Crop and soil organic matter simulation models – A brief review of their basic features and application in sub-Saharan Africa

Over the past decades, numerous crop-soil models have been developed to represent dynamic processes in cropland systems, including soil organic carbon (SOC) dynamics (Campbell and Paustian, 2015). These models use mathematical equations that determine carbon allocation in the vegetation and biomass and soils to represent biogeochemical processes, such as photosynthesis, respiration and decomposition. Furthermore, a range of crop management practices are represented in most of the models, enabling an assessment of their impacts on SOC in agricultural systems. Although models were initially developed for research purposes, they are increasingly becoming important in many aspects of environmental policies (Manlay et al., 2007). Extensively tested models provide effective tools that can be used in identifying sustainable land management practices across different agroecological conditions. Compared to field experiments, which are time and resource consuming, models are more effective for making predictions and understanding crop and SOC dynamics on large scales and different time scales. However, the choice of the model depends on the ability of the model to simulate key processes in the region of interest. We conducted a survey to identify the features of the commonly used crop-soil models in order to inform the choices for application in sub-Saharan Africa. The survey was administered online to the model developers. In addition, we also conducted a literature search to assess the usage of the different models in different parts of sub-Saharan. In this brief, we provide a basic summary of the information from the survey and literature review

East Africa Soil Carbon Workshop: Science to inform policy

Introduction and rationale: Global soils contain about 2344 billion tons of organic carbon. This is the largest terrestrial pool of organic carbon. Small changes in soil organic carbon (SOC) stocks could result in significant impacts on the global carbon balance. Trapping carbon in the soil contributes to reducing greenhouse gas (GHG) emissions from agriculture. Managing our soils better can also help us to adapt to a changing climate by improving soil health, soil productivity (and crop yields) and agro-ecosystem resilience. However, not all soils are the same. Geography, climate, and land use play a crucial role in how much carbon soils can potentially absorb, or how much they lose. While expectations are high – especially for degraded soils of sub-Saharan Africa – that soils can play crucial role in mitigating climate change, details on the where, how, and potential costs are missing. The East Africa Soil Carbon Workshop – Science to Inform Policy brought together 28 participants from 11 countries: Ethiopia, Kenya, Uganda, Rwanda, Tanzania, South Africa, Madagascar, Germany, France, Netherlands, and Sweden (10 women and 18 men). Participants included decision makers, practitioners and implementers, and researchers in the fields of biophysical and social science. The aim was to exchange state-of-the art knowledge; review and discuss latest methods, metrics and tools for assessing SOC and mapping & monitoring SOC dynamic hotspots; and to discuss entry points for shaping gender-sensitive policies towards a green economy where carbon sequestration in soils is a recognized component. During group work sessions, the participants discussed and developed key messages that are relevant for policymaking on SOC sequestration in East Africa and beyond. This report summarizes contributions from participants, lessons learnt and action points

Soil health and ecosystem services: Lessons from sub-Sahara Africa (SSA)

Management practices to improve soil health influence several ecosystem services including regulation of water flows, changes in soil biodiversity and greenhouse gases that are important at local, regional and global levels. Unfortunately, the primary focus in soil health management over the years has been increasing crop productivity and to some extent the associated economics and use efficiencies of inputs. There are now efforts to study the inter-relationship of associated ecosystem effects of soil health management considering that sustainable intensification cannot occur without conscious recognition of these associated non-provisioning ecosystem services. This review documents the current knowledge of ecosystem services for key management practices based on experiences from agricultural lands in sub-Sahara Africa (SSA). Here, practicing conservation agriculture (CA) and Integrated Soil fertility management (ISFM) have overall positive benefits on increasing infiltration (> 44), reducing runoff (> 30%) and soil erosion (> 33%) and increases soil biodiversity. While ISFM and Agroforestry increase provisioning of fuelwood, fodder and food, the effect of CA on the provisioning of food is unclear. Also, considering long-term perspectives, none of the studied soil health promoting practices are increasing soil organic carbon (SOC). Annual contributions to greenhouse gases are generally low (< 3 kg N2O ha−1) with few exceptions. Nitrogen leaching vary widely, from 0.2 to over 200 kg N ha−1 and are sometimes inconsistent with N inputs. This summary of key considerations for evaluating practices from multiple perspectives including provisioning, regulating, supporting and cultural ecosystem services is important to inform future soil health policy and research initiatives in SSA

Unlocking the potential of soil organic carbon in agricultural landscapes in Kenya and Ethiopia

