Modeling the multi-functionality of African savanna landscapes under global change

Various recent publications have indicated that accelerated global change and its negative impacts on terrestrial ecosystems in Southern Africa urgently demand quantitative assessment and modelling of a range of ecosystem services on which rural communities depend. Information is needed on how these Ecosystem Services (ES) can be enhanced through sustainable land management interventions and enabling policies. Yet, it has also been claimed that, to date, the required system analyses, data and tools to quantify important interactions between biophysical and socio-economic components, their resilience and ability to contribute to livelihood needs do not exist. We disagree, but acknowledge that building an appropriate integrative modelling framework for assessing the multi-functionality of savanna landscapes is challenging. Yet, in this Letter-to-the-Editor, we show that a number of suitable modelling components and required data already exist and can be mobilized and integrated with emerging data and tools to provide answers to problem-driven questions posed by stakeholders on land management and policy issues.German Federal Ministry of Education and Researchhttps://onlinelibrary.wiley.com/journal/1099145xhj2022Zoology and Entomolog

Typology of small-scale farmers in southern Africa and implications for policy design

Small-scale farmers play a vital role in providing food for a growing urbanized population and improving food security in Southern Africa. The smallholder farms are highly heterogeneous in terms of types of farming, levels of productivity and commercialization. These heterogeneous groups of smallholder faming systems require different forms of government interventions, depending on the objective and characteristics of each group. The aim of this paper is to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies. For this, a cluster analysis is conducted on the basis of a comprehensive survey among 212 small-scale farmers in the Limpopo region in 2019. An unsupervised machine learning approach with Partitioning Around Medoids (PAM) for the subsequent clustering is used. According to the results, the small-scale farmers can be grouped into four clusters. The largest cluster with 37.7% of the farmers represents the group of subsistence oriented farmers, while the smallest cluster with 14% of respondents indicates the emerging (commercial-oriented) farmers. The other two clusters are the semi-subsistence livestock farmers as well as the and crop oriented farmers that predominantly producing for own consumption and selling their surplus at their farm. According to the results, implications for target-group-specific policies are exemplary derived with regards to the topics of extension services, the adaptation of irrigation technologies and credit access

Tackling climate risk to sustainably intensify smallholder maize farming systems in southern Africa

Sustainable intensification (SI) of low input farming systems is promoted as a strategy to improve smallholder farmer food security in southern Africa. Using the Limpopo province South Africa as a case study (four villages across a climate gradient), we combined survey data (140 households) and quantitative agronomic observations to understand climate-induced limitations for SI of maize-based smallholder systems. Insights were used to benchmark the agroecosystem model Agricultural Production System sIMulator, which was setup to ex ante evaluate technology packages (TPs) over 21-seasons (1998–2019): TP0 status quo (no input, broadcast sowing), TP1 fertiliser (micro dosing), TP2 planting density (recommended), TP3 weeding (all removed), TP4 irrigation, TP5 planting date (early, recommended), and TP6 all combined (TPs 1–5). An additional TP7 (forecasting) investigated varying planting density and fertiliser in line with weather forecasts. Input intensity levels were low and villages expressed similar challenges to climate risk adaptation, with strategies mostly limited to adjusted planting dates and densities, with less than 2% of farmers having access to water for irrigation. Simulations showed that combining all management interventions would be expected to lead to the highest mean maize grain yields (3200 kg ha ^−1 across villages) and the lowest harvest failure risk compared to individual interventions. Likewise, simulations suggested that irrigation alone would not result in yield gains and simple agronomic adjustments in line with weather forecasts indicated that farmers could expect to turn rainfall variability into an opportunity well worth taking advantage of. Our study emphasises the need for a cropping systems approach that addresses multiple crop stresses simultaneously