Skip to content

Advertisement

  • Research
  • Open Access

Unraveling the diversity, phylogeny, and ecological role of cryptic Coleopteran species of Vadodara district: a first comparative approach from India

The Journal of Basic and Applied Zoology201879:53

https://doi.org/10.1186/s41936-018-0062-2

  • Received: 28 February 2018
  • Accepted: 5 November 2018
  • Published:

Abstract

Background

More than 350 K described species, Coleoptera (beetles) represent the most diverse order from Class Insecta in the entire animal kingdom. However, their phylogeny is highly controversial due to their morphological crypticness and multiple markers used previously for sequence homology. Although many studies suggest that their diversity currently relies majorly on morphological analysis, nevertheless DNA barcodes may provide a functional, standardized tool for their unique identification. In the present report, a fragment of the mitochondrial cytochrome c oxidase I (COI) gene has been proposed as standard DNA barcoding marker for the identification of organisms.

Result

To evaluate this hypothesis, a random sampling was conducted in and around Vadodara, Gujarat, where 2690 individual of 65 species belonging to 16 families were reported from different sites, and diversity indices were employed to unravel the species composition of that habitat. Further, 12 beetles from dominant families were selected for sequence analysis using various bioinformatics tools and were compared with the rest of the beetles to obtain a more robust phylogeny which is not reported earlier in previous studies.

Conclusion

Hence, the present study suggests that Scarabaeidae tends to be more diverse in and nearby of Vadodara compared to all other families of Coleoptera and while in contrast Chrysomelidae showed maximum diversity of pest species. DNA barcoding and nucleotide analysis resolves the phylogeny of controversial taxa; (Adephaga(Gyrinidae+ (Dytiscidae++ Carabidae)) (Polyphaga(Histeridae+Buprestidae+Lampyridae+Elateridae+(Scarabaeidae+(Coccinelidae+ Apionidae+Curculionidae+ (Meloidae+Tenebrionidae+(Cerambycidae+Chrysomelidae)))))).

Keywords

  • Coleoptera
  • Phylogeny
  • DNA-barcoding
  • Sequence
  • Vadodara
  • Cryptic

Background

Insects comprise the most diverse and successful group of multicellular organisms on the planet, and they contribute significantly to vital ecological functions such as pollination, pest control, decomposition, and maintenance of wildlife species (Losey and Vaughan, 2006). The composition of this group reflects the dynamicity of the ecosystem (Fagundes et al. 2011) and is fundamental in the investigating of the landscape structure. An approximation of 350,000 species of beetles that is identified which comprise about 40% of all insects and 30% of all animals out of which 15,088 are reported from India (Choate, 2001; Kazmi and Ramamurthy, 2004). Beetles comprise of 25% of all described species (Hunt et al. 2007).

The Coleoptera can be found in nearly all natural habitats, that is, vegetative foliage, from trees and their bark to flowers, leaves, and underground near roots, even inside plant tissue like galls, tissue, including dead or decaying ones (Gullan and Cranston, 2010). About three fourth of beetle species are phytophagous in both the larval and adult stages, living in or on plants, wood, fungi, and a variety of stored products, including cereals, tobacco, and dried fruits (Gillott, 2005). Many of the beetles are considered as pest (Banerjee, 2014); they are also beneficial, acting as predators by controlling the populations of pests (Davis et al. 2001; Shearin et al. 2007; Brown et al. 2010). Some are bio-control agents for, e.g., dung beetles have been successfully used to reduce the populations of certain pestilent flies and parasitic worms that breed in cattle dung (Brown et al. 2010; Kakkar and Gupta, 2010), and they also prompt a series of ecosystem functions ranging from secondary seed dispersal to nutrient cycling and parasite suppression (Nichols et al. 2009), forest disruptions (Davis et al. 2001) and shaping the landscape structure. (Büchs, 2003).

Routine identification based on morphological characters are sometimes difficult and time-consuming if the specimen is damaged or is an immature stage of development, even specialist may be unable to make identification. However, barcoding solves these problems and serves a dual purpose as a new tool in the taxonomists’ toolbox supplementing their traditional knowledge as well as being an innovative device. (Valentini et al. 2008). The DNA barcoding are of high value which helps in obtaining more detailed analysis of the species, broadening our understanding of both phylogenetic signal and population-level variation. (Hajibabaei et al. 2007). In this context, the use of DNA sequences represents a promising and effective tool for fast and accurate species identification. Further, DNA barcoding shares an emphasis on large-scale genetic data acquisition that offers new answers to questions previously beyond the reach of traditional disciplines. It consists of a standardized short sequence of DNA that can be easily generated and characterized for all species on the planet (Koch, 2010).

Globally, Coleoptera is the largest order among insects in terms of described species diversity (Foottit and Adler, 2009). Despite “the Creator’s inordinate fondness for beetles” (Puspitasari, 2016), Coleoptera has not been favored to date by barcodes. For example, using the public data portal available through BOLD v.4, there were only 23,000 public barcode records for beetles forming 32,758 BIN’S from 159 countries. By comparison, the others of the top four most diverse insect orders are represented by approximately 2.5-fold (Hymenoptera), 3.5-fold (Diptera), and 8.5-fold (Lepidoptera). Moreover, several important studies on genetic variability within and between beetle species have largely employed genetic regions other than the standard animal barcode region (Bergsten et al. 2012). Thus, the DNA barcoding of Coleoptera is still in its infancy, especially when considering their known (Foottit and Adler, 2009) and projected (Odegaard, 2000) global diversity.

Diversity of Coleoptera based on their morphological characters in Gujarat has been reported earlier from Shoolpaneshwar sanctuary (Pilo et al. 1996); from Gir PA, (Parikh, 2001) from Vadodara district, (Naidu and Kumar, 2011), and from Gujarat (Thakkar and Parikh, 2016), if the identification of beetles with DNA barcodes are concerned, no studies have been reported for Vadodara district till date. Moreover, studies linking the diversity and ecological status (pest and beneficial) are scarce. Hence, the present study aims to find the diversity and classify beetles with the help of DNA barcode approach in agriculture field of Vadodara district.

Materials and methods

Site selection and insect collection

Vadodara was surveyed and a total of 20 sites were visited monthly without any habitat bias keeping agricultural fields common in each (Fig. 1). They were collected by standard collecting methods, viz. hand-picking, light trap, net-sweeping, and pitfall trap. In addition, visual sighting and photo documentation were also carried out. Following the standard protocols of pinning each specimen was pinned for further identification. Identification was done by using standard reference books and published articles according to their morphological traits till species level or morphospecies. The species identified were confirmed by comparing with the authentic specimens from the repository at Department of Zoology, Faculty of Science, The Maharaja Sayajirao University of Baroda.
Fig. 1
Fig. 1

A district map of Vadodara with its latitudinal (22.310696) and longitudinal (73.192635) extents, where only the dominant and selected families are shown in particular area of it

