 2015, Rohlf 1998). This method focuses on the Right forewings were first completely removed retention of geometric information throughout a study from the sphingid specimens and were transferred to, and can easily relate extracted characteristics to the and fully soaked in, 70% ethanol solution for at least three minutes for full infiltration into the wings. The physical structure of the original specimens (Slice aim was to remove the scales while maintaining their 2007). The geometric morphometric method has been elasticity to avoid damaging them in the subsequent applied extensively in medicine and other fields (Bookstein et al. 2001, Fruciano et al. 2012, Groning et steps. Forceps were used to transfer the wings from the al. 2011, Marcus et al. 2013, Muschick et al. 2012, Wang ethanol solution to sodium hypochlorite solution for 1– et al. 2017); nevertheless, few examples of its application 3 minutes. The wings were then immersed in the on identification of insects can be found. hydrochloric acid solution for 1–3 minutes. The scales and stripes gradually faded, but the second and third The purpose of this study was to determine the steps were repeated as needed until the veins became feasibility of the geometric morphometric method for clearly discernible clearly. Finally, the wings were the ecological taxonomy and identification of the ten transferred to fresh water and underwent three to four species of Sphingidae. In our study, the right forewings repeated washes in water to remove chemical residues. of ten species of Sphingidae were used as the research Filter paper was used to retrieve the wings from the object given that wing vein is one of the main water, and they were gently pressed flat onto a layer of characteristics used for the identification of insects (Bai filter paper until there was no more flow of water on the et al. 2011, Roggero and d’Entreves 2005), and wing surface. The wing specimens were placed in a dry, homologous landmarks are easy to extract. dark area until analysis.

MATERIALS AND METHODS A Microtek Phantom v900 Plus flatbed scanner with transmission scanning function was used to create the Experimental Materials moth wing vein digital image. The wing specimens A black light lamp was used to capture ten were scanned under 6000 DPI. The images were saved Sphingidae species in Yanqing, Beijing. These species as 8-bit grayscale. are considered to be the main pests for agriculture and forestry and include Herse convolvuli (Linnaeus), Geometric Morphometry Callambulyx tatarinovi (Bremer et Grey), Smerithus planus Selection and Digitalization of Landmarks. planus Walker, Clanis deucalion (Walker), Amorpha The landmarks refer to the obvious and easily amurensis Staudinger, Marumba gaschkewitschi recognizable points, which can be identified in gaschkewitschi (Bremer et Grey), Pergesa elpenor lewisi organisms and be designated by name. The landmarks (Butler), Celerio gallii (Rottemburg), Theretra japonica must, of course, indicate the location of the same (Orza), rubiginosa rubiginosa Bremer et anatomical feature across different specimens (Rohlf, Grey. Thirty right forewing samples were collected 1998), and how the points are selected is very important from each species. The ten species of sphingidae are to the analysis results. Landmarks can be broadly common and topological structures among veins are divided into three categories in their application to very similar. Geometric morphometry focuses on biology (Bookstein 1985, 1991)： Landmark I refers to topological structure of biology morphology, which a kind of mathematical point between species that has

