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Geographic Distribution and Niche Divergence of Two Stink- Bugs, Parastrachia Japonensis and Parastrachia Nagaensis

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Geographic Distribution and Niche Divergence of Two Stink- Bugs, Parastrachia Japonensis and Parastrachia Nagaensis Journal of Insect Science: Vol. 13 | Article 102 Zhu et al. Geographic distribution and niche divergence of two stink- bugs, Parastrachia japonensis and Parastrachia nagaensis Gengping Zhu1a*, Guoqing Liu2b, Wenjun Bu2c, Jerzy A. Lis3d 1Tianjin Key Laboratory of Animal and Plant Resistance, College of Life Sciences, Tianjin Normal University, Tianjin 300387, China 2Institute of Entomology, College of Life Sciences, Nankai University, Tianjin 300071, China 3Department of Biosystematics, Opole University, Oleska 22, 45-052 Opole, Poland Abstract Parastrachiidae is a small stinkbug family containing only one genus and two species, Parastra- chia japonensis (Scott) (Hemiptera: Heteroptera: Pentatomoidea) and Parastrachia nagaensis Distant. The geographic distribution of the genus has been poorly studied. Niche conservatism refers to that idea that closely related species are more ecologically similar than would be ex- pected, whereas niche divergence predicts they occupy distinct niche spaces. The existence of only two species within one genus suggests niche conservatism or differentiation might exist among them. Herein, the distribution of the genus was mapped, potential distributions were pre- dicted using ecological niche modeling, and climate spaces occupied by the two species were identified and compared. Our outlined map supports the general spreading route proposed by Schaefer et al. The potential distributions suggest that the genus’ range could extend beyond its presently known distribution, and further investigation into this area could aid in their conserva- tion, particularly P. nagaensis. The niche space inferred by ecological niche modeling suggests the two species do not occupy identical habitat, but the differences between their models could simply be due to the differential availability of habitat in the different regions that they occupy. Keywords: ecological niche, ecological niche modeling, potential distribution, principle component analysis Abbreviations: AUC, area under the curve; ENM, ecological niche modeling, PCA, principal component analysis Correspondence: a [email protected], b [email protected], c [email protected], d [email protected], *Corresponding author Editor: Robert Jetton was editor of this paper. Received: 3 February 2012 Accepted: 5 October 2013 Published: 5 October 2013 Copyright: This is an open access paper. We use the Creative Commons Attribution 3.0 license that permits unrestricted use, provided that the paper is properly attributed. ISSN: 1536-2442 | Vol. 13, Number 102 Cite this paper as: Zhu G, Liu G, Bu W, Lis JA. 2013. Geographic distribution and niche divergence of two stinkbugs, Parastrachia japonensis and Parastrachia nagaensis. Journal of Insect Science 13:102. Available online: http://www.insectscience.org/13.102 Journal of Insect Science | http://www.insectscience.org 1 Journal of Insect Science: Vol. 13 | Article 102 Zhu et al. Introduction Sigwalt and Lis 2008; Lis and Ziaja 2010). However, the geographic distribution of the It is widely accepted that ecology plays an genus throughout the world, and especially in important role in speciation (Rice et al. 2003; China, has been poorly studied (Schaefer et al. Rissler and Apodaca 2007; Pyron and Bur- 1988; Schaefer and Kikuhara 2007). The fact brink 2009). Generally, the speciation event that there are only two species within one ge- takes place in geographic dimensions and may nus suggests niche conservatism or not be accompanied by ecological innovation differentiation might exist among them. (Peterson et al. 1999; Pyron and Burbrink 2009; McCormack et al. 2010; Peterson Principle component analysis (PCA) and eco- 2011). When populations enter into a new en- logical niche modeling (ENM) are two vironment, however, the ecological niche of a approaches that have been widely used to species might diverge to adapt to the novel study niche conservatism and differentiation environment, and subsequent natural selection (Broennimann et al. 2007; Fitzpatrick et al. might promote this process and facilitate spe- 2007; Warren et al. 2008; Rödder and Lötters ciation (Graham et al. 2004; Wiens and 2009; McCormack et al. 2010; Medley 2010; Graham 2005; Sánchez-Fernández et al. Zhu et al. 2012). PCA uses pooled environ- 2011). Ecological niche differences among mental variables associated with species different species can be visualized and ana- occurrence to reveal reduced significant com- lyzed to assess the likely ecological and ponents that account for the observed evolutionary forces that shape the species’ distribution. The defining niche space of re- geographical