Isolation of DNA, PCR, and sequencing

For DNA isolation, the protocol from Silveira et al. (1998) was followed by required modification. The procedure used was as follows: muscles were removed from the thoracic and abdominal region and were homogenized with lysis buffer (0.4 M NaCl, 10 mM Tris-HCl pH 8.0, 2 mM EDTA pH 8.0, containing proteinase k, and 2% SLS). Then, the homogenate was incubated at 60 °C for 1 h, later 6 M NaCl was added to the suspension and vortexed for 1 min, followed by centrifugation at 14,000 rpm for 20 min. The supernatant was removed, and an equal amount of isopropanol was added (1:1) and was further incubated at − 20 °C for 1 h followed by next cycle of centrifugation at 14,000 rpm for 20 min. The obtained pellet was washed with 70% ethanol and kept in 25 μl of milliQ water at − 20 °C condition for further process. The integrity of DNA was checked by using 0.8% Agarose using gel electrophoresis. Quantification of DNA was done by calculating the ratio of optical density obtained at 260/280 nm. The DNA product was then amplified in PCR at 94 °C denaturation for 1 min, 45 °C annealing for 1:30 min and50 °C for 1:30 min, and extension was carried out 72 °C for 7 min. A total of 35 cycles were performed using primers LCO-1490 5′GTCAACAAATCATAAAGATATTGG-3′, HCO2198–5′TAAACTTCAGGGTGACCAAAAAATCA-3′ (Folmer et al. 1994). The amplified product was purified using the thermos-Exosap kit (cat. no. 78200.200.UL.), and sequencing steps were performed according to Yuan et al. (2015a, b).

Data analysis

The diversity indices like Shannon diversity indices, Pielou’s evenness, and Margalef’s richness were calculated by PAST 3.X software.

Sequence validation and bioinformatics analysis

The sequence was validated and specific contigs of 12 beetles were obtained using BioEdit 7.0.5.3.

Further, the sequence was submitted to BOLD v.4 having process Id as given in Additional file 1: Table S1 and barcode gap analysis (Additional file 2: Table S2) was performed to find out the distance from the nearest neighbor. To have a holistic approach, COI sequences of 43 beetles were downloaded from NCBI as given in (Additional file 2: Table S2). Nucleotide composition and codon usage of all the beetles was determined using the MEGA7 software. The sequence was subjected to strand asymmetric analysis which was calculated using the formula(s)

AT-skew = (A−T)/(A + T), GC skew = (G−C)/(G + C).

Taxa selection and phylogenetic analysis

Among all the families reported Scarabaeidae, Carabidae, and Tenebrionidae species were selected due to their abundance. Chrysomelidae and Cerambycidae, due to their pest status, on the other hand, Lampyridae and Gyrinidae were selected due to its sparse availability and only representative of water beetle respectively. Hence, a total 65 individuals belonging to 16 families found in the present study, from which 56 species were selected for phylogenetic tree analysis. Furthermore, it was subjected to tree construction using statistical neighborhood joining distance where the test of phylogeny was performed using the bootstrap method with 500 replicates and was subjected to nucleotide type substitution. The maximum composite likelihood method and Gamma rate (G) were used to assess the diversity, and complete deletion was applied to obtain the complete sequence. This was accomplished through phyloT and was viewed in interactive Tree of life (iTOL) and re-confirmed in MEGA7 software.

Results

Diversity, pest-status, and indices

During the present survey, 2690 individuals representing 65 species, belonging to 16 families of Coleoptera were recorded. Annotated checklist and pest statuses of recorded species are represented in Table 1. Of the total 16 families, Scarabaeidae was found to be the most dominant with 18 representatives, followed by Carabidae with 9 species; Chrysomelidae with 8 species, followed by Cerambycidae having 5 species. Tenebrionidae, Meloidae, and Coccinellidae were represented by four species and Elateridae with three species. Only two representatives were from Dytiscidae and Curculionidae. Families Gyrinidae, Buprestidae, Histeridae, Apionidae, Cicindelidae, and Lampyridae were represented by only one species each.
Table 1

Annotated checklist and pest status of Coleoptera of Vadodara, Gujarat, India

Family

Species

Pest status

Importance

Scarabaeidae

Oxycetonia versicolor

Yes

Pest of pigeon pea, mung beans, and rose

Phyllophaga sp.

Yes

Pest of grasses and cereal roots

Onthophagus gazella

No

Pest predator

Oryctes nasicora

Yes

Pest of coconut

Xyloryctes jamaicensis

Yes

Pest of coconut

Aphodius fossor

No

Decomposers, enricher

Onthophagus sp.

No

 

Onthophagus taurus

No

Decomposer, enricher

Copris incertus

No

Enricher

Cremastocheilus sp.

Yes

Pest of banana

Heliocopris gigas

No

 

Onthophagus dama

No

 

Phyllophaga nebulosa

No

Pest predator

Ateuchus sp.

No

 

Gymnopleurus miliaris

No

 

Canthon viridis

No

Decomposer and enricher

Garreta sp.

No

Decomposer and enricher

Cheironitis indicus

No

 

Catharsius molossus

No

Decomposer and enricher

Carabidae

Calosoma maderae

No

Pest predator

Pterostichus strenuus

No

 

Pheropsophus verticalis

No

 

Pterostichus aethiops

No

Pest predator

Scaritus quadriceps

No

Pest predator

Paranchus albipes

No

 

Anthia sexguttata

No

Pest predator

Chlaenius bimaculatus

No

 

Chlaenius sp.

No

 

Cicindela sp.

No

Pest predator

Tenebrionidae

Tribolium castenium

Yes

Pest of flour and stored grains

Mesostena sp.

No

 

Gonocephalum sp.

Yes

Pest of groundnut

Tenebrio molitor

Yes

Pest of stored grains

Chrysomelidae

Oides bipunctata

Yes

Pest of grapes and grape vine

Oulema melanopus

Yes

Pest of oat crop

Aspidomorpha sp.

No

 

Podagrica fuscicornis

Yes

Pest of okra leaves

Clytra sp.

Yes

Pest of soalu leaves, Vateria indica L.

Lilioceris sp.

No

biological control

Metriona bicolor

Yes

Pest of sweet potato

Charidotella sp.

Yes

Pest of Ipomoea, sunflower, and cabbage

Elateridae

Athous haemorrhoidalis

No

Pollinator of Coeloglossum viride

Hemicrepidius sp.

Yes

Pest of cereals, crops, and grasses

Lanelater fuscipes

Yes

Pest of cereals and vegetable crops

Buprestidae

Acmaeodera sp.

No

Pollinator of lily

Meloidae

Mylabris cichorii

No

Pollinators and Phytophagus

Phodaga alticeps

No

 

Mylabris postulata

No

Pollinators and Phytophagus

Alosimus syriacus

Yes

Pest of cotton fields

Gyrinidae

Gyrinus natator

No

 

Coccinilidae

Cheilomenes sexmaculata

No

Pest predator

Coccinella transversalis

No

Pest predator

Harmonia sedecimnotata

Yes

Pests of eggplant and cauliflower

Cheilomenes sp.

No

 

Apionidae

Apion clavipes

Yes

Pests of pigeon pea and soya bean

Histeridae

Euspilotus nigrita

No

 

Dytiscidae

Eretes sp.

No

 

Cybister fimbriolatus

No

 

Cucurlionidae

Polydrusus sericeus

Yes

Pests of oak and hazel

Cleonus sp.

Yes

Pest of lack plant

Cerambycidae

Trachysida sp.

