Evaluation of projected soil organic carbon stocks under future climate and land cover changes in South Africa using a deep learning approach
Resource type
Journal Article
Authors/contributors
- Odebiri, Omosalewa (Author)
- Mutanga, Onisimo (Author)
- Odindi, John (Author)
- Naicker, Rowan (Author)
- Slotow, Rob (Author)
- Mngadi, Mthembeni (Author)
Title
Evaluation of projected soil organic carbon stocks under future climate and land cover changes in South Africa using a deep learning approach
Abstract
Environmental degradation and carbon emissions have become a major global concern. This has forced policymakers to consider strategic and long-term contingencies to increase carbon sequestration capacity and mitigate the effects of climate change. Soil organic carbon (SOC) provides a reliable long-lasting mechanism to ameliorate climate change and regulate carbon fluxes. However, unanticipated rates of climate change coupled with the dynamic nature of land-use transformation threatens current mitigation approaches and can jeopardise carbon stock assimilation. To effectively manage and protect SOC stocks, large-scale projections that accurately model both current and future SOC pools are necessary. Hence, this study modelled the effects of simulated climate and land-cover change on SOC inventories across South Africa up to the year 2050. A digital soil mapping strategy in concert with a deep neural network (DNN) was used to model current SOC stocks distribution. Subsequently, WorldClim general circulation models and a space-for-time substitution (SFTS) method were used to derive future SOC stocks under four shared socio-economic emission pathways. Results show a relatively high accuracy with RMSE of 7.44 t/h for current stocks, while future stocks ranged from 11.37 to 13.56 t/h. Depending on emission rates, results showed a reduction in SOC inventories, with overall SOC stocks declining from 5.64 Pg to between 4.97 and 5.38 Pg by 2050. Meanwhile, forests, which account for approximately 1.2 Pg of total SOC in South Africa, were found to have lost more than 1% of their total coverage by 2050. These findings provide a glimpse into the state of South Africa's current and future SOC stock inventories and the influence of climate and land-use change. These findings are valuable to among others policymakers, land use managers and climate change experts in assessing the long-term feasibility of South Africa's existing SOC management protocols and land-use planning agenda. However, to adequately protect future SOC stocks, current land-use planning frameworks need to be re-adjusted to prioritize pressing environmental concerns.
Publication
Journal of Environmental Management
Volume
330
Pages
117127
Date
2023-03-01
Journal Abbr
Journal of Environmental Management
Call Number
openalex:W4313731734
Extra
openalex:W4313731734
mag:
Citation
Odebiri, O., Mutanga, O., Odindi, J., Naicker, R., Slotow, R., & Mngadi, M. (2023). Evaluation of projected soil organic carbon stocks under future climate and land cover changes in South Africa using a deep learning approach. Journal of Environmental Management, 330, 117127. https://doi.org/10.1016/j.jenvman.2022.117127
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