Ecological insights and conservation strategies for the data-deficient Indian horseshoe crab Tachypleus gigas (Müller, 1785) along the Odisha coast, India

Ecological insights and conservation strategies for the data-deficient Indian horseshoe crab Tachypleus gigas (Müller, 1785) along the Odisha coast, India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Ecological insights and conservation strategies for the data-deficient Indian horseshoe crab Tachypleus gigas (Müller, 1785) along the Odisha coast, India Biswajeet Panda, Arabinda Singha, Atchuthan Purushothaman, Kumaralingam S. This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6659913/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Sep, 2025 Read the published version in Environmental Monitoring and Assessment → Version 1 posted 4 You are reading this latest preprint version Abstract This study focuses on the conservation of Tachypleus gigas (Müller), a marine chelicerate of ecological significance, threatened by habitat degradation, pollution, and fishing activities along the Odisha coastline. Listed as ‘Data Deficient’ by the IUCN, T. gigas populations face severe risks, necessitating targeted conservation measures. The study objective is to (1) assess environmental factors influencing T. gigas distribution and survival, (2) evaluate the effectiveness of rescue and relocation efforts, and (3) engage local communities in conservation. A total of 483 individuals were rescued from fishing zones and relocated to protected areas to support population recovery. Field surveys (July 2023–March 2024) at ten stations (five rescue and five relocation sites) revealed that seasonal salinity variations, driven by monsoon influx and pre-monsoon evaporation, significantly influenced habitat suitability and reproductive success. Morphometric analyses indicated positive allometric growth in carapace length (R² = 0.79), width (R² = 0.79), and telson length (R² = 0.59), supporting locomotion, defense, and reproduction. Rescues varied seasonally and spatially, with lunar phases influencing distribution. Principal Component Analysis highlighted salinity, temperature, and sediment composition as key drivers of T. gigas distribution, with organic carbon levels correlating positively with T. gigas counts during the monsoon. Monsoonal shifts in sediment composition and water quality altered benthic ecosystems, impacting long-term habitat suitability. Despite these findings, ghost net entanglement remained a critical threat, with 40.7% of fishermen discarding trapped crabs. Community engagement, including educational outreach to 235 fisherfolk, was crucial in garnering support for protected no-fishing stations. Post-relocation monitoring indicated a 72.5% survival rate over six months, reinforcing the effectiveness of targeted conservation. This study underscores the need for an interdisciplinary approach integrating long-term monitoring, habitat restoration, stricter fishing regulations, and community participation to ensure T. gigas resilience. Marine conservation community engagement habitat degradation coastal intertidal zones environmental monitoring Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Human activities have drastically enhanced species extinction rates, driving the planet toward what many scientists describe as the sixth mass extinction (Keith et al., 2014; Nelson, 2024). Habitat destruction, pollution, overexploitation, and climate change have significantly disrupted ecosystems, threatening countless species and the essential services they provide to humanity. Despite the urgency, many species remain underrepresented on the IUCN Red List, underscoring the critical need for focused conservation efforts to ensure their survival (Miqueleiz-Legaz 2021). Over the years, marine biodiversity in India has been increasingly threatened by habitat destruction, pollution, and overfishing, leading to the decline of numerous species (Prakash and Verma, 2022). According to the 2023 update of the IUCN Red List, more than 950 animal species in India are classified as threatened, spanning both terrestrial and marine ecosystems. Specifically, within marine biodiversity, studies have identified 50 marine fish species as threatened, with an additional 45 species categorized as near-threatened (Sudhi 2012; IUCN 2023). Among these vulnerable marine organisms, Tachypleus gigas ( T. gigas ), commonly known as the Indian horseshoe crab, is one such species requiring urgent attention. This marine chelicerate arthropod, belonging to the family Limulidae, is often referred to as a "living fossil" due to its remarkable evolutionary stability over 500 million years (Sekiguchi et al., 1988; Sadava et al., 2009; Botton et al., 2021). Originating in the Ordovician period, T. gigas has retained its distinctive anatomy, including its horseshoe-shaped carapace and spike-like telson, which aid in navigation, orientation, and defense (Chiu & Morton, 2003; Kumar et al., 2016; Haque et al., 2024). In India, T. gigas is predominantly found along the northeastern coastline, particularly in Odisha, Andhra Pradesh, and West Bengal (Basudev et al 2013). Odisha, in particular, harbors the largest population of T. gigas (Behera et al., 2015), yet the species is classified as "Data Deficient" by the IUCN. This re-lack of data complicates conservation efforts, as population trends and distribution patterns remain poorly understood (Chatterji, 1994a, b; Pati et al., 2022). Historically abundant along Odisha's coast, reports suggest a significant decline in T. gigas populations (Behera et al 2015) over the past two decades due to habitat loss, pollution, and other anthropogenic pressures (Alam, 2007; Kandasamy, 2017; Yadav et al 2022). The coastal habitats of Odisha play a critical role in the life cycle of T. gigas , particularly for spawning and juvenile development (Nelson et al., 2015; 2016a; b; Fairuz-Foziet al., 2018; John et al., 2018). These intertidal zones, including estuaries and mudflats, provide essential ecological services, but are increasingly threatened by human activities such as sand mining, coastal development, pollution, and fishing activies. These disturbances have altered sediment composition and disrupted the ecological balance necessary for successful reproduction (Zauki et al., 2019; Pati et al., 2020b). In addition, horseshoe crabs face significant threats from entanglement in fishing nets, particularly ghost nets, which are a major cause of mortality (Goodman et al., 2020). These abandoned or discarded nets often trap horseshoe crabs, leading to entanglement, injury, and death. While the crabs can occasionally damage ghost nets, the larger concern lies in the harm these nets inflict on the species, intensifying its conservation challenges and creating economic difficulties for local fishermen. Currently, Tachypleus gigas is listed under Schedule IV of the Indian Wildlife (Protection) Act, 1972, which offers some degree of legal protection but does not prioritize the species for the highest conservation measures. The penalties for violations under Schedule IV are minimal compared to those for species listed under Schedule I, reserved for the most critically endangered species. This highlights the urgent need for stronger legal frameworks and enforcement to ensure the effective protection of T. gigas . Furthermore, the lack of awareness among local communities about the species' ecological significance exacerbates these threats, emphasizing the critical need for targeted educational outreach and conservation programs (Pati et al., 2017). Tachypleus gigas plays a vital role in the marine food web, serving as a key food source for migratory birds and supporting marine biodiversity by providing habitat for other organisms (Botton & Loveland, 2003; Sikorski et al., 2020). Despite its ecological importance, T. gigas remains understudied, particularly in India. Research has highlighted its reproductive behaviour (Alam et al., 2015; Pati et al., 2015; Nelson et al., 2016a; b; Biswal et al., 2016; John et al., 2018; Shingate et al., 2020) but threats such as commercial exploitation persist. In Odisha, T. gigas is used in health tonics, handicrafts, and as an aphrodisiac, further endangering its population (Mishra, 2009a, b; Mondal & Bandyopadhyay, 2014; Pati et al., 2020a). Moreover, its perivitelline fluid, with potential biomedical applications, further underscores the species' importance (Mirshahi et al., 2011; Pati et al., 2015). These studies have also explored its spatial-temporal patterns, population dynamics, and habitat preferences, revealing insights into its ecology and the threats from human exploitation (Tripathy et al., 2013; Yennawar, 2015; Pati et al., 2015; Zauki et al., 2019; Pramanik et al., 2021). Given the escalating threats to Tachypleus gigas , targeted conservation efforts have become crucial. Recent media reports highlight the large-scale exploitation of horseshoe crab Tachypleus gigas along the Odisha coast, raising urgent conservation concerns. Recommendations from the Department of Science and Technology, Government of India, have called for the inclusion of this species under the Indian Wildlife (Protection) Act, 1972. This would provide the necessary legal protection to mitigate threats and support conservation efforts (Chatterji, 1999; Behera et al., 2015; Rajesh et al., 2019; Pati et al., 2022). Such legal protections would be particularly critical during the peak spawning season, coinciding with India's no-fishing period (Pati et al., 2015; John et al., 2018). Recognizing significant gaps in conservation efforts and community engagement, this study was designed to address these challenges through a comprehensive approach. Conducted between July 2023 and March 2024, the initiative employed a multi-faceted strategy focusing on habitat rescue and relocation, community involvement, environmental monitoring, and raising awareness. Recognizing significant gaps in conservation efforts and community engagement, this study was designed to address these challenges through a comprehensive approach. While much past research has centered on the species' ecology, there has been limited focus on the role of local communities and their involvement in sustainable conservation strategies. The findings of this study have been reported in ZOO'S PRINT by one of the study authors (Patra et al., 2024), who detailed the programs conducted as part of the study. However, in this article, we focus on the environmental influences on T. gigas and provide a more in-depth exploration of community engagement and the programs implemented to foster conservation. Methodology Study area The study was conducted in Balasore, also referred to as Baleswar, a district located in the state of Odisha, covering an 88 km² area (Figure 1). Located in the northeast Bay of Bengal, where capture fisheries and T. gigas (horseshoe crab) bycatch are common, human-wildlife interactions occur frequently among the Odia community in Odisha. Data Collection The collection and study of Tachypleus gigas specimens were conducted following the necessary regulatory approvals. Fieldwork was carried out with institutional and governmental permissions, ensuring compliance with ethical and conservation guidelines. The research received funding support through a conservation initiative and was implemented in partnership with a local environmental organization actively involved in marine biodiversity protection. The study was conducted between July 2023 and March 2024 at ten stations, categorized into five rescue stations and five relocation stations. The rescue stations included 4000, Kasafal, Parikhi, Chandipur, and Dagra, where horseshoe crabs were identified and rescued. These stations were selected based on observed habitat disturbances, particularly the entanglement of T. gigas in ghost fishing nets, habitat degradation due to coastal erosion, and increased anthropogenic activities such as unregulated fishing and shoreline development. The relocation stations, consisting of Hanskara, Inchudi, Inchudi 1, Dublagadi, and Dublagadi 1, were determined through surveys with local communities, universities, schools, and with forest officials to identify suitable habitats for conservation efforts. This nested design allowed for systematic observation and assessment of habitat conditions and the effectiveness of conservation interventions across different ecological zones (Figure 1). Sampling was carried out in three seasonal phases: July to September 2023 (Monsoon – MON), October to November 2023 (Post-monsoon – PM), and December 2023 to March 2024 (Pre-monsoon – PreM). Fieldwork involved species identification, station surveys, data analysis, the inauguration of the Horseshoe Crab Conservation Campaign, community knowledge assessments, engagement efforts, and beach clean-up operations. Sampling at each rescue station was conducted once a month over two consecutive days, with three stations sampled each day and two stations on alternate days when feasible, particularly in estuarine areas where habitats were disturbed and the largest numbers of T. gigas were caught in gillnet fisheries, as identified through stations surveys and interviews with local fishermen. Collected T. gigas were identified using their morphometric characteristics, and their numerical counts were recorded. The identification of T. gigas species was achieved by matching morphological characteristics with standard descriptions (Suparta 1922). The relative abundance of T. gigas was estimated based on the number of individuals captured in monofilament gill nets used by local fishers. This data allowed for the analysis of the proportion of male and female T. gigas caught and provided an estimate of their relative abundance. Each measured T. gigas was marked with a pin label to avoid duplicate measurements upon recapture. After measurement, the T. gigas were released into the protected relocation stations. Specific morphological features (cm) observed are illustrated in Figure 2 and Table 1. At the rescue stations, environmental parameters were recorded to assess habitat conditions. These included sediment texture (sand silt and clay), sediment organic carbon, seawater pH, dissolved oxygen (DO), salinity and temperature. Data collection was carried out fortnightly during the new moon and full moon high tides at the rescue stations. Monitoring of T. gigas populations was carried out every 2–3 days across all study months. Both live and dead T. gigas were counted to evaluate survival and mortality rates. Dead specimens were marked with white or yellow paint to prevent repeated counts and ensure accurate population assessments. These specimens were later removed from the field and handed over to the Chief Wildlife Warden for proper documentation and handling. Data Collection on Community Knowledge A month-long survey conducted in July 2023 aimed to assess community awareness about T. gigas at several key locations: Kasafal, Parikhi, Chandipur, and Dagra, with 235 respondents participating. The respondents were divided into three age groups: 18–34 years (Group 1), 35–44 years (Group 2), and 45–54 years (Group 3) (Supplementary Figure 1C and D). They were further classified by occupation into two main categories: Fisherfolk (both men and women) and the General Public. The survey aimed to assess local knowledge regarding T. gigas , its cultural significance, and its role in the ecosystem. Questions were designed to examine the level of awareness about the species and the impact of horseshoe crab by-catch on local fisheries. The analysis explored how factors such as age, education, and occupation influenced people's interactions with T. gigas in the context of fishing practices and broader environmental changes. This allowed the study to identify key demographics that were more or less informed about conservation issues and their attitudes toward sustainable fishing. Environmental Monitoring and sediment Analysis Sediment samples were collected from three square quadrats, each measuring 15 cm × 15 cm, at each rescue station throughout the study months. During these months, seawater quality parameters were measured in situ using a digital thermometer, refractometer, pH meter, and dissolved oxygen (DO) meter. The sediment grain size was measured using the pipette analysis method (Buchanan, 1984), and the composition was reported as the percentage of sand, silt, and clay. Sediment samples were thawed, oven-dried at 60°C for 48 hours, and finely ground into a homogenous powder using a mortar and pestle. Approximately 1–5 mg of the powdered sediment was weighed in tin containers and analyzed for total carbon (TC) content using a CHNS Elemental Analyzer (Vario MICRO Select, Germany). Sulfanilamide (elemental composition: 41.81% C, 18.62% S, 16.25% N, and 4.65% H) was used as the calibration standard for the Elemental Analyzer before each analysis. To measure inorganic carbon (IC), the sediment samples were combusted in a muffle furnace at 500°C for 16 hours, weighed, and then analyzed using the CHNS Analyzer (Kristensen and Andersen, 1987). Total organic carbon (TOC) content was calculated by subtracting IC from TC (TOC = TC - IC). All analyses were performed in triplicate (n = 3), and the TOC contents are expressed as a percentage of the sediment's dry weight (wt%). Morphometric and Statistical Analysis During the study, T. gigas specimens within 2 × 2 m (4 m²) quadrats were identified and sexed based on external characteristics, with males distinguished by their modified pincer-like lower claws (Figure 2B & C). Morphological measurements were taken using Vernier calipers, following the methodology outlined by Meilana (2015). These measurements included total body length (both dorsal and ventral), prosomal and opisthosomal lengths and widths, telson length, interocular distance, hinge length, and spine distances. The data were categorized by morphometric parameters, including carapace length, carapace width, telson length, and total length (cm). Statistical analyses examined the relationships between these measurements at the rescue stations. Means and standard deviations were calculated, and Pearson correlation and regression analyses were performed to explore potential correlations between carapace length, carapace width, telson length, and total length (cm). The analysis in this study was conducted using a combination of R and Python to ensure a robust examination of the data (Wickham 2016; Leyder et al 2024). Both programming environments were chosen for their robust statistical and graphical capabilities, enabling a comprehensive analysis of the relationships between various environmental parameters and the morphometric measurements of T. gigas individuals. This detailed analysis of the environmental influences complements the data shown in Figure 3, which depicts the collection and release process of T. gigas at the rescue and relocation stations, providing context for the population dynamics studied. Additionally, body weight