Generating Within-Plant Spatial Distributions of an Insect Herbivore Based on Aggregation Patterns and Per-Node...

Area of Science:

• Ecology
• Entomology
• Agricultural Science

Background:

• Predator-prey models often assume uniform interactions, neglecting spatial heterogeneity within plants.
• Herbivores like the silverleaf whitefly (Bemisia tabaci) exhibit non-uniform distributions, influenced by plant defenses and nutrient needs.
• Accurate spatial distribution data is needed to scale up functional responses in individual-based models.

Purpose of the Study:

• To develop an algorithm for generating explicit spatial counts of silverleaf whitefly nymphs within tomato plants.
• To create a tool for simulating whitefly distribution at the leaf and leaflet level.
• To support analytical frameworks for understanding predator-whitefly interactions in heterogeneous environments.

Main Methods:

• Developed an algorithm using plant size and whitefly numbers as inputs.
• Incorporated models for infestation probability based on nodal position and whitefly aggregation patterns.
• Estimated parameters using nymph counts from 30 artificially infested tomato plants.

Main Results:

• The algorithm successfully generated explicit spatial counts of silverleaf whitefly nymphs.
• Validation showed strong agreement between simulated and observed distributions of eggs and nymphs.
• The model effectively captures the aggregated nature of whitefly populations within plants.

Conclusions:

• The developed algorithm provides a robust method for simulating whitefly spatial distribution.
• This tool can enhance the realism of simulation models exploring pest-predator dynamics.
• Accounting for local heterogeneity is vital for accurate ecological modeling of insect pests.