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All issues Volume 55 (2019) Ann. Limnol. - Int. J. Lim., 55 (2019) 1 Full HTML
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Ann. Limnol. - Int. J. Lim.
Volume 55, 2019
Article Number 1
Number of page(s) 12
DOI https://doi.org/10.1051/limn/2018030
Published online 24 January 2019

© EDP Sciences, 2019

1 Introduction

Aquatic Coleoptera are one of the largest groups of insects with more than 13,000 described species (Short, 2018). This high diversity is often attributed to multiple independent aquatic invasions by ancestral terrestrial forms of aquatic beetles and their ability to adapt to the different environments (Jäch and Balke, 2008; Toussaint et al., 2017; Short, 2018). Species composition of aquatic beetle communities is known to be affected by environmental factors such as microhabitat (Fairchild et al., 2003), habitat size (Nilsson, 1984; Nilsson et al., 1994), vegetation structure (Nilsson et al., 1994; McAbendroth et al., 2005; Bloechl et al., 2010), ecological habitat types (Ribera and Vogler, 2000; Ribera et al., 2003), hydroperiod (Lundkvist et al., 2001), water chemistry (Eyre et al., 1986; Bloechl et al., 2010) and habitat age (Fairchild et al., 2000; Bloechl et al., 2010). However, most of these studies are available from temperate regions, and very few faunistic studies are from tropical regions, especially from south Asia (Mohd Rasdi et al., 2012; Freitag et al., 2016).

Previous work on Indian aquatic beetles is primarily taxonomical (see supplementary material) with limited information on their habitats (Sheth et al., 2018) and some general observations (Tonapi and Ozarkar, 1969a,b). The Northern Western Ghats (NWG) are part of the Western Ghats–Sri Lanka megadiverse region with high endemism in its floral and faunal elements (Myers et al., 2000; Mittermeier et al., 2005). The region was declared as a biodiversity hotspot based mainly on the knowledge about vertebrates, as most of its invertebrate diversity was not well known (Myers et al., 2000). The freshwater ecosystems of NWG are rich in faunal diversity as suggested by recent studies on the freshwater invertebrates (Kulkarni et al., 2015), including crustaceans (Shinde et al., 2014; Padhye and Dahanukar, 2015; Padhye and Dumont, 2015; Padhye and Victor, 2015; Kulkarni and Pai, 2016), rotifers (Vanjare and Pai, 2010; Vanjare et al., 2010 and Vanjare et al., 2017) and sponges (Jakhalekar and Ghate, 2013, 2014, 2016), and vertebrates such as freshwater fishes (Keskar et al., 2018). On the contrary, Thakare and Zade (2011) is the only available report on species richness of aquatic beetles from Melghat tiger reserve, Maharashtra.

Therefore, to estimate the current diversity of aquatic beetles and to understand the environmental correlates influencing the distributions of aquatic beetles, we conducted qualitative surveys during 2013–2017 in and around NWG. We assessed the relative occurrence of aquatic beetles in NWG. We estimated the species richness of types of freshwater habitats using non-parametric estimators and studied the associations of environmental factors with aquatic beetles using canonical correspondence analysis (CCA). To examine species distributions along the geographical gradient, we investigated the association between altitude classes and the aquatic beetles using chi-square test and multiple correspondence analysis.

2 Methods

2.1 Study area

Northern Western Ghats (Fig. 1) are parts of the western Maharashtra which include the Western Ghats escarpment (with high and low hills) and the Konkan region down the Ghats along the west coast, separating the land from the Arabian Sea (Mani, 1974; Watve, 2013). This region is composed largely of basaltic rock with intermittent laterite (Mani, 1974; Jog et al., 2002) and ranges from 600 to 1000 m above sea level (asl). During monsoon (June–October) the Ghats receive maximum rainfall (Mani, 1974).

thumbnail Fig. 1

Sampling localities in and around the Northern Western Ghats.

