Fluvial processes strongly influence riparian forests through rapid and predictable shifts in dominant species, stand density, and tree size that occur in the decades following large floods. Modeling riparian forest characteristics based on the age and evolution of floodplains is useful in predicting forest biomass and carbon accumulation, wildlife habitat quality, and instream large wood volumes from rates of bank erosion and channel migration. We developed a dynamic model of riparian forest structure that predicts changes in tree size and density using floodplain age derived from air photos. Using a riparian field inventory and vegetation chronosequence for the 160-km middle reach of the Sacramento River (California, USA), we fit Weibull diameter distributions with time-varying parameters to the empirical data. Tree species were stratified into early and late successional groups, each with distinct functions of tree density and diameter distributions over time. From these relationships, we modeled how tree densities for all diameter classes changed throughout forest succession, and evaluated the goodness-of-fit of model predictions.
Results/Conclusions
Model outputs for the early successional species group, composed primarily of cottonwoods and willows, accounted for most of the stand basal area and large trees >10 cm DBH for the first 90 years. Post-pioneer species with slower growth and smaller maximum diameters had initially low densities that increased slowly from the time of floodplain creation. The early successional group contained more large trees later into the chronosequence that have the potential to influence fluvial processes, carbon storage. and instream habitat, relative to the late successional groups. We applied the model to evaluate the potential size and volume of large wood for the middle Sacramento River under historical bank migration rates. Going forward, this modeling approach can be used to predict how riparian forest structure and associated ecosystem benefits respond to different river management and restoration actions.