Disease Prevalence, Physical Damage, and Recruitment

This week I looked at three data sets, Coral Observations for Disease Prevalence, Coral Observations for Physical Damage, and Coral Observations for Recruitment. In terms of Disease Prevalence, data had been collected in 2008, 2010, and 2013 for a total of 90147 observations distributed among 68 different species. After analyzing the data, it was shown that a majority of the disease in the Hawaiian Coral Reefs occurred in 2010 with a total of 35609 cases. In 2008 there were 22984 cases and in 2013 there were 31581 cases. But while 2010 had the most diseased species, 2013 had the most deaths resulting from diseased species. In 2013, there were a total of 9004 deaths of species, in 2010 there were 4330 deaths, and in 2008 there were 3050 deaths. This showed that the disease in 2013 made up approximately 55% of all species deaths within the Hawaiian Coral Reefs.

When it comes to damage, this data set only covered 2013 instead of 2013 along with 2010 and 2008.  Among the 68 species, there were 17731 instances of no damage and 144 instances of damage in 2013. Additionally, the 144 instances of damage was spread across only seven different species, but even then, those same species had more not damaged than damaged. These species are the montipora capitata (18 damaged, 3167 not damaged), montipora patula (2 damaged, 2424 not damaged), porites compressa (19 damaged, 858 not damaged), porites evernmanni (2 damaged, 163 not damaged), pocillopora eydouxi (1 damaged, 26 not damaged), porites lobata (53 damaged, 5885 not damaged), and pocillopora meandrina (41 damaged, 2464 not damaged). Because of this small amount of damages, it only makes up about 1% of the entire data on the Hawaiian Coral Reefs in 2013, whereas 99% is made up of not damaged species.

For the last data set I looked at, Coral Observations for Recruitment. From what I could tell after looking at this data set was that there was nothing really notable to take away from it. The reason I say this is because the variables represented in the data set were the same ones represented in the previous three data sets I’ve looked at, except there was nothing new added. So for that reason I don’t think I’ll be using this specific data set in my final analysis.

I’ve made descriptive charts ranging from grouped bar charts to pie charts for the first two data sets, and I plan on expanding on these along with my analysis with the data once I finish looking through all of the data sets. I’m also still thinking that I might change my research question for this data set if I get inspired to do so.

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