Abstract The stability of cropping systems in a changing climate context depends on numerous factors, including row orientation, to optimize the use of environmental resources. This study aimed to evaluate the performance of agricultural systems based on the row orientation of cowpea (Vigna unguiculata) and maize (Zea mays) in three different ecological conditions in Côte d’Ivoire, in 2020 and 2021. An experimental design with plots divided into three complete randomized blocks with six subplots per block and three repetitions was set up, varying the row orientation in intercropping and monoculture. Row orientation, cropping system used, and ecological zone significantly influenced crop yield and its components. In intercropping, cowpea (tiligré) showed the best yields when oriented North–South (NS) in the tropical rainforest zone and the sub-Sudanian savannah, while East–West (EW) orientation was optimal in the forest-savannah mosaic zone. In contrast, maize (GMRP18) yielded the best in intercropping when rows were oriented East–West, regardless of the season. In monoculture, cowpea yielded best when oriented EW in the tropical rainforest zone (488.17 kg ha−1) and in the forest-savannah mosaic zone (1262.12 kg ha−1), while NS orientations were preferable (228.6 and 259.54 kg ha−1) in the sub-Sudanian savannah zone. For maize monoculture, EW orientation was also preferable. Throughout the study, for both seasons, the highest yield advantages in maize-cowpea intercropping were obtained in EW orientation, regardless of the ecological zone. Overall, the forest-savannah mosaic zone yielded the best cowpea yields (1262.12 and 663.9 kg ha−1).

Abstract To solve fertility problems, most smallholder farmers in sub-Saharan Africa use fallow periods. However, population growth along with land shortage tend to shorten the duration of fallows, resulting in a steady decline in soil fertility. Assuming that nitrogen (N) plays a key role in soil fertility, we designed an ecological model describing N cycle in a cropping system. We examined the impact of different processes involved in N cycle, including mineralization, nitrification and fallow characteristics on the yield of a maize crop in a humid savanna, Côte d’Ivoire. The objective of this study was to explore ways to maintain N supply in N poor soils by identifying the appropriate levers and practices. The model revealed that in low input agricultural systems, soil fertility is maintained by the dynamics of soil organic matter and mineralization. We showed that, variation in nitrification during the cropping cycle (fallow-crop) does not have a significant effect on maize yield. However, with the addition of N fertilizers, reduced nitrification significantly increases crop yield. Indeed, low nitrification increases the efficiency of fertilizer use, which reduces the negative impact of excessive N fertilizer application. Furthermore, legume-based fallow was able to increase maize productivity much more than a nitrification-inhibiting fallow regardless of long duration of fallow periods. Also, the models suggested suggest that using nitrification-inhibiting grasses as cover crops for maize would be beneficial if mineral N fertilizer is used.

Aim Macroinvertebrates comprise a highly diverse set of taxa with great potential as indicators of soil quality. Communities were sampled at 3,694 sites distributed world-wide. We aimed to analyse the patterns of abundance, composition and network characteristics and their relationships to latitude, mean annual temperature and rainfall, land cover, soil texture and agricultural practices. Location Sites are distributed in 41 countries, ranging from 55 degrees S to 57 degrees N latitude, from 0 to 4,000 m in elevation, with annual rainfall ranging from 500 to >3,000 mm and mean temperatures of 5-32 degrees C. Time period 1980-2018. Major taxa studied All soil macroinvertebrates: Haplotaxida; Coleoptera; Formicidae; Arachnida; Chilopoda; Diplopoda; Diptera; Isoptera; Isopoda; Homoptera; Hemiptera; Gastropoda; Blattaria; Orthoptera; Lepidoptera; Dermaptera; and "others". Methods Standard ISO 23611-5 sampling protocol was applied at all sites. Data treatment used a set of multivariate analyses, principal components analysis (PCA) on macrofauna data transformed by Hellinger's method, multiple correspondence analysis for environmental data (latitude, elevation, temperature and average annual rainfall, type of vegetation cover) transformed into discrete classes, coinertia analysis to compare these two data sets, and bias-corrected and accelerated bootstrap tests to evaluate the part of the variance of the macrofauna data attributable to each of the environmental factors. Network analysis was performed. Each pairwise association of taxonomic units was tested against a null model considering local and regional scales, in order to avoid spurious correlations. Results Communities were separated into five clusters reflecting their densities and taxonomic richness. They were significantly influenced by climatic conditions, soil texture and vegetation cover. Abundance and diversity, highest in tropical forests (1,895 +/- 234 individuals/m(2)) and savannahs (1,796 +/- 72 individuals/m(2)), progressively decreased in tropical cropping systems (tree-associated crops, 1,358 +/- 120 individuals/m(2); pastures, 1,178 +/- 154 individuals/m(2); and annual crops, 867 +/- 62 individuals/m(2)), temperate grasslands (529 +/- 60 individuals/m(2)), forests (232 +/- 20 individuals/m(2)) and annual crops (231 +/- 24 individuals/m(2)) and temperate dry forests and shrubs (195 +/- 11 individuals/m(2)). Agricultural management decreased overall abundance by <= 54% in tropical areas and 64% in temperate areas. Connectivity varied with taxa, with dominant positive connections in litter transformers and negative connections with ecosystem engineers and Arachnida. Connectivity and modularity were higher in communities with low abundance and taxonomic richness. Main conclusions Soil macroinvertebrate communities respond to climatic, soil and land-cover conditions. All taxa, except termites, are found everywhere, and communities from the five clusters cover a wide range of geographical and environmental conditions. Agricultural practices significantly decrease abundance, although the presence of tree components alleviates this effect.

