Articles | Volume 17, issue 24
https://doi.org/10.5194/bg-17-6377-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-6377-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Root uptake under mismatched distributions of water and nutrients in the root zone
Life and Environmental Sciences Department, University of California, Merced, CA, 95343, USA
Nathaniel A. Bogie
Geology Department, San Jose State University, San Jose, CA, 95192, USA
Teamrat A. Ghezzehei
CORRESPONDING AUTHOR
Life and Environmental Sciences Department, University of California, Merced, CA, 95343, USA
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This preprint is open for discussion and under review for SOIL (SOIL).
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Buried ancient topsoils (Brady paleosol, Nebraska) sequester vast SOC. We found repeated drying/rewetting causes greater C loss than continuous wetting, destabilizing the slow-cycling C pool, especially in shallower soils. Decomposition rates are higher in erosional settings. Burial depth and moisture regime are key to the long-term vulnerability of these ancient C stocks under climate change.
Toshiyuki Bandai and Teamrat A. Ghezzehei
Hydrol. Earth Syst. Sci., 26, 4469–4495, https://doi.org/10.5194/hess-26-4469-2022, https://doi.org/10.5194/hess-26-4469-2022, 2022
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Scientists use a physics-based equation to simulate water dynamics that influence hydrological and ecological phenomena. We present hybrid physics-informed neural networks (PINNs) to leverage the growing availability of soil moisture data and advances in machine learning. We showed that PINNs perform comparably to traditional methods and enable the estimation of rainfall rates from soil moisture. However, PINNs are challenging to train and significantly slower than traditional methods.
Samuel N. Araya, Jeffrey P. Mitchell, Jan W. Hopmans, and Teamrat A. Ghezzehei
SOIL, 8, 177–198, https://doi.org/10.5194/soil-8-177-2022, https://doi.org/10.5194/soil-8-177-2022, 2022
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We studied the long-term effects of no-till (NT) and winter cover cropping (CC) practices on soil hydraulic properties. We measured soil water retention and conductivity and also conducted numerical simulations to compare soil water storage abilities under the different systems. Soils under NT and CC practices had improved soil structure. Conservation agriculture practices showed marginal improvement with respect to infiltration rates and water storage.
Jing Yan and Teamrat Ghezzehei
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-52, https://doi.org/10.5194/bg-2022-52, 2022
Publication in BG not foreseen
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Although hydraulic redistribution (HR) is a well-documented phenomenon, whether it is a passive happy accident or actively controlled by roots is not well understood. Our modeling study suggests HR is long-range feedback between roots that inhabit heterogeneously resourced soil regions. When nutrients and organic matter are concentrated in shallow layers that experience frequent drying, root-exudation facilitated HR allows plants to mineralize and extract the otherwise inaccessible nutrients.
Daniel Rath, Nathaniel Bogie, Leonardo Deiss, Sanjai J. Parikh, Daoyuan Wang, Samantha Ying, Nicole Tautges, Asmeret Asefaw Berhe, Teamrat A. Ghezzehei, and Kate M. Scow
SOIL, 8, 59–83, https://doi.org/10.5194/soil-8-59-2022, https://doi.org/10.5194/soil-8-59-2022, 2022
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Storing C in subsoils can help mitigate climate change, but this requires a better understanding of subsoil C dynamics. We investigated changes in subsoil C storage under a combination of compost, cover crops (WCC), and mineral fertilizer and found that systems with compost + WCC had ~19 Mg/ha more C after 25 years. This increase was attributed to increased transport of soluble C and nutrients via WCC root pores and demonstrates the potential for subsoil C storage in tilled agricultural systems.
Samuel N. Araya, Anna Fryjoff-Hung, Andreas Anderson, Joshua H. Viers, and Teamrat A. Ghezzehei
Hydrol. Earth Syst. Sci., 25, 2739–2758, https://doi.org/10.5194/hess-25-2739-2021, https://doi.org/10.5194/hess-25-2739-2021, 2021
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We took aerial photos of a grassland area using an unoccupied aerial vehicle and used the images to estimate soil moisture via machine learning. We were able to estimate soil moisture with high accuracy. Furthermore, by analyzing the machine learning models we developed, we learned how different factors drive the distribution of moisture across the landscape. Among the factors, rainfall, evapotranspiration, and topography were most important in controlling surface soil moisture distribution.
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Short summary
An uneven supply of water and nutrients in soils often drives how plants behave. We observed that plants extract all their required nutrients from dry soil patches in sufficient quantity, provided adequate water is available elsewhere in the root zone. Roots in nutrient-rich dry patches facilitate the nutrient acquisition by extensive growth, water release, and modifying water retention in their immediate environment. The findings are valuable in managing nutrient losses in agricultural systems.
An uneven supply of water and nutrients in soils often drives how plants behave. We observed...
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