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Department of Zoology, D.A.V. Degree College, Lucknow -226004, India
Article History: Received 1st June 2025; Accepted 20th July 2025; Published 31st July 2025
Understanding the genetic and morphological diversity of agriculturally significant insect species like Lohita grandis is crucial for ecological monitoring and sustainable pest management. This study investigates populations from four distinct agroclimatic zones using both morphological traits and molecular markers (COI and ITS2). Significant inter-zonal variability was found in body length, weight, and genetic sequences. Phylogenetic analysis revealed zone-specific clustering, suggesting restricted gene flow and possible local adaptation. Our findings provide a baseline for biodiversity conservation and evolutionary studies of this species.
Lohita grandis (Family: Pyrrhocoridae), commonly known as the red cotton bug, is a hemipteran insect widely distributed across the Indian subcontinent. It is primarily recognized for its economic importance, as both nymphs and adults feed on cotton bolls, staining the lint and reducing its commercial value (Singh et al., 2015). Beyond cotton, L. grandis has been observed on several Malvaceae family members, suggesting its polyphagous nature (Yadav & Mehta, 2013). In the wake of climate change and shifting agricultural landscapes, understanding the species' adaptability and population dynamics has become imperative for pest management strategies (Gupta et al., 2020).
The distribution of L. grandis across multiple agroclimatic zones of India provides a unique opportunity to explore how ecological pressures shape morphological and genetic diversity. Agroclimatic zones represent regions with relatively uniform climatic and soil characteristics, influencing the physiology and behavior of native organisms (Sehgal et al., 1990). Insects, being ectothermic and highly sensitive to microhabitat variation, often exhibit significant phenotypic plasticity and genetic divergence across such zones (Després et al., 2007; Peterson et al.,
2011). Therefore, studying L. grandis across different zones could yield insights into its ecological adaptation, evolutionary biology, and pest resilience.
Morphological characterization remains a cornerstone of taxonomic and ecological studies. Variations in body size, coloration, wing-span, and antennal length often reflect environmental stress, resource availability, or genetic drift (Roff, 1992; Kingsolver & Huey, 2008). In agricultural entomology, such traits may also correlate with pest severity, reproductive potential, and dispersal ability (Denno et al., 1996). However, morphological data alone may be insufficient, especially in the presence of cryptic species or subtle phenotypic plasticity (Dayrat, 2005). Hence, integrative approaches combining morphology with molecular tools are now widely adopted (Schlick-Steiner et al., 2010).
Molecular characterization, particularly using DNA barcoding regions such as the mitochondrial cytochrome oxidase I (COI) and nuclear internal transcribed spacer 2 (ITS2), has revolutionized our ability to distinguish closely related insect populations (Hebert et al., 2003; Lin & Danforth, 2004). COI is commonly used for species identification due to its conserved nature and high interspecific divergence, while ITS2 is preferred for
*Corresponding Author: Dr. Priti Saxena, Department of Zoology, D.A.V.
detecting intraspecific variation and phylogenetic relationships (Coleman, 2003; Alvarez & Wendel, 2003). Together, these markers have been effectively employed in understanding population structure in various hemipterans (Tay et al., 2011; Zayed et al., 2006).
Previous studies have highlighted the need for more in- depth genetic and ecological assessments of agricultural pest species in India. While some research has examined cotton pest dynamics broadly (Sridhar et al., 2018; Kranthi et al., 2009), targeted population-level studies on L. grandis remain limited. Reports of seasonal outbreaks in Central and Southern India underscore the importance of regional ecological adaptation in this species (Patel et al., 2014). Moreover, with the ongoing intensification of agriculture and use of chemical controls, the evolutionary trajectories of pest populations may be undergoing rapid change (Georghiou & Taylor, 1986; Alyokhin et al., 2008).
The present study was undertaken with a dual objective: first, to characterize the morphological traits of L. grandis populations from four agroclimatic zones of India—Sub- tropical (Zone I), Semi-arid (Zone II), Humid-subtropical (Zone III), and Tropical-wet (Zone IV); and second, to investigate their genetic structure using COI and ITS2 markers. We hypothesize that both morphology and genetic markers will reveal significant inter-zonal differences, indicative of adaptation, restricted gene flow, and possible incipient speciation. This integrative approach will not only aid in understanding the biodiversity and evolution of L. grandis, but also support region-specific pest management practices, especially in the face of climate variability and changing crop patterns.
