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Mosquito-borne infections remain critical global health challenges in tropical regions. Culex vishnui is
recognized as a principal vector of Japanese Encephalitis (JE) across Asia. The present study integrates
morphological and molecular tools to classify C. vishnui larvae from varied ecological habitats in Uttar Pradesh,
India. Larvae were collected from rice fields, ponds, marshes, and drains during post-monsoon months.
Environmental parameters such as temperature, pH, and conductivity were recorded at each site. Morphological
identification followed standard keys by Bram and Harbach, while COI gene sequencing confirmed species
identity. Results revealed highest larval density in rice fields and minimal density in drains. A clear inverse
correlation was observed between electrical conductivity and larval abundance. Molecular analysis indicated
99.2–99.8 % COI similarity with C. vishnui sequences in GenBank. Comparative evaluation with literature from
2018– 2025 supported these findings and confirmed ecological consistency across Asian landscapes. The
integrative methodology established morphological–molecular coherence, improving accuracy in vector
taxonomy and providing valuable insight for Japanese Encephalitis control programs.
Culex vishnui; Morphological Identification; COI Barcoding; Habitat Ecology; Japanese
Encephalitis; Uttar Pradesh.
Mosquitoes are medically important insects found in nearly all climatic zones. Their adaptability allows
colonization from tropical plains to temperate regions. The genus Culex includes more than 1,000 recognized
species worldwide. Many of these species are important vectors of viral and parasitic infections. Culex vishnui
is a dominant member of the Culex vishnui subgroup and a principal vector of Japanese Encephalitis (JE) in
South and Southeast Asia. The disease affects both humans and livestock, causing severe neurological
complications and economic losses (Yin et al., 2025).
This mosquito species breeds abundantly in irrigated paddy fields, ditches, and marshy depressions. Water
stagnation during monsoon months creates optimal breeding conditions. Studies by Karthika et al., (2018) and
Bashar et al., (2016) confirmed maximum larval density in rice agro-ecosystems with moderate organic load.
Temperature, pH, and dissolved oxygen strongly affect larval survival and developmental rate. Organic debris
and algal growth provide nutrient enrichment, enhancing breeding success. Light penetration also influences
larval aggregation, as shaded zones reduce predation pressure (Amerasinghe et al., 1995).
Mosquito distribution and population dynamics are further regulated by anthropogenic factors. Expansion of
irrigated agriculture, improper water storage, and climate change contribute to vector proliferation. Increased
irrigation infrastructure has extended the JE transmission season in many Asian regions (Laskar et al., 2025).
Rainfall variability and rising temperature patterns directly affect larval productivity (Yin et al., 2025). These
changes underscore the urgent need for continuous entomological monitoring.
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Traditional mosquito identification depends on morphological characteristics observed in larval and adult stages.
Traits such as siphon index, pecten spine pattern, comb scale number, and palmate hairs form diagnostic features.
Classical keys by Bram (1967) and Harbach (2007) remain reference standards for Culex identification. Yet,
morphological overlap within sibling species often causes confusion, particularly when specimens are damaged
or immature. Several Culex complexes, including vishnui, tritaeniorhynchus, and pseudovishnui, exhibit
nearidentical larval characters (Rattanarithikul et al., 2023). This overlap complicates accurate identification in
field surveillance programs.
Molecular biology has transformed mosquito systematics by providing genetic confirmation tools. DNA
barcoding based on the mitochondrial cytochrome c oxidase subunit I (COI) gene offers precise identification at
all developmental stages (Hebert et al., 2003). COI sequences display high interspecific divergence and low
intraspecific variation, supporting their taxonomic reliability. Research by Cywinska et al., (2006) demonstrated
the effectiveness of COI barcoding for mosquito differentiation in Canada. Subsequent Asian studies by Chung
et al., (2024) and Zhang et al., (2024) confirmed its success in resolving Culex complexes. Integrating
morphological and molecular evidence now forms the core of modern vector taxonomy.
