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Francisco Rodríguez Sánchez shared with the R Consortium how the R language has changed and improved his work as a computational ecologist, leading him to become a passionate advocate, professional, and promoter of R, especially in the context of environmental causes.
Francisco is a scientist specializing in computational ecology who works at the intersection of various disciplines, such as ecology, biogeography, statistics, and data science. His research focuses on understanding and predicting the effects of climate change on biodiversity. To achieve this, he combines field observations with computational approaches that rely on analyzing large datasets, complex statistical models, and reproducible workflows. He is also interested in developing new quantitative methods and computer tools that facilitate reproducible research.
Besides his research, he also teaches ecology, statistics, and programming, playing an important role as a founding member and coordinator of two groups: the ‘R Users Group’ in Seville and the Ecoinformatics working group of Asociación Española de Ecología Terrestre (AEET), both with the objective of promoting good statistical and programming practices among ecologists.
Among his hobbies, he enjoys being in nature, listening to flamenco music and playing the guitar, spending time with friends and family, traveling, and reading.
How was the creation of Seville R carried out? Was it well accepted by the community? What were the challenges you faced during the pandemic?
It has been a wonderful experience, full of ups and downs as it happens in many groups. Our first meeting took place at a cocktail bar here in Seville, where we were given space. Approximately 15 to 20 people attended, which was quite good considering Seville has around 700,000 inhabitants. Most of the attendees were colleagues, but we also had people who discovered the event through Twitter or maybe through our blog. For several years, we gathered there with great interest and turnout. Among other great talks, we were lucky to have Karthik Ram from rOpenSci and Romain François from Posit (Rstudio), who came together in the first year of the group’s foundation. At that time, dplyr had just been released and quickly growing up, so we had the scoop on how it worked, and it was very impressive. Karthik also gave an amazing talk on the importance of reproducible research. The news spread and many people in Spain started to closely follow the Sevilla R Users Group.
We held monthly or quarterly meetings, attracting people from both academia and the private sector, until the pandemic hit, and everything came to a halt. The pandemic times were challenging, and we had only one or two online meetings. We highly valued the opportunity to physically gather in a place. Usually, after the talks, we would go to a bar for a drink and continue discussing projects and what we were doing. Online meetings are more distant and colder; they do not motivate us as much.
In the online mode, during the live broadcasts, there were very few people connected, and there were rarely any questions. It was not so easy to achieve that sense of community. That is why we decided to stop the online meetings since we were all busy and did not enjoy that format as much. We were on pause for a while, but fortunately, we have resumed in-person meetings. Thanks to the addition of new people with a lot of energy and initiative, we are now quite active, and everything is going very well.
What’s your level of experience with the R language?
I am not a professional programmer, but I am self-taught. However, I dedicate a significant amount of time to learning and enjoying programming, as it is very useful for my work and helps me solve many of my problems. Over time, I have acquired intermediate to advanced-level knowledge through self-teaching. Although I am not a professional programmer and there are still many things that elude me, I consider myself quite competent in R. In my community, people usually come to me when they have programming or analysis problems; they know me as “Paco, the R guy.”
Please share about a project you are currently working on or have worked on in the past using the R language.
I use R mostly for teaching or developing research projects, but I have also developed several packages. One of the most recent is called CityShadeMapper. We worked on it last year, and we are currently in the final phase. This package, available on my GitHub, is used to create shadow maps in urban environments. Basically, it works as follows: LIDAR (Light Detection and Ranging) data, which are remote sensing technologies that accurately measure terrain heights, are downloaded from various sources. Many countries offer this data for free, so it can be downloaded from the internet. CityShadeMapper takes this remote sensing data and generates high-resolution shadow maps, at a one-meter level, for every hour of the day and throughout the year.
In other words, with this package, we can obtain detailed information about shadow intensity or lighting in every square meter of a city, both on building rooftops and at street level where pedestrians and cyclists are. It is important to highlight that CityShadeMapper utilizes infrastructure from other essential packages for its operation, but integrates them in a way that any user, citizen, or municipal administrator can easily generate shadow maps.
This tool is particularly useful in the context of climate change, as it allows us to identify areas with a lack of shade, which leads to high temperatures. I live in Seville, a very hot city in summer, and every year we face the issue and debate about the lack of shade. That is why developing this package has been a goal for us for years, as we believe it can be very useful. In fact, I know that some municipalities are already using it to improve urban planning and address the problem of shade deficiency. The CityShadeMapper package excites us a lot because we consider it a fundamental tool for climate change adaptation, not only in the Mediterranean but also in other parts of the world.
