Leaf area index identified as a major source of variability in modeled CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; fertilization

Qianyu Li,Xin Huang,Yiqi Luo,Xingjie Lu,Yingping Wang,Peter M Cox

doi:10.5194/bg-15-6909-2018

Abstract

Abstract. The concentration–carbon feedback (β), also called the CO2 fertilization effect, is a key unknown in climate–carbon-cycle projections. A better understanding of model mechanisms that govern terrestrial ecosystem responses to elevated CO2 is urgently needed to enable a more accurate prediction of future terrestrial carbon sink. We conducted C-only, carbon–nitrogen (C–N) and carbon–nitrogen–phosphorus (C–N–P) simulations of the Community Atmosphere Biosphere Land Exchange model (CABLE) from 1901 to 2100 with fixed climate to identify the most critical model process that causes divergence in β. We calculated CO2 fertilization effects at various hierarchical levels from leaf biochemical reaction and leaf photosynthesis to canopy gross primary production (GPP), net primary production (NPP), and ecosystem carbon storage (cpool) for seven C3 plant functional types (PFTs) in response to increasing CO2 under the RCP 8.5 scenario. Our results show that β values at biochemical and leaf photosynthesis levels vary little across the seven PFTs, but greatly diverge at canopy and ecosystem levels in all simulations. The low variation of the leaf-level β is consistent with a theoretical analysis that leaf photosynthetic sensitivity to increasing CO2 concentration is almost an invariant function. In the CABLE model, the major jump in variation of β values from leaf levels to canopy and ecosystem levels results from divergence in modeled leaf area index (LAI) within and among PFTs. The correlation of βGPP, βNPP, or βcpool each with βLAI is very high in all simulations. Overall, our results indicate that modeled LAI is a key factor causing the divergence in β in the CABLE model. It is therefore urgent to constrain processes that regulate LAI dynamics in order to better represent the response of ecosystem productivity to increasing CO2 in Earth system models.

Highlights

Terrestrial ecosystems absorb roughly 30 % of anthropogenic CO2 emissions, and is of great uncertainty and vulnerable to global climate change (Cox et al, 2000; Le Quéré et al, 2018)
The magnitudes of βcpool differ among different plant functional types (PFTs), with the highest values occurring in deciduous broadleaf forest from 2011 to 2075 and in shrub after 2075, and the lowest values occurring in deciduous needleleaf forest and tundra. βcpool values for deciduous needleleaf forest and tundra nearly overlap over time
Deciduous broadleaf forest and evergreen broadleaf forest have the greatest βcpool values, while deciduous needleleaf forest and tundra still have the lowest βcpool values in C–N simulation. When both N and P limitations are taken into account as in carbon– nitrogen–phosphorus (C–N–P) simulation, magnitudes and trends of βcpool are

Summary

Introduction

Terrestrial ecosystems absorb roughly 30 % of anthropogenic CO2 emissions, and is of great uncertainty and vulnerable to global climate change (Cox et al, 2000; Le Quéré et al, 2018). Persistent increase in atmospheric CO2 concentration will stimulate plant growth and ecosystem carbon storage, forming a negative feedback to CO2 concentration (Long et al, 2004; Friedlingstein et al, 2006; Canadell et al, 2007). This concentration–carbon feedback (β), called the CO2 fertilization effect, has been identified as a major uncertainty in modeling terrestrial carbon-cycle response to historical climate change (Huntzinger et al, 2017).

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