Weaker land–climate feedbacks from nutrient uptake during photosynthesis-inactive periods. Issue 11 (November 2018)

• Record Type: Journal Article
• Authors: Riley, W.; Zhu, Q.; Tang, J.
• Is Part Of: Nature climate change. Volume 8:Issue 11(2018)
• Page Start: 1002
• Page End: 1006
• Publication Date: 2018-11
• Subjects: Climatic changes -- Periodicals; 333.7205
• DOI: 10.1038/s41558-018-0325-4
• Languages: English
• ISSNs: 1758-678X

Abstract

Abstract Terrestrial carbon–climate feedbacks depend on two large and opposing fluxes—soil organic matter decomposition and photosynthesis—that are tightly regulated by nutrients1, 2 . Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 represented nutrient dynamics poorly1, 3, rendering predictions of twenty-first century carbon–climate feedbacks highly uncertain. Here, we use a new land model to quantify the effects of observed plant nutrient uptake mechanisms missing in most other ESMs. In particular, we estimate the global role of root nutrient competition with microbes and abiotic processes during periods without photosynthesis. Nitrogen and phosphorus uptake during these periods account for 45 and 43%, respectively, of annual uptake, with large latitudinal variation. Globally, night-time nutrient uptake dominates this signal. Simulations show that ignoring this plant uptake, as is done when applying an instantaneous relative demand approach, leads to large positive biases in annual nitrogen leaching (96%) and N2 O emissions (44%). This N2 O emission bias has a GWP equivalent of ~2.4 PgCO2 yr−1, which is substantial compared to the current terrestrial CO2 sink. Such large biases will lead to predictions of overly open terrestrial nutrient cycles and lower carbon sequestration capacity. Both factors imply over-prediction of positive terrestrial feedbacks with climate in current ESMs. During periods of photosynthetic inactivity, roots compete for nutrients with microbes and abiotic processes. Most ESMs neglect this competition, leading to large positive biases in annual N leaching and N2 O emissions estimates.