Spinner Dolphin Sonar Activity vs. Tourism Rates in Maui Nui

AP Capstone Project

Introduction

Dolphins have been constantly subjected to harm and disturbance due to various types of human interactions [1]. The primary disturbances come from commercial and fishing vessels [2], and swimmers [1]. The native or residential dolphins of the Hawaiian islands are more subject to this negative effect, especially since the annual rates of visitor arrivals to the islands are increasing by millions every year [4, 5], and the vast majority of the incoming population are tourists planning for their honeymoon, marriage, or family vacation [4]. This portion of the tourist population is observed to be directly related to the activity in cruise ships, boating tours, and beach visits, potentially disturbing wildlife in the area. The Hawai’i Tourism Authority group, an unacademic but applicable source due to their ties with the government, estimated that the incoming tourists had increased by roughly two million visitors per year, however, it faced a sudden drop-off in 2020, then came back even stronger in the last two years [4]. It has been determined by several studies that these high touristic rates have proven to have a negative relationship with the well-being of Hawaiian dolphins in terms of their foraging activity and physical health [1,2,5], primarily the most “long-term” [3] residential dolphins, the spinner dolphin population.

Spinner dolphins are a nocturnal, coastal species that stick to strict, habitual routines [5]. They tend to rest in deeper waters during the day, and swim in-shore and to the surface at night; however, in order to avoid predators during their four-to-five hour rest periods, pods of spinner dolphins prefer to rest in “open, sandy-bottom areas,” with “clear, calm, and relatively shallow waters” [6]. This, paired with their unvarying routine, leads spinner dolphins to prefer specific bays as resting areas. Some popular bays for tourists in the Maui Nui area, such as Honolua, Manele, and Hulopoe, are home to some of these dolphin pods. Hulopoe Bay neighbors Four Seasons Resort Lanai, which advertises it as a “spinner dolphin playground” [10] available for snorkeling and swimming, while Manele Bay is ironically both a marine preserve and the island’s only public harbor for commercial vessels. Due to these bays’ popularity, the ideal locations have been stated to have a significantly negative effect on the dolphins’ ability to rest in between their nightly foraging bouts [1, 5].

These factors led me to question whether or not there has been a prominent trend between tourism rates in the Maui Nui area and spinner dolphin sonar activity in the Manele and Hulopoe bays within the last year. This research would allow me to put into question the efficacy of current protective regulations regarding human interference on spinner dolphins, and bring further reason for extended causal research on this topic. With six months worth of recorded clips of spinner dolphins from Manele and Hulopoe, I organized the data by month and graded each month by activity levels on a set scale. By comparing this data to the tourism rates of the Maui Nui area over the same time period, this study will attempt to establish a correlative trend between spinner dolphin activity and tourism rates to examine its strength and the overall potential necessity for further improvements and research in the conservation of the local spinner dolphin population.

Literature Review

The examination of cetacean activity around human activity is widespread and highly variable due to the various aspects of the spinner dolphins’ behavior. The “rigid behavioral patterns” [5] of the species allow for its various habits to be examined in-depth. However, despite the efforts of researchers and conservationists, the species remains threatened by tourism and commercial vessels in public bay areas throughout the Hawaiian Islands [1,2, 3, 5]. Thus, several papers research various different threats to spinner dolphins’ population size, foraging activity, and physical being to provide an impetus for “conservation management plans” from Hawaiian officials [5]. These studies provide my project with a foundation regarding the impact of tourism on common dolphin populations and spinner dolphin behavior, by using various methods to evaluate their physical health and behavioral patterns. In examining the results for both local and global populations, I was able to extrapolate my project on a correlative trend between spinner dolphin sonar specifically in the Manele and Hulopoe bays, and incoming tourism rates on Maui from 2021.

