The overlooked spatial dimension of climate-smart agriculture

A systematic review of the methodology of trade-off analysis in agriculture

Trade-off analysis (TOA) is central to policy and decision-making aimed at promoting sustainable agricultural landscapes. Yet, a generic methodological framework to assess trade-offs in agriculture is absent, largely due to the wide range of research disciplines and objectives for which TOA is used. In this study, we systematically reviewed 119 studies that have implemented TOAs in landscapes and regions dominated by agricultural systems around the world. Our results highlight that TOAs tend to be unbalanced, with a strong emphasis on productivity rather than environmental and socio-cultural services. TOAs have mostly been performed at farm or regional scales, rarely considering multiple spatial scales simultaneously. Mostly, TOAs fail to include stakeholders at study development stage, disregard recommendation uncertainty due to outcome variability and overlook risks associated with the TOA outcomes. Increased attention to these aspects is critical for TOAs to guide agricultural landscapes towards sustainability.

Spatiotemporal co-optimization of agricultural management practices towards climate-smart crop production

Co-optimization of multiple management practices may facilitate climate-smart agriculture, but is challenged by complex climate-crop-soil management interconnections across space and over time. Here we develop a hybrid approach combining agricultural system modelling, machine learning and life cycle assessment to spatiotemporally co-optimize fertilizer application, irrigation and residue management to achieve yield potential of wheat and maize and minimize greenhouse gas emissions in the North China Plain. We found that the optimal fertilizer application rate and irrigation for the historical period (1995-2014) are lower than local farmers' practices as well as trial-derived recommendations. With the optimized practices, the projected annual requirement of fertilizer, irrigation water and residue inputs across the North China Plain in the period 2051-2070 is reduced by 16% (14-21%) (mean with 95% confidence interval), 19% (7-32%) and 20% (16-26%), respectively, compared with the current supposed optimal management in the historical reference period, with substantial greenhouse gas emission reductions. We demonstrate the potential of spatiotemporal co-optimization of multiple management practices and present digital mapping of management practices as a benchmark for site-specific management across the region.

Sustainable transformation of agriculture requires landscape experiments

Transformation of agriculture to realise sustainable site-specific management requires comprehensive scientific support based on field experiments to capture the complex agroecological process, incite new policies and integrate them into farmers' decisions. However, current experimental approaches are limited in addressing the wide spectrum of sustainable agroecosystem and landscape characteristics and in supplying stakeholders with suitable solutions and measures. This review identifies major constraints in current field experimentation, such as a lack of consideration of multiple processes and scales and a limited ability to address interactions between them. It emphasizes the urgent need to establish a new category of landscape experimentation that empowers agricultural research on sustainable agricultural systems, aiming at elucidating interactions among various landscape structures and functions, encompassing both natural and anthropogenic features. It extensively discusses the key characteristics of landscape experiments and major opportunities to include them in the agricultural research agenda. In particular, simultaneously considering multiple factors, and thus processes at different scales and possible synergies or antagonisms among them would boost our understanding of heterogeneous agricultural landscapes. We also highlight that though various studies identified promising approaches with respect to experimental design and data analysis, further developments are still required to build a fully functional and integrated framework for landscape experimentation in agricultural settings.

The Progress of the Development of a Climate-smart Agriculture in Europe: Is there Cohesion in the European Union?

The development of climate-smart agriculture (CSA) is crucial in ensuring the creation of a low-carbon society and mitigation of climate change. These tasks require concerted actions from multiple stakeholders since the very concept of CSA is rather complex and requires multi-dimensional consideration. This study defines and applies various indicators to evaluate the development of CSA in the European Union (EU). To do this, three different multi-criteria decision-making methods, namely Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR; multi-criteria optimization and compromise solution), were employed for the construction of a composite indicator. A combination of both objective (entropy) and subjective (Analytic Hierarchy Process) weighting techniques was utilized to derive the weights of the indicators. The leaders in the EU in terms of CSA are Austria, Denmark and the Netherlands, whereas the countries with the lowest levels of CSA development are Cyprus, Greece and Portugal. This study also revealed divergence in the development of these practices in the EU-24 for the period 2004-2019. Thus, a more inclusive approach is needed to ensure the spread of climate-smart ideas in European agriculture sectors.

