There is an urgent need for agricultural development strategies that reconcile agricultural production and biodiversity conservation. This is especially true in the Global South where population growth is rapid and much of the world’s remaining biodiversity is located. Combining conceptual thoughts with empirical insights from case studies in Indonesia and Ethiopia, we argue that such strategies will have to pay more attention to agri- cultural labour dynamics. Farmers have a strong motivation to reduce the heavy toil associated with farming by adopting technologies that save labour but can negatively affect biodiversity. Labour constraints can also prevent farmers from adopting technologies that improve biodiversity but increase labour intensity. Without explicitly accounting for labour issues, conservation efforts can hardly be successful. We hence highlight the need for biodiversity-smart agriculture, that is farming practices or systems that reconcile biodiversity with land and labour productivity. Our empirical insights suggest that technological and institutional options to reconcile farmers' socio-economic goals and biodiversity conservation exist but that more needs to be done to implement such options at scale.

A growing urban population and dietary changes increased wheat import bills in Africa to 9% per year. Though wheat production in the continent has been increasing over the past decades, to varying degrees depending on regions, this has not been commensurate with the rapidly increasing demand for wheat. Analyses of wheat yield gaps show that there is ample opportunity to increase wheat production in Africa through improved genetics and agronomic practices. Doing so would reduce import dependency and increase wheat self-sufficiency at national level in many African countries. In view of the uncertainties revealed by the global COVID-19 pandemic, extreme weather events, and world security issues, national policies in Africa should re-consider the value of self-sufficiency in production of staple food crops, specifically wheat. This is particularly so for areas where water-limited wheat yield gaps can be narrowed through intensification on existing cropland and judicious expansion of rainfed and irrigated wheat areas. Increasing the production of other sources of calories (and proteins) should also be considered to reduce dependency on wheat imports

Acid tropical soils may become more productive when treated with agricultural lime, but optimal lime rates have yet to be determined in many tropical regions. In these regions, lime rates can be estimated with lime requirement models based on widely available soil data. We reviewed seven of these models and introduced a new model (LiTAS). We evaluated the models' ability to predict the amount of lime needed to reach a target change in soil chemical properties with data from four soil incubation studies covering 31 soil types. Two foundational models, one targeting acidity saturation and the other targeting base saturation, were more accurate than the five models that were derived from them, while the LiTAS model was the most accurate. The models were used to estimate lime requirements for 303 African soil samples. We found large differences in the estimated lime rates depending on the target soil chemical property of the model. Therefore, an important first step in formulating liming recommendations is to clearly identify the soil property of interest and the target value that needs to be reached. While the LiTAS model can be useful for strategic research, more information on acidity-related problems other than aluminum toxicity is needed to comprehensively assess the benefits of liming."

Maize production in Zambia must increase with a view towards improved food security and reduced food imports whilst avoiding cropland expansion. To achieve this, it is important to understand the causes behind the large maize yield gaps observed in smallholder farming systems across the country. This is the first study providing a yield gap decomposition for maize in Zambia, and combining it with farm typology delineation, to identify the key limiting factors to maize yield gaps across the diversity of farms in the country. The analysis builds upon a nationally representative household survey covering three growing seasons and crop model simulations to benchmark on-farm maize yields and N application rates. Three farm types were delineated, including households for which maize is a marginal crop, households who are net buyers of maize, and households who are market-oriented maize producers. Yield gap closure was about 20% of the water-limited yield, corresponding to an actual yield of 2.4 t ha???1. Market-oriented maize farms yielded slightly more than the other farm types, yet the drivers of yield variability were largely consistent across farm types. The large yield gap was mostly attributed to the technology yield gap indicating that more efficient production methods are needed to raise maize yields beyond the levels observed in highest yielding fields. Yet, narrowing efficiency and resource yield gaps through improved crop management (i.e., sowing time, plant population, fertilizer inputs, and weed control) could more than double current yields. Creating a conducive environment to increase maize production should focus on the dissemination of technologies that conserve soil moisture in semi-arid areas and improve soil health in humid areas. Recommendations of sustainable intensification practices need to consider profitability, risk, and other non-information constraints to improved crop management and must be geographically targeted to the diversity of farming systems across the country."

The production and trade of agricultural commodities is a major driver of the loss of tropical biodiversity. In the Mid Zambezi Valley, Zimbabwe, which is home to many emblematic African mammals, cotton production has historically been a major driver of land cover change. The collapse of cotton production in Zimbabwe over the last decade provides a unique opportunity to understand the linkages between the profitability of cotton and land-use changes in this multifunctional landscape. By re-visiting 141 households that had been surveyed in 2007 and combining this panel survey data with a land cover analysis and secondary data, we demonstrate that the decreasing profitability of cotton led to a shift from cotton farming (mean area per farm decreasing from 1.79 +/- 2.05 ha in 2007 to 0.72 +/- 0.90 ha in 2020) to livestock farming (mean number of cattle and goats per farm increasing several-fold between 2007 and 2020), resulting in drastic land cover changes. Indeed, open vegetation (including crops, fallows and grazing areas) expanded from 10 to 20% of the total land cover area between 2007 and 2020. Populations of wildlife species have declined drastically during this period, although this cannot be attributed solely to the observed changes in land cover. However, increasing human-wildlife conflicts are likely to threaten the long-term coexistence of people and wildlife in the area. We argue that commodity crops can be an opportunity for nature conservation, not only a threat, and that conservation needs to support a ‘living income’ for people coexisting with wildlife.

In sub-Saharan Africa there is increasing focus on identifying women’s trait preferences within crop breeding to enable gender-responsive product development. In the case of maize, breeding programs are ready to incorporate specific traits to increase gender-responsiveness but lack guidance on what these specific traits might be. We propose an inductive approach to determine a pathway towards increasing gender-responsiveness within maize breeding. A survey of 306 farmers was conducted to determine gender differences in maize varieties used together with key agronomic practices. Variety was a significant predictor of the gender of the plot manager and of the household head in contrast to previous surveys conducted in researcher-led on-farm trials. On-farm trials are conducted using pre-defined agronomic management practices and preferences identified at harvest are likely to centre around yield. This study highlighted significant differences in several agronomic practices used by female plot managers and female household heads. Although further studies are required to understand preferences associated with varietal choice, our results suggest that current researcher-led on-farm trials may not identify gender-specific trait preferences driving varietal choice. Furthermore, a trait-specific approach is not the only avenue towards increasing gender-responsiveness in maize breeding in southern Africa. The scope for increasing gender-intentionality in maize breeding could be expanded to incorporate selection environments more relevant to agronomic management practices used by female plot managers and households at advanced stages of the breeding pipeline. This approach could provide an immediate entry point to increase gender-intentional maize breeding in southern Africa.