Environmental Systems & Societies SL's Sample Internal Assessment

Environmental Systems & Societies SL's Sample Internal Assessment

To what extent does annual tree cover loss from wildfires (Km2) correlate with annual precipitation (mm) and mean annual temperatures (°C) in Sicily, Italy, between 2001-2021?

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Word count: 2,233

Table of content

Identifying the context

Research Question

To what extent does annual tree cover loss from wildfires (km2) correlate with annual precipitation (mm) and mean annual temperatures (°C) in Sicily, Italy, between 2001-2021?

Background

The environmental issue (wildfires) is defined as “an unplanned fire that burns in a natural area such as a forest, grassland, or prairie ... often caused by human activity or a natural phenomenon such as lightning” (WHO, n.d.). Wildfires have important ecological functions: as “nature's way of clearing out dead litter on forest floors'', facilitating reproduction of some plants (Supriya, 2017). Globally, wildfires are increasing in frequency and severity in recent years. Climate change and change in land-use are expected to cause an increase in extreme fires of up to 50% by 2100 (UNEP, 2022).

 

Sicily, an island in southern Italy, has a Mediterranean biome, with long, dry summers and short, mild winters (S., 2001).

Figure 1 - “Sicily, Italy” (Encyclopædia Britannica, n.d.)

Wildfires are prevalent in hot and dry conditions because “higher temperatures cause more evaporation and this dries vegetation, creating fuel for the fires” (Met Office, n.d.). There is evidence that climate change increases wildfires (WMO, 2020). With increasing global warming, it is clear that wildfires will become a greater threat to ecosystems and human societies of Sicily.

Impacts of Wildfires

Wildfires represent a significant threat to communities and ecosystems of Sicily. Even the resources used for extinguishing fires (e.g. seawater, firefighting foam and additives) can pollute ecosystems (NFCC, n.d.). Wildfires can cause mass wildlife mortality, which is especially detrimental for more vulnerable species (IFAW, 2021). Additionally, wildfires lead to reduction in size of habitats, gene pools, and subsequently, genetic diversity. Other consequences include habitat fragmentation, desertification, and emission of particles and gases such as CO2 (European Environment Agency, 2016). After vegetation loss, soil can become hydrophobic, preventing absorption of water and facilitating transportation of sediment and debris into bodies of water (Nelson, 2020).

 

Wildfires can negatively impact local communities in many ways. Natural resources vital for humans can be destroyed (e.g. timber, recreational services, and crops). Destruction of agriculture can cause food insecurity. Air pollution from wildfires can cause respiratory and cardiovascular problems, placing strains on Sicily’s healthcare sector. Globally, wildfires cause approximately 5-8% out of 3.3 million annual premature deaths from poor air quality globally (Lelieveld et al., 2015). For the government, reparations from damage are costly. From 1900-2013, Italy spent 1.7 billion USD for damage caused by wildfires (Doerr & Santin, 2013).

 

It is clear from the impacts detailed above that wildfires are destructive to ecosystems and communities of Sicily.

 

The purpose of this IA is to investigate -

  • Whether mean annual temperatures in Sicily are increasing
  • Whether annual precipitation in Sicily is decreasing
  • Whether there is a correlation between the above mentioned variables and annual tree cover loss from wildfires

Planning

Sicily was chosen because, due to its Mediterranean climate, it is vulnerable to wildfires. The time period of 2001-2021 was selected because it represents a crucial period which has seen change in the climate.

 

The variable of annual “tree cover loss” refers to “complete removal of tree cover for any reason, including human-caused loss and natural events” (Global Forest Review, n.d.). It was chosen for this IA because it is a wide term encompassing “forest loss as well as loss of industrial tree plantations and agricultural tree crops, which are not typically considered forests” (ibid.).

 

Variables “annual precipitation” and “mean annual temperature” were selected because they may be causing factors that lead to increased wildfires, such as dry vegetation.

Figure 2 - Variable Table

Sources

The following sources were used for data collection -

  • ‘Climate Change Knowledge Portal’ is “the hub for climate-related information, data, and tools for the World Bank Group'' (Climate Change Knowledge Portal, n.d.). This source was selected because it is reputable (a renowned intergovernmental organisation).
  • ‘Global Forest Watch’ is an online platform that provides data on deforestation and forest fires, which “allows anyone to access near real-time information about where and how forests are
  • changing around the world” (About GFW | Global Forest Watch, n.d.). This source was chosen due to its international validity.

Methodology

Data relating to mean annual temperature and annual precipitation was extracted from the ‘Climate Change Knowledge Portal’ by selecting “Italy” under the “Country” section of the website (https://climateknowledgeportal.worldbank.org/country/italy). Sicily can be selected on a map, and data relating to “observed annual mean-temperature” and “observed annual mean-precipitation” is shown. This data is collected by the World Bank from reliable governmental sources and displayed on this website.

 

Data relating to tree cover loss from wildfires was taken from the “Sicily” section of the Global Forest Watch website, which can be found after selecting the “Dashboard” menu, then “Italy” (https://www.globalforestwatch.org/dashboards/country/ITA/). There is a section entitled “Fires'' which displays data solely relating to tree cover loss from wildfires. Data from Global Forest Watch is sourced from “the Global Land Analysis & Discovery (GLAD) lab at the University of Maryland” (GLAD, 2022).

