Contribution of soil respiration to the global carbon equation

Abstract

a b s t r a c tSoil respiration (Rs) is the second largest carbon flux next to GPP between the terrestrial ecosystem (the largest organic carbon pool) and the atmosphere at a global scale. Given their critical role in the global carbon cycle, Rs measurement and modeling issues have been well reviewed in previous studies. In this paper, we briefly review advances in soil organic carbon (SOC) decomposition processes and the factors affecting Rs. We examine the spatial and temporal distribution of Rs measurements available in the literature and found that most of the measurements were conducted in North America, Europe, and East Asia, with major gaps in Africa, East Europe, North Asia, Southeast Asia, and Australia, especially in dry ecosystems. We discuss the potential problems of measuring Rs on slope soils and propose using obliquely-cut soil collars to solve the existing problems. We synthesize previous estimates of global Rs flux and find that the estimates ranged from 50 PgC/yr to 98 PgC/yr and the error associated with each estimation was also high (4 PgC/yr to 33.2 PgC/yr). Using a newly integrated database of Rs measurements and the MODIS vegetation map, we estimate that the global annual Rs flux is 94.3 PgC/yr with an estimation error of 17.9 PgC/yr at a 95% confidence level. The uneven distribution of Rs measurements limits our ability to improve the accuracy of estimation. Based on the global estimation of Rs flux, we found that Rs is highly correlated with GPP and NPP at the biome level, highlighting the role of Rs in global carbon budgets.

Constraining estimates of global soil respiration by quantifying sources of variability

“…Our R SG estimates from the first‐order exponential model parameterized with annual R S data [ 100.72 Pg C year −1 and , 97.01 Pg C year −1 )] were close to estimates by Bond‐Lamberty and Thomson (2010a) [98 ± 12 Pg C year −1 ], Hashimoto et al. () [91(±4) Pg C year −1 ], Xu and Shang () [94.3(±17.9) Pg C year −1 ], and Adachi et al. () [93.8 and 94.8 Pg C year −1 ].…”

“…() was a second‐order exponential with a hyperbolic precipitation component model. Xu and Shang () estimated R SG based on annual R S data and MODIS vegetation map. Adachi et al.…”

Analytically tractable climate-carbon cycle feedbacks under 21st century anthropogenic forcing

“…Revelle (buffer) factor r 12.5 Williams et al (2016) Solubility temperature effect DT 4.23%/K Takahashi et al (1993); Ciais et al (2013, p498) Pre-industrial biological pump B0 13 PgC/yr Ciais et al (2013) Temperature dependence of biological pump BT 3.2%/K 12% decrease (Bopp et al, 2013, Fig 9b) after approximately 3.7 K climate change (Collins et al, 2013) Solubility pump rate w0 0.1 yr −1 DIC flux rate from ocean mixed layer divided by DIC stock in mixed layer (Ciais et al, 2013) Weakening of overturning circulation with climate change wT 10%/K Approximate fit to values reported by Collins et al (2013 Terrestrial respiration temperature dependence QR 1.72 Raich et al (2002); Xu and Shang (2016). Based on soil respiration, which contributes the majority of terrestrial ecosystem respiration.…”

“…We approximate the net temperature response of global soil respiration using the Q10 formalism (Xu and Shang, 2016), where Q R is the proportional increase in respiration for a 10 K temperature 20 increase. We assume that pre-industrial soil respiration is balanced by pre-industrial net primary productivity, R 0 = NPP 0 .…”

Analytically tractable climate–carbon cycle feedbacks under 21st century anthropogenic forcing

“…We approximate the net temperature response of global soil respiration using the Q 10 formalism R( T ) = R 0 Q T /10 R c t /c t0 (Xu and Shang, 2016), where Q R is the proportional increase in respiration for a 10 K temperature increase. We assume that preindustrial soil respiration is balanced by pre-industrial NPP, R 0 = NPP 0 .…”