Sustaining biodiversity in fish populations is extremely

important to the quality of our aquatic environment. High genetic variation in

fish populations has the potential to protect them from environmental pressures

like climate change, pollutants and mass mortalities due to the spread of

diseases. According to research, the loss of biodiversity could also lead to

the decrease in the ocean’s ability to sustain water quality and resources (Worm

et al., 2006). This is why areas with high levels of biodiversity decrease are

being protected (MPA’s). MPA’s are Marine Protected Areas were human activities

like fishing is greatly reduced for conservation purposes.

Many professionals would come to a similar conclusion that

the protection of marine areas have a positive effect on fish populations and

biodiversity (Gubbay, 1995). This report studies the relationship between

MPA’s, number of threatened fish species and fish species richness using

quantitative data. This relationship is studied in order to find out if the

protection of marine areas has any significant effect on fish populations. Two hypotheses

are proposed, the first one suggests that the larger the MPA’s, the lower the

number of threatened fish species seen. The second one suggests that the larger

the MPA’s, the more species richness seen in the area.

Method

Firstly, the data is uploaded into a programme called R, R

is a software environment most commonly used for statistical data analysis.

Once the programme is uploaded, the areas lacking MPA’s are filtered out

because we are only studying marine protected environments. Normal Q-Q plots are then made for the MPA’s,

number of threatened species and species richness, this is done to view the

normality of the data on a graph. A Sharpio-Wilk test for normality is then

used to determine if the data is modelled by a normal distribution. This test

is repeated with logs of data in order to improve the normality. The

Sharpio-Wilk test null hypothesis suggests that the data set is normally

distributed. The normality or abnormality of the data set used here determines

what tests should be taken out next. The data is plotted on scatter graphs to

show the relationship between MPA’s and the number of threatened fish species

and MPA’s and species richness. Linear models are used to show trend lines on

the graphs. The results generated allows the visual study of the effects of

MPA’s on fish populations globally, therefore, allowing the acceptance or

rejection of the hypothesis proposed.

Results

Figure 1 shows the normal Q-Q plot for the Marine Protected

Areas. The results of the Sharpio-Wilk test suggests that the data does not

follow a normal distribution (p = 2.2e-16) this allows us to reject the null

hypothesis the sharpio test suggests. Figure 2 and 3 also shows similar trends

with p-values <0.05 (p = 5.387e-12 <0.05, 1.83e-13 <0.05), meaning
they do not follow a normal distribution, allowing the rejection of the null
hypothesis.
Figure 4 shows that the normal Q-Q plot for the Marine
Protected Areas data remained abnormal even after being logged (p = 0.002906).
On the other hand, the dataset for both the number of threatened fish species
and the species richness became normal after being logged (p = 0.6289, p = 0.37). This can be seen in figure 5
and 6.
Figure 7 shows the relationship between Marine Protected
Areas and number of threatened fish species on a scatter graph. The trend line
shows a significant positive correlation (F-statistics (1,120): 9.91, p-value = 0.002074).
Studying figure 8, similar trends can be seen. The relationship between Marine
Protected Areas and fish species richness also has a significant positive
correlation F-statistics (1,120): 23.62, p-value: 3.582e-06). These results
suggests that MPA's have a positive effect on the fish species richness.