Soil microbial communities underpin ecosystem functions critical for sustainable agriculture, yet our understanding of how long-term management of tropical agroecosystems shapes these communities remains limited. This is particularly the case in sub-Saharan Africa where soil health challenges are most acute for food security. Using four long-term (~20 years) experiments across contrasting agroecological zones in Kenya, we studied how organic inputs (farmyard manure, Tithonia diversifolia, Zea mays stover; applied at 4 Mg C ha-1 year-1) and nitrogen fertilizer (±120 kg N ha-1 per season as calcium ammonium nitrate) affect soil microbial communities. We combined amplicon sequencing of prokaryotic (16S rRNA) and fungal (ITS2) communities with quantification of nitrogen-cycling functional genes to examine microbial diversity, community composition, and functional potential. Site-level edaphic properties were the main correlate of community variation, namely 30% and 28% of prokaryotic and fungal β-diversity, respectively. Despite this strong environmental control, farmyard manure created distinguishable community patterns across all sites, significantly affecting 65 prokaryotic genera and achieving 96% reclassification success for fungal communities. Prokaryotic and fungal communities exhibited contrasting response patterns: prokaryotes responded predominantly to farmyard manure through enrichment of copiotrophic Bacillota (formerly Firmicutes), while fungi were sensitive to both farmyard manure and T. diversifolia green manure, recruiting distinct decomposer guilds based on substrate biochemistry. Functional gene responses were amplified at the driest, most nutrient-poor site, where farmyard manure led to a 30-fold increase in the abundance of ammonia-oxidizing bacteria compared to the control treatment. Mineral nitrogen fertilization alone did not produce distinct community composition but modestly reduced specific nitrogen-cycling genes. This demonstrates that organic resource management, not mineral inputs, drives long-term microbial community development. These findings provide decadal-scale evidence that sustained organic amendments can generate predictable microbial responses across environmentally heterogeneous tropical landscapes, informing integrated soil fertility management strategies for sub-Saharan Africa.

Climate change is projected to exacerbate food insecurity in sub-Saharan Africa (SSA) by reducing crop yields and soil fertility. Many climate change impact studies in SSA have overlooked long-term effects of soil fertility on crop yield. We evaluated maize yields under different scenarios of soil fertility (using soil organic carbon as a proxy) and climate change (considering changes in temperature, rainfall, and CO2) at four sites in SSA. Using an ensemble of 15 calibrated soil-crop models, we found a strong consensus that, without fertilization, soil fertility declines over time, impacting maize yields more strongly than changes in temperature, rainfall, or CO2. The model ensemble indicated that when accounting for soil fertility changes, the yield benefits of combined application of organic and mineral inputs increase over time, even under climate change. These findings highlight the importance of considering long-term change in soil fertility when assessing impacts of climate change and integrated nutrient management on crop production in SSA.

Soil degradation severely limits agricultural productivity and food security across sub-Saharan Africa, particularly due to declining soil functions related to nutrient cycling, organic matter turnover, and water retention. Addressing this challenge requires management practices that can regenerate and sustain these functions, as well as sensitive indicators to track progress. In this study, we evaluated the effects of crop diversification, legume integration, manure application, and their impacts on soil health across four sites representing contrasting agroecological settings in Kenya. All sites contained long-term experiments that were recently redesigned from maize monoculture to include more diversified systems, such as maize-legume rotations, maize-fodder relay, and improved intercropping. We assessed soil health indicators linked to carbon (C) cycling (permanganate oxidizable C, POXC; particulate organic matter, POM), nutrient availability (potentially mineralizable nitrogen, PMN, available N and Phosphorus, pH), and substrate-induced respiration (SIR)rates. Within one year of implementation, crop diversification had improved soil health indicators relative to a degraded control soil, although the magnitude of improvement varied by site. Sandy soils exhibited stronger increases in soil health indicators compared to clay soils. Legume integration had a stronger influence on SIR than manure inputs (evenness decreased from similar to 2.0 to similar to 1.3 in legume systems), contributing to more specialized respiration patterns linked to labile C, likely root derived substrates. Manure application generally improved available P and PMN, though effects varied by site and cropping system. Mineral N fertilizer application contributed to soil acidification (pH decreased by 0.3-0.6 units) despite recent liming but had limited effects on other soil health indicators. Microbial activity was driven primarily by cropping treatments rather than site, whereas other soil health parameters were sensitive to both treatment and site differences. Our findings highlight that integrating legumes and applying organic amendments can initiate rapid improvements in key soil properties and functions, but agroecological context and crop type strongly modulate these outcomes.

