Environmental Factors Influencing the Sightings of Whale Shark (Rhincodon typus, Smith 1828): The Case Study in Kilindoni Bay, Mafia District, Tanzania

Environmental Factors Influencing the Sightings of Whale Shark (Rhincodon typus, Smith 1828): The Case Study in Kilindoni Bay, Mafia District, Tanzania | 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 Environmental Factors Influencing the Sightings of Whale Shark (Rhincodon typus, Smith 1828): The Case Study in Kilindoni Bay, Mafia District, Tanzania Edna Swai, Edmond Alavaisha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5296297/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The whale shark ( Rhincodon typus , Smith 1828) is among the largest fish that tends to swim at the surface in aggregation. Several locations in are known habitats for whale sharks. However, there is still a need to understand the environmental factors that influence their occurrences and sighting. This paper investigated the environmental factors essential to whale sharks' s in Kilindoni bay, Mafia. Data were collected through observations supplemented with secondary historical data sets from 2012 to 2019, including whale shark sightings and environmental variables. These datasets were obtained from the Marine Megafauna Foundation (MMF) and the Tanzania Fisheries Research Institute (TAFIRI). The Generalized Linear Model (GLM) was used to analyse 510 whale shark sighting records from October to February (2012–2019). The variables involved were sea surface temperature, zooplankton abundance, moon illumination, and weather conditions. Results revealed that weather conditions (χ2 = 10.626, df = 4, p = 0.031), zooplankton abundance (χ2 = 206.580, df = 2, p = 0.001), and moon illumination (χ2 = 7.464, df = 1, p = 0.006) are significant factors influencing the sighting of whale sharks. Sea Surface Temperature (χ2 = 0.951, df = 1, p = 0.329) was not a significant factor in the sighting of whale sharks. Generally, weather conditions, moon illumination, and zooplankton abundance were vital factors for the Mafia's distribution of whale sharks. The study recommends sustained, regular monitoring of environmental variables linked to whale sharks, reinforcing the implementation of a code of conduct for whale shark sighting, and advocating for an integrated management approach inclusive of all local stakeholders. Whale Shark Environmental factor Sighting Mafia Island Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Whale sharks ( Rhincodon typus , Smith 1828) are the largest known cartilaginous fish, inhabiting warm waters in tropical and subtropical regions. Despite their impressive size, they are rarely sighted and face numerous threats, including bycatch, vessel collisions, and changes in oceanographic conditions (Norman et al., 2017; Schoeman et al., 2020 )(Ref). Although conservation efforts are underway, only a few small populations of whale sharks remain, and their numbers continue to decline (Norman et al., 2017; Pierce and Norman, 2016). Protecting these limited and geographically isolated populations is crucial, as they hold significant ecological and economic value, particularly in countries where these endangered creatures attract marine tourism (Hacohen-Domené et al. 2015 ). There are approximately 20 recognized global hotspots for whale shark activity, many of which are seasonal feeding aggregations occurring in easily accessible surface waters (Norman et al., 2017; Reynolds et al., 2022 ). Noteworthy locations with such constellation include Ningaloo Reef in Australia (Taylor 1996 ), Belize (Young 2008 ), Seychelles (Rowat and Gore 2007 ), Madagascar (Jonahson and Harding 2007 ), Maldives (Kundur 2012 ), Mozambique (Speed et al. 2008 ), Mexico (Eckert and Stewart 2001 ), Qatar (Robinson et al. 2017 ), Mafia Island (Rohner et al. 2013 ), and St Helena (Perry 2017 ). These aggregations offer valuable opportunities to study the environmental factors affecting phytoplankton and zooplankton, examine how prey availability impacts whale sharks, and support the tourism industry by drawing visitors eager to observe these magnificent creatures in their natural habitat. The predictability of whale shark aggregations, along with the frequency of foraging activity reported in the area, offers a unique opportunity to explore the potential mechanistic role of environmental factors, such as prey density and oceanographic conditions (Reynolds et al. 2022 ; D’Antonio et al. 2024 ), in driving whale shark movement patterns. Environmental conditions play a crucial role in the behavior of whale shark, often linked to specific physical or biological habitats, and they significantly influence distribution and abundance patterns. (Guillera-Arroita et al. 2014 ; Reynolds et al. 2022 ). Whale sharks form aggregations in areas associated with dense prey collections (Rohner et al. 2020 ). This suggests that areas where whale shark sightings occur are linked to primary productivity, which supplies food for many plankton feeders like whale sharks. The occurrence of prey is an essential driver of the movements and distribution of whale sharks, where higher zooplankton densities are associated with oceanographic processes such as upwelling, coastal currents, fronts, or river inlets (Colman 1997 ). Changes in these variables, directly and indirectly, relate to whale shark physiology and feeding ecology regarding phytoplankton and zooplankton availability (Norman et al., 2017; Reynolds et al., 2022 ) consequently influencing the sighting and occurrence of whale shark populations. Changes in Sea Surface Temperature (SST), chlorophyll-a, and moon phases may influence the increase or decrease of macro plankton (Rowat and Brooks 2012 ). Several studies e.g., (Cagua et al., 2015 ; Hacohen-Domené et al., 2015 ; Norman et al., 2017; Reynolds et al., 2022 ; Rohner et al., 2020 , 2013 ) have revealed that whale sharks are threatened by human activities and changes in environmental factors related to food availability and surfacing behaviors. In the Mexican Caribbean, for example, primary productivity and sea surface temperature were strongly associated with whale shark sightings (Reyes-Mendoza et al. 2021 ). Other studies (Micaela and Sequeira 2013 ; Perry et al. 2020 ) have stressed that whale shark distribution and abundance are influenced by oceanographic processes such as upwelling, coastal currents, and sea surface temperature, all of which affect productivity in the global and local environment. In Kilindoni Bay, Mafia Island, located in the Western Indian Ocean, sightings of up to 50 individual whale sharks have been documented (Lind 2018 ). This area has experienced increased tourism and fishing activities correlated with these sightings (Rohner et al. 2020 ). Notably, the patterns of whale shark aggregation exhibit significant temporal and spatial variability. While human activities contribute to these fluctuations, oceanographic factors are crucial in determining whale shark presence. Despite this, there is a limited understanding of the ecological dynamics of whale sharks and how local environmental conditions influence their visibility, particularly between October and February. This study aims to investigate the relationship between environmental factors and whale shark sightings in Kilindoni Bay, enhancing our understanding of their ecology and informing conservation strategies. Materials and Methods The study was conducted in Kilindoni Bay, in the western region of Mafia Island, Tanzania (Fig. 1). A case study design was employed in the study to review the existing data on whale shark sightings. Data were collected from the Marine Megafauna Foundation and Tanzania Fisheries Research Institute (TAFIRI) between 2012 and 2019. These data sets were collected through observations and monitoring of whale sharks. Acoustic telemetry was used to tag 51 sharks with a transmitter and deployed 20 receivers in Kilindoni Bay, which sought to record each tagged shark in the area from October to February, making a total of 358 trips and 1,862 shark encounters in 8 years. All trips started and lasted 45 minutes to 9 hours. Data were collected from the highest accessible point (the "primary platform"). A handheld GPS unit (Garmin Etrex 10) was used to record time, sight location, course, and speed at the beginning and end of each data session. Figure 1: Map showing Kilindoni Bay on Mafia Island Plankton was collected from the ocean using a 200 µm mesh net with a 50 cm diameter, which was dragged for 3 minutes at the surface approximately 15 m behind the boat. After collection, the samples were promptly preserved in a 5% formaldehyde solution and stored until analysis. Two types of plankton samples were obtained: "feeding" samples, where the net was towed within 5 meters of one or more actively feeding whale sharks at the surface, and "background" samples, which were collected at predetermined locations. The background samples were consistent in their starting location, direction, and duration. However, due to the opportunistic nature of the feeding tows, which depended on