No

 

Batocera rufomaculata

Yes

Major pest of fig trees

Macrotoma palmate

Yes

Pests of fruits, woods, and ornamental plants

Celosterna scabratoea

Yes

Minor pests of mango, pomegranate, and casuarina

Xystrocera globosa

Yes

Pest of cocoa

Lampyridae

Luciola sp.

No

 
As far as diversity indices are concerned, Scarabaeidae, Carabidae, and Chrysomelidae families were found to be most diverse and rich among all families with Shannon diversity index above 2.0 and Margalef’s Index in the range of 1.1–2.5 (Fig. 2). Tenebrionidae, Elateridae, Meloidae, Coccinellidae, and Cerambycidae had Shannon index ranged between 1.08 and 1.56, and the Margalef’s richness index was in the range of 0.23–0.56 indicating moderately rich families. Buprestidae, Gyrinidae, Apionidae, Histeridae, Cicindelidae, and Lampyridae had just one representative species making the least diverse families (Fig. 2). Pest and beneficial status was observed in different species as an ecological evaluation parameter. Among all the species reported, the highest numbers of Phytophagus pest species were from Chrysomelidae (six) trailed by Scarabaeidae (five), Carabidae (four), and Cerambycidae (four). However, the beneficial insects were represented by Scarabaeidae (five) as decomposers, followed by Elateridae, Meloidae, and Buprestidae as pollinators having one species each.
Fig. 2
Fig. 2

Graph depicting the diversity indices, calculated for the obtained families in Vadodara

Universal primers were used in this study, which perfectly amplified a 710 bp fragment of the mitochondrial COI gene when applied to template DNA (Fig. 3) from the specimens as shown in Fig. 4. Twelve species barcode sequences were obtained from the seven selected families. Table 2 represents the processID and sampleID of the species submitted on BOLD v.4.
Fig. 3
Fig. 3

0.8% Agarose gel image representing the DNA obtained from some of the species labeled in numerical order. Intact mt-DNA band was obtained for the Coleopteran species and was further processed for PCR reaction

Fig. 4
Fig. 4

2% Agarose gel image of amplified DNA obtained after the PCR done in some of the samples. (L) on the first well indicates the 100-bp ladder used to check the amplification of PCR product. The 1 and 2 represent the intact amplified COI gene of mt-DNA of two species, and the third lane was of negative control

Table 2

List of species with their families submitted to BOLD v.4 along with their processID and sampleID

Sr. no

Family

Species name

processID

sampleID

1

Scarabaeidae

Gymnopleurus miliaris

PBSL002-17

GMA1

2

Carabidae

Calosoma maderae

PBSL006-17

CMS1

3

Cerambycidae

Batocera rufomaculata

PBSL001-17

BRC1

4

Chrysomelidae

Oides bipunctata

PBSL004-17

OBF1

5

Tenebrionidae

Mesosterna sp.

PBSL003-17

MSE1

6

Lampyridae

Luciola sp.

PBSL005-17

LSG1

7

Scarabaeidae

Orcytes nasicora

PBSL008-17

ONcol2

8

Scarabaeidae

Xyloryctes jamaicensis

PBSL010-17

XJCol4

9

Scarabaeidae

Chironitis indicus

PBSL012-17

CICol6

10

Carabidae

Paranchus abipes

PBSL009-17

PACol3

11

Carabidae

Pherophosphus verticalis

PBSL011-17

PVCol5

12

Gyrinidae

Gyrinus natator

PBSL007-17

GNCol1

Sequence annotation

To find the sequence composition, GC% analysis was performed which resulted in decreasing order as follows; O. nasicora (39.4%), B. rufomacula (35.9%), C. maderae (35.3%), Luciola sp. (34.9%), Pherophophus sp. (34.4%), Mesostena sp. (33.4%), Oides sp. (31.9%), G. miliaris (31.6%), X. jamaicensis (30.9%), G. natator (29.9%), P. albipes (29.3%). Further, the sequence was analyzed for GC and AT skews, where GC skew was found the maximum in Luciola sp. (0.1), whereas the lowest was found in O. nasicora (− 0.2) among the selected species. However, overall comparison with other species, the maximum GC skew was shared between Chlaenius sp. and Luciola sp. of Carabidae and Lampyridae respectively (Fig. 5).
Fig. 5
Fig. 5

GC skew of all the species in study is calculated with predefined formula as mentioned in materials and method. The species sequenced are highlighted in the graph. Luciola sp. had the maximum value of + 0, while the lowest was of O.nasicornis. G.miliaris, C.maderae, P.albipes, G.natator, B.rufomaculata, Pherpsophus sp., and Luciola sp. had values between 0 and + 1

However, the AT% was ranging from 70.7% to 60.6%, where P. albipes was more AT-biased (70.7%), while O. nasicora had the lowest AT% (60.4%). Additionally, AT skew analysis revealed that Luciola sp. (0.10) has the highest AT value, whereas the lowest one was C. indicus (− 0.13). To map the AT richness of selected species among the other species, we found that P. strennus had the highest value (+ 0.13), while Trachysida sp. was recorded with the lowest value of (− 0.2) (Fig. 6).
Fig. 6
Fig. 6

AT skew of the species in study is calculated with predefined formula. The selected species sequenced are highlighted in the graph. Luciola sp. had the maximum value of + 0.1, while the lowest was of C.indicus (− 0.13). Mesostena sp., Luciola sp., and B.rufomaculata are the only three species having values > 0. All the rest species are less AT biased

Phylogenetic analysis

Coleoptera is considered to be one of the most controversial orders of Class Insecta, as it is the dominant order representing the highest level of species among other insect orders. Hence, the neighbor-joining statistical method for phylogeny reconstruction was performed which yielded maximum likelihood among the selected species. The sequence analysis also revealed that the computed overall mean distance was 833.28 ± 83.3 among the species; however, the pairwise mean distance showed a remarkable range of 2254.84 (Trachysida sp.) to 0.024 (O. taurus) of individual species comparison as depicted in Table 3 and Additional file 2: Table S2.
Table 3

Families of Coleoptera with their species submitted to NCBI along with its extension numbers by different authors used in the present report

Family

Species

NCBI ID/BOLD ID

References

bp length

Scarabaeidae

Gametis versicolor

KJ559408.1

Karthika, P. and Krishnaveni, N. (unpublished)

695 bp

Phyllophaga sp.

JX963332.1

García-López, et al. 2011

693 bp

Onthophagus gazella

EU162450.1

Emlen, D.J., et al. 2005

612 bp

Oryctes nasicornis

AAP9162

Direct submission

657 bp

Xyloryctes jamaicensis

PBSL010-17

Direct submission

776 bp

Aphodius fossor

AY132615.1

Mate, J.F. and Vogler, A.P. (unpublished)

795 bp

Onthophagus sp.

KR486381.1

Hebert, P.D., et al. 2003

573 bp

Onthophagus taurus

EU162476.1

Emlen, D.J., et al. 2005

612 bp

Copris sp.

MF804615.1

Blaimer, B. and Mulcahy, D.G. (unpublished)

658 bp

Onthophagus dama

Taxonomy ID: 1675891

  

Phyllophaga nebulosa

KX686390.1

Richmond, M.P. et.al. 2016

1191 bp

Ateuchus sp.