Silvopasture systems could be effective carbon sinks but their mitigation potential across geo-climatic gradients and management regimes remains understudied. To address this, we compared the simulated establishment of high-density hybrid walnut (Juglans regia x nigra) silvopasture across Europe over 30 years using DayCent with different scenarios and assumptions: regional-scale simulations with i) country-specific nitrogen (N) input rates, and ii) similar medium N input (∼100 kg N ha-1 yr-1), contrasted with iii) country-scale scenarios, co-designed with stakeholders (for the Netherlands, Switzerland, and Spain). Simulated regional greenhouse gas (GHG) mitigation potential (from CO2 plus N2O) was largely driven by net primary productivity and N availability. Mitigation potentials of the similar N input rates scenario were around 1 t CO2-Ceq ha-1 yr-1 between 43 and 52° N latitude, up to 2 t CO2-Ceq ha-1 yr-1 in the most suitable area. For the high Belgian and Dutch N input rates (250-400 kg N ha-1 yr-1), the country-specific N input scenario suggested even higher mitigation potentials, but it is possible that this was an artifact of oversensitivity of DayCent to N, and requires further field investigation. The mitigation potentials at lower latitudes in both regional scenarios ranged from 0.7 t CO2-Ceq ha-1 yr-1 to no mitigation. Except for Switzerland, mitigation potentials of country-scale scenarios correlated strongly with those of regional simulations (R2 of 0.97 across all three countries; 0.88, 0.77, and 0.43 for the Netherlands, Spain and Switzerland, respectively), despite varying N input rates within the Netherlands and replacing walnut by Quercus ilex/suber trees in Spain. Thus, geo-climatic productivity constraints dominated the simulated GHG mitigation potential while management choices influenced the degree of its realization, especially in mountainous Switzerland.

Arable soils are generally characterised by a low soil organic carbon (SOC) content, with negative consequences for soil health, crop yield and global climate. Thus, over the past decades, there has been a focus on how agricultural management practices, such as organic resource amendments, can increase the amount of SOC. To sustainably increase SOC stocks, a portion of the organic resources added to the soil has to be stabilised in persistent fractions such as mineral-associated organic carbon (MAOC). However, there is a lack of research on the magnitude of changes in MAOC in tropical agroecosystems in response to organic resource amendments. Here, we show for four long-term field trials in Kenya that the addition of large amounts of organic resources (farmyard manure or Tithonia diversifolia biomass at 4 t C ha1 yr-1 for 16 to 19 years) to maize monocropping systems had variable effects on topsoil MAOC stocks (0-15 cm depth), and no significant effect on subsoil MAOC stocks (15-50 cm depth) compared to a control treatment. The addition of mineral N fertiliser did not affect MAOC stocks at any site. Using the distinct stable carbon isotopic signature (delta 13C) of the maize crop (C4) and the Tithonia amendments (C3), we calculated that the portion of topsoil MAOC originating from Tithonia biomass was larger in the sandy (25 %-40 %) compared to the clayey soils (0.5 %-12 %), while the portion of total added Tithonia biomass that was stabilised over a time period of 16-19 years was below 7 % across all sites, or a SOC stabilisation rate of 0.8-27 g C m-2 yr-1. Using these results, we conclude that while in sandy soils the stabilisation of added OC contributed substantially to limiting SOC losses upon cultivation, this was not the case for clayey soils. These differences were due to the much lower SOC stocks in the sandy soils, compared to the clayey soils. Our results underline the challenges associated with improving soil health in sub-Saharan Africa and stress the need for more research to reliably assess if and how organic resource amendments can be stabilised over decadal time scales in highly weathered tropical soils.

