Using the US National Forest Inventory to Model and Simulate Forest Dynamics, Composition, and Land Conversion

Abstract

Forests are dynamic ecosystems that are not only tied to important cultural beliefs but also provide essential ecosystem services including clean water, temperature regulation, wildlife habitat, and carbon storage. Carbon stored in forests corresponds to the largest terrestrial sink, representing a potential for managing forests for climate change mitigation. Forests are also in constant change and factors such as disturbances, land conversion, and climate change alter forest dynamics and threaten their ability to sustain their ecosystem services. Therefore, the study of forest dynamics is extremely important.This study contributes to understanding forest dynamics by exploring different tools and methods using the US National Forest Inventory to model, simulate, and explore relationships between forest composition, disturbances, and land conversion. Results showed that (1) Between 2000 and 2017, 3.4% of the analyzed Forest Inventory and Analysis (FIA) plots transitioned from forest to mixed or non-forested conditions. Results indicated that the change in land use from forests is more likely with increasing human population and housing growth rates. (2) Disturbances can be measured in different magnitudes and scales and the methods for quantifying these disturbances can significantly change results for stand productivity and carbon sequestration. (3) Utilizing individual tree variables may provide early disturbance detection that directly affects tree demographics and forest dynamics. (4) Landscape simulation models are a helpful tool to project forest dynamics and composition. Understanding the behavior of these landscape simulation models is critical and doing so at a site scale helps identify potential bias and areas of improvement. Overall, our results showed different applications to model and simulate forest dynamics that will be useful tools for land managers and policymakers for building prescriptions, reporting on greenhouse gas emissions and stand productivity, and building confidence towards the use of simulation models.