The Impact of Human Activities on Common Dolphin Populations

The behavioral patterns of dolphins have been observed to be disturbed by the presence of human activity, especially invasive activity such as swimmers and commercial vessels touring, specifically to watch and follow dolphin pods. A study conducted by Anna Meissner in New Zealand on the correlative Markov Analysis of various trends in common dolphin behavior around human activity demonstrated that the presence of swimmers and vessels heavily impacted the behavior and well-being of common Delphinus dolphins. Most notably, it decreased their foraging activity by 12.4% while severely increasing their traveling time [1], thus decreasing their time spent resting and foraging, as noted in Karen A. Stockin’s similar study on common dolphin behavior around various types of vessels [2]. Stockin also noted that the bottlenose dolphins took “ significantly longer to return to their initial behavioral state in the presence of a tour boat” [2], indicating that the issue is directly related to tourist activity due to boating and touring companies’ constant pursuit of common dolphins. 

In relation to this point, Meissner’s team observed an average of two to three vessels  approaching the dolphins at one time in a popular New Zealand bay; however, the number of boats sometimes reached up to 61 commercial vessels surrounding a single pod of dolphins, despite the regulations and sanctions regarding dolphin and human interactions, raising the question of their effectiveness [1]. The vessels varied in size and speed, but the general bar that Meissner determined for “vessel traffic intensity” that would cause the dolphins to shift out of their comfortable routine was passed several times throughout the observational period of about a year. These disturbances were noted to cause short-term behavioral changes that have previously been examined to snowball into “long-term implications for targeted populations by disrupting energy budgets, reducing energy uptake and/or increasing physical demands” [1]. The overwhelming presence of commercial vessels, including cruises, day tours, and swimming and scuba diving tours, has been inevitably increasing in proportion to the average yearly tourism rates in the Maui Nui area for many years, potentially leading to a significant decline in the spinner dolphin populations’ size and the health of the dolphins overall [5]. In order to combat this, government officials have recently implemented protective measures. However, the efficacy of government conservation efforts has been noted by several studies as inconsistent and unbeneficial to the dolphin population.

Current Policies and Regulations, and their Effectiveness

The spinner dolphin and common dolphin populations are both marked as “Least Concerned” species in terms of endangerment by the IUCN Red List of Threatened species for countless years. The IUCN describes itself as the “most comprehensive” indicator of population trends, but Meissner notes that, despite the large population of spinner dolphins, their dwindling population size could be ignored or disregarded by public officials due to the IUCN’s lack of consideration for spinner dolphins’ constant struggle with pollution, fishery injuries, and human activity [1]. Julian Tyne, a Ph.D. candidate for marine sciences at Murdoch University, noted several similar points surrounding this disregard for the health of spinner dolphins in his effort to establish a more accurate estimate of the local Hawaiian spinner dolphin population. He stated that spinner dolphins in the Hawaiian Islands are “likely more vulnerable to negative impacts from human disturbance than previously believed,” and that the deficient information regarding spinner dolphin population is “a significant impediment to developing appropriate management plans for any spinner dolphin management unit in Hawai’i” [5]. Tyne, as well as countless scientists with the National Ocean and Atmospheric Administration (NOAA), worry that government officials will not move to enforce their propositions for sufficient protective measures without proper evidence from reputable sources such as the IUCN. For many years, in fact, there were little to no prohibitory laws in place to restrict human interference in residential dolphins’ routines.

Only recently, in September of 2021, did Hawaii State government accepted a regulatory law proposed by the NOAA, prohibiting “swimming with, approaching, or remaining within 50 yards of spinner dolphins,” including interference from vessels or “other objects” [8]. However, the law does not account for illegal fishing vessels, and though it proposed time-area closures of certain residential shallow bays, such restrictions have yet to be implemented [2, 8]. Spinner dolphins are almost completely unprotected from curious tourists and unregulated interference due to the lacking awareness of the “intense viewing pressure” [8] that they face on a daily basis.

The Gap

Taking into account the data and suggestions from previous studies, it has come to light that there is a lack of studies demonstrating a clear trend between tourism rates and dolphin activity. Rather, they focus more on specific aspects of the dolphins’ well-being, such as physical wounds and observed activity in the presence of commercial vessels. However, the recording of dolphin sonar and using it to interpret patterns in dolphin behavior is a more recent proposition following the creation of certain devices, creating the gap that I pursued in my research. The main method of data analysis has been via direct observation of dolphin behavior in the water, which could have resulted in unintentional disturbance of the spinner dolphins due to the presence of the scientists and their observation vessels. Using stagnant recording devices, such as the ones that the NOAA used to record spinner dolphins, minimizes contact between the scientists and the dolphins, unfortunately eliminating the possibility of in-person qualitative monitoring, but also decreasing the chance of artificially produced results due to human disturbance. Previous studies, such as Meissner’s and Machernis’ studies, also focus primarily on bottlenose dolphins, due to their larger population size and more variable nature. I have found my gap in examining the local spinner dolphin population through its sonar activity and relating it directly to tourism rates with correlative analysis rather than using field observations such as interference from fisheries and swimmers to assess dolphin behavior.

