Lagged effects regulate the inter-annual variability of the tropical carbon balance

Abstract

Abstract. Inter-annual variations in the tropical land carbon (C) balance are a dominant component of the global atmospheric CO2 growth rate. Currently, the lack of quantitative knowledge on processes controlling net tropical ecosystem C balance on inter-annual timescales inhibits accurate understanding and projections of land–atmosphere C exchanges. In particular, uncertainty on the relative contribution of ecosystem C fluxes attributable to concurrent forcing anomalies (concurrent effects) and those attributable to the continuing influence of past phenomena (lagged effects) stifles efforts to explicitly understand the integrated sensitivity of a tropical ecosystem to climatic variability. Here we present a conceptual framework – applicable in principle to any land biosphere model – to explicitly quantify net biospheric exchange (NBE) as the sum of anomaly-induced concurrent changes and climatology-induced lagged changes to terrestrial ecosystem C states (NBE = NBECON+NBELAG). We apply this framework to an observation-constrained analysis of the 2001–2015 tropical C balance: we use a data–model integration approach (CARbon DAta-MOdel fraMework – CARDAMOM) to merge satellite-retrieved land-surface C observations (leaf area, biomass, solar-induced fluorescence), soil C inventory data and satellite-based atmospheric inversion estimates of CO2 and CO fluxes to produce a data-constrained analysis of the 2001–2015 tropical C cycle. We find that the inter-annual variability of both concurrent and lagged effects substantially contributes to the 2001–2015 NBE inter-annual variability throughout 2001–2015 across the tropics (NBECON IAV = 80 % of total NBE IAV, r = 0.76; NBELAG IAV = 64 % of NBE IAV, r = 0.61), and the prominence of NBELAG IAV persists across both wet and dry tropical ecosystems. The magnitude of lagged effect variations on NBE across the tropics is largely attributable to lagged effects on net primary productivity (NPP; NPPLAG IAV 113 % of NBELAG IAV, r = −0.93, p value < 0.05), which emerge due to the dependence of NPP on inter-annual variations in foliar C and plant-available H2O states. We conclude that concurrent and lagged effects need to be explicitly and jointly resolved to retrieve an accurate understanding of the processes regulating the present-day and future trajectory of the terrestrial land C sink.

Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020)

“…Therefore, we recommend combining NBE with other ancillary variables, e.g., GPP, to better understand carbon dynamics. Combining NBE with component carbon fluxes can shed light on the processes controlling the changes of NBE (e.g., Bowman et al, 2017;Liu Figure 12. Comparison between posterior CO 2 and the NOAA marine boundary layer (MBL) reference sites.…”

“…1). Satellite carbon monoxide (CO) observations provide constraints on fire emissions (Arellano et al, 2006;van der Werf, 2008;Jones et al, 2009;Jiang et al, 2017;Bowman et al, 2017;Liu et al, 2017). In addition to the FLUXSAT GPP product used here, solar-induced chlorophyll fluorescence (SIF) can be directly used as a proxy for GPP (e.g., Parazoo et al, 2014).…”

“…In addition to the FLUXSAT GPP product used here, solar-induced chlorophyll fluorescence (SIF) can be directly used as a proxy for GPP (e.g., Parazoo et al, 2014). Once NBE, fire, and GPP carbon fluxes are quantified, TER can be calculated as a residual (e.g., Bowman et al, 2017;Liu et al, 2017Liu et al, , 2018. Because of the diffusive manner of atmospheric transport and the limited observation coverage, the gridded flux values are not independent from each other.…”

“…The CMS-Flux framework exploits globally available X CO 2 to infer spatially resolved total surface-atmosphere exchange. In combination with constituent fluxes, e.g., gross primary production (GPP), NBE from CMS-Flux framework has been used to assess the impacts of El Niño on terrestrial biosphere fluxes (Bowman et al, 2017;Liu et al, 2017) and the role of droughts in the North American carbon balance (Liu et al, 2018). These fluxes have furthermore been ingested into land-surface data assimilation systems to quantify heterotrophic respiration (Konings et al, 2019), evaluate structural and parametric uncertainty in carbon-climate models (Quetin et al, 2020), and inform climate dynamics (Bloom et al, 2020).…”

Optimal model complexity for terrestrial carbon cycle prediction

“…In this paper, we demonstrate the extent to which the prediction accuracy of two key carbon cycle variables can theoretically scale with model complexity. Net ecosystem exchange (NEE) and leaf area index (LAI) were chosen for the analysis because they represent integrated effects of different parts of the carbon cycle (NEE is the balance of photosynthesis and ecosystem respiration fluxes, while LAI strongly controls canopy photosynthesis; Bonan, 1993). Additionally, both are commonly measured and modeled.…”