Data from: Environmental DNA metabarcoding effectively detects invasive species, pests, and community changes in Taiwan’s rice fields
Data files
Apr 01, 2026 version files 383 MB
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HF1a.R1.clean.fastq.gz
11.51 MB
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HF1aR2.clean.fastq.gz
12.62 MB
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HF1b.R1.clean.fastq.gz
14.99 MB
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HF1b.R2.clean.fastq.gz
16.66 MB
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HF2a.R1.clean.fastq.gz
18.37 MB
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HF2a.R2.clean.fastq.gz
19.66 MB
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HF2b.R1.clean.fastq.gz
24.07 MB
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HF2b.R2.clean.fastq.gz
26.93 MB
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HF3a.R1.clean.fastq.gz
300.52 KB
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HF3a.R2.clean.fastq.gz
328.31 KB
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HF3b.R1.clean.fastq.gz
5.59 MB
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HF3b.R2.clean.fastq.gz
6.42 MB
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HF4a.R1.clean.fastq.gz
4.68 MB
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HF4a.R2.clean.fastq.gz
5.34 MB
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HF4b.R1.clean.fastq.gz
6.85 MB
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HF4b.R2.clean.fastq.gz
7.64 MB
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PF1a.R1.clean.fastq.gz
8.49 MB
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PF1a.R2.clean.fastq.gz
9.47 MB
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PF1b.R1.clean.fastq.gz
8.82 MB
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PF1b.R2.clean.fastq.gz
9.94 MB
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PF2a.R1.clean.fastq.gz
4.33 MB
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PF2a.R2.clean.fastq.gz
4.74 MB
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PF2b.R1.clean.fastq.gz
9.47 MB
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PF2b.R2.clean.fastq.gz
10.51 MB
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PF3a.R1.clean.fastq.gz
17.66 MB
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PF3a.R2.clean.fastq.gz
20.03 MB
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PF3b.R1.clean.fastq.gz
12.20 MB
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PF3b.R2.clean.fastq.gz
14.16 MB
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PF4a.R1.clean.fastq.gz
24.31 MB
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PF4a.R2.clean.fastq.gz
27.01 MB
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PF4b.R1.clean.fastq.gz
9.40 MB
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PF4b.R2.clean.fastq.gz
10.48 MB
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README.md
4.30 KB
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stats.txt
2.02 KB
Abstract
Rice fields represent man-made semi-aquatic wetlands primed for invasive pests. Monitoring rice field biodiversity using conventional methods, however, is time-consuming and laborious. Environmental DNA (eDNA) methods can provide a fast and effective means to monitor rice field communities and inform management decisions. Our study provides proof-of-concept of rice field eDNA biodiversity assessments, with a focus on native and non-native pests across cultivation phases. We collected eDNA samples from locations in southern Taiwan during planting and harvesting, employing eDNA metabarcoding (COI) to detect diverse taxonomic groups. We assigned 78 ASVs across all sites to animal taxa, 34 of which were identified to species. Overall, 18 species were designated as native or non-native (83.3 % and 16.6 %, respectively), including three major rice pests, Chilo suppressalis (native), Coptotermes formosanus (native), and Pomacea canaliculata (non-native). Cultivation affected overall diversity, with higher species richness during planting compared to harvesting. No significant differences were observed between native and non-native taxa between cultivation phases. Altogether, we detected a complex environment across trophic levels comprised of both native and non-native agricultural pests using limited sampling effort, demonstrating eDNA as an efficient biomonitoring approach in rice agroecosystems with direct applications for pest, invasive species, and vector surveillance within Taiwan.
Dataset DOI: 10.5061/dryad.mw6m9069f
Description of the data and file structure
Description of the data and file structure
1. General Information
Title of Dataset
Environmental DNA Metabarcoding Effectively Detects Invasive Species, Pests, and Community Changes in Taiwan’s Rice Fields
Authors and Affiliations
Pritam Banerjee1,2,*, Gobinda Dey2, Kathryn A. Stewart3, Matthew A. Barnes4, Md. Taharia2, Mathew Seymour5, Chin-Wen Wang2, Raju Kumar Sharma2, Jyoti Prakash Maity6, Chien-Yen Chen2, 8,*
1Department of Environmental Science, Policy, and Management, University of California, University Avenue and Oxford St, Berkeley, CA, 94720, USA
2Department of Earth and Environmental Sciences, National Chung Cheng University, 168 University Road, Min-Hsiung, Chiayi County 62102, Taiwan.
