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Project Overview
This research develops a (Bayesian) statistical model, to predict the abundance of a crop pest or its natural enemies in a crop using samples from other crops that are growing nearby and within a certain period of time. This will allow estimates of how each neighbouring crop affects pest or enemy abundance in the focal crop, and how these effects change over space and time.
This model will use a large dataset gathered across Andalusia, Spain, which includes many commonly grown crops along with widespread and economically important pests and natural enemies. The analysis focuses on a subset of these, that affect the largest number of crops and reach the highest population densities.
Why This Matters
Movement of agricultural pests between neighboring crops, makes it harder for farmers to control them and leads to significant losses in yield. Meanwhile, their natural enemies that prey on these pests also move across crop boundaries and can help reduce crop damage. However, it is unclear which crop combinations encourage spillover of beneficial insects between crops while limiting the spread of harmful pests.
This research aims to improve understanding of pest and natural enemy population dynamics, and how cropping landscapes could be better configured for sustainable pest management. For example, farmers could reduce risk by separating crops that share pests, or anticipate pest pressure based on what crops are planted nearby earlier in the season.
Project Objectives
To understand the pest and enemy population dynamics of:
- Which crops are pests or their natural enemies are most likely to disperse between?
- How far apart in space (distance) should susceptible crops be planted to avoid outbreaks of pests, or to allow movement of natural enemies?
- During which months do pest or beneficial insect numbers in one crop influence what happens in nearby crops?
- Which variable or variables allow us to best predict pest or enemy spillover among crops?