Agroforestry is part of the package of good agricultural practices (GAPs) referred to as a reference to basic environmental and operational conditions necessary for the safe, healthy, and sustainable production of cocoa. Furthermore, cocoa agroforestry is one of the most effective nature-based solutions to address global change including land degradation, nutrient depletion, climate change, biodiversity loss, food and nutrition insecurity, and rural poverty and current cocoa supply chain issues. This study was carried out in South-Western Côte d’Ivoire through a household survey to assess the willingness of cocoa farmers to adopt cocoa agroforestry, a key step towards achieving sustainability in the cocoa supply chain markedly threatened by all types of biophysical and socio-economic challenges. In total, 910 cocoa households were randomly selected and individually interviewed using a structured questionnaire. Findings revealed that from the overwhelming proportion of farmers practicing full-sun cocoa farming with little or no companion trees associated, 50.2 to 82.1% were willing to plant and to keep fewer than 20 trees per ha in their farms for more than 20 years after planting. The most preferred trees provide a range of ecosystem services, including timber and food production, as well as shade regulation. More than half of the interviewed households considered keeping in their trees in their plantations for more than 20 years subject to the existence of a formal contract to protect their rights and tree ownership. This opinion is significantly affected by age, gender, access to seedlings of companion trees and financial resources. A bold step forward towards transitioning to cocoa agroforestry and thereby agroecological intensification lies in (i) solving the issue of land tenure and tree ownership by raising awareness about the new forest code and, particularly, the understanding of cocoa agroforestry, (ii) highlighting the added value of trees in cocoa lands, and (iii) facilitating access to improved cocoa companion tree materials and incentives. Trends emerged from this six-year-old study about potential obstacles likely to impede the adoption of agroforestry by cocoa farmers meet the conclusions of several studies recently rolled out in the same region for a sustainable cocoa sector, thereby confirming that not only the relevance of this work but also its contribution to paving the way for the promotion of agroecological transition in cocoa farming.

Plant invasion may have significant ecological and socio-economic impacts across agroecologies. Chromolaena odorata (Asteraceae) is one of the world's most invasive plants albeit it is considered a suitable fallow plant in West Africa. However, its impacts on soil biological processes are poorly understood. This study was conducted in intermingled forest and savanna sites invaded by C. odorata in Central Cote d'Ivoire (West Africa) to bridge this knowledge gap. Invaded forest sites (COFOR) were compared to adjacent natural forest fragments (FOR) while invaded savanna sites (COSAV) were compared to adjacent natural savanna fragments (SAV). Soil (0-10 cm depth) physico-chemical variables, including soil organic C (SOC), total soil N and available N and P concentrations were measured. Additionally, soil microbial biomass (MBC), carbon mineralization (C-min), acid phosphatase, beta-glucosidase, and fluorescein diacetate were measured. Further, the MBC/SOC ratio and the metabolic quotient (qCO(2)) were calculated. An index of invasion effect (IE) computed as the cumulative percent change in the microbial and enzyme activities was determined for each ecosystem context. Results showed that soil MBC and MBC/SOC ratio declined in COFOR relative to FOR. In general, Cmin, enzymatic activities, qCO(2) and available N and P significantly increased in the C. odorata sites relative to the respective reference ecosystems, particularly savanna, potentially due to a larger gap in the litters' quality. As a result, the invasion effect was twice as high in savanna (IE = 292.8%) as in forest (IE = 147.5%). However, a Principal Component Analysis showed that the COSAV were close to COFOR stands without mixing, probably due to contrasting initial soil organic matter and clay contents. These results improved our knowledge on the changes in soil microbial attributes and the mechanisms of soil fertility restoration or improvement in response to C. odorata invasion in natural forests and savannas of West Africa.