Land-based mitigation technologies and practices (LMTs) are central to climate policy scenarios that limit global warming to below 2 °C and ideally 1.5 °C by reducing carbon dioxide emissions and enhancing carbon dioxide removals from the atmosphere. Reliable estimates of their mitigation potential are essential for informing climate policies across spatial scales and governance levels. However, assessments must move beyond maximum technical potential to account for environmental constraints, social equity, competing land uses and barriers to large-scale deployment. We argue for an analytical framework that integrates numerical modelling with stakeholder engagement in integrated transdisciplinary analyses. This approach enables equitable coproduction of knowledge and supports a deeper understanding of the complex interactions between social and environmental processes that shape the implementation and governance of LMTs, thereby improving their realistic contribution to climate change mitigation and broader socioeconomic objectives.

Context: The global shift toward sustainable agriculture has increased interest in using process-based models to design and optimize intercropping systems. However, these models differ fundamentally in how they represent trade-offs (competition for light, water, and nutrients) and synergies (facilitation, complementarity) in resource sharing between species. This conceptual variation creates uncertainty in model selection and application, particularly since most models were originally developed for monoculture and subsequently adapted for intercropping. Objective: In this study, we describe how current crop models represent interspecies resource-sharing mechanisms, analyse their structural differences, and synthesize findings from existing validation studies to understand how their structural differences affect model performance. The models examined include APSIM (APSIM-Canopy, APSIM-Micromet, APSIM-Strip, APSIM-Alternating, APSIM-APSwim, APSIM-SoilArbitrator), DayCent, DSSAT-Mixed, DSSAT-MPI, LandscapeDNDC, LUCIA, MONICA, SIMPLACE Lintul5-Intercrop, STICS-Big-Leaf, STICS-Multilayer, and WaNuLCAS. Methods: Through the Agricultural Model Intercomparison and Improvement Project (AgMIP) platform, we engaged with model developers and expert users to collect detailed information on how crop models represent intercropping systems using structured interviews and questionnaires. We then developed a framework that groups models by their core conceptual approaches to simulating resource sharing. Finally, we synthesize findings from existing quantitative validation studies to connect conceptual intercomparison to predictive performance across different intercrop characteristics and environments. Results and Conclusions: Our analysis identifies six distinct conceptual approaches for simulating light sharing and four for belowground resource (water and nutrient) competition. Intercrop models show greater structural divergence in canopy than in belowground representation. Furthermore, competitive trade-offs (light, water, and nutrients) are widely represented while facilitative and other complex processes like Na-fixation, plasticity (shoot and root), microclimate effects or hydraulic lift are often simplified or omitted. Our analysis of model validation studies reveals a critical trade-off: structurally complex models often perform well in simulating intercropping when calibration is done on sole crops, whereas simpler models require extensive intercrop-specific calibration to achieve better prediction performance. This distinction is vital for model application in data-scarce environments, as more complex architectures can leverage existing sole-crop data to effectively simulate intercrop systems. The classification of the structural resource capture differences in combination with the evaluated model performance analysis allowed us to devise an evidence-based model selection criteria framework useful also for for non-specialist, while the unique detailed description provided are highly valuable for the model research community. Significance: This study establishes a conceptual framework that provides the necessary foundation for a meaningful quantitative intercomparison of intercrop models, as structural understanding enables the interpretation of numerical differences in model outputs. It also guides hypothesis testing, model choice, priorities in model development and improvements.