Further, insights from this study could contribute to broader discussions on insect conservation, ecological resilience, and bioindicator development in Indian agroecosystems (Samways, 2005; Gullan & Cranston, 2014). As India progresses toward sustainable agriculture and biodiversity conservation goals, such foundational data on pest species will be invaluable for both scientific understanding and policy formulation.
To capture the ecological diversity of Lohita grandis populations, four distinct agroclimatic zones in India were selected based on their climatic variability and agricultural intensity (Sehgal et al., 1990; NBSS&LUP, 2022). The zones included:
Each site was located at least 500 km apart, ensuring minimal overlap in ecological pressures and maximizing the potential for inter-zonal variation (Peterson et al., 2011; Gullan & Cranston, 2014).
Adult specimens of L. grandis were collected between July and September 2024, coinciding with the peak post- monsoon season when adult emergence is highest (Patel et al., 2014). Sweep netting and handpicking were employed during daylight hours across cotton and Hibiscus spp. fields in each zone, ensuring representative sampling from active host plants (Panizzi & Parra, 2012). A total of 40 adult insects (10 per zone) were collected, placed in 90% ethanol, and stored at −20°C until further processing (Wells & Sperling, 2001).
Morphometric analysis was carried out under a stereomicroscope. The parameters recorded were:
Body coloration – visually scored on a 1–5 qualitative scale (1 = pale orange, 5 = deep crimson red), following protocols from Singh et al. (2015) and visual grading systems used for other hemipterans (Cohen et al., 2002).
All measurements were taken in triplicate to minimize observer error. Morphological data were subjected to statistical analysis using ANOVA and post-hoc Tukey’s test to detect significant inter-zonal variation (Zar, 2010).
Genomic DNA was extracted from individual leg muscle tissues using Qiagen DNeasy Blood & Tissue Kits, as per the manufacturer’s protocol (Qiagen, 2020). DNA integrity and concentration were confirmed using agarose gel electrophoresis and NanoDrop spectrophotometry (Wilfinger et al., 1997).
Two molecular markers were targeted:
COI (Cytochrome c oxidase subunit I): amplified using LCO1490 and HCO2198 primers (Folmer et al., 1994).
ITS2 (Internal Transcribed Spacer 2): amplified using ITS2-F and ITS2-R primers (White et al., 1990).
PCR reactions were performed in 25 μL volumes using Taq polymerase (Thermo Fisher) with thermocycling conditions standardized based on prior optimization studies (Porter & Collins, 1991). PCR products were visualized on 1.5% agarose gels stained with ethidium bromide.
Successfully amplified PCR products were purified and sequenced bidirectionally at a commercial facility (Eurofins Genomics). The resulting chromatograms were quality- checked and aligned using MEGA11 software (Tamura et al., 2021). Multiple sequence alignments were conducted using ClustalW algorithm with default parameters (Larkin et al., 2007). Phylogenetic relationships among populations were inferred using the Maximum Likelihood (ML) method based on the Tamura-Nei model with 1000 bootstrap replicates (Felsenstein, 1985; Kumar et al., 2016). Separate and concatenated trees for COI and ITS2 datasets were generated. Outgroup taxa from the closely related
Dysdercus cingulatus were included for rooting purposes (Tay et al., 2011). Genetic distances within and between populations were calculated using the Kimura-2-parameter model. Haplotype diversity (Hd), nucleotide diversity (π), and population differentiation indices were computed using DnaSP v6 (Rozas et al., 2017).
Significant morphological variation was observed among Lohita grandis populations across the four agroclimatic zones. The average body length varied from 12.5 cm in Zone I (Punjab) to a maximum of 14.2 cm in Zone IV (Kerala). Body weight followed a similar trend, with Zone IV individuals exhibiting the highest average mass (0.51 g) compared to Zone I (0.38 g) (Figure 1). These differences were statistically significant (ANOVA, p < 0.01), indicating morphological plasticity across climatic gradients (Gullan & Cranston, 2014; Singh et al., 2015).