The use of earth observation data for crop mapping and monitoring in West Africa has concentrated on rainfed systems due to its pre-dominance in the sub-region. However, irrigated systems, though of limited extent, provide critical livelihood support to many. Accurate statistics on irrigated crops are, thus, needed for effective management and decision making. This study explored the use of Sentinel 1 (S-1) and Sentinel 2 (S-2) data to map the extent and yield of irrigated crops in an informal irrigation scheme in Burkina Faso. Random Forest classification and regression were used together with an extensive field data comprising 842 polygons. Four irrigated crops (tomoto, onion, green bean and other) were classified while the yield of tomatoes was modelled through regression analysis. Apart from spectral bands, derivatives (e.g. biophysical parameters and vegetation indices) from S-2 were used. Different data configuration of S-1, S-2 and their derivatives were tested to ascertain optimal temporal windows for accurate irrigated crop mapping and yield estimation. Results of the crop classification revealed a greater overall accuracy (76.3%) for S-2 compared to S-1 (69.4%), with S-2 biophysical parameters (especially the fraction of absorbed photosynthetic active radiation i.e fAPAR) being prominent. For yield prediction, however, S-1 VV polarization came up as the most prominent predictor in the regression analysis (R-adj(2) = 0.63), while the addition of S-2 fAPAR marginally improved the fit (R-adj(2) = 0.64). Tomato yield in the study area was found to range from 1 to 16 kg m(-2), although about 83% of the area have yields of less than 10 kg m(-2). Our study revealed that early season images (acquired in December) perform better in classifying irrigated crop compared to mid or late season. On the other hand, the use of early to mid-season (December to February) images for yield modelling produced reasonable prediction accuracy. This indicates the possibility of using S-1 and S-2 data to predict crop yield prior to harvest season for efficient planning and food security attainment.

High rainfall events and flash flooding are becoming more frequent, leading to severe damage to crop production and water infrastructure in Burkina Faso, Western Africa. Special attention must therefore be given to the design of water control structures to ensure their flexibility and sustainability in discharging floods, while avoiding overdrainage during dry spells. This study assesses the hydroclimatic risks and implications of floodplain climate-smart rice production in southwestern Burkina Faso in order to make informed decisions regarding floodplain development. Statistical methods (Mann-Kendall test, Sen’s slope estimator, and frequency analysis) combined with rainfall-–runoff modeling (HBV model) were used to analyze the hydroclimatic conditions of the study area. Moreover, the spatial and temporal water availability for crop growth was assessed for an innovative and participatory water management technique. From 1970 to 2013, an increasing delay in the onset of the rainy season (with a decreasing pre-humid season duration) occurred, causing difficulties in predicting the onset due to the high temporal variability of rainfall in the studied region. As a result, a warming trend was observed for the past 40 years, raising questions about its negative impact on very intensive rice cultivation packages. Farmers have both positive and negative consensual perceptions of climatic hazards. The analysis of the hydrological condition of the basin through the successfully calibrated and validated hydrological HBV model indicated no significant increase in water discharge. The sowing of rice from the 10th to 30th June has been identified as optimal in order to benefit from higher surface water flows, which can be used to irrigate and meet crop water requirements during the critical flowering and grain filling phases of rice growth. Furthermore, the installation of cofferdams to increase water levels would be potentially beneficial, subject to them not hindering channel drainage during peak flow.