2.2 Sampling

Qualitative surveys of 105 localities were conducted in and around the Northern Western Ghats of India during May 2013–June 2017 for aquatic beetle collection. Aquatic beetles were found in 85 localities with a total of 213 samples. The freshwater habitats encountered in the study area ( Fig. 2) were broadly categorised as pools, ponds, tanks, reservoirs and streams as per Williams et al. (2004) and Williams (2006). Tanks are man-made water bodies, more than 200 cm in depth, which were constructed on the top of hills as a source of water. A pond net with mesh size of 1 mm and an extendible telescopic handle was used for the aquatic beetle collection. The net was randomly swept to and fro along the margins of water bodies and then the collected beetles were preserved in ethanol. The water parameters pH, salinity, conductivity, total dissolved solids and temperature were measured using multiparameter probe (PCTestr 35) on the day of sampling. Permanence (perennial/temporary), substrate type (rock, mud, gravel) and vegetation (present/absent) were used as categorical variables. The altitude, latitude and longitude were obtained using Google Earth© (parameter ranges are provided in Appendix 2).

thumbnail Fig. 2

Freshwater habitat types within the study area: A − pool (Tableland); B − pond (Korigad); C − tank (Harishchandragad); D − reservoir (Talegaon); E − rock puddle (Harishchandragad); F − stream (Harishchandragad).

2.3 Identification

In all, five families were studied: Dytiscidae, Gyrinidae, Haliplidae and Noteridae under Adephaga and Hydrophilidae under Polyphaga. The species were identified using literature (see supplementary material for references). The beetles and their male genitalia were studied using Leica SMZ6 microscope and Olympus CX41 microscope, respectively.

2.4 Data analysis

Aquatic beetles were classified as rare (R; less than 5%), average (A; 5–15%), common (C; 15–40%) and widespread (Ws; more than 40%) based on their relative occurrence.

The species richness estimation with 500 randomisations per sample for the incidence-based data was carried out in Estimate S version 9.1.0 using non-parametric Chao2, Jackknife1 and Bootstrap estimators with their biased correction form and (when necessary) classic form (http://viceroy.eeb.uconn.edu/EstimateS) (Chao, 1987; Colwell and Coddington, 1994; Colwell, 2005, 2013; Chao and Chiu, 2016). A species accumulation curve was computed in PAST 3.15 (Hammer et al., 2001), in which the species richness is estimated as a function of number of samples. It uses Mao's tau with standard deviation, and standard errors are presented as 95% confidence intervals in a plot (Colwell et al., 2004).

The associations between the environmental variables and aquatic beetle species were tested using canonical correspondence analysis in PAST 3.15 (Hammer et al., 2001). The CCA is a multivariate method which provides an ordination map for data visualization based on the synthetic gradients extracted from the datasets (ter Braak and Verdonschot, 1995). The pH, salinity, water temperature, altitude, hydroperiod (temporary and perennial), depth, substrate type and vegetation were used for analysis. The hydroperiod, depth, substrate and vegetation were used as categorical variables. The conductivity and total dissolved solids were excluded as they were collinear with salinity (Pearson correlation r > 0.7). Monte Carlo permutations (n = 999) were used to test the significance of extracted canonical axes.

Altitude was classified into five bins: 1–299, 300–599, 600–899, 900–1199 and 1200–1499. The chi-square test was used to find out whether there was a relationship between the altitude classes and frequencies of species with 9999 Monte Carlo permutations in PAST 3.15. Multiple correspondence analysis (MCA) was performed in PAST 3.15 to visualise the associations between altitude classes and species. The row principal biplot scaling was used to examine proximity of altitude classes and the similarity of species distributions between the classes.