EU162435.1

Emlen, D.J., et al. 2005

584 bp

chirontits indicus

PBSL012-17

Direct submission

517 bp

Gympleurus miliaris

PBSL002-17

Direct submission

718 bp

Canthon viridis

AY131817.1

Monaghan, M.T et al. 2005

792 bp

Garreta sp.

   

Catharsius molossus

JQ855895.1

Wang, C.Y., et al. 2005

658 bp

Carabidae

Calosoma maderae

ADJ6357

Direct submission

696 bp

pterostichus strenuus

EU142597.1

Will, K.W. and Gill, A.S. 2008

817 bp

Pheropsophus verticalis

AAZ0127

Direct submission

555 bp

Pterostichus aethiops

KM444318.1

Hendrich, L., et al. 2015

658 bp

Scarites quadriceps

DQ063222.1

Greenstone, M.H., et al. 2005

1237 bp

Paranchus albipes

AAL7246

Direct submission

658 bp

Chlaenius sp.

   

Tenebrionidae

Tribolium castaneum

KU494281.1

Fohrer, F. and Meusnier, I. (unpublished)

658 bp

Mesostena sp.

PBSL003-17

Direct submission

668 bp

Gonocephalum sp.

JQ753368.1

Gunter, N.L., et al. (unpublished)

723 bp

Tenebrio molitor

KR915361.1

Hebert, P.D., et al. 2003

615 bp

Chrysomelidae

Oides bipunctata

PBSL005-17

Direct submission

733 bp

Oulema melanopus

KR490936.1

Hebert, P.D., et al. 2003

658 bp

Podagrica fuscicornis

KF656267.1

Baselga, A., et al. 2015

655 bp

Lilioceris sp.

AM283150.1

Vogler, A.P. (unpublished)

826 bp

charidotella sexpunctata

AM283219.1

Vogler, A.P. (unpublished)

823 bp

Elateridae

Athous haemorrhoidalis

JF781273.1

Wysocka, A et al. 2011

588 bp

Hemicrepidius sp.

KF442245.1

Han, T., et.al. (unpublished)

669 bp

Lanelater fuscipes

MF804547.1

Blaimer, B. and Mulcahy, D.G. (unpublished)

658 bp

Buprestidae

Acmaeodera sp.

KM364403.1

Evans, A.M., et al. 2015

1206 bp

Meloidae

Mylabris cichorii

FJ462783.2

Park, H.C.(unpublished)

658 bp

Mylabris pustulata

KX013089.1

Ajish, S.S. and Balaji, S. (unpublished)

682 bp

Gyrinidae

Gyrinus natator

PBSL007-17

Direct submission

655 bp

Coccinellidae

Cheilomenes sexmaculata

FJ154102.1

Khushboo, S et al. (unpublished)

517 bp

Coccinella transversalis

KX758112.1

Poolprasert, P. (unpublished)

675 bp

Harmonia sedecimnotata

EU392410.1

Aruggoda, A.G.B., (unpublished)

583 bp

Apionidae

Apion sp.

HQ883612.1

Jordal, B.H., et al. 2011

690 bp

Histeridae

Euspilotus nigrita

   

Dytiscidae

Eretes sp.

LT615895.1

Lam, A., (unpublished)

744 bp

Cybister fimbriolatus

DQ813676.1

Miller, K.B., et al. 2007

1294 bp

Cucurlionidae

Polydrusus sericeus

KJ166400.1

Dewaard, J.R., et al. (unpublished)

621 bp

Cleonus sp.

   

Cerambycidae

Trachysida sp.

KR126483.1

Dewaard, J.R., et al. (unpublished)

564 bp

Batocera rufomaculata

PBSL001-17

Direct submission

679 bp

hoplocerambyx spinicornis

KJ159160.1

Zheng, S., et.al. (unpublished)

500 bp

xystrocera globosa

KY357523.1

Wu, Y., et al. 2017

658 bp

Cicindelidae

Cicindela sp.

KC963753.1

Lopez-Lopez, A. and Vogler, A.P. (direct submission)

657 bp

Lampyridae

Luciola sp.

PBSL005-17

Direct submission

683 bp

Nucleotide substitution with maximum composite likelihood method with Gamma distribution (G) yielded the sequence similarity suggesting that among all the species selected for the study, G. natator, P. albipes, and Pheropsophus sp. belong to suborder Adephaga, while other nine species belong to Polyphaga. The present study also reported that scarabaeids were closest to Elateridae and Coccinellidae compared to other Polyphagans. On the other hand, Carabidae was found to be closer to Dytiscidae (Fig. 7).
Fig. 7
Fig. 7

Diagram of the phylogenetic tree obtained from 54 species of Coleoptera. The families’ clades are represented at right side of species belonging to it respectively. Some of the species, not having any sequencing record in NCBI, are not included. Color coding was emphasized so as to highlight different taxonomic levels in Polyphaga (12 families) and Adephaga (3 families) both

Further, we tried to look into the phylogeny of individual species (Additional file 1: Table S1) taking into consideration only barcoded species, the study showed that in family Scarabaeidae, O. nasicora, and X. jamaicensis were phylogenetically more close belonging to subfamily of Dynastini. On the other hand, C. indicus and G. miliaris were closest belonging to subfamily Scarabaeinae. In case of Carabidae, the obtained phylogeny showed that P. albipes, C. maderae, Pheropsophus sp. belong to Platininae, Carabinae, and Brachininae respectively (Fig. 8). The least distance was obtained between P. albipes and C. maderae suggesting they are more phylogenetically close. Moreover, as in the present study, individual species reported from Gyrinidae, Tenebrionidae, Chrysomelidae, Lampyridae, and Cerambycidae were less, it is difficult to comment on its phylogeny.
Fig. 8
Fig. 8

Circular phylogenetic tree of Coleoptera populations based on maximum likelihood method at level of genus. The line in the center represents the higher taxonomic levels, which includes Kingdom-Animalia, Phylum-Arthropod, and Order-Coleoptera, and coding is according to different taxonomic levels in Polyphaga (12 families) and Adephaga (3 families) both. The tree was constructed in MEGA 7

Discussion

In the present study, an attempt has been made to correlate the identification and assess the diversity of Coleoptera of Vadodara morphologically and genetically. An annotated list of the Coleoptera is represented in Table 1. Of all the collected species, the Scarabaeidae was the most dominant which is not a surprise as it is the largest family of the order Coleoptera. Unlike other groups of insects, the members of the family Scarabaeidae contain both coprophagous (beneficial) and phytophagous (harmful) beetles. The coprophagous represented by 14 species have an important ecological role through their habitat of burrowing and burying of dung. This performs a series of ecological functions such as nutrient cycling, soil aeration, and secondary seed dispersal. (Larsen 2004; Chandra et al. 2012a, b; Chandra and Gupta, 2013). On the other hand, phytophagous (leaf chafers) represented by four species were the agricultural pests of various commercial crops, feeding on leaves, flowers, fruits, roots, and other parts of the plant. A good assemblage of Scarabaeidae is thus self-explanatory. (Chatterjee, 2009; Thakkar and Parikh, 2016). Due to the presence of diverse vegetation, five Phytophagus pest beetles were recorded, two pest-feeding species, and five species of decomposers suggest that they were evenly distributed in different habitats.

