Investigating old-growth ponderosa pine physiology using tree-rings, δ¹³ C, δ¹⁸ O, and a process-based model

In dealing with predicted changes in environmental conditions outside those experienced today, forest managers and researchers rely on process-based models to inform physiological processes and predict future forest growth responses. The carbon and oxygen isotope ratios of tree-ring cellulose (δ¹³ C_cell , δ¹⁸ O_cell ) reveal long-term, integrated physiological responses to environmental conditions. We incorporated a submodel of δ¹⁸ O_cell into the widely used Physiological Principles in Predicting Growth (3-PG) model for the first time, to complement a recently added δ¹³ C_cell submodel. We parameterized the model using previously reported stand characteristics and long-term trajectories of tree-ring growth, δ¹³ C_cell , and δ¹⁸ O_cell collected from the Metolius AmeriFlux site in central Oregon (upland trees). We then applied the parameterized model to a nearby set of riparian trees to investigate the physiological drivers of differences in observed basal area increment (BAI) and δ¹³ C_cell trajectories between upland and riparian trees. The model showed that greater available soil water and maximum canopy conductance likely explain the greater observed BAI and lower δ¹³ C_cell of riparian trees. Unexpectedly, both observed and simulated δ¹⁸ O_cell trajectories did not differ between the upland and riparian trees, likely due to similar δ¹⁸ O of source water isotope composition. The δ¹⁸ O_cell submodel with a Peclet effect improved model estimates of δ¹⁸ O_cell because its calculation utilizes 3-PG growth and allocation processes. Because simulated stand-level transpiration (E) is used in the δ¹⁸ O submodel, aspects of leaf-level anatomy such as the effective path length for transport of water from the xylem to the sites of evaporation could be estimated.