Field Inclusive, Inc.

Experience Reflection: Nathália Susin Streher

“Thus, the efforts made by Field inclusive, along with its partners and sponsors, benefit not only individuals like me but also have the potential to create broader impacts, enhancing our understanding of nature’s intricate interactions.”

BY Nathália Susin Streher

Thanks to Field Inclusive, which awarded me the Summer 2025 Travel Award, I had the delight of participating in the workshop “Integrating Theory and Data in Plant-Pollinator Interactions”. As a significant bonus, this opportunity also allowed me to fulfill one of my academic dreams of visiting the Rocky Mountain Biological Laboratory, where the course took place.

I’m currently a postdoc at the University of Pittsburgh, but I’m originally from Brazil, where I got my Master’s and PhD in Plant Biology from the University of Campinas. My academic training back in Brazil was heavily rooted in natural history and plant taxonomy, equipping me with key skills to study plant-pollinator interactions. However, it did not focus as much on data analysis, which I’ve been trying to catch up on since (and I’m glad to say that I have been making successful progress). I’m particularly interested in understanding the drivers and consequences of pollinator sharing on community structure and assembly. What fascinates me about studying plant communities is the intricate nature of life. Plants often flower simultaneously with other plants and can use the same pollinators available in the area to transport their pollen grains. Thus, the presence of one species can influence the reproductive success of others, shaping the dynamics of plant communities. Studying interactions per se is already challenging, and it can become even trickier when more species are involved, as in the highly biodiverse ecosystems that I study. The beauty of ecological networks is that they can be a powerful tool to analyze entire systems and make sense of these many interactions. I was particularly interested in attending this workshop to deepen my understanding of plant-pollinator networks and to enhance my mathematical and modeling skills.

To be honest, mathematics and I were never close friends. Growing up, I always struggled with numbers and recalling math facts. And even with a lot of tutoring, I wasn’t able to “fix” it, which resulted in math anxiety that haunts me to this day. It was only when I had my first middle-school student with a learning difference that I realized the activities I was adapting for her were also somehow making more sense to me- even though I was the one creating them. Learning that my (now known to be dyscalculic and dyslexic) brain processes information slightly differently was a game-changer for me to stop feeling “dumb” and gain control of my learning process. Since mathematical theory underpins most ecological theory, I consider delving into it essential for me as a pollination ecologist. Attending this workshop was a step toward addressing the lack of inclusive training and the gender bias I faced while trying to learn quantitative methods as a student. I knew that going over topics that are exhausting for me would be easier in a place surrounded by mountains, especially while being instructed by researchers I deeply admire- and I was right.

There were several aspects of the accessibility implemented in this workshop that I truly appreciated. For instance, I really liked that instructors provided the material we would be covering ahead of time, which is incredibly helpful for people who struggle with math. Reviewing the material before the lessons helps you prepare for what’s coming, relieving much of the anxiety that comes when you see an equation. I also appreciated the several small breaks planned between topics to give our brains a moment to recharge, helping to avoid cognitive overload. All equations we learned/reviewed began simply, gradually increased in complexity, and were always grounded in biological applicability. Numerical simulations in R helped reinforce our understanding and connect theory to biological data. The only aspect I found difficult to follow was the parameter symbols used in the equations. I had anticipated this challenge since I knew I was gonna be learning this in my second language. However, my main struggle was more related to the increasing complexity of the equations throughout the workshop. With this, I had a hard time remembering what each letter represented, which is a common issue for individuals with weaker working memory, like myself. Going back into my notes took time and would make me fall behind the professor’s teaching pace. A simple modification that could have been beneficial to me would be to display or write on the board what each letter represented, or provide basic cheat sheets. I mention all of these because inclusive teaching strategies benefit all students, and I want to encourage others to learn more about and adopt them. I also want to emphasize, as the instructors mentioned in the workshop, that repeated exposure and practice to math theory is likely the most effective way to tackle the challenges of learning it. Thus, it is my job (or anyone who needs/wants to learn it) to make an effort to stay engaged and interested. As a hands-on learner, I found this workshop to be the perfect environment to build the skills I was looking for in an interactive and supportive setting. While the instructors set the tone with accessible teaching, the diverse group of attendees, with people from different backgrounds, nationalities, and career stages, made the space inclusive and enriching for everyone.

“What does data-theory integration mean to you?” That was the question we, the participants, were teased with from the very beginning. From there, the instructors explored metrics of network structure and their implications for community dynamics, discussed approaches to comparing ecological networks, and taught statistical methods that integrate empirical observations with mechanistic models. All of this helped us understand why and how to merge empirical data with theoretical frameworks. I am grateful for the skills I gained from this workshop, as they will allow me to conduct more comprehensive and impactful research on plant-pollinator interactions. This experience has been particularly valuable as I begin to shape the research plan I intend to develop once I have my own lab. The workshop emphasized the importance of long-term field data, especially when it comes to understanding how species interactions respond to ecological disturbances. This message resonated even more given the location we were in: the Rocky Mountain Biological Laboratory- one of the oldest active field stations in the US, and home to both seminal and long-term studies on plant-pollinator interactions. Getting to know this place truly felt like a dream come true for me, as I had read so much about it and its research since back when I was a student in Brazil.

We wrapped up the workshop with a group discussion revisiting the question we started with, now through the lens of the knowledge we acquired during these days together. Accessibility, equity issues, and geographical biases were identified as significant challenges in integrating data and theory when studying plant-pollinator interactions. Thus, the efforts made by Field inclusive, along with its partners and sponsors, benefit not only individuals like me but also have the potential to create broader impacts, enhancing our understanding of nature’s intricate interactions. I met wonderful people in this course, and I’m incredibly grateful for the opportunity to network with these amazing attendees and instructors. I hope to collaborate with them in the future and share the knowledge I have gained with other underrepresented scientists. As an international postdoc facing limited funding opportunities in the US, Field Inclusive was the crucial support that made this experience possible. Long live Field Inclusive and our shared cause!