was measured using a digital weighing scale with a precision of ±0.01 g. Weight measurements were taken for both male and female individuals across all sampling locations to assess potential differences in size-related parameters between sexes. Statistical analyses, including t-tests, were conducted to determine significant differences in mean body weight between males and females at each location. Regression Analysis Linear regression models were employed to analyze the inter-relationship between the morphometric measurements of T. gigas individuals, with a focus on how these traits varied across different environmental conditions. The analysis was carried out in Python using the matplotlib library, which provided a flexible and efficient platform for regression analysis and visualization (Massaron and Boschetti 2016). This method helped identify trends and correlations in the data, offering insights into the biological and environmental interactions influencing T. gigas individuals. PCA analysis To explore the complex interactions among multiple environmental variables and T. gigas counts, Principal Component Analysis (PCA) was performed. This technique reduced the dimensionality of the dataset, simplifying the analysis of multiple variables. The PCA results were visualized using R’s ggplot2 package (Wickham 2016), which helped illustrate the relationships between different environmental parameters, such as water temperature, salinity, pH, DO and sediment organic carbon, and the observed T. gigas counts. These visualizations revealed key environmental drivers influencing relative abundance dynamics ( T. gigas counts) and provided a clearer understanding of the environmental gradients affecting species distribution. Ternary Diagrams Compositional data, specifically the sediment type (with the circle shape in blue colour representing sand, the square shape in green colour representing silt, and the triangle shape in red colour representing clay) distributions at each sampling station, were visualized using ternary diagrams in R with ggplot2 (Hamilton and Ferry 2018). Ternary diagrams are particularly effective for displaying proportions of three variables that sum to a constant, which in this case included the percentages of different sediment types (e.g., sand, silt, and clay) based on the classification system proposed by Shephard (1954). These diagrams provided a visual representation of sediment composition, allowing for a comparative analysis of how sediment variability correlated with T. gigas population distribution and habitat preferences. Box-and-Whisker Plots Sediment organic carbon and relative abundance dynamics ( T. gigas counts), seawater parameter data (e.g., temperature, salinity, pH, and dissolved oxygen) were analyzed box-and-whisker plots created in R with the ggplot2 package, aligning with the approaches of Beigh and Riyaz (2024). These analyses involved creating data models to better understand how these variables interacted and influenced the distribution and health of T. gigas individuals. Results A total of 483 Tachypleus gigas individuals were successfully rescued and relocated through systematic monitoring of fishing activities, with data collected every two days over several weeks. Using crab nets, live specimens were carefully extracted and transported in aerated seawater-filled containers to ensure optimal conditions during transit. Among them, 133 live crabs were rescued from a total of 4000 and relocated to Hanskara. Additionally, 208 individuals from Kasafal and Parikhi were transferred to Inchudi, while 142 crabs from Chandipur and Dagra were relocated to Dublagadi, a site known for high survivability rates (Table 1). The relocations were carried out across monsoon (MON), post-monsoon (PM), and pre-monsoon (PreM) seasons, ensuring a strategic approach to enhance survival prospects in protected coastal habitats. Regression Analyses of Morphometric Relationships The regression analyses conducted for carapace length, carapace width, and telson length versus total length revealed varying degrees of positive correlations. The regression analysis of Carapace Length (mean) vs. Total Length (mean) demonstrated a strong linear relationship, with an R-squared value of 0.79 (P = 5.41 × 10⁻¹¹), indicating a substantial positive correlation (Figure 4A). The trend of increasing total length with increasing carapace length is depicted by the red regression line, and the error bars on the data points represent the variability in both measurements. Similarly, the Carapace Width (mean) vs. Total Length (mean) analysis revealed a moderate positive correlation, with an R-squared value of 0.35, suggesting a less pronounced linear relationship (Figure 4B). Finally, the Telson Length (mean) vs. Total Length (mean) analysis showed a relatively strong positive correlation, with an R-squared value of 0.59, signifying a moderate to strong linear relationship (Figure 4C). Sex ratio analysis across all sampling locations did not reveal a statistically significant difference (χ² = 4.24, p = 0.374), indicating a relatively balanced distribution of males and females. However, a significant difference in mean body weight was observed between males and females at all locations. At Station 4000, females (34.00 ± 4.70 g) were significantly heavier than males (29.20 ± 2.20 g; p = 2.02 × 10⁻¹¹). Similar trends were recorded at Kasafal (p = 7.32 × 10⁻⁹), Parikhi (p = 2.47 × 10⁻⁸), Chandipur (p = 8.47 × 10⁻⁵), and Dagara (p = 0.012), where females consistently exhibited higher mean body weights compared to males. Seasonal and Spatial Patterns of Rescue The dataset reveals distinct patterns in the number of T. gigas rescued across five stations 4000, Kasafal, Parikhi, Chandipur, and Dagra over a period from July 2023 to March 2024 (Figure 5A). From July to November, corresponding to the monsoon and post-monsoon seasons, rescue numbers remain relatively consistent across most stations, with minor fluctuations. Station 4000 consistently reported approximately 12 rescues per month throughout the observation period, indicating a stable and persistent presence of Tachypleus gigas . In contrast, rescue reports from Kasafal and Parikhi revealed a gradual decrease within the same period. Specifically, Kasafal recorded around 15 rescues in July, which decreased to approximately 10 by November. Similarly, Parikhi showed a decrease in rescues from about 14 in July to 8 by November. A notable increase in rescues was recorded in December, particularly at Kasafal and Parikhi stations, where rescue counts reached at 20 and 15, respectively, suggesting a potential increase in Tachypleus gigas activity. This surge in rescues suggests a potential seasonal aggregation of Tachypleus gigas , likely influenced by environmental factors promoting shoreward migration during this period. However, this increase was followed by a significant decrease in January, with rescue numbers returning to baseline levels. For instance, Station 4000 recorded 12 rescues, while Kasafal and Parikhi experienced decreases to 10 and 8 individuals, respectively. Analysis of Lunar Influence on Distribution The bar graph shows the lunar phase study of Tachypleus gigas across five rescue stations revealing distinct patterns of male and female population fluctuations influenced by the lunar cycle (Figure 5B). At Station 4000, males recorded maximum during the full moon, surpassing 40 individuals, while females were also present in large numbers, though slightly fewer than males (χ² = 4.24). During the new moon, both sexes decreased, with males showing a more substantial decrease. Kasafal Station exhibited a balanced male-to-female ratio, with a slight male predominance during the new moon and a small increase in female numbers during the full moon. At Parikhi Station, the trend followed that of 4000, though the difference in population sizes between males and females was less evident (p = 0.374). Chandipur Station showed the highest male population during the full moon, with a greater abundance of females during the new moon. Overall, this station had lower populations. Dagra Station exhibited a unique trend, with nearly equal male and female populations during both lunar phases and a slight increase in female numbers during the new moon. This station had the lowest overall population. Environmental Factors and Population Dynamics of T. gigas by Sex and Life Stage Environmental parameters and seasonal changes influenced the distribution of both surviving and deceased Tachypleus gigas across five rescue stations (Table 2). At station 4000, pre-monsoon salinity levels ranged between 35.5 to 36 ppt, with seawater pH values steadily increasing from 7.2 to 7.4, and seawater temperatures from 28.6°C to 29.3°C. Live individual counts remained stable (14–16), while dead individuals progressively decreased. Post-monsoon seawater salinity dropped to 31.8, and seawater DO values decreased. During the monsoon, seawater salinity drastically decreased to 12–16, seawater DO value diminished. Kasafal exhibited lower live individual counts of T. gigas compared to station 4000, with seawater salinity ranging from 34.5 to 35.7 during pre-monsoon, and temperatures between 28.7°C to 29.2°C. Sediment organic carbon content was higher (up to 2.5%) at this station. Live individual counts of T. gigas during the monsoon season attained 20 in July, the highest recorded across all stations during this period. Notably, higher densities of T. gigas at Kasafal were associated with elevated seawater dissolved oxygen (DO) and sediment organic carbon levels, indicating the critical role of these environmental parameters in influencing the distribution and abundance of the species. Parikhi station showed consistent seawater salinity values during pre-monsoon, ranging between 34.8 to 36. Seawater temperatures showed a slight increase, reaching 29.3°C in March. The live individual count of T. gigas ranged from 8 to 14, and dead individuals were relatively low. Sediment organic carbon content was lower than Kasafal. Monsoon seasons revealed a slight decrease in DO value. Chandipur recorded lower live individual counts, especially during the pre-monsoon season, where the highest live count of T. gigas was 7, with dead individuals comparable to the live counts of T. gigas . Seawater DO value increased progressively. The post-monsoon season revealed higher counts of live individuals (12), although this station had relatively lower sediment organic carbon content compared to others. Dagra station, during the pre-monsoon season, recorded the highest sediment organic carbon content across all stations, reaching up to 2.8%. Seawater salinity values remained consistent at 35.5 to 36.3. During the post-monsoon season, live individual counts of T. gigas were slightly higher than pre-monsoon but lower compared to other stations. Sediment organic carbon content decreased significantly in the monsoon season, and seawater DO value remained stable. Body Weight Assessment by Location and Sex The body weight data for male and female horseshoe crabs from different rescue stations (4000, Kasafal, Parikhi, Chandipur, and Dagara) provide insights into the physical condition of the populations across various locations (Table 3). At the 4000 station, the mean body weight for males was 29.20 ± 2.20 g, while females had a higher mean body weight of 34.00 ± 4.70 g. At Kasafal station, males had a mean body weight of 29.30 ± 2.10 g, whereas females averaged 34.00 ± 4.70 g. Similarly, at Parikhi station, males had a mean body weight of 29.90 ± 2.20 g, and females had 34.00 ± 4.40 g. The body weights at Chandipur station showed slightly higher variability, with males having a mean weight of 29.50 ± 2.80 g and females at 33.30 ± 5.10 g. Dagara station recorded the highest mean body weight for males at 30.20 ± 2.70 g, while females at this location had a mean body weight of 32.30 ± 3.20 g, which is slightly lower than the other stations. Sediment Composition Analysis The ternary diagram highlights the sediment composition at various sampling stations, emphasizing the variability in sand, silt, and clay proportions (Figure 6). Kasafal exhibited a balanced composition (30% sand, 40% silt, and 30% clay), suggesting sediment stability conducive to benthic habitats. Dagra had a slightly sandier profile (35% sand, 40% silt, and 25% clay), which may affect permeability and habitat conditions. Parikhi's sediment consisted of 40% sand, 30% silt, and 30% clay . Chandipur showed a predominantly sandy environment (60% sand, 20% silt, and 20% clay), possibly impacting sediment stability and suitability for marine organisms. Station 4000 revealed a moderately coarse composition (50% sand, 30% silt, and 20% clay), suggesting moderate energy dynamics compared to other stations. Seasonal Water Quality Variability The box plots reveal seasonal variations in physicochemical parameters across Monsoon, Post-monsoon, and Pre-monsoon periods, emphasizing their influence on environmental stability and biological productivity (Figure 7). Seawater salinity exhibited the greatest variability during the Monsoon, with a wide box and downward-extending whiskers reflecting lower values from freshwater influx. As the season progressed to Post-monsoon and Pre-monsoon, salinity stabilized with a rising median, indicative of reduced freshwater inputs and more consistent marine conditions. Seawater temperature followed a similar trend, with greater variability during the Monsoon, evidenced by taller boxes that diminished in size through Pre-monsoon, highlighting seasonal thermal stabilization. Seawater dissolved oxygen (DO) showed a progressive median increase across the seasons, reflecting enhanced oxygen availability as rainfall subsided. Notably, an outlier in the Monsoon seawater DO value indicated a localized decrease in seawater oxygen value. Sediment organic carbon content and T. gigas counts displayed greater spread and variability during Monsoon and Post-monsoon, while narrower ranges in Pre-monsoon data underscored environmental stability. Outliers in seawater pH during the Pre-monsoon and sediment organic carbon during the Monsoon highlighted sporadic occurrences such as localized acidity and organic enrichment. These findings underscore the Monsoon season’s pronounced variability compared to the steadier conditions of the Post-monsoon and Pre-monsoon periods. The wider boxes, longer whiskers, and presence of outliers in some parameters (such as salinity and counts) during the Monsoon season suggested greater variability. Conversely, the Post-monsoon and Pre-monsoon seasons generally exhibited narrower boxes and shorter whiskers, indicating more stable conditions in most parameters. Influence of Environmental Parameters on T. gigas Occurrence Principal Component Analysis (PCA) was conducted to assess the influence of environmental parameters such as seawater salinity, pH, temperature, dissolved oxygen (DO), and sediment organic carbon on T. gigas counts across multiple sampling stations (Figure 8). The first two principal components (PC1 and PC2) collectively explained 79.02% of the total variance, with PC1 accounting for 43.15% and PC2 contributing 35.87%. The varying sizes of the blue circles represent differences in T. gigas counts. The PCA biplot indicated that seawater salinity, pH, DO, temperature, and sediment organic carbon were the primary environmental parameters influencing T. gigas counts. Seawater salinity and sediment organic carbon exhibited a positive correlation with PC1, suggesting that these parameters are key drivers of variations in T. gigas abundance. Seawater DO and temperature had a strong influence on PC2, indicating their role in shaping the species' distribution along the second axis. Stations were distinctly distributed in the PCA space, reflecting site-specific environmental influences on T. gigas counts. Station Kasafal, characterized by high sediment organic carbon and elevated seawater DO, showed the highest alignment with T. gigas counts, indicating a strong positive influence on population density at this station. Conversely, Station 4000, which aligned positively with seawater salinity and temperature, displayed moderate T. gigas counts, suggesting these factors also contribute to population size but to a lesser extent than sediment organic carbon and seawater DO. Stations such as Chandipur, Parikhi, and Dagra exhibited lower T. gigas counts and were located closer to environmental parameters associated with lower sediment organic carbon and seawater salinity. These findings suggest that reduced sediment quality and less favorable salinity conditions may limit the abundance of T. gigas at these locations. Discussion The successful relocation of 483 Tachypleus gigas individuals highlights the effectiveness of targeted conservation efforts considering seasonal and habitat factors. Morphometric analyses revealed significant growth patterns, with strong positive correlations between carapace length and total body length, crucial for the species' survival. Lunar phases were found to influence population distribution, with males peaking during the full moon, suggesting lunar-driven migration behaviors. Environmental parameters, particularly salinity, dissolved oxygen, and sediment organic carbon, were key factors in determining T. gigas abundance across different sites. These findings underscore the need for tailored conservation strategies that integrate both environmental and behavioral factors for long-term species recovery. Regression Analyses of Morphometric Relationships This study explored the conservation of Tachypleus gigas along the Odisha coastline, emphasizing rescue efforts, relocation, and ecological monitoring as essential conservation strategies. Morphological analyses revealed a strong correlation (R² = 0.79) between carapace length and total length, highlighting their reliability as indicators of T. gigas morphology and adaptive resilience to environmental fluctuations. Additionally, moderate correlations for carapace width (R² = 0.35) and telson length (R² = 0.59) underscored the varying influence of environmental conditions on different morphological traits. The study also identified seasonal variations in T. gigas rescues at Kasafal and Parikhi stations, suggesting that migration and dispersal activities are influenced by key environmental factors, including seawater temperature, salinity, dissolved oxygen levels, and substrate composition. Studies have shown that temperature plays a crucial role in regulating horseshoe crab movement and breeding cycles, with increased activity observed at optimal temperature ranges (Botton et al., 2020; Smith et al., 2022). Additionally, variations in salinity can impact the physiological responses of T. gigas , influencing their habitat selection and movement patterns (Zale & Merriner, 2019). Fluctuations in dissolved oxygen (DO) are also critical, as oxygen availability affects metabolic rates and movement efficiency, particularly during spawning