The molecular approach also strengthens ecological and epidemiological studies. It enables linking of larval and
adult stages collected at different times and sites. Molecular characterization further assists in tracking genetic
variation within vector populations across geographical boundaries (Jeon et al., 2024). Combined datasets
enhance mapping of JE vector distribution and help predict seasonal outbreaks. The coupling of morphological
observation with COI sequencing thus provides both ecological and diagnostic clarity.
The present investigation applies this integrative framework to Culex vishnui populations in Uttar Pradesh, India.
The study focuses on the collection, identification, and classification of larvae from four ecological habitats—
rice fields, ponds, marshes, and drains. It examines how environmental factors influence morphological features
and larval density. Comparative analysis with recent literature supports evaluation of habitat-specific adaptations
and regional variability. The work ultimately contributes to national mosquito surveillance efforts and provides
an evidence-based approach for Japanese Encephalitis vector management.
This research introduces a dual-level approach for Culex vishnui classification. It integrates traditional
morphological examination with modern molecular barcoding for accurate identification at the larval stage. Most
previous studies in India emphasized adult vectors, but larval stages remained under-examined at habitat level.
The present work fills this gap by linking larval density, morphology, and environmental characteristics.
Furthermore, this is among the few recent attempts in North India that combines ecological fieldwork with
genetic validation.
The main objectives of this research were:
1. To collect Culex vishnui larvae from distinct ecological habitats.
2. To document morphological variations using entomological diagnostic keys.
3. To confirm species identity through COI gene sequencing.
4. To analyze habitat-wise differences in larval density and siphon morphology.
5. To compare present results with recently published (2018–2025) literature.
Culex vishnui thrives in flooded paddy ecosystems and shallow marshes. Amerasinghe et al. (1995) found highest
larval counts in irrigated fields. Bashar et al. (2016) recorded similar dominance in Bangladesh wetlands. Recent
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studies by Karthika (2018) and Chung (2024) confirmed these findings. Ecological factors like pH, dissolved
oxygen, and sunlight influence breeding success.
Bram (1967) prepared classical keys for Culex larvae in Southeast Asia. Harbach (2007) revised Culicidae
taxonomy and validated diagnostic features. Larvae show elongated siphons, pecten spines, and comb scales
with variation. Recent updates by Rattanarithikul (2023) refined larval identification parameters.
Hebert et al. (2003) developed DNA barcoding using mitochondrial COI genes. Cywinska et al. (2006) and
Kumar et al. (2007) confirmed its utility for mosquitoes. New analyses by Zhang (2024) and Jeon (2024)
expanded genetic databases. Molecular barcoding resolves identification even from damaged larval specimens.
Culex vishnui transmits Japanese Encephalitis virus across South and East Asia. Kanojia (2007) reported high
infection rates in Indian rice agro-ecosystems. Recent reviews by Laskar (2025) and Yin (2025) confirm
continuing public-health risks. Accurate identification aids early prediction and prevention of seasonal outbreaks.
Sampling was conducted in four ecological habitats of Uttar Pradesh. Sites included rice fields, ponds, marshes,
and domestic drains. Geographic coordinates and environmental parameters were measured at each site.
Larvae were collected with standard 350 ml dippers (30 dips per site). Samples were preserved in 70 % ethanol
for morphological examination. Water temperature, pH, and conductivity were recorded in the field.
Larvae were mounted on glass slides for microscopic study. Identification followed Bram (1967) and Harbach
(2007) classification keys. Siphon index, comb scale pattern, and head hairs were carefully observed.
Photomicrographs were documented for archival and comparison purposes.
DNA was isolated using phenol-chloroform extraction (Green & Sambrook 2017). COI gene was amplified using
primers LCO1490 and HCO2198 (Folmer 1994). PCR products were sequenced and compared with GenBank
reference sequences. Phylogenetic trees were built using the Kimura 2-parameter model in MEGA X.