the presence and movements of the whale sharks, there were fewer feeding tows compared to background tows. Data analysis A study on whale shark sightings utilized a Generalized Linear Model (GLM) (see equation i) to analyze 510 records collected between October and February from 2012 to 2019. The model integrated season (year) and Julian day as independent variables to assess how the number of whale shark sightings varied with changing seasons and days of the year. Additionally, environmental factors such as weather (overcast, partial overcast, rain, sunny), zooplankton abundance (high, medium, low), moon illumination, and sea surface temperature were included to explore their impact on sightings in Kilindoni Bay. To address potentially non-linear relationships, splines were introduced for Julian day, moon illumination, weather, and sea surface temperature. Y = β 0 + β 1 Χ 1 + β 2 Χ 2 + β 3 Χ 3 + β 4 Χ 4 + β 5 Χ 5 + β 6 Χ 6 + e ---------------------------- (i) Where: Y = whale shark sightings (dependent variable) and Χ 1, Χ 2,.., Χ 6 are independent variables β 0 = is the intercept, representing the baseline level of whale shark sightings when all predictors are zero. β1,β2,…,β6: Coefficients for each independent variable that quantify how each variable influences the whale shark sightings. Χ 1 = Season represents the effect of the year on whale shark sightings, capturing potential inter annual variability. Χ 2 = Julian Day accounts for the day of the year, controlling for seasonal cycles. Χ 3 = Weather captures the influence of weather conditions (e.g., rainy, clear) on sightings. Χ 4 = Zooplankton which serves as a key food source in feeding chain for whale sharks. Χ 5 = Moon Illumination measures the impact of moonlight, which can affect whale shark behaviour and visibility. Χ 6 = Sea surface emperature represents the effect of sea surface temperature on sightings. e: The error term, representing the unexplained variation in whale shark sighting Initially fitted as a Poisson GLM, the model indicated significant overdispersion (z = 5.8847, p-value < 0.001), leading to the adoption of a negative binomial distribution to rectify this issue. The negative binomial GLM was implemented using the glm.nb function from the MASS package (Venables and Ripley 2002 ). Model selection, based on the Akaike Information Criterion corrected for small samples (AICc), involved choosing the top-ranked model after assessing various term combinations from the global model using the dredge function from the MuMIn package. All analyses were carried out in R 4.1.2 (R Core Team 2021), with visualizations created using the ggplot2 package (Wickham 2016 ). Results The occurrence and distribution of whale sharks varied throughout the year, with a higher concentration observed within the enclosed area of Kilindoni Bay (Fig. 2). This increased concentration is associated with favorable environmental conditions, such as elevated zooplankton abundance, partial overcast weather, and optimal moon illumination. Figure 2: Map showing whale shark aggregation detected in Kilindoni Bay between 2012 and 2019 Seasonal Change in Whale Shark Sighting Between Days and Years. The model analyzing the seasonal and daily sightings of whale sharks in Kilindoni Bay (Fig. 3) revealed variations in daily trends and annual seasonal occurrences of whale shark sightings at the bay. Statistical analysis showed a significant difference in daily trends (χ 2 = 13.4, df = 3, p = 0.004) and annual seasonal occurrence (χ2 = 38.307, df = 7, p = 0.001). Regarding the seasonal pattern, lower sightings of whale sharks were recorded in 2016, while there was a substantial increase in sightings in 2019, with a notable increasing trend (Fig. 3(a)). Regarding the daily observations, higher sightings were observed during the early days of the survey (around 290 days), whereas lower sightings in the later days (around 360 days). A lower peak was also observed in the '320 days of the year (Fig. 3(b)). It is important to note that the figure includes grey shading, representing the confidence intervals. Generally, results indicate that whale shark sightings at Kilindoni Bay exhibit seasonal and daily variations, with specific years and periods showing higher or lower occurrences. The model provides valuable insights into the temporal patterns of whale shark sightings, offering a basis for further analysis and understanding of the factors influencing their presence in the bay. Figure 3: showing whale shark sighted during (a) Annual seasonal of the year and (b) Day of the year (jday) at Kilindoni Bay from 2012 to 2019. The dots are sighting data, and the blue horizontal bars with grey shading represent mean estimates with confidence intervals across the seasons and day of the year. Environmental Factors that Influence Whale Shark Sightings at Kilindoni Bay Weather conditions, sea surface temperature, moon illumination, and Zooplankton influenced whale shark sightings at Kilindoni Bay (Fig. 4). The grey shade indicates confidence intervals, while the line indicates the mean average. Based on AICc, the best model included weather, Zooplankton, moon illumination and sea surface temperature as essential variables in explaining variation in whale shark sightings at Kilindoni Bay. Figure 4(a) indicates that weather significantly (χ2 = 10.626, df = 4, p = 0.031) influenced whale shark sightings in the study area, with most of the sightings made during partial overcast. The Zooplankton availability had also significantly (χ2 = 206.580, df = 2, p = 0.001) influenced whale shark sightings, whereby shark sightings were higher in the areas with a higher number of Zooplankton and were lower in the regions with no or negligible amount zooplankton (Fig. 4(b)). Moreover, Fig. 4(c) indicates that moon illumination significantly influences whale shark sightings at Kilindoni Bay (χ2 = 7.464, df = 1, p = 0.006), whereby there was a positive relationship between shark sightings and moon illumination. Most of the limited sightings occurred during rainy weather, and sea surface temperature (Fig. 3(d)) was initially expected to play a significant role in explaining shark sightings. However, its influence was not statistically significant (χ² = 0.951, df = 1, p = 0.329). Contrary to common assumptions, temperature variation did not effectively predict whale shark sightings (see Fig. 4(d)). Figure 4: Environmental factors (a) weather, (b) zooplankton, (c)moon illumination and (d) sea surface temperature and whale shark at Kilindoni Bay. The dots are sighting data, and the blue horizontal bars with grey shading represent mean estimates with confidence intervals. Discussion Understanding the factors influencing whale shark sightings is crucial for enhancing conservation efforts and predicting patterns of their occurrence in marine ecosystems. In this study, we examined a range of environmental variables that could impact whale shark sightings, including seasons, temperature, weather conditions, moon illumination and zooplankton. While previous research has often highlighted the importance of seasons and other physical chemical variables in influencing whale shark sightings, our findings challenge some of these assumptions. The following discussion explores how these variables, influenced the whale shark sightings in our study area. Additionally, we compare our results with existing literature, identifying key consistencies and discrepancies, and propose potential explanations for the unexpected findings. This discussion provides a broader context for the implications of our results on whale shark conservation and management strategies. Seasonal Change of Whale Shark Sighting. Seasonal sightings of whale sharks on Mafia Island vary in season. The findings revealed that the period from the 290th day to the 360th day of the year was identified as the most favorable time for whale shark sightings (Fig. 3). Additionally, the month factor was found to be a good predictor in the model, showing a peak in sightings during the Northeast (NE) monsoon season November to February. This pattern aligns with observations from other whale shark aggregation sites worldwide (Rohner et al. 2013 ; Prebble et al. 2018 ; Reynolds et al. 2022 ), where a defined peak season in whale shark presence is often attributed to increased productivity linked to daily variation (Rowat and Brooks 2012 ). While the exact reasons for this seasonality in whale shark sightings on Mafia Island remain speculative, the abundance of zooplankton likely plays a key role. This concurs with other studies in the WIO region (Diamant et al. 2018 ; Prebble et al. 2018 ), pointing out the factors associated with whale shark aggregation. On the contrary, other studies (Marcus et al. 2019 ; Frixione et al. 2020 ; Rohner et al. 2020 ) indicated zooplankton serves as a primary food source for whale sharks, and its availability may influence the movement and aggregation of whale sharks. The association between zooplankton abundance and the observed seasonality suggests a possible link between the two factors. However, further research