Articles | Volume 21, issue 16
https://doi.org/10.5194/bg-21-3691-2024
© Author(s) 2024. 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-21-3691-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Aug 2024
Research article |
| 22 Aug 2024
| 22 Aug 2024
Modeling integrated soil fertility management for maize production in Kenya using a Bayesian calibration of the DayCent model
Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
Magdalena Necpalova
Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
School of Agriculture and Food Science, University College Dublin, Dublin, Ireland
Marijn Van de Broek
Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
Marc Corbeels
AIDA, University of Montpellier, CIRAD, Avenue d’Agropolis, 34398 Montpellier, France
International Institute of Tropical Agriculture (IITA), c/o ICIPE Compound, P.O. Box 30772, 00100, Nairobi, Kenya
Samuel Mathu Ndungu
International Institute of Tropical Agriculture (IITA), c/o ICIPE Compound, P.O. Box 30772, 00100, Nairobi, Kenya
Monicah Wanjiku Mucheru-Muna
Department of Environmental Science and Education, Kenyatta University, P.O. Box 43844, 00100, Nairobi, Kenya
Daniel Mugendi
Department of Water and Agricultural Resource Management, University of Embu, P.O. Box 6, 60100, Embu, Kenya
Rebecca Yegon
Department of Water and Agricultural Resource Management, University of Embu, P.O. Box 6, 60100, Embu, Kenya
Wycliffe Waswa
International Institute of Tropical Agriculture (IITA), c/o ICIPE Compound, P.O. Box 30772, 00100, Nairobi, Kenya
Bernard Vanlauwe
International Institute of Tropical Agriculture (IITA), c/o ICIPE Compound, P.O. Box 30772, 00100, Nairobi, Kenya
Johan Six
Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
Related authors
Marijn Van de Broek, Fiona Stewart-Smith, Moritz Laub, Marc Corbeels, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
EGUsphere, https://doi.org/10.5194/egusphere-2025-2287, https://doi.org/10.5194/egusphere-2025-2287, 2025
This preprint is open for discussion and under review for SOIL (SOIL).
Short summary
Short summary
To improve soil health and increase crop yields, organic matter is commenly added to arable soils. Studying the effect of different organic amenmends on soil organic carbon sequestration in four long-term field trials in Kenya, we found that only a small portion (< 7 %) of added carbon was stabilised. Moreover, this was only observed in the top 15 cm of the soil. These results underline the challenges associated with increasing the organic carbon content of tropical arable soils.
Johan Six, Sebastian Doetterl, Moritz Laub, Claude R. Müller, and Marijn Van de Broek
SOIL, 10, 275–279, https://doi.org/10.5194/soil-10-275-2024, https://doi.org/10.5194/soil-10-275-2024, 2024
Short summary
Short summary
Soil C saturation has been tested in several recent studies and led to a debate about its existence. We argue that, to test C saturation, one should pay attention to six fundamental principles: the right measures, the right units, the right dispersive energy and application, the right soil type, the right clay type, and the right saturation level. Once we take care of those six rights across studies, we find support for a maximum of C stabilized by minerals and thus soil C saturation.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Moritz Laub, Marc Corbeels, Antoine Couëdel, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Magdalena Necpalova, Wycliffe Waswa, Marijn Van de Broek, Bernard Vanlauwe, and Johan Six
SOIL, 9, 301–323, https://doi.org/10.5194/soil-9-301-2023, https://doi.org/10.5194/soil-9-301-2023, 2023
Short summary
Short summary
In sub-Saharan Africa, long-term low-input maize cropping threatens soil fertility. We studied how different quality organic inputs combined with mineral N fertilizer could counteract this. Farmyard manure was the best input to counteract soil carbon loss; mineral N fertilizer had no effect on carbon. Yet, the rates needed to offset soil carbon losses are unrealistic for farmers (>10 t of dry matter per hectare and year). Additional agronomic measures may be needed.
Antoine de Clippele, Astrid C. H. Jaeger, Simon Baumgartner, Marijn Bauters, Pascal Boeckx, Clement Botefa, Glenn Bush, Jessica Carilli, Travis W. Drake, Christian Ekamba, Gode Lompoko, Nivens Bey Mukwiele, Kristof Van Oost, Roland A. Werner, Joseph Zambo, Johan Six, and Matti Barthel
Biogeosciences, 22, 3011–3027, https://doi.org/10.5194/bg-22-3011-2025, https://doi.org/10.5194/bg-22-3011-2025, 2025
Short summary
Short summary
Tropical forest soils as a large terrestrial source of carbon dioxide (CO2) contribute to the global greenhouse gas budget. Despite this, carbon flux data from forested wetlands are scarce in tropical Africa. The study presents 3 years of semi-continuous measurements of surface CO2 fluxes within the Congo Basin. Although no seasonal patterns were evident, our results show a positive effect of soil temperature and moisture, while a quadratic relationship was observed with the water table.
Claude Raoul Müller, Johan Six, Daniel Mugendi Njiru, Bernard Vanlauwe, and Marijn Van de Broek
Biogeosciences, 22, 2733–2747, https://doi.org/10.5194/bg-22-2733-2025, https://doi.org/10.5194/bg-22-2733-2025, 2025
Short summary
Short summary
We studied how different organic and inorganic nutrient inputs affect soil organic carbon (SOC) down to 70 cm in Kenya. After 19 years, all organic treatments increased SOC stocks compared with the control, but mineral nitrogen had no significant effect. Manure was the organic treatment that significantly increased SOC at the deepest soil depths, as its effect could be observed down to 60 cm. Manure was the best strategy to limit SOC loss in croplands and maintain soil quality after deforestation.
Marijn Van de Broek, Fiona Stewart-Smith, Moritz Laub, Marc Corbeels, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
EGUsphere, https://doi.org/10.5194/egusphere-2025-2287, https://doi.org/10.5194/egusphere-2025-2287, 2025
This preprint is open for discussion and under review for SOIL (SOIL).
Short summary
Short summary
To improve soil health and increase crop yields, organic matter is commenly added to arable soils. Studying the effect of different organic amenmends on soil organic carbon sequestration in four long-term field trials in Kenya, we found that only a small portion (< 7 %) of added carbon was stabilised. Moreover, this was only observed in the top 15 cm of the soil. These results underline the challenges associated with increasing the organic carbon content of tropical arable soils.
