This is a question I have received quite frequently in recent weeks. Computer programming languages can be used to make scientific analysis much easier. This applies directly to environmental science because there is a wealth of data within the world of ecological studies. Coding offers a way for scientists to automate repetitive tasks using lines of code, and therefore freeing up time for other work. This can result in the creation of new software that can be utilized by scientists across disciplines.
Statistics and environmental science go hand in hand. Science experiments involve a natural order of determining a hypothesis, establishing test methods, collecting data, analyzing data, and drawing conclusions.
The data analysis portion is where statistical models are important. Oftentimes, scientists want to know whether the results of their experiments hold statistical significance. This means proving that the trends observed in data are not just a result of some sort of mistake in the experiment design or execution. Computer programming languages such as Python can help scientists execute the statistical analysis of data by writing code to analyze their data. Python packages like NumPy provide a basis for computational analysis and Python libraries like SciPy offer modules such as scipy.stats that offer the ability to perform hypothesis tests. These include T-Tests and Analysis of Variance (ANOVA) tests on numerical data and the Chi Square test for categorical data. Packages in R such as car offer a function for ANOVA tables, but R Studio itself includes functions such as t.test to analyze data. Programming languages offer packages for creating graphs and visuals to display analytical tests, such as Matplotlib in Python and ggplot2 in R.
Sections of environmental science, such as conservation biology, can benefit from programming because of different computer models. As a college student, the first software I was introduced to that was created specifically for use in conservation science was a population viability analysis (PVA) software called Vortex. Population viability measures the likelihood of a group of organisms to thrive or decline under a certain set of circumstances. The Vortex software allows users to adjust the circumstances for populations in areas such as genetic diversity, number of organisms, and mortality rate. I used the software in a classroom setting while studying in Peru, and I performed various tests to see what factors would be detrimental to the population of a theoretical species. This tool is one of many that can be of assistance for environmental science professionals who can use PVA to inform management decisions for threatened species.
Within the field of environmental science, computer programming can be a great advantage because it allows scientists to analyze data in efficient ways that can make everyday tasks easier. The utilization of programming languages and modeling software offers opportunities to put computers to use where humans would have otherwise performed repetitive tasks. This can provide scientists with more time to make discoveries and inform decisions to make the world a better place.