Desert locusts pose threat to agriculture and food security worldwide. In recent years, particularly from 2019 to 2021, locust swarms devastated crops across East Africa and South Asia. This period marked one of the largest upsurges in locust populations in two decades. In response to this crisis, scientists have developed a predictive tool to forecast locust behaviour and swarm movements. This tool integrates various data sources and models to aid farmers and governments in preparing for future invasions.
About Desert Locust Behaviour
Desert locusts are known for their migratory behaviour. They can form massive swarms that travel long distances. Their invasions are often sudden and can destroy vegetation rapidly. About their life cycle is crucial for predicting their movements. The life cycle includes egg, hopper, and adult stages, each of which influences swarm dynamics.
Integrated Modelling Framework
The new modelling framework combines several components. It selects potential breeding sites based on environmental conditions. It tracks the maturation of locusts through their life stages. The model also incorporates weather data to understand wind trajectories. This helps predict daily swarm migration paths.
Data Utilisation in the Model
The model uses remote-sensed data for accurate predictions. It assesses vegetation availability to determine how long swarms can feed at a location. This data is critical for understanding locust feeding behaviour and swarm duration at landing sites.
Accuracy and Testing
The predictive tool boasts an accuracy of 83%. It was tested across five sub-Saharan countries affected by the 2019 locust upsurge. These countries include Kenya, Ethiopia, Somalia, Eritrea, and Djibouti. The model was validated against recorded swarm movements in these regions.
Significance for Agriculture
This tool is designed to assist government agencies, agronomists, and farmers. It provides a practical resource to prepare for locust invasions. By forecasting potential breeding areas, it helps mitigate the impact of locust swarms on food security.
Historical Context of Locust Invasions
India experienced one of its worst locust attacks in 2020-21, following a 26-year gap. The swarms migrated from neighbouring regions, affecting multiple states. This historical context marks the importance of predictive modelling in preventing future agricultural crises.
Future Implications
The development of this modelling framework is step in pest management. It addresses gaps in previous studies by incorporating a comprehensive understanding of locust biology and environmental factors. This integrated approach can lead to more effective strategies for controlling locust populations.
Questions for UPSC:
- Critically analyse the impact of desert locust swarms on food security in affected regions.
- Estimate the role of climate change in the frequency and intensity of locust invasions.
- What is the significance of remote sensing in agricultural pest management? Discuss with examples.
- Point out the measures that can be taken to mitigate the effects of locust swarms on smallholder farmers.
Answer Hints:
1. Critically analyse the impact of desert locust swarms on food security in affected regions.
- Desert locusts can devastate crops, leading to immediate food shortages.
- Invasions disrupt local economies, particularly in regions dependent on agriculture.
- Loss of vegetation affects livestock feed, further threatening food security.
- Regions like East Africa and South Asia faced severe agricultural losses during the 2019-2021 upsurge.
- Long-term impacts include increased poverty and malnutrition in affected communities.
2. Estimate the role of climate change in the frequency and intensity of locust invasions.
- Climate change alters weather patterns, affecting locust breeding conditions.
- Increased temperatures and changing rainfall patterns can lead to more favorable conditions for locusts.
- Extreme weather events may create ideal habitats for locust swarms to thrive.
- Research indicates a correlation between climate variability and locust population surges.
- Future climate scenarios predict increased locust invasions due to these changes.
3. What is the significance of remote sensing in agricultural pest management? Discuss with examples.
- Remote sensing provides real-time data on vegetation health and land cover.
- It helps identify potential breeding sites for pests like desert locusts.
- Remote sensing can track environmental changes that affect pest populations.
- Examples include using satellite imagery to monitor locust swarm movements and vegetation availability.
- This technology enhances early warning systems for pest invasions, aiding timely interventions.
4. Point out the measures that can be taken to mitigate the effects of locust swarms on smallholder farmers.
- Implement early warning systems using predictive modelling to anticipate invasions.
- Promote sustainable agricultural practices to enhance resilience against locust damage.
- Provide training and resources for farmers to manage locust outbreaks effectively.
- Encourage government support for pest control measures and financial assistance post-invasion.
- Strengthen regional cooperation for coordinated responses to locust threats.