First report of aeroponically grown Bambara groundnut, an African indigenous hypogeal legume: Implications for climate adaptation

Global agricultural production is currently limited by negative climate-related hazards such as drought, uneven rainfall and rising temperatures. Many efforts have been put in place by government and non-government agencies to mitigate the challenges of climate change in the sector. However, the approaches do not seem feasible due to the growing demand for food. With these challenges, climate-smart agricultural technologies such as aeroponics and underutilised crops have been projected as the future of agriculture in developing African countries to reduce the risk of food insecurity. In this paper, we present the cultivation of an underutilised indigenous African legume crop, Bambara groundnut, in an aeroponics system. Seventy Bambara groundnut landraces were cultivated in a low-cost climate-smart aeroponics system and in sawdust media. The results showed that Bambara groundnut landraces cultivated in aeroponics performed better than those cultivated in a traditional hydroponics (sawdust/drip irrigation) technique in terms of plant height and chlorophyll content, where the landraces cultivated in sawdust had a higher number of leaves than those cultivated in aeroponics. This study also demonstrated the feasibility of introducing a generic Internet of Things platform for climate-smart agriculture in developing countries. The proof-of-concept and the successful cultivation of a hypogeal crop in aeroponics can be useful for cost-effective adaptation and mitigation plans for climate change, particularly for food security in rural African agricultural sectors.

Assessment of the Climate-Smart Agriculture Interventions towards the Avenues of Sustainable Production–Consumption

In the current scenario, climatic adversities and a growing population are adding woes to the concerns of food safety and security. Furthermore, with the implementation of Sustainable Development Goal (SDG) 12 by the United Nations (UN), focusing on sustainable production–consumption, climatic vulnerabilities need to be addressed. Hence, in order to map the sustainable production–consumption avenues, agricultural practices need to be investigated for practices like Climate-Smart Agriculture (CSA). A need has arisen to align the existing agricultural practices in the developing nation towards the avenues of CSA, in order to counter the abrupt climatic changes. Addressing the same, a relation hierarchical model is developed which clusters the various governing criteria and their allied attributes dedicated towards the adoption of CSA practices. Furthermore, the developed model is contemplated for securing the primacies of promising practices for the enactment of CSA using the duo of the Analytical Hierarchical Process (AHP) and Fuzzy AHP (FAHP). The outcomes result in the substantial sequencing of the key attributes acting as a roadmap toward the CSA. This emphasizes the adoption of knowledge-based smart practices, which leaps from the current agricultural practices toward the CSA. Furthermore, by intensifying the utilization of the improved and resilient seed varieties and implying the fundamentals of agroforestry, we secure primacy to counter the adversities of the climate.

Social-ecological analysis of timely rice planting in Eastern India

Timely crop planting is a foundation for climate-resilient rice-wheat systems of the Eastern Gangetic Plains-a global food insecurity and poverty hotspot. We hypothesize that the capacity of individual farmers to plant on time varies considerably, shaped by multifaceted enabling factors and constraints that are poorly understood. To address this knowledge gap, two complementary datasets were used to characterize drivers and decision processes that govern the timing of rice planting in this region. The first dataset was a large agricultural management survey (rice-wheat: n = 15,245; of which rice: n = 7597) from a broad geographic region that was analyzed by machine learning methods. The second dataset was a discussion-based survey (n = 112) from a more limited geography that we analyzed with graph theory tools to elicit nuanced information on planting decisions. By combining insights from these methods, we show for the first time that differences in rice planting times are primarily shaped by ecosystem and climate factors while social factors play a prominent secondary role. Monsoon onset, surface and groundwater availability, and land type determine village-scale mean planting times whereas, for resource-constrained farmers who tend to plant later ceteris paribus, planting is further influenced by access to farm machinery, seed, fertilizer, and labor. Also, a critical threshold for economically efficient pumping appears at a groundwater depth of around 4.5 m; below this depth, farmers do not irrigate and delay planting. Without collective action to spread risk through synchronous timely planting, ecosystem factors such as threats posed by pests and wild animals may further deter early planting by individual farmers. Accordingly, we propose a three-pronged strategy that combines targeted strengthening of agricultural input chains, agroadvisory development, and coordinated rice planting and wildlife conservation to support climate-resilient agricultural development in the Eastern Gangetic Plains.