The Sudanian Savanna (SS) of West Africa is characterized by tropical savannas and woodlands. Accurate estimation of AGB and carbon stocks in this biome is important for addressing sustainable development goals as the information can aid natural resource management at varied spatial scales. Previous AGB mapping efforts focused on humid forests, with little attention on savannas. This study explored the use of annual monthly time-series of Senitinel-1 (S-1) and Sentinel-2 (S-2) data to map AGB in the SS. Backscatter, spectral reflectance, and derivatives (vegetation indices and biophysical parameters) were combined with field inventory data in a Random Forest regression to map AGB. Eight experiments were conducted with different data configurations to determine: (1) the potential of S-1 and S-2 for AGB mapping, (2) optimal image acquisition period for AGB mapping, and (3) contribution of image derivatives to improving the accuracy of AGB mapping. The predicted map was validated with 40% of the inventory data. Uncertainty in the AGB was assessed using mean absolute error, root mean squared error, coefficient of determination and symmetrical mean absolute percentage error. Results show that about 90% of the study area have low AGB stocks of less than 90 Mg/ha. Compared to S-1 (RMSE: 78.6; MAE: 25.6), S-2 achieved better prediction accuracy (RMSE: 60.6; MAE: 19.2), although combination of the two according to seasonality produced the best results (RMSE: 45.4; MAE: 16.3). Images acquired in the dry season were found to be more useful for predicting AGB than those of rainy season. Also, stress-related vegetation indices and a red-edge dependent normalized difference vegetation index not tested in previous AGB studies using Sentinels were found to be significant contributors to the superior performance of S-2. Since biomass is a finite resource, our results can provide valuable information on the sustainable use of biomass and energy security including studies on carbon cycling and ecosystem functions in the region. The demonstrated possibility of using open access earth observation data to map and monitor AGB in data scarce regions is useful and beneficial to attaining SDG indicators 15.2.1 (sustainable forest management) and 15.3.1 (proportion of land that is degraded over total land area). Further work on developing species-specific wood densities and allometric equations is required to improve AGB and carbon stock estimation in the SS.

Soil organic carbon (SOC) is a key component of terrestrial ecosystems. Experimental studies have shown that soil texture and geochemistry have a strong effect on carbon stocks. However, those findings primarily rely on data from temperate regions or use model approaches that are often based on limited data from tropical and sub-tropical regions. Here, we evaluate the controls on soil carbon stocks in Africa, using a dataset of 1,580 samples. These were collected across Sub-Saharan Africa (SSA) within the framework of the Africa Soil Information Service (AfSIS) project, which was built on the well-established Land Degradation Surveillance Framework (LDSF). Samples were taken from two depths (0–20 cm and 20–50 cm) at 46 LDSF sites that were stratified according to Koeppen-Geiger climate zones. The different pH-values, clay content, exchangeable cations and extractable elements across various soils of the different climatic zones (i.e. from arid to humid (sub)tropical) allow us to identify different soil and climate parameters that best explain SOC variance across SSA. We tested if these SOC predictors differed across climatological conditions, using the ratio of potential evapotranspiration (PET) to mean annual precipitation (MAP) as indicator. For water-limited regions (PET/MAP > 1), the best predictors were climatic variables, likely because of their effect on the quantity of carbon inputs. Geochemistry dominated SOC storage in energy-limited systems (PET/MAP < 1), reflecting its effect on carbon protection. On a continental scale, climate (e.g. PET) is key to predicting SOC content in topsoil, whereas geochemistry, particularly iron-oxyhydroxides and aluminum-oxides, is more important in subsoil. Clay content had little influence on SOC at both depths. These findings contribute to an improved understanding of the controls on SOC stocks in tropical and sub-tropical regions.

Although soil degradation is a major threat to food security and carbon sequestration, our knowledge of the spatial extent of the problem and its drivers is very limited in Southern Africa. Therefore, this study aimed to quantify the risk of soil structural degradation and determine the variation in soil stoichiometry and nutrient limitations with land use categories (LUCs) and climatic zones. Using data on soil clay, silt, organic carbon (SOC), total nitrogen (N), available phosphorus (P), and sulfur (S) concentrations collected from 4,468 plots on 29 sites across Angola, Botswana, Malawi, Mozambique, Zambia and Zimbabwe, this study presents novel insights into the variations in soil structural degradation and nutrient limitations. The analysis revealed strikingly consistent stoichiometric coupling of total N, P, and S concentrations with SOC across LUCs. The only exception was on crop land where available P was decoupled from SOC. Across sample plots, the probability (φ) of severe soil structural degradation was 0.52. The probability of SOC concentrations falling below the critical value of 1.5% was 0.49. The probabilities of soil total N, available P, and S concentrations falling below their critical values were 0.95, 0.70, and 0.83, respectively. N limitation occurred with greater probability in woodland (φ = .99) and forestland (φ = .97) than in cropland (φ = .92) and grassland (φ = .90) soils. It is concluded that soil structural degradation, low SOC concentrations, and N and S limitations are widespread across Southern Africa. Therefore, significant changes in policies and practices in land management are needed to reverse the rate of soil structural degradation and increase soil carbon storage.