The second most diverse family was Carabidae, representing a total of nine species. These beetles are increasingly used as a taxonomic study group in biodiversity and as bio-indicators in monitoring or site assessment studies for nature conservation purposes (Ghahari et al. 2010). Four predator species were found in the study that were feeding on small insects and larvae suggesting population of pest species are high due to which Carabids were found more. So an appreciable number of ground beetles in Vadodara and its predator habit thus suggest a positive ecological role of these insects. (Koivula, 2011; Thakkar and Parikh, 2016).

Leaf beetles or Chrysomelidae are considered to be one of important pest family due to their phytophagous feeding habits (Ding et al. 2007; Meissle et al. 2009). In the present study, eight species were reported making it the third most diverse family. Among all, the highest number of Phytophagus pest species was recorded (six) in this family. Furthermore, the remaining data obtained suggests it biological control activity. Hence, feeding characteristic and their high abundance makes them an important component of the food webs and a major component of herbivore guilds as well as an important food component for higher trophic organisms (Sánchez-Reyes et al. 2014).

Tenebrionidae is one more family having the highest number of stored grain pest. Stored product insects have a large economic impact on stored bulk grains and processed commodities. These insects can survive on small amounts of food that accumulate in inaccessible places. (Campbell and Arbogast, 2004). It is estimated that over-all damage caused by stored grain pest account for 10–40% loss annually (Mishra and Tripathi, 2011). The beetles found in this family showed more or less Phytophagus pest habit. Example of tenebrionid species includes Tribolium castaneum, feeds on flour, cereals, meals, crackles’, beans, spices, pasta, etc. (Weston and Rattingourd, 2000). Due to their nocturnal habit, small size, and their burrowing tendency that may have led to less number of Tenebrionidae in this study.

Families like Buprestidae, Apionidae, Lampyridae, and Gyrinidae were very less diverse as beetles of these families are very habitat specific. Hence, in the present study, the less number sighted could be because habitat species studies were not carried out. Buprestidae (jewel beetles) and Meloidae beetles are found nearby flowering plants suggesting their ecological role as pollinators. Gyrinids are water beetle so availability of water determines their presence. A single species of Apionidae family which was collected is Apion clavipes and is considered to be a pest of Pigeon pea (Bandyopadhyay et al. 2009). In case of Elateridae, they were commonly sighted under the bark of the trees. Phytophagus individuals were found on feeding large variety of crops, resulting in damage to seeds, roots, stems, and harvestable plant parts, which can facilitate secondary crop damage by pathogens.

Coccinellidae, Cerambycidae, and Curculionidae families were represented by total of 11 species in the study area. However, as these groups of coleopterans are usually considered to be the harmful one and at no time or place, they were reported to be in aggregation that can lead to the serious problem. Hence, the reported harmful groups of coleopterans are comparatively less. Although records of beetles as habitat indicator are common, however, most of the species collected in this work hold up huge alteration in the environmental factors and there is no substitution of species along with the diversification of the habitat (Spector & Ayzama, 2005; Scheffler 2005; Da Silva et al. 2010). Thus, at this point, it is difficult to comment on their habitat distribution and ecophysiological nature of the studied beetles.

The vast number of insect species are often exceedingly difficult to recognize using only morphological approach (Witt et al. 2006) and thus creates an insurmountable barrier for cataloging total biodiversity by only traditional taxonomy (Blaxter 2004; Pentinsaari et al. 2014), for which morphological identification have fallen short and the DNA barcoding has filled the gap (Bourke et al. 2013; Laurito et al. 2013). Several scientists are now using DNA-barcoding to understand the biodiversity of insects (Hebert et al. 2003; Hajibabaei et al. 2007). In line with this, the present study was focused on barcoding of 12 species on the basis of its habit, number, previously known literature, and its controversial status (Yuan et al. 2016), where barcoding and sequence analysis were totally based on mitochondrial COI. The selection of this marker is based on its low rate of mutation caused by habitat-specific adaptive radiation (Raupach et al. 2010) and so that a concrete phylogenetic tree is constructed of the selected species using standard models (lanfear et al. 2014).

Scarabaeidae considered to be one of the important family in Coleoptera as discussed above was found to be monophyletic to Elateridae, Buprestidae, Lampyridae, and Histeridae. The barcoding of X. jamaicensis and O. nasicora illustrated very less paired-wise distance indicating its phylogenetic closeness. Both the species had almost the same morphological characteristics, i.e., both have horns, similar size, thoracic, and abdominal hairs making it controversial for identification (Dechambre and Lachaume, 2001). However, in the present report, barcoding of these species revealed that both of them belong to individual tribe and genus. Similarly, Carabidae was found to be monophyletic to Gyrinidae; however, it shared homology with Dytiscidae. Species-level phylogeny showed P. albipes and C. maderae showed least paired-wise distance compared to Pheropsophus sp. This is the first study which shows the phylogenetic distance among these species of this family.

Moreover, Gyrinidae was found to be monophyletic to Dytiscidae and polyphyletic to Carabidae. During the present investigation, only G. natator was found as a representative of Gyrinidae and was closest to Eretes sp. belonging from Dytiscidae, suggesting that both shares ancestral characteristics of the clade (Yuan et al. 2016). Similarly, Tenebrionidae was polyphyletic to Cerambycidae and Chrysomelidae. However, it was found to be monophyletic to Meloidae (lanfear et al. 2014). The sister clade of B. rufomaculata, O. bipunctata, and Mesostena sp. was showing lowest pairwise distance to Trachysida sp., P. fuscicornis, and Gonocephalum sp. respectively. Our study is parallel with previous established molecular and morphological studies. (Caterino et al. 2002; Hunt et al. 2007; Pons et al. 2010; Lawrence et al. 2011; Bocak et al. 2014).

GC and AT% provided the evidence of two suborders, Adephaga and Polyphaga. Our results account for the fact that Scarabaeidae forms sister clade with Elateridae, Lampyridae, Buprestidae, and Histeridae. Correspondingly, Carabidae with Dytiscidae and Gyrinidae, Chrysomelidae with Cerambycidae, Tenebrionidae with Meloidae, Curculionidae, and Coccinellidae. Our studies were incongruent with earlier mitochondrial genomes studies of Yuan et al. (2015a, b, 2016).

Conclusion

Despite optimistic views, the taxonomic impediment remains the main concern and thus demands an urgent need for comprehensive biodiversity assessments due to biodiversity crises: the risk of human activity causing mass extinction. Thus, barcoding can accelerate the process of taxonomic inventory. In conclusion, the present study incorporates genetical, morphological, and ecological data which specify its species distribution, richness, and diversity in different sites of Vadodara, Gujarat, and the phylogeny derived from present study unravels the status of unknown species of Coleoptera:
  1. 1.

    (Adephaga(Gyrinidae+ (Dytiscidae++ Carabidae))

     
  2. 2.

    (Polyphaga(Histeridae+Buprestidae+Lampyridae+Elateridae+(Scarabaeidae+(Coccinelidae+ Apionidae+Cucurlionodae+ (Meloidae+Tenebrionidae+(Cerambycidae+Chrysomelidae))))))

     

Thus, from this study, it can be derived that Scarabidae are the most diverse group of beetles in and around Vadodara, and pest status of beetles are high due to several adaptations. Thus, we suggest further studies are needed to understand the ecophysiological role of different beetle families.