Roxanne Daelman, Marijn Bauters, Matti Barthel, Emmanuel Bulonza, Lodewijk Lefevre, José Mbifo, Johan Six, Klaus Butterbach-Bahl, Benjamin Wolf, Ralf Kiese, and Pascal Boeckx
Biogeosciences, 22, 1529–1542, https://doi.org/10.5194/bg-22-1529-2025, https://doi.org/10.5194/bg-22-1529-2025, 2025
Short summary
Short summary
The increase in atmospheric concentrations of several greenhouse gases (GHGs) since 1750 is attributed to human activity. However, natural ecosystems, such as tropical forests, also contribute to GHG budgets. The Congo Basin hosts the second largest tropical forest and is understudied. In this study, measurements of soil GHG exchange were carried out during 16 months in a tropical forest in the Congo Basin. Overall, the soil acted as a major source of CO2 and N2O and a minor sink of CH4.
Marijn Van de Broek, Gerard Govers, Marion Schrumpf, and Johan Six
Biogeosciences, 22, 1427–1446, https://doi.org/10.5194/bg-22-1427-2025, https://doi.org/10.5194/bg-22-1427-2025, 2025
Short summary
Short summary
Soil organic carbon models are used to predict how soils affect the concentration of CO2 in the atmosphere. We show that equifinality – the phenomenon that different parameter values lead to correct overall model outputs, albeit with a different model behaviour – is an important source of model uncertainty. Our results imply that adding more complexity to soil organic carbon models is unlikely to lead to better predictions as long as more data to constrain model parameters are not available.
Mosisa Tujuba Wakjira, Nadav Peleg, Johan Six, and Peter Molnar
Hydrol. Earth Syst. Sci., 29, 863–886, https://doi.org/10.5194/hess-29-863-2025, https://doi.org/10.5194/hess-29-863-2025, 2025
Short summary
Short summary
In this study, we implement a climate, water, and crop interaction model to evaluate current conditions and project future changes in rainwater availability and its yield potential, with the goal of informing adaptation policies and strategies in Ethiopia. Although climate change is likely to increase rainfall in Ethiopia, our findings suggest that water-scarce croplands in Ethiopia are expected to face reduced crop yields during the main growing season due to increases in temperature.
Vira Leng, Rémi Cardinael, Florent Tivet, Vang Seng, Phearum Mark, Pascal Lienhard, Titouan Filloux, Johan Six, Lyda Hok, Stéphane Boulakia, Clever Briedis, João Carlos de Moraes Sá, and Laurent Thuriès
SOIL, 10, 699–725, https://doi.org/10.5194/soil-10-699-2024, https://doi.org/10.5194/soil-10-699-2024, 2024
Short summary
Short summary
We assessed the long-term impacts of no-till cropping systems on soil organic carbon and nitrogen dynamics down to 1 m depth under the annual upland crop productions (cassava, maize, and soybean) in the tropical climate of Cambodia. We showed that no-till systems combined with rotations and cover crops could store large amounts of carbon in the top and subsoil in both the mineral organic matter and particulate organic matter fractions. We also question nitrogen management in these systems.
Claude Raoul Müller, Johan Six, Liesa Brosens, Philipp Baumann, Jean Paolo Gomes Minella, Gerard Govers, and Marijn Van de Broek
SOIL, 10, 349–365, https://doi.org/10.5194/soil-10-349-2024, https://doi.org/10.5194/soil-10-349-2024, 2024
Short summary
Short summary
Subsoils in the tropics are not as extensively studied as those in temperate regions. In this study, the conversion of forest to agriculture in a subtropical region affected the concentration of stabilized organic carbon (OC) down to 90 cm depth, while no significant differences between 90 cm and 300 cm were detected. Our results suggest that subsoils below 90 cm are unlikely to accumulate additional stabilized OC through reforestation over decadal periods due to declining OC input with depth.
Johan Six, Sebastian Doetterl, Moritz Laub, Claude R. Müller, and Marijn Van de Broek
SOIL, 10, 275–279, https://doi.org/10.5194/soil-10-275-2024, https://doi.org/10.5194/soil-10-275-2024, 2024
Short summary
Short summary
Soil C saturation has been tested in several recent studies and led to a debate about its existence. We argue that, to test C saturation, one should pay attention to six fundamental principles: the right measures, the right units, the right dispersive energy and application, the right soil type, the right clay type, and the right saturation level. Once we take care of those six rights across studies, we find support for a maximum of C stabilized by minerals and thus soil C saturation.
Armwell Shumba, Regis Chikowo, Christian Thierfelder, Marc Corbeels, Johan Six, and Rémi Cardinael
SOIL, 10, 151–165, https://doi.org/10.5194/soil-10-151-2024, https://doi.org/10.5194/soil-10-151-2024, 2024
Short summary
Short summary
Conservation agriculture (CA), combining reduced or no tillage, permanent soil cover, and improved rotations, is often promoted as a climate-smart practice. However, our knowledge of the impact of CA on top- and subsoil soil organic carbon (SOC) stocks in the low-input cropping systems of sub-Saharan Africa is rather limited. Using two long-term experimental sites with different soil types, we found that mulch could increase top SOC stocks, but no tillage alone had a slightly negative impact.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Moritz Laub, Marc Corbeels, Antoine Couëdel, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Magdalena Necpalova, Wycliffe Waswa, Marijn Van de Broek, Bernard Vanlauwe, and Johan Six
SOIL, 9, 301–323, https://doi.org/10.5194/soil-9-301-2023, https://doi.org/10.5194/soil-9-301-2023, 2023
Short summary
Short summary
In sub-Saharan Africa, long-term low-input maize cropping threatens soil fertility. We studied how different quality organic inputs combined with mineral N fertilizer could counteract this. Farmyard manure was the best input to counteract soil carbon loss; mineral N fertilizer had no effect on carbon. Yet, the rates needed to offset soil carbon losses are unrealistic for farmers (>10 t of dry matter per hectare and year). Additional agronomic measures may be needed.
Kristof Van Oost and Johan Six
Biogeosciences, 20, 635–646, https://doi.org/10.5194/bg-20-635-2023, https://doi.org/10.5194/bg-20-635-2023, 2023
Short summary
Short summary
The direction and magnitude of the net erosion-induced land–atmosphere C exchange have been the topic of a big scientific debate for more than a decade now. Many have assumed that erosion leads to a loss of soil carbon to the atmosphere, whereas others have shown that erosion ultimately leads to a carbon sink. Here, we show that the soil carbon erosion source–sink paradox is reconciled when the broad range of temporal and spatial scales at which the underlying processes operate are considered.