What was the objective and outcome of this project?
The project is still incomplete, there is a missing functionality that is in the prototype stage: the creation of shadow routes. These shadow routes work like Google Maps or a map service, but instead of taking the user on the shortest path, they guide you along a route that maximizes shade. In this way, you can walk through cooler areas during the summer and avoid the heat. Currently, we are working on finalizing this part of the project; it is something we have pending. We plan to start next month with tutorials and workshops for those interested in learning how to use it. We will publish all the information online. There is still more outreach needed, but I am confident that it will be useful, as several people have contacted me expressing their interest in starting to use it.
Would you like to mention something interesting about the R language especially related to the industry you work in?
Currently, I hold the position of university professor and researcher in ecology, and R has become by large the dominant language in our field. Therefore, it has become indispensable for research, both for doctoral students and researchers, who are learning and using it to carry out their work.
Furthermore, in the realm of teaching, I have always felt a great interest. Although I did not learn R through formal education and had to learn it on my own, I am passionate about teaching and how to provide effective instruction in programming and data analysis to individuals who are not programmers or computer scientists, who have no prior experience with code, and who may feel some fear or apprehension towards programming. However, once they start working with R, they usually love it and realize that they can acquire skills quickly. Therefore, both in teaching and research, R has become an invaluable tool.
As mentioned earlier, I also use R in all aspects of my work, whether it be creating graphics, designing slides for my classes, or preparing presentations. In summary, R is a versatile tool that I use in all stages of my academic work.
How well accepted is R in your community?
In my experience, most people get excited and really enjoy using R once they start using it. It is true that they may encounter difficulties at first, as it is their first time dealing with code, and they may feel some frustration with things like commas or typographical errors. However, in just a few hours, they usually perceive its potential and, despite the initial challenges, they become motivated to learn and explore all the possibilities that the language offers. In my role as a teacher, I teach both programming and data analysis, and I have observed that the R language, thanks to its design and the freely available teaching resources on the internet and in books, facilitates the progress and advancement of those who are starting out.
The R language is relatively easy to grasp, especially for those taking their first steps. However, when it comes to statistics and data analysis, I believe the complexity increases and more insecurities arise, requiring greater effort. Despite that, in general, the R language is very well received. In fact, there is a growing demand from students for R to be used in many universities, as they recognize its great potential.
That being said, I believe it is important to use teaching techniques that facilitate the first steps in R, especially for non-programmers. Teaching R to a computer scientist who is not afraid to open a terminal and start programming is different from teaching it to a biologist who has never written code. Therefore, I think it is essential to approach those first steps in a pedagogical way so that they can truly perceive the potential and make progress without feeling too frustrated. In my experience, the reception of R has been excellent.
What resources do you use?
I started using Posit (RStudio) since it came out on the market. I was very attentive to RBloggers and also followed the updates on Twitter. When I saw that RStudio was released, I decided to give it a try and was delighted with its functionality. Previously, I used a program called Tinn-R, but since I tried RStudio, I liked it so much that I continue to use it as my main working tool.
I also used Visual Studio for a few years, but currently, RStudio is my primary choice. In 2012, I started using GitHub. I discovered its usefulness on the internet, although it took me some time to learn how to use it fluently. Since then, I have been using it almost daily.
I became a big fan of RMarkdown many years ago and use it to create class slides, presentations, and to write papers, scientific articles, and theses. We have been using RMarkdown for years. Recently, we have also started using Quarto.
As for Tidyverse, I also use it extensively. I do not consider myself an expert in Tidyverse, as it is a broad and constantly evolving ecosystem, making it challenging to stay fully updated. However, I am in love with dplyr and dbplyr as they offer a lot of functionality for working with databases. I believe they have great potential and work excellently. Of course, I also make use of the entire ggplot ecosystem.
What would you say to anyone interested in learning R?
I would like to make a special invitation to include the teaching of programming languages to biology and environmental sciences students, as I consider it highly beneficial. Learning R provides students with numerous opportunities and opens many doors for them. Additionally, I would like to extend an invitation to everyone in Sevilla to get in touch with the Sevilla R group. We are delighted to welcome new people and share our knowledge.
Lastly, I would like to express my deep gratitude to the R Consortium for their ongoing support to local groups over the years. In Sevilla, our group has received various forms of support that have been extremely valuable in maintaining and strengthening these local communities, which I consider vital in energizing the R community as a whole. Our sincere appreciation for all the support provided.
Francisco was also interviewed in 2022, read more.
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The post Bridging Ecology, Statistics, and Data Science with R for Biodiversity and Climate Change Research appeared first on R Consortium.
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