Lucash Lab

Our REsearch

Our planet faces immense challenges as rising temperatures, shifting disturbance regimes, and extreme events reshape our world. Inaction is not an option. Addressing these complex, "wicked" problems requires collaborative, interdisciplinary solutions.

In our lab, we employ a suite of cutting-edge tools—including big data analytics, spatially explicit simulation modeling, remote sensing, and artificial intelligence—to quantify vegetation dynamics, disturbance regimes, and carbon and nitrogen cycling across large spatial scales. Our research is often translational using visualization as the bridge between researchers and managers, because we deem it important to conduct applied research that is useful for managers. We thrive on interdisciplinary collaboration, particularly across diverse fields such as computer science, immersive technology, philosophy, and anthropology. Overall, our research is guided by the belief that only through a better understanding of the interactions between biological, chemical, geologic, and physical processes using multiple research methods will we identify the most effective strategies to help terrestrial ecosystems to adapt to changes in our climate and disturbance regimes, while mitigating changes in our climate.

Our research addresses critical questions such as:

1. Carbon Dynamics: How and when do terrestrial ecosystems transition from carbon sinks to carbon sources? What strategies can be implemented to prevent or delay this shift?

2. Species Dynamics: Will ecosystems be able to keep pace with climate change or will biome boundaries shift? Which tree species will be “winners” and “losers” under different scenarios of climate change?

3. Post-Disturbance Recovery: Which management strategies are most effective at promoting ecosystem resilience following wildfires? Do these strategies remain effective under climate change?

Our research focuses on developing effective strategies for managing forests and shrublands in the face of a changing climate. We leverage spatial datasets, like the Forest Inventory and Analysis (FIA) database developed by USDA Forest Service, to investigate how disturbances like wildfire shape current forest conditions. A significant component of our work involves spatial modeling, with Dr. Lucash serving as both a lead developer of the LANDIS-II model and the president of the LANDIS-II Foundation. LANDIS-II is the most widely used forest landscape model in the U.S., with a community of over 1,800 registered users publishing >220 papers. This powerful tool simulates forest succession and disturbances (e.g. fire, wind, and insect outbreaks) across spatial scales ranging from hundreds to millions of hectares and temporal scales spanning decades to centuries.

Our research takes place in many different ecosystems, including the coastal forests of OR, boreal forests of Alaska, boreal forests and alpine areas of Siberia, temperate rainforests of southeast Alaska, boreal and mixed hardwoods of MN and WI, sagebrush steppe of eastern Oregon, mixed coniferous forests in the Klamath Mountains of OR and CA, longleaf pine forests of NC, northern hardwoods of MA and NH, and the deciduous forests of UK.