Charlotte Decock, Juhwan Lee, Matti Barthel, Elizabeth Verhoeven, Franz Conen, and Johan Six
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-221, https://doi.org/10.5194/bg-2022-221, 2022
Preprint withdrawn
Short summary
Short summary
One of the least well understood processes in the nitrogen (N) cycle is the loss of nitrogen gas (N2), referred to as total denitrification. This is mainly due to the difficulty of quantifying total denitrification in situ. In this study, we developed and tested a novel modeling approach to estimate total denitrification over the depth profile, based on concentrations and isotope values of N2O. Our method will help close N budgets and identify management strategies that reduce N pollution.
Tegawende Léa Jeanne Ilboudo, Lucien NGuessan Diby, Delwendé Innocent Kiba, Tor Gunnar Vågen, Leigh Ann Winowiecki, Hassan Bismarck Nacro, Johan Six, and Emmanuel Frossard
EGUsphere, https://doi.org/10.5194/egusphere-2022-209, https://doi.org/10.5194/egusphere-2022-209, 2022
Preprint withdrawn
Short summary
Short summary
Our results showed that at landscape level SOC stock variability was mainly explained by clay content. We found significant linear positive relationships between VC and SOC stocks for the land uses annual croplands, perennial croplands, grasslands and bushlands without soil depth restrictions until 110 cm. We concluded that in the forest-savanna transition zone, soil properties and topography determine land use, which in turn affects the stocks of SOC and TN and to some extent the VC stocks.
Rey Harvey Suello, Simon Lucas Hernandez, Steven Bouillon, Jean-Philippe Belliard, Luis Dominguez-Granda, Marijn Van de Broek, Andrea Mishell Rosado Moncayo, John Ramos Veliz, Karem Pollette Ramirez, Gerard Govers, and Stijn Temmerman
Biogeosciences, 19, 1571–1585, https://doi.org/10.5194/bg-19-1571-2022, https://doi.org/10.5194/bg-19-1571-2022, 2022
Short summary
Short summary
This research shows indications that the age of the mangrove forest and its position along a deltaic gradient (upstream–downstream) play a vital role in the amount and sources of carbon stored in the mangrove sediments. Our findings also imply that carbon capture by the mangrove ecosystem itself contributes partly but relatively little to long-term sediment organic carbon storage. This finding is particularly relevant for budgeting the potential of mangrove ecosystems to mitigate climate change.
Florian Lauryssen, Philippe Crombé, Tom Maris, Elliot Van Maldegem, Marijn Van de Broek, Stijn Temmerman, and Erik Smolders
Biogeosciences, 19, 763–776, https://doi.org/10.5194/bg-19-763-2022, https://doi.org/10.5194/bg-19-763-2022, 2022
Short summary
Short summary
Surface waters in lowland regions have a poor surface water quality, mainly due to excess nutrients like phosphate. Therefore, we wanted to know the phosphate levels without humans, also called the pre-industrial background. Phosphate binds strongly to sediment particles, suspended in the river water. In this research we used sediments deposited by a river as an archive for surface water phosphate back to 1800 CE. Pre-industrial phosphate levels were estimated at one-third of the modern levels.
Philipp Baumann, Juhwan Lee, Emmanuel Frossard, Laurie Paule Schönholzer, Lucien Diby, Valérie Kouamé Hgaza, Delwende Innocent Kiba, Andrew Sila, Keith Sheperd, and Johan Six
SOIL, 7, 717–731, https://doi.org/10.5194/soil-7-717-2021, https://doi.org/10.5194/soil-7-717-2021, 2021
Short summary
Short summary
This work delivers openly accessible and validated calibrations for diagnosing 26 soil properties based on mid-infrared spectroscopy. These were developed for four regions in Burkina Faso and Côte d'Ivoire, including 80 fields of smallholder farmers. The models can help to site-specifically and cost-efficiently monitor soil quality and fertility constraints to ameliorate soils and yields of yam or other staple crops in the four regions between the humid forest and the northern Guinean savanna.
Laura Summerauer, Philipp Baumann, Leonardo Ramirez-Lopez, Matti Barthel, Marijn Bauters, Benjamin Bukombe, Mario Reichenbach, Pascal Boeckx, Elizabeth Kearsley, Kristof Van Oost, Bernard Vanlauwe, Dieudonné Chiragaga, Aimé Bisimwa Heri-Kazi, Pieter Moonen, Andrew Sila, Keith Shepherd, Basile Bazirake Mujinya, Eric Van Ranst, Geert Baert, Sebastian Doetterl, and Johan Six
SOIL, 7, 693–715, https://doi.org/10.5194/soil-7-693-2021, https://doi.org/10.5194/soil-7-693-2021, 2021
Short summary
Short summary
We present a soil mid-infrared library with over 1800 samples from central Africa in order to facilitate soil analyses of this highly understudied yet critical area. Together with an existing continental library, we demonstrate a regional analysis and geographical extrapolation to predict total carbon and nitrogen. Our results show accurate predictions and highlight the value that the data contribute to existing libraries. Our library is openly available for public use and for expansion.
Sebastian Doetterl, Rodrigue K. Asifiwe, Geert Baert, Fernando Bamba, Marijn Bauters, Pascal Boeckx, Benjamin Bukombe, Georg Cadisch, Matthew Cooper, Landry N. Cizungu, Alison Hoyt, Clovis Kabaseke, Karsten Kalbitz, Laurent Kidinda, Annina Maier, Moritz Mainka, Julia Mayrock, Daniel Muhindo, Basile B. Mujinya, Serge M. Mukotanyi, Leon Nabahungu, Mario Reichenbach, Boris Rewald, Johan Six, Anna Stegmann, Laura Summerauer, Robin Unseld, Bernard Vanlauwe, Kristof Van Oost, Kris Verheyen, Cordula Vogel, Florian Wilken, and Peter Fiener
Earth Syst. Sci. Data, 13, 4133–4153, https://doi.org/10.5194/essd-13-4133-2021, https://doi.org/10.5194/essd-13-4133-2021, 2021
Short summary
Short summary
The African Tropics are hotspots of modern-day land use change and are of great relevance for the global carbon cycle. Here, we present data collected as part of the DFG-funded project TropSOC along topographic, land use, and geochemical gradients in the eastern Congo Basin and the Albertine Rift. Our database contains spatial and temporal data on soil, vegetation, environmental properties, and land management collected from 136 pristine tropical forest and cropland plots between 2017 and 2020.
