Estuarine cline in fish eDNA composition and ecotone between the inside and outside of locally enclosed areas
Data files
Apr 21, 2026 version files 12.77 MB
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changelist.csv
7.12 KB
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Database240917.json
12.72 MB
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datachecker.R
3.14 KB
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Fig-01.R
716 B
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Fig-02.R
2.40 KB
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Fig-03.R
2.36 KB
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Fig-04.R
6.58 KB
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Fig-05.R
972 B
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input_script.R
3.31 KB
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matmaker.R
11.12 KB
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Model_allcomb.R
8.12 KB
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README.md
5.78 KB
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STD.csv
1.60 KB
Abstract
Estuaries are dynamic environments where monitoring fish biodiversity and detecting ecological change can be logistically difficult and expensive. Environmental DNA metabarcoding offers a cost‐effective alternative for biodiversity assessment. However, recent studies have shown that sharp transitions in fish eDNA composition (ecotones) can occur across boundaries of enclosed areas within estuaries. If these ecotones are strong or occur at unknown locations, they may distort spatial patterns in fish community data. This study investigated the conditions under which such ecotones form and assessed their impact on patterns of fish eDNA distribution in estuarine systems. We compared fish eDNA composition inside and outside six enclosed areas within Tokyo Bay, an estuary with a strong salinity gradient. Our spatially nested sampling design revealed that fish eDNA composition varies along the gradients of salinity and total nitrogen and differs consistently between the inside and outside of localized enclosed areas. These contrasts between inside and outside communities were stronger at high‐salinity sites. Therefore, the choice of sampling location (inside versus outside) can significantly affect estimates of species richness, community structure, and species‐specific DNA concentrations at the bay‐wide scale. We conclude that eDNA ecotones across enclosure boundaries may lead to misinterpretation of fish biodiversity in estuarine systems, and recommend sampling from outside enclosed areas to more accurately capture estuary‐wide patterns of fish biodiversity.
Dataset DOI: 10.5061/dryad.9w0vt4btp
Description of the data and file structure
Estuarine cline in fish eDNA composition and ecotone between the inside and outside of locally enclosed areas
Description of the data and file structure
This dataset was collected for research presented in the following paper, which focuses on environmental DNA (eDNA) surveys targeting fish species:
Hosokawa, S., & Homma, S. (submitted). Estuarine cline in fish eDNA composition and ecotone between the inside and outside of locally enclosed areas
This study includes the eDNA composition of fish in Tokyo Bay. The dataset includes metabarcoding results. The dataset contains processed data used for analysis. Details of the sampling strategy and analysis methods are provided in the paper and supplementary information.
Files and variables
File: Fig-01.R
Description: This script performs ANOVAs on salinity, water temperature, and total nitrogen in Tokyo Bay.
File: Fig-02.R
Description: This script draws the fish community based on Bray-Curtis dissimilarity in Tokyo Bay and analyzes the explanatory variables relating to the fish community.
File: Fig-03.R
Description: This script draws the fish community based on Sørensen dissimilarity in Tokyo Bay and analyzes the explanatory variables relating to the fish community.
File: Fig-04.R
Description: This script analyzes the explanatory variables relating to the number of species in freshwater, brackish, marine, and combinations thereof.
File: Fig-05.R
Description: This script plots the monthly variability in the concentration of environmental DNA for Siganus fuscescens, along with its detection/non-detection status.
File: input_script.R
Description: This script is written for reading "Database240917.json".
File: datachecker.R
Description: This script is written for checking whether the data frame of environmental data is formed correctly . This process is read by input_script.R.
File: matmaker.R
Description: This script is written for forming the data frames of biological data and environmental data. This process is read by input_script.R.
File: Model_allcomb.R
Description: This script is written for analyzing models of all combinations in variables. This script is called by Fig-04.R.
File: Database240917.json
Description: This file includes the data of metabarcoding and related environments. To extract the data in this study, input_script.R, matmaker.R, and datachecker.R are needed.
File: STD.csv
Description: This file contains the read counts of three internal standard species (row) in 60 sites (column).
Variables
- Species: Names of three internal standard species
- SKIBA: Inside of Tokyo in August
- SKIBA: Inside of Tokyo in September
- SKIBA: Inside of Tokyo in October
- SKIBA: Inside of Tokyo in November
- SKIBA: Inside of Tokyo in December
- Wakasu: Outside of Tokyo in August
- Wakasu: Outside of Tokyo in September
- Wakasu: Outside of Tokyo in October
- Wakasu: Outside of Tokyo in November
- Wakasu: Outside of Tokyo in December
- A_p: Inside of Yokohama in August
- A_p: Inside of Yokohama in September
- A_p: Inside of Yokohama in October
- A_p: Inside of Yokohama in November
- A_p: Inside of Yokohama in December
- M_H: Outside of Yokohama in August
- M_H: Outside of Yokohama in September
- M_H: Outside of Yokohama in October
- M_H: Outside of Yokohama in November
- M_H: Outside of Yokohama in December
- Test_site: Inside of Kurihama in August
- Test_site: Inside of Kurihama in September
- Test_site: Inside of Kurihama in October
- Test_site: Inside of Kurihama in November
- Test_site: Inside of Kurihama in December
- Tomyodo: Outside of Kurihama in August
- Tomyodo: Outside of Kurihama in September
- Tomyodo: Outside of Kurihama in October
- Tomyodo: Outside of Kurihama in November
- Tomyodo: Outside of Kurihama in December
- MRI: Inside of Moroiso in August
- MRI: Inside of Moroiso in September
- MRI: Inside of Moroiso in October
- MRI: Inside of Moroiso in November
- MRI: Inside of Moroiso in December
- HMORO: Outside of Moroiso in August
- HMORO: Outside of Moroiso in September
- HMORO: Outside of Moroiso in October
- HMORO: Outside of Moroiso in November
- HMORO: Outside of Moroiso in December
- HOTA: Inside of Kyonan in August
- HOTA: Inside of Kyonan in September
- HOTA: Inside of Kyonan in October
- HOTA: Inside of Kyonan in November
- HOTA: Inside of Kyonan in December
- KYONAN: Outside of Kyonan in August
- KYONAN: Outside of Kyonan in September
- KYONAN: Outside of Kyonan in October
- KYONAN: Outside of Kyonan in November
- KYONAN: Outside of Kyonan in December
- TATE: Inside of Tateyama in August
- TATE: Inside of Tateyama in September
- TATE: Inside of Tateyama in October
- TATE: Inside of Tateyama in November
- TATE: Inside of Tateyama in December
- OKI: Outside of Tateyama in August
- OKI: Outside of Tateyama in September
- OKI: Outside of Tateyama in October
- OKI: Outside of Tateyama in November
- OKI: Outside of Tateyama in December
File: changelist.csv
Description: This list provides the species names after NCBI (1st column), for matching FishBase (2nd column), and for analysis in the study (3rd column). This file is read in the process of input_script.R.
Variables
- recordedspecies: Species name after NCBI
- changespecies: Species name for matching FishBase
- names_in_maintext: Species name for analysis in this study
Code/software
The statistical analysis was conducted in R v.4.4.1 as described in the paper.