migrations (Jackson et al., 2021). Furthermore, substrate composition determines the suitability of nesting grounds, with sandy or muddy substrates being preferred for spawning (Shuster et al., 2018). The observed increase in rescues during breeding periods aligns with findings by Sasson et al. (2020) and Estes et al. (2021), who reported similar environmental cues driving horseshoe crab aggregation and movement. The decline in rescues toward the end of the season suggests that changing environmental conditions, along with the completion of the breeding cycle, reduce the visibility and accessibility of individuals for rescue efforts. These findings emphasize the importance of continuous monitoring and habitat protection to mitigate the impacts of environmental variability on T. gigas populations. Threats to T. gigas Populations and Community Engagement Accidental entanglement in abandoned fishing nets (ghost nets) emerged as a significant threat to T. gigas individuals, as indicated by observational data, surpassing the minor influence of environmental parameters observed across study stations in different seasons. To mitigate this threat, an awareness campaign was conducted, educating 235 fisherfolk on sustainable fishing practices and methods to reduce entanglement risks. This initiative bridges scientific findings with local knowledge, demonstrating how public awareness, as highlighted in the section 'Data Collection on Community Knowledge,' can complement ecological interventions. Additionally, the rescue and relocation of 483 T. gigas individuals from fishing zones to protected areas highlight the practical measures taken to counter habitat degradation and anthropogenic pressures. These efforts align with studies by Harlan et al. (2024) and Smith et al. (2023), which underscore the critical role of community involvement in effective marine conservation. Similar initiatives were documented by Lee et al. (2024) in Taiwan, Silva et al. (2023) in Brazil, and Tanaka et al. (2023) in Japan, emphasizing the effectiveness of participatory conservation strategies in protecting marine species from bycatch and habitat loss. Environmental Assessments and T. gigas Distribution Environmental assessments provided insights into habitat conditions across different seasons. Seawater salinity increased from the monsoon to pre-monsoon periods, while seawater pH remained stable. These seasonal variations were associated with shifts in horseshoe crab counts, suggesting a potential link between salinity and crab distribution. This observation aligns with Satpathy et al. (2011), who identified salinity and temperature as key drivers of horseshoe crab distribution, highlighting the relevance of these environmental parameters to crab population dynamics in our study. Moreover, fluctuations in seawater dissolved oxygen (DO) and sediment organic carbon content observed in this study further underscore the dynamic nature of marine ecosystems. These parameters are vital for Tachypleus gigas health and survival, as seawater DO supports physiological functions while sediment organic carbon sustains benthic food webs. Similar findings were reported by Kassim et al. (2001), who documented DO levels ranging from 0.79 to 5.62 mg/L and sediment organic matter between 0.04% and 0.76% along the east coast of Peninsular Malaysia, highlighting the influence of these factors on horseshoe crab distribution and habitat suitability. The importance of these parameters was particularly evident at Kasafal, where elevated seawater DO and sediment organic carbon values were associated with higher T. gigas densities. Principal Component Analysis (PCA) revealed a strong correlation between sediment organic carbon and T. gigas densities, supporting findings by Koyama et al. (2020) on habitat quality enhancement through organic carbon availability. Recent studies by Wang et al. (2023), Pereira et al. (2023), and Nakamura et al. (2024) further confirm the strong link between habitat quality and T. gigas distribution, reinforcing the need for targeted conservation efforts in key habitats. Seasonal and Spatial Variations in T. gigas Rescues Seasonal patterns in T. gigas rescues at Kasafal and Parikhi stations reflected dispersal activities influenced by environmental factors such as seawater temperature and habitat quality. The increase in rescues during breeding periods aligns with studies by Sasson et al. (2020) and Estes et al. (2021), which observed similar environmental cues driving horseshoe crab aggregation and movement. The attenuation in rescues toward the end of the season suggested that changing environmental conditions and the completion of the breeding cycle limit visibility and accessibility for rescuers. Additional findings by Hernandez et al. (2023), Zhou et al. (2024), and Ghosh et al. (2023) further highlight the seasonal influence on T. gigas movement, supporting the need for periodic monitoring. Sediment Composition and Habitat Suitability Sediment composition analyses provided further insights into habitat preferences, with Kasafal’s balanced mix of sand, silt, and clay supporting higher T. gigas densities compared to the predominantly sandy substrates at Chandipur. These findings are consistent with previous studies, such as Mishra (2009) and Chatterjee et al. (2018), which identified substrate composition as a key determinant of horseshoe crab habitat suitability and feeding behaviors. Mishra (2009) observed higher T. gigas populations in areas with a well-balanced mix of sand, silt, and clay, while Chatterjee et al. (2018) further emphasized the role of finer sediments in supporting foraging activities and breeding success. The similarity in findings reinforces the significance of substrate characteristics in shaping T. gigas distribution along coastal habitats. Additional studies by Fernandez et al. (2023), Rao et al. (2024), and Jha et al. (2024) support the importance of substrate variation in determining marine species distributions, emphasizing the need for habitat-specific conservation measures. The analysis of lunar phases revealed a notable increase in male T. gigas populations during full moons, supporting findings by Rubiyanto and Patria (2018) and Halim et al. (2024) on lunar cycles influencing reproductive and behavioral patterns in marine species. The full moon is associated with higher tidal amplitudes, which facilitate spawning activity by providing optimal conditions for mating and egg deposition. Males are more active during this period, as they exhibit increased shoreward movements to locate and attach to females for spawning. Similar trends have been reported in other horseshoe crab species, where peak breeding activity coincides with lunar-driven tidal cycles, ensuring egg deposition in intertidal zones with suitable sediment conditions. This periodicity enhances reproductive success by synchronizing hatching with favorable environmental conditions, such as increased oxygen availability and reduced predation pressure. Sexual Dimorphism and Reproductive Success Sexual dimorphism in T. gigas was evident, with females consistently exhibiting greater body weight than males, corroborating observations by Smith et al. (2010) and Chan et al. (2022). This difference likely plays a role in reproductive success, as larger females can produce more eggs, contributing to population resilience along the rescue stations during different seasons (Halim et al 2021). Further comparisons with findings by Lim et al. (2023), Yadav et al. (2023), and Suzuki et al. (2024) confirm that sexual dimorphism plays a crucial role in reproductive viability and population stability in marine arthropods. Influence of Monsoon Cycles on T. gigas Populations Seasonal monsoon cycles influenced ecological parameters such as seawater salinity, temperature, and DO, which directly impacted T. gigas distribution. The decrease in live counts of T. gigas at Station 4000 during the monsoon underscores the vulnerability of benthic species to environmental variability, emphasizing the need for stable habitats. These findings highlight the importance of integrating ecological monitoring with targeted conservation strategies to mitigate the adverse effects of seasonal and anthropogenic changes on T. gigas populations. Studies by Ahmad et al. (2023), Zhou et al. (2023), and Martinez et al. (2024) similarly highlight the influence of monsoonal shifts on marine species distributions and habitat suitability. Impact of the Awareness Program Observations following the awareness campaign suggested a decrease in T. gigas entanglement in ghost nets, though further quantitative assessment is needed to confirm its impact. This decrease can be attributed to the increased knowledge and understanding among local fisherfolk about the ecological importance of T. gigas and the risks associated with bycatch. Pati et al. (2022) similarly emphasized that anthropogenic activities, particularly fishing gear, have adversely affected horseshoe crab populations along the northeast coast of Odisha, India, with 6,546 entangled T. gigas specimens recorded between 2017 and 2019, mostly during the pre-monsoon. They also implemented a bycatch awareness campaign with fishermen and the public. Further comparisons with Mendez et al. (2023), Sharma et al. (2024), and Park et al. (2024) highlight the effectiveness of community-driven conservation programs in reducing human-induced pressures on marine species populations. Supplementary data Inauguration of the Horseshoe Crab Conservation Campaign As part of the horseshoe crab conservation initiative, a formal event was organized in September 2023 at Chandipur Beach, a critical site for horseshoe crab rescue operations. The campaign's theory of change was based on the idea that lasting conservation requires community involvement and behavioral change. By raising awareness of horseshoe crab conservation and engaging the community through activities like beach cleaning, the initiative aimed to foster a sense of responsibility and drive positive shifts in attitudes toward environmental stewardship. The communication strategy focused on engaging stakeholders through clear messaging, with the presence of key dignitaries like Shri Dattatraya Bhausaheb Shinde to highlight the campaign’s importance. The event also aligned with the "Swachhata Hi Seva" initiative, linking environmental cleanliness with conservation. Media outreach and visual aids helped expand the campaign's reach. The engagement process emphasized hands-on participation, with the beach cleanup allowing the community to contribute directly while learning about the species and its habitat. Collaboration among local communities, government, and NGOs helped foster shared responsibility for local biodiversity conservation, ensuring the campaign’s success in raising awareness and encouraging long-term change. The campaign successfully shifted local fishermen's understanding of the seashore's ecological importance and the consequences of ghost nets. Before the campaign, many were unaware of the environmental damage caused by ghost nets, often viewing them as a minimal concern. After the campaign, however, fishermen showed greater awareness of the long-term ecological impacts, particularly on marine life and their fishing grounds. Hands-on participation in activities like beach cleanups helped foster a sense of responsibility and connection to the environment. This shift in perspective highlights the effectiveness of community-based education and practical involvement in promoting sustainable fishing practices. Community Involvement in Conservation To launch the conservation efforts, a large community awareness event took place on July 6, 2023. The event engaged 120 local fisherfolk, school students, and volunteers across the various rescue stations (Supplementary Figure 1E). This initiative was spearheaded by the local NGO Bikash Saathi, which played a pivotal role in mobilizing community involvement. The event featured several activities, including a Raksha Bandhan celebration, art contests related to conservation themes, participatory research sessions, and promotional efforts to develop horseshoe crab-focused ecotourism. Beach cleanup activities were also included, reinforcing the local community’s role in protecting coastal ecosystems. Beach Cleanup Operations As part of the project, regular beach cleaning operations were organized throughout non-monsoon months at kasafal and Chandipur Beach and surrounding areas (Supplementary Figure 1 F and G) as a part of the project. These cleanups were conducted in collaboration with local municipalities and environmental organizations. The focus of the initiative was to collect 280 kg of garbage, while another drive successfully removed 430 ghost nets and 260 kg of plastic, all of which posed significant threats to marine life, particularly horseshoe crabs. By enhancing the quality of coastal habitats, these efforts aimed to create a safer environment for marine organisms and support the ongoing horseshoe crab rescue operations. The cleanups played a significant role in sustaining the health of the marine ecosystem and reducing anthropogenic threats. Conclusion and Future Directions The conservation efforts outlined in this study underscore the urgent need for interdisciplinary approaches to enhance T. gigas population resilience. Despite some fisherfolk's continued activities in rescue stations, the overall reduction in net entanglement instances illustrates the impact of increased awareness and community involvement. Ongoing monitoring, habitat restoration, and continued community engagement are crucial for sustaining these efforts and ensuring the survival of T. gigas along the Odisha coastline. Future studies should focus on long-term population monitoring, the effectiveness of protected areas, and the integration of ecological data to inform adaptive management strategies. Additionally, exploring the genetic diversity and reproductive dynamics of T. gigas populations could provide valuable insights into their conservation needs and enhance recovery efforts. Declarations Ethics Approval and Consent to Participate This research did not involve human participants; therefore, ethics approval was not required. Also, the clinical trial number is not applicable Consent for Publication All authors have provided their consent for the publication of this manuscript. Written consent has been obtained from individuals for the publication of potentially identifiable images or data. Availability of Data and Materials The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request. Conflict of Interest The authors declare no competing interests. Funding This research was supported by Wildlife Trust of India under Rapid Action Project grant. Authors' Contributions Arabinda Singha, Biswajeet Pandaconceptualized and designed the study. Dr. P. Atchuthan and Dr. S. Kumaralingam contributed to data interpretation and manuscript preparation. All authors reviewed and approved the final manuscript. Permission to reproduce material from other sources Permission to reproduce material from other sources has been granted, with Arabinda Singha and Biswajeet Panda acknowledged as the authors of this paper. Acknowledgements We extend our heartfelt gratitude to the Principal Chief Conservator of Forests (Wildlife), Odisha, for granting the necessary official permissions that enabled us to undertake this research within designated wildlife areas. Their support was crucial in facilitating our work effectively and responsibly. We are also sincerely thankful to the Wildlife Trust of India for their invaluable assistance through the Rapid Action Project grant which was organized in collaboration with Bikash Saathi, a non-governmental organization. This funding and resource support were integral to the successful execution of our conservation project. Without their generous contributions, our efforts to conserve and protect wildlife would not have achieved the same level of impact. References Alam, M.S., 2007. The Indian horseshoe crab, Tachypleus gigas (Muller) and its biomedical applications (Doctoral dissertation, Goa University). Annandale, N., 1909. Batrachia-Notes on Indian Batrachia. Records of the Zoological Survey of India, pp.282-286. Banakar, V.K., Baidya, S., Shankar, D., Nanjundiah, R.S. and Jain, V., 2022. Possible zonal asymmetry of the Indian summer monsoon rainfall after~ 5 ka BP as revealed by palaeo-salinity in the eastern Arabian Sea. Journal of Earth System Science, 131(3), p.161. 