Forest fine-root production and nitrogen use under elevated CO2: contrasting responses in evergreen and deciduous trees explained by a common principle

Despite the importance of nitrogen (N) limitation of forest carbon (C) sequestration at rising atmospheric CO2 concentration, the mechanisms responsible are not well understood. To elucidate the interactive effects of elevated CO2 (eCO(2)) and soil N availability on forest productivity and C allocation, we hypothesized that (1) trees maximize fitness by allocating N and C to maximize their net growth and (2) that N uptake is controlled by soil N availability and root exploration for soil N. We tested this model using data collected in Free-Air CO2 Enrichment sites dominated by evergreen (Pinus taeda; Duke Forest) and deciduous [Liquidambar styraciflua; Oak Ridge National Laboratory (ORNL)] trees. The model explained 80-95% of variation in productivity and N-uptake data among eCO(2), N fertilization and control treatments over 6 years. The model explains why fine-root production increased, and why N uptake increased despite reduced soil N availability under eCO(2) at ORNL and Duke. In agreement with observations at other sites, the model predicts that soil N availability reduced below a critical level diminishes all eCO(2) responses. At Duke, a negative feedback between reduced soil N availability and N uptake prevented progressive reduction in soil N availability at eCO(2). At ORNL, soil N availability progressively decreased because it did not trigger reductions in N uptake; N uptake was maintained at ORNL through a large increase in the production of fast turnover fine roots. This implies that species with fast root turnover could be more prone to progressive N limitation of carbon sequestration in woody biomass than species with slow root turnover, such as evergreens. However, longer term data are necessary for a thorough evaluation of this hypothesis. The success of the model suggests that the principle of maximization of net growth to control growth and allocation could serve as a basis for simplification and generalization of larger scale forest and ecosystem models, for example by removing the need to specify parameters for relative foliage/stem/root allocation.