Problem: Low crop yields in sub-Saharan Africa mainly result from low soil fertility and insufficient nutrient inputs. A key component of Integrated Soil Fertility Management (ISFM), namely combining inputs of mineral fertilizers and organic resources, presents an opportunity to boost yields and maintain soil organic carbon (SOC) stocks in the long run. Soil-crop models help to assess the performance of ISFM under contrasting soil, climate, and management combinations. Yet, to date, most soil-crop models have been calibrated and tested in temperate conditions. Objective: Our objective was to evaluate and compare the performance of two different soil-crop models, DayCent and STICS, to represent crop yields and SOC dynamics under contrasting organic resource amendments. Methods: We used a large dataset representing 3384 cropping situations (site x season x treatment) from four long-term experiments in Kenya. Each experiment included the same treatments with the addition of two quantities of low- to high-quality organic resource amendments (high vs low C/N ratio, respectively), with (+N) and without (-N) mineral nitrogen fertilizer. Each treatment included a cropped and uncropped subplot, allowing for a unique stepwise calibration of soil and crop parameters. Results: Both models represented SOC and yield dynamics with similar accuracy across sites and treatments. They reproduced SOC dynamics well (nRMSE below 30 %) in the two clayey soils sites but not in the two sandy soils. Yet, in most sites they reproduced well SOC differences between high (Farmyard manure, Thithonia and Calliandra) and low-quality (maize stover and sawdust) organic resources. Models reproduced the average yield across sites and treatments similarly. They reproduced the positive effects of high-quality organic resources and the addition of mineral N on maize yield well. Models had similar inaccuracy in reproducing yield and yield variability under poor-quality organic resources and -N treatments. Conclusion: The stepwise calibration approach used in this study enabled highlighting the models' strengths and weaknesses in soil and plant simulations. The results suggest that the two models have similar strengths and struggle with the same problems despite having different structures. Collecting detailed plant (leaf area index, plant N uptake) and soil (water, nitrogen dynamics) in-season data from long-term experiments will be critical to exploit the full model complexity and improve their accuracy for tropical conditions.

Abstract. Agriculture is the dominant source of anthropogenic nitrous oxide (N2O), a potent greenhouse gas with a high global warming potential. In Switzerland, substantial changes in fertiliser use alongside climatic conditions have occurred over the past four decades, yet the relative contributions of management practices versus environmental change to long-term N2O emission trends remain incompletely understood. Here, we applied the biogeochemical model DayCent at 1 km resolution across Switzerland, integrating spatially explicit datasets on climate, soil properties and agricultural management, to quantify N2O emissions for the period 1981–2020 from croplands and grasslands and attribute emission changes to management versus climate drivers. Simulated national N2O emissions from agricultural soils declined by roughly 5 % from 4.0 to 3.8 kt N yr⁻¹ between the 1980s and 2010s, primarily due to a 25 % reduction in N fertiliser use. Our attribution simulations suggested that under real climate conditions, such a decrease in fertiliser N inputs (–25 %) over the period studied lowered emissions by 15.2 % in croplands and by 12.0 % in grasslands (including permanent meadows and pastures, and high alpine summer pastures). However, compared to a control scenario (in the absence of climate change), rising temperatures over the past 40 years offset these gains, increasing emissions by 5.7 % in croplands and 13.6 % in grasslands. These results show that warming-induced N2O emissions partially negate mitigation from improved fertiliser management, highlighting the need for integrated agricultural N2O mitigation strategies that are resilient to future warming.

