Nitrogen Limitation Reduces Co2 Emissions from Land Use Change Primarily by Decreasing Co2 and Climate Interactions

Abstract

Estimates of CO2 emissions from land-use change strongly influence the inferred land carbon sink but remain highly uncertain. One key source of this uncertainty is nitrogen (N) limitation and its interactions with climate and CO2 emissions from land-use change. In this study, we developed and implemented a land-use change scheme into the Australian Community Atmosphere Biosphere Land Exchange model (CABLE) and conducted simulations using a full factorial design combining changes in land use, climate, and atmospheric CO2, both with and without nitrogen limitation. Benchmarking showed that CABLE with nitrogen limitation effectively simulates global gross primary production (GPP), soil respiration, plant biomass, and soil carbon, with correlation coefficients from 0.6 to 0.9. From 1960 to 2020, estimated cumulative CO2 emissions from land-use change were 119 Pg C without nitrogen limitation and 73 Pg C with nitrogen limitation, compared to 100 ± 35 Pg C from 20 dynamic global vegetation models and 87±24 Pg C from three bookkeeping approaches reported in the Global Carbon Budget 2023. We further partitioned total emissions into direct emissions from land-use change and indirect emissions arising from interactions with climate, nitrogen deposition, and atmospheric CO2. Nitrogen limitation reduced global direct CO2 emissions from land-use change by 0.12 Pg C/yr and indirect emissions by 0.24 Pg C/yr during 1701–1959, and by 0.4 Pg C/yr for both emissions during 1960–2020. The primary mechanism was a reduction in soil carbon inherited from lands when converted to secondary forests, while reduced regrowth of secondary forests contributed less than 25% of the total reduction. In addition, nitrogen limitation had the strongest effect on the interaction between land-use change and atmospheric CO2. Therefore, accounting for nitrogen limitation in both direct and indirect emissions from land-use change is critical for understanding emission drivers, improving model accuracy, and informing climate policy.

Keywords: Land use change, nitrogen limitation, CO2 emission, Modelling, Carbon Cycle