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The climate of West Africa is expected to become more arid due to increased temperature and uncertain rainfall regimes, while its population is expected to grow faster than the rest of the world. As such, increased demand for food will likely coincide with declines in agricultural production in a region where severe undernutrition already occurs. Here, we attempt to discriminate between the impacts of climate and other factors (e.g. land management/degradation) on crop production across West Africa using satellite remote sensing. We identify trends in the land surface phenology and climate of West African croplands between 2000 and 2018. Using the combination of a an attribution framework and residual trend anlaysis, we discriminate between climate and other impacts on crop productivity. The combined effect of rainfall, land surface temperature and solar radiation explains approximately 40% of the variation in cropland productivity over West Africa at the 95% significance level. The largest proportions of croplands with greening trends were observed in Mali, Niger and Burkina Faso, and the largest proportions with browning trends were in Nigeria, The Gambia and Benin. Climate was responsible for 52% of the greening trends and 25% of the browning trends. Within the other driving factors, changes in phenology explained 18% of the greening and 37% of the browning trends across the region, the use of inputs and irrigation explained 30% of the greening trends and land degradation 38% of the browning trends. These findings have implications for adaptation policies as we map out areas in need of improved land management practices and those where it has proven to be successful.

International audience; Abstract Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.

The Great Green Wall (GGW) Initiative aims at combatting land degradation while achieving socio-economic development across the Sahel through a mosaic of sustainable land management (SLM) and restoration practices. As the Global Environment Facility (GEF) is the main funding mechanism for land degradation neutrality related projects, we have analyzed its previous SLM projects in four pilot countries in an effort to assess their capacity to foster scaling of interventions and fast track progress towards the GGW objectives. We developed a literature-based scaling evaluation framework and scoring methods to harmonize the GEF agency based project ratings in terms of performance and persistence along seven evaluation domains. We found that projects perform better over time particularly in terms of monitoring, financing and resilience to shocks but are overall only moderately likely to achieve benefits persistent over time, which is necessary to allow for the scaling of interventions. While these efforts should be maintained and further pursued, we also recommend special attention to be placed on a number of interventions that are often less successful or ignored by projects such as enforcing mechanisms for new SLM regulations, empowering vulnerable groups and ensuring sufficient capacity and finances for sustaining achievements even during periods of political or climatic instability.

In recent years, Large Scale Land Acquisitions (LSLA), direct land tenure changes have been gaining momentum in developing countries. In this study, we evaluate the potential extent to which agricultural land deals in Africa are able to address the host countries’ food security needs, a commonly cited motivation for their establishment. First, we develop a framework to evaluate the priority food security needs of 38 African countries in 2000 based on indicators of food availability, accessibility, stability, and utilization. Second, we estimate whether the crops from land deals would be sold on export or local food markets based on the origin of investments (domestic, foreign or mixed), type of investors (eg. agribusiness, finance, or government) and the intended crops (eg. food, cash crop, or biofuel). This enables us to estimate how likely the investment is to improve in-country food security, versus serving other purposes (e.g., speculation, enclosure of natural resources). Third, we account for the characteristics of the locations where the deals happen (population density, land cover and distance to markets) in order to estimate the level of conflict and deforestation that they could exacerbate. We find that LSLA are only likely to address the identified food security needs of 7 countries. LSLA are also at risk of increasing land pressures and conflicts or deforestation on 83% of the acquired area, including in countries where they could meet food security needs. We also find that the more productive lands are most often allocated to flex crops, while food crops are produced on more marginal lands. We thus argue that even when their purpose is agricultural production, most LSLA are not likely to improve food security; rather, they often serve the financial interests of transnational companies and local elites with the support of host governments. Finally, we recommend agricultural investments to be elaborated in consultation with local communities and marginalized groups to sustainably support their socio-ecological systems.

