Role of Ecological Disturbances in Global Carbon Cycling: Historical Baselines and Future Trajectories in Drylands

A Department of Computational Biology Seminar

Featuring Dr. Adam Pellegrini, Associate Professor, Department of Plant Sciences, University of Cambridge

The trajectory of climate change will partly depend on the responses of ecosystems to ongoing global changes in climate and land use because ecosystems play an important role in regulating greenhouse gas cycling. In particular, shifting frequencies and intensities of disturbances such as fires and herbivory are changing the capacity of ecosystems to store carbon. Yet management of these disturbances–either through restoration or prevention–offers an opportunity to reduce net greenhouse gas emissions that many governments and companies are employing to hit net-zero targets. My research talk will address how disturbances are changing carbon cycling in ecosystems by focusing on belowground pools of carbon in soil organic matter–the dominant carbon storage pool globally. Using a globally distributed fire manipulation network, I will first demonstrate that fires impact ecosystem carbon storage the most in drier ecosystems where plants are less able to recover in between disturbances. This higher sensitivity of drylands is underestimated by most global ecosystem models, and results in an unexpected carbon sink in dryland soils where fires are declining. Shifting gears, I will discuss how remote sensing of fires and vegetation recovery using millions of observations reveal that the size of fire is less important than the shapes of the burn patches within a fire in explaining trends in severity. Finally, I will show how statistical artifacts and spatial autocorrelation have led to inaccurate estimates of soil carbon sequestration from altered livestock grazing. In summary, this research talk both highlights progress in our understanding of how ecosystems may contribute to trends in climate change but also methodological challenges that should give us caution in overgeneralizing and prescribing solutions in real-world settings.