Context: To avoid soil fertility decline and increased greenhouse gas (GHG) emissions, it has been recommended to improve maize yields in sub-Saharan Africa with sustainable practices such as Integrated Soil Fertility Management (ISFM), instead of relying solely on mineral fertilizer. However, the yield responses and environmental trade-offs of ISFM likely depend on soil and climatic conditions. Objective: To explore this, we used the DayCent model to simulate 30-year average yields of maize monoculture across Kenya under 17 different ISFM scenarios, co-created with Kenyan smallholder farmers. We compared yields, changes in SOC stocks and N2O emissions against current baseline conditions (monocropping with minimal nutrient inputs). Methods: The scenario that best represented a 'feasible-input' level consisted of 2 t C ha-1 yr-1 of farmyard manure and 60 kg N ha-1 season-1 of mineral fertilizer. Other scenarios included different amounts (0, 1, and 2 t C ha-1 yr-1) and types of organic inputs in combination with four rates of mineral N fertilizer (0, 30, 60, and 90 kg N ha-1 season-1). The uncertainty of model predictions was quantified through Monte Carlo simulations. Results and Conclusions: The model results indicate a significant potential for yield improvements in the humid regions of western Kenya (from 3.7 to 8.1 t ha-1 yr-1) with the 'feasible-input' compared to the baseline scenario; GHG emissions per kg of yield were generally lower (the median value reduced from 0.9 to 0.5 kg CO2-eq kg-1 yield). However, in the semi-arid regions of eastern Kenya, maximum yields under any scenario were 1.1 t ha-1 yr-1, reached at inputs of 1 t C farmyard manure ha-1 yr-1 or 60 kg mineral N ha-1 season-1. The uncertainty analysis showed a high confidence in the 'feasible-input' scenario's ability to increase yields and reduce SOC losses compared to the baseline, but a high uncertainty regarding its impact on GHG emissions. Specifically, the 95% credibility intervals for the combined CO2 and N2O emissions ranged from reductions of up to 1000 kg CO2-eq ha-1 yr-1 to increases of up to 200 kg CO2-eq ha-1 yr-1. Significance: These results strongly support the use of ISFM practices to enhance maize yields and mitigate soil fertility losses, particularly in areas with sufficient rainfall. However, due to the high uncertainty surrounding simulated N2O emissions, we cannot establish with certainty whether ISFM reduces GHG emissions on a per hectare basis or increases them.

Background With the adoption of the 2015 Paris Agreement, the global community committed to limiting the rise in global temperatures to below 2°C. Achieving this goal requires reductions in greenhouse gas emissions and the implementation of Carbon Dioxide Removals (CDRs). Among the 1,202 climate scenarios outlined in the IPCC AR6 report, over half depend on large-scale deployment of CDRs. A key category of CDRs is Nature-based Solutions (NbS), which includes land management among its practices, and holds an estimated global mitigation potential of over 10 GtCO2 per year. This paper addresses land-based NbS. Heavy reliance on NbS for mitigation can be risky if their potential is overestimated or if their implementation does not account for climate and social impacts, making a deeper understanding of their environmental effects and the perceptions of those implementing the practices essential. Methods This study explores stakeholder perceptions of the environmental impacts and climate risks associated with various NbS through interviews with 97 participants from 12 countries by focusing on well-established practices, such as afforestation, reforestation, sustainable agriculture, agroforestry, and wetland management. Results The study identifies rain irregularity, heavy rainfall, heatwaves, and erosion as major perceived climate risks to NbS, with stakeholders particularly valuing NbS for their role in enhancing climate adaptation and resilience against the effects of climate change and climate extremes. While carbon sequestration is a recognized benefit, the primary drivers for implementing NbS are their adaptation and resilience benefits. Conclusions The upscaling of NbS faces significant barriers, such as high initial costs, bureaucratic obstacles, and inadequate policy support. The findings emphasize the need to bridge the gap between policies, focused mainly on mitigation following a top-down approach, and the land users’s immediate need for adaptation, suggesting that recognizing both aspects could enhance the effectiveness of NbS in tackling global climate challenges.