This study was carried out to investigate the relationship between earthworm trophic groups and soil morphology and chemical attributes, and moreover, to determine which of these attributes would be most significant in explaining the distribution of earthworm communities in agro-ecosystems in the Centre-West region of Côte d’Ivoire. Earthworms' soil morphology and soil samples were studied in three agro-ecosystems: 20-year-old cocoa plantations, 5-year-old mixed cocoa plantations and mixed crop-fields. The semi-deciduous forests near the agro-ecosystems were also sampled and considered as control plots. Earthworm global densities varied on average between 53.9 ± 7.9 and 86.0 ± 19.0 individuals m −2 and biomass between 16.5 ± 3.1 and 20.6 ± 4.1 g m −2 under these ecosystems. Path analysis produced a significant model: soil morphology and chemical attributes under different agro-ecosystems affected the density and biomass of earthworm trophic groups, and these attributes are potential regulators of the fauna communities. The morphological components related to dead leaves ( r 2 = 0.73, P < 0.05) and fine woods quantities ( r 2 = 0.71, P < 0.05) are most decisive for detritivore abundances, whereas geophageous mesohumic abundances were positively affected by soil organic carbon ( r 2 = 0.79, P < 0.05) and N ( r 2 = 0.84, P < 0.05) and geophageous polyhumic abundances were positively affected only by soil N ( r 2 = 0.63, P < 0.05). In agro-ecosystems the relationship between soil conditions and earthworm communities varied between earthworm trophic groups, so detritivores were more affected by litter quantity, whereas shallow geophageous populations were guided by soil organic matter.

Abstract Background To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on the carbon density per land use/land cover (LULC) class and in situ carbon and nitrogen data is needed. This allows a better representation of the spatial distribution of carbon and nitrogen stocks across LULC. The aim of this study was to emphasize the relevance of using in situ carbon and nitrogen content of the main tree species of the site when quantifying the aboveground carbon and nitrogen stocks in the context of carbon accounting. This paper contributes to that, by combining satellite images with in situ carbon and nitrogen content in dry matter of stem woods together with locally derived and published allometric models to estimate aboveground carbon and nitrogen stocks at the Dassari Basin in the Sudan Savannah zone in the Republic of Benin. Results The estimated mean carbon content per tree species varied from 44.28 ± 0.21% to 49.43 ± 0.27%. The overall mean carbon content in dry matter for the 277 wood samples of the 18 main tree species of the region was 47.01 ± 0.28%—which is close to the Tier 1 coefficient of 47% default value suggested by the Intergovernmental Panel on Climate Change (IPCC). The overall mean fraction of nitrogen in dry matter was estimated as 0.229 ± 0.016%. The estimated mean carbon density varied from 1.52 ± 0.14 Mg C ha−1 (for Cropland and Fallow) to 97.83 ± 27.55 Mg C ha−1 (for Eucalyptus grandis Plantation). In the same order the estimated mean nitrogen density varied from 0.008 ± 0.007 Mg ha−1 of N (for Cropland and Fallow) to 0.321 ± 0.088 Mg ha−1 of N (for Eucalyptus grandis Plantation). Conclusion The results show the relevance of using the in situ carbon and nitrogen content of the main tree species for estimating aboveground carbon and nitrogen stocks in the Sudan Savannah environment. The results provide crucial information for carbon accounting programmes related to the implementation of the REDD + initiatives in developing countries.

