ALPINE TREELINE GROWTH VARIABILITY - SIMULATION USING AN ECOSYSTEM PROCESS MODEL

Standard approaches in dendroclimatology used to determine climate-tre e growth relationships at individual alpine treeline sites have primar ily focused on empirically based statistical reconstructions. While su ch statistical relationships produce highly significant results, it is not possible to explore the underlying biophysiology in the links bet ween climate and forest growth. Use of a deterministic forest ecosyste m process model (FOREST-BGC) allows an evaluation of the impact of gro wing season and prior year meteorological conditions on phenological p arameters such as net canopy photosynthesis (PSN) and net carbon gain (NETC). These variables were modeled over the course of a year and wer e statistically related to tree growth at an upper treeline site in th e Sierra Nevada Mountains of California. The predicted growth incremen ts over a 40-yr period exhibit trends similar to the measured variatio n in increment growth and perform better (R(adj)2 = 0.62) than regress ion models based on monthly/seasonal mean temperature and precipitatio n totals (R(adj)2 = 0.52). The standard principal component based appr oach, while producing results similar to the components identified in the forest ecosystem (FOREST-BGC) analysis, provided a better reconstr uction of increment growth (R(adj)2 = 0.79). However, site- and specie s-specific tuning of the FOREST-BGC model could make this approach a v iable alternative to standard response function analysis and potential ly a valuable tool for pursuing a theoretically based explanation of t reeline processes.