3Institute of Environmental Sciences, Leiden University, Leiden, 2333 CC, The Netherlands
4Department of Natural Resources Management, Texas Tech University, Lubbock, Texas, USA
5School of Biological Sciences, The University of Hong Kong SAR, China
6Department of Chemistry, School of Applied Sciences, KIIT Deemed to be University, Bhubaneswar, Odisha 751024, India.
8Center for Nano Bio-Detection, Center for Innovative Research on Aging Society, AIM-HI, National Chung Cheng University, Chiayi 62102, Taiwan
Date of Data Collection
- Sampling Period: 22 February 2022 (planting phase), and 31 May 2022 (harvesting phase)
Geographic Location
- Sampling Sites: Minxiong Township, Chiayi County, Taiwan
Contact Information
- Contact Person: Pritam Banerjee
- Email: [pritam8683@gmail.com]
- Affiliation: Department of Environmental Science, Policy, and Management, University of California, University Avenue and Oxford St, Berkeley, CA 94720, USA
2. Dataset Description
Files Included
- HF1a.R1.clean.fastq.gz
- HF3b.R2.clean.fastq.gz
- PF2b.R1.clean.fastq.gz
- HF1aR2.clean.fastq.gz
- HF4a.R1.clean.fastq.gz
- PF2b.R2.clean.fastq.gz
- HF1b.R1.clean.fastq.gz
- HF4a.R2.clean.fastq.gz
- PF3a.R1.clean.fastq.gz
- HF1b.R2.clean.fastq.gz
- HF4b.R1.clean.fastq.gz
- PF3a.R2.clean.fastq.gz
- HF2a.R1.clean.fastq.gz
- HF4b.R2.clean.fastq.gz
- PF3b.R1.clean.fastq.gz
- HF2a.R2.clean.fastq.gz
- PF1a.R1.clean.fastq.gz
- PF3b.R2.clean.fastq.gz
- HF2b.R1.clean.fastq.gz
- PF1a.R2.clean.fastq.gz
- PF4a.R1.clean.fastq.gz
- HF2b.R2.clean.fastq.gz
- PF1b.R1.clean.fastq.gz
- PF4a.R2.clean.fastq.gz
- HF3a.R1.clean.fastq.gz
- PF1b.R2.clean.fastq.gz
- PF4b.R1.clean.fastq.gz
- HF3a.R2.clean.fastq.gz
- PF2a.R1.clean.fastq.gz
- PF4b.R2.clean.fastq.gz
- HF3b.R1.clean.fastq.gz
- PF2a.R2.clean.fastq.gz
- stats.txt
3. Methods
Sample Collection
- Environmental DNA samples collected during planting and hervesting time of rice from Minxiong Township, Chiayi County, Taiwan 62102.
DNA Extraction and Sequencing
- DNA was extracted using the DNeasy Blood & Tissue Kit.
- The mitochondrial COI gene was amplified for metabarcoding.
- Sequencing was conducted on the Illumina MiSeq.
Data Analysis
- Sequence reads were quality filtered and trimmed using Cutadapt (v3.4), DADA2.
- Taxonomic assignments were performed using NCBI Blast.
- Diversity analyses and visualizations were carried out in R using the vegan and phyloseq packages.
4. Usage Notes
- Raw Data:
- FASTQ files can be re-analyzed using bioinformatics pipelines such as QIIME2 or DADA2.
5. Licensing and Citation
License
CC0
Citation
Please cite this dataset as:
Banerjee, P., et al. (2026). Dataset for: Environmental DNA Metabarcoding Effectively Detects Invasive Species, Pests, and Community Changes in Taiwan’s Rice Fields Dryad Digital Repository. https://doi.org/10.5061/dryad.mw6m9069f.
6. Limitations
- The dataset reflects observations from specific geographic locations and sampling conditions.
- Interpretation of species interactions may require consideration of environmental and ecological context.