Integrated soil fertility management options are being promoted as ways of adapting agricultural systems to sustain yields on highly degraded and poor soils encountered throughout West Africa. The efficiency of these practices may be affected by high variability and uncertainty associated with seasonal rainfall, especially for areas such as Côte d’Ivoire, where intra-seasonal rainfall has been observed to change from 1 year to another. The DSSAT crop simulation model was used in this study as a tool to evaluate the impacts of soil improvement options including inorganic fertilizer and conservation agriculture generating higher carbon sequestration and crop yield in maize agro-ecosystems. The model was calibrated using agronomic data for three cropping seasons from 2009 to 2010 in Goulikao (Center-West Côte d’Ivoire) and Ahérémou 2 (Central Côte d’Ivoire), respectively and validated against independent datasets of yield of 2003–2004 seasons in the buffer zone of the Lamto Natural Reserve, Central Côte d’Ivoire. The model predicted average maize yields of 1454 kg ha−1 across the sites versus an observed average value of 1736 kg ha−1, R2 of 0.72, and RMSE of 597 kg ha−1 after the default values for stable soil organic matter fraction used in the model were substituted by the estimated one. For the validation, the predicted higher maize yield was consistently related to fallow biomass inputs and different rates of fertilizer, thus generating a RMSE of total aboveground biomass and grain yield of 606 kg ha−1 and 350 kg ha−1, respectively. The impact of fallow residues and cropping sequence on subsequent maize yield was simulated and compared with conventional fertilizer and control data using 12 years historic climate time series. We conclude that soil fertility improvements through conservation agriculture can sustain grain yield at the same level as conventional inputs of urea against larger climate variability. However, this system may be substituted by conventional agriculture when climate forecast reveals a dry cropping season year.

The LDSF was carried out at two-100 km2 sites within the West Africa Sentinel Landscape: Cassou and Koungoussi in Burkina Faso. Field teams were trained by Jerome Tondoh. Field surveys were completed in March 2014. The LDSF is a spatially stratified, randomized sampling design, developed to provide a biophysical baseline at landscape level and a monitoring and evaluation framework for assessing processes of land degradation and effectiveness of rehabilitation measures over time. Measured variables include: land cover, tree and shrub densities, tree biodiversity, erosion prevalence, infiltration capacity, along with an assessment of impact to habitat and occurrence of soil conservation structures. Soil samples were also collected (320 top (0-20 cm) and sub (20-50 cm) soil samples per site) and were processed in Burkina Faso. Processed samples were shipped to Nairobi and subjected to infrared spectroscopy and wet chemistry analysis. These combined data sets will be used to assess soil and ecosystem health for the landscape in more detail.

The use of crop models is motivated by the prediction of crop production under climate change and for the evaluation of climate risk adaptation strategies. Therefore, in the present study the performance of DSSAT 4.6 was evaluated in a cropping system involving integrated soil fertility management options that are being promoted as ways of adapting agricultural systems to improve both crop yield and carbon sequestration on highly degraded soils encountered throughout middle Cote d’Ivoire. Experimental data encompassed two seasons in the Guinea savanna zone. Residues from the preceding vegetation were left to dry on plots like mulch on an experimental design that comprised the following treatments: (i) herbaceous savanna-maize, (ii)10 year-old of the shrub Chromolaena odorata fallow-maize (iii) 1 or 2 year-old Lalab pupureus stand-rotation, (iv) the legume L. pupureus -maize rotation; (v) continuous maize crop fertilized with urea; (vi) continuous maize crop fertilized with triple superphosphate; (vii) continuous maize crop, fertilized with both urea and triple superphosphate (TSP); (viii) continuous maize cultivation. The model’s sensitivity analysis was run to figure out how uncertainty of stable organic carbon (SOM3) can generate variation in the prediction of soil organic carbon (SOC) dynamics during the monitoring period of two years, within the first soil layer and to estimate the most suitable value. The observed variations were of 0.05 % in total SOC within the short-term and acceptable dynamics of changes were obtained for 0.80% of SOM3. The DSSAT model was calibrated using data from the 2007-2008 season and validated against independent data sets of yield of 2008-2009 to 2011-2012 cropping seasons. After the default values for SOM3 used in the model was substituted by the estimated one from sensitivity analysis, the model predicted average maize yields of 1 454 kg ha-1 across the sites versus an observed average value of 1 736 kg ha-1, R2 of 0.72 and RMSE of 597 kg ha-1. The impact of fallow residues and cropping sequence on maize yield was simulated and compared to conventional fertilizer and control data using historical climate scenarios over 12 years. Improving soil fertility through conservation agriculture cannot maintain grain yield in the same way as conventional urea inputs, although there is better yield stability against high climate variability according to our results.

