My primary research interests is plants and how the biosphere has evolved through Earth's history. Originally, I was schooled in Earth Sciences and Geology with a special focus on Paleobiology. But through time my interests broadened from paleobotany to modern plant functional ecology, adaptation, and ecophysiology. My work constitutes a combination of field methods, lab techniques, and computational / statistical analyses. As a geologist, I am particularly fond of fieldwork, but the reality is that the skills that I use the most in my research can best be described as big data analytics applied to paleobotany and terrestrial paleoclimate. 

Plants represent the ideal window into the ancient world. Since plants are sessile organisms, their morphology and physiology needs to be fine-tuned to the environment they live in. Abiotic selective pressure is high in plants and as such, we see convergent evolutionary strategies in many traits reflective of the environment. These convergent evolutionary strategies are apparently stable through time, which means that fossil plants can provide key insights into long-lost ancient environments. 

My focus is on everything pre-Quaternary, with a special place in my heart for the Triassic period, since this was my gateway drug into paleo-ecology and paleobotany. My PhD research on the other hand was on reconstructing paleoclimate of the Miocene in New Zealand. Since then, there hasn't been a single epoch of the Cenozoic era, or period of the Mesozoic era, that I haven't worked on! I have used fossil plants to reconstruct a wide array of paleoclimate variables, including carbon dioxide levels, temperature, seasonality, and precipitation. I am especially interested in "extinct" climates — the combination of climatic variables that cannot co-exist in the modern world — since these climates are the most interesting puzzles, but may represent the closest analog to future climates

The foremost analytical technique I developed is a probability-based quantitative paleoclimate reconstruction technique based on the distribution of the nearest living relatives of plants in a fossil assemblage. Simply put: this technique calculates the most likely climatic interval at which all of the plant groups in the assemblage can co-occur. My approach builds on older nearest living relative-based techniques in three key ways: 1) the data is reproducible, as the occurrence data used is derived from publicly available continuously updated metadata, 2) the calculated interval considers all climatic parameters together, rather than separate, and 3) the technique is fully quantitative and probability-based; no subjectivity involved. Any researcher should be able to reproduce this technique in R following the instructions in the papers where I applied it, for example this one. However, I have, at this stage vetted and filtered the modern distributions of >1,000 plant groups. This is probably the most time-consuming part of nearest living relative-based paleoclimate reconstructions and I will add that the analysis is quite sensitive to distribution bias. Therefore, if you'd like me to use my database of vetted plant distributions, or simply like me to run an analysis, feel free to reach out! I'm sure one day I'll get around to publishing that database...