Throughout 2016, the Queensland Government caught 532 sharks off 86 different beaches in the state as part of their Shark Control Program. The aim of this report is to place this data in context, allowing some trends in the data to be understood by more readers. In a question of public safety, the report analyses the sharks captured in summer, as opposed to winter, finding that there were 45% more sharks present in summer. The average length of sharks captured was also compared to the average Australian male height, to allow readers an insight into what beaches might be like, if it was not for the Shark Control Program keeping sharks out, and it was found that sharks, on average, are taller than humans.
This dataset originates from the Queensland Government’s Department of Agriculture and Fisheries, as they conducted their Shark Control Program in 2016. The data can be found on the department’s corresponding statistics website, ‘QFish.’ (Queensland Government, 2022c). Open government data such as this is usually considered valid, a view which has been maintained by various researchers and academics (Ceolin et al., 2013). Furthermore, the Queensland Government first started the Shark Control Program in 1962 (Queensland Government, 2022b), meaning the 2016 dataset is the 55th iteration of the program. Consequently, researchers have had a considerable amount of time to refine their data collection methods, as well as bring in new technologies such as drones and catch alert drumlines (Queensland Government, 2022b), to refine the data they use. The aim of the Shark Control Program is to “reduce the chance of shark attacks on humans” (Queensland Government, 2022a). Thus, the most important stakeholders for this data is the Queensland Government, as they oversee the safety of the beaches, as well as any individuals using Queensland beaches. Other stakeholders include the Australian Tourism industry, who would potentially use this data to plan future building or events at various beaches, and marine biologists or other scientists hoping to investigate the behaviour of varying shark species.
The sharks.csv dataset contains 10 variables, represented by each column of the file, and 532 observations, each in a separate row. Each variable provides an insight into the patterns of sharks in Queensland, from their migration habits to growth patterns and seasonal sightings. The full list of variables, and their classification in this particular report, can be found in the code below.
The key variables used include:
• Water Temperature (given in degrees Celsius) – Used in research question 1 as it is a very useful indicator of shark migration patterns from cooler to warmer water.
• Month – Also used in research question 1 as a method of determining migration patterns, as the month of the year can be used to define seasonal trends of summer and winter.
• Length (given in metres) – Used in research question 2 to compare the size of sharks with that of humans.
sharks=read.csv("data/sharks.csv")
## Classification of variables:
species=sharks$Species.Name
date=sharks$Date
area=sharks$Area
location=sharks$Location
latitude=sharks$Latitude
longitude=sharks$Longitude
length=sharks$Length..m.
temp=sharks$Water.Temp..C.
month=sharks$Month
day=sharks$Day.of.Week
dates=as.Date(date,tryFormats = c("%d/%m/%Y"))
An estimated 14.4 million Australians visited the coastline in 2021, making 500 million individual visitations in total. Nearly all of these beach days involved swimming, or at least wading, through the ocean, and most of them were in the warmer months of the year. Therefore, for the sake of public safety, it is important to know when sharks can be most frequently found in ocean waters. It was hypothesised that there are more sharks captured throughout summer – which is defined as December, January, and February – than winter, which is from June to August. This is due to the migration patterns of some Australian shark species, such as the Bull Shark (Heupel et al., 2020) or the White Shark (Government of Western Australia, 2022), among others. The following code depicts numerous numerical and graphical summaries of the data, including the mean of both the warmer and colder months, as well as a bar plot visualising the data.
## Number of shark captures in each month of the year:
## Bar plot:
ordermonth = ordered(month, levels=c("January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"))
barplot(table(ordermonth), main="Figure 1.1: Number of Shark Captures in Each Month of the Year", las=2, xlab="Month", ylab="Number of Shark Captures",col="yellow")
plot(ordermonth, temp, main="Figure 1.2: Seasonal Range and Medians of Water Temperature", las=2, xlab="Month", ylab="Water Temperature (C)",col="green")
warmer=sum((month=="December")+(month=="January")+(month=="February"))/3
cooler=sum((month=="June")+(month=="July")+(month=="August"))/3
result=(warmer/cooler)*100
##results:
print(paste0("The mean shark captures in summer was ", warmer))
## [1] "The mean shark captures in summer was 50.3333333333333"
print(paste0("The mean shark captures in winter was ", cooler))
## [1] "The mean shark captures in winter was 34.6666666666667"
print(paste0("Therefore, the shark captures in summer, as a percentage of the captures in winter, was ", result))
## [1] "Therefore, the shark captures in summer, as a percentage of the captures in winter, was 145.192307692308"
From the above code, it can be seen that the mean shark captures throughout summer was 50.33 captures a month, whilst the number decreased to 34.66 per month in winter. Therefore, the shark captures in summer, as a percentage of the captures in winter, was 145.19%, meaning there was approximatelt 45% more captures in summer than in winter. This relationship can be visualised in Figure 1.1, which is a bar plot demonstrating the higher number of captures in summer compared to winter, whilst Figure 1.2, which has a very similar to shape to Figure 1.1, demonstrates the water temperature each month. Therefore, it can also be concluded that the water temperature of the ocean is correlated to the number of sharks captured off Queensland shores.
