Ecological trade-offs between leaf structure and plant nutrient demand to predict nutrient resorption in a terrestrial biosphere model

Nutrient resorption from senescing leaves is a critical process of plant nutrient cycling that can significantly affect plant nutrient status and growth, making it essential for land surface models in order to predict long-term primary productivity. Most models assume leaf resorption to be a fixed value of 50% for N and P partially because we lack the knowledge of what drives this process, being unknown its implications when simulating nutrient cycling. Based on our own analysis of global patterns of nutrient resorption from trait data, we developed a dynamic scheme of nutrient resorption for nitrogen and phosphorus driven by leaf structure, longevity and environmental factors, to be implemented in the QUINCY model. We present the concept behind this novel scheme through ecophysiological traits trade-offs, as well as first implications for ecosystem functioning. We show that we can better predict plant and soil nutrient dynamics at steady state and crucially, under altered climate and CO2 conditions. Plant internal nutrient cycling has cascading implications for ecosystem nutrient pools and fluxes, being an essential process in ecosystem models, that allows us to improve our predictions of the future and furthers our understanding of nutrient cycling processes.