Abbreviations

A: 

Adenine

BOLD: 

Barcode Of Life Data System

C: 

Cytosine

DNA: 

Deoxyribonucleic acid

G: 

Guanidine

iTOL: 

Interactive Tree of life

MEGA: 

Molecular Evolutionary Genetics Analysis

mtCOI: 

Mitochondrial cytochrome oxidase I

PCR: 

Polymerase chain reaction

PhyloT: 

Phylogenetic Tree Generator

T: 

Thymine

Declarations

Acknowledgements

The authors are thankful to the head of Department of Zoology, The Maharaja Sayajirao University of Baroda, Vadodara for providing lab facilities to carry out the present work.

Funding

This is a study performed by corresponding authors and her group (other authors) and has not taken any funding from any of the agencies.

Availability of data and materials

Please contact the author(s) for data requests.

Authors’ contributions

All authors have contributed equally to the present work (field visits, identification of insect species, DNA isolation, PCR amplification, and sequencing) and preparation of the final manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

All the insects collected were according to the laws of India, and none of the collected species were in the IUCN red list. We declare that we do not need ethical clearance for the present diversity and phylogeny work.

Consent for publication

Not applicable to the present study.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Department of Zoology, Faculty of Science, The Maharaja Sayajirao University of Baroda, Vadodara, India
(2)
Department of Life Science, School of Science and Engineering, Navrachana University, Vadodara, India

