Author: Nurah Niazy
Food is important for our survival, yet it is a contributing factor to one of the greatest threats to our generation: climate change. This contested nature is further complicated with the inequality of food availability, access, and utilisation. As these environmental and social challenges posed by climate change loom over us, ensuring food security is imperative. It is a global challenge that is at the forefront for international bodies – such as the United Nations and its Sustainable Development Goals.
Being a Geography and International Relations student, I’ve had the opportunity to delve into studies surrounding food security and justice, sustainability, and environmentalism. I have noticed, however, that countries from the Global South are often neglected in these discussions. I even designed my dissertation to address this gap, but I wanted to also experience research opportunities that focus on these inequities. When I came across the NERC-QUADRAT Research Experience Placement Scheme, I found the perfect project. It is called: “Addressing food security through data and innovation: analysing the effectiveness of a novel fruit fly trap for small farmers in a developing country.” Supervised by Dr Juliano Morimoto at the University of Aberdeen and joined by a fellow undergraduate student, we worked with an industry partner based in India. The novel fruit fly trap was designed to be cheaper and more efficient for local farmers in India.
During the 10 weeks of this placement, I analysed the field trial dataset provided by the industry partner to assess the performance of the new trap which captures both male and female fruit flies (Bactrocera cucurbitae). This was compared to the performance of standard traps that attract only male flies (i.e., cue-lure traps). We worked with the programming language R to conduct these analyses. Coming from a predominantly social science background, I was excited to learn programming and to develop my statistical modelling skills (as I don’t get many chances to do this in my degree). My supervisor provided resources and support that allowed me to become comfortable and proficient in R.
We first cleaned up and organised the dataset that contained the number of male and female flies caught by each trap type across the 16 locations in the last three years (i.e., 2018-2020). The amount of the new traps and cue-lure traps at each location were not equivalent, so we had to standardise the number of trapped flies before comparing their performances. This was followed by a statistical analysis of the standardised dataset using mixed effects modelling.
Seeing as the collection period of the empirical data was only three years long, we decided to develop predictive simulations that would help us understand the influence of trapping female flies on future fly populations. This would allow us to understand the novel trap’s potential long-term influence at reducing the overall fly population (which would prevent substantial losses of yield from widespread fruit fly infestation). We carried out a critical evaluation of the literature to extract information about the lifespan and fecundity of B. cucurbitae females to use as modelling parameters for our simulation. We also simulated an estimate of the original fly population using an equation proposed by Hayne (1949) and data from the field trials – adding another parameter.
We have been working on presenting our findings in a peer-review publication that will be submitted later in this year. Fortnightly meetings allowed us to exchange ideas and voice concerns – successfully tackling obstacles as a team. Since I was learning new skills in a different field, I was grateful for the level of support and encouragement that I received throughout the placement. This experience gave me the chance to not only develop my quantitative skills but also develop confidence as both an individual and researcher. This has been, by far, one of the most engaging and invaluable experiences. It has now motivated me to explore a career in research within the environmental sciences.