Combination of poor soil fertility and climate change and variability is the biggest obstacle to agricultural productivity in Sub-Saharan Africa. While each of these factors requires different promising adaptive and climate-resilient options, it is important to be able to disaggregate their effects. This can be accomplished with ordinary agronomic trials for soil fertility and climate year-to-year variability, but not for long-term climate change effects. In turn, by using climate historical records and scenario outputs from climate models to run dynamic models for crop growth and yield, it is possible to test the performance of crop management options in the past but also anticipate their performance under future climate change or variability. Nowadays, the overwhelming importance given to the use of crop models is motivated by the need of predicting crop production under future climate change, and outputs from running crop models may serve for devising climate risk adaptation strategies. In this study we predicted yield of one maize variety named Massongo for the time periods 1980–2010 (historical) and 2021–2050 (2030s, near future) across agronomic practices including the fertilizer input rates recommended by the national extension services (28 kg N, 20 kg P, and 13 kg K ha−1). The performance of the crop model DSSAT 4.6 for maize was first evaluated using on-farm experimental data that encompassed two seasons in the Sudano-Sahelian zone in six contrasting sites of Central West Burkina Faso. The efficiency of the crop model was evidenced by reliable simulations of total aboveground biomass and yields after calibration and validation. The root-mean-square error (RMSE) of the entire dataset for grain yield was 643 kg ha−1 and 2010 kg ha−1 for total aboveground biomass. Three regional climate change projections for Central West Burkina Faso indicate a decrease in rainfall during the growing period of maize. All the three scenarios project that the decrease in rainfall is to the tune of 3–9% in the 2030s under RCP4.5 in contrast to climate scenarios produced by the regional climate model GCM ICHEC-EC-Earth which predicted an increase of rainfall of 25% under RCP8.5. Simulations using the CERES-DSSAT model reveal that maize yields without fertilizer show the same trend as with fertilizer in response to climate change projections across RCPs. Under RCP4.5 with output from the climate model ICHEC-EC-Earth, yield can slightly increase compared to the historical baseline on average by less than 5%. In contrast, under RCP8.5, yield is increased by 13–22% with the two other climate models in fertilized and non-fertilized plots, respectively. Nevertheless, the average maize yield will stay below 2000 kg ha−1 under non-fertilized plots in RCP4.5 and with recommended mineral fertilizer rates regardless of the RCP scenarios produced by ICHEC-EC-Earth. Giving the fact that soil fertility improvement alone cannot compensate for the adverse impact of future climate on agricultural production particularly in case of high rainfall predicted by ICHEC-EC-Earth, it is recommended to combine various agricultural techniques and practices to improve uptake of nitrogen and to reduce nitrogen leaching such as the splitting of fertilizer applications, low-release nitrogen fertilizers, agroforestry, and any other soil and water conservation practices.

The agro-ecological drawbacks of the spread of rubber tree plantations in Cote d’Ivoire since 1990’s are obvious even though they have not been properly investigated. They consist of biodiversity loss, land degradation and food insecurity, which have extended to the existing cocoa-led degraded areas whose rehabilitation has unfortunately not started. This situation increases not only the threat on soil health status but also undermines the capability of soils to deliver ecosystem services that are key to sustainable agricultural production. The current study took advantage of a chronosequence in rubber tree landscapes to assess soil health deterioration in general and possibly earthworm-mediated role in soil heath changes. The hypothesis underpinning the current study was that earthworms can contribute to mitigating soil health deterioration in rubber-dominated landscapes due to their key role in soil functioning. This study confirmed that the conversion of forest into rubber tree plantations has significantly impaired all soil biological, physical and chemical parameters at the beginning (7 years) of the chronosequence followed further by a restorative trend taking place beneath the plantations in, or after, 12 years. This is due to an enabling microenvironment caused by an improved SOC storage, increased aggregate stability, exchangeable K, total phosphorus concentration in aged rubber tree plantations and the development of geophageous mesohumic earthworms. However, this study failed to evidence a direct role of earthworms in soil health rehabilitation over time. Mesoscale studies along with the use of appropriate models could help unravel this “black box” and shed some light on the contribution of earthworms as key soil ecosystem engineers.