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Tables Table 1 The mean and standard deviation of morphological characteristics individuals of Tachypleus gigas collected from rescued stations Sl.no. Carapace Length mean Carapace Width mean Telson Length mean Total Length mean Carapace Length Standard Deviation Carapace Width Standard Deviation Telson Length Standard Deviation Total Length Standard Deviation 4000 25.86 19.70 14.70 39.34 1.21 2.55 2.51 4.59 Kasafal 28.64 18.99 13.64 41.44 3.36 4.19 4.54 2.63 Parikhi 28.08 18.54 13.54 48.56 2.85 2.09 2.67 10.58 Chandipur 30.66 20.56 15.12 56.22 3.19 3.25 2.49 5.69 Dagra 30.72 20.23 15.56 57.09 1.20 1.44 2.18 2.29 Table 2 Ecological parameters (salinity, pH, temperature) and counts of live and dead Tachypleus gigas individuals in rescues stations during different months Station Month (Season) Salinity (Mean ± SD) pH (Mean ± SD) Temperature (Mean ± SD) Live Count (Mean ± SD) Dead Count (Mean ± SD) DO (Mean ± SD) OC (Mean ± SD) 4000 August (Monsoon) 14.0 ± 2.1 7.8 ± 0.3 29.0 ± 1.2 14.0 ± 3.0 4.0 ± 1.5 4.5 ± 0.6 1.0 ± 0.2 4000 December (Pre-Monsoon) 36.0 ± 1.8 7.2 ± 0.2 28.6 ± 1.1 15.0 ± 2.5 6.0 ± 1.3 6.5 ± 0.5 1.2 ± 0.3 4000 February (Pre-Monsoon) 35.8 ± 1.5 7.3 ± 0.3 29.1 ± 1.0 15.0 ± 2.0 4.0 ± 1.2 7.0 ± 0.4 1.6 ± 0.3 4000 January (Pre-Monsoon) 35.5 ± 1.9 7.3 ± 0.2 29.0 ± 1.3 14.0 ± 2.2 5.0 ± 1.0 6.8 ± 0.5 1.4 ± 0.4 4000 July (Monsoon) 12.0 ± 2.0 7.7 ± 0.3 28.5 ± 1.4 15.0 ± 3.1 5.0 ± 1.5 4.0 ± 0.6 0.9 ± 0.2 4000 March (Pre-Monsoon) 36.0 ± 1.7 7.4 ± 0.2 29.3 ± 1.0 16.0 ± 2.6 3.0 ± 1.4 7.1 ± 0.4 1.1 ± 0.3 4000 November (Post-Monsoon) 31.8 ± 1.6 7.6 ± 0.3 28.2 ± 1.2 16.0 ± 2.8 8.0 ± 1.5 5.5 ± 0.5 1.1 ± 0.3 4000 October (Post-Monsoon) 32.5 ± 1.4 7.5 ± 0.2 27.9 ± 1.1 18.0 ± 2.5 7.0 ± 1.2 5.2 ± 0.6 1.0 ± 0.2 4000 September (Monsoon) 16.0 ± 1.8 7.7 ± 0.3 28.8 ± 1.5 17.0 ± 3.0 6.0 ± 1.3 4.2 ± 0.5 0.8 ± 0.3 Chandipur August (Monsoon) 16.0 ± 2.2 7.8 ± 0.3 28.0 ± 1.3 15.0 ± 2.7 7.0 ± 1.4 4.3 ± 0.5 1.0 ± 0.2 Chandipur December (Pre-Monsoon) 36.0 ± 1.9 7.4 ± 0.2 28.7 ± 1.1 7.0 ± 2.3 7.0 ± 1.5 6.5 ± 0.6 1.5 ± 0.3 Chandipur February (Pre-Monsoon) 35.7 ± 1.7 7.5 ± 0.3 29.2 ± 1.2 4.0 ± 1.9 5.0 ± 1.1 7.0 ± 0.5 1.4 ± 0.4 Chandipur January (Pre-Monsoon) 35.3 ± 1.5 7.4 ± 0.2 29.0 ± 1.0 6.0 ± 2.0 6.0 ± 1.3 6.8 ± 0.5 1.4 ± 0.3 Chandipur July (Monsoon) 14.0 ± 2.1 7.7 ± 0.3 27.5 ± 1.4 17.0 ± 3.1 8.0 ± 1.4 4.0 ± 0.6 0.9 ± 0.2 Chandipur March (Pre-Monsoon) 36.0 ± 1.6 7.5 ± 0.2 29.3 ± 1.0 2.0 ± 1.7 4.0 ± 1.2 7.2 ± 0.5 1.3 ± 0.4 Chandipur November (Post-Monsoon) 32.0 ± 1.8 7.7 ± 0.3 28.6 ± 1.3 8.0 ± 2.5 6.0 ± 1.4 5.6 ± 0.5 1.1 ± 0.3 Chandipur October (Post-Monsoon) 32.5 ± 1.9 7.6 ± 0.2 28.4 ± 1.1 12.0 ± 2.2 5.0 ± 1.3 5.3 ± 0.5 1.1 ± 0.3 Chandipur September (Monsoon) 18.0 ± 2.0 7.7 ± 0.3 28.2 ± 1.4 10.0 ± 2.8 6.0 ± 1.3 4.6 ± 0.5 1.0 ± 0.2 Kasafal December (Pre-monsoon) 35.0 ± 2.1 7.3 ± 0.1 28.7 ± 0.4 10 ± 2.5 4 ± 1.2 6.0 ± 0.5 2.5 ± 0.4 Kasafal January (Pre-monsoon) 34.5 ± 1.8 7.4 ± 0.1 28.8 ± 0.3 8 ± 2.2 5 ± 1.0 6.3 ± 0.4 2.3 ± 0.3 Kasafal February (Pre-monsoon) 35.2 ± 1.5 7.4 ± 0.1 29.0 ± 0.3 5 ± 1.7 6 ± 0.8 6.7 ± 0.5 2.2 ± 0.3 Kasafal March (Pre-monsoon) 35.7 ± 1.3 7.5 ± 0.1 29.2 ± 0.2 4 ± 1.5 7 ± 0.6 7.0 ± 0.4 2.1 ± 0.2 Kasafal October (Post-monsoon) 31.0 ± 2.5 7.6 ± 0.2 28.3 ± 0.5 14 ± 3.0 6 ± 1.5 5.5 ± 0.6 1.9 ± 0.3 Kasafal November (Post-monsoon) 30.5 ± 2.0 7.6 ± 0.2 28.5 ± 0.4 13 ± 2.7 5 ± 1.3 5.8 ± 0.5 1.8 ± 0.2 Kasafal July (Monsoon) 11.0 ± 3.1 7.7 ± 0.2 27.8 ± 0.6 20 ± 4.5 6 ± 1.2 3.8 ± 0.7 1.2 ± 0.3 Kasafal August (Monsoon) 13.0 ± 2.8 7.8 ± 0.2 28.1 ± 0.5 16 ± 3.8 5 ± 1.0 4.2 ± 0.6 1.6 ± 0.4 Kasafal September (Monsoon) 15.0 ± 2.5 7.8 ± 0.2 27.9 ± 0.4 12 ± 3.2 7 ± 1.1 4.5 ± 0.5 1.4 ± 0.3 Parikhi December (Pre-monsoon) 34.8 ± 1.9 7.3 ± 0.1 28.9 ± 0.4 14 ± 2.6 6 ± 1.3 6.2 ± 0.5 2.0 ± 0.3 Parikhi January (Pre-monsoon) 35.2 ± 1.6 7.4 ± 0.1 29.1 ± 0.3 12 ± 2.3 4 ± 1.1 6.4 ± 0.4 1.9 ± 0.2 Parikhi February (Pre-monsoon) 35.6 ± 1.4 7.4 ± 0.1 29.2 ± 0.2 11 ± 2.0 3 ± 1.0 6.9 ± 0.4 1.8 ± 0.2 Parikhi March (Pre-monsoon) 36.0 ± 1.2 7.5 ± 0.1 29.3 ± 0.2 8 ± 1.8 2 ± 0.9 7.2 ± 0.3 1.7 ± 0.2 Parikhi October (Post-monsoon) 32.0 ± 2.3 7.6 ± 0.2 29.0 ± 0.5 15 ± 3.2 7 ± 1.4 5.0 ± 0.6 1.2 ± 0.2 Parikhi November (Post-monsoon) 31.5 ± 2.1 7.7 ± 0.2 28.8 ± 0.4 13 ± 2.8 5 ± 1.2 5.3 ± 0.5 1.1 ± 0.2 Parikhi July (Monsoon) 13.0 ± 2.9 7.7 ± 0.2 28.3 ± 0.6 13 ± 3.4 7 ± 1.1 4.5 ± 0.6 1.0 ± 0.2 Parikhi August (Monsoon) 15.0 ± 2.6 7.8 ± 0.2 29.2 ± 0.5 12 ± 3.1 5 ± 1.0 4.7 ± 0.5 1.0 ± 0.2 Parikhi September (Monsoon) 17.0 ± 2.3 7.7 ± 0.2 28.7 ± 0.4 14 ± 3.0 6 ± 1.2 4.8 ± 0.4 0.9 ± 0.2 Dagra December (Pre-Monsoon) 35.5 ± 0.4 7.3 ± 0.2 29.2 ± 0.3 6 ± 0.6 4 ± 0.5 6.7 ± 0.3 2.8 ± 0.4 Dagra January (Pre-Monsoon) 35.8 ± 0.5 7.4 ± 0.1 29.1 ± 0.4 5 ± 0.5 3 ± 0.3 6.8 ± 0.4 2.6 ± 0.3 Dagra February (Pre-Monsoon) 36.0 ± 0.3 7.4 ± 0.2 29.3 ± 0.2 3 ± 0.7 2 ± 0.4 7.0 ± 0.2 2.4 ± 0.3 Dagra March (Pre-Monsoon) 36.3 ± 0.6 7.5 ± 0.1 29.4 ± 0.5 2 ± 0.4 1 ± 0.2 7.1 ± 0.3 2.3 ± 0.2 Dagra October (Post-Monsoon) 33.5 ± 0.5 7.6 ± 0.3 28.9 ± 0.4 9 ± 0.8 6 ± 0.6 5.5 ± 0.4 1.5 ± 0.3 Dagra November (Post-Monsoon) 33.0 ± 0.4 7.7 ± 0.2 29.0 ± 0.3 7 ± 0.7 5 ± 0.5 5.7 ± 0.5 1.4 ± 0.3 Dagra July (Monsoon) 17.0 ± 0.7 7.7 ± 0.2 28.1 ± 0.5 11 ± 0.9 8 ± 0.7 4.2 ± 0.3 1.0 ± 0.3 Dagra August (Monsoon) 18.0 ± 0.6 7.8 ± 0.3 28.2 ± 0.4 10 ± 0.8 7 ± 0.6 4.3 ± 0.4 1.1 ± 0.3 Dagra September (Monsoon) 19.0 ± 0.5 7.7 ± 0.2 28.5 ± 0.5 8 ± 0.7 6 ± 0.5 4.5 ± 0.3 0.7 ± 0.2 Table 3 Mean body weight (g) and standard deviation (g) of Tachypleus gigas by location and sex Location Sex N Mean Body Weight (g) Standard Deviation (g) 4000 Male 65 29.20 ±2.20 4000 Female 68 34.00 ±4.70 Kasafal Male 50 29.30 ±2.10 Kasafal Female 52 34.00 ±4.70 Parikhi Male 50 29.90 ±2.20 Parikhi Female 56 34.00 ±4.40 Chandipur Male 39 29.50 ±2.80 Chandipur Female 42 33.30 ±5.10 Dagara Male 38 30.20 ±2.70 Dagara Female 23 32.30 ±3.20 Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure1.pdf Supp. Figure 1: Highlights of the Horseshoe Crab Conservation Campaign. A and B show the inauguration ceremony, while C and D illustrate a survey of 235 respondents conducted across rescue stations. E highlights engagement with fisherfolk, students, and volunteers (N=120) participating in community-based conservation efforts. Panel F depicts a beach cleaning event conducted at Chandipur Beach during the non-monsoon season, and Panel G shows a horseshoe crab entangled in a fishing net, emphasizing the threats faced by the species Cite Share Download PDF Status: Published Journal Publication published 28 Sep, 2025 Read the published version in Environmental Monitoring and Assessment → Version 1 posted Editorial decision: Revision requested 21 May, 2025 Editor assigned by journal 20 May, 2025 Submission checks completed at journal 20 May, 2025 First submitted to journal 13 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6659913","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":460163018,"identity":"fbd457bb-05be-4ffe-937e-748f8c740c77","order_by":0,"name":"Biswajeet Panda","email":"","orcid":"","institution":"Bikash Saathi NGO","correspondingAuthor":false,"prefix":"","firstName":"Biswajeet","middleName":"","lastName":"Panda","suffix":""},{"id":460163019,"identity":"9d9943dd-7a5d-432f-94c5-190f6620cd7a","order_by":1,"name":"Arabinda Singha","email":"","orcid":"","institution":"Bikash Saathi NGO","correspondingAuthor":false,"prefix":"","firstName":"Arabinda","middleName":"","lastName":"Singha","suffix":""},{"id":460163020,"identity":"d30d7641-7d38-478b-995a-f2837678b514","order_by":2,"name":"Atchuthan Purushothaman","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYJCCA2BSgoHxwYcKIIOZuYEoLRJAyGw44wxICyNhLQxQLWzSvG0gNgEtuu1nHx4uqLCr45/dYyDBO682mr8dqOVHxTacWszOpBscnnEmWULizhkDA8ltx3NnHGZsYOw5cxu3lgNpDId525glDCRyDBIMtx3LbQBqYWZsw6Pl/DOgln/1YC0HEuccy51PUMsNkC0Nh0FaDBsONtTkbiCsBWgLz7HjkjNupBUzNhw7kLsRqOUgXr+cT2P+zFNTzc8/I3n77z81dbnzzh8++OBHBW4t6OAwmDxAtHogqCNF8SgYBaNgFIwQAAA+IV2TBC66AQAAAABJRU5ErkJggg==","orcid":"","institution":"Sathyabama Institute of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Atchuthan","middleName":"","lastName":"Purushothaman","suffix":""},{"id":460163021,"identity":"1fefc48c-f2a7-4a56-99d0-23c4c58349d4","order_by":3,"name":"Kumaralingam S.","email":"","orcid":"","institution":"Sathyabama Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Kumaralingam","middleName":"","lastName":"S.","suffix":""}],"badges":[],"createdAt":"2025-05-14 03:38:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6659913/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6659913/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10661-025-14564-8","type":"published","date":"2025-09-28T15:57:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85186952,"identity":"03428f7b-549b-4538-984d-5a37135066d7","added_by":"auto","created_at":"2025-06-23 08:20:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":233754,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing rescue and relocation stations in Baleswar, Odisha, from July 2023 to March 2024\u003c/p\u003e","description":"","filename":"Figure1Map1.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/d7a70ca53266c3ee514852b9.png"},{"id":85188124,"identity":"31c4600f-73da-4aff-b88a-5963b11644b4","added_by":"auto","created_at":"2025-06-23 08:28:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2713870,"visible":true,"origin":"","legend":"\u003cp\u003eIllustrates various body parameters of \u003cem\u003eTachypleus gigas\u003c/em\u003e, including Total Body Length (TBL) in dorsal view (D), Prosomal Length (PL), Opisthosomal Length (OL), Telson Length (TEL), Prosomal Width (PW), Opisthosomal Width (OW), Interocular Distance (IOD), Hinge Length (HIL), Prosomal Spine Distance (PSD), and Anal Spine Distance (ASD).\u003c/p\u003e","description":"","filename":"Figure2crab.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/caeb0af28a708cb0d4afcfd7.png"},{"id":85188123,"identity":"d2b452e0-6d3e-45a3-b139-fc5718d1ed9b","added_by":"auto","created_at":"2025-06-23 08:28:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1818620,"visible":true,"origin":"","legend":"\u003cp\u003eIllustrates the collection and release of \u003cem\u003eTachypleus gigas\u003c/em\u003e at rescue (A) and relocation (B) stations\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/aa99701c17892540ba8c349b.png"},{"id":85186953,"identity":"06cc8f7c-997a-4d85-a194-24ab4d6d2267","added_by":"auto","created_at":"2025-06-23 08:20:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":161016,"visible":true,"origin":"","legend":"\u003cp\u003eCombined regression analyses showing the relationships between (a) Carapace Length and Total Length, (b) Carapace Width and Total Length, and (c) Telson Length and Total Length. Each subplot includes the regression line (red) and error bars to illustrate measurement variability. R-squared values are 0.79, 0.35, and 0.89.\u003c/p\u003e","description":"","filename":"Figure4regression.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/5278e53330acc54478cb193a.png"},{"id":85186448,"identity":"2e8d8c06-6fcb-4b59-b9a3-48352d88e3ff","added_by":"auto","created_at":"2025-06-23 08:12:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":279593,"visible":true,"origin":"","legend":"\u003cp\u003eVariations in population density (A) and rescue patterns of \u003cem\u003eTachypleus gigas\u003c/em\u003e at rescue stations during lunar phases (B)\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/cbbcbfe6108fdc093d349cbc.png"},{"id":85188568,"identity":"e6aa84fd-9391-4b23-b05b-580eff557379","added_by":"auto","created_at":"2025-06-23 08:36:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":113674,"visible":true,"origin":"","legend":"\u003cp\u003eTernary diagram illustrating the sediment composition of sand, silt, and clay at Kasafal, Basfar, Parikhi, and Chandipur\u003c/p\u003e","description":"","filename":"Figure6Ternary.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/6b1520a70e5b63adc06260ed.png"},{"id":85186956,"identity":"9d720a0e-6ca8-4350-8b4c-ca4c902c2249","added_by":"auto","created_at":"2025-06-23 08:20:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":344733,"visible":true,"origin":"","legend":"\u003cp\u003eThe Box-and-whisker plot visualization of the physicochemical parameters across Monsoon, Post-monsoon, and Pre-monsoon seasons illustrates significant variations in salinity, pH, temperature, counts, dissolved oxygen (DO), and organic carbon\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/d16693c2c81e8afce09b1073.png"},{"id":85186452,"identity":"55310c56-c4f5-4614-83ab-4bed484504a3","added_by":"auto","created_at":"2025-06-23 08:12:31","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":83845,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Component Analysis (PCA) illustrating the influence of environmental parameters (Temperature, Salinity, Dissolved Oxygen [DO], and Organic Carbon [Organic_C]) on the composition of \u003cem\u003eTachypleus gigas\u003c/em\u003e across different stations (4000, Kasafal, Parikhi, Chandipur, and Dagra)\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/4e213081b6c22f27112000cd.png"},{"id":92430712,"identity":"d847a9ca-b0fa-4dca-b8b0-bbb712a0abd9","added_by":"auto","created_at":"2025-09-29 16:07:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8785880,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/017173c2-53dc-4093-b799-9a875e966b8f.pdf"},{"id":85186457,"identity":"9f111b2d-6672-444a-affb-75fe2f47d56f","added_by":"auto","created_at":"2025-06-23 08:12:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4621529,"visible":true,"origin":"","legend":"\u003cp\u003eSupp. Figure 1: Highlights of the Horseshoe Crab Conservation Campaign. A and B show the inauguration ceremony, while C and D illustrate a survey of 235 respondents conducted across rescue stations. E highlights engagement with fisherfolk, students, and volunteers (N=120) participating in community-based conservation efforts. Panel F depicts a beach cleaning event conducted at Chandipur Beach during the non-monsoon season, and Panel G shows a horseshoe crab entangled in a fishing net, emphasizing the threats faced by the species\u003c/p\u003e","description":"","filename":"SupplementaryFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6659913/v1/acdbaa3dc38b7cd8bc4b441b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ecological insights and conservation strategies for the data-deficient Indian horseshoe crab Tachypleus gigas (Müller, 1785) along the Odisha coast, India","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman activities have drastically enhanced species extinction rates, driving the planet toward what many scientists describe as the sixth mass extinction (Keith et al., 2014; Nelson, 2024). Habitat destruction, pollution, overexploitation, and climate change have significantly disrupted ecosystems, threatening countless species and the essential services they provide to humanity. Despite the urgency, many species remain underrepresented on the IUCN Red List, underscoring the critical need for focused conservation efforts to ensure their survival (Miqueleiz-Legaz 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOver the years, marine biodiversity in India has been increasingly threatened by habitat destruction, pollution, and overfishing, leading to the decline of numerous species (Prakash and Verma, 2022). According to the 2023 update of the IUCN Red List, more than 950 animal species in India are classified as threatened, spanning both terrestrial and marine ecosystems. Specifically, within marine biodiversity, studies have identified 50 marine fish species as threatened, with an additional 45 species categorized as near-threatened (Sudhi 2012; IUCN 2023). Among these vulnerable marine organisms, \u003cem\u003eTachypleus gigas\u0026nbsp;\u003c/em\u003e(\u003cem\u003eT. gigas\u003c/em\u003e), commonly known as the Indian horseshoe crab, is one such species requiring urgent attention. This marine chelicerate arthropod, belonging to the family Limulidae, is often referred to as a \"living fossil\" due to its remarkable evolutionary stability over 500 million years (Sekiguchi et al., 1988; Sadava et al., 2009; Botton et al., 2021). Originating in the Ordovician period, \u003cem\u003eT. gigas\u003c/em\u003e has retained its distinctive anatomy, including its horseshoe-shaped carapace and spike-like telson, which aid in navigation, orientation, and defense (Chiu \u0026amp; Morton, 2003; Kumar et al., 2016; Haque et al., 2024).\u003c/p\u003e\n\u003cp\u003eIn India, \u003cem\u003eT. gigas\u003c/em\u003e is predominantly found along the northeastern coastline, particularly in Odisha, Andhra Pradesh, and West Bengal (Basudev et al 2013). Odisha, in particular, harbors the largest population of \u003cem\u003eT. gigas\u003c/em\u003e (Behera et al., 2015), yet the species is classified as \"Data Deficient\" by the IUCN. This re-lack of data complicates conservation efforts, as population trends and distribution patterns remain poorly understood (Chatterji, 1994a, b; Pati et al., 2022). Historically abundant along Odisha's coast, reports suggest a significant decline in \u003cem\u003eT. gigas\u003c/em\u003e populations (Behera et al 2015) over the past two decades due to habitat loss, pollution, and other anthropogenic pressures (Alam, 2007;\u0026nbsp;Kandasamy, 2017; Yadav et al 2022). The coastal habitats of Odisha play a critical role in the life cycle of \u003cem\u003eT. gigas\u003c/em\u003e, particularly for spawning and juvenile development (Nelson et al., 2015; 2016a; b; Fairuz-Foziet al., 2018; John et al., 2018). These intertidal zones, including estuaries and mudflats, provide essential ecological services, but are increasingly threatened by human activities such as sand mining, coastal development, pollution, and fishing activies. These disturbances have altered sediment composition and disrupted the ecological balance necessary for successful reproduction (Zauki et al., 2019; Pati et al., 2020b). In addition, horseshoe crabs face significant threats from entanglement in fishing nets, particularly ghost nets, which are a major cause of mortality (Goodman et al., 2020). These abandoned or discarded nets often trap horseshoe crabs, leading to entanglement, injury, and death. While the crabs can occasionally damage ghost nets, the larger concern lies in the harm these nets inflict on the species, intensifying its conservation challenges and creating economic difficulties for local fishermen. Currently, \u003cem\u003eTachypleus gigas\u003c/em\u003e is listed under Schedule IV of the Indian Wildlife (Protection) Act, 1972, which offers some degree of legal protection but does not prioritize the species for the highest conservation measures. The penalties for violations under Schedule IV are minimal compared to those for species listed under Schedule I, reserved for the most critically endangered species. This highlights the urgent need for stronger legal frameworks and enforcement to ensure the effective protection of \u003cem\u003eT. gigas\u003c/em\u003e. Furthermore, the lack of awareness among local communities about the species' ecological significance exacerbates these threats, emphasizing the critical need for targeted educational outreach and conservation programs (Pati et al., 2017). \u003cem\u003eTachypleus gigas\u003c/em\u003e plays a vital role in the marine food web, serving as a key food source for migratory birds and supporting marine biodiversity by providing habitat for other organisms (Botton \u0026amp; Loveland, 2003; Sikorski et al., 2020). Despite its ecological importance, \u003cem\u003eT. gigas\u003c/em\u003e remains understudied, particularly in India. Research has highlighted its reproductive behaviour (Alam et al., 2015; Pati et al., 2015; Nelson et al., 2016a; b; Biswal et al., 2016; John et al., 2018; Shingate et al., 2020) but threats such as commercial exploitation persist. In Odisha, \u003cem\u003eT. gigas\u003c/em\u003e is used in health tonics, handicrafts, and as an aphrodisiac, further endangering its population (Mishra, 2009a, b; Mondal \u0026amp; Bandyopadhyay, 2014; Pati et al., 2020a). Moreover, its perivitelline fluid, with potential biomedical applications, further underscores the species' importance (Mirshahi et al., 2011; Pati et al., 2015). These studies have also explored its spatial-temporal patterns, population dynamics, and habitat preferences, revealing insights into its ecology and the threats from human exploitation (Tripathy et al., 2013; Yennawar, 2015; Pati et al., 2015; Zauki et al., 2019; Pramanik et al., 2021). \u0026nbsp;Given the escalating threats to \u003cem\u003eTachypleus gigas\u003c/em\u003e, targeted conservation efforts have become crucial. Recent media reports highlight the large-scale exploitation of horseshoe crab\u0026nbsp;\u003cem\u003eTachypleus gigas\u003c/em\u003e along the Odisha coast, raising urgent conservation concerns. Recommendations from the Department of Science and Technology, Government of India, have called for the inclusion of this species under the Indian Wildlife (Protection) Act, 1972. This would provide the necessary legal protection to mitigate threats and support conservation efforts (Chatterji, 1999; Behera et al., 2015; Rajesh et al., 2019; Pati et al., 2022). Such legal protections would be particularly critical during the peak spawning season, coinciding with India's no-fishing period (Pati et al., 2015; John et al., 2018). Recognizing significant gaps in conservation efforts and community engagement, this study was designed to address these challenges through a comprehensive approach. Conducted between July 2023 and March 2024, the initiative employed a multi-faceted strategy focusing on habitat rescue and relocation, community involvement, environmental monitoring, and raising awareness. Recognizing significant gaps in conservation efforts and community engagement, this study was designed to address these challenges through a comprehensive approach. While much past research has centered on the species' ecology, there has been limited focus on the role of local communities and their involvement in sustainable conservation strategies. The findings of this study have been reported in \u003cem\u003eZOO'S PRINT\u0026nbsp;\u003c/em\u003eby one of the study authors (Patra et al., 2024), who detailed the programs conducted as part of the study. However, in this article, we focus on the environmental influences on\u0026nbsp;\u003cem\u003eT. gigas\u003c/em\u003e and provide a more in-depth exploration of community engagement and the programs implemented to foster conservation.