3 Results

During this work, we identified 66 species ( Tab. 1) belonging to five families: Dytiscidae (43 species), Hydrophilidae (13 species), Gyrinidae (6), Noteridae (2) and Haliplidae (2) from NWG. A total of 11 species were encountered in all habitat types while Copelatus mysorensis, Copelatus cryptarchoides, Microdytes svensoni, Clypeodytes hemani, Lacconectus lambai, Berosus indiges and Hydrobiomorpha spinicollis were found only in pools. Hygrotus musicus, Canthydrus laetabilis and Sternolophus inconspicuus were found only in ponds, Patrus assimilis was found only in the streams and Hygrotus nilghiricus was encountered only in man-made tanks on hill forts. The laccophilines and hydroporines were observed to co-occur in the same habitat (28% of all samples). C. hemani, Microdytes sabitae and L. lambai co-occurred in temporary pools on rocky outcrops (23% of rocky outcrop samples).

The distribution free estimators showed that around 70–80% fauna was covered by our sampling effort. The observed and estimated species richness per type of habitat is given in Table 2. The sample-based rarefaction showed that observed and estimated number of species by accumulation curve is similar; however, intensive sampling within the study area is likely to yield more species. The species estimation curves and sample-based rarefaction curve are presented in Figure 3.

The first two canonical axes explained 31.7% and 16% of the variation (permutations = 999, trace = 1.324, p = 0.0001) attributable to the environmental factors ( Fig. 4). The first canonical axis was highly and negatively correlated with the increasing altitude followed by rocky substrate based on their length and the proximity to the axis. The axis 1 was positively correlated with increase in salinity. The second canonical axis was positively correlated with temporary habitat and muddy substrate, while negatively correlated with increasing depth (perennial habitat). L. lambai, C. hemani and M. sabitae showed association with temporary habitats at higher altitude with rocky substrate and co-occurred frequently. C. mysorensis, Copelatus deccanensis, Rhantus taprobanicus, Hyphydrus intermixtus and Hydaticus luczonicus showed association with altitude and habitats with rock as substrate. Hydrovatus acuminatus, Hydrovatus cardoni, H. musicus, Berosus indicus, Peschetius toxophorus, Peschetius quadricostatus and Hyphydrus l. flavicans showed association with habitats with increasing salinity. Cybister cognatus, Cybister sugillatus, Cybister tripuctuatus lateralis, Berosus chinensis, Haliplus arrowi and Amphiops sp. were found to be associated with deeper and perennial water bodies. Laccophilus inefficiens and Hyphydrus renardi were encountered at many localities and hence were less limited by the environmental characteristics, thus appear at the centre of the CCA.

There was a significant association between altitude classes and species occurrence (Chi-square = 545.57, p < 0.0001). In MCA, four dimensions were sufficient to explain 100% of inertia. The first two axes explained 53.6% and 20.1% of total inertia, respectively ( Fig. 5). Altitude classes 900–1199 and 1200–1499 were positioned in proximity, suggesting similarity in their species composition as compared to 1–299, 300–599 and 600–899. The classes 1–999, 900–1199 and 1200–1499 resolved on the first axis. The class 1–199 showed strong association with Laccophilus obtusus, Copelatus schuhi, C. sugillatus, Berosus pulchellus, Allocotocerus sp., Sternolophus rufipes, Amphiops sp., Canthydrus luctuosus and Hydroglyphus flammulatus. The classes 900–1199 and 1200–1499 were found to be strongly correlated with H. intermixtus, M. sabitae, C. hemani, H. nilghiricus, R. taprobanicus, L. lambai, H. luczonicus, Hydaticus vittatus and Hydrophilus sp. The class 300–599 resolved on the second axis and showed strong association with H. flavicans, P. toxophorus, Laccophilus ceylonicus, Lacconectus andrewesi, Hydaticus incertus, Dineutus indicus, B. indiges, S. inconspicuus and C. laetabilis.

Table 1

The list of aquatic beetles from NWG with their relative occurrence and abbreviations.

Table 2

The observed and estimated species richness per habitat type within NWG.

thumbnail Fig. 3

Species richness estimation and sample-based rarefaction curves.
thumbnail Fig. 4

Canonical correspondence analysis ordinations of aquatic beetles with respect to environmental factors in freshwater habitats of NWG.
thumbnail Fig. 5

Multiple correspondence analysis ordinations of aquatic beetles in relations to altitude classes.