Philipp Baumann, Anatol Helfenstein, Andreas Gubler, Armin Keller, Reto Giulio Meuli, Daniel Wächter, Juhwan Lee, Raphael Viscarra Rossel, and Johan Six
SOIL, 7, 525–546, https://doi.org/10.5194/soil-7-525-2021, https://doi.org/10.5194/soil-7-525-2021, 2021
Short summary
Short summary
We developed the Swiss mid-infrared spectral library and a statistical model collection across 4374 soil samples with reference measurements of 16 properties. Our library incorporates soil from 1094 grid locations and 71 long-term monitoring sites. This work confirms once again that nationwide spectral libraries with diverse soils can reliably feed information to a fast chemical diagnosis. Our data-driven reduction of the library has the potential to accurately monitor carbon at the plot scale.
Mario Reichenbach, Peter Fiener, Gina Garland, Marco Griepentrog, Johan Six, and Sebastian Doetterl
SOIL, 7, 453–475, https://doi.org/10.5194/soil-7-453-2021, https://doi.org/10.5194/soil-7-453-2021, 2021
Short summary
Short summary
In deeply weathered tropical rainforest soils of Africa, we found that patterns of soil organic carbon stocks differ between soils developed from geochemically contrasting parent material due to differences in the abundance of organo-mineral complexes, the presence/absence of chemical stabilization mechanisms of carbon with minerals and the presence of fossil organic carbon from sedimentary rocks. Physical stabilization mechanisms by aggregation provide additional protection of soil carbon.
Sophie F. von Fromm, Alison M. Hoyt, Markus Lange, Gifty E. Acquah, Ermias Aynekulu, Asmeret Asefaw Berhe, Stephan M. Haefele, Steve P. McGrath, Keith D. Shepherd, Andrew M. Sila, Johan Six, Erick K. Towett, Susan E. Trumbore, Tor-G. Vågen, Elvis Weullow, Leigh A. Winowiecki, and Sebastian Doetterl
SOIL, 7, 305–332, https://doi.org/10.5194/soil-7-305-2021, https://doi.org/10.5194/soil-7-305-2021, 2021
Short summary
Short summary
We investigated various soil and climate properties that influence soil organic carbon (SOC) concentrations in sub-Saharan Africa. Our findings indicate that climate and geochemistry are equally important for explaining SOC variations. The key SOC-controlling factors are broadly similar to those for temperate regions, despite differences in soil development history between the two regions.
Anatol Helfenstein, Philipp Baumann, Raphael Viscarra Rossel, Andreas Gubler, Stefan Oechslin, and Johan Six
SOIL, 7, 193–215, https://doi.org/10.5194/soil-7-193-2021, https://doi.org/10.5194/soil-7-193-2021, 2021
Short summary
Short summary
In this study, we show that a soil spectral library (SSL) can be used to predict soil carbon at new and very different locations. The importance of this finding is that it requires less time-consuming lab work than calibrating a new model for every local application, while still remaining similar to or more accurate than local models. Furthermore, we show that this method even works for predicting (drained) peat soils, using a SSL with mostly mineral soils containing much less soil carbon.
Simon Baumgartner, Marijn Bauters, Matti Barthel, Travis W. Drake, Landry C. Ntaboba, Basile M. Bazirake, Johan Six, Pascal Boeckx, and Kristof Van Oost
SOIL, 7, 83–94, https://doi.org/10.5194/soil-7-83-2021, https://doi.org/10.5194/soil-7-83-2021, 2021
Short summary
Short summary
We compared stable isotope signatures of soil profiles in different forest ecosystems within the Congo Basin to assess ecosystem-level differences in N cycling, and we examined the local effect of topography on the isotopic signature of soil N. Soil δ15N profiles indicated that the N cycling in in the montane forest is more closed, whereas the lowland forest and Miombo woodland experienced a more open N cycle. Topography only alters soil δ15N values in forests with high erosional forces.
Simon Baumgartner, Matti Barthel, Travis William Drake, Marijn Bauters, Isaac Ahanamungu Makelele, John Kalume Mugula, Laura Summerauer, Nora Gallarotti, Landry Cizungu Ntaboba, Kristof Van Oost, Pascal Boeckx, Sebastian Doetterl, Roland Anton Werner, and Johan Six
Biogeosciences, 17, 6207–6218, https://doi.org/10.5194/bg-17-6207-2020, https://doi.org/10.5194/bg-17-6207-2020, 2020
Short summary
Short summary
Soil respiration is an important carbon flux and key process determining the net ecosystem production of terrestrial ecosystems. The Congo Basin lacks studies quantifying carbon fluxes. We measured soil CO2 fluxes from different forest types in the Congo Basin and were able to show that, even though soil CO2 fluxes are similarly high in lowland and montane forests, the drivers were different: soil moisture in montane forests and C availability in the lowland forests.