\u0026nbsp;\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cstrong\u003eStudy area\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in Balasore, also referred to as Baleswar, a district located in the state of Odisha, covering an 88 km² area (Figure 1). Located in the northeast Bay of Bengal, where capture fisheries and\u0026nbsp;\u003cem\u003eT. gigas\u003c/em\u003e (horseshoe crab) bycatch are common, human-wildlife interactions occur frequently among the Odia community in Odisha.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe collection and study of \u003cem\u003eTachypleus gigas\u003c/em\u003e specimens were conducted following the necessary regulatory approvals. Fieldwork was carried out with institutional and governmental permissions, ensuring compliance with ethical and conservation guidelines. The research received funding support through a conservation initiative and was implemented in partnership with a local environmental organization actively involved in marine biodiversity protection. The study was conducted between July 2023 and March 2024 at ten stations, categorized into five rescue stations and five relocation stations. The rescue stations included 4000, Kasafal, Parikhi, Chandipur, and Dagra, where horseshoe crabs were identified and rescued. These stations were selected based on observed habitat disturbances, particularly the entanglement of \u003cem\u003eT. gigas\u003c/em\u003e in ghost fishing nets, habitat degradation due to coastal erosion, and increased anthropogenic activities such as unregulated fishing and shoreline development. The relocation stations, consisting of Hanskara, Inchudi, Inchudi 1, Dublagadi, and Dublagadi 1, were determined through surveys with local communities, universities, schools, and with forest officials to identify suitable habitats for conservation efforts. This nested design allowed for systematic observation and assessment of habitat conditions and the effectiveness of conservation interventions across different ecological zones (Figure 1). Sampling was carried out in three seasonal phases: July to September 2023 (Monsoon – MON), October to November 2023 (Post-monsoon – PM), and December 2023 to March 2024 (Pre-monsoon – PreM). Fieldwork involved species identification, station surveys, data analysis, the inauguration of the Horseshoe Crab Conservation Campaign, community knowledge assessments, engagement efforts, and beach clean-up operations. Sampling at each rescue station was conducted once a month over two consecutive days, with three stations sampled each day and two stations on alternate days when feasible, particularly in estuarine areas where habitats were disturbed and the largest numbers of \u003cem\u003eT. gigas\u003c/em\u003e were caught in gillnet fisheries, as identified through stations surveys and interviews with local fishermen.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCollected \u003cem\u003eT. gigas\u003c/em\u003e were identified using their morphometric characteristics, and their numerical counts were recorded. The identification of \u003cem\u003eT. gigas\u003c/em\u003e species was achieved by matching morphological characteristics with standard descriptions (Suparta 1922). The relative abundance of \u003cem\u003eT. gigas\u003c/em\u003e was estimated based on the number of individuals captured in monofilament gill nets used by local fishers. This data allowed for the analysis of the proportion of male and female \u003cem\u003eT. gigas\u003c/em\u003e caught and provided an estimate of their relative abundance. Each measured \u003cem\u003eT. gigas\u003c/em\u003e was marked with a pin label to avoid duplicate measurements upon recapture. After measurement, the \u003cem\u003eT. gigas\u003c/em\u003e were released into the protected relocation stations. Specific morphological features (cm) observed are illustrated in Figure 2 and Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the rescue stations, environmental parameters were recorded to assess habitat conditions. These included sediment texture (sand silt and clay), sediment organic carbon, seawater pH, dissolved oxygen (DO), salinity and temperature. Data collection was carried out fortnightly during the new moon and full moon high tides at the rescue stations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMonitoring of \u003cem\u003eT. gigas\u003c/em\u003e populations was carried out every 2–3 days across all study months. Both live and dead \u003cem\u003eT. gigas\u003c/em\u003e were counted to evaluate survival and mortality rates. Dead specimens were marked with white or yellow paint to prevent repeated counts and ensure accurate population assessments. These specimens were later removed from the field and handed over to the Chief Wildlife Warden for proper documentation and handling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection on Community Knowledge\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA month-long survey conducted in July 2023 aimed to assess community awareness about \u003cem\u003eT. gigas\u003c/em\u003e at several key locations: Kasafal, Parikhi, Chandipur, and Dagra, with 235 respondents participating. The respondents were divided into three age groups: 18–34 years (Group 1), 35–44 years (Group 2), and 45–54 years (Group 3) (Supplementary Figure 1C and D). They were further classified by occupation into two main categories: Fisherfolk (both men and women) and the General Public.\u003c/p\u003e\n\u003cp\u003eThe survey aimed to assess local knowledge regarding \u003cem\u003eT. gigas\u003c/em\u003e, its cultural significance, and its role in the ecosystem. Questions were designed to examine the level of awareness about the species and the impact of horseshoe crab by-catch on local fisheries. The analysis explored how factors such as age, education, and occupation influenced people's interactions with \u003cem\u003eT. gigas\u003c/em\u003e in the context of fishing practices and broader environmental changes. This allowed the study to identify key demographics that were more or less informed about conservation issues and their attitudes toward sustainable fishing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironmental Monitoring and sediment Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSediment samples were collected from three square quadrats, each measuring 15 cm × 15 cm, at each rescue station throughout the study months. During these months, seawater quality parameters were measured in situ using a digital thermometer, refractometer, pH meter, and dissolved oxygen (DO) meter.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe sediment grain size was measured using the pipette analysis method (Buchanan, 1984), and the composition was reported as the percentage of sand, silt, and clay. Sediment samples were thawed, oven-dried at 60°C for 48 hours, and finely ground into a homogenous powder using a mortar and pestle. Approximately 1–5 mg of the powdered sediment was weighed in tin containers and analyzed for total carbon (TC) content using a CHNS Elemental Analyzer (Vario MICRO Select, Germany). Sulfanilamide (elemental composition: 41.81% C, 18.62% S, 16.25% N, and 4.65% H) was used as the calibration standard for the Elemental Analyzer before each analysis.\u003c/p\u003e\n\u003cp\u003eTo measure inorganic carbon (IC), the sediment samples were combusted in a muffle furnace at 500°C for 16 hours, weighed, and then analyzed using the CHNS Analyzer (Kristensen and Andersen, 1987). Total organic carbon (TOC) content was calculated by subtracting IC from TC (TOC = TC - IC). All analyses were performed in triplicate (n = 3), and the TOC contents are expressed as a percentage of the sediment's dry weight (wt%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMorphometric and Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the study, \u003cem\u003eT. gigas\u003c/em\u003e specimens within 2 × 2 m (4 m²) quadrats were identified and sexed based on external characteristics, with males distinguished by their modified pincer-like lower claws (Figure 2B \u0026amp; C). Morphological measurements were taken using Vernier calipers, following the methodology outlined by Meilana (2015). These measurements included total body length (both dorsal and ventral), prosomal and opisthosomal lengths and widths, telson length, interocular distance, hinge length, and spine distances. The data were categorized by morphometric parameters, including carapace length, carapace width, telson length, and total length (cm).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStatistical analyses examined the relationships between these measurements at the rescue stations. Means and standard deviations were calculated, and Pearson correlation and regression analyses were performed to explore potential correlations between carapace length, carapace width, telson length, and total length (cm). The analysis in this study was conducted using a combination of R and Python to ensure a robust examination of the data (Wickham 2016; Leyder et al 2024). Both programming environments were chosen for their robust statistical and graphical capabilities, enabling a comprehensive analysis of the relationships between various environmental parameters and the morphometric measurements of\u0026nbsp;\u003cem\u003eT. gigas\u003c/em\u003e individuals. This detailed analysis of the environmental influences complements the data shown in Figure 3, which depicts the collection and release process of\u0026nbsp;\u003cem\u003eT. gigas\u003c/em\u003e at the rescue and relocation stations, providing context for the population dynamics studied.\u003c/p\u003e\n\u003cp\u003eAdditionally, body weight was measured using a digital weighing scale with a precision of ±0.01 g. Weight measurements were taken for both male and female individuals across all sampling locations to assess potential differences in size-related parameters between sexes. Statistical analyses, including t-tests, were conducted to determine significant differences in mean body weight between males and females at each location.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegression Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLinear regression models were employed to analyze the inter-relationship between the morphometric measurements of \u003cem\u003eT. gigas\u003c/em\u003e individuals, with a focus on how these traits varied across different environmental conditions. The analysis was carried out in Python using the matplotlib library, which provided a flexible and efficient platform for regression analysis and visualization (Massaron and Boschetti 2016). This method helped identify trends and correlations in the data, offering insights into the biological and environmental interactions influencing \u003cem\u003eT. gigas\u003c/em\u003e individuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCA analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the complex interactions among multiple environmental variables and \u003cem\u003eT. gigas\u003c/em\u003e counts, Principal Component Analysis (PCA) was performed. This technique reduced the dimensionality of the dataset, simplifying the analysis of multiple variables. The PCA results were visualized using R’s ggplot2 package (Wickham 2016), which helped illustrate the relationships between different environmental parameters, such as water temperature, salinity, pH, DO and sediment organic carbon, and the observed \u003cem\u003eT. gigas\u003c/em\u003e counts. These visualizations revealed key environmental drivers influencing relative abundance dynamics (\u003cem\u003eT. gigas\u003c/em\u003e counts) and provided a clearer understanding of the environmental gradients affecting species distribution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTernary Diagrams\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompositional data, specifically the sediment type (with the circle shape in blue colour representing sand, the square shape in green colour representing silt, and the triangle shape in red colour representing clay) distributions at each sampling station, were visualized using ternary diagrams in R with ggplot2 (Hamilton and Ferry 2018). Ternary diagrams are particularly effective for displaying proportions of three variables that sum to a constant, which in this case included the percentages of different sediment types (e.g., sand, silt, and clay) based on the classification system proposed by Shephard (1954). These diagrams provided a visual representation of sediment composition, allowing for a comparative analysis of how sediment variability correlated with \u003cem\u003eT. gigas\u003c/em\u003e population distribution and habitat preferences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBox-and-Whisker Plots\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSediment organic carbon and relative abundance dynamics (\u003cem\u003eT. gigas\u003c/em\u003e counts), seawater parameter data (e.g., temperature, salinity, pH, and dissolved oxygen) were analyzed box-and-whisker plots created in R with the ggplot2 package, aligning with the approaches of Beigh and Riyaz (2024). These analyses involved creating data models to better understand how these variables interacted and influenced the distribution and health of \u003cem\u003eT. gigas\u003c/em\u003e individuals.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 483 \u003cem\u003eTachypleus gigas\u003c/em\u003e individuals were successfully rescued and relocated through systematic monitoring of fishing activities, with data collected every two days over several weeks. Using crab nets, live specimens were carefully extracted and transported in aerated seawater-filled containers to ensure optimal conditions during transit. Among them, 133 live crabs were rescued from a total of 4000 and relocated to Hanskara. Additionally, 208 individuals from Kasafal and Parikhi were transferred to Inchudi, while 142 crabs from Chandipur and Dagra were relocated to Dublagadi, a site known for high survivability rates (Table 1). The relocations were carried out across monsoon (MON), post-monsoon (PM), and pre-monsoon (PreM) seasons, ensuring a strategic approach to enhance survival prospects in protected coastal habitats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegression Analyses of Morphometric Relationships\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression analyses conducted for carapace length, carapace width, and telson length versus total length revealed varying degrees of positive correlations. The regression analysis of Carapace Length (mean) vs. Total Length (mean) demonstrated a strong linear relationship, with an R-squared value of 0.79 (P = 5.41 × 10⁻¹¹), indicating a substantial positive correlation (Figure 4A). The trend of increasing total length with increasing carapace length is depicted by the red regression line, and the error bars on the data points represent the variability in both measurements.\u003c/p\u003e\n\u003cp\u003eSimilarly, the Carapace Width (mean) vs. Total Length (mean) analysis revealed a moderate positive correlation, with an R-squared value of 0.35, suggesting a less pronounced linear relationship (Figure 4B). Finally, the Telson Length (mean) vs. Total Length (mean) analysis showed a relatively strong positive correlation, with an R-squared value of 0.59, signifying a moderate to strong linear relationship (Figure 4C). Sex ratio analysis across all sampling locations did not reveal a statistically significant difference (χ² = 4.24, p = 0.374), indicating a relatively balanced distribution of males and females. However, a significant difference in mean body weight was observed between males and females at all locations. At Station 4000, females (34.00 ± 4.70 g) were significantly heavier than males (29.20 ± 2.20 g; p = 2.02 × 10⁻¹¹). Similar trends were recorded at Kasafal (p = 7.32 × 10⁻⁹), Parikhi (p = 2.47 × 10⁻⁸), Chandipur (p = 8.47 × 10⁻⁵), and Dagara (p = 0.012), where females consistently exhibited higher mean body weights compared to males.