TY - JOUR
T1 - Modelling and mapping soil organic carbon stocks under future climate change in south-eastern Australia
AU - Wang, Bin
AU - Gray, Jonathan M.
AU - Waters, Cathy M.
AU - Rajin Anwar, Muhuddin
AU - Orgill, Susan E.
AU - Cowie, Annette L.
AU - Feng, Puyu
AU - Li Liu, De
N1 - Funding Information:
This study was funded by the NSW Primary Industries Climate Change Research Strategy and the NSW Climate Change Fund. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. We thank Dr Bernie Dominiak for his review to improve an early version of the manuscript. We also thank anonymous reviewers and editor for their detailed and constructive comments.
Funding Information:
This study was funded by the NSW Primary Industries Climate Change Research Strategy and the NSW Climate Change Fund. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. We thank Dr Bernie Dominiak for his review to improve an early version of the manuscript. We also thank anonymous reviewers and editor for their detailed and constructive comments.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Soil organic carbon (SOC) plays a key role in the sequestration of carbon that could otherwise be warming the atmosphere. Climate change including increased temperature and changed rainfall will greatly impact the global SOC cycle. There are still significant gaps in our knowledge of the size of the global SOC pool and how future climate will affect SOC stocks and flows in many parts of the world, including Australia. In this study, we used SOC data in a Digital Soil Mapping framework to predict current and future SOC stocks across the state of New South Wales (NSW) in south-eastern Australia. In the first phase of the study we estimated the current SOC stock using multiple linear regression (MLR) and random forest (RF) modelling, and in the second phase we projected the change of SOC stocks in the near future (2050s) and far future (2090s) under two Shared Socio-economic Pathways (SSPs) scenarios based on 25 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 6 (CMIP6). Our spatial modelling showed that estimated current SOC stocks in NSW decreased from east to west. Multi-GCM ensemble means suggested SOC stocks would decrease by 7.6–12.9% under SSP2-4.5 and 9.1–20.9% under SSP5-8.5 across NSW under future climate. The extent of change in SOC stocks varied spatially with the largest mean decrease of SOC stocks occurring in the North Coast and South East (alpine) regions of NSW. Our findings can support decision-making in land management and climate change mitigation strategies in NSW at the regional level. Furthermore, the modelling methods can be applied to other areas where edaphic and landscape properties, land use, and climate data are available.
AB - Soil organic carbon (SOC) plays a key role in the sequestration of carbon that could otherwise be warming the atmosphere. Climate change including increased temperature and changed rainfall will greatly impact the global SOC cycle. There are still significant gaps in our knowledge of the size of the global SOC pool and how future climate will affect SOC stocks and flows in many parts of the world, including Australia. In this study, we used SOC data in a Digital Soil Mapping framework to predict current and future SOC stocks across the state of New South Wales (NSW) in south-eastern Australia. In the first phase of the study we estimated the current SOC stock using multiple linear regression (MLR) and random forest (RF) modelling, and in the second phase we projected the change of SOC stocks in the near future (2050s) and far future (2090s) under two Shared Socio-economic Pathways (SSPs) scenarios based on 25 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 6 (CMIP6). Our spatial modelling showed that estimated current SOC stocks in NSW decreased from east to west. Multi-GCM ensemble means suggested SOC stocks would decrease by 7.6–12.9% under SSP2-4.5 and 9.1–20.9% under SSP5-8.5 across NSW under future climate. The extent of change in SOC stocks varied spatially with the largest mean decrease of SOC stocks occurring in the North Coast and South East (alpine) regions of NSW. Our findings can support decision-making in land management and climate change mitigation strategies in NSW at the regional level. Furthermore, the modelling methods can be applied to other areas where edaphic and landscape properties, land use, and climate data are available.
KW - Climate change
KW - Global climate models
KW - Multiple linear regression
KW - Random forest
KW - Soil organic carbon
KW - South-eastern Australia
UR - http://www.scopus.com/inward/record.url?scp=85114293202&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85114293202&partnerID=8YFLogxK
U2 - 10.1016/j.geoderma.2021.115442
DO - 10.1016/j.geoderma.2021.115442
M3 - Article
AN - SCOPUS:85114293202
SN - 0016-7061
VL - 405
SP - 1
EP - 12
JO - Geoderma
JF - Geoderma
M1 - 115442
ER -