A mechanistic framework for order-specific fine-root turnover and carbon dynamics: application to the Duke forest...

Accurate quantification of fine-root turnover, a pathway representing a large and uncertain flux of carbon into soils, is critical for improving terrestrial ecosystem models. Efforts to model this carbon flux directly have relied on tracing stable carbon isotopes through root systems, and these studies reveal complex dynamics in sampled fine roots, best described to date by two-rate models. The rates derived from these models have been traditionally interpreted either as two distinct turnover rates (fast and slow), or as movement through two distinct biochemical pools (labile, recently fixed carbon and recalcitrant carbon consisting of complex polymers like lignin). However, a competing, mechanistic explanation exists: the observed two-rate dynamics may reflect the demography of the root system, where roots of different functional classes (e.g., defined by root order) inherently possess differential lifespans and turnover rates. Here we introduce a new model, the demographic carbon distribution model (DCDM) that models both the carbon flux into root systems and the demography of fine roots. We then fit each of these models to $\delta ^{13}$C values obtained from loblolly (Pinus taeda L.) fine roots. The DCDM model predicts that root turnover is substantially faster than has been previously reported. Pairing this model with data on fine roots assayed by root order, we were able to obtain estimates of fine-root turnover for different functional groups of roots. Furthermore, sampling individual roots highlights the importance of variation in root turnover estimates, indicating that mean behavior alone is insufficient to capture complex root dynamics. Because terrestrial carbon models depend on estimates of root turnover, we demonstrate how the estimates obtained here could impact predictions from ecosystem models.