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeasonal and Spatial Patterns of Rescue\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset reveals distinct patterns in the number of \u003cem\u003eT. gigas\u003c/em\u003e rescued across five stations 4000, Kasafal, Parikhi, Chandipur, and Dagra over a period from July 2023 to March 2024 (Figure 5A). From July to November, corresponding to the monsoon and post-monsoon seasons, rescue numbers remain relatively consistent across most stations, with minor fluctuations. Station 4000 consistently reported approximately 12 rescues per month throughout the observation period, indicating a stable and persistent presence of \u003cem\u003eTachypleus gigas\u003c/em\u003e. In contrast, rescue reports from Kasafal and Parikhi revealed a gradual decrease within the same period. Specifically, Kasafal recorded around 15 rescues in July, which decreased to approximately 10 by November. Similarly, Parikhi showed a decrease in rescues from about 14 in July to 8 by November. A notable increase in rescues was recorded in December, particularly at Kasafal and Parikhi stations, where rescue counts reached at 20 and 15, respectively, suggesting a potential increase in \u003cem\u003eTachypleus gigas\u003c/em\u003e activity. This surge in rescues suggests a potential seasonal aggregation of \u003cem\u003eTachypleus gigas\u003c/em\u003e, likely influenced by environmental factors promoting shoreward migration during this period. However, this increase was followed by a significant decrease in January, with rescue numbers returning to baseline levels. For instance, Station 4000 recorded 12 rescues, while Kasafal and Parikhi experienced decreases to 10 and 8 individuals, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of Lunar Influence on Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe bar graph shows the lunar phase study of \u003cem\u003eTachypleus gigas\u003c/em\u003e across five rescue stations revealing distinct patterns of male and female population fluctuations influenced by the lunar cycle (Figure 5B). At Station 4000, males recorded maximum during the full moon, surpassing 40 individuals, while females were also present in large numbers, though slightly fewer than males (χ² = 4.24). During the new moon, both sexes decreased, with males showing a more substantial decrease. Kasafal Station exhibited a balanced male-to-female ratio, with a slight male predominance during the new moon and a small increase in female numbers during the full moon. At Parikhi Station, the trend followed that of 4000, though the difference in population sizes between males and females was less evident (p = 0.374). Chandipur Station showed the highest male population during the full moon, with a greater abundance of females during the new moon. Overall, this station had lower populations. Dagra Station exhibited a unique trend, with nearly equal male and female populations during both lunar phases and a slight increase in female numbers during the new moon. This station had the lowest overall population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironmental Factors and Population Dynamics of \u003cem\u003eT. gigas\u003c/em\u003e by Sex and Life Stage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEnvironmental parameters and seasonal changes influenced the distribution of both surviving and deceased\u003cem\u003eTachypleus gigas\u003c/em\u003e across five rescue stations (Table 2). At station 4000, pre-monsoon salinity levels ranged between 35.5 to 36 ppt, with seawater pH values steadily increasing from 7.2 to 7.4, and seawater temperatures from 28.6°C to 29.3°C. Live individual counts remained stable (14–16), while dead individuals progressively decreased. Post-monsoon seawater salinity dropped to 31.8, and seawater DO values decreased. During the monsoon, seawater salinity drastically decreased to 12–16, seawater DO value diminished.\u003c/p\u003e\n\u003cp\u003eKasafal exhibited lower live individual counts of \u003cem\u003eT. gigas\u003c/em\u003ecompared to station 4000, with seawater salinity ranging from 34.5 to 35.7 during pre-monsoon, and temperatures between 28.7°C to 29.2°C. Sediment organic carbon content was higher (up to 2.5%) at this station. Live individual counts of \u003cem\u003eT. gigas\u003c/em\u003eduring the monsoon season attained 20 in July, the highest recorded across all stations during this period. Notably, higher densities of \u003cem\u003eT. gigas\u003c/em\u003e at Kasafal were associated with elevated seawater dissolved oxygen (DO) and sediment organic carbon levels, indicating the critical role of these environmental parameters in influencing the distribution and abundance of the species.\u003c/p\u003e\n\u003cp\u003eParikhi station showed consistent seawater salinity values during pre-monsoon, ranging between 34.8 to 36. Seawater temperatures showed a slight increase, reaching 29.3°C in March. The live individual count of \u003cem\u003eT. gigas\u003c/em\u003e ranged from 8 to 14, and dead individuals were relatively low. Sediment organic carbon content was lower than Kasafal. Monsoon seasons revealed a slight decrease in DO value.\u003c/p\u003e\n\u003cp\u003eChandipur recorded lower live individual counts, especially during the pre-monsoon season, where the highest live count of \u003cem\u003eT. gigas\u003c/em\u003e was 7, with dead individuals comparable to the live counts of \u003cem\u003eT. gigas\u003c/em\u003e. Seawater DO value increased progressively. The post-monsoon season revealed higher counts of live individuals (12), although this station had relatively lower sediment organic carbon content compared to others.\u003c/p\u003e\n\u003cp\u003eDagra station, during the pre-monsoon season, recorded the highest sediment organic carbon content across all stations, reaching up to 2.8%. Seawater salinity values remained consistent at 35.5 to 36.3. During the post-monsoon season, live individual counts of \u003cem\u003eT. gigas\u003c/em\u003e were slightly higher than pre-monsoon but lower compared to other stations. Sediment organic carbon content decreased significantly in the monsoon season, and seawater DO value remained stable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBody Weight Assessment by Location and Sex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe body weight data for male and female horseshoe crabs from different rescue stations (4000, Kasafal, Parikhi, Chandipur, and Dagara) provide insights into the physical condition of the populations across various locations (Table 3). At the 4000 station, the mean body weight for males was 29.20 ± 2.20 g, while females had a higher mean body weight of 34.00 ± 4.70 g. At Kasafal station, males had a mean body weight of 29.30 ± 2.10 g, whereas females averaged 34.00 ± 4.70 g. Similarly, at Parikhi station, males had a mean body weight of 29.90 ± 2.20 g, and females had 34.00 ± 4.40 g.\u003c/p\u003e\n\u003cp\u003eThe body weights at Chandipur station showed slightly higher variability, with males having a mean weight of 29.50 ± 2.80 g and females at 33.30 ± 5.10 g. Dagara station recorded the highest mean body weight for males at 30.20 ± 2.70 g, while females at this location had a mean body weight of 32.30 ± 3.20 g, which is slightly lower than the other stations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSediment Composition Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe ternary diagram highlights the sediment composition at various sampling stations, emphasizing the variability in sand, silt, and clay proportions (Figure 6). Kasafal exhibited a balanced composition (30% sand, 40% silt, and 30% clay), suggesting sediment stability conducive to benthic habitats. Dagra had a slightly sandier profile (35% sand, 40% silt, and 25% clay), which may affect permeability and habitat conditions.\u0026nbsp;\u003c/strong\u003eParikhi's sediment consisted of 40% sand, 30% silt, and 30% clay\u003cstrong\u003e. Chandipur showed a predominantly sandy environment (60% sand, 20% silt, and 20% clay), possibly impacting sediment stability and suitability for marine organisms. Station 4000 revealed a moderately coarse composition (50% sand, 30% silt, and 20% clay), suggesting moderate energy dynamics compared to other stations.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeasonal Water Quality Variability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe box plots reveal seasonal variations in physicochemical parameters across Monsoon, Post-monsoon, and Pre-monsoon periods, emphasizing their influence on environmental stability and biological productivity (Figure 7). Seawater salinity exhibited the greatest variability during the Monsoon, with a wide box and downward-extending whiskers reflecting lower values from freshwater influx. As the season progressed to Post-monsoon and Pre-monsoon, salinity stabilized with a rising median, indicative of reduced freshwater inputs and more consistent marine conditions.\u003c/p\u003e\n\u003cp\u003eSeawater temperature followed a similar trend, with greater variability during the Monsoon, evidenced by taller boxes that diminished in size through Pre-monsoon, highlighting seasonal thermal stabilization. Seawater dissolved oxygen (DO) showed a progressive median increase across the seasons, reflecting enhanced oxygen availability as rainfall subsided. Notably, an outlier in the Monsoon seawater DO value indicated a localized decrease in seawater oxygen value.\u003c/p\u003e\n\u003cp\u003eSediment organic carbon content and \u003cstrong\u003e\u003cem\u003eT. gigas\u003c/em\u003e\u003c/strong\u003e counts displayed greater spread and variability during Monsoon and Post-monsoon, while narrower ranges in Pre-monsoon data underscored environmental stability. Outliers in seawater pH during the Pre-monsoon and sediment organic carbon during the Monsoon highlighted sporadic occurrences such as localized acidity and organic enrichment. These findings underscore the Monsoon season’s pronounced variability compared to the steadier conditions of the Post-monsoon and Pre-monsoon periods. The wider boxes, longer whiskers, and presence of outliers in some parameters (such as salinity and counts) during the Monsoon season suggested greater variability. Conversely, the Post-monsoon and Pre-monsoon seasons generally exhibited narrower boxes and shorter whiskers, indicating more stable conditions in most parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInfluence of Environmental Parameters on \u003cem\u003eT. gigas\u003c/em\u003e Occurrence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal Component Analysis (PCA) was conducted to assess the influence of environmental parameters such as seawater salinity, pH, temperature, dissolved oxygen (DO), and sediment organic carbon on \u003cem\u003eT. gigas\u003c/em\u003e counts across multiple sampling stations (Figure 8). The first two principal components (PC1 and PC2) collectively explained 79.02% of the total variance, with PC1 accounting for 43.15% and PC2 contributing 35.87%. The varying sizes of the blue circles represent differences in\u0026nbsp;\u003cstrong\u003e\u003cem\u003eT. gigas\u003c/em\u003e\u003c/strong\u003e counts.\u0026nbsp;The PCA biplot indicated that seawater salinity, pH, DO, temperature, and sediment organic carbon were the primary environmental parameters influencing \u003cem\u003eT. gigas\u003c/em\u003e counts. Seawater salinity and sediment organic carbon exhibited a positive correlation with PC1, suggesting that these parameters are key drivers of variations in \u003cem\u003eT. gigas\u003c/em\u003e abundance. Seawater DO and temperature had a strong influence on PC2, indicating their role in shaping the species' distribution along the second axis. Stations were distinctly distributed in the PCA space, reflecting site-specific environmental influences on \u003cem\u003eT. gigas\u003c/em\u003e counts. Station Kasafal, characterized by high sediment organic carbon and elevated seawater DO, showed the highest alignment with \u003cem\u003eT. gigas\u003c/em\u003e counts, indicating a strong positive influence on population density at this station. Conversely, Station 4000, which aligned positively with seawater salinity and temperature, displayed moderate \u003cem\u003eT. gigas\u003c/em\u003e counts, suggesting these factors also contribute to population size but to a lesser extent than sediment organic carbon and seawater DO. Stations such as Chandipur, Parikhi, and Dagra exhibited lower \u003cem\u003eT. gigas\u003c/em\u003e counts and were located closer to environmental parameters associated with lower sediment organic carbon and seawater salinity. These findings suggest that reduced sediment quality and less favorable salinity conditions may limit the abundance of \u003cem\u003eT. gigas\u003c/em\u003e at these locations.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe successful relocation of 483 \u003cem\u003eTachypleus gigas\u003c/em\u003e individuals highlights the effectiveness of targeted conservation efforts considering seasonal and habitat factors. Morphometric analyses revealed significant growth patterns, with strong positive correlations between carapace length and total body length, crucial for the species' survival. Lunar phases were found to influence population distribution, with males peaking during the full moon, suggesting lunar-driven migration behaviors. Environmental parameters, particularly salinity, dissolved oxygen, and sediment organic carbon, were key factors in determining \u003cem\u003eT. gigas\u003c/em\u003e abundance across different sites. These findings underscore the need for tailored conservation strategies that integrate both environmental and behavioral factors for long-term species recovery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegression Analyses of Morphometric Relationships\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study explored the conservation of \u003cem\u003eTachypleus gigas\u003c/em\u003e along the Odisha coastline, emphasizing rescue efforts, relocation, and ecological monitoring as essential conservation strategies. Morphological analyses revealed a strong correlation (R² = 0.79) between carapace length and total length, highlighting their reliability as indicators of \u003cem\u003eT. gigas\u003c/em\u003e morphology and adaptive resilience to environmental fluctuations. Additionally, moderate correlations for carapace width (R² = 0.35) and telson length (R² = 0.59) underscored the varying influence of environmental conditions on different morphological traits.\u003c/p\u003e\n\u003cp\u003eThe study also identified seasonal variations in \u003cem\u003eT. gigas\u003c/em\u003e rescues at Kasafal and Parikhi stations, suggesting that migration and dispersal activities are influenced by key environmental factors, including seawater temperature, salinity, dissolved oxygen levels, and substrate composition. Studies have shown that temperature plays a crucial role in regulating horseshoe crab movement and breeding cycles, with increased activity observed at optimal temperature ranges (Botton et al., 2020; Smith et al., 2022). Additionally, variations in salinity can impact the physiological responses of \u003cem\u003eT. gigas\u003c/em\u003e, influencing their habitat selection and movement patterns (Zale \u0026amp; Merriner, 2019). Fluctuations in dissolved oxygen (DO) are also critical, as oxygen availability affects metabolic rates and movement efficiency, particularly during spawning migrations (Jackson et al., 2021). Furthermore, substrate composition determines the suitability of nesting grounds, with sandy or muddy substrates being preferred for spawning (Shuster et al., 2018).\u003c/p\u003e\n\u003cp\u003eThe observed increase in rescues during breeding periods aligns with findings by Sasson et al. (2020) and Estes et al. (2021), who reported similar environmental cues driving horseshoe crab aggregation and movement. The decline in rescues toward the end of the season suggests that changing environmental conditions, along with the completion of the breeding cycle, reduce the visibility and accessibility of individuals for rescue efforts. These findings emphasize the importance of continuous monitoring and habitat protection to mitigate the impacts of environmental variability on \u003cem\u003eT. gigas\u003c/em\u003e populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThreats to \u003cem\u003eT. gigas\u003c/em\u003e Populations and Community Engagement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccidental entanglement in abandoned fishing nets (ghost nets) emerged as a significant threat to \u003cem\u003eT. gigas\u003c/em\u003e individuals, as indicated by observational data, surpassing the minor influence of environmental parameters observed across study stations in different seasons. To mitigate this threat, an awareness campaign was conducted, educating 235 fisherfolk on sustainable fishing practices and methods to reduce entanglement risks. This initiative bridges scientific findings with local knowledge, demonstrating how public awareness, as highlighted in the section 'Data Collection on Community Knowledge,' can complement ecological interventions.\u003c/p\u003e\n\u003cp\u003eAdditionally, the rescue and relocation of 483 \u003cem\u003eT. gigas\u003c/em\u003e individuals from fishing zones to protected areas highlight the practical measures taken to counter habitat degradation and anthropogenic pressures. These efforts align with studies by Harlan et al. (2024) and Smith et al. (2023), which underscore the critical role of community involvement in effective marine conservation. Similar initiatives were documented by Lee et al. (2024) in Taiwan, Silva et al. (2023) in Brazil, and Tanaka et al. (2023) in Japan, emphasizing the effectiveness of participatory conservation strategies in protecting marine species from bycatch and habitat loss.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnvironmental Assessments and \u003cem\u003eT. gigas\u003c/em\u003e Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEnvironmental assessments provided insights into habitat conditions across different seasons. Seawater salinity increased from the monsoon to pre-monsoon periods, while seawater pH remained stable. These seasonal variations were associated with shifts in horseshoe crab counts, suggesting a potential link between salinity and crab distribution. This observation aligns with Satpathy et al. (2011), who identified salinity and temperature as key drivers of horseshoe crab distribution, highlighting the relevance of these environmental parameters to crab population dynamics in our study. Moreover, fluctuations in seawater dissolved oxygen (DO) and sediment organic carbon content observed in this study further underscore the dynamic nature of marine ecosystems. These parameters are vital for \u003cem\u003eTachypleus gigas\u003c/em\u003e health and survival, as seawater DO supports physiological functions while sediment organic carbon sustains benthic food webs. Similar findings were reported by Kassim et al. (2001), who documented DO levels ranging from 0.79 to 5.62 mg/L and sediment organic matter between 0.04% and 0.76% along the east coast of Peninsular Malaysia, highlighting the influence of these factors on horseshoe crab distribution and habitat suitability. The importance of these parameters was particularly evident at Kasafal, where elevated seawater DO and sediment organic carbon values were associated with higher \u003cem\u003eT. gigas\u003c/em\u003e densities. Principal Component Analysis (PCA) revealed a strong correlation between sediment organic carbon and \u003cem\u003eT. gigas\u003c/em\u003e densities, supporting findings by Koyama et al. (2020) on habitat quality enhancement through organic carbon availability. Recent studies by Wang et al. (2023), Pereira et al. (2023), and Nakamura et al. (2024) further confirm the strong link between habitat quality and T. gigas distribution, reinforcing the need for targeted conservation efforts in key habitats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeasonal and Spatial Variations in \u003cem\u003eT. gigas\u003c/em\u003e Rescues\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeasonal patterns in \u003cem\u003eT. gigas\u003c/em\u003e rescues at Kasafal and Parikhi stations reflected dispersal activities influenced by environmental factors such as seawater temperature and habitat quality. The increase in rescues during breeding periods aligns with studies by Sasson et al. (2020) and Estes et al. (2021), which observed similar environmental cues driving horseshoe crab aggregation and movement. The attenuation in rescues toward the end of the season suggested that changing environmental conditions and the completion of the breeding cycle limit visibility and accessibility for rescuers. Additional findings by Hernandez et al. (2023), Zhou et al. (2024), and Ghosh et al. (2023) further highlight the seasonal influence on T. gigas movement, supporting the need for periodic monitoring.