References

  1. Bandyopadhyay, B., Paul, S. K., Jha, S., & Ghosh, M. R. (2009). Pod weevil Apion clavipes Gerst (Apionidae: Coleoptera) infestation on pigeon-pea in West Bengal. Environment and Ecology, 27(3A), 1262–1264.Google Scholar
  2. Banerjee, M. (2014). Diversity and composition of beetles (order: Coleoptera) of Durgapur, West Bengal, India. Psyche: A Journal of Entomology. vol. 2014, Article ID 792746, 6 pages. https://doi.org/10.1155/2014/792746.
  3. Baselga, A., Gómez-Rodríguez, C., & Vogler, A. P. (2015). Multi-hierarchical macroecology at species and genetic levels to discern neutral and non-neutral processes. Global Ecology Biogeography, 24, 873–882.Google Scholar
  4. Bergsten, J., Bilton, D.T., Fujisawa, T., Elliott, M., Monaghan, M.T., Balke, M., Hendrich, L., Geijer, J., Herrmann, J., Foster, G.N., Ribera, I., Nilsson, A.N., Barraclough, T.G. & Vogler, A. P. (2012). The effect of geographical scale of sampling on DNA barcoding. Syst Biol. 61(5):851-869.Google Scholar
  5. Blaxter, M. L. (2004). The promise of a DNA taxonomy. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 359(1444), 669–679.View ArticleGoogle Scholar
  6. Bocak, L., Barton, C., crampton-platt, A. L. E. X., Chesters, D., Ahrens, D., & Vogler, A. P. (2014). Building the Coleoptera tree-of-life for > 8000 species: Composition of public DNA data and fit with Linnaean classification. Systematic Entomology, 39(1), 97–110.View ArticleGoogle Scholar
  7. Bourke, B. P., Oliveira, T. P., Suesdek, L., Bergo, E. S., & Sallum, M. A. M. (2013). A multi-locus approach to barcoding in the Anopheles strodei subgroup (Diptera: Culicidae). Parasites and vectors, 6(1), 111.View ArticleGoogle Scholar
  8. Brown, J., Scholtz, C. H., Janeau, J. L., Grellier, S., & Podwojewski, P. (2010). Dung beetles (Coleoptera: Scarabaeidae) can improve soil hydrological properties. Applied Soil Ecology, 46(1), 9–16.View ArticleGoogle Scholar
  9. Büchs, W. (2003). Biodiversity and agri-environmental indicators—general scopes and skills with special reference to the habitat level. Agriculture, Ecosystems and Environment, 98(1), 35–78.View ArticleGoogle Scholar
  10. Campbell, J. F., & Arbogast, R. T. (2004). Stored-product insects in a flour mill: Population dynamics and response to fumigation treatments. Entomologia Experimentalis et Applicata, 112(3), 217–225.View ArticleGoogle Scholar
  11. Caterino, M. S., Shull, V. L., Hammond, P. M., & Vogler, A. P. (2002). Basal relationships of Coleoptera inferred from 18S rDNA sequences. Zoologica Scripta, 31(1), 41–49.View ArticleGoogle Scholar
  12. Chandra, K., & Gupta, D. (2013). Taxonomic studies on dung beetles (Coleoptera: Scarabaeidae, Geotrupidae, Hybosoridae) of Chhattisgarh, India. Munis Entomology and Zoology, 8, 331–360.Google Scholar
  13. Chandra, K., Gupta, D., Uniyal, V. P., Bharadwaj, M., & Sanyal, A. K. (2012b). Studies on scarabaeid beetles (Coleoptera) of Govind wildlife sanctuary, Garhwal, Uttarakhand, India. Biological Forum-An International Journal, 4(1), 48–54.Google Scholar
  14. Chandra, K., Gupta, D., Uniyal, V. P., Sanyal, A. K., & Bhargav, V. (2012a). Taxonomic studies on lamellicorn Scarabaeids (Coleoptera) of Simbalbara wildlife sanctuary, Sirmour, Himachal Pradesh, India. Records of the Zoological survey of India, 112, 81–91.Google Scholar
  15. Chattrjee, S., Isaia, M., & Venturino, E. (2009). Spiders as biological controllers in the agroecosystem. J Theor Biol, 258, 352–362.View ArticleGoogle Scholar
  16. Choate P.M. (2001). Manual for the identification of Ground beetles (Coleoptera: Carabidae)(including tiger beetles) of Florida., Department Entomology and Nematology University of Florida. http://www.entnemdept.ufl.edu/choate/florida_carabidae_new.pdf
  17. da Silva, N. S., da Silva-Nunes, M., Malafronte, R. S., Menezes, M. J., D’Arcadia, R. R., Komatsu, N. T., … Ferreira, M. U. (2010). Epidemiology and control of frontier malaria in Brazil: lessons from community-based studies in rural Amazonia. Trans R Soc Trop Med Hyg., 104, 343–350.Google Scholar
  18. Davis, A. J., Holloway, J. D., Huijbregts, H., Krikken, J., Kirk-Spriggs, A. H., & Sutton, S. L. (2001). Dung beetles as indicators of change in the forests of northern Borneo. Journal of Applied Ecology, 38(3), 593–616.View ArticleGoogle Scholar
  19. Dechambre, R.-P., & Lachaume, G. (2001). The genus Oryctes (Dynastidae). The beetles of the world. 27. Canterbury: Hillside Books Archived from the original on 2010-08-06.Google Scholar
  20. Ding, J., Wang, Y., & Jin, X. (2007). Monitoring populations of Galerucella birmanica (Coleoptera: Chrysomelidae) on Brasenia schreberi and Trapa natans (Lythraceae): Implications for biological control. Biological Control, 43(1), 71–77.View ArticleGoogle Scholar
  21. Emlen, D. J., Hunt, J., & Simmons, L. W. (2005). Evolution of sexual dimorphism in the expression of beetle horns: phylogenetic evidence for modularity, evolutionary lability and constraint. Am Nat, 166, S42–S68.Google Scholar
  22. Evans, A. M., McKenna, D. D., Bellamy, C. L., & Farrell, B. D. (2015). Large-scale molecular phylogeny of metallic wood-boring beetles (Coleoptera: Buprestoidea) provides new insights into relationships and reveals multiple evolutionary origins of the larval leaf-mining habit. Syst Entomol, 40(2), 385–400.Google Scholar
  23. Fagundes, C. K., Di Mare, R. A., Wink, C., & Manfio, D. (2011). Diversity of the families of Coleoptera captured with pitfall traps in five different environments in Santa Maria, RS. Brazil. Braz J Biol, 71(2), 381–390.Google Scholar
  24. Foottit, R. G., & Adler, P. H. (2009). Insect biodiversity: Science and society. John Wiley and Sons. vol 1, 2nd Edition.Google Scholar
  25. Folmer, O., Black, M., Hoeh, W., Lutz, R., & Vrijenhoek, R. (1994). DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol, 3(5), 294–299.Google Scholar
  26. Garcia-Lopez, A., Mico, S., Zumbado, M. A., & Galante, E. (2011). Sampling scarab beetles in tropical forests: The effect of light source and night sampling periods. J Insects Science, 11, 1–14.Google Scholar
  27. Ghahari, H., Avgin, S. S., & Ostovan, H. (2010). Carabid beetles (Coleoptera: Carabidae) collected from different ecosystems in Iran with new records. Turkish Journal of Entomology, 34(2), 179–195.Google Scholar
  28. Gillott, C. (2005). The remaining endopterygote orders. In Entomology, (pp. 297–351).Google Scholar
  29. Greenstone, M. H., Rowley, D. L., Heimbach, U., Lundgren, J. G., Pfannenstiel, R. S., & Rehner, S. A. (2005). Barcoding generalist predators by polymerase chain reaction: carabids and spiders. Molecular Ecology, 14, 3247–3266.Google Scholar
  30. Gullan, P. J., & Cranston, P. (2010). Insect systematics: Phylogeny and classification. The Insects: An Outline of Entomology, (fourth ed., pp. 189–222). Oxford: Wiley-Blackwell.Google Scholar
  31. Hajibabaei, M., Singer, G. A., Hebert, P. D., & Hickey, D. A. (2007). DNA barcoding: How it complements taxonomy, molecular phylogenetics and population genetics. Trends in Genetics, 23(4), 167–172.View ArticleGoogle Scholar
  32. Hebert, P. D., Cywinska, A., & Ball, S. L. (2003). Biological identifications through DNA barcodes. Proceedings of the Royal Society of London B: Biological Sciences, 270(1512), 313–321.View ArticleGoogle Scholar
  33. Hebert, P. D., Ratnasingham, S., & DeWaard, J. R. (2003). Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. Proc R Soc Lond B, 270(Suppl), s96–s99.Google Scholar
  34. Hendrich, L., Morinière, J., Haszprunar, G., Hebert, P. D., Hausmann, A., Köhler, F., & Balke, M. (2015). A comprehensive DNA barcode database for Central European beetles with a focus on Germany: adding more than 3500 identified species to BOLD. Mol Ecol Resour, 15(4), 795–818.Google Scholar
  35. Hunt, T., Bergsten, J., Levkanicova, Z., Papadopoulou, A., John, O. S., Wild, R., & Gómez-Zurita, J. (2007). A comprehensive phylogeny of beetles reveals the evolutionary origins of a super-radiation. Science, 318(5858), 1913–1916.View ArticleGoogle Scholar
  36. Jordal, B. H., Sequeira, A. S., & Cognato, A. I. (2011). The age and phylogeny of wood boring weevils and the origin of subsociality. Mol PhyloEvol, 59, 708–724.Google Scholar
  37. Kakkar, N., & Gupta, S. K. (2010). Diversity and seasonal fluctuations in dung beetle (Coleoptera) community in Kurukshetra, India. Entomological Research, 40(3), 189–192.View ArticleGoogle Scholar
  38. Kazmi, S. I., & Ramamurthy, V. V. (2004). Coleoptera fauna from the Thar desert of Rajasthan, India. Zoos print, 19(4), 1447–1448.View ArticleGoogle Scholar