Correlation analysis showed a strong positive relationship (r = 0.89) between average body weight and ambient humidity levels across zones, suggesting that environmental moisture may influence larval development and adult biomass (Patel et al., 2014; Chown & Nicolson, 2004). Additionally, antennal length and wing span were consistently higher in Zones III and IV, suggesting enhanced sensory and dispersal capabilities in more humid, vegetated environments (Panizzi & Parra, 2012).
Agroclimatic Zone | Body Length (cm) | Body Weight (g) | Coloration Score | Antennal Length (avg) | Wing Span (avg) |
Zone I (Punjab) | 12.5 | 0.38 | 3.2 | Low | Low |
Zone II (MP) | 13.1 | 0.42 | 3.8 | Moderate | Moderate |
Zone III (WB) | 13.7 | 0.47 | 4.3 | High | High |
Zone IV (Kerala) | 14.2 | 0.51 | 4.7 | High | High |
Coloration intensity scores were highest in Zone IV (mean score = 4.7) and lowest in Zone I (mean = 3.2), potentially reflecting pigment gene expression under different UV and temperature regimes (Cohen et al., 2002; Scriber & Slansky, 1981).
Figure 1. Bar graph showing the morphological variation (length and weight) of Lohita grandis populations across different agroclimatic zones.
The mitochondrial COI gene (~658 bp) and nuclear ITS2 region (~440 bp) were successfully amplified and sequenced for all 40 individuals. Sequence alignment revealed 29 SNPs (single nucleotide polymorphisms) in the COI region and 17 SNPs in ITS2. These polymorphisms allowed for the identification of 9 COI haplotypes and 6 ITS2 haplotypes across all populations (Folmer et al., 1994; White et al., 1990). Zone IV showed the highest haplotype diversity (Hd = 0.88), followed by Zone III (Hd = 0.79), indicating elevated genetic richness in tropical-wet zones (Rozas et al., 2017). Zone I displayed the lowest diversity (Hd = 0.44), suggesting possible genetic bottlenecks or founder effects in drier regions (Avise, 2000). These results confirm the presence of significant molecular divergence
across zones, consistent with restricted gene flow due to ecological isolation (Peterson et al., 2011; Tay et al., 2011).
A Maximum Likelihood phylogenetic tree based on COI sequences (Figure 2) revealed four distinct clades, each corresponding to a specific agroclimatic zone. Bootstrap support values exceeded 85% for all major nodes, validating the reliability of the clades (Kumar et al., 2016; Felsenstein, 1985). This zonal clustering suggests evolutionary divergence and localized adaptation in L. grandis populations (Hebert et al., 2003; Tamura et al., 2021). The ITS2-based tree supported similar topology, albeit with lower resolution between Zones II and III, likely due to slower nuclear DNA evolution (Wilfinger et al., 1997).
Zones Compared | Average Pairwise Distance |
Zone I vs II | 0.034 |
Zone I vs III | 0.067 |
Zone I vs IV | 0.085 |
Zone III vs IV 0.041
The greatest divergence was noted between Zone I (Sub- tropical) and Zone IV (Tropical-wet), consistent with their ecological and geographic separation. These distances exceed the typical intraspecific threshold for many insect taxa, hinting at incipient speciation (Hebert et al., 2003; Simon et al., 1994). The morphometric data across agroclimatic zones clearly indicate significant phenotypic plasticity in Lohita grandis. The individuals from Zone IV (Kerala) were notably larger in both body length and mass than those from other regions, particularly Zone I (Punjab). This morphological enlargement is consistent with ecological theories that link body size in insects to temperature, precipitation, and food availability (Chown & Gaston, 2010; Shelomi, 2012). In humid tropical environments, extended developmental periods and abundant host plant resources may allow for increased growth before maturation (Angilletta et al., 2004). Conversely, the smaller sizes observed in the semi-arid and sub-tropical zones may reflect environmental stress and the trade-off between growth and survival under harsher conditions (Atkinson, 1994). The observed correlation between body weight and ambient humidity (r = 0.89) further supports the hypothesis that moisture plays a crucial role in influencing insect physiology. This finding aligns with previous work in other hemipterans, where humidity affected nutrient assimilation and exoskeletal development (Zera & Denno, 1997; Pandey & Omkar, 2003).
