Subalpine forests of the Northern Rocky Mountains in the 21st century:
Western North America is experiencing warmer temperatures and larger, more severe wildfires than at anytime in recorded history. Current analyses suggest the emergence of novel fire regimes during the 21st century, with profound consequences for forest resilience, defined as the ability of a system to tolerate disturbance without shifting to a qualitatively different state. Biological communities are often well adapted to the particular disturbances and climatic variation that are common in their environment. However, abrupt change in ecosystem structure and function can be caused by novel disturbance regimes and climates. Determining whether and how climate-disturbance interactions will push regional vegetation into alternative states is difficult for long-lived organisms like trees. Few studies have explored forest transitions at local and regional scales or elucidated mechanisms underpinning such shifts. Although resilience theory is well developed, how to operationalize the theory in real landscapes is unclear, especially in a no-analog climate of the future. Changes to climate and disturbance pattern will substantively influence forest landscapes, potentially disrupting feedbacks that confer resilience and triggering conversion of forest ecosystems to grasslands or shrublands.
In this context, we focus on the ability of trees to regenerate following high-severity fire, as that is necessary for forest resilience to be sustained. We are asking: how and why might warming climate and changing fire regimes (altered fire frequency, size, severity) push forest stands over a tipping point, such that tree regeneration fails? Where and when might projected changes in climate and fire activity erode local, landscape and regional forest resilience? How do stand and landscape indicators of resilience scale to the region, and what geographical areas are most likely to be vulnerable to changing drivers? We are developing and calibrating stand-to-region process-based models; exploring combinations of climate, fire, forest type, and spatial context on forest dynamics using downscaled historical and projected climate data; testing model predictions against our own extensive field data as well as regional databases (e.g., USFS FIA data); and evaluating metrics of resilience with process models and data.