Romain Frelat

Drivers of household food availability in sub-Saharan Africa based on big data from small farms

Significance We collated a unique dataset covering land use and production data of more than 13,000 smallholder farm households in 93 sites in 17 countries across sub-Saharan Africa. The study quantifies the importance of off-farm income and market conditions across sites differing strongly in agroecology and derives generally applicable threshold values that determine whether farm households have enough food available to feed their families. These results show there is a strong need for multisectoral policy harmonization and incentives and improved interconnectedness of people to urban centers and diversification of employment sources, rather than a singular focus on agricultural development of smallholder farmers in sub-Saharan Africa. We calculated a simple indicator of food availability using data from 93 sites in 17 countries across contrasted agroecologies in sub-Saharan Africa (>13,000 farm households) and analyzed the drivers of variations in food availability. Crop production was the major source of energy, contributing 60% of food availability. The off-farm income contribution to food availability ranged from 12% for households without enough food available (18% of the total sample) to 27% for the 58% of households with sufficient food available. Using only three explanatory variables (household size, number of livestock, and land area), we were able to predict correctly the agricultural determined status of food availability for 72% of the households, but the relationships were strongly influenced by the degree of market access. Our analyses suggest that targeting poverty through improving market access and off-farm opportunities is a better strategy to increase food security than focusing on agricultural production and closing yield gaps. This calls for multisectoral policy harmonization, incentives, and diversification of employment sources rather than a singular focus on agricultural development. Recognizing and understanding diversity among smallholder farm households in sub-Saharan Africa is key for the design of policies that aim to improve food security.

Is production intensification likely to make farm households food-adequate? A simple food availability analysis across smallholder farming systems from East and West Africa

Despite considerable development investment, food insecurity remains prevalent throughout East and West Africa. The concept of ‘sustainable intensification’ of agricultural production has been promoted as a means to meet growing food needs in these regions. However, inadequate attention has been given to assessing whether benefits from intensification would be realized by farm households considering highly diverse resource endowments, household and farm characteristics, and agroecological contexts. In this study, we apply a simple energy-based index of food availability to 1800 households from research sites in 7 countries in East and West Africa to assess the food availability status of each of these households and to quantify the contribution of different on- and off-farm activities to food availability. We estimate the effects of two production intensification strategies on food availability: increased cereal crop production from crop-based options, and increased production of key livestock products from livestock-based options. These two options are contrasted with a third strategy: increased off-farm income for each household from broader socioeconomic-based options. Using sensitivity analysis, each strategy is tested against baseline values via incremental production increases. Baseline results exhibit considerable diversity within and across sites in household food availability status and livelihood strategies. Interventions represented in the crop and livestock options may primarily benefit food-adequate and marginally food-inadequate households, and have little impact on the most food-inadequate households. The analysis questions what production intensification can realistically achieve for East and West African smallholders, and how intensification strategies must be augmented with transformational strategies to reach the poorest households.

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

Food availability and livelihood strategies among rural households across Uganda

Despite continuing economic growth, Uganda faces persistent challenges to achieve food security. The effectiveness of policy and development strategies to help rural households achieve food security must improve. We present a novel approach to relate spatial patterns of food security to livelihood strategies, including the contribution of on- and off-farm activities to household food availability. Data from 1927 households from the World Bank Living Standards Measurement Study were used to estimate the calorific contribution of livelihood activities to food availability. Consumption of crops produced on-farm contributed most to food availability for households with limited food availability, yet the majority of these households were not food self-sufficient. Off-farm and market-oriented on-farm activities were more important for households with greater food availability. Overall, off-farm income was important in the north, while market-oriented on-farm activities were important in western and central Uganda. Food availability patterns largely matched patterns of agroecological conditions and market access, with households doing worst in Uganda’s drier and remote northeast. Less food-secure households depended more on short-cycle food crops as compared with better-off households, who focused more on plantation (cash) crops, although this varied among regions. Targeting interventions to improve food security should consider such differences in enterprise choice and include options to improve household market access and off-farm income opportunities.

Regional watershed characterization and classification with river network analyses

In order to understand and manage a hydrological region, one usually needs to comprehensively characterize the watersheds (basins) and their river networks. This usually and primarily involves analysis of hydrological and geomorphological properties of the watershed derived from the digital terrain model (DTM), but this approach neglects the information content of the associated river networks. In this study, we used a combination of traditional DTM and original river network-related indices to the watersheds of an understudied region, Haiti. We also used Monte Carlo simulations to estimate index confidence levels of these indices. Compared to commonly used indices, the network indices provided valuable information that could then be used in statistical analyses as a way to identify the dominant features of the countrys watershed morphology. On this basis, we identified four watershed groups in Haiti: (i) high, elongated watersheds, (ii) lowlands, with sinuous networks and relatively slow runoff, (iii) high watersheds with dendritic networks, and (iv) lowlands with high downstream–upstream contrast in properties and rapid runoffs. We argue that river network features provide complementary information in terms of flow topology, highly relevant to characterize contrasting relief countries, such as Haiti. Hence, more exhaustive characterization of watersheds would predictably benefit from the approach outlined in this paper. Copyright

Time–frequency analysis to profile hydrological regimes: application to Haiti

Abstract Comprehensive characterization of its flow rates is prerequisite to a proper understanding and water management of a given hydrological region. Several studies question the soundness of stationarity in time series and suggest the need for a quantification of the events and non-stationary features in flow rate time series. In this study, we combine statistical and time–frequency (TF) analyses to characterize and classify the flow rates of an understudied region, namely Haiti. Wavelet transforms and cyclostationarity analyses were combined with principal component analysis and hierarchical clustering to identify three groups of hydrological regimes in the country, suggesting similar management: (1) relatively stable flow rates with TF behaviour; (2) periodic and strongly seasonal flow rates; and (3) unstable flow rates. We argue that the TF methodology can yield additional information in regard to flow events and multiscale behaviour, even for short records. Flow rate characterization would benefit from the exhaustive approach described here. EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR E. Toth