Analysis of Natural Bridges National Park
Introduction:
This website was created to analyze data from the Natural Bridges National Park. The analysis considers vegetation area, plant litter, volumetric water content, and summer indicators. I focused on the summer indicators, because these variables offered the most information.
The collected data comes from measurements made at the Natural Bridges National Park from 1980 to 2018. Data from 2021 to 2024 are predictions made by the U.S. Geological Survey based on RCP 4.5 (moderate climate impact) and RCP 8.5 (potentially catastrophic climate impact) scenarios.
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Vegetation Status at Natural Bridge National Park
Intuitively, I decided to first look at the vegetation area of the National Park. I assumed that this measurement would be a good indicator of the park's environmental status. Since climate change and global warming have strong, negative impacts on vegetation, I expected to see a decrease in the vegetation area over time.
Interestingly, figures 1.1, 1.2, and 1.3 show that vegetation area in the Park from 1980, 2018, and 2024 (predicted) respectively, changed in unexpected ways. A quick look at the maps above shows slight differences across time; the vegetation in the northeastern part of the park increased, while the center and southern parts decreased. After doing this analysis, I remained interested in knowing why the organization's model (Fig. 1.3) predicts an increase in the northern area. With the environment in its current state, I would have expected to see a decrease in vegetation throughout the whole park.
[Figure 2]
The previous analysis made me want to dive deeper into the plant litter variable.
According to the article:
Litter decomposition, effects of temperature driven by soil moisture and vegetation type, plant litter has both direct and indirect relationships with temperature.
Based on this article, my inital assumption was that plant litter would decrease the temperature of the soil, which can also lead to a decrease in the annaul temperature overall.
Figure 2, which includes both collected and predicted data, shows the relationship between plant litter and temperature. As plant litter amount increases, temperature decreases. This analysis confirmed my assumption, indicating that retaining plant litter on the ground is more beneficial for the environment.
[Figure 3]
The second analysis I made utilized volumetric water content features. Volumetric water content (VWC) is the amount of water in a given volume of soil. I believed that the VWC could be related to other indicators.
Figure 3 shows the VWC value by season and RCP scenarios. Since the evaporation rate is the highest in the summer, the amount of water in the soil is also expected to be the lowest in the summer.
My initial thought was that the VWC would be lower in RCP 4.5 and RCP 8.5 scenario, but Fig. 3 shows that the VWC will be higher than that of the past. This means that the soil will contain more water than the past, which is a good sign for the environment. This also aligns with the first analysis.
[Figure 4]
Since there are many indicators in the summer data, I chose to focus only on the following: number of days of dry soil, evaporation, and precipitation before I analyze the relationship with the VWC.
I assumed that the trend of evaporation rate and the number of days of dry soil would be the same, and that the precipitation rate would be the opposite.
Figure 4 shows the trend of the normalized indicators over the time period, and it shows an interesting result. We can see that the rate of evaporation and precipitation are related, whereas the number of days of dry soil is inversly related. As the precipitation and evaporation rates increase, the number of days of dry soil decreases. It can also be said that the rate of precipitation has more impact on dry soil than that of the evaporation.
Figure 5 has six indicators: number of days with dry soil, evaporation, non-dry soil water, precipitation, maximum temperature, and volumetric water content.
The historical data showed that the VWC is mainly affected by evaporation rate. The higher the evaporation rate, the lower the VWC value. Also, we could find the relationship between the number of days with dry soil and the precipitation rate. The higher the precipitation rate, the lower the number of days with dry soil.
Interestingly, the predicted data from 2021 to 2024 did not work well with this analysis. Across 4 years, it was difficult to figure out the relationships that we had found in the historical data.
[Figure 6.1]
[Figure 6.2]
Based on the analysis above, I wanted to know whether we can predict the future climate of the National Park.
Figures 6.1 and 6.2 show the correlation of the vegetation data and the summer indicators. Since the prediction is based on the RCP scenarios, I expected that the features would have strong correlations with the RCP and scenario feature.
However, both sets of data showed no strong correlations with the RCP and scenario feature, which leads me to question the validity of the prediction.
Conclusion:
Taking the World Resources Institute and United Nations articles into consideration, I assumed that the predicted results (2021-2024) would be worse than the past.
The maps in the first section showed that the environment will be in a better state in 2024 than it was in the past. After further analysis, however, I found that this prediction might not be as accurate as initially thought.
In future work, I would recommend the organization to ensure that the weights they assign to features correctly represent the relationships they have to the predicted variables; some of these features have stronger correlations than the others.