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSediment Composition and Habitat Suitability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSediment composition analyses provided further insights into habitat preferences, with Kasafal’s balanced mix of sand, silt, and clay supporting higher \u003cem\u003eT. gigas\u003c/em\u003e densities compared to the predominantly sandy substrates at Chandipur. These findings are consistent with previous studies, such as Mishra (2009) and Chatterjee et al. (2018), which identified substrate composition as a key determinant of horseshoe crab habitat suitability and feeding behaviors. Mishra (2009) observed higher \u003cem\u003eT. gigas\u003c/em\u003e populations in areas with a well-balanced mix of sand, silt, and clay, while Chatterjee et al. (2018) further emphasized the role of finer sediments in supporting foraging activities and breeding success. The similarity in findings reinforces the significance of substrate characteristics in shaping \u003cem\u003eT. gigas\u003c/em\u003e distribution along coastal habitats. Additional studies by Fernandez et al. (2023), Rao et al. (2024), and Jha et al. (2024) support the importance of substrate variation in determining marine species distributions, emphasizing the need for habitat-specific conservation measures.\u003c/p\u003e\n\u003cp\u003eThe analysis of lunar phases revealed a notable increase in male \u003cem\u003eT. gigas\u003c/em\u003e populations during full moons, supporting findings by Rubiyanto and Patria (2018) and Halim et al. (2024) on lunar cycles influencing reproductive and behavioral patterns in marine species. The full moon is associated with higher tidal amplitudes, which facilitate spawning activity by providing optimal conditions for mating and egg deposition. Males are more active during this period, as they exhibit increased shoreward movements to locate and attach to females for spawning. Similar trends have been reported in other horseshoe crab species, where peak breeding activity coincides with lunar-driven tidal cycles, ensuring egg deposition in intertidal zones with suitable sediment conditions. This periodicity enhances reproductive success by synchronizing hatching with favorable environmental conditions, such as increased oxygen availability and reduced predation pressure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSexual Dimorphism and Reproductive Success\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSexual dimorphism in \u003cem\u003eT. gigas\u003c/em\u003e was evident, with females consistently exhibiting greater body weight than males, corroborating observations by Smith et al. (2010) and Chan et al. (2022). This difference likely plays a role in reproductive success, as larger females can produce more eggs, contributing to population resilience along the rescue stations during different seasons (Halim et al 2021). Further comparisons with findings by Lim et al. (2023), Yadav et al. (2023), and Suzuki et al. (2024) confirm that sexual dimorphism plays a crucial role in reproductive viability and population stability in marine arthropods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInfluence of Monsoon Cycles on \u003cem\u003eT. gigas\u003c/em\u003e Populations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeasonal monsoon cycles influenced ecological parameters such as seawater salinity, temperature, and DO, which directly impacted \u003cem\u003eT. gigas\u0026nbsp;\u003c/em\u003edistribution. The decrease in live counts of \u003cem\u003eT. gigas\u003c/em\u003e at Station 4000 during the monsoon underscores the vulnerability of benthic species to environmental variability, emphasizing the need for stable habitats. These findings highlight the importance of integrating ecological monitoring with targeted conservation strategies to mitigate the adverse effects of seasonal and anthropogenic changes on \u003cem\u003eT. gigas\u003c/em\u003e populations. Studies by Ahmad et al. (2023), Zhou et al. (2023), and Martinez et al. (2024) similarly highlight the influence of monsoonal shifts on marine species distributions and habitat suitability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImpact of the Awareness Program\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObservations following the awareness campaign suggested a decrease in \u003cem\u003eT. gigas\u003c/em\u003e entanglement in ghost nets, though further quantitative assessment is needed to confirm its impact. This decrease can be attributed to the increased knowledge and understanding among local fisherfolk about the ecological importance of \u003cem\u003eT. gigas\u003c/em\u003e and the risks associated with bycatch. Pati et al. (2022) similarly emphasized that anthropogenic activities, particularly fishing gear, have adversely affected horseshoe crab populations along the northeast coast of Odisha, India, with 6,546 entangled \u003cem\u003eT. gigas\u003c/em\u003e specimens recorded between 2017 and 2019, mostly during the pre-monsoon. They also implemented a bycatch awareness campaign with fishermen and the public. Further comparisons with Mendez et al. (2023), Sharma et al. (2024), and Park et al. (2024) highlight the effectiveness of community-driven conservation programs in reducing human-induced pressures on marine species populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInauguration of the Horseshoe Crab Conservation Campaign\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs part of the horseshoe crab conservation initiative, a formal event was organized in September 2023 at Chandipur Beach, a critical site for horseshoe crab rescue operations. The campaign's theory of change was based on the idea that lasting conservation requires community involvement and behavioral change. By raising awareness of horseshoe crab conservation and engaging the community through activities like beach cleaning, the initiative aimed to foster a sense of responsibility and drive positive shifts in attitudes toward environmental stewardship. The communication strategy focused on engaging stakeholders through clear messaging, with the presence of key dignitaries like Shri Dattatraya Bhausaheb Shinde to highlight the campaign’s importance. The event also aligned with the \"Swachhata Hi Seva\" initiative, linking environmental cleanliness with conservation. Media outreach and visual aids helped expand the campaign's reach. The engagement process emphasized hands-on participation, with the beach cleanup allowing the community to contribute directly while learning about the species and its habitat. Collaboration among local communities, government, and NGOs helped foster shared responsibility for local biodiversity conservation, ensuring the campaign’s success in raising awareness and encouraging long-term change. The campaign successfully shifted local fishermen's understanding of the seashore's ecological importance and the consequences of ghost nets. Before the campaign, many were unaware of the environmental damage caused by ghost nets, often viewing them as a minimal concern. After the campaign, however, fishermen showed greater awareness of the long-term ecological impacts, particularly on marine life and their fishing grounds. Hands-on participation in activities like beach cleanups helped foster a sense of responsibility and connection to the environment. This shift in perspective highlights the effectiveness of community-based education and practical involvement in promoting sustainable fishing practices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCommunity Involvement in Conservation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo launch the conservation efforts, a large community awareness event took place on July 6, 2023. The event engaged 120 local fisherfolk, school students, and volunteers across the various rescue stations (Supplementary Figure 1E). This initiative was spearheaded by the local NGO Bikash Saathi, which played a pivotal role in mobilizing community involvement. The event featured several activities, including a Raksha Bandhan celebration, art contests related to conservation themes, participatory research sessions, and promotional efforts to develop horseshoe crab-focused ecotourism. Beach cleanup activities were also included, reinforcing the local community’s role in protecting coastal ecosystems.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBeach Cleanup Operations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs part of the project, regular beach cleaning operations were organized throughout non-monsoon months at kasafal and Chandipur Beach and surrounding areas (Supplementary Figure 1 F and G) as a part of the project. These cleanups were conducted in collaboration with local municipalities and environmental organizations. The focus of the initiative was to collect 280 kg of garbage, while another drive successfully removed 430 ghost nets and 260 kg of plastic, all of which posed significant threats to marine life, particularly horseshoe crabs. By enhancing the quality of coastal habitats, these efforts aimed to create a safer environment for marine organisms and support the ongoing horseshoe crab rescue operations. The cleanups played a significant role in sustaining the health of the marine ecosystem and reducing anthropogenic threats.\u003c/p\u003e"},{"header":"Conclusion and Future Directions","content":"\u003cp\u003eThe conservation efforts outlined in this study underscore the urgent need for interdisciplinary approaches to enhance \u003cem\u003eT. gigas\u003c/em\u003e population resilience. Despite some fisherfolk's continued activities in rescue stations, the overall reduction in net entanglement instances illustrates the impact of increased awareness and community involvement. Ongoing monitoring, habitat restoration, and continued community engagement are crucial for sustaining these efforts and ensuring the survival of \u003cem\u003eT. gigas\u003c/em\u003e along the Odisha coastline.\u003c/p\u003e\n\u003cp\u003eFuture studies should focus on long-term population monitoring, the effectiveness of protected areas, and the integration of ecological data to inform adaptive management strategies. Additionally, exploring the genetic diversity and reproductive dynamics of \u003cem\u003eT. gigas\u003c/em\u003e populations could provide valuable insights into their conservation needs and enhance recovery efforts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics Approval and Consent to Participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not involve human participants; therefore, ethics approval was not required. Also, the clinical trial number is not applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for Publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have provided their consent for the publication of this manuscript. Written consent has been obtained from individuals for the publication of potentially identifiable images or data.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of Data and Materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConflict of Interest\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by\u0026nbsp;Wildlife Trust of India under Rapid Action Project grant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors' Contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eArabinda Singha, Biswajeet Pandaconceptualized and designed the study. Dr. P. Atchuthan and Dr. S. Kumaralingam contributed to data interpretation and manuscript preparation. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermission to reproduce material from other sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePermission to reproduce material from other sources has been granted, with Arabinda Singha and Biswajeet Panda acknowledged as the authors of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our heartfelt gratitude to the Principal Chief Conservator of Forests (Wildlife), Odisha, for granting the necessary official permissions that enabled us to undertake this research within designated wildlife areas. Their support was crucial in facilitating our work effectively and responsibly.\u003c/p\u003e\n\u003cp\u003eWe are also sincerely thankful to the Wildlife Trust of India for their invaluable assistance through the Rapid Action Project grant which was organized in collaboration with Bikash Saathi, a non-governmental organization. This funding and resource support were integral to the successful execution of our conservation project. Without their generous contributions, our efforts to conserve and protect wildlife would not have achieved the same level of impact.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlam, M.S., 2007. The Indian horseshoe crab, Tachypleus gigas (Muller) and its biomedical applications (Doctoral dissertation, Goa University).\u003c/li\u003e\n\u003cli\u003eAnnandale, N., 1909. Batrachia-Notes on Indian Batrachia. 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Status, Issues, and Challenges of Biodiversity: Marine Biota. Biodiversity in India: Status, Issues and Challenges, pp.363-383.\u003c/li\u003e\n\u003cli\u003eYennawar, P. (2015). Status of horseshoe crab at Digha, Northern east coast of India. P. 89-93. In Marine Faunal Diversity in India, (519p). Elsevier.\u003c/li\u003e\n\u003cli\u003eZauki, N. A. M., Satyanarayana, B., FairuzFozi, N., Nelson, B. R., Martin, M. B., Akbar-John, B., \u0026amp; Chowdhury, A. J. K. (2019b). Horseshoe crab bio-ecological data from Balok, east coast peninsular Malaysia. Data in Brief, 22, 458-463.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 The mean and standard deviation of morphological characteristics individuals of \u003cem\u003eTachypleus gigas\u003c/em\u003e collected from rescued stations\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"697\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSl.no.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarapace Length mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarapace Width mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTelson Length mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Length mean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarapace Length\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarapace Width Standard Deviation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTelson Length\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Length\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKasafal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChandipur\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDagra\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2 Ecological parameters (salinity, pH, temperature) and counts of live and dead\u0026nbsp;\u003cem\u003eTachypleus gigas\u003c/em\u003e individuals in rescues stations during different months\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMonth (Season)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSalinity (Mean ± SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003epH (Mean ± SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTemperature (Mean ± SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLive Count (Mean ± SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDead Count (Mean ± SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDO (Mean ± SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOC (Mean ± SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAugust (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.0 ± 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.8 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.0 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.0 ± 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.0 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.5 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.0 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDecember (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.0 ± 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.2 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.6 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.0 ± 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.5 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.2 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFebruary (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.8 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.3 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.1 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.0 ± 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.0 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.6 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJanuary (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.5 ± 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.3 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.0 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.0 ± 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.0 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.8 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.4 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJuly (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.0 ± 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.5 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.0 ± 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.0 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.0 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarch (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.0 ± 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.4 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.3 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.0 ± 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.0 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.1 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNovember (Post-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.8 ± 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.6 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.2 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.0 ± 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.0 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.5 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOctober (Post-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.5 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.5 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.9 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.0 ± 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.2 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.0 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeptember (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.0 ± 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.8 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.0 ± 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.2 