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Fig. 1. Right forewing image of Celerio gallii individual with seventeen landmarks used in the geometric morphometricanalysis (1–7, junctions of veins of cell wing begin with the basal junction of veins R1 with clockwise direction; 8, junction of vein R4 and R5; 9, basal junction of anal vein A2 and A3; 10–17, junctions of outer margin from termination of vein R4 to A2. strong evidence to support the homology, such as Procrustes superimposition, the difference in junction and termination of wing vein. Landmark II corresponding landmarks among various species can be represents a kind of mathematical points between used to describe the morphological distinctions among species with homology supported only by geometry species. rather than histology, such as concave or convex point The relative warp scores in the structure, the salient points of genitalia, and other Relative Warp Analysis. matrix was obtained by relative warp analysis of conspicuous points for description. Landmark III landmark data of the consensus configuration indicates that the point has at least one defective corresponding to ten species of sphinx forewing using coordinate such as both ends of the longest diameter or tpsRelw software, and orthogonal alignment projection recessed bottom. The junction and termination of the is implemented to the matrix. To explore the wing vein, which are Landmark I and II characteristics, deformations associated with different positions of respectively, were applied in this paper. points in the space spanned by the displayed pair of The first step in the identification procedure was to relative warps, the corresponding ten species of sphinx prepare an initial tps file that simply provided a list of average landmark configurations (Fig. 2) was given. the images to be processed (the ID, COMMENT, and The ten plots show the shape change as a deformation VARIABLES fields can also be included if desired). The (the default mode), and a sequence of points can be easiest way to build this initial file was to use the tpsUtil visualized. These plots were used to visualize the shape software. Locations of the landmarks were then deformations of the right forewing of ten species of digitized using the tpsDig software; 17 landmarks on sphinx. Singular values and percent explained for the right forewings were manually located at the relative warps are shown in Table 1. The first two intersections of the wing veins in sequence and percent explained got up to 70.39% of the relative warps, consisted of x, y coordinates (Fig. 1). which was useful for average landmark configurations (Fig. 2). Procrustes Superimposition. Landmark coordinates can be used in many statistical analysis and geometric morphometric analysis. However, the initial coordinate values contains a number of nonshape factors such as the location and direction of the specimen, coordinate selection (origin, scale) and size. The purpose of Procrustes superimposition analysis is to remove nonshape variation from the landmark coordinates (Rohlf 1990, 1999). It can be accomplished through centered, rotated, and scaled operations carried out by tpsSuper software. Thus, redundant information mentioned above was eliminated, and information regarding the desired shape was obtained. After

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Fig. 2. Map of OMU Pond I and sampling station (Anonymous 1975)

Table 1. Singular values and percent explained for relative warps No. of relative Singular Percent No. of relative Singular Percent Cumulative % Cumulative % warps Values Explained warps Values Explained 1 0.789 41.21 41.21 16 0.063 0.26 98.73 2 0.664 29.18 70.39 17 0.060 0.24 98.97 3 0.369 9.03 79.41 18 0.055 0.2 99.17 4 0.291 5.61 85.02 19 0.044 0.13 99.3 5 0.238 3.73 88.76 20 0.042 0.12 99.42 6 0.196 2.54 91.3 21 0.040 0.11 99.52 7 0.176 2.05 93.35 22 0.038 0.09 99.62 8 0.152 1.52 94.86 23 0.037 0.09 99.71 9 0.118 0.92 95.78 24 0.033 0.07 99.78 10 0.099 0.65 96.43 25 0.029 0.06 99.84 11 0.090 0.53 96.96 26 0.026 0.05 99.88 12 0.081 0.43 97.4 27 0.025 0.04 99.92 13 0.080 0.42 97.82 28 0.023 0.03 99.96 14 0.072 0.34 98.16 29 0.019 0.02 99.98 15 0.069 0.31 98.47 30 0.018 0.02 100

RESULTS principal component variates (Fig. 3), samples clustered Principal Component Analysis. Principal into species groups very well. component analysis on the Procrustes-transformed data Discriminant Analysis. The relative warp analysis set subsequently resulted in 34 principal component on tps file was applied to obtain relative warp scores variates (PCVs) (Table 2). It was easily shown that the matrix, which could be used as parameters of first three components explained 97.66% of the classification identification by the tpsRelw software. variation. The first three PCVs were graphically The tps file contained landmark data of ten species of represented for each of the ten sample groups (Fig. 3). Sphingidae, totally 300 samples. Based on the graphical presentation of the first three

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Table 2. Variance cumulative of every principal component variate Initial Eigenvalues Extraction Sums of Squared Loadings Component Total % of Variance Cumulative % Total % of Variance Cumulative % 1 29.244 86.0 86.0 29.244 86.0 86.0 2 3.265 9.6 95.6 3.265 9.6 95.6 3 0.695 2.0 97.7 0.695 2.0 97.7 4 0.267 0.8 98.4 0.267 0.8 98.4 5 0.249 0.7 99.2 0.249 0.7 99.2 6 0.080 0.2 99.4 0.080 0.2 99.4 … … … … … … … 34 0.000 0.0 100.0 0.000 0.0 100.0