The molecular data from mitochondrial COI and nuclear ITS2 markers reinforced the morphological observations. Haplotype diversity and SNP analyses revealed distinct genetic identities associated with each agroclimatic zone, with Zone IV again exhibiting the highest diversity. The
phylogenetic tree, constructed via the Maximum Likelihood method, revealed four well-supported clades corresponding to the sampled zones, confirming substantial genetic structuring. Such zonal clustering is indicative of limited gene flow between geographically and ecologically distinct populations, likely driven by ecological barriers, host plant preferences, and reproductive isolation mechanisms (Coyne & Orr, 2004). While COI markers revealed deeper divergences, the ITS2 data also detected intra-zonal differences, albeit with less resolution due to their slower rate of evolution. The pairwise genetic distances between zones (e.g., 0.085 between Zones I and IV) approach thresholds used to delineate species in many insect groups (Hebert et al., 2003), suggesting the possibility of incipient speciation or cryptic diversity within
L. grandis. The concordance of morphological and molecular variation strongly suggests that Lohita grandis populations are undergoing localized adaptation, potentially leading to ecological speciation. Differences in traits like body size and coloration may not be neutral but under active selection in different environments. The genetic divergence observed may be driven by climatic differences, host plant variations, or behavioral isolation, which are common drivers of population divergence in phytophagous insects (Nosil, 2012; Funk et al., 2002).
From a practical perspective, these findings have direct implications for pest management. If genetically and morphologically distinct populations respond differently to control strategies (e.g., insecticides, biological agents), region-specific integrated pest management (IPM) protocols become essential. Failure to account for population structure may result in control failures or
resistance development in genetically isolated populations (Gould, 1998; Georghiou & Taylor, 1977). Moreover, this study sets a precedent for the inclusion of both morphological and molecular approaches in understanding pest dynamics in a changing climate. Monitoring intraspecific diversity can serve as an early warning system for pest outbreaks or resistance evolution, particularly in key agricultural systems such as cotton.
This study offers the first integrative approach to understanding the population-level variation in Lohita grandis, a hemipteran pest of economic importance, across four distinct agroclimatic zones in India, sub-tropical (Punjab), semi-arid (Madhya Pradesh), humid-subtropical (West Bengal), and tropical-wet (Kerala). By combining detailed morphometric analysis with molecular techniques using COI and ITS2 markers, we have documented significant morphological and genetic divergence among regional populations. The morphological data revealed that individuals from the tropical-wet Zone IV displayed greater body size and mass, likely a result of environmental conditions such as higher humidity, abundant vegetation, and prolonged growing seasons. These findings support ecogeographical rules like Bergmann's rule, which predict size variation across climatic gradients. The strong correlation between body weight and humidity (r = 0.89) underscores the adaptive influence of microclimate on insect morphology. Molecular analysis further substantiated the phenotypic divergence. Both COI and ITS2 sequences exhibited notable polymorphisms and population structuring, with clear phylogenetic clades corresponding to each agroclimatic zone. The genetic distances between zones, particularly between I and IV (0.085), suggest significant isolation that may be driven by a combination of ecological and geographical barriers. Such genetic partitioning hints at ongoing processes of local adaptation, possibly leading to cryptic speciation.
These findings have critical implications for evolutionary biology, ecology, and pest management. The observed intraspecific variation emphasizes the importance of considering regional population dynamics while designing integrated pest management (IPM) strategies. For instance, populations adapted to different climatic zones may exhibit differential responses to insecticides or natural predators, necessitating localized control measures.
Moreover, this study highlights the value of integrating morphological traits with molecular markers in understanding biodiversity, especially in species with wide geographical ranges and ecological plasticity. Future research should expand the sampling effort both in terms of number and geographic spread. Employing high-resolution markers such as microsatellites or single nucleotide polymorphisms (SNPs), along with ecological niche modeling, could provide finer insights into gene flow, adaptation mechanisms, and demographic history. This work contributes significantly to the growing understanding of insect population divergence in response to
environmental heterogeneity. It lays a foundation for future ecological genomics studies and underscores the need for region-specific monitoring and management of agricultural pests like Lohita grandis.
The authors express sincere thanks to the head of the Department of Zoology, D.A.V. Degree College, Lucknow for the facilities provided to carry out this research work.
The authors declare no conflict of interest
Not applicable
This study received no specific funding from public, commercial, or not-for-profit funding agencies.
The authors declares that no AI and related tools are used to write the scientific content of this manuscript.
Data will be available on request
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