Understanding the multiple facets of climate-resilient agricultural production and food security
Ensuring there is always food on our tables and living under a habitable climate are key global challenges faced by humankind. Though appearing simple, these two challenges are complex to solve. Moreover, we first have to reach a common understanding of key concepts (e.g. food security, sustainability and resilience) and the indicators used to evaluate them. Often the evaluation of agricultural production systems is done in silos by different specialists of given scientific disciplines. For example, soil, crop and animal scientists evaluate the production systems while socio-economists emphasize management system. This set-up commonly results in communication challenges. Different experts tend to understand concepts differently and may have different objectives. I aim to bridge the methodological and communication gaps in my research as I emphasize alternative evaluation methods that put together several specialists: interdisciplinary research evaluation methods.
Both food security and climate change are heavily embedded in the social and technological facets of development. The multiple facets require the integration of disciplines to better understand factors determining food security and resilience of agricultural production systems. In my research, I promote a socio-ecological research approach because the social components affect the biophysical ones and vice-versa. To do so, we have used multivariate method, Partial Least Squares (PLS), to study crop performance at the plot level and smallholder farmers’ well-being at the household level. This method allows us to analyze agricultural production systems and evaluate latent variables such as crop or animal performance in given socio-ecological conditions, where the input data consider the integral agricultural production system. This makes it easier to understand the factors that are likely to influence the targeted outcome including household food security and resilience. It paves the ground for an in-depth understanding of the system and applying the results in specific social or biophysical conditions.
My future research vision is to understand and design sustainable farming and food systems using the three pillars of climate-smart agriculture as my entry point. The pillars are ssustainably increasing agricultural productivity, adapting and building resilience and reducing greenhouse gas emissions from agriculture. In recent years, I work in teams with international scientists with a background and expertise in agronomy, soil sciences, agroecology, ecology, economy and social sciences. We try to integrate knowledge towards a more holistic understanding of agricultural production systems to suggest options for designing resilient and sustainable farming and food systems. Two projects are ongoing: i) climate-smart agriculture options of sandy soils in Zimbabwe and ii) increasing farm system resilience and carbon sinks on sandy soils in Kenya. In both projects, we use on-farm survey data and experimentation and we intend to include the production systems' social and biophysical aspects' in the analyses. This interdisciplinary framework will continue to evaluate different existing and new climate-smart agriculture options and come up with recommendations, which will enable better decision making at the level of agricultural production systems. I will build on my experience on PLS method, which has already extensive applications in social sciences (e.g. education, psychology and marketing) and in industrial processing (e.g. chemical engineering, chemometrics). There is a consensus that PLS is a robust method, but it has also trade-offs to be considered such as the lack of clear causal relationships among drivers and the outcomes. PLS-Path modelling, also known as Structural equation Modelling (SEM), is another method in my toolbox for further analyses. It is more straightforward when it comes to causal relationships among system components.