The average height of an Australian male is 1.756m tall (Australian Bureau of Statistics, 2012), placing them in the 30 tallest nationalities in the world (World Population Review, 2022). If an Australian male was to find a shark in the water while at a Queensland beach, however, would the shark be taller than him? What would beaches be like without the Shark Control Program? This research question allows the reader to picture the true size of a shark, if it were swimming next to them at the beach. The null hypothesis is that the shark’s average height is 1.756m, (H0: μlength= 1.756), and the alternative hypothesis is that the shark’s average height is greater than 1.756m (H1: μlength > 1.756). To visualise the average height of the sharks, Figure 2.1 demonstrates the lengths of all sharks captured throughout the year. Since each observation in this dataset is a different shark capture, it is clear that the data was collected independently. Furthermore, there are 532 observations, allowing for the assumption that the data follows the Central Limit Theorem, and that the sample taken is approximately normal. Consequently, a t-test can be performed to assess the research question. It is performed in the code below:
## write code here
avglen=mean(length)
t.test(length,mu=1.765,,alternative="greater")
##
## One Sample t-test
##
## data: length
## t = 4.2879, df = 531, p-value = 1.071e-05
## alternative hypothesis: true mean is greater than 1.765
## 95 percent confidence interval:
## 1.860426 Inf
## sample estimates:
## mean of x
## 1.919981
plot(dates,length, main="Figure 2.1: Lengths of Sharks Captured Throughout 2016", xlab="Date", ylab="Length of Shark (m)", las=1, pch=20, col="darkorange2")
The results of the t-test conducted indicate that the average shark would in fact be longer than the average Australian male is tall. The test statistic of 4.29 indicates that the mean length of sharks captured by the Shark Control Program is much greater than the mean average Australian male height. The 95% confidence interval value of 1.86 further supports this conclusion, meaning that the result is extremely likely to be greater than the average male height of 1.756m. The p-value of 1.07x10-5 indicates that this result is extremely significant, and is not simply a coincidence. Taking into consideration that the mean shark length, 1.91m, is also much greater than the average Australian male height, it can be definitively concluded that the average shark captured off the coast of Australia would be longer than the average Australian male is tall.
Australian Bureau of Statistics. (2012, October). Profiles of Health, Australia, 2011-13 (No. 4338.0). https://www.abs.gov.au/ausstats/abs@.nsf/lookup/4338.0main+features212011-13
Coelin. D, Moreau. L, O’Hara. K, Schreiber. G, Sackley. A, Fokkink. W, Robert van Hage. W, & Shadbolt. N. (2014). Reliability Analyses of Open Government Data. 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, 1(1), https://www.cs.vu.nl/~guus/papers/Ceolin14a.pdf
Government of Western Australia. (2022). White Shark Movement & Population. SharkSmart. Retrieved October 26, 2022, from https://www.sharksmart.com.au/research/white-shark-distribution-population/
Heupel. M, Peddemors. V, Espinoza. M, Smoothey. A, & Simpfendorfer, C. (2020). Continental-scale shark migrations. State and Trends of Australia’s Ocean Report, 1(1), https://www.imosoceanreport.org.au/wp-content/uploads/2020/01/STAR4.7-Heupel.et.al.pdf
Queensland Government. (2022a). About. Department of Agriculture and Fisheries. Retrieved October 25, 2022, from https://qfish.fisheries.qld.gov.au/help/about
Queensland Government. (2022b). How we catch and detect sharks. Department of Agriculture and Fisheries. Retrieved October 25, 2022, from https://www.daf.qld.gov.au/business-priorities/fisheries/shark-control-program/shark-control-equipment
Queensland Government. (2022c). QFish. Department of Agriculture and Fisheries. Retrieved October 25, 2022, from https://qfish.fisheries.qld.gov.au/
World Population Review. (2022). Average Height by Country 2022. Retrieved October 27, 2022, from https://worldpopulationreview.com/country-rankings/average-height-by-country