The world has become increasingly telecoupled throughdistant flows of information, energy, people, organisms,goods, and matter. Recent advances suggest thattelecouplings such as trade and species invasion oftengenerate spillover systems with profound effects. To untanglespillover complexity, we make the first attempt to develop atypology of spillover systems based on six criteria: flows fromand to sending and receiving systems, distances from sendingand receiving systems, types of spillover effects, sizes ofspillover systems, roles of agents in spillover systems, and theorigin of spillover systems. Furthermore, we highlight aportfolio of qualitative and quantitative methods for detectingthe often-overlooked spillover systems. To effectively governspillover systems for global sustainability, we propose anoverall goal (minimize negative and maximize positive spillovereffects) and three general principles (fairness, responsibility,and capability). The world has become increasingly telecoupled through distant flows of information, energy, people, organisms, goods, and matter. Recent advances suggest that telecouplings such as trade and species invasion often generate spillover systems with profound effects. To untangle spillover complexity, we make the first attempt to develop a typology of spillover systems based on six criteria: flows from and to sending and receiving systems, distances from sending and receiving systems, types of spillover effects, sizes of spillover systems, roles of agents in spillover systems, and the origin of spillover systems. Furthermore, we highlight a portfolio of qualitative and quantitative methods for detecting the often-overlooked spillover systems. To effectively govern spillover systems for global sustainability, we propose an overall goal (minimize negative and maximize positive spillover effects) and three general principles (fairness, responsibility, and capability).

This work was financially supported by the Spanish National Institute for Agricultural and Food Research and Technology (INIA, MACSUR01-UPM), the Italian Ministry of Agriculture and Forestry and the Finnish Ministry of Agriculture and Forestry (D.M. 24064/7303/15) through FACCE MACSUR − Modelling European Agriculture with Climate Change for Food Security, a FACCE JPI knowledge hub; MULCLIVAR, from the Spanish Ministerio de Economía y Competitividad (MINECO, CGL2012-38923-C02-02); the Academy of Finland (decisions: 277276 and 277403), the EU FP7 IMPRESSIONS project (grant agreement no. 603416), the NORFASYS project (decision nos. 268277 and 292944) and PLUMES project (decision nos. 277403 and 292836); project IGA AF MENDELU no. 7/2015 with the support of the Specific University Research Grant provided by the Ministry of Education, Youth Sports of the Czech Republic; the Ministry of Education, Youth Sports of the Czech Republic within the National Sustainability Programme I (NPU I), grant number LO1415 NAZV QJ1310123 the Polish National Centre for Research and Development in frame of the projects: LCAgri, contract number BIOSTRATEG1/271322/3/NCBR/2015 and GyroScan, contract number BIOSTRATEG2/298782/11/NCBR/2016.; Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the “According to Our Current Knowledge” (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T), [CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based on a cultivar without vernalization requirements showed good and wide adaptation potential. Few combined adaptation options performed well under rainfed conditions. However, a single sI was sufficient to develop a high adaptation potential, including options mainly based on spring wheat, current cycle duration and early sowing date. Depending on local environment (e.g. soil type), many of these adaptations can maintain current yield levels under moderate changes in T and P, and some also under strong changes. We conclude that ARSs can offer a useful tool for supporting planning of field level adaptation under conditions of high uncertainty.

Large-scale land acquisitions (LSLA) in resource-rich countries came to global attention after the food and financial crises of 2008. Previous research has assessed the magnitude of these land investments in terms of land areas acquired. In this study, we analyze the trends in the evolution of LSLA by framing the latter as virtual land trade network with land transactions occurring between 2000 and 2015, in order to shed light on the development and evolution of this system. Based on an index we introduce to represent both the number of countries and size of deals, we discover three main phases of trade activity: a steady increase from 2000 until 2007 (Phase 1) followed by a peak coinciding with the food and financial crises between 2008 and 2010 (Phase 2) and concluded by a decline from 2011 to 2015 (Phase 3). We identify 73 countries that remained active in land trading during all three phases and form a core of land traders much larger than previously thought. Using network analysis methods, we group countries with similar trade patterns into categories of competitive, preferential, diversified, and occasional importers or exporters. Finally, in exploring the changes in investors and their interests in land throughout the phases, we attribute the evolution of LSLA to the different stages in the globalization and financialization of different industries. By showing that land investments seem fully integrated as investment strategies across industries we argue for the urgency of better regulation of LSLA so that they also benefit local populations without damaging the environment regardless of their primary purpose.