Cited articles
Abramoff, R., Xu, X., Hartman, M., O’Brien, S., Feng, W., Davidson, E., Finzi, A., Moorhead, D., Schimel, J., Torn, M., and Mayes, M. A.: The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century, Biogeochemistry, 137, 51–71, https://doi.org/10.1007/s10533-017-0409-7, 2018. a, b
Abramoff, R. Z., Guenet, B., Zhang, H., Georgiou, K., Xu, X., Viscarra Rossel, R. A., Yuan, W., and Ciais, P.: Improved global-scale predictions of soil carbon stocks with Millennial Version 2, Soil Biol. Biochem., 164, 108466, https://doi.org/10.1016/j.soilbio.2021.108466, 2022. a
Ahrens, B., Guggenberger, G., Rethemeyer, J., John, S., Marschner, B., Heinze, S., Angst, G., Mueller, C. W., Kögel-Knabner, I., Leuschner, C., Hertel, D., Bachmann, J., Reichstein, M., and Schrumpf, M.: Combination of energy limitation and sorption capacity explains 14C depth gradients, Soil Biol. Biochem., 148, 107912, https://doi.org/10.1016/j.soilbio.2020.107912, 2020. a
Arias-Navarro, C., Díaz-Pinés, E., Klatt, S., Brandt, P., Rufino, M. C., Butterbach-Bahl, K., and Verchot, L. V.: Spatial variability of soil N2O and CO2 fluxes in different topographic positions in a tropical montane forest in Kenya, J. Geophys. Res.-Biogeo., 122, 514–527, https://doi.org/10.1002/2016JG003667, 2017. a
Barthel, M., Bauters, M., Baumgartner, S., Drake, T. W., Bey, N. M., Bush, G., Boeckx, P., Botefa, C. I., Dériaz, N., Ekamba, G. L., Gallarotti, N., Mbayu, F. M., Mugula, J. K., Makelele, I. A., Mbongo, C. E., Mohn, J., Mandea, J. Z., Mpambi, D. M., Ntaboba, L. C., Rukeza, M. B., Spencer, R. G. M., Summerauer, L., Vanlauwe, B., Van Oost, K., Wolf, B., and Six, J.: Low N2O and variable CH4 fluxes from tropical forest soils of the Congo Basin, Nat. Commun., 13, 330, https://doi.org/10.1038/s41467-022-27978-6, 2022. a
Bates, D., Mächler, M., Bolker, B., and Walker, S.: Fitting Linear Mixed-Effects Models Using lme4, J. Stat. Softw., 67, 1–48, https://doi.org/10.18637/jss.v067.i01, 2015. a
Chivenge, P., Vanlauwe, B., Gentile, R., Wangechi, H., Mugendi, D., Kessel, C. v., and Six, J.: Organic and Mineral Input Management to Enhance Crop Productivity in Central Kenya, Agron. J., 101, 1266–1275, https://doi.org/10.2134/agronj2008.0188x, 2009. a, b
Chivenge, P., Vanlauwe, B., and Six, J.: Does the combined application of organic and mineral nutrient sources influence maize productivity? A meta-analysis, Plant Soil, 342, 1–30, https://doi.org/10.1007/s11104-010-0626-5, 2011. a, b
Clark, M. and Tilman, D.: Comparative analysis of environmental impacts of agricultural production systems, agricultural input efficiency, and food choice, Environ. Res. Lett., 12, 064016, https://doi.org/10.1088/1748-9326/aa6cd5, 2017. a
Clifford, D., Pagendam, D., Baldock, J., Cressie, N., Farquharson, R., Farrell, M., Macdonald, L., and Murray, L.: Rethinking soil carbon modelling: a stochastic approach to quantify uncertainties, Environmetrics, 25, 265–278, https://doi.org/10.1002/env.2271, 2014. a
Corbeels, M., Cardinael, R., Naudin, K., Guibert, H., and Torquebiau, E.: The 4 per 1000 goal and soil carbon storage under agroforestry and conservation agriculture systems in sub-Saharan Africa, Soil Till. Res., 188, 16–26, https://doi.org/10.1016/j.still.2018.02.015, 2019. a
Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K., and Paul, E.: The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter?, Glob. Change Biol., 19, 988–995, https://doi.org/10.1111/gcb.12113, 2013. a, b
Dangal, S. R. S., Schwalm, C., Cavigelli, M. A., Gollany, H. T., Jin, V. L., and Sanderman, J.: Improving Soil Carbon Estimates by Linking Conceptual Pools Against Measurable Carbon Fractions in the DAYCENT Model Version 4.5, J. Adv. Model. Earth Sy., 14, e2021MS002622, https://doi.org/10.1029/2021MS002622, 2022. a
Del Grosso, S. J., Parton, W. J., Mosier, A. R., Hartman, M. D.,Brenner, J., Ojima, D. S., and Schimel, D. S.: Simulated interaction of carbon dynamics and nitrogen trace gas fluxes using the DAYCENT model, in: Modeling Carbon and Nitrogen Dynamics for Soil Management, edited by: Schaffer, M., Ma, L., and Hansen, S., CRC Press, Boca Raton, Florida, 303–332, ISBN 978-0-367-80137-3, https://www.taylorfrancis.com/books/edit/ (last access: 19 August 2024), 2001. a, b
Del Grosso, S., Parton, W., Mosier, A., Holland, E., Pendall, E., Schimel, D., and Ojima, D.: Modeling soil CO2 emissions from ecosystems, Biogeochemistry, 73, 71–91, https://doi.org/10.1007/s10533-004-0898-z, 2005. a
Denef, K., Plante, A. F., and Six, J.: Characterization of soil organic matter, in: Soil Carbon Dynamics: An Integrated Methodology, edited by Heinemeyer, A., Bahn, M., and Kutsch, W. L., Cambridge University Press, Cambridge, 91–126, ISBN 978-0-521-86561-6, https://doi.org/10.1017/CBO9780511711794.007, 2009. a
dos Reis Martins, M., Necpalova, M., Ammann, C., Buchmann, N., Calanca, P., Flechard, C. R., Hartman, M. D., Krauss, M., Le Roy, P., Mäder, P., Maier, R., Morvan, T., Nicolardot, B., Skinner, C., Six, J., and Keel, S. G.: Modeling N2O emissions of complex cropland management in Western Europe using DayCent: Performance and scope for improvement, Eur. J. Agron., 141, 126613, https://doi.org/10.1016/j.eja.2022.126613, 2022. a
FAO: FAOSTAT Online Database, FAO, https://www.fao.org/faostat/en/#data/QCL (last access: 28 April 2023), 2023. a
Frimmel, F. H. and Christman, R. F.: Humic substances and their role in the environment, edited by: Frimmel, F. H., Bracewell, J. M., and Christman, R. F., John Wiley and Sons Ltd., ISBN 9780471918172, 1988. a