is needed to explore and confirm the specific mechanisms underlying the seasonality of whale sharks in this region. Higher sightings were observed during the early days of October to January, whereas lower sightings were seen in the later days of February (see Fig. 3). This is consistent with previous studies which demonstrated a peak in whale shark occurrence between October and February (Hardenstine 2015 ; Prebble et al. 2018 ). This period aligns with the warmer seasons characterized by sunny and cool weather with weak monsoon wind, suggesting a seasonal suitability for whale shark sightings. The results of this study underscore the critical role of timing in the seasonal occurrence of whale sharks, as illustrated in Fig. 3(b). These findings align with the hypothesis that whale shark sighting patterns are closely linked to seasonal environmental fluctuations, which have shown considerable variability over time (Hueter et al. 2013 ) This dynamic relationship between whale shark activity and changing environmental conditions further emphasizes the need for ongoing monitoring to better understand and predict their movement patterns in response to shifting ecological factors. Similarly, the results indicate a notable increase in whale shark sightings during 2017, 2018, and 2019 compared to previous years. Studies such as Cagua et al. ( 2015 ), Jonahson & Harding ( 2007 ), and Rohner et al. ( 2020 ) reported a similar trend of increasing whale shark sightings in the Mafia. This increase can be attributed to several factors, including technological advancements, such as using fiberglass boats, which provide better opportunities for spotting whale sharks. The improved experience and knowledge of boatmen and tour guides encountering whale sharks at Kilindoni Bay may also have contributed to the increased sightings. These findings suggest that technological advancements play a key role in enhancing the ability to detect whale sharks in the area. However, the use of such technologies—such as modern boats—can also negatively affect whale shark observations if not properly managed, particularly due to issues like noise pollution and oil spills. It is worth noting that this study observed a notable decline in whale shark sightings in 2016, a trend that has also been reported globally, coinciding with a significant downturn in whale shark tourism (Theberge and Dearden 2006 ; Sánchez et al. 2020 ). This decline may be partially attributed to intensified fishing and tourism activities that exceed the ecological carrying capacity of the area. Additionally, oceanographic changes, such as shifting currents, could disrupt whale shark behavior, potentially causing them to retreat from typical sighting areas or become less visible. These activities may have had a temporary negative impact on the presence of whale sharks in the area. Thus, technological advancements, coupled with a reduction in disruptive activities (Rohner, Pierce, Marshall, et al., 2013), such as fishing and tourism practices that can disturb whale sharks, are factors associated with variation in the sighting of whale sharks at Kilindoni Bay. Environmental Factors Influence Whale Shark Sightings Whale shark distribution and sightings at Kilindoni Bay vary by season and are mostly driven by food availability. Other important factors for whale shark sightings were calm weather conditions, which enhance visibility, making it easier to spot whale sharks, while rough seas can impede observations. Moon illumination may influence their feeding behavior, potentially affecting their activity levels and sea surface temperature that affects the abundance and availability of whale shark's food − plankton including small fishes. Understanding these variables is essential for effective conservation efforts aimed at protecting whale shark populations and their habitats. Weather Results revealed that weather was an essential factor affecting the sighting of whale sharks with most of the sightings made during partial overcast (Fig. 4 (a)). According to Morgado et al. ( 2017 )d Antonio et al. ( 2024 ) overcast conditions, where the sky is partially covered with clouds, increase visibility into the water. This can be particularly beneficial for detecting whale sharks that may be swimming deeper in the water column. Partial overcast conditions can reduce surface glare, enhancing underwater visibility and potentially influencing whale shark feeding behavior. Cloudy weather may also lead to more subdued whale shark activity, while heavy rainfall can create rough seas and further decrease visibility. The impact of raindrops on the water surface can distort the view, making it challenging to spot whale sharks. However, other studies (Perry, 2017 ; Rohner et al., 2020 ) have reported that light rain can enhance plankton activity near the surface, likely due to nutrient runoff, which may attract whale sharks to these nutrient-enriched areas. According to a study by (Rohner et al. 2020 ), rain causes nutrients to flow from the Rufiji River to the Mafia, increasing plankton availability. Sunny weather with clear skies provides excellent visibility above and below the water's surface, allowing observers to spot whale sharks even from a distance. Whale sharks often come closer to the surface to feed on plankton and small fish. During sunny conditions, the contrast between the shark's light-colored skin and the darker ocean water makes it easier to spot them. Zooplankton This study has uncovered a significant relationship (χ2 = 206.580, df = 2, p = 0.001) between whale shark sightings and the presence of zooplankton. As noted by (Marcus et al. 2019 ), this was not surprising because the higher amount of zooplankton reflects the food availability for whale sharks. Similarly, study indicated that there are a greater number of whale shark sightings off Mafia Island when a high concentration of zooplankton is present. This relationship becomes clearer when considering the role of nutrients as indicators of phytoplankton abundance, a key driver of zooplankton productivity. Mateka et al. ( 2015 ) observed a seasonal cycle of phytoplankton in the surface waters of Mafia, with growth peaking during the rainy season in March and reaching maximum productivity between June and September. The closed-circuit nature of the current system accumulates plankton during the Northeast monsoon, while nutrient-rich waters from the Somali Current may also feed into the East African circulation system, further enhancing productivity in the region. A high zooplankton biomass in the waters coincided with a higher recorded number of whale sharks (see Fig. 4 (b)). This relationship can be attributed to the specific feeding behaviour of whale sharks, which necessitates a substantial intake of food daily to meet their physiological needs. The substantial number of whale shark sightings in Kilindoni Bay, mainly when zooplankton biomass was high, is indicated in Fig. 4(b). This finding suggests the importance of zooplankton abundance as a critical factor influencing whale sharks' presence and feeding behaviour in the study area. Moon Illumination There was a relationship between lunar illumination and the sightings of whale sharks (Fig. 4(c)). Sightings were more frequent during periods of higher moon illumination, particularly when the moon was more than half full. This pattern is consistent with findings from other regions, such as Madagascar and Kenya, where more sightings occurred during the full moon (Temple et al. 2019 ). This suggests that the moon phase may directly or indirectly influence whale shark behavior, significantly affecting their visibility and occurrence in surface waters. Moon phases not only influence lunar illumination but also impact tides. The researcher observed that whale shark sightings were more frequent during periods of higher moon illumination, particularly near the full moon. This pattern aligns with the idea that increased lunar light may play a role in whale shark activity, possibly by enhancing prey visibility or influencing their movement patterns (Ranintyari et al. 2018 ). Although tidal patterns were not a direct focus, the connection between moon illumination and whale shark sightings suggests that lunar light may indirectly create favorable conditions for foraging or other behaviors. Sea Surface Temperature Sea surface temperature is a key factor influencing the distribution of many marine organisms, but in this study, it did not have a significant impact on whale shark sightings (χ2 = 0.951, df = 1, p = 0.329). This finding aligns with previous studies by Robinson et al. ( 2017 ); and Thums et al. ( 2012 ), who also reported no clear relationship between SST and whale shark presence. Whale sharks, due to their large body size, maintain a stable internal temperature, allowing them to undertake deep dives (over 1000 m) into cooler waters without experiencing high metabolic costs typically associated with thermoregulation. This ability enables whale sharks to move across environments with different temperature profiles without being significantly