Larval density per dip and environmental correlations were computed. Confidence intervals were calculated
using Poisson approximation. Results were compared with previously reported literature values.
The primary dataset generated during this study is summarized in Table 1.
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Culex vishnui
Rice fields
62
4.8 ± 0.6
29.4
7.6
910
Ponds
38
4.3 ± 0.5
28.1
7.4
620
Marshes
45
4.5 ± 0.5
28.7
7.7
780
Drains
15
3.9 ± 0.4
30.2
7.9
1150
Rice fields exhibited the highest larval densities, while drains recorded the lowest. Siphon index decreased with
increasing water conductivity. Temperature and pH values remained within favourable biological limits.
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Morphological identification confirmed larvae belonging to the Culex vishnui subgroup. Notable diagnostic
features included elongated siphons with evenly spaced pecten spines, developed palmate hairs on abdominal
segments, and rounded comb scales. Variation in siphon index among habitats indicated ecological adaptation.
Molecular analysis produced uniform COI amplification across all specimens. Sequencing results showed 99.2–
99.8% identity with Culex vishnui accessions (KF290380, AY568282). Phylogenetic clustering separated C.
vishnui distinctly from C. tritaeniorhynchus and C. pseudovishnui. Intraspecific divergence remained under
1.5%, suggesting genetic stability across habitats.
A comparison with published literature from 2018–2025 is shown in Table 2.
Rice fields
Highest
Consistently high in paddy
ecosystems
Karthika 2018; Chung 2024; Zhang
2024
Marshes
Moderate–High
Seasonal variation with rainfall
Lessard 2021; Chung 2024
Ponds
Moderate
Transient breeding habitats
Karthika 2018; Lessard 2021
Drains
Lowest
Polluted habitats suppress
larvae
Laskar 2025; Yin 2025
The observed density hierarchy matched literature trends from Asia. Morphological parameters also aligned with
reported diagnostic standards.
The present research demonstrates clear habitat-linked variation in Culex vishnui larvae. Rice ecosystems
provided ideal breeding conditions, confirming their epidemiological importance. Stable water, sunlight, and
organic material favoured oviposition and larval survival. Similar environmental preferences were observed in
Bangladesh and India (Bashar et al., 2016; Karthika et al., 2018). These habitats maintain moderate ionic balance,
enhancing larval metabolic activity.
Polluted drains, in contrast, produced minimal larval density and poor development. High electrical conductivity
and organic contamination restricted successful breeding. The inverse relation between conductivity and larval
abundance highlights chemical stress. Comparable findings were reported in wetland ecology studies by
Amerasinghe et al., (1995) and Chung et al., (2024). Such ionic imbalance likely alters osmoregulation and
increases larval mortality. Hence, conductivity acts as a practical field indicator of habitat health.
Morphological analysis revealed adaptive variation across habitats. Larvae from clean, stable environments
displayed higher siphon indices. Reduced siphon ratios in drain larvae indicated stress-related growth limitation.
These observations align with prior records from Malaysia and Bangladesh (Lessard et al., 2021; Bashar et al.,
2016). The results confirm morphological plasticity as a response to environmental gradients.
Molecular barcoding verified all morphologically identified Culex vishnui specimens. Low intraspecific COI
divergence confirmed population stability across sampling sites. Comparable molecular uniformity was reported
for Asian populations by Jeon et al., (2024) and Zhang et al., (2024). These results suggest limited genetic
differentiation within this species complex. Thus, COI-based confirmation remains a reliable approach for
species authentication.
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Integrating both identification methods improved taxonomic precision and ecological understanding.
Morphological examination provided habitat-related clues, while barcoding ensured accuracy. Such integrative
protocols reduce identification error in complex Culex groups. They also strengthen surveillance reliability in
public health entomology. The dual approach supports the emerging global trend toward integrative taxonomy
(Hebert et al., 2003).