Soils are a very important component of the global carbon cycle as they contain the largest sink of carbon in the terrestrial biosphere. At the same time, soil organic carbon (SOC) is the basis for soil fertility and the production of food to feed the growing global population. Healthy soils are not only important from an agricultural production point of view, but they also provide a multitude of other benefits that are critical to human well-being

Simulating forage yields and soil organic carbon under Brachiaria hybrid cv. Cayman in Tanzania with the CROPGRO perennial forage model

Land and soil degradation in cropping systems in sub-Saharan Africa has been exacerbated by inappropriate use of landscapes and poor management practices that result into environmental and subsequential social damages. Biophysical models are key to inform management activities that can restore degraded soils and ultimately improve yields and soil organic carbon (SOC) sequestration. Numerous modelling studies have been conducted on annual cropping systems, however there are no modelling studies on perennial forages. The goal of this study was to adjust and evaluate the ability of DSSAT CROPGRO-Perennial Forage model version 4.7.5.0, which was initially parameterised for Brachiaria cv. Marandu in Brazil, to simulate biomass yields and SOC under Brachiaria cv. hybrid Cayman (BHC) in three districts in the southern highlands of Tanzania. The key adjusted parameters were soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. After model calibration, the root means square error ranged from 638 to 2111 kg/ha for harvested biomass. The d-Statistic for harvested biomass ranged from 0.78 to 0.97. The RMSE for % SOC ranged from 0.26 to 1.01 % and 0.23 to 1.55 % at 0-20 cm and 20-40 cm depth respectively. The d-Statistic for SOC from ranged 0.19 to 0.35 and 0.40 to 0.53 for 0-20 cm and 20-40 cm respectively. The results indicate that the model can be used to simulate the growth of Brachiaria cv. Cayman under different soils and weather conditions with an acceptable adjustment of specific parameters including soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. Also, the model simulated SOC reasonably well despite the wide variability between observed and simulated values, which was attributed to short period for experimentation and other factors not captured by the model including residue return among others. The adapted parameterised model for Brachiaria cv. Marandu performed reasonably well in simulating biomass and SOC in a different region with different soils, climate and management. Hence, the parameterised model for Brachiaria cv. Marandu can also be used for Brachiaria cv. Cayman in a different region with different soils and climate conditions

Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa

Biophysical models are key to inform management activities that can restore degraded soils and ultimately improve biomass production and soil organic carbon (SOC) sequestration. Within East Africa several studies have been conducted to evaluate models in annual cropping systems, and to quantify the impacts of different agronomic management options on soil organic carbon and yields. However, no modelling studies exist on perennial forage grasses, which are important for mixed-crop livestock systems within the region. We evaluate the CROPGRO-Perennial Forage model (CROPGRO-PFM) using harvested biomass and SOC data from several sites across Kenya and Tanzania. The model version initially parametrized for Brachiaria cv. Marandu and Panicum maximum in Brazil is applied to simulate Brachiaria cv. hybrid Cayman and Panicum maximum in the two countries. We modify model parameters to improve d-statistic and root mean square error (RMSE) for biomass and SOC. Our results show that the CROPRO-PFM model can simulate biomass of Brachiaria cv. Cayman under different soils and weather conditions with an acceptable adjustment of parameters including soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. The d-statistic for harvested biomass across the Tanzania sites ranged between 0.78 to 0.97, while the root means square error ranged between 0.6 to 2 t/ha. Sensitivity simulations with increased manure application rates of 5t/ha show an increase in SOC of up 0.833 t/ha/yr. These results suggest that the CROPGRO-PFM can be used to simulate growth of Brachiaria cv. Cayman adequately under rainfed conditions in the East African highlands

Harvest data for 6 cowpeas and 6 maize farms in sandy soils in Makueni County, Kenya

The data shows the harvested yield in 6 maize farms and 6 cowpeas farms in Mtito Andei- Makueni County. The data was collected in 3 plots in each farm to compare crop productivity in sandy soils plots installed with the sub-surface water retaining technology (SWRT) against plots without this technology. 2 of the plots are installed with SWRT (plot 1 and 2) while the third plot is treated as the control plot. All the plots received equal amounts of manure and fertilizer during planting. The maize plots were also top-dressed

Soil analysis for selected forage on-farm demonstration plots in Western Kenya

The data contains results for soil organic carbon and texture for selected forage treatments in 6 on-farm demonstration plots located in Bungoma, Kakamega, Siaya and Busia counties in Western Kenya. The soils were analyzed in 2022, 3 years after the planting of the forages. The 6 demonstration plots were set up within the Grass2cash project. The data will be used for calibrating and evaluating the DSSAT CROPGRO Perennial Forage Model