Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9

Abstract

Biological nitrogen fixation (BNF) by symbiotic and free-living bacteria is an important source of plant-available nitrogen (N) in terrestrial ecosystems supporting carbon (C) sequestration and food production worldwide. Dynamic global vegetation models (DGVMs) are frequently used to assess the N and C cycles under dynamic land use and climate. BNF plays an important role in the components of both these cycles, making a robust representation of the processes and variables that BNF depends on important to reduce uncertainty within the C and N cycles and improve the ability of DGVMs to project future ecosystem productivity, vegetation patterns or the land C sink. Still, BNF is often modelled as a function of net primary productivity or evapotranspiration, and the actual drivers are neglected. We implemented plant-functional-type-specific limitations for BNF dependent on soil temperature and soil water content, as well as a cost of BNF, in the Lund–Potsdam–Jena managed Land (LPJmL) DGVM and compared the new (“C-costly”) against the previous (“Original”) approach and data from the scientific literature. For our comparison, we simulated a potential natural vegetation scenario and one including anthropogenic land use for the period from 1901 to 2016 for which we evaluate BNF and legume crop yields. Our results show stronger agreement with BNF observations for the C-costly than the Original approach for natural vegetation and agricultural areas. The C-costly approach reduced the overestimation of BNF, especially in hot spots of legume crop production. Despite the reduced BNF in the C-costly approach, yields of legume crops were similar to the Original approach. While the net C and N balances were similar between the two approaches, the reduced BNF in the C-costly approach results in a slight underestimation of N losses from leaching, emissions and harvest compared to the values in the literature, supporting further investigation of the underlying reasons, such as processes represented in DGVMs and scenario assumptions. While we see the potential for further model development, for example, to separate symbiotic and free-living BNF, the C-costly approach is a major improvement over the simple Original approach because of the separate representation of important drivers and limiting factors of BNF, and the C-costly approach also improves the ability of LPJmL to project future C and N cycle dynamics.