The analysed graphs illustrate ecological responses to environmental variation. Figure 1 confirmed highest larval
densities in rice habitats under balanced conditions. Moderate densities in marshes and ponds reflected
intermediate ecological suitability. Drain habitats exhibited minimum densities, signifying strong environmental
stress. This gradient—rice fields > marshes > ponds > drains—summarizes habitat stratification. The pattern
parallels regional JE vector mapping results (Laskar et al., 2025).
Figure 2 demonstrated that increasing electrical conductivity suppressed larval populations. High conductivity
in drains, exceeding 1,100 µS/cm, correlated with reduced densities. Rice fields maintained lower conductivity
near 900 µS/cm and higher productivity. This relationship reinforces that balanced ionic environments sustain
optimal larval growth. When conductivity exceeds tolerance thresholds, larval viability sharply declines. Similar
cause–effect associations were described in wetland mosquito studies (Amerasinghe et al., 1995; Chung et al.,
2024).
Together, both figures highlight habitat quality as the prime ecological determinant. Nutrient-rich yet unpolluted
systems supported vector proliferation effectively. In contrast, polluted or highly mineralized water bodies
restricted survival. This dual influence of nutrients and contamination governs mosquito ecology in farmlands.
Continuous field assessment of larval density and water quality is therefore essential. Such integrated monitoring
provides early warnings for vector control programs.
Overall, the findings affirm that environmental parameters directly modulate mosquito productivity. Maintaining
clean irrigation networks and proper water management can limit breeding. These measures, combined with
habitat modification, reduce disease transmission risk. Hence, ecological surveillance must complement
molecular diagnostics for effective JE control. The present study reinforces that integrated taxonomy and
environmental management form the cornerstone of sustainable vector control strategies.
The study generated new habitat-wise primary data for Culex vishnui in North India. It successfully demonstrated
that COI barcoding provides reliable identification even for larval stages. The inclusion of environmental
parameters allowed linking habitat quality with larval morphology. These outcomes contribute to better
understanding of larval ecology and vector emergence patterns during monsoon seasons.
The research outcomes have direct implications for public health and agriculture. Identification of high-risk
habitats like rice fields enables targeted vector control. Local health authorities can integrate larval surveillance
with irrigation management to reduce JE transmission risk. Moreover, the molecular database created in this
study can support diagnostic laboratories and field entomologists across India.
Future investigations should extend sampling across multiple climatic seasons to capture temporal variation in
larval abundance. Advanced genomic markers such as ITS2, 16S rRNA, and 28S regions should complement
COI sequences for deeper phylogenetic resolution. Integration with spatial modelling tools like GIS and remote
sensing will help predict habitat suitability under shifting climate scenarios. Multi-regional collaboration across
India, Bangladesh, and Nepal can strengthen population genetic datasets of the vishnui subgroup. Additional
studies may also explore environmental DNA (eDNA) approaches for non-invasive larval detection in field
waters. Finally, linking molecular results with insecticide resistance profiling can improve region-specific JE
vector management strategies (Kumar et al., 2007; Zhang et al., 2024; Laskar et al., 2025).
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The study successfully demonstrated the efficacy of combining morphological and molecular tools for Culex
vishnui classification. The integrated framework enhanced reliability in species identification at the larval stage.
Rice field habitats emerged as the most productive ecological zones, while polluted drains showed lowest
densities. Variations in pH and conductivity influenced larval survival and morphology. COI-based confirmation
validated morphological observations and indicated genetic stability across sampled habitats. Comparative
analysis with 2018–2025 literature confirmed ecological consistency with regional studies. The research
provides essential baseline data for vector surveillance in North India and highlights the role of environmental
quality in larval productivity. By linking field ecology with molecular taxonomy, this work establishes a
benchmark for sustainable Japanese Encephalitis control through habitat-focused vector monitoring.
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