To ensure the sustainable management of tropical cropping systems, tracking changes in soil fertility and distinguishing long-term crop yield trends from season-to-season fluctuations are essential. However, a scarcity of long-term datasets for tropical systems has left a gap in understanding how soil organic carbon (SOC, used as a proxy for soil fertility) and yield co-evolve in these systems. Here, we present a unique analysis of maize yield and SOC trends in four long-term experiments in Kenya, conducted under contrasting pedo-climatic conditions. Experimental treatments consisted of yearly applications of organic resources with different C:N ratios (12 to 200) at two quantities (1.2 and 4 t C ha-1 yr-1), with and without mineral nitrogen fertilizer (240 kg ha-1 yr-1). At sites with adequate rainfall (475-600 mm in-season rainfall), long-term Maintenance of Maize yields and SOC were strongly correlated. Specifically, 74% of the variation in long-term yield trends across sites was explained by the interaction between site and the trend in SOC, increasing to 84% when adding the interaction with the mineral nitrogen fertilizer treatment. In contrast, no significant correlation between yield and SOC trends existed at the driest site (300 mm in-season rainfall). Differences in the strength of the SOC-yield relationships between treatments with and without mineral N fertilizer were significant at only one of the four sites. In addition, seasonal maize yield variability at three of the four sites was strongly influenced by seasonal mean temperature and total rainfall, overriding the effect of site fertility and SOC in any given season. However, the strength of climate effects varied between sites. We conclude that maintaining SOC is important for sustaining maize yields, but this potential can only be fully realized under favorable climatic conditions, particularly sufficient rainfall.

Agroforestry can offer carbon sequestration, higher system productivity and biodiversity. However, a limited number of field experiments exist to study their feasibility and trade-offs for large scale deployment. Agroecosystem models could represent a valuable tool for their ex ante assessment. Here, we present ZonalCent, a novel approach to use the DayCent model to simulate multi-component agroforestry systems by splitting them into several independent zones, and simulating each zone individually. We used six agroforestry sites in France to evaluate how well ZonalCent represented carbon sequestration in tree biomass, soil organic carbon stocks and in the total system. This proved promising because with the default parameter set of DayCent, ZonalCent was highly suitable to represent tree carbon sequestration (Nash–Sutcliffe modelling efficiency; NSE of 0.86), and suitable for total system carbon sequestration potential (NSE of 0.55), despite a tendency to overestimate SOC stocks (NSE of 0.38). Only one site had yield data and there, ZonalCent approach could approximate the mean yield reduction—yet more detailed evaluation is necessary. Negative correlations showed that simulated yield was most strongly affected by (a) shading by mature trees and (b) the loss of arable area due to grass strips. While more detailed models may be needed for a detailed process understanding, ZonalCent includes the most important interactions (light, water, nutrients, temperature) in a simple but effective way and can be readily used—because it is based on DayCent—to estimate the potential carbon sequestration of agroforestry systems at larger scales.

Accurate and timely estimation of carbon sequestration in soil and forest biomass is crucial for applications such as carbon stock assessment, forest degradation monitoring, and climate change mitigation. Traditional methods such as field inventories, remote sensing, and biogeochemical models each have strengths and limitations, particularly in data-scarce regions. To address these challenges, this study integrates the light-use efficiency based ETLook model, which is driven by remotely sensed data, with the biogeochemical model DayCent, which is driven by management and weather data, to spatially model aboveground biomass and carbon sequestration. This novel approach aims to improve carbon sequestration estimates in a case study area in Burkina Faso, where ongoing political instability severely limits the availability of field data. In the absence of ground-truth data, we compare the outputs from DayCent and ETLook across time and space to build confidence in our estimates. Our findings indicate that, despite being driven by different input data, the DayCent model closely matches the aboveground biomass patterns observed in the ETLook model, with an r2 value of 0.81, a Kling-Gupta efficiency (KGE) of 0.77, low bias, and consistent seasonal patterns. Since ETLook lacks a soil carbon module, combining its Net Primary Productivity (NPP) and growth estimates with DayCent’s soil organic carbon (SOC) outputs provides a more robust estimate of total carbon sequestration than either model alone. Future work will focus on applying this hybrid approach across different ecological and geographical regions to evaluate its broader applicability.