Hypothesis

My hypothesis is that -

  • Trendlines for each variable will be statistically significant (>0.3).
  • As annual tree cover loss from wildfires increases, temperatures will also increase (positivecorrelation). There will be, at least, a medium correlation (>0.3)
  • As annual tree cover loss from wildfires increases, annual precipitation will decrease (negative correlation). There will be, at least, a medium correlation (>0.3)

This hypothesis is supported by the theory that hot and dry conditions, exacerbated by climate change, cause increased wildfires.

Calculations

For these variables (annual tree cover loss from wildfires (km2), mean annual temperature in degrees celsius (°C) and annual precipitation in millimetres (mm), all between 2001-2021), the following calculations will be utilised -

  • Trendline (r 2 ) - to notice trends in individual variables
  • Pearson product-moment coefficient (statistical test): to test correlation between mean annual temperature and annual precipitation, and tree cover loss from wildfires
  • Spearman’s rank-order correlation: similarly, to test correlation; however, Spearman’s can also assess monotonic (non-linear) correlations, and is less sensitive to outliers (Laerd Statistics, n.d.).

 

The value of r (correlation) ranges between -1 and 1, and the further this number is away from zero, the stronger the correlation is. As such, r = 1 would indicate a very strong positive correlation, and r = -1 would be a very strong negative correlation (University of Miami, n.d.).

 

Two tests for correlation are being used because it is not certain whether the data is monotonic or linear, and I would like to account for outliers by using Spearman’s.

 

Finally, outliers will be examined. Outliers will be pointed out and compared to other variables in those years.

Ethical Considerations

Since this IA relies on secondary data, reliable and authentic sources were used, correctly cited to avoid plagiarism. This IA has no environmental impacts.

Materials

The following materials were utilised to carry out this IA -

  • Laptop
  • Internet connection
  • Calculator
  • Google Sheets

Results, Analysis and Conclusion

Raw Data

YearAnnual tree cover loss from wildfires (km2)Annual precipitation (mm)Mean annual temperature (°C)
20011.04468.8417.13
20020.29524.6216.81
20030.25650.7917.01
20040.82567.6116.53
20050.08583.5916.31
20060.48495.1116.85
20072.0584.4616.96
20082.02433.3517.04
20091.45728.0716.9
20100.14585.017.0
20110.51533.3116.72
20121.26456.817.17
20135.37452.917.01
20142.26505.5917.24
20151.44555.1317.21
201612.7447.2317.29
201724.2357.2216.99
20186.13523.0717.32
20191.78469.6817.18
20202.05413.3917.17
202111.8515.4717.37

Figure 3 - Table on Table Of Annual Tree Cover Loss From Wildfires (km2), Annual Precipitation (MM), And Mean Temperatures (°C) From 2001 to 2021 In Sicily

Figure 4 - Graph Of Mean Annual Temperature (°C) In Sicily From 2001-2021

Figure 5 - Graph Of Annual Precipitation (MM) In Sicily From 2001-2021

Initial Analysis

Some initial correlations can be observed. Figure 3 demonstrates a climb in annual tree cover loss from wildfires. An increase in temperature is not as prominent in the stable line in Figure 4. Nonetheless, annual precipitation appears to be decreasing in Figure 5.

Trendlines

VariablesTrendline (r 2 )
Mean annual temperature (°C)0.408
Annual precipitation (mm)0.184
Annual tree cover loss from wildfires (km2)0.28

Figure 6 - Table On Variables And Their Associated Trendlines (r 2

The most statistically significant trendline is that of mean annual temperature. The conclusion can be drawn that mean annual temperature in Sicily is increasing. The trendline for annual precipitation is also significant, if weaker than the former. Nonetheless, warming of the planet by 1.5 °C would have catastrophic consequences (IPCC, 2021): even the small change observed can have great impacts on wildfires in Sicily.

 

It also appears that annual tree cover loss from wildfires has some statistical significance. It can be determined from these trendlines that wildfires in Sicily are gradually increasing.

Correlations

VariablesCorrelation (r)
Mean annual temperature (°C) and annual tree cover loss from wildfires (km2)0.3258
Annual precipitation (mm) and annual tree cover loss from wildfires (km2)-0.5146

Figure 7 - Table On Variables And Their Associated Pearson’s Product - Moment Correlations (r)

The correlation between mean annual temperature and annual tree cover loss from wildfires could be considered a medium strength positive correlation. This suggests that as the temperature of Sicily increases, so does annual tree cover loss from wildfires.

 

Mean annual temperature and annual tree cover loss from wildfires correlation have a strong negative correlation. It can be concluded therefore that as annual precipitation decreases, annual tree cover loss from wildfires increases in Sicily.

VariablesCorrelation (r)
Mean annual temperature (°C) and annual tree cover loss from wildfires (km2)0.64328
Annual precipitation (mm) and annual tree cover loss from wildfires (km2)-0.6090

Figure 8 - Table On Variables And Their Associated Spearman’s Rank-Order Correlations (r)