Dynamic nitrogen resorption improves predictions of nitrogen cycling responses to global change in a next generation ecosystem model

Abstract

Nutrient resorption from senescing leaves can significantly affect plant nutrient status and growth, making it an important process for carbon-cycle predictions for land surface models (LSMs). Based on a recent analysis of global nutrient resorption patterns from trait data, we develop a dynamic scheme of nitrogen (N) resorption driven by leaf structural and environmental factors and test its effect on present-day global simulations for woody plant functional types (PFTs) using the QUINCY biosphere model. Consistent with observations, we predict higher N resorption for deciduous PFT compared to evergreens, while reproducing the global gradient of decrease in resorption with key environmental drivers such as air temperature. As a result, the novel scheme increases N resorption in N-limited plants, enhancing stored N for the subsequent year and reducing their internal N limitation. This has cascading implications for ecosystem nutrient pools, plant productivity and, to a small extent, the response of carbon and N cycling to elevated CO2. The new scheme contributes to the development of an ecologically realistic representation of nutrient resorption in an LSM, with implications for both present day and future nitrogen limitation of the terrestrial biosphere.