I have experience in a variety of academic disciplines. I have worked explicitly on learning and studying interdisciplinary processes in environmental science, as well as working at the interface between statistical modeling and ecology. I also have experience in seismology and condensed matter physics. I currently work on complex social-ecological system management and critical studies of participatory data science.
Current Research Directions
My broad research interests are to understand long-term change in complex social-ecological systems, as well as understanding how participatory data science functions to counteract injustice. Feedbacks between different parts and scales of complex systems can lead to emergent, unexpected behaviors, and latencies can lead to delayed reactions in one or more components of the system, sometimes leading to tipping points where the entire system flips to a different (and potentially undesirable) stable state which is hard to reverse.
In particular, I am interested in understanding how human modification of the environment affects the sustainability of keystone species and functional groups, as well as how these changes in turn impact the humans who are a part of the system. Changes in these species and groups can often be subtle and hard to detect over short time scales, and systems can reach tipping points suddenly, with unexpected losses in ecosystem function and biodiversity. My focus is on methodologies for modeling and understanding the temporal dynamics of these systems, especially using re-purposed pre-existing long-term data. My hope is to use this legacy data to better predict system shifts.
At the same time, many environmental problems have a component of injustice and I seek to explore how participatory data science using these long-term datasets (as well as other community-generated datasets) might be used to further environmental justice. Re-purposing data for better understanding of complex systems and trusting data science in general to improve democracy are both assumptions that require testing, so while I use these methods to better understand complex systems dynamics, I also apply critical social science approaches to investigate whether and how they result in better knowledge and equity.
Reflections on Disciplinary Perspectives
I find that physics gives me both an excellent background in mathematics and computation as well as an appreciation for fundamental underlying processes. My background in geology gives me a sense of “deep time” (time scales much longer than human lifespans or observation periods) and the ability to infer process from pattern (that is, guessing at the forces that shaped a landscape from looking at the results). In statistics, I found the explicit treatment of variation both helps to model non-identical objects (individual lions or trees have differences which may be important in understanding them, as opposed to carbon atoms or electrons), and also helps to model our observation or measurement processes, improving our calculations about the process of interest. And sometimes the variation is the interesting part in a system! Ecology’s emphasis on interactions between organisms of the same and different species and their interactions with their environments gives me a way to view complex interconnected systems, which I expand to my study of social-ecological systems. The combination of complex systems theory and the applied practice of adaptive management gives me an interest in and sensitivity to feedbacks and latencies in systems and the need to iteratively observe and intervene. Feminist Science and Technology Studies has provided ways to understand objectivity which are consistent with my own lived experience in doing model-heavy science, as well as being comforting as a way to proceed with an imperfect but very useful set of quantitative methods. All these abilities come together in the study of complex social-ecological systems, which requires sophisticated statistics, understanding of underlying mechanisms, appreciation of long-term changes, and accounting of human influences.