Gauch, H. G., Hwang, J. T. G., and Fick, G. W.: Model Evaluation by Comparison of Model-Based Predictions and Measured Values, Agron. J., 95, 1442–1442, https://doi.org/10.2134/agronj2003.1442, 2003. a
Gentile, R., Vanlauwe, B., and Six, J.: Litter quality impacts short- but not long-term soil carbon dynamics in soil aggregate fractions, Ecol. Soc. Am., 21, 695–703, https://doi.org/10.1890/09-2325.1, 2011. a
Gurung, R. B., Ogle, S. M., Breidt, F. J., Williams, S. A., and Parton, W. J.: Bayesian calibration of the DayCent ecosystem model to simulate soil organic carbon dynamics and reduce model uncertainty, Geoderma, 376, 114529, https://doi.org/10.1016/j.geoderma.2020.114529, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
Gurung, R. B., Ogle, S. M., Breidt, F. J., Parton, W. J., Del Grosso, S. J., Zhang, Y., Hartman, M. D., Williams, S. A., and Venterea, R. T.: Modeling nitrous oxide mitigation potential of enhanced efficiency nitrogen fertilizers from agricultural systems, Sci. Total Environ., 801, 149342, https://doi.org/10.1016/j.scitotenv.2021.149342, 2021. a, b, c
Hartman, M., Parton, W., Del Grosso, S., Easter, M., Hendryx, J., Hilinski, T., Kelly, R., Keough, C., Killian, K., Lutz, S., Marx, E., McKeown, R., Ogle, S., Ojima, D., Paustian, K., Swan, A., and Williams, S.: The Daily Century Ecosystem, Soil Organic Matter, Nutrient Cycling, Nitrogen Trace Gas, and Methane Model, User Manual, Scientific Basis, and Technical Documentation, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, 2020. a, b, c, d
Hodnett, M. G. and Tomasella, J.: Marked differences between van Genuchten soil water-retention parameters for temperate and tropical soils: a new water-retention pedo-transfer functions developed for tropical soils, Geoderma, 108, 155–180, https://doi.org/10.1016/S0016-7061(02)00105-2, 2002. a, b, c
Hutchinson, G. L. and Mosier, A. R.: Improved Soil Cover Method for Field Measurement of Nitrous Oxide Fluxes, Soil Sci. Soc. Am. J., 45, 311–316, https://doi.org/10.2136/sssaj1981.03615995004500020017x, 1981. a
Iooss, B., Veiga, S. D., Janon, A., Pujol, G., Broto, W. C. F. B., Boumhaout, K., Delage, T., Amri, R. E., Fruth, J., Gilquin, L., Guillaume, J., Idrissi, M. I., Gratiet, L. L., Lemaitre, P., Marrel, A., Meynaoui, A., Nelson, B. L., Monari, F., Oomen, R., Rakovec, O., Ramos, B., Roustant, O., Song, E., Staum, J., Sueur, R., Touati, T., and Weber, F.: sensitivity: Global Sensitivity Analysis of Model Outputs, https://CRAN.R-project.org/package=sensitivity (last access: 23 February 2023), 2021. a
Ittersum, M. K. v., Bussel, L. G. J. v., Wolf, J., Grassini, P., Wart, J. v., Guilpart, N., Claessens, L., Groot, H. d., Wiebe, K., Mason-D’Croz, D., Yang, H., Boogaard, H., Oort, P. A. J. v., Loon, M. P. v., Saito, K., Adimo, O., Adjei-Nsiah, S., Agali, A., Bala, A., Chikowo, R., Kaizzi, K., Kouressy, M., Makoi, J. H. J. R., Ouattara, K., Tesfaye, K., and Cassman, K. G.: Can sub-Saharan Africa feed itself?, P. Natl. Acad. Sci. USA, 113, 14964–14969, https://doi.org/10.1073/pnas.1610359113,2016. a
Kallenbach, C. M., Frey, S. D., and Grandy, A. S.: Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls, Nat. Commun., 7, 1–10, https://doi.org/10.1038/ncomms13630, 2016. a, b
Kamoni, P. T., Gicheru, P. T., Wokabi, S. M., Easter, M., Milne, E., Coleman, K., Falloon, P., and Paustian, K.: Predicted soil organic carbon stocks and changes in Kenya between 1990 and 2030, Agr. Ecosyst. Environ., 122, 105–113, https://doi.org/10.1016/j.agee.2007.01.024, 2007. a
Laub, M., Demyan, M. S., Nkwain, Y. F., Blagodatsky, S., Kätterer, T., Piepho, H.-p., and Cadisch, G.: DRIFTS band areas as measured pool size proxy to reduce parameter uncertainty in soil organic matter models, Biogeosciences, 17, 1393–1413, https://doi.org/10.5194/bg-17-1393-2020, 2020. a
Laub, M., Corbeels, M., Couëdel, A., Ndungu, S. M., Mucheru-Muna, M. W., Mugendi, D., Necpalova, M., Waswa, W., Van de Broek, M., Vanlauwe, B., and Six, J.: Managing soil organic carbon in tropical agroecosystems: evidence from four long-term experiments in Kenya, SOIL, 9, 301–323, https://doi.org/10.5194/soil-9-301-2023, 2023a. a, b, c, d, e, f, g, h, i
Laub, M., Corbeels, M., Mathu Ndungu, S., Mucheru-Muna, M. W., Mugendi, D., Necpalova, M., Van de Broek, M., Waswa, W., Vanlauwe, B., and Six, J.: Combining manure with mineral N fertilizer maintains maize yields: Evidence from four long-term experiments in Kenya, Field Crops Res., 291, 108788, https://doi.org/10.1016/j.fcr.2022.108788, 2023b. a, b, c, d
Laub, M., Blagodatsky, S., Van de Broek, M., Schlichenmaier, S., Kunlanit, B., Six, J., Vityakon, P., and Cadisch, G.: SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation, Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, 2024. a, b, c
Lee, J., Hopmans, J. W., Rolston, D. E., Baer, S. G., and Six, J.: Determining soil carbon stock changes: Simple bulk density corrections fail, Agr. Ecosyst. Environ., 134, 251–256, https://doi.org/10.1016/j.agee.2009.07.006, 2009. a
Lee, J., Necpálová, M., and Six, J.: Biophysical potential of organic cropping practices as a sustainable alternative in Switzerland, Agr. Syst., 181, 102822, https://doi.org/10.1016/j.agsy.2020.102822, 2020. a, b
Leitner, S., Pelster, D. E., Werner, C., Merbold, L., Baggs, E. M., Mapanda, F., and Butterbach-Bahl, K.: Closing maize yield gaps in sub-Saharan Africa will boost soil N2O emissions, Current Opinion in Environ. Sustain., 47, 95–105, https://doi.org/10.1016/j.cosust.2020.08.018, 2020. a, b
Lemma, B., Williams, S., and Paustian, K.: Long term soil carbon sequestration potential of smallholder croplands in southern Ethiopia with DAYCENT model, J. Environ. Manag., 294, 112893, https://doi.org/10.1016/j.jenvman.2021.112893, 2021. a