affected by fluctuations in surface temperatures. Hueter et al. ( 2013 ) demonstrated that whale sharks can dive to depths exceeding 979.5 m and tolerate a wide temperature range, with individuals thriving in both tropical and subtropical waters where temperatures range from 18°C to 30°C. This thermal tolerance, combined with their capacity for deep diving, suggests that whale sharks are less reliant on specific SST ranges for their distribution, which explains why temperature is not a primary factor governing their sightings in this study. Conclusion The analysis of whale shark sightings in Kilindoni Bay reveals that their sighting is influenced by environmental factors such as seasonal changes, weather conditions, lunar illumination, and zooplankton availability. Whale sharks were present year-round, with peak sightings in November and December, and were positively correlated with higher lunar illumination and increased zooplankton density. This highlights the ecological significance of Mafia Island’s productive waters, where whale sharks concentrate. To sustain Mafia Island as a prime whale shark habitat, it is vital to protect the marine environment, particularly by conserving zooplankton and ensuring long-term ecosystem health. The study recommends continuous monitoring of environmental variables affecting whale shark behavior, along with enforcing a code of conduct for whale shark interactions to minimize disturbances. Declarations Source of fund This research was fully funded by Marine Megafauna Foundation and Tanzania Fisheries Research Institute (TAFIRI). Conflicts of Interest The authors declare no conflict of interest. Author Contribution E.S. and E.A. jointly conceptualized, designed, and conducted the research. E.S. led the fieldwork, and both E.S. and E.A. analyzed and interpreted the data. E.A. contributed to writing, reviewing, and editing the manuscript draft. Acknowledgement We are deeply grateful to Dr. Chris Rohner for shaping the study design. Special thanks to the fishers and fisheries experts from Mafia for their pivotal role in advancing our whale shark research. Sincere appreciation to the Megafauna Foundation and the Tanzania Fisheries Research Institute for their generous support and proactive data sharing. The collective effort of everyone involved enriched the depth and scope of our research, making it more comprehensive. 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Marine Ecology Progress Series 482:153–168. https://doi.org/10.3354/meps10290 Rowat D, Brooks KS (2012) A review of the biology, fisheries and conservation of the whale shark Rhincodon typus. Journal of Fish Biology 80:1019–1056. https://doi.org/10.1111/j.1095-8649.2012.03252.x Rowat D, Gore M (2007) Regional scale horizontal and local scale vertical movements of whale sharks in the Indian Ocean off Seychelles. Fisheries Research 84:32–40. https://doi.org/10.1016/j.fishres.2006.11.009 Sánchez L, Briceño Y, Tavares R, et al (2020) Decline of whale shark deaths documented by citizen scientist network along the Venezuelan Caribbean coast. Oryx 54:600–601. https://doi.org/10.1017/s0030605320000514 Schoeman RP, Patterson-Abrolat C, Plön S (2020) A Global Review of Vessel Collisions With Marine Animals. Frontiers in Marine Science 7:1–25. https://doi.org/10.3389/fmars.2020.00292 Speed CW, Meekan MG, Rowat D, et al (2008) Scarring patterns and relative mortality rates of Indian Ocean whale sharks. Journal of Fish Biology 72:1488–1503. https://doi.org/10.1111/j.1095-8649.2008.01810.x Taylor JG (1996) Seasonal occurrence, distribution and movements of the whale shark, Rhincodon typus, at Ningaloo Reef, Western Australia. Marine and Freshwater Research 47:637–642. https://doi.org/10.1071/MF9960637 Temple AJ, Wambiji N, Poonian CNS, et al (2019) Marine megafauna catch in southwestern Indian Ocean small-scale fisheries from landings data. Biological Conservation 230:113–121. https://doi.org/10.1016/j.biocon.2018.12.024 Theberge MM, Dearden P (2006) Detecting a decline in whale shark Rhincodon typus sightings in the Andaman Sea, Thailand, using ecotourist operator-collected data. Oryx 40:337–342. https://doi.org/10.1017/S0030605306000998 Thums M, Meekan M, Stevens J, et al (2012) Evidence for behavioural thermoregulation by the world ’ s largest fish Venables WN, Ripley BD (2002) Random and Mixed Effects. 271–300. https://doi.org/10.1007/978-0-387-21706-2_10 Wickham H (2016) ggplot2: Elegant Graphics for Data Analysis Young CA (2008) Belize’s ecosystems: Threats and challenges to conservation in Belize. Tropical Conservation Science 1:18–33 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-5296297","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":369710835,"identity":"d8461f80-6fe4-41f2-8cbe-4bc1c481942e","order_by":0,"name":"Edna Swai","email":"","orcid":"","institution":"University of Dar es Salaam","correspondingAuthor":false,"prefix":"","firstName":"Edna","middleName":"","lastName":"Swai","suffix":""},{"id":369710836,"identity":"be255840-c47a-45ef-9b29-881877f4e70a","order_by":1,"name":"Edmond Alavaisha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYFCCBCBmY5ABMQ8wNtgwMEgQqYUHqiWNRC0MjA2HCWvhZ89OfFxQZsfDPyP54cGfO84n9s9uPviAocYmGpcWyZ63m41nnEvmkbiRZnCY98ztxBl3jiUbMBxLy23AocXgRu42ad42Zh6GMwcMDjO23U5suJFjJgF0IU4t9hAt9TzyZ45/OPiz7VzifEJaDCTAWg7zGBzvMTjA23YgcQMhLRJngH7hOXecx/B4T8Fh3rZk44030pINEvD4hb89d+NjnrJqObnD7Js//myzk513I/nggw81Nji1YABHsMoEYpWDgD0pikfBKBgFo2BkAACMgWImv5ihtgAAAABJRU5ErkJggg==","orcid":"","institution":"University of Dar es Salaam","correspondingAuthor":true,"prefix":"","firstName":"Edmond","middleName":"","lastName":"Alavaisha","suffix":""}],"badges":[],"createdAt":"2024-10-19 23:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5296297/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5296297/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":67470846,"identity":"7760b93f-0692-40a2-b753-2ad0a1e2c202","added_by":"auto","created_at":"2024-10-25 11:31:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":313112,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing Kilindoni Bay on Mafia Island.\u003c/p\u003e","description":"","filename":"Figure1MapshowingKilindoniBayonMafiaIsland.png","url":"https://assets-eu.researchsquare.com/files/rs-5296297/v1/ad4fcbb1e60c0bfe96a0e792.png"},{"id":67470847,"identity":"a3f46870-0160-41e9-989e-637c33b02865","added_by":"auto","created_at":"2024-10-25 11:31:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":358209,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing whale shark aggregation detected in Kilindoni Bay between 2012 and 2019.\u003c/p\u003e","description":"","filename":"Figure2MapshowingwhalesharkaggregationdetectedinKilindoniBaybetween2012and2019.png","url":"https://assets-eu.researchsquare.com/files/rs-5296297/v1/0f3a4b5fb6b8b21f79ed52ef.png"},{"id":67470844,"identity":"7622851f-ed8a-42fe-ba10-dc230a997cb0","added_by":"auto","created_at":"2024-10-25 11:31:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":469195,"visible":true,"origin":"","legend":"\u003cp\u003eShowing whale shark sighted during (a) Annual seasonal of the year and (b) Day of the year (jday) at Kilindoni Bay from 2012 to 2019. The dots are sighting data, and the blue horizontal bars with grey shading represent mean estimates with confidence intervals across the seasons and day of the year.\u003c/p\u003e","description":"","filename":"Figure38.png","url":"https://assets-eu.researchsquare.com/files/rs-5296297/v1/e55951239681bf41c5bba304.png"},{"id":67470848,"identity":"3b7d7733-c548-419c-b8b8-617ab0377af9","added_by":"auto","created_at":"2024-10-25 11:31:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":165444,"visible":true,"origin":"","legend":"\u003cp\u003eEnvironmental factors (a) weather, (b) zooplankton, (c)moon illumination and (d) sea surface temperature and whale shark at Kilindoni Bay. The dots are sighting data, and the blue horizontal bars with grey shading represent mean estimates with confidence intervals.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5296297/v1/871371852dc22619cf8256db.png"},{"id":73191858,"identity":"f62f0626-9511-4bb1-aa78-53143a42f221","added_by":"auto","created_at":"2025-01-07 14:47:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1727208,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5296297/v1/9a9a2864-b054-461d-badc-2cf27a9c2599.