Using this gap, I aim to answer the question: Is there a statistically strong and linear correlation between spinner dolphin sonar activity in Manele and Hulopoe bays and tourism rates in Maui Nui between March and August of 2021? In examining spinner dolphins in particular in these popular local bay areas, my research will further implicate tourism as a potentially negative impact on spinner dolphins’ health, adding to pressure on local and state governments to reinforce currently existing regulatory laws. Furthermore, by examining the correlation between their sonar activity and tourism rates, I hope to add impetus for more research on this topic to solidify a causal relationship between the two.

Methodology

To answer my question, I compared the varying rates between tourism and spinner dolphin sonar activity from March to August 2021 and calculated their correlation coefficient to assess the strength and direction of their relationship. The two populations that I examined were the coastal residential pods in Hulopoe and Manele bays. I used correlative analysis to see whether or not there was a statistically significant, indirect trend between the two variables to implicate tourism rates as a negative impact on spinner dolphin activity.

Assessing Dolphin Activity

The program I used with the NOAA analyzes sounds for the Ecological Acoustic Recorders, or EARs, that were deployed around Maui and Lana’i in March of 2021, and transfers them into a visual representation of a whistle or click from a dolphin. Sounds can be ambiguous or can be representative of other species, so the purpose of my analysis was to manually confirm the readings from the NOAA’s algorithm as to whether or not a dolphin created the noises picked up from the EAR. The EARs collected acoustic activity once a certain threshold of decibels, the standard unit for measuring the noise level of audios, was met, resulting in small soundbites of data across the spectrogram. If the sound was too far away, or if the creature producing it was too small, or alone, the noise was not picked up. This resulted in more geographically precise data, and less potential for ambiguous sonar. The data was then visualized on the data map (Figure 1) in the software that is used to analyze the audio. Dolphin sonar was typically in bursts of activity, that were shown as grouped up points on the data map.

Figure 1: Dolphin activity was indicated by the linear bursts of activity, generally around the hours of 6 AM - 12 PM, signifying their return to their habitual resting area during the day.

Justification

In order to assess the data, a correlational analysis method was implemented following quantitative data collection surrounding the monthly rates of tourism income in the Maui area and overall dolphin sonar recorded in Manele and Hulopoe to adequately establish a non-causal but direct relationship between the two.

The dolphin sonar rates mix both clicks and whistles recorded in the bay areas, as the dolphins showed very few if any clicks throughout the data, thus providing insufficient evidence to analyze separately from the whistles. Clicks indicate that the dolphins are echolocating, implying that they are foraging or encountering other creatures. Whistles indicate interspecies communication, either to coordinate traveling or to indicate a resting period [6], so in studying their resting areas, it was expected that there would be significantly more whistles.

For the purpose of this study, the correlational analysis would allow for the most direct connection between tourism rates and spinner dolphin sonar rates in Manele and Hulopoe without access to field observations, as it uses purely quantitative data to establish a relationship between two potentially related variables.

Procedure

To begin data collection, I set up the PamGuard software and followed instructions given to me by the NOAA. Instead of manually inputting the raw data that the NOAA’s algorithm gave me, I used the data map (Figure 1) to determine the presence of dolphins at certain times in order to minimize the amount of time I spent collecting one portion of my data. To categorize activity, an hourly marked spreadsheet from March to August was utilized, and represented activity with a “1” next to the hour the activity was detected. Once the spreadsheet was filled out, I went back to manually confirm ambiguous sound groups, which generally consisted of one vertical line of activity, or a few small blips, in order to minimize the potential for misrepresentation in my data.