4 Discussion

The literature-based list of aquatic beetles of Maharashtra (Sharma and Bano, 2012) is an underestimation (57 species) as the present survey revealed 66 species, including new records and discovery of new species (Sheth et al., 2018).

The species estimators Chao2, Jackknife1 and Bootstrap showed that almost 70–80% of the aquatic beetle diversity was recorded from the study region, suggesting more sampling in the area may reveal additional species. Earlier studies (Foggo et al., 2003; Padhye and Dumont, 2015; Kulkarni and Pai, 2016) showed that the non-parametric richness estimators provided more accurate and precise species richness estimate for freshwater invertebrates. Thakare and Zade (2011) used individual-based rarefaction and called it as sample-based rarefaction. Therefore, it is difficult to compare their results with present work. The majority of the beetle species collected are small to intermediate sized as many samples were collected from the marginal areas of the water bodies. Hence, a few open water species could have been neglected. Therefore, more sampling can improve the estimate of the true species richness, which was reflected in sample-based rarefaction.

Altitude is known to be a crucial geographical factor that changes characteristics of aquatic habitats and influences the composition of aquatic insects (Garrido et al., 1994; Touaylia et al., 2011) and other aquatic invertebrates (Williams et al., 2004). Within the area, C. hemani and L. lambai were found at higher altitudes, while L. andrewesi and L. ceylonicus at lower altitudes, and a few species like L. inefficiens were found along the entire altitudinal gradient in the study region. Similar patterns of species distributions were observed in Tunisian habitats by Touaylia et al. (2011). In a comparable work, in Colorado Rockies the caddisflies, mayflies and stoneflies showed association with altitude which may be related to the part of their life cycle affected by the altitude (Dodds and Hisaw, 1925). In the present work, differential altitudinal affinity of congeneric species of Lacconectus and Peschetius is interesting and may be related to specific microhabitat selection and dispersal abilities (Morris, 2003). Therefore, altitude can be considered as an important factor for species distribution of these beetles in NWG. Salinity is one of the stressors as a physiological constraint for the inhabitants affecting their distribution, abundance and diversity in aquatic ecosystems (Millán et al., 2011; Arribas et al., 2014). As an instance, hydraenids were the most abundant coleopterans found in natural saline streams in arid and semiarid regions of Spain (Millán et al., 2011). Similarly, tolerance to salinity evolved multiple times in hydrophilids and could have resulted because of drought resistance, which can be advantageous to avoid competition and risk of predation (Arribas et al., 2014). In the present work, a few species were frequently found in ponds with more salinity, suggesting that these species can be tolerant to higher salinity (Larson, 1985; Lancaster and Scudder, 1987; Céspedes et al., 2013). Hydroperiod is known factor for structuring aquatic beetle composition in freshwater habitats (Eyre et al., 1992; Lundkvist et al., 2001). In particular, the inhabitants of temporary freshwater habitats are tolerant of extreme environmental conditions such as dry phase which must be an evolutionary adaptation (Wiggins et al., 1980; Williams, 2006; Jocque et al., 2010). C. hemani, M. sabitae and L. lambai in this study were found to be associated with the temporary habitats. The affinity of H. arrowi observed in the present study to perennial water bodies is in support with Hickman (1931), Hilsenhoff and Brigham (1978) and Sheth et al. (2016). Haliplus immaculicollis and Haliplus longulus from Kendal pools in Ontario prefer temporary habitats to avoid risk of fish predation (Wiggins et al., 1980). Also, Fairchild et al. (2003) showed that hydroperiod along with microhabitat and landscape structure affect the aquatic beetle composition of ponds in northern Delaware, USA. Habitat selection thus plays an important role in structuring the distribution patterns of aquatic species and their communities (Morris, 2003). Therefore, the factors (see introduction) that affect composition of aquatic beetle communities in temperate region and those revealed in the present study of NWG appear to be similar.