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Environmental Factors Influencing the Sightings of Whale Shark (Rhincodon typus, Smith 1828): The Case Study in Kilindoni Bay, Mafia District, Tanzania","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWhale sharks (\u003cem\u003eRhincodon typus\u003c/em\u003e, Smith 1828) are the largest known cartilaginous fish, inhabiting warm waters in tropical and subtropical regions. Despite their impressive size, they are rarely sighted and face numerous threats, including bycatch, vessel collisions, and changes in oceanographic conditions (Norman et al., 2017; Schoeman et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)(Ref). Although conservation efforts are underway, only a few small populations of whale sharks remain, and their numbers continue to decline (Norman et al., 2017; Pierce and Norman, 2016). Protecting these limited and geographically isolated populations is crucial, as they hold significant ecological and economic value, particularly in countries where these endangered creatures attract marine tourism (Hacohen-Domen\u0026eacute; et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere are approximately 20 recognized global hotspots for whale shark activity, many of which are seasonal feeding aggregations occurring in easily accessible surface waters (Norman et al., 2017; Reynolds et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Noteworthy locations with such constellation include Ningaloo Reef in Australia (Taylor \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), Belize (Young \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), Seychelles (Rowat and Gore \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), Madagascar (Jonahson and Harding \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), Maldives (Kundur \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), Mozambique (Speed et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), Mexico (Eckert and Stewart \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), Qatar (Robinson et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Mafia Island (Rohner et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and St Helena (Perry \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These aggregations offer valuable opportunities to study the environmental factors affecting phytoplankton and zooplankton, examine how prey availability impacts whale sharks, and support the tourism industry by drawing visitors eager to observe these magnificent creatures in their natural habitat.\u003c/p\u003e \u003cp\u003eThe predictability of whale shark aggregations, along with the frequency of foraging activity reported in the area, offers a unique opportunity to explore the potential mechanistic role of environmental factors, such as prey density and oceanographic conditions (Reynolds et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; D\u0026rsquo;Antonio et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), in driving whale shark movement patterns. Environmental conditions play a crucial role in the behavior of whale shark, often linked to specific physical or biological habitats, and they significantly influence distribution and abundance patterns. (Guillera-Arroita et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Reynolds et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Whale sharks form aggregations in areas associated with dense prey collections (Rohner et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This suggests that areas where whale shark sightings occur are linked to primary productivity, which supplies food for many plankton feeders like whale sharks. The occurrence of prey is an essential driver of the movements and distribution of whale sharks, where higher zooplankton densities are associated with oceanographic processes such as upwelling, coastal currents, fronts, or river inlets (Colman \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Changes in these variables, directly and indirectly, relate to whale shark physiology and feeding ecology regarding phytoplankton and zooplankton availability (Norman et al., 2017; Reynolds et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) consequently influencing the sighting and occurrence of whale shark populations. Changes in Sea Surface Temperature (SST), chlorophyll-a, and moon phases may influence the increase or decrease of macro plankton (Rowat and Brooks \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral studies e.g., (Cagua et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hacohen-Domen\u0026eacute; et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Norman et al., 2017; Reynolds et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rohner et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) have revealed that whale sharks are threatened by human activities and changes in environmental factors related to food availability and surfacing behaviors. In the Mexican Caribbean, for example, primary productivity and sea surface temperature were strongly associated with whale shark sightings (Reyes-Mendoza et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Other studies (Micaela and Sequeira \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Perry et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) have stressed that whale shark distribution and abundance are influenced by oceanographic processes such as upwelling, coastal currents, and sea surface temperature, all of which affect productivity in the global and local environment.\u003c/p\u003e \u003cp\u003eIn Kilindoni Bay, Mafia Island, located in the Western Indian Ocean, sightings of up to 50 individual whale sharks have been documented (Lind \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This area has experienced increased tourism and fishing activities correlated with these sightings (Rohner et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notably, the patterns of whale shark aggregation exhibit significant temporal and spatial variability. While human activities contribute to these fluctuations, oceanographic factors are crucial in determining whale shark presence. Despite this, there is a limited understanding of the ecological dynamics of whale sharks and how local environmental conditions influence their visibility, particularly between October and February. This study aims to investigate the relationship between environmental factors and whale shark sightings in Kilindoni Bay, enhancing our understanding of their ecology and informing conservation strategies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThe study was conducted in Kilindoni Bay, in the western region of Mafia Island, Tanzania (Fig.\u0026nbsp;1). A case study design was employed in the study to review the existing data on whale shark sightings. Data were collected from the Marine Megafauna Foundation and Tanzania Fisheries Research Institute (TAFIRI) between 2012 and 2019. These data sets were collected through observations and monitoring of whale sharks. Acoustic telemetry was used to tag 51 sharks with a transmitter and deployed 20 receivers in Kilindoni Bay, which sought to record each tagged shark in the area from October to February, making a total of 358 trips and 1,862 shark encounters in 8 years. All trips started and lasted 45 minutes to 9 hours. Data were collected from the highest accessible point (the \"primary platform\"). A handheld GPS unit (Garmin Etrex 10) was used to record time, sight location, course, and speed at the beginning and end of each data session.\u003c/p\u003e \u003cp\u003eFigure 1: Map showing Kilindoni Bay on Mafia Island\u003c/p\u003e \u003cp\u003ePlankton was collected from the ocean using a 200 \u0026micro;m mesh net with a 50 cm diameter, which was dragged for 3 minutes at the surface approximately 15 m behind the boat. After collection, the samples were promptly preserved in a 5% formaldehyde solution and stored until analysis. Two types of plankton samples were obtained: \"feeding\" samples, where the net was towed within 5 meters of one or more actively feeding whale sharks at the surface, and \"background\" samples, which were collected at predetermined locations. The background samples were consistent in their starting location, direction, and duration. However, due to the opportunistic nature of the feeding tows, which depended on the presence and movements of the whale sharks, there were fewer feeding tows compared to background tows.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eA study on whale shark sightings utilized a Generalized Linear Model (GLM) (see equation i) to analyze 510 records collected between October and February from 2012 to 2019. The model integrated season (year) and Julian day as independent variables to assess how the number of whale shark sightings varied with changing seasons and days of the year. Additionally, environmental factors such as weather (overcast, partial overcast, rain, sunny), zooplankton abundance (high, medium, low), moon illumination, and sea surface temperature were included to explore their impact on sightings in Kilindoni Bay. To address potentially non-linear relationships, splines were introduced for Julian day, moon illumination, weather, and sea surface temperature.