My foremost goal is to (1) get students comfortable working collaboratively on novel problems and (2) instill the excitement and some basic knowledge to pursue deeper, independent study. Foundational to achieving this are active, group-based learning and clearly connecting fundamental concepts with the classical studies and patterns in nature.
In computational ecology, many useful tools and insightful theories begin with specific biological questions. For this reason, I emphasize a firm familiarity with biological processes and data constraints in specific systems when students learn to apply or develop models. Among the things I would love to teach is an applied ecological theory course (syllabus PDF). My primer on how to write a fundamental research paper
How do I "get into" theory? I come from a field ecology background and developed a joy for math only after recognizing it as the language of logic and nature. Paying forward some of the best advice I received, I recommend biologists interested in doing theory to start from a system-specific biological question. This helps avoid the common pitfall of building complex models that are neither simple to understand and gain insights from nor have much to do with reality.
Once you have a specific question, I'd figure out a good model approach using texts and by reaching out to chat with other theoreticians (we're very friendly, love students, and love biology!). Some books I enjoy are: Dynamic Models in Biology (Ellner and Guckenheimer): great start for modeling Population Ecology (Hastings) Encyclopedia of Theoretical Ecology: great reference and overview Complex Population Dynamics (Turchin): fun overview of modeling time series Mathematical Models in Biology (Leah-Edelstein Keshet): thorough reference if you have some math background
My teaching: ECL 290 Scales in Ecology (2019), UC Davis Organized and led a seminar synthesizing research on scaling relationships and pattern formation in ecology.
ESP 121 Population Ecology (2018), UC Davis Introduced students to dynamical models and led computer labs in R.
WFC 122 Population Dynamics and Estimation (2015), UC Davis Introduced students to statistics and population models, led computer labs.
BIOEE 3610 Advanced Ecology (2013), Cornell University Helped lead labs in formulating and simulating population and community models.
Training - EDU390 College Teaching: hands-on study of theory, methods, assessment. NSF Graduate Research Fellowship seminar (2017): Co-led discussions and gave detailed weekly draft feedback to 14 applicants. R Workshop, UC Davis (2016): Helped introduce students to programming