Maize productivity in sub-Saharan Africa often falls below its potential due to soil fertility challenges. Researchers assessed the potential to counteract soil organic carbon (SOC) losses and yield declines using different organic resource treatments, with and without mineral nitrogen (N) fertilizer. While all treatments that received mineral N had similar yields in the first year, the application of farmyard manure (FYM) combined with mineral N was the only treatment that did not lose yields over the two decades, eventually outperforming all others. The results suggest that combining FYM with mineral N is the most effective of all tested strategies for simultaneously sustaining maize yields and SOC levels in similar tropical soils.

Food insecurity in sub-Saharan Africa is partly due to low staple crop yields, resulting from poor soil fertility and low nutrient inputs. Integrated soil fertility management (ISFM), which includes the combined use of mineral and organic fertilizers, can contribute to increasing yields and sustaining soil organic carbon (SOC) in the long term. Soil-crop simulation models can help assess the performance and trade-offs of a range of crop management practices including ISFM, under current and future climate. Yet, uncertainty in model simulations can be high, resulting from poor model calibration and/or inadequate model structure. Multi-model simulations have been shown to be more robust than those with single models and help understand and reduce modelling uncertainty. In this study, we aim to perform the first multi-model comparison for long-term simulations of crop yield and SOC and their feedbacks in SSA. We evaluated the performance of 16 soil-crop models using data from four long-term maize experiments at sites in SSA with contrasting climates and soils. Each experiment had four treatments: i) no exogenous inputs, ii) addition of mineral nitrogen (N) fertilizer, iii) use of organic amendments, and iv) combined use of mineral and organic inputs. We assessed model performance in two steps: through blind calibration involving a minimum level of experimental data provided to the modeling teams, and subsequently through full calibration, which included a more extensive set of observational data. Model ensemble accuracy was greater with full calibration than blind calibration. Improvement in model accuracy was larger for maize yields (nRMSE 48 vs 18%) than for topsoil SOC (nRMSE 22 vs 14%). Model ensemble uncertainty (defined as the coefficient of variation across the 16 models) increased over the duration of the long-term experiments. Uncertainty of SOC simulations increased when organic amendments were used, whilst uncertainty of yield predictions was largest when no inputs were applied. Our study revealed large discrepancies among the models in simulating i) crop-to-soil feedbacks due to uncertainties in simulated carbon coming from roots, and ii) soil-to-crop feedbacks due to large uncertainties in simulated crop N supply from soil organic matter decomposition. These discrepancies were largest when organic amendments were applied. The results highlight the need for long-term experiments in which root and soil N dynamics are monitored. This will provide the corresponding data to improve and calibrate soil-crop models, which will lead to more robust and reliable simulations of SOC and crop productivity, and their interactions.

The concept of soil organic carbon (SOC) saturation emerged a bit more than 2 decades ago as our mechanistic understanding of SOC stabilization increased. Recently, the further testing of the concept across a wide range of soil types and environments has led some people to challenge the fundamentals of soil C saturation. Here, we argue that, to test this concept, one should pay attention to six fundamental principles or “rights” (R's): 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 a maximum of C stabilized by minerals and estimate based on current data available that this maximum stabilization is around 82 ± 4 g C kg−1 silt + clay for 2 : 1-clay-dominated soils while most likely being only around 46 ± 4 g C kg−1 silt + clay for 1 : 1-clay-dominated soils. These estimates can be further improved using more data, especially for different clay types across varying environmental conditions. However, the bigger challenge is a matter of which C sequestration strategies to implement and how to implement them in order to effectively reach this 82/46 g C kg−1 silt + clay in soils across the globe.