\u003c/p\u003e \u003cp\u003eY\u0026thinsp;=\u0026thinsp;β\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e1\u003c/sub\u003e Χ\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e2\u003c/sub\u003e Χ\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e3\u003c/sub\u003e Χ\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e4\u003c/sub\u003e Χ\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e5\u003c/sub\u003e Χ\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β \u003csub\u003e6\u003c/sub\u003e Χ\u003csub\u003e6\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;e ---------------------------- (i)\u003c/p\u003e \u003cp\u003eWhere:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eY\u0026thinsp;=\u0026thinsp;whale shark sightings (dependent variable) and Χ\u003csub\u003e1,\u003c/sub\u003e Χ\u003csub\u003e2,..,\u003c/sub\u003e Χ\u003csub\u003e6\u003c/sub\u003e are independent variables\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eβ\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;is the intercept, representing the baseline level of whale shark sightings when all predictors are zero.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eβ1,β2,\u0026hellip;,β6: Coefficients for each independent variable that quantify how each variable influences the whale shark sightings.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eΧ\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Season represents the effect of the year on whale shark sightings, capturing potential inter annual variability.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eΧ\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Julian Day accounts for the day of the year, controlling for seasonal cycles.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eΧ\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Weather captures the influence of weather conditions (e.g., rainy, clear) on sightings.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eΧ\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Zooplankton which serves as a key food source in feeding chain for whale sharks.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eΧ\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Moon Illumination measures the impact of moonlight, which can affect whale shark behaviour and visibility.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eΧ\u003csub\u003e6\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;Sea surface emperature represents the effect of sea surface temperature on sightings.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ee: The error term, representing the unexplained variation in whale shark sighting\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eInitially fitted as a Poisson GLM, the model indicated significant overdispersion (z\u0026thinsp;=\u0026thinsp;5.8847, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001), leading to the adoption of a negative binomial distribution to rectify this issue. The negative binomial GLM was implemented using the glm.nb function from the MASS package (Venables and Ripley \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Model selection, based on the Akaike Information Criterion corrected for small samples (AICc), involved choosing the top-ranked model after assessing various term combinations from the global model using the dredge function from the MuMIn package. All analyses were carried out in R 4.1.2 (R Core Team 2021), with visualizations created using the ggplot2 package (Wickham \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe occurrence and distribution of whale sharks varied throughout the year, with a higher concentration observed within the enclosed area of Kilindoni Bay (Fig.\u0026nbsp;2). This increased concentration is associated with favorable environmental conditions, such as elevated zooplankton abundance, partial overcast weather, and optimal moon illumination.\u003c/p\u003e \u003cp\u003eFigure 2: Map showing whale shark aggregation detected in Kilindoni Bay between 2012 and 2019\u003c/p\u003e \u003cp\u003e \u003cb\u003eSeasonal Change in Whale Shark Sighting Between Days and Years.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe model analyzing the seasonal and daily sightings of whale sharks in Kilindoni Bay (Fig.\u0026nbsp;3) revealed variations in daily trends and annual seasonal occurrences of whale shark sightings at the bay. Statistical analysis showed a significant difference in daily trends (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;13.4, df\u0026thinsp;=\u0026thinsp;3, p\u0026thinsp;=\u0026thinsp;0.004) and annual seasonal occurrence (χ2\u0026thinsp;=\u0026thinsp;38.307, df\u0026thinsp;=\u0026thinsp;7, p\u0026thinsp;=\u0026thinsp;0.001). Regarding the seasonal pattern, lower sightings of whale sharks were recorded in 2016, while there was a substantial increase in sightings in 2019, with a notable increasing trend (Fig.\u0026nbsp;3(a)). Regarding the daily observations, higher sightings were observed during the early days of the survey (around 290 days), whereas lower sightings in the later days (around 360 days). A lower peak was also observed in the '320 days of the year (Fig.\u0026nbsp;3(b)). It is important to note that the figure includes grey shading, representing the confidence intervals. Generally, results indicate that whale shark sightings at Kilindoni Bay exhibit seasonal and daily variations, with specific years and periods showing higher or lower occurrences. The model provides valuable insights into the temporal patterns of whale shark sightings, offering a basis for further analysis and understanding of the factors influencing their presence in the bay.\u003c/p\u003e \u003cp\u003eFigure 3: showing whale shark sighted during (a) Annual seasonal of the year and (b) Day of the year (jday) at Kilindoni Bay from 2012 to 2019. The dots are sighting data, and the blue horizontal bars with grey shading represent mean estimates with confidence intervals across the seasons and day of the year.\u003c/p\u003e\n\u003ch3\u003eEnvironmental Factors that Influence Whale Shark Sightings at Kilindoni Bay\u003c/h3\u003e\n\u003cp\u003eWeather conditions, sea surface temperature, moon illumination, and Zooplankton influenced whale shark sightings at Kilindoni Bay (Fig.\u0026nbsp;4). The grey shade indicates confidence intervals, while the line indicates the mean average. Based on AICc, the best model included weather, Zooplankton, moon illumination and sea surface temperature as essential variables in explaining variation in whale shark sightings at Kilindoni Bay. Figure\u0026nbsp;4(a) indicates that weather significantly (χ2\u0026thinsp;=\u0026thinsp;10.626, df\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;=\u0026thinsp;0.031) influenced whale shark sightings in the study area, with most of the sightings made during partial overcast. The Zooplankton availability had also significantly (χ2\u0026thinsp;=\u0026thinsp;206.580, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.001) influenced whale shark sightings, whereby shark sightings were higher in the areas with a higher number of Zooplankton and were lower in the regions with no or negligible amount zooplankton (Fig.\u0026nbsp;4(b)). Moreover, Fig.\u0026nbsp;4(c) indicates that moon illumination significantly influences whale shark sightings at Kilindoni Bay (χ2\u0026thinsp;=\u0026thinsp;7.464, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;=\u0026thinsp;0.006), whereby there was a positive relationship between shark sightings and moon illumination. Most of the limited sightings occurred during rainy weather, and sea surface temperature (Fig.\u0026nbsp;3(d)) was initially expected to play a significant role in explaining shark sightings. However, its influence was not statistically significant (χ\u0026sup2; = 0.951, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;=\u0026thinsp;0.329). Contrary to common assumptions, temperature variation did not effectively predict whale shark sightings (see Fig.\u0026nbsp;4(d)).\u003c/p\u003e \u003cp\u003eFigure 4: Environmental factors (a) weather, (b) zooplankton, (c)moon illumination and (d) sea surface temperature and whale shark at Kilindoni Bay. The dots are sighting data, and the blue horizontal bars with grey shading represent mean estimates with confidence intervals.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eUnderstanding the factors influencing whale shark sightings is crucial for enhancing conservation efforts and predicting patterns of their occurrence in marine ecosystems. In this study, we examined a range of environmental variables that could impact whale shark sightings, including seasons, temperature, weather conditions, moon illumination and zooplankton. While previous research has often highlighted the importance of seasons and other physical chemical variables in influencing whale shark sightings, our findings challenge some of these assumptions. The following discussion explores how these variables, influenced the whale shark sightings in our study area. Additionally, we compare our results with existing literature, identifying key consistencies and discrepancies, and propose potential explanations for the unexpected findings. This discussion provides a broader context for the implications of our results on whale shark conservation and management strategies.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSeasonal Change of Whale Shark Sighting.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSeasonal sightings of whale sharks on Mafia Island vary in season. The findings revealed that the period from the 290th day to the 360th day of the year was identified as the most favorable time for whale shark sightings (Fig.