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Publication Date
11 July 2019

Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking



Over the past several decades, the land modeling community has recognized the importance of nutrient regulation on the global terrestrial carbon cycle. Implementations of nutrient limitation in land models are diverse, varying from applying simple empirical down‐regulation of potential gross primary productivity under nutrient deficit conditions to more mechanistic treatments. In this study, we introduce a new approach to model multinutrient (nitrogen [N] and phosphorus [P]) limitations in the Energy Exascale Earth System Model (E3SM) Land Model version 1 (ELMv1‐ECA). The development is grounded on (1) advances in representing multiple‐consumer, multiple‐nutrient competition; (2) a generic dynamic allocation scheme based on water, N, P, and light availability; (3) flexible plant CNP stoichiometry; (4) prognostic treatment of N and P constraints on several carbon cycle processes; and (5) global data sets of plant physiological traits. Through benchmarking the model against best knowledge of global plant and soil carbon pools and fluxes, we show that our implementation of nutrient constraints on the present‐day carbon cycle is robust at the global scale. Compared with predecessor versions, ELMv1‐ECA better predicts global‐scale gross primary productivity, ecosystem respiration, leaf area index, vegetation biomass, soil carbon stocks, evapotranspiration, N2O emissions, and NO3‐ leaching. Factorial experiments indicate that representing the phosphorus cycle improves modeled carbon fluxes, while considering dynamic allocation improves modeled carbon stock density. We also highlight the value of using the International Land Model Benchmarking (ILAMB) package to evaluate and document performance during model development.
“Representing Nitrogen, Phosphorus, And Carbon Interactions In The E3Sm Land Model: Development And Global Benchmarking ”. 2019. Journal Of Advances In Modeling Earth Systems. doi:10.1029/2018ms001571.
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