Long-term experiments (LTEs) are critical for evaluating strategies that can maintain or increase crop yields, soil fertility and soil organic carbon (SOC), and help adapt to climate change. Yet, scientific knowledge is advancing and research questions are evolving. Therefore, it is important to review the objectives of LTEs over time. A change in their design may be necessary to keep the experimental treatments scientifically interesting, innovative, and relevant in the context of evolving agricultural challenges. Here, we describe the process of redesigning four LTEs in Kenya. These LTEs are unique in that they represent four different pedoclimatic conditions but with identical experimental treatments across sites. Initially, they focused on investigating how to maintain or increase SOC and maize yields over time by applying a combination of mineral nitrogen (N) and external organic resources. Specifically, the experimental treatments consisted of maize monoculture with different rates (1.2 and 4 t C ha(-1) yr(-1)) and qualities of organic resources, either with or without mineral N fertilizer input. After about 20 years, it became clear that SOC was lost in most treatments. Therefore, continuing with the current experimental design was not an option. Taking advantage of the fact that the different former treatments led to different levels of soil degradation, we redesigned the LTEs to study the effectiveness of regenerative cropping strategies in rebuilding SOC and increasing crop yields starting from the different levels of soil degradation. The focus shifted from external to in situ organic inputs by increasing the root biomass of the cultivated crops. The newly established cropping system treatments are maize-legume rotation, maize-legume intercropping (double row configuration) and relay intercropping of maize with forage grass. A key finding from the previous phase of the experiments, namely, that external organic inputs with low C:N ratios are most efficient in building SOC, has been incorporated into the redesign. The relative contribution of external versus in situ organic resources is tested by splitting the cropping system treatments into those receiving either farmyard manure or green manure in the form of Tithonia diversifolia prunings and those receiving no external inputs. Split-plot treatments with and without mineral N were retained. The overall objective of studying mechanisms of tropical soil fertility maintenance and, more specifically, SOC formation, remained unchanged. However, the redesign aligned the LTEs with the current state of knowledge and pressing research questions, specifically focusing on the relative effectiveness of in-situ versus external organic inputs in SOC formation.

Sustainable intensification schemes such as integrated soil fertility management (ISFM) are a proposed strategy to close yield gaps, increase soil fertility, and achieve food security in sub-Saharan Africa. Biogeochemical models such as DayCent can assess their potential at larger scales, but these models need to be calibrated to new environments and rigorously tested for accuracy. Here, we present a Bayesian calibration of DayCent, using data from four long-term field experiments in Kenya in a leave-one-site-out cross-validation approach. The experimental treatments consisted of the addition of low- to high-quality organic resources, with and without mineral nitrogen fertilizer. We assessed the potential of DayCent to accurately simulate the key elements of sustainable intensification, including (1) yield, (2) the changes in soil organic carbon (SOC), and (3) the greenhouse gas (GHG) balance of CO2 and N2O combined. Compared to the initial parameters, the cross-validation showed improved DayCent simulations of maize grain yield (with the Nash–Sutcliffe model efficiency (EF) increasing from 0.36 to 0.50) and of SOC stock changes (with EF increasing from 0.36 to 0.55). The simulations of maize yield and those of SOC stock changes also improved by site (with site-specific EF ranging between 0.15 and 0.38 for maize yield and between −0.9 and 0.58 for SOC stock changes). The four cross-validation-derived posterior parameter distributions (leaving out one site each) were similar in all but one parameter. Together with the model performance for the different sites in cross-validation, this indicated the robustness of the DayCent model parameterization and its reliability for the conditions in Kenya. While DayCent poorly reproduced daily N2O emissions (with EF ranging between −0.44 and −0.03 by site), cumulative seasonal N2O emissions were simulated more accurately (EF ranging between 0.06 and 0.69 by site). The simulated yield-scaled GHG balance was highest in control treatments without N addition (between 0.8 and 1.8 kg CO2 equivalent per kg grain yield across sites) and was about 30 % to 40 % lower in the treatment that combined the application of mineral N and of manure at a rate of 1.2 t C ha−1 yr−1. In conclusion, our results indicate that DayCent is well suited for estimating the impact of ISFM on maize yield and SOC changes. They also indicate that the trade-off between maize yield and GHG balance is stronger in low-fertility sites and that preventing SOC losses, while difficult to achieve through the addition of external organic resources, is a priority for the sustainable intensification of maize production in Kenya.