\u0026nbsp;3). Additionally, the month factor was found to be a good predictor in the model, showing a peak in sightings during the Northeast (NE) monsoon season November to February. This pattern aligns with observations from other whale shark aggregation sites worldwide (Rohner et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Prebble et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Reynolds et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), where a defined peak season in whale shark presence is often attributed to increased productivity linked to daily variation (Rowat and Brooks \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile the exact reasons for this seasonality in whale shark sightings on Mafia Island remain speculative, the abundance of zooplankton likely plays a key role. This concurs with other studies in the WIO region (Diamant et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Prebble et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), pointing out the factors associated with whale shark aggregation. On the contrary, other studies (Marcus et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Frixione et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Rohner et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) indicated zooplankton serves as a primary food source for whale sharks, and its availability may influence the movement and aggregation of whale sharks. The association between zooplankton abundance and the observed seasonality suggests a possible link between the two factors. However, further research is needed to explore and confirm the specific mechanisms underlying the seasonality of whale sharks in this region.\u003c/p\u003e \u003cp\u003eHigher sightings were observed during the early days of October to January, whereas lower sightings were seen in the later days of February (see Fig.\u0026nbsp;3). This is consistent with previous studies which demonstrated a peak in whale shark occurrence between October and February (Hardenstine \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Prebble et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This period aligns with the warmer seasons characterized by sunny and cool weather with weak monsoon wind, suggesting a seasonal suitability for whale shark sightings. The results of this study underscore the critical role of timing in the seasonal occurrence of whale sharks, as illustrated in Fig.\u0026nbsp;3(b). These findings align with the hypothesis that whale shark sighting patterns are closely linked to seasonal environmental fluctuations, which have shown considerable variability over time (Hueter et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) This dynamic relationship between whale shark activity and changing environmental conditions further emphasizes the need for ongoing monitoring to better understand and predict their movement patterns in response to shifting ecological factors.\u003c/p\u003e \u003cp\u003eSimilarly, the results indicate a notable increase in whale shark sightings during 2017, 2018, and 2019 compared to previous years. Studies such as Cagua et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Jonahson \u0026amp; Harding (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and Rohner et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported a similar trend of increasing whale shark sightings in the Mafia. This increase can be attributed to several factors, including technological advancements, such as using fiberglass boats, which provide better opportunities for spotting whale sharks. The improved experience and knowledge of boatmen and tour guides encountering whale sharks at Kilindoni Bay may also have contributed to the increased sightings. These findings suggest that technological advancements play a key role in enhancing the ability to detect whale sharks in the area. However, the use of such technologies\u0026mdash;such as modern boats\u0026mdash;can also negatively affect whale shark observations if not properly managed, particularly due to issues like noise pollution and oil spills.\u003c/p\u003e \u003cp\u003eIt is worth noting that this study observed a notable decline in whale shark sightings in 2016, a trend that has also been reported globally, coinciding with a significant downturn in whale shark tourism (Theberge and Dearden \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; S\u0026aacute;nchez et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This decline may be partially attributed to intensified fishing and tourism activities that exceed the ecological carrying capacity of the area. Additionally, oceanographic changes, such as shifting currents, could disrupt whale shark behavior, potentially causing them to retreat from typical sighting areas or become less visible. These activities may have had a temporary negative impact on the presence of whale sharks in the area. Thus, technological advancements, coupled with a reduction in disruptive activities (Rohner, Pierce, Marshall, et al., 2013), such as fishing and tourism practices that can disturb whale sharks, are factors associated with variation in the sighting of whale sharks at Kilindoni Bay.\u003c/p\u003e\n\u003ch3\u003eEnvironmental Factors Influence Whale Shark Sightings\u003c/h3\u003e\n\u003cp\u003eWhale shark distribution and sightings at Kilindoni Bay vary by season and are mostly driven by food availability. Other important factors for whale shark sightings were calm weather conditions, which enhance visibility, making it easier to spot whale sharks, while rough seas can impede observations. Moon illumination may influence their feeding behavior, potentially affecting their activity levels and sea surface temperature that affects the abundance and availability of whale shark's food\u0026thinsp;\u0026minus;\u0026thinsp;plankton including small fishes. Understanding these variables is essential for effective conservation efforts aimed at protecting whale shark populations and their habitats.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eWeather\u003c/h2\u003e \u003cp\u003eResults revealed that weather was an essential factor affecting the sighting of whale sharks with most of the sightings made during partial overcast (Fig.\u0026nbsp;4 (a)). According to Morgado et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)d Antonio et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) overcast conditions, where the sky is partially covered with clouds, increase visibility into the water. This can be particularly beneficial for detecting whale sharks that may be swimming deeper in the water column. Partial overcast conditions can reduce surface glare, enhancing underwater visibility and potentially influencing whale shark feeding behavior. Cloudy weather may also lead to more subdued whale shark activity, while heavy rainfall can create rough seas and further decrease visibility. The impact of raindrops on the water surface can distort the view, making it challenging to spot whale sharks. However, other studies (Perry, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rohner et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) have reported that light rain can enhance plankton activity near the surface, likely due to nutrient runoff, which may attract whale sharks to these nutrient-enriched areas. According to a study by (Rohner et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), rain causes nutrients to flow from the Rufiji River to the Mafia, increasing plankton availability. Sunny weather with clear skies provides excellent visibility above and below the water's surface, allowing observers to spot whale sharks even from a distance. Whale sharks often come closer to the surface to feed on plankton and small fish. During sunny conditions, the contrast between the shark's light-colored skin and the darker ocean water makes it easier to spot them.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eZooplankton\u003c/h3\u003e\n\u003cp\u003eThis study has uncovered a significant relationship (χ2\u0026thinsp;=\u0026thinsp;206.580, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.001) between whale shark sightings and the presence of zooplankton. As noted by (Marcus et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), this was not surprising because the higher amount of zooplankton reflects the food availability for whale sharks. Similarly, study indicated that there are a greater number of whale shark sightings off Mafia Island when a high concentration of zooplankton is present. This relationship becomes clearer when considering the role of nutrients as indicators of phytoplankton abundance, a key driver of zooplankton productivity. Mateka et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) observed a seasonal cycle of phytoplankton in the surface waters of Mafia, with growth peaking during the rainy season in March and reaching maximum productivity between June and September. The closed-circuit nature of the current system accumulates plankton during the Northeast monsoon, while nutrient-rich waters from the Somali Current may also feed into the East African circulation system, further enhancing productivity in the region. A high zooplankton biomass in the waters coincided with a higher recorded number of whale sharks (see Fig.