distributions and habitat prefer- duced dimension allows investigation of niche ences (Graham et al. 2004; Wiens and conservatism and differentiation. ENM seeks Graham 2005; Raxworthy et al. 2007; to characterize environmental conditions that Sánchez-Fernández et al. 2011). are suitable for the species, and then to identi- fy where suitable environments are distributed Parastrachiidae is a small stinkbug family spatially (Pearson 2007). ENM has been wide- containing only one genus and two species, ly used in biological responses to climate Parastrachia japonensis (Scott) (Hemiptera: change, setting conservation priorities, and the Heteroptera: Pentatomoidea) and Parastra- study of evolutionary biology (Guisan and chia nagaensis Distant. The genus has Thuiller 2005; Raxworthy et al. 2007; Rissler attracted the attention of some heteropterists and Apodaca 2007; Martínez-Gordillo et al. due to its unstable position in Pentatomoidea 2010). (i.e., in different families or subfamilies) (Goel and Schaefer 1970; Schaefer et al. In this study, the global distribution of the ge- 1988; Gapud 1991; Hasan and Kitching 1993; nus was mapped with many records, Hasan and Nasreen 1994; Schuh and Slater especially in China, potential distributions 1995), and the maternal care behavior of P. were predicted using ENM, and niche spaces japonensis (Tsukamoto et al. 1994; Filippi et occupied by the two species were identified al. 1995a, b, 2000a, b, 2001; Nomakuchi et al. and compared using PCA and ENM. The eco- 1998, 2001; Hironaka et al. 2003a, b, 2005, logical niche of a species here can be defined 2007). The genus was raised to the family lev- as “a set of environmental conditions under el (Sweet and Schaefer 2002), which was which it is able to maintain populations with- widely accepted (Grazia et al. 2008; Pluot- out immigrational subsidy” (Grinnell 1917, Journal of Insect Science | http://www.insectscience.org 2 Journal of Insect Science: Vol. 13 | Article 102 Zhu et al. Table 1. Principal components analysis of 13 environmental vari- climatic variables were chosen. Among the ables associated with occurrences of the genus Parastrachia, variables, 6 (i.e., BIO 1, 5, 6, 12, 13, 14) were eigenvalues for significant variables (> 0.8) are in bold. summarizing aspects of temperature and pre- cipitation and were obtained from WorldClim (Hijmans et al. 2005), and 3 (i.e., BIO 20, 21, 22) were summarizing aspects of radiation from CliMond (Kriticos et al. 2011). Topog- raphy variables represented by elevation, slope, aspect, and compound topographic in- dex were derived from the US Geological Survey’s HYDRO1k Elevation Derivative Da- tabase (USGS 2001). Variables at a resolution of 2.5 min were used for model calibration. Principle component analysis 1924). This study also highlighted the correla- PCA was used to explore significant variables tive approach for biodiversity conservation, that related to the genus’distribution and to especially for the localized endemic species. compare niche spaces occupied by the 2 spe- cies. After superimposing the occurrence data Materials and Methods on bioclimate and topography grids, values for each record were extracted in ArcGIS 10. A Occurrence data correlation matrix of 40 × 13 was prepared for Occurrence records were assembled from ex- the PCA performed in SPSS 19 (IBM 2009). isting literature (Tsukamoto and Tojo 1992; To facilitate data visualization, the occurrence Hironaka et al. 2003a; Schaefer and Kikuhara records were pooled for P. nagaensis and P. 2007; Hosokawa et al. 2010) and our speci- japonensis respectively. mens (see Supplementary Figure 1). Localities were georeferenced in Google Maps Ecological niche modeling (http://maps.google.com), Gazetteer of China A wide range of methods have been explored (1997), or BioGeomancer for ENM. Among them, the maximum entro- (http://bg.berkeley.edu/latest/), then mapped py algorithm implemented in the Maxent in ArcGIS 10 (ESRI 2006). A total of 34 and software (Phillips et al. 2004, 2006; Elith et al. 6 occurrence records were prepared for P. ja- 2011) generally performs better than other ponensis and P. nagaensis respectively. algorithms (Elith et al. 2006; Phillips et al. 2006; Ortega-Huerta and Peterson 2008). Environmental variables Maximum entropy is a machine-learning Environmental variables were selected by technique that predicts species distributions by considering climate and topography factors using detailed environmental variables associ- that might affect the genus’ distribution (Tsu- ated with species occurrence. It follows the kamoto et al. 1994; Filippi et al. 1995a, b, principle of maximum entropy and spreads 2000a, b, 2001; Nomakuchi et al. 1998, 2001; out probability as uniformly as possible, but Hironaka et al. 2003a, b, 2005, 2007) (Table subject to the caveat that they must match 1). Annual trends and extreme or limiting bio- empirical information such as known
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