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAugust (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.0 ± 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.8 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.0 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.0 ± 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.3 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.0 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDecember (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.0 ± 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.4 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.7 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 ± 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.5 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.5 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFebruary (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.7 ± 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.5 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.2 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.0 ± 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.0 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.4 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJanuary (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.3 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.4 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.0 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 ± 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.8 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.4 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJuly (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.0 ± 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.5 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.0 ± 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.0 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.0 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarch (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.0 ± 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.5 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.3 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.0 ± 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.0 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.2 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.3 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNovember (Post-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.0 ± 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.6 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.0 ± 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.6 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOctober (Post-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.5 ± 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.6 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.4 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.0 ± 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.0 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.3 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeptember (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.0 ± 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.2 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.0 ± 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.6 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.0 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDecember (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.0 ± 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.3 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.7 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10 ± 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.0 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eJanuary (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.5 ± 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.4 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.8 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 ± 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.3 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.3 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFebruary (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.2 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.4 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.0 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 ± 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 ± 0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.7 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.2 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMarch (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.7 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.5 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.2 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.0 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.1 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOctober (Post-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31.0 ± 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.6 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.3 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 ± 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 ± 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.5 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.9 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNovember (Post-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.5 ± 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.6 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.5 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 ± 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.8 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.8 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eJuly (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.0 ± 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.8 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20 ± 4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.8 ± 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.2 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAugust (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.0 ± 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.8 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.1 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16 ± 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.2 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.6 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSeptember (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.0 ± 2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.8 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.9 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 ± 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.5 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.4 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDecember (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.8 ± 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.3 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.9 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 ± 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 ± 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.2 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.0 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eJanuary (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.2 ± 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.4 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.1 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 ± 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.4 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.9 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFebruary (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.6 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.4 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.2 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 ± 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.9 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.8 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMarch (Pre-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36.0 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.5 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.3 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 ± 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 ± 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.2 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOctober (Post-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32.0 ± 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.6 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.0 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15 ± 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 ± 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.0 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.2 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNovember (Post-monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31.5 ± 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.8 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 ± 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.3 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eJuly (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.0 ± 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.3 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 ± 3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 ± 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.5 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.0 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAugust (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.0 ± 2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.8 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.2 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 ± 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 ± 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.7 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.0 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParikhi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSeptember (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.0 ± 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.7 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 ± 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 ± 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.8 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.9 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDecember (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.5 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.3 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.2 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.7 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.8 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJanuary (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.8 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.4 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.1 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.8 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.6 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFebruary (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.0 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.4 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.3 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 ± 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.4 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarch (Pre-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.3 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.5 ± 0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.4 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.1 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.3 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOctober (Post-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.5 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.6 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.9 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 ± 0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.5 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.5 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNovember (Post-Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.0 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.0 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 ± 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.7 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.4 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJuly (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.0 ± 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.1 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 ± 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 ± 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.2 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.0 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAugust (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.0 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.8 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.2 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 ± 0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 ± 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.3 ± 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDagra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeptember (Monsoon)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.0 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.5 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 ± 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 ± 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.5 ± 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7 ± 0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3 Mean body weight (g) and standard deviation (g) of\u0026nbsp;\u003cem\u003eTachypleus gigas\u003c/em\u003e by location and sex\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLocation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMean Body Weight (g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Deviation (g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e4000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKasafal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eParikhi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eParikhi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eChandipur\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDagara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDagara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e±3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Marine conservation, community engagement, habitat degradation, coastal intertidal zones, environmental monitoring","lastPublishedDoi":"10.21203/rs.3.rs-6659913/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6659913/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study focuses on the conservation of \u003cem\u003eTachypleus gigas\u003c/em\u003e (M\u0026uuml;ller), a marine chelicerate of ecological significance, threatened by habitat degradation, pollution, and fishing activities along the Odisha coastline. Listed as \u0026lsquo;Data Deficient\u0026rsquo; by the IUCN, \u003cem\u003eT. gigas\u003c/em\u003e populations face severe risks, necessitating targeted conservation measures. The study objective is to (1) assess environmental factors influencing \u003cem\u003eT. gigas\u003c/em\u003e distribution and survival, (2) evaluate the effectiveness of rescue and relocation efforts, and (3) engage local communities in conservation. A total of 483 individuals were rescued from fishing zones and relocated to protected areas to support population recovery. Field surveys (July 2023\u0026ndash;March 2024) at ten stations (five rescue and five relocation sites) revealed that seasonal salinity variations, driven by monsoon influx and pre-monsoon evaporation, significantly influenced habitat suitability and reproductive success. Morphometric analyses indicated positive allometric growth in carapace length (R\u0026sup2; = 0.79), width (R\u0026sup2; = 0.79), and telson length (R\u0026sup2; = 0.59), supporting locomotion, defense, and reproduction. Rescues varied seasonally and spatially, with lunar phases influencing distribution. Principal Component Analysis highlighted salinity, temperature, and sediment composition as key drivers of \u003cem\u003eT. gigas\u003c/em\u003e distribution, with organic carbon levels correlating positively with \u003cem\u003eT. gigas\u003c/em\u003e counts during the monsoon. Monsoonal shifts in sediment composition and water quality altered benthic ecosystems, impacting long-term habitat suitability. Despite these findings, ghost net entanglement remained a critical threat, with 40.7% of fishermen discarding trapped crabs. Community engagement, including educational outreach to 235 fisherfolk, was crucial in garnering support for protected no-fishing stations. Post-relocation monitoring indicated a 72.5% survival rate over six months, reinforcing the effectiveness of targeted conservation. This study underscores the need for an interdisciplinary approach integrating long-term monitoring, habitat restoration, stricter fishing regulations, and community participation to ensure \u003cem\u003eT. gigas\u003c/em\u003e resilience.\u003c/p\u003e","manuscriptTitle":"Ecological insights and conservation strategies for the data-deficient Indian horseshoe crab Tachypleus gigas (Müller, 1785) along the Odisha coast, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-23 08:12:26","doi":"10.21203/rs.3.rs-6659913/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-22T02:41:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-20T05:56:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-20T05:53:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2025-05-14T03:23:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"db0a08a3-e69e-4c29-9919-779319f7c964","owner":[],"postedDate":"June 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-29T16:04:46+00:00","versionOfRecord":{"articleIdentity":"rs-6659913","link":"https://doi.org/10.1007/s10661-025-14564-8","journal":{"identity":"environmental-monitoring-and-assessment","isVorOnly":false,"title":"Environmental Monitoring and Assessment"},"publishedOn":"2025-09-28 15:57:24","publishedOnDateReadable":"September 28th, 2025"},"versionCreatedAt":"2025-06-23 08:12:26","video":"","vorDoi":"10.1007/s10661-025-14564-8","vorDoiUrl":"https://doi.org/10.1007/s10661-025-14564-8","workflowStages":[]},"version":"v1","identity":"rs-6659913","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6659913","identity":"rs-6659913","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}