Levavasseur, F., Mary, B., and Houot, S.: C and N dynamics with repeated organic amendments can be simulated with the STICS model, Nutr. Cycl. Agroecosys., 119, 103–121, https://doi.org/10.1007/s10705-020-10106-5, 2021. a
Levy, P. E., Cowan, N., van Oijen, M., Famulari, D., Drewer, J., and Skiba, U.: Estimation of cumulative fluxes of nitrous oxide: uncertainty in temporal upscaling and emission factors, Eur. J. Soil Sci., 68, 400–411, https://doi.org/10.1111/ejss.12432, 2017. a
Loague, K. and Green, R. E.: Statistical and graphical methods for evaluating solute transport models: Overview and application, J. Contamin. Hydrol., 7, 51–73, https://doi.org/10.1016/0169-7722(91)90038-3, 1991. a
Lobell, D. B., Bänziger, M., Magorokosho, C., and Vivek, B.: Nonlinear heat effects on African maize as evidenced by historical yield trials, Nat. Clim. Change, 1, 42–45, https://doi.org/10.1038/nclimate1043, 2011. a
Mainka, M., Summerauer, L., Wasner, D., Garland, G., Griepentrog, M., Berhe, A. A., and Doetterl, S.: Soil geochemistry as a driver of soil organic matter composition: insights from a soil chronosequence, Biogeosciences, 19, 1675–1689, https://doi.org/10.5194/bg-19-1675-2022, 2022. a
Mathers, C., Black, C. K., Segal, B. D., Gurung, R. B., Zhang, Y., Easter, M. J., Williams, S., Motew, M., Campbell, E. E., Brummitt, C. D., Paustian, K., and Kumar, A. A.: Validating DayCent-CR for cropland soil carbon offset reporting at a national scale, Geoderma, 438, 116647, https://doi.org/10.1016/j.geoderma.2023.116647, 2023. a, b, c, d, e
Mtangadura, T. J., Mtambanengwe, F., Nezomba, H., Rurinda, J., and Mapfumo, P.: Why organic resources and current fertilizer formulations in Southern Africa cannot sustain maize productivity: Evidence from a long-term experiment in Zimbabwe, PLOS ONE, 12, e0182840, https://doi.org/10.1371/journal.pone.0182840, 2017. a
Mueller, T., Jensen, L. S., Magid, J., and Nielsen, N. E.: Temporal variation of C and N turnover in soil after oilseed rape straw incorporation in the field: simulations with the soil-plant-atmosphere model DAISY, Ecol. Model., 99, 247–262, https://doi.org/10.1016/S0304-3800(97)01959-5, 1997. a
Mutuku, E. A., Roobroeck, D., Vanlauwe, B., Boeckx, P., and Cornelis, W. M.: Maize production under combined Conservation Agriculture and Integrated Soil Fertility Management in the sub-humid and semi-arid regions of Kenya, Field Crops Res., 254, 107833, https://doi.org/10.1016/j.fcr.2020.107833, 2020. a
Möhring, J. and Piepho, H.-P.: Comparison of Weighting in Two-Stage Analysis of Plant Breeding Trials, Crop Sci., 49, 1977–1988, https://doi.org/10.2135/cropsci2009.02.0083, 2009. a
Necpalova, M., Lee, J., Skinner, C., Büchi, L., Wittwer, R., Gattinger, A., van der Heijden, M., Mäder, P., Charles, R., Berner, A., Mayer, J., and Six, J.: Potentials to mitigate greenhouse gas emissions from Swiss agriculture, Agr. Ecosyst. Environ., 265, 84–102, https://doi.org/10.1016/j.agee.2018.05.013, 2018. a, b, c, d
Necpálová, M., Anex, R. P., Fienen, M. N., Del Grosso, S. J., Castellano, M. J., Sawyer, J. E., Iqbal, J., Pantoja, J. L., and Barker, D. W.: Understanding the DayCent model: Calibration, sensitivity, and identifiability through inverse modeling, Environ. Model. Softw., 66, 110–130, https://doi.org/10.1016/j.envsoft.2014.12.011, 2015. a, b, c, d, e
Nezomba, H., Mtambanengwe, F., Rurinda, J., and Mapfumo, P.: Integrated soil fertility management sequences for reducing climate risk in smallholder crop production systems in southern Africa, Field Crops Res., 224, 102–114, https://doi.org/10.1016/j.fcr.2018.05.003, 2018. a
Nyawira, S. S., Hartman, M. D., Nguyen, T. H., Margenot, A. J., Kihara, J., Paul, B. K., Williams, S., Bolo, P., and Sommer, R.: Simulating soil organic carbon in maize-based systems under improved agronomic management in Western Kenya, Soil Till. Res., 211, 105000, https://doi.org/10.1016/j.still.2021.105000, 2021. a, b, c, d
Parton, W. J., Schimel, D. S., Cole, C. V., and Ojima, D. S.: Analysis of Factors Controlling Soil Organic Matter Levels in Great Plains Grasslands, Soil Sci. Soc. Am. J., 51, 1173–1179, https://doi.org/10.2136/sssaj1987.03615995005100050015x, 1987. a
Parton, W. J., Hartman, M., Ojima, D., and Schimel, D.: DAYCENT and its land surface submodel: description and testing, Glob. Planet. Change, 19, 35–48, https://doi.org/10.1016/S0921-8181(98)00040-X, 1998. a
Pelster, D., Rufino, M., Rosenstock, T., Mango, J., Saiz, G., Diaz-Pines, E., Baldi, G., and Butterbach-Bahl, K.: Smallholder farms in eastern African tropical highlands have low soil greenhouse gas fluxes, Biogeosciences, 14, 187–202, https://doi.org/10.5194/bg-14-187-2017, 2017. a
Puttaso, A., Vityakon, P., Rasche, F., Saenjan, P., Treloges, V., and Cadisch, G.: Does Organic Residue Quality Influence Carbon Retention in a Tropical Sandy Soil?, Soil Sci. Soc. Am. J., 77, 1001–1001, https://doi.org/10.2136/sssaj2012.0209, 2013. a
Rattalino Edreira, J. I., Andrade, J. F., Cassman, K. G., van Ittersum, M. K., van Loon, M. P., and Grassini, P.: Spatial frameworks for robust estimation of yield gaps, Nature Food, 2, 773–779, https://doi.org/10.1038/s43016-021-00365-y, 2021. a
Reichenbach, M., Fiener, P., Garland, G., Griepentrog, M., Six, J., and Doetterl, S.: The role of geochemistry in organic carbon stabilization against microbial decomposition in tropical rainforest soils, SOIL, 7, 453–475, https://doi.org/10.5194/soil-7-453-2021, 2021. a
