Alpine Treeline Growth Variability: Simulation Using an Ecosystem Process Model

Abstract

Standard approaches in dendroclimatology used to determine climate-tree growth relationships at individual alpine treeline sites have primarily focused on empirically based statistical reconstructions. While such statistical relationships produce highly significant results, it is not possible to explore the underlying biophysiology in the links between climate and forest growth. Use of a deterministic forest ecosystem process model (FOREST-BGC) allows an evaluation of the impact of growing season and prior year meteorological conditions on phenological parameters such as net canopy photosynthesis (PSN) and net carbon gain (NETC). These variables were modeled over the course of a year and were statistically related to tree growth at an upper treeline site in the Sierra Nevada Mountains of California. The predicted growth increments over a 40-yr period exhibit trends similar to the measured variation in increment growth and perform better (R²_adj = 0.62) than regression models based on monthly/seasonal mean temperature and precipitation totals (R²_adj = 0.52). The standard principal component based approach, while producing results similar to the components identified in the forest ecosystem (FOREST-BGC) analysis, provided a better reconstruction of increment growth (R²_adj = 0.79). However, site- and species-specific tuning of the FOREST-BGC model could make this approach a viable alternative to standard response function analysis and potentially a valuable tool for pursuing a theoretically based explanation of treeline processes.