^{Photo courtesey of Chuliang Song}

Assistant professor Chuliang Song is one of two new faculty members to join the UCLA Department of Ecology and Evolutionary Biology this summer.

Song is a quantitative ecologist who studied mathematics as an undergraduate at Zhejiang University–in Hangzhou, China. He went on to develop his skills in quantitative ecology during his Ph.D. at MIT, then continued to refine his skills through his post-doctoral training at Princeton.

How did Song go from being focused solely on mathematics as an undergraduate to a career as a quantitative ecologist?  How might the quantitative frameworks he develops in his lab benefit conservation? Learn more about Song and his work in this Q&A.

How did your career path evolve from the time you were an undergraduate?

As an undergraduate in China, I focused on mathematics at Zhejiang University, the state university of my province. In my senior year, I had the opportunity to do an exchange program at Harvard Medical School, a year-long research internship where I learned to use statistical physics to study coexistence in microbial communities. Through this research I saw how math could be used to study nature. I was grateful for my advisor who patiently guided me through the intricacies of research and the cultural adjustments of living abroad. 

During the internship, my advisor brought me to an ecological research conference organized by a new research professor at MIT. This new professor spoke about ecology with such passion and infectious enthusiasm. After his talk, I started a conversation with him, which eventually led to an offer to start as a Ph.D. student in his lab. 

My advisor at MIT helped me learn about academia and research– how to go from a rough research idea to a publishable paper, and how to study ecological systems using math as a tool. I was hooked on research, wanting to decode the mysteries of ecosystems, species interactions and responses to change. 

Can you provide some insight into your work as a quantitative ecologist? 

As a quantitative ecologist, I use the power of math and statistics to unravel the complexities of ecosystems. I’m particularly fascinated by how different species manage to coexist, especially in the face of environmental change.

Imagine a meadow filled with wildflowers, buzzing with bees and butterflies. Each of these species depends on the others in a delicate balance. My work involves building mathematical models that can predict how resilient this community is to disturbances like climate change or habitat loss.

To do this, we analyze ‘motifs’—small, recurring patterns of interaction within the ecosystem. Think of them as the basic building blocks of the ecological network. For example, a motif might involve a plant that provides nectar to two different pollinators who then compete with each other. By studying the frequency of these beneficial, neutral, and harmful motifs, we can get a sense of the overall coexistence potentials of the ecosystem.

When we put our model to test, we see a strong correlation between our theoretical predictions and empirical reality. So our models can help conservationists prioritize their efforts. Instead of spending vast resources monitoring every single interaction in a complex ecosystem, we can identify the key species and relationships that are most critical for maintaining biodiversity.

Beyond coexistence, I’m also exploring how ecosystems behave over time, especially systems that are far from equilibrium, also how large-scale spatial patterns, like the distribution of different plant species across a landscape, influence ecological processes. I feel incredibly fortunate to be at UCLA, where I have the opportunity to collaborate with amazing colleagues and contribute to a deeper understanding of the natural world.

What role have mentors played in your career?

 I wouldn’t be where I am today without the guidance of some truly exceptional mentors, who are not only at the absolute top of their field, but also genuinely invested in nurturing the next generation of scientists. My mentors went above and beyond to provide me with support to develop my skills and invaluable advice, encouragement, and the occasional reality check. All my advisors made me feel like they care about me. And I really hope that I can pass this on and give my future students the same kind of support and encouragement.