Saito, K., Six, J., Komatsu, S., Snapp, S., Rosenstock, T., Arouna, A., Cole, S., Taulya, G., and Vanlauwe, B.: Agronomic gain: Definition, approach, and application, Field Crops Res., 270, 108193, https://doi.org/10.1016/j.fcr.2021.108193, 2021. a
Saltelli, A.: Making best use of model evaluations to compute sensitivity indices, Comput. Phys. Commun., 145, 280–297, https://doi.org/10.1016/S0010-4655(02)00280-1, 2002a. a
Saltelli, A.: Sensitivity Analysis for Importance Assessment, Risk Anal., 22, 579–590, https://doi.org/10.1111/0272-4332.00040, 2002b. a
Saxton, K. E. and Rawls, W. J.: Soil Water Characteristic Estimates by Texture and Organic Matter for Hydrologic Solutions, Soil Sci. Soc. Am. J., 70, 1569–1578, https://doi.org/10.2136/sssaj2005.0117, 2006. a, b
Sommer, R., Paul, B. K., Mukalama, J., and Kihara, J.: Reducing losses but failing to sequester carbon in soils – the case of Conservation Agriculture and Integrated Soil Fertility Management in the humid tropical agro-ecosystem of Western Kenya, Agr. Ecosyst. Environ., 254, 82–91, https://doi.org/10.1016/j.agee.2017.11.004, 2018. a
Stella, T., Mouratiadou, I., Gaiser, T., Berg-Mohnicke, M., Wallor, E., Ewert, F., and Nendel, C.: Estimating the contribution of crop residues to soil organic carbon conservation, Environ. Res. Lett., 14, 094008–094008, https://doi.org/10.1088/1748-9326/ab395c, 2019. a
Tuszynski, J.: caTools: Tools: Moving Window Statistics, GIF, Base64, ROC AUC, etc., https://CRAN.R-project.org/package=caTools (last access: 19 August 2024), 2021. a
van Genuchten, M.: A comparison of numerical solutions of the one-dimensional unsaturated–saturated flow and mass transport equations, Adv. Water Res., 5, 47–55, https://doi.org/10.1016/0309-1708(82)90028-8, 1982. a
van Oijen, M.: Bayesian Compendium, Springer International Publishing, Cham, ISBN 978-3-030-55896-3 978-3-030-55897-0, https://doi.org/10.1007/978-3-030-55897-0, 2020. a
Vanlauwe, B., Bationo, A., Chianu, J., Giller, K., Merckx, R., Mokwunye, U., Ohiokpehai, O., Pypers, P., Tabo, R., Shepherd, K., Smaling, E., Woomer, P., and Sanginga, N.: Integrated Soil Fertility Management: Operational Definition and Consequences for Implementation and Dissemination, Outlook Agr., 39, 17–24, https://doi.org/10.5367/000000010791169998, 2010. a, b, c
Vanlauwe, B., Six, J., Laub, M., Mathu, S., and Mugendi, D.: ISFM/SOM long-term trials soil data, IITA [data set], https://doi.org/10.25502/wdh5-6c13/d, 2022a. a
Vanlauwe, B., Six, J., Laub, M., Mathu, S., and Mugendi, D.: ISFM/SOM long-term trials maize, IITA [data set], https://doi.org/10.25502/be9y-xh75/d, 2022b. a
Wang, Q., Barré, P., Baudin, F., Clivot, H., Ferchaud, F., Li, Y., Gao, X., and Le Noë, J.: The AMG model coupled with Rock-Eval® analysis accurately predicts cropland soil organic carbon dynamics in the Tuojiang River Basin, Southwest China, J. Environ. Manag., 345, 118850, https://doi.org/10.1016/j.jenvman.2023.118850, 2023. a
Wang, Y., Dou, F., Paustian, K. H., Grosso, S. J. D., Storlien, J. O., Wight, J. P., and Hons, F. M.: Simulating impacts of nitrogen fertilization using DAYCENT to optimize economic returns and environmental services from bioenergy sorghum production, Agron. J., 112, 4861–4878, https://doi.org/10.1002/agj2.20390, 2020. a
Wendt, J. W. and Hauser, S.: An equivalent soil mass procedure for monitoring soil organic carbon in multiple soil layers, Eur. J. Soil Sci., 64, 58–65, https://doi.org/10.1111/ejss.12002, 2013. a
World-Bank: Arable land (% of land area) – Kenya – Data, https://data.worldbank.org/indicator/AG.LND.ARBL.ZS?locations=KE (last access: 21 April 2021), 2021a. a
World-Bank: Prevalence of severe food insecurity in the population (%) – Kenya, World, Sub-Saharan Africa, Malawi – Data, https://data.worldbank.org/indicator/SN.ITK.SVFI.ZS?locations=KE-1W-ZG-MW (last access: 21 April 2021), 2021b. a
Xiao, Q., Huang, Y., Wu, L., Tian, Y., Wang, Q., Wang, B., Xu, M., and Zhang, W.: Long-term manuring increases microbial carbon use efficiency and mitigates priming effect via alleviated soil acidification and resource limitation, Biol. Fertil. Soil., 57, 925–934, https://doi.org/10.1007/s00374-021-01583-z, 2021. a
Yang, Y., Ogle, S., Grosso, S. D., Mueller, N., Spencer, S., and Ray, D.: Regionalizing crop types to enhance global ecosystem modeling of maize production, Environ. Res. Lett., 17, 014013, https://doi.org/10.1088/1748-9326/ac3f06, 2021. a, b, c, d
Zhai, R., Tao, F., Lall, U., and Elliott, J.: Africa Would Need to Import More Maize in the Future Even Under 1.5 °C Warming Scenario, Earth's Future, 9, e2020EF001574, https://doi.org/10.1029/2020EF001574, 2021. a
Zhang, Y. and Yu, Q.: Does agroecosystem model improvement increase simulation accuracy for agricultural N2O emissions?, Agr. Forest Meteorol., 297, 108281, https://doi.org/10.1016/j.agrformet.2020.108281, 2021. a
Zhou, W., Guan, K., Peng, B., Margenot, A., Lee, D., Tang, J., Jin, Z., Grant, R., DeLucia, E., Qin, Z., Wander, M. M., and Wang, S.: How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the US Midwest?, Geoderma, 429, 116254, https://doi.org/10.1016/j.geoderma.2022.116254, 2023. a, b
Zimmermann, M., Leifeld, J., Schmidt, M. W. I., Smith, P., and Fuhrer, J.: Measured soil organic matter fractions can be related to pools in the RothC model, Eur. J. Soil Sci., 58, 658–667, https://doi.org/10.1111/j.1365-2389.2006.00855.x, 2007. a
Short summary
We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
We used the DayCent model to assess the potential impact of integrated soil fertility management...
Altmetrics
Final-revised paper
Preprint