\u0026nbsp;4 (b)). This relationship can be attributed to the specific feeding behaviour of whale sharks, which necessitates a substantial intake of food daily to meet their physiological needs. The substantial number of whale shark sightings in Kilindoni Bay, mainly when zooplankton biomass was high, is indicated in Fig.\u0026nbsp;4(b). This finding suggests the importance of zooplankton abundance as a critical factor influencing whale sharks' presence and feeding behaviour in the study area.\u003c/p\u003e\n\u003ch3\u003eMoon Illumination\u003c/h3\u003e\n\u003cp\u003eThere was a relationship between lunar illumination and the sightings of whale sharks (Fig.\u0026nbsp;4(c)). Sightings were more frequent during periods of higher moon illumination, particularly when the moon was more than half full. This pattern is consistent with findings from other regions, such as Madagascar and Kenya, where more sightings occurred during the full moon (Temple et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This suggests that the moon phase may directly or indirectly influence whale shark behavior, significantly affecting their visibility and occurrence in surface waters. Moon phases not only influence lunar illumination but also impact tides. The researcher observed that whale shark sightings were more frequent during periods of higher moon illumination, particularly near the full moon. This pattern aligns with the idea that increased lunar light may play a role in whale shark activity, possibly by enhancing prey visibility or influencing their movement patterns (Ranintyari et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although tidal patterns were not a direct focus, the connection between moon illumination and whale shark sightings suggests that lunar light may indirectly create favorable conditions for foraging or other behaviors.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSea Surface Temperature\u003c/h2\u003e \u003cp\u003eSea surface temperature is a key factor influencing the distribution of many marine organisms, but in this study, it did not have a significant impact on whale shark sightings (χ2\u0026thinsp;=\u0026thinsp;0.951, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;=\u0026thinsp;0.329). This finding aligns with previous studies by Robinson et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); and Thums et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), who also reported no clear relationship between SST and whale shark presence. Whale sharks, due to their large body size, maintain a stable internal temperature, allowing them to undertake deep dives (over 1000 m) into cooler waters without experiencing high metabolic costs typically associated with thermoregulation. This ability enables whale sharks to move across environments with different temperature profiles without being significantly affected by fluctuations in surface temperatures. Hueter et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) demonstrated that whale sharks can dive to depths exceeding 979.5 m and tolerate a wide temperature range, with individuals thriving in both tropical and subtropical waters where temperatures range from 18\u0026deg;C to 30\u0026deg;C. This thermal tolerance, combined with their capacity for deep diving, suggests that whale sharks are less reliant on specific SST ranges for their distribution, which explains why temperature is not a primary factor governing their sightings in this study.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe analysis of whale shark sightings in Kilindoni Bay reveals that their sighting is influenced by environmental factors such as seasonal changes, weather conditions, lunar illumination, and zooplankton availability. Whale sharks were present year-round, with peak sightings in November and December, and were positively correlated with higher lunar illumination and increased zooplankton density. This highlights the ecological significance of Mafia Island\u0026rsquo;s productive waters, where whale sharks concentrate. To sustain Mafia Island as a prime whale shark habitat, it is vital to protect the marine environment, particularly by conserving zooplankton and ensuring long-term ecosystem health. The study recommends continuous monitoring of environmental variables affecting whale shark behavior, along with enforcing a code of conduct for whale shark interactions to minimize disturbances.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eSource of fund\u003c/h2\u003e \u003cp\u003eThis research was fully funded by Marine Megafauna Foundation and Tanzania Fisheries Research Institute (TAFIRI).\u003c/p\u003e \u003ch2\u003eConflicts of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.S. and E.A. jointly conceptualized, designed, and conducted the research. E.S. led the fieldwork, and both E.S. and E.A. analyzed and interpreted the data. E.A. contributed to writing, reviewing, and editing the manuscript draft.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe are deeply grateful to Dr. Chris Rohner for shaping the study design. Special thanks to the fishers and fisheries experts from Mafia for their pivotal role in advancing our whale shark research. Sincere appreciation to the Megafauna Foundation and the Tanzania Fisheries Research Institute for their generous support and proactive data sharing. The collective effort of everyone involved enriched the depth and scope of our research, making it more comprehensive.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCagua EF, Cochran JEM, Rohner CA, et al (2015) Acoustic telemetry reveals cryptic residency of whale sharks. 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Tropical Conservation Science 1:18\u0026ndash;33\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Whale Shark, Environmental factor, Sighting, Mafia Island","lastPublishedDoi":"10.21203/rs.3.rs-5296297/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5296297/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe whale shark (\u003cem\u003eRhincodon typus\u003c/em\u003e, Smith 1828) is among the largest fish that tends to swim at the surface in aggregation. Several locations in are known habitats for whale sharks. However, there is still a need to understand the environmental factors that influence their occurrences and sighting. This paper investigated the environmental factors essential to whale sharks' s in Kilindoni bay, Mafia. Data were collected through observations supplemented with secondary historical data sets from 2012 to 2019, including whale shark sightings and environmental variables. These datasets were obtained from the Marine Megafauna Foundation (MMF) and the Tanzania Fisheries Research Institute (TAFIRI). The Generalized Linear Model (GLM) was used to analyse 510 whale shark sighting records from October to February (2012\u0026ndash;2019). The variables involved were sea surface temperature, zooplankton abundance, moon illumination, and weather conditions. Results revealed that weather conditions (χ2\u0026thinsp;=\u0026thinsp;10.626, df\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;=\u0026thinsp;0.031), zooplankton abundance (χ2\u0026thinsp;=\u0026thinsp;206.580, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.001), and moon illumination (χ2\u0026thinsp;=\u0026thinsp;7.464, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;=\u0026thinsp;0.006) are significant factors influencing the sighting of whale sharks. Sea Surface Temperature (χ2\u0026thinsp;=\u0026thinsp;0.951, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;=\u0026thinsp;0.329) was not a significant factor in the sighting of whale sharks. Generally, weather conditions, moon illumination, and zooplankton abundance were vital factors for the Mafia's distribution of whale sharks. The study recommends sustained, regular monitoring of environmental variables linked to whale sharks, reinforcing the implementation of a code of conduct for whale shark sighting, and advocating for an integrated management approach inclusive of all local stakeholders.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"Environmental Factors Influencing the Sightings of Whale Shark (Rhincodon typus, Smith 1828): The Case Study in Kilindoni Bay, Mafia District, Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-25 11:30:55","doi":"10.21203/rs.3.rs-5296297/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"001a61d1-d2c9-45be-85a1-443c27a0da5c","owner":[],"postedDate":"October 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-07T14:38:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-25 11:30:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5296297","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5296297","identity":"rs-5296297","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}