[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics]

Area of Science:

• Agricultural Entomology
• Spatial Statistics
• Pest Management

Context:

• Understanding the spatial distribution of insect pests like Chilo suppressalis is crucial for effective agricultural management.
• Classical methods for spatial analysis have inherent limitations, particularly concerning grid placement and its influence on results.
• Geostatistical approaches offer advanced tools for characterizing complex spatial patterns in biological populations.

Purpose:

• To analyze and compare the spatial distribution patterns of Chilo suppressalis using classical and geostatistical methods.
• To identify the limitations of classical spatial analysis techniques for pest distribution.
• To accurately characterize the spatial distribution, congregation intensity, and heterogeneity of Chilo suppressalis populations.

Summary:

• Geostatistics provided a comprehensive characterization of Chilo suppressalis spatial distribution, outperforming classical methods.
• At low densities, populations followed a Poisson distribution, shifting to an aggregative distribution at higher densities.
• Higher density populations exhibited spatial heterogeneity, with stronger spatial correlation in the line direction (115 cm) than in the row direction (264 cm), and an aggregation intensity of 0.1056 with a dependence range of 193 cm.

Impact:

• The findings demonstrate the superiority of geostatistics in analyzing pest spatial dynamics, offering more reliable data for management decisions.
• Accurate characterization of pest distribution and aggregation intensity can lead to more targeted and efficient pest control strategies.
• Understanding spatial heterogeneity informs the development of precision agriculture techniques for Chilo suppressalis management.