Fig. 3. Distribution of the ten different species of Sphingidae. The first three principal component variates as coordinate axis produced from principal component analysis on Procrustes coordinate data based on seventeen forewing landmarks from all sphinx individuals

Table 3. Eigenvalues and variancecontribution of the nine unstandardized canonical discriminant functions produced following discriminant analysis Function Eigenvalue % of Variance Cumulative % Canonical Correlation 1 25.072 51.3 51.3 0.981 2 7.066 14.4 65.7 0.936 3 6.172 12.6 78.3 0.928 4 3.225 6.6 84.9 0.874 5 3.142 6.4 91.4 0.871 6 1.889 3.9 95.2 0.809 7 1.302 2.7 97.9 0.752 8 0.706 1.4 99.3 0.643 9 0.326 0.7 100.0 0.496

A discriminant analysis was carried out on relative was completely correct, and only one, T. japonica,was warp scores matrix using SPSS 13.0 software. wrongly identified asP. elpenor lewisibased on cross Eigenvalues and cumulative variance efficacy (Table 3) analysis. The results demonstrate that relative warp could be generated by the analysis. The first five scores were valuable for the identification of insect functions already provided 91.4% cumulative efficacy species. for the analysis (Table 3). This result indicates that these functions could explain the difference of 91.4% DISCUSSION and could lead to accurate discrimination between the The results obtained from the relative warps of a ten insect species. total of 17 landmarks on the right forewing demonstrate that these parameters successfully fulfilled our intended Original and cross-validation tests based on purpose as a means of identifying ten species of discriminant functions correctly identified 100% and Sphingidae. It has shown that relative warp parameters 99.7% of the species, respectively (Table 4). It showed could be used to rapidly identify moths and would be that the classification results based on original analysis