A TI-84 was used to calculate the correlational coefficient. By inputting the six standardized values representing dolphin sonar rates in the L1 list on the x-axis, and the corresponding tourism rates into the L2 list on the y-axis. Using these lists, the linear regression can be found through the “STAT -> CALC” option on the calculator to find the correlational coefficient “r.” Since the correlational coefficient is not reliant on a dependent or independent variable, axes were not an integral consideration for the procedure.

The “r” value of the linear regression, typically given by a TI-84 upon solving for the linear regression model of any graph, represents the correlational coefficient on a scale of -1 to 1. To determine the strength, or significance, of the correlational coefficient, it must be compared to the critical value corresponding to the degree of freedom. If r is in between the positive and negative critical values, it is not significant, but if it is greater than the positive value or less than the negative value, it can be regarded as significant. For this project, the critical values corresponding to a data set of n = 6 are 0.811 and -0.811. For this research study, the null hypothesis that the correlational coefficient would be “0,” representing little to no strength, and therefore a correlation between the two variables was employed. Because I aimed to establish the relationship between the two variables in terms of strength and linearity, I also employed the “r²” variable from the linear regression, otherwise known as the coefficient of determination, representative of the linearity of a relationship from a scale of 0 to 1. Similar to the correlation coefficient, the null hypothesis for my coefficient of determination was “0,” illustrating little to no linearity between the two variables, which would indicate that the x-values on the graph did not line up proportionally with their corresponding y-values.

In calculating the correlation coefficient and the coefficient of determination, I was able to account for the main variables in the question of whether or not there was a strong, linear relationship between the data I received from the NOAA on dolphin sonar rates and tourism rates.

Results

“Hulopoe Bay” and “Manele Bay” representative of the number of hours with spinner dolphin activity recorded, “Tourism Rates” by the number of visitors to Maui per month in 2021.

        In the raw data, Manele displayed more activity overall in comparison to Hulopoe. This could be due to Manele’s role as a marine preservation site. Additionally, outside of the table, it is important to note that, typically, the dolphins displayed the most activity around 6 AM to 10 AM, followed by long periods of silence. This indicates heavy communication in the pod, potentially due to their return from nocturnal foraging activity, followed by their resting period. However, in the months of June and July, these patterns fluctuated, and there would occasionally be several days without any activity, followed by large bursts of sonar around 12 AM to 3 AM, and from 2 PM to 5 PM. This variation coincides with May, June, and July, the months with the highest tourism rates within the study period, but that is a speculative observation that requires further research to confirm.

        In order to calculate the correlation between dolphin sonar activity and tourism rates, the bays’ data were considered separately. The graphs shown below depict the trendline through GoogleSheets, whereas the correlative coefficient was calculated on a separate graph through a TI-84 calculator. “r2” indicates the coefficient of determination or the linearity of the data, and “r” indicates the strength of the relationship, thus directly answering the question of whether or not there is a strong, linear correlation between dolphin sonar activity and tourism rates in the Maui Nui area.

Calculations for Hulopoe Bay

The correlational coefficient and the coefficient of determination found by the TI-84 for the relationship between Hulopoe’s dolphin sonar activity and Maui Nui’s tourism rates from March to August of 2021 was r = -0.834, and r2 = 0.696. In comparing r to the critical values for n = 6, we see that -0.834 < -0.811, indicating that the r-value is statistically significant and that the majority of the points fall near or within the trendline.

The correlation between Hulopoe’s spinner dolphin sonar activity and the tourism rates from March through August of 2021 is a strong, linear, indirect relationship. As tourism rates increased, spinner dolphin sonar activity decreased proportionally.

Calculations for Manele Bay

        The correlational coefficient and coefficient of determination for the relationship between Manele Bay’s spinner dolphin sonar rates and the same tourism rates were r = -0.860 and r2 = 0.740. In comparing it to the critical values, since r < -0.811, it indicates the statistical significance of the calculated correlational coefficient. The r2 value similarly indicates the linearity of the scatter plot, showing that the points mostly coincide with the trendline.

        Since the r-value is statistically significant and the r2 value was high, it can be concluded that there is a strong, linear correlation between the spinner dolphin sonar activity in Manele Bay and the tourism rates in Maui Nui. Similar to Hulopoe, there was a negative association between the two: as the tourism rates went up, spinner dolphin sonar activity decreased.

