Stand to landscape level ANPP: Using tree-cores and disturbances to model forest growth patterns

Background/Question/Methods

In conifer forests of the Sierra Nevada, climatic variables have been shown to be a major factor influencing tree growth and annual net primary productivity (ANPP). The effects of drought events on tree growth and ANPP can be compounded by biotic factors. Understanding the contribution of each of these influences on growth and regeneration requires information at multiple spatial scales and is essential for understanding regional forest response to changing climatic conditions. Our objectives were to 1) quantify stand- and landscape-level ANPP through both tree-core (empirical) data and an existing landscape scale model in the Lake Tahoe Basin, CA, NV 2) scale empirical data to provide an estimate for validation of modeled forest growth, and 3) evaluate to what extent the landscape disturbance and succession model is accurately capturing the dynamics of the system, as influenced by drought and bark beetle outbreaks relative to empirical estimates for a 20 year period (1987-2006). Tree ring data were acquired from 21 sites across the Lake Tahoe Basin. The Landscape Disturbance and Succession model, LANDIS-II, was used to model ANPP across the Basin; 4 model scenarios were constructed in order to test the influence of drought sensitivity and disturbance impacts to basin-wide ANPP.

Results/Conclusions

Variability within the tree ring data was captured well within modeled ANPP, which suggests that the underlying system dynamics that determine tree growth are well represented. As a measure of regional drought, PDSI was a useful index and helped identify periods of expected model and empirical ANPP reduction, though in certain years total winter precipitation was more closely associated with observed growth than PDSI. With regards to disturbance, simulating the combined impacts of moderate drought sensitivity and bark beetle outbreak provides the best approximation of the empirical data.