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Table 4. Original and cross-validation resultsa,b for all individuals of the ten sphinx species, based on the discriminant functions and group centroids for relative warp parameters of all species Predicted Group Membership Genus. Species 1 2 3 4 5 6 7 8 9 10 Total % Corrected Original Herse convolvuli 1 30 0 0 0 0 0 0 0 0 0 30 100 Pergesa elpenor lewisi 2 0 30 0 0 0 0 0 0 0 0 30 100 Amorpha amurensis 3 0 0 30 0 0 0 0 0 0 0 30 100 Smerithus planus planus 4 0 0 0 30 0 0 0 0 0 0 30 100 Ampelophaga rubiginosa rubiginos 5 0 0 0 0 30 0 0 0 0 0 30 100 Theretra japonica 6 0 0 0 0 0 30 0 0 0 0 30 100 Celerio gallii 7 0 0 0 0 0 0 30 0 0 0 30 100 Clanis deucalion 8 0 0 0 0 0 0 0 30 0 0 30 100 Callambulyx tatarinovi 9 0 0 0 0 0 0 0 0 30 0 30 100 Marumba gaschkewitschi gaschkewitschi 10 0 0 0 0 0 0 0 0 0 30 30 100 Cross-validatedc Herse convolvuli 1 30 0 0 0 0 0 0 0 0 0 30 100 Pergesa elpenor lewisi 2 0 30 0 0 0 0 0 0 0 0 30 100 Amorpha amurensis 3 0 0 30 0 0 0 0 0 0 0 30 100 Smerithus planus planus 4 0 0 0 30 0 0 0 0 0 0 30 100 Ampelophaga rubiginosa rubiginos 5 0 0 0 0 30 0 0 0 0 0 30 100 Theretra japonica 6 0 1 0 0 0 29 0 0 0 0 30 96.67 Celerio gallii 7 0 0 0 0 0 0 30 0 0 0 30 100 Clanis deucalion 8 0 0 0 0 0 0 0 30 0 0 30 100 Callambulyx tatarinovi 9 0 0 0 0 0 0 0 0 30 0 30 100 Marumba gaschkewitschi gaschkewitschi 10 0 0 0 0 0 0 0 0 0 30 30 100 a 100.0% of original grouped cases correctly classified. b 99.7% of cross-validated grouped cases correctly classified. c Cross-validation is done only for those cases in the analysis. In cross-validation, each case is classified by the functions derived from all cases other than that case. useful for the automatic recognition of moths in the Because the wing surface of moths is covered with a future. In this paper, only ten species were used as large number of scales, it is difficult to study vein samples to test the feasibility of a geometric characteristics by a geometric morphometric method. morphometric method for classification and Further, it is challenging to perform the de-scaling identification of Sphingidae. In future research and process for smaller and thinner wings. Solutions to development of this method, more species would be resolve this issue must be explored so that the added in the discriminating groups, and other junctions characteristics of wing veins can be applied for the of veins might also play a very significant role in the classification and identification for more species of process of identification. Moreover, other parts of the moths. moth such as the underwing, head, mesonotum, and abdomen could additionally be utilized to select The location of extracted landmarks require clear landmarks. anatomical characteristics; however, many biological structures lack clear positioning points. To solve the The patterns of the landmark coordinates after problem, Bookstein (1996, 1997) has presented the Procrustes superimposition were studied with principle concept of “semilandmark” and applied a sliding component analysis (PCA). The extracted first three technique in the process of extracting semilandmark PCVs from our analysis had a clear geometric data. The sliding technique defines how semilandmarks explanation in the ten species of Sphingidae. Fig. 3, in could slide so as to minimize bending energy particular, obtained from the PCA with the first three (Bookstein 1996, Sheets et al. 2004) during a generalized PCVs supports our conclusion (Table 4) from Procrustes analysis superimposition or in the Procrustes discriminant analysis; that is, geometric morphometric distance between two landmarks. One can draw links analyses demonstrate the capacity to identify the ten between any triplets of landmarks, the middle landmark species of Sphingidae. The method provides a of a triplet is then considered a semilandmark, and it promising opportunity to quickly and relatively easily will be allowed to slide in a direction parallel to the identify the morphology of insects and has the potential difference between the other two landmarks. The for use as a rapid identification tool given a broader, semilandmark with sliding is the same as landmark in more comprehensive dataset. statistics, and can reflect the specimen shape correctly (Zelditch et al., 2004; Slice, 2005). Although we did not

