Disturbance, Fine-Scale Environment, and Forest Change in Great Smoky Mountains National Park

Tuttle, Julie

ABSTRACT: When Great Smoky Mountains National Park (GRSM) was protected in the 1930s, approximately 20% of the landscape was old-growth forest, the remainder second-growth forest recovering from logging, settlement, and other land use. Despite protection, indirect human disturbances have continued to influence change in this diverse landscape. I use vegetation datasets from the 1930s and 1990s-2000s to investigate changes in forest structure and composition (Chapter 1) and tree species distributions (Chapter 3) with respect to environmental gradients, disturbance history, and species functional groups. The influence of complex topography on fine-scale patterns of soil moisture has not previously been quantified for GRSM. Here, I present a fine-scale empirical model of soil moisture (Chapter 2). In Chapter 1, I show how disturbance history interacts with environmental gradients to structure southern Appalachian forests. Historical disturbances have remained important as predictors of forest structure and composition, although their importance has decreased relative to topography since the 1930s. Structural comparison of vegetation plots matched by environmental conditions reveals widespread change, reﬂecting disturbance history and successional processes. Chapter 2 presents an empirical model of fine-scale soil moisture for GRSM, structured hierarchically to account for nested effects of climate and topography operating at different spatial scales. Fine-scale soil moisture is influenced by differences in growing-season precipitation at the regional scale, site position within the landform context at the watershed scale, and site topography at the local scale. Soil moisture is buffered above an elevation threshold in this model, likely a result of cloud immersion and lower temperature that produce additional moisture inputs and reduced evapotranspiration at higher elevation. In Chapter 3, I use hierarchical Bayesian species distribution modeling to investigate change in GRSM tree species distributions with respect to three drivers of global change: major disturbance, climate change, and fire suppression. In aggregate, species’ optima on the elevation and topographic moisture gradients shifted to lower, drier sites. Patterns of species response suggest the influence of all three drivers of change, although major disturbance may explain changes not explained by climate change or fire suppression. Future work should address multiple stressors and interaction among drivers of change.