The observed co-occurrence of laccophilines and hydroporines in different habitat types, their wide range of distribution in the study area and their position near centroids in CCA suggest that the species belonging to these two subfamilies can be generalists (Juliano and Lawton, 1990; Fairchild et al., 2000). Similarly, observed co-occurrence of C. hemani, M. sabitae and L. lambai may be related to their body shape and size, affecting their swimming and prey capture abilities (Ribera and Nilsson, 1995).

The work presented here provides baseline data to build ecological and biological hypotheses for the aquatic beetles of the Western Ghats. Additional studies on microhabitat preference, prey base, resource competition, egg laying and dispersal of the species will help to understand their dis tribution patterns; influence of landscape-level factors as land scape type (area of wetland, grassland or forest), conditions of shorelines of the biotopes, different spatial scales (e.g., first-, second- and third-order streams) will further help to interpret beetle communities in details.

Supplementary material

Supplementary material provided by the authors.

Access here

Acknowledgements

We are grateful to Dr. Anders Nilsson (Sweden) for initial comments on the manuscript, and Dr. Robert Angus (England) and Dr. Kelly Miller (USA) for linguistic corrections. Special thanks to Dr. Neelesh Dahanukar (IISER, Pune), Dr. Sameer Padhye (Belgium) and Dr. Félix Picazo (Spain) for help and support. SDS is thankful to her teammates for their valuable help in the field, Maharashtra State Biodiversity Board for collection permits and University Grants Commission (Delhi) for funding. A part of the work was supported by BCUD (Pune) funds. We are obliged to Dr. Anders Nilsson (Sweden), Dr. Jiri Hájek (Czech Republic), Dr. Martin Fikáček (Czech republic), Dr. Kelly Miller (USA), Dr. Lars Hendrich (Germany), Dr. Michael Balke (Germany), Dr. Olof Biström (Finland), Dr. Manfred Jäch (Austria), Dr. David Bilton (UK), Dr. Fernando Pederzani (Italy), Dr. Mario Toledo (Italy), Dr. Günther Wewalka (Austria), Stephen Baca (USA), Dr. Ignacio Ribera (Spain) and Dr. Grey Gustafson (USA) for sharing some older literature, their help in identification of aquatic beetles, comments on the taxonomic work, timely correspondence and encouragement. We acknowledge authorities of Abasaheb Garware College, Pune, Modern College, Pune, and Indian Institute of Science Education and Research, Pune, for providing the facilities. We are grateful to the reviewers for their criticisms.

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Cite this article as: Sheth SD, Padhye AD, Ghate HV. 2019. Factors affecting aquatic beetle communities of Northern Western Ghats of India (Arthropoda: Insecta: Coleoptera). Ann. Limnol. - Int. J. Lim. 55: 1

Appendix

Appendix 1

The list of sampling localities visited in and around the Northern Western Ghats, India.

Appendix 2

Mean and range values for water chemistry and altitude of water bodies in Northern Western Ghats of India.

All Tables

Table 1

The list of aquatic beetles from NWG with their relative occurrence and abbreviations.

In the text
Table 2

The observed and estimated species richness per habitat type within NWG.

In the text
Appendix 1

The list of sampling localities visited in and around the Northern Western Ghats, India.

In the text
Appendix 2

Mean and range values for water chemistry and altitude of water bodies in Northern Western Ghats of India.

In the text

All Figures

thumbnail Fig. 1

Sampling localities in and around the Northern Western Ghats.
In the text
thumbnail Fig. 2

Freshwater habitat types within the study area: A − pool (Tableland); B − pond (Korigad); C − tank (Harishchandragad); D − reservoir (Talegaon); E − rock puddle (Harishchandragad); F − stream (Harishchandragad).
In the text
thumbnail Fig. 3

Species richness estimation and sample-based rarefaction curves.
In the text
thumbnail Fig. 4

Canonical correspondence analysis ordinations of aquatic beetles with respect to environmental factors in freshwater habitats of NWG.
In the text
thumbnail Fig. 5

Multiple correspondence analysis ordinations of aquatic beetles in relations to altitude classes.
In the text

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