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Taxonomic Ecology of Geometric Morphometry on Classification and Identification of Sphingid Moths … use sliding semilandmarks, it would play a very useful for the automatic recognition of moths in the important role in entomology by strengthening the future. In this paper, only ten species were used as application of this technology in research and by samples to test the feasibility of a geometric increasing the opportunity to identify a greater number morphometric method for classification and of species. identification of Sphingidae. In future research and development of this method, more species would be The application of geometric morphometrics in added in the discriminating groups, and other junctions entomology is increasingly expanding. Geometric of veins might also play a very significant role in the morphometrics not only has important application for process of identification. Moreover, other parts of the insect identification but also provides a convenient way moth such as the underwing, head, mesonotum, and to study phylogeny (Güler 2006), the division of sibling abdomen could additionally be utilized to select species (Villemant 2007), the division of disputed landmarks. species (Prieto, 2009), or fluctuating asymmetry (Klingenberg, 2003). For instance, molecular biology is The patterns of the landmark coordinates after the most commonly used method to the study insect Procrustes superimposition were studied with principle phylogenetics, for which geometric characteristics with component analysis (PCA). The extracted first three homology can also be used. Compared with molecular PCVs from our analysis had a clear geometric biology, the latter can improve efficiency and save explanation in the ten species of Sphingidae. Fig. 3, in manpower, funds and so on. Geometric morphometry particular, obtained from the PCA with the first three will have better application prospects in insect PCVs supports our conclusion (Table 4) from taxonomy and may have expanded application in discriminant analysis; that is, geometric morphometric various fields concurrent with increased knowledge of analyses demonstrate the capacity to identify the ten insect species, improvement in technology, and species of Sphingidae. The method provides a intensive study of relevant professionals and scholars. promising opportunity to quickly and relatively easily identify the morphology of insects and has the potential At present, published research results preferentially for use as a rapid identification tool given a broader, address only two-dimensional (2D) form, and three- more comprehensive dataset. dimensional (3D) images are largely constrained in publication (Adams 2004). Moreover, the application of Because the wing surface of moths is covered with a 3D data is not as extensive as 2D data, and there will be large number of scales, it is difficult to study vein higher requirements for 3D data acquisition equipment characteristics by a geometric morphometric method. and higher costs. However, the extension from 2D to Further, it is challenging to perform the de-scaling 3D analysis has been available in principle for many process for smaller and thinner wings. Solutions to years, and the use of 3D landmarks is becoming resolve this issue must be explored so that the standard practice in fields such as biomedical science. characteristics of wing veins can be applied for the The problem of how to sufficiently characterize relative classification and identification for more species of amounts and directions of variation of individual moths. landmarks is of interest to many researchers, especially those utilizing Procrustes analyses of 3D coordinates The location of extracted landmarks require clear (Strauss 2010). The research of geometric morphology anatomical characteristics; however, many biological may gradually transfer to 3D data from 2D data with the structures lack clear positioning points. To solve the development of biological imaging and electronic problem, Bookstein (1996, 1997) has presented the science and technology, and the continuous concept of “semilandmark” and applied a sliding improvement of computer capacity of processing mass technique in the process of extracting semilandmark data. data. The sliding technique defines how semilandmarks could slide so as to minimize bending energy DISCUSSION (Bookstein 1996, Sheets et al. 2004) during a generalized The results obtained from the relative warps of a Procrustes analysis superimposition or in the Procrustes total of 17 landmarks on the right forewing demonstrate distance between two landmarks. One can draw links that these parameters successfully fulfilled our intended between any triplets of landmarks, the middle landmark purpose as a means of identifying ten species of of a triplet is then considered a semilandmark, and it Sphingidae. It has shown that relative warp parameters will be allowed to slide in a direction parallel to the could be used to rapidly identify moths and would be difference between the other two landmarks. The

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Su et al. semilandmark with sliding is the same as landmark in At present, published research results preferentially statistics, and can reflect the specimen shape correctly address only two-dimensional (2D) form, and three- (Slice 2005, Zelditch et al. 2004). Although we did not dimensional (3D) images are largely constrained in use sliding semilandmarks, it would play a very publication (Adams 2004). Moreover, the application of important role in entomology by strengthening the 3D data is not as extensive as 2D data, and there will be application of this technology in research and by higher requirements for 3D data acquisition equipment increasing the opportunity to identify a greater number and higher costs. However, the extension from 2D to of species. 3D analysis has been available in principle for many years, and the use of 3D landmarks is becoming The application of geometric morphometrics in standard practice in fields such as biomedical science. entomology is increasingly expanding. Geometric The problem of how to sufficiently characterize relative morphometrics not only has important application for amounts and directions of variation of individual insect identification but also provides a convenient way landmarks is of interest to many researchers, especially to study phylogeny (Güler 2006), the division of sibling those utilizing Procrustes analyses of 3D coordinates species (Villemant 2007), the division of disputed (Strauss 2010). The research of geometric morphology species (Prieto 2009), or fluctuating asymmetry may gradually transfer to 3D data from 2D data with the (Klingenberg 2003). For instance, molecular biology is development of biological imaging and electronic the most commonly used method to the study insect science and technology, and the continuous phylogenetics, for which geometric characteristics with improvement of computer capacity of processing mass homology can also be used. Compared with molecular data. biology, the latter can improve efficiency and save manpower, funds and so on. Geometric morphometry ACKNOWLEDGEMENTS will have better application prospects in insect This paper belongs to the project of the “Hebei taxonomy and may have expanded application in Province Department of Education Project”, various fields concurrent with increased knowledge of No.QN2017077; Mathematical morphological insect species, improvement in technology, and characteristics of nocturnal pests in Hebei province and intensive study of relevant professionals and scholars. basic research on Digitalized identification.

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