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Environmental DNA Metabarcoding Effectively Detects Invasive Species, Pests, and Community Changes in Taiwan's Rice

Pritam Banerjee^1,2, Gobinda Dey², Kathryn A Stewart³

¹Department of Environmental Science, Policy, and Management University of California Berkeley California USA.

Ecology and Evolution

|April 13, 2026

Summary

This summary is machine-generated.

Environmental DNA (eDNA) analysis offers a rapid method for monitoring rice field biodiversity, including native and non-native pests. This approach efficiently surveys agricultural ecosystems, aiding pest and invasive species surveillance.

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Area of Science:

Agricultural Ecology
Molecular Ecology
Environmental Monitoring

Background:

Rice fields are vital agroecosystems susceptible to invasive pests.
Traditional biodiversity monitoring in rice fields is labor-intensive and time-consuming.
Environmental DNA (eDNA) presents a promising alternative for rapid community assessment.

Purpose of the Study:

To demonstrate the feasibility of using eDNA metabarcoding for assessing biodiversity in rice fields.
To identify native and non-native species, including major agricultural pests, within rice agroecosystems.
To evaluate the impact of cultivation phases on species richness and community composition.

Main Methods:

Collected eDNA samples from southern Taiwan rice fields during planting and harvesting.
Utilized eDNA metabarcoding targeting the COI gene for taxonomic identification.
Analyzed amplicon sequence variants (ASVs) to determine species presence and diversity.

Main Results:

Identified 77 animal ASVs, with 34 assigned to species level.
Detected 18 species, including three significant rice pests: Chilo suppressalis (native), Coptotermes formosanus (native), and Pomacea canaliculata (non-native).
Observed higher species richness during the planting phase compared to the harvesting phase, though differences in native/non-native taxa and cultivation phases were not significant.

Conclusions:

eDNA analysis is an efficient biomonitoring tool for rice agroecosystems.
This method allows for the detection of diverse native and non-native species, including pests.
Findings support the application of eDNA for pest, invasive species, and vector surveillance in Taiwan's rice fields.