Discussion

This study sought to establish a direct relationship between tourism rates in the Maui Nui area and dolphin sonar rates from two prominent bay areas on Lanai by establishing a strong, linear correlational trend between the two variables, represented as quantitative values. The resulting data rejects the null hypothesis, thus establishing that there is a strong, linear, and therefore prominent correlational trend between the spinner dolphin population’s activity throughout the study period and the overall tourist population, implying the possibility of a causal relationship between the two. By investigating this relationship, the research adds to the impetus for further research surrounding effective measures for spinner dolphin preservation by concluding that tourism could be having a statistically significant negative effect on residential spinner dolphins in Maui Nui. The question, “Is there a statistically strong and linear correlation between spinner dolphin sonar activity in Manele and Hulopoe and tourism rates between March and August of 2021?” enabled me to observe and understand the behaviors of spinner dolphins and how clear the negative effect that tourism has on spinner dolphins through my observations.

In comparing my results to previous studies, I found many similarities between our conclusions. Since spinner dolphin behavior appeared to vary the most from May to July, there is an abundance of correlative evidence of a potential underlying causal relationship that indicates the negative relationship between tourism and spinner dolphin activity. The pod could have been returning to the bays earlier and leaving later to avoid touristic activity, thus altering their habitual behavior to revolve around human disturbance, reflecting the behavior that Meissner observed in common dolphins following exposure to commercial vessels and swimmers. Additionally, this could be leading the pod to expend more energy in order to avoid touristic activity, as indicated by both Meissner’s and Stockin’s studies. In addition, the correlation itself reflects Tyne’s prediction that the spinner dolphin population, which is inevitably tied to spinner dolphin activity would decline in the following years [5].

Limitations

Due to the nature of the correlational analysis, this study cannot be regarded as concrete proof of the negative impact of tourism on the local spinner dolphin population in the Maui Nui area, it can only serve as an indication that there may be a causal force between the two variables due to their strong, linear correlational relationship. While it adds to the slowly progressing knowledge base surrounding the negative impacts of human interference on spinner dolphin health and routines, it requires further evaluation to be declared as causal proof of a statistically undeniable negative relationship between the two. The lack of visual confirmation, such as camera footage or field research, also decreased the possibility of establishing a causal relationship between tourism rates and spinner dolphin activity, as the dolphins were not directly observed while interacting with commercial vessels. Using camera footage in addition to the audio recordings to cover this limitation could prove to be advantageous, as it would open up the possibility for field observation without the physical presence of researchers, as was the case with Meissner and Stockin’s studies.

Additionally, there were many time constraints on my project that limited the full potential of my research. Six months of recordings did not account for outside influence on the two variables, primarily concerning the effect of COVID-19 on tourism rates. To account for influences on my variables, environmental or otherwise, and to eliminate outliers in the data, lengthier recording periods are necessary for the future. Lastly, manually confirming each of my data points on the data map proved to be unfeasible given the time frame that I had to complete my research.

Implications

        My research confirmed the presence of a strong, linear correlation between spinner dolphin activity and tourism rates in the Maui Nui area, as of 2021. While it isn’t an indication of a causal relationship between the two, it does provide an impetus for additional research to confirm the negative effects of tourism on the local Maui Nui spinner dolphin population. My results could inform incoming tourists and commercial companies about their impact on our oceanic neighbors, and hopefully, encourage activism from the local community to push for more effective conservation and regulatory laws from local and state officials to protect spinner dolphins. Future research involving field observations over the course of several years is necessary to prove causation for the negative relationship between tourism and spinner dolphins and to establish concrete evidence that such regulatory laws are necessary. Additionally, the NOAA’s continued use of EARs expands research possibilities past that of spinner dolphins alone and opens the door for research to improve conservation efforts for multiple different coastal species.

        Finally, the results of my research continue the long-standing wish of Julian Tyne, Anna Meissner, Karen Stockin, as well as countless other marine biologists to preserve and protect our oceanic ecosystems, so that we may have the chance to study, interact with, and coexist with them for years to come.

Works Cited

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