  39. Koch, H. (2010). Combining morphology and DNA barcoding resolves the taxonomy of western Malagasy Liotrigona Moure, 1961 (hymenoptera: Apidae: Meliponini). African Invertebrates, 51(2), 413–421.View ArticleGoogle Scholar
  40. Koivula, M. J. (2011). Useful model organisms, indicators, or both? Ground beetles (Coleoptera, Carabidae) reflecting environmental conditions. ZooKeys, 100, 287.View ArticleGoogle Scholar
  41. Lanfear, R., Calcott, B., Kainer, D., Mayer, C., & Stamatakis, A. (2014). Selecting optimal partitioning schemes for phylogenomic datasets. BMC Evolutionary Biology, 14(1), 82.View ArticleGoogle Scholar
  42. Larsen, T. (2004). Escarabajos peloteros/dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae).Google Scholar
  43. Laurito, M., de Oliveira, T. M., Almiron, W. R., & Sallum, M. A. M. (2013). COI barcode versus morphological identification of Culex (Culex) (Diptera: Culicidae) species: A case study using samples from Argentina and Brazil. Memórias do Instituto Oswaldo Cruz, 108, 110–122.View ArticleGoogle Scholar
  44. Lawrence, J. F., Ślipiski, A., Seago, A. E., Thayer, M. K., Newton, A. F., and Marvaldi, A. E. (2011). Phylogeny of the Coleoptera based on morphological characters of adults and larvae. In Annales Zoologici Museum and Institute of Zoology, Polish Academy of Sciences. 61(1), 1–217.Google Scholar
  45. Losey, J. E., & Vaughan, M. (2006). The economic value of ecological services provided by insects. Bioscience, 56(4), 311–323.View ArticleGoogle Scholar
  46. Meissle, M., Pilz, C., & Romeis, J. (2009). Susceptibility of Diabrotica virgifera virgifera (Coleoptera: Chrysomelidae) to the entomopathogenic fungus Metarhizium anisopliae when feeding on Bacillus thuringiensis Cry3Bb1-expressing maize. Applied and Environmental Microbiology, 75(12), 3937–3943.View ArticleGoogle Scholar
  47. Miller, K. B., Bergsten, J. and Whiting. M. F. (2007). Phylogeny and classification of diving beetles in the tribe Cybistrini (Coleoptera, Dytiscidae, Dytiscinae). Zoologica Scripta 36(1), 41–59.Google Scholar
  48. Mishra, B. B., & Tripathi, S. P. (2011). Repellent activity of plant derived essential oils against Sitophilous oryzae (Linnaeus) and Tribolium castenium (Herbst). Singapore Journal of Scientific Research, 1(2), 173–178.View ArticleGoogle Scholar
  49. Monaghan, M. T., Balke, M., Gregory, T. R., & Vogler, A. P. (2005). DNA-based species delineation in tropical beetles using mitochondrial and nuclear markers. Philosophical transactions of the Royal Society of London. Ser B, Biol Sciences, 360(1462), 1925–1933.Google Scholar
  50. Naidu, B., & Kumar, D. (2011). Diversity and distribution of social apocrites of Vadodara, Gujarat, western India. Halters, 17(1), 23–27.Google Scholar
  51. Nichols, E., Gardner, T. A., Peres, C. A., & Spector, S. (2009). Co-declining mammals and dung beetles: An impending ecological cascade. Oikos, 118(4), 481–487.View ArticleGoogle Scholar
  52. Odegaard, F. (2000). The relative importance of trees versus lianas as hosts for phytophagous beetles (Coleoptera) in tropical forests. Journal of Biogeography, 27(2), 283–296.View ArticleGoogle Scholar
  53. Parikh, P. H. (2001). Studies of lesser known fauna of Gir PA withspecial reference to Invertebrates. Sasan Gir, Gujarat: Report submitted to DCF, Department of forest, Wildlife Division.Google Scholar
  54. Pentinsaari, M., Hebert, P. D., & Mutanen, M. (2014). Barcoding beetles: a regional survey of 1872 species reveals high identification success and unusually deep interspecific divergences. PLoS One, 9(9), e108651.View ArticleGoogle Scholar
  55. Pilo, B., Pathak, B. J., Kumar, B. A., Muruksan, V. K., Vinod, K. R., & Kumari, S. (1996). Biological diversity of Gujarat–Current knowledge. Vadodara: Gujarat Ecological Commission.Google Scholar
  56. Pons, J., Ribera, I., Bertranpetit, J., & Balke, M. (2010). Nucleotide substitution rates for the full set of mitochondrial protein-coding genes in Coleoptera. Molecular Phylogenetics and Evolution, 56(2), 796–807.View ArticleGoogle Scholar
  57. Puspitasari, S. (2016). Biogeography and ecology of beetles in a tropical archipelago: A case study from Kepulauan Seribu Marine National Park (Doctoral dissertation, UCL (University College London)).Google Scholar
  58. Raupach, M. J., Astrin, J. J., Hannig, K., Peters, M. K., Stoeckle, M. Y., & Wägele, J. W. (2010). Molecular species identification of central European ground beetles (Coleoptera: Carabidae) using nuclear rDNA expansion segments and DNA barcodes. Frontiers in Zoology, 7(1), 26.View ArticleGoogle Scholar
  59. Richmond, M. P., Park, J., & Henry, C. S. (2016). The function and evolution of male and female genitalia in Phyllophaga harris scarab beetles (Coleoptera: Scarabaeidae). J Evol Biol, 29, 2276–2288.Google Scholar
  60. Sánchez-Reyes, U. J., Niño-Maldonado, S., & Jones, R. W. (2014). Diversity and altitudinal distribution of Chrysomelidae (Coleoptera) in Peregrina Canyon, Tamaulipas, Mexico. ZooKeys, 417, 103.View ArticleGoogle Scholar
  61. Scheffler, S. (2005). Choice, circumstance, and the value of equality. Politics, Philosophy & Economics, 4(1), 5–28 https://doi.org/10.1177/1470594X05049434.
  62. Shearin, A. F., Reberg-Horton, S. C., & Gallandt, E. R. (2007). Direct effects of tillage on the activity density of ground beetle (Coleoptera: Carabidae) weed seed predators. Environmental Entomology, 36(5), 1140–1146.View ArticleGoogle Scholar
  63. Silveira, F. T., Blackwell, J. M., Ishikawa, E. A., Braga, R., Shaw, J. J., Quinnell, R. J., & Shaw, M. A. (1998). T cell responses to crude and defined leishmanial antigens in patients from the lower Amazon region of Brazil infected with different species of Leishmania of the subgenera Leishmania and Viannia. Parasite Immunology, 20(1), 19–26.View ArticleGoogle Scholar
  64. Spector, S., & Ayzama, S. (2005). Rapid Turnover and Edge Effects in Dung Beetle Assemblages (Scarabaeidae) at a Bolivian Neotropical Forest‐Savanna Ecotone. Biotropica, 35(3), 394–404.Google Scholar
  65. Thakkar, B., & Parikh, P. (2016). A study on diversity and abundance of coleopterans in Gujarat, India.Google Scholar
  66. Valentini, A., Pompanon, F., & Taberlet, P. (2008). DNA barcoding for ecologist. Trends in Ecology and Evolution., 24(2), 110–117.View ArticleGoogle Scholar
  67. Wang, C. Y., Feng, Y., & Xiao-Ming, C. (2005). DNA barcoding analysis of processed medicinal insect Catharsius molossus. Zoological Research, 33(6), 597–602. https://doi.org/10.3724/SP.J.1141.2012.06597.
  68. Weston, P. A., & Rattingourd, P. L. (2000). Progeny production by Tribolium castenium (Coleoptera: Tenebrionidae) and Oryzaephilus surinamensis (Coleoptera: Silvanidae) on maize previously infested by Sitotroga cerealella. J.Econ. Entoml., 93, 533–536.View ArticleGoogle Scholar
  69. Will, K. W., & Gill, A. S. (2008). Phylogeny and classification of Hypherpes auctorum (Coleoptera: Carabidae: Pterostichini: Pterostichus). Annals Carnegie Museum, 77(1), 93–127.Google Scholar
  70. Witt, J. D., Threloff, D. L., & Hebert, P. D. (2006). DNA barcoding reveals extraordinary cryptic diversity in an amphipod genus: Implications for desert spring conservation. Molecular Ecology, 15(10), 3073–3082.View ArticleGoogle Scholar
  71. Wu, Y., Trepanowski, N. F., Molongoski, J. J., Reagel, P. F., Lingafelter, S. W., Nadel, H., Myers, S. W., Ray, A. M. (2017). Scientific Reports volume7, Article number: 40316. https://doi.org/10.1038/srep40316.
  72. Wysocka, A., Kaczmarczyk, A., Buchholz, L., & Sell, J. (2011). Morphologically intermediate form between Athous haemorrhoidalis and A. vittatus (Coleoptera: Elateridae): a case of hybridization? a preliminary study. Ann Zool, 61, 629–635.Google Scholar
  73. Yuan, M. L., Zhang, Q. L., Guo, Z. L., Wang, J., & Shen, Y. Y. (2015a). Comparative mitogenomic analysis of the superfamily Pentatomoidea (Insecta: Hemiptera: Heteroptera) and phylogenetic implications. BMC Genomics, 16(1), 460.View ArticleGoogle Scholar
  74. Yuan, M. L., Zhang, Q. L., Guo, Z. L., Wang, J., & Shen, Y. Y. (2015b). The complete mitochondrial genome of Corizus tetraspilus (Hemiptera: Rhopalidae) and phylogenetic analysis of Pentatomomorpha. PLoS One, 10(6), e0129003.View ArticleGoogle Scholar
  75. Yuan, M. L., Zhang, Q. L., Zhang, L., Guo, Z. L., Liu, Y. J., Shen, Y. Y., & Shao, R. (2016). High-level phylogeny of the Coleoptera inferred with mitochondrial genome sequences. Molecular phylogenetics and evolution, 104, 99–111.Google Scholar

Copyright

© The Author(s) 2018

Advertisement