Deep soil organic carbon: A review

Author:

Dubeux, José C.B.1,Lira Junior Mário de A.2,Simili Flávia F.3,Bretas Igor L.1,Trumpp Kevin R.1,Bizzuti Beatriz E.4,Garcia Liza1,Oduor Kenneth T.1,Queiroz Luana M.D.1,Acuña Javier P.1,Mendes Cristian T.E.1

Affiliation:

1. University of Florida, North Florida Research and Education Center, 3925 Highway 71, Marianna, FL, 32446, USA

2. Universidade Federal Rural de Pernambuco, Rua D. Manoel de Medeiros, S/N, Dois Irmãos, Recife, PE, Brazil

3. Instituto de Zootecnia/APTA/SAA, Ribeirão Preto, SP, 14030-670, Brazil

4. University of Wisconsin, Madison, WI, USA

Abstract

Abstract Soil organic carbon (SOC) sequestration promotes several ecological, economic, and social co-benefits. However, most SOC studies rely on topsoil evaluations (0–30 cm), disregarding a significant fraction of the SOC that is stored in deep layers. Understanding the relationship between deep soil carbon and climate change is imperative in guiding sustainable land management practices, informing climate change mitigation strategies, and preserving the crucial role of deep soil carbon in regulating atmospheric CO 2 levels. We conducted a comprehensive literature review to discuss the origins of deep soil carbon, the globally standardized methodology recommended for measuring SOC stocks, the mechanisms controlling SOC sequestration (physical, chemical, and biochemical) in deep layers, the significance of microbial community in deep soil layers, advancements in radiocarbon studies, the impact of management practices on deep SOC, and the influence of climate change on deep SOC stocks. Overall, more empirical data and long-term studies are needed to address the knowledge gaps in terms of deep SOC and advance our understanding of the role of deep soil carbon in shaping global carbon cycles and climate resilience. The main challenges for accurate SOC estimations and global carbon budgets are the high spatial variability, the relative lack of deep soil measurements, and the need for reliable reference data for modeling improvements. A practical and accurate soil bulk density (BD) estimation in deep layers (i.e., 30–100 cm) is crucial to improve the accuracy of global C stock estimations and should be addressed in further studies. Modeling approaches based on sensors and machine learning techniques are promising tools to overcome this challenge. However, there is still a large variability in methods to measure and report soil BD and SOC stocks worldwide, preventing further advances.

Publisher

CABI Publishing

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