Desert locusts, known for their solitary existence, can transform into devastating swarms when triggered by intense rainfall and other climate-induced events. In one day, a swarm covering just one square kilometre can consume food sufficient to feed 35,000 people.
The widespread crop destruction they cause not only drives up local food prices but can also lead to riots and mass starvation—critical issues in an era increasingly marked by climate change.
In response, a team led by the University of Cambridge has developed an innovative model to predict when and where desert locusts will swarm. Utilizing advanced weather forecast data from the UK Met Office, coupled with sophisticated computational models of locust movements, the researchers can now anticipate swarming patterns as locusts search for new breeding and feeding grounds. This proactive approach enables timely pesticide application in vulnerable areas, mitigating the impact before it escalates.
Traditional efforts inconsistent
Traditionally, efforts to predict and control locust swarms have been inconsistent, often relying on reactive measures. The new model, published in the journal PLOS Computational Biology, allows national agencies to respond swiftly to emerging locust threats, thereby safeguarding food security—a paramount concern for smallholder farmers across Africa and Asia.
Climate change plays a critical role in this phenomenon, driving more frequent, intense desert locust swarms through increased moisture from events like cyclones and heavy rainfall. This surge in moisture allows vegetation to flourish, providing the necessary sustenance for locusts to breed, exacerbating the risks to food supplies.
“During a desert locust outbreak, we can now predict swarm movements several days in advance, allowing for targeted interventions. If swarms aren’t contained in one area, we can track their next likely destination and prepare accordingly,” said Dr. Renata Retkute, a researcher in the University of Cambridge’s Department of Plant Sciences and lead author of the study.
Professor Chris Gilligan, senior author of the paper, emphasized the urgent need for prompt action: “If we can anticipate a significant locust upsurge, early intervention is essential to prevent crop losses. The potential for large swarms to lead to food scarcity is dire and must be addressed swiftly.”
The impetus for this comprehensive model arose during a massive locust upsurge from 2019 to 2021, which stretched from Kenya to India, wreaking havoc on wheat production and devastating crops like sugarcane, sorghum, maize, and root vegetables. This experience highlighted the inefficiencies of ad-hoc responses that struggled to integrate critical information from diverse sources.
“Our response to the last locust invasion was inefficient. With this new model, we can approach future events prepared rather than scrambling for information,” Retkute stated.
A significant advance
This groundbreaking model represents a significant advancement in the ability to predict and manage locust behavior reliably, taking into account their life cycle and preferences for breeding sites.
With rigorous testing against actual surveillance and weather data from previous outbreaks, it stands to enhance early warning systems and management strategies for desert locusts by national governments and international organizations such as the Food and Agriculture Organization of the United Nations (FAO).
As climate change continues to disrupt the natural environment, countries that have not faced locust swarms in years—often lacking adequate surveillance, resources, and contingency planning—must now adapt to a new reality.
