Option #1: Scientific Inquiry Using WildCam Gorongosa

Introduction

Located in Mozambique, Gorongosa National Park is a vast land area measuring
approximately 1,570 square miles and housing multiple animal species, from lions to warthogs to
baboons (BioInteractive, 2015, p. 1). Lion researcher Bouley Paola and her team have been
collecting images using motion-detecting trail cameras for the past few years, providing insights
into animal population estimates, behaviors, and interactions. The public has identified animals
and gathered data from these images, publishing the information on a website called “WildCam
Gorongosa.” This paper will propose a testable research question using two variables, define a
hypothesis to test the research question, make a prediction, draw a pivot table using the variables
identified, and analyze the results to disqualify or qualify the hypothesis.

Testable Question

The testable question is: “During which years are the abundance of animals the lowest and the
highest in Gorongosa National Park?”

Hypothesis and Prediction

Null hypothesis: The years with the highest number of animals in Gorongosa National Park are
2014 and 2013, while the years with the lowest population are 2011 and 2018.
Alternate hypothesis: The years with the highest number of animals in Gorongosa National
Park are not 2014 and 2013, while the years with the lowest population are not 2011 and 2018.

Methodology

Data was first filtered in WildCam Lab to include only photographs from the Gorongosa
National Park. A research question (during which years are the abundance of animals the lowest
and the highest in Gorongosa National Park?” was then formulated to guide the inquiry/research

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process. The next step was to formulate a hypothesis and prediction for the inquiry. A pivot bar
graph was afterward drawn using the WildCam Gorongosa dataset to answer the research
question and test the hypothesis. The numerical variable “species _ count” was grouped by the
categorical variable “year. A bar graph was finally drawn using the selected datasets before
being customized to meet the instructor’s guidelines. The vertical and horizontal axes were
labeled appropriately.

Results & Discussion

Figure 1. Bar Graph of the number of animals photographed in the Gorongosa National Park
each year from 2011 to 2018

Year

0
5000
10000
15000
20000
25000
30000
35000
40000

487
6546
23001
35573

2038
198

2011
2012
2013
2014
2015
2018

Based on the results shown in figure 1 above, the null hypothesis is not rejected because
2014 (35,573) and 2013 (23,001) are the years in which the highest number of animal species
were recorded at Gorongosa National Park. At the same time, 2018 (198) and 2011 (487) were
the years the least number of animals were photographed in Gorongosa National Park. The

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assumption is that no recordings were made in 2016 and 2017 because no records are available
for the two years. In 2015 and 2013, a substantially high number of animals was recorded at
2,038 and 6,546, respectively. This information can provide critical insights into understanding
the animal population trend in game research. For example, an ecologist might want to dig deep
to understand some of the weather, environment, and human factors that might have been
responsible for the sharp decline in the animal population from a high 35,573 in 2014 to just 198
five years later. Ongoing drought and drying of rivers due to climate change coupled with the El
Nino weather might explain this trend. Poaching and armed conflicts around the Gorongosa
region can also be blamed for the decrease in the animal population (Pringle & Goncalves, 2022,
p, 182).

Conclusion

Evidence from the pivot bar graph confirms the hypothesis that 2014 and 2013 were the
years the highest number of animal populations were recorded in Gorongosa National Park,
while 2011 and 2018 were the years the lowest numbers were recorded. This information can
provide clues for future research, particularly in trying to understand the factors driving the
decline in animal populations in the region.

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References

BioInteractive. (2015). Classroom resource: Gorongosa: Scientific inquiry & data analysis.
Student Worksheet. https://www.biointeractive.org/sites/default/files/Gorongosa-Data-
Student.pdf
Pringle, R. M., & Goncalves, D. (2022). Rewilding case study: Gorongosa National Park,
Mozambique. In S. Hawkins, I. Convery, S. Carver & R. Bayers (Eds.), Routledge
handbook of rewilding (pp. 180-190). Routledge. doi:10.4324/9781003097822-20