Dataset DOI: 10.5061/dryad.wdbrv1635

Description of the data and file structure

This dataset compiles the raw data and R analysis scripts related to a research project on the Yangtze River fishing ban.

The project integrates raw field data with a suite of advanced statistical analyses and visualizations in R.

It is structured into 11 thematic modules, each addressing a specific research question—from basic community metrics (diversity, size structure) to advanced topics like functional traits, spatial distribution, rare species conservation, and causal modeling.

It constitutes a finalized and cohesive analytical pipeline, designed to ensure full reproducibility and readiness for publication.

All data and scripts are organized by research theme into main files, facilitating the reproduction of study results and further investigation.

Files and variables

Overall data set file: 20260131_Yangtze_Fishing_Ban_Raw_data_and_R_code.zip

Note:

•.RData = Work Environment Archive (store objects)

•.RDataTmp = Temporary backup when auto-saving (can be ignored)

•.Rhistory = Command History (store code)

Folder1: Raw data

Description:

Name: Raw data.xlsx

This raw_data.xlsx contains the integrated raw field and laboratory data from a comprehensive ecological survey.

This is primary observed and measured data, not an output from analytical scripts.

The dataset includes the following sheets:

Sheet name: Sampling location

It includes Site ID, Longitude, and Latitude for each site.

Sheet name: Abundance (ind)

It includes Site ID, Netting area, Time (YYYYMM, the same as below), and abundance of each of the fish species collected from each site.

Sheet name: Biomass (g)

It includes Site ID, Netting area, Time, and biomass of each of the fish species collected from each site.

Sheet name: Fish Body Characteristics Index

It includes Time, Species name, Weight, Number (i.e., number of individuals; when the value is not 1, the total weight was recorded while no individual total length was recorded as we only measured some of the collected samples), Mean weight, and Total length of fish species collected.

Sheet name: Average Fulton Index

It includes Site ID, Time, and Fulton index for fish species collected.

A condition factor calculated as K = (W / L³) * 100, where W is weight and L is length

Sheet name: Porpoise and Chinese sturgeon

Records for the presence/abundance of key protected species, i.e., the Yangtze Finless Porpoise and Chinese sturgeon, in different years.

Sheet name: Functional Traits Comparison

It includes Name (fish species), Code (fish species abbreviation), and functional traits (i.e., Population, History strategy, Maximum body length, Diet, Migration type, Lifespan.

Sheet name: Environmental factors

It includes Site ID, Time,

Water quality parameters:

• WT or water temperature, °C,
• TUR or turbidity, NTU,
• Cond or conductivity, μS/cm,
• DO or dissolved oxygen, mg/L,
• pH, pH unit,
• SD or Secchi Disk visibility, cm,
• Cl or chloride, mg/L
• TA or total hardness, mg/L,
• TP or total phosphorus, mg/L,
• PO4 or phosphate, mg/L
• TN or total nitrogen, mg/L
• NH4 or ammonia, mg/L
• NO3 or nitrate, mg/L
• NO2 or nitrite, mg/L
• Chla or chlorophyll a, μg/L
• TSS or total suspended solids, mg/L

Land use parameters:

• Water, %
• Forest, %
• Wetland, %
• Cropland, %
• Urban, %
• Bareland, %
• Clouds, %
• Grassland, %

Hydrology parameters:

• WL or water level, m
• Flow, m³/s
• MR or monthly runoff, m³

Climate parameters:

• MACP or monthly average cumulative precipitation, cm
• MAP or monthly average precipitation, cm
• MMAT or monthly maximum air temperature, °C
• MMIT or monthly minimum air temperature, °C
• MAT or monthly average air temperature, °C
• Navigation, number of shipping vessels
• Fishing, number of fishing boats
• Shoreline modification, %.

Folder2: Analysis of diversity and body length

Description:

This folder contains the complete R project workspace, raw data, processed datasets, analysis scripts, and generated results for the analysis of fish community diversity and body size metrics (length/weight).

The structure includes both input data and the outputs of statistical tests and visualizations, allowing for the full replication of the analytical workflow from raw data to final figures and statistical summaries.

Data.csv

Name: Abundance data.csv

The "Abundance data.csv" in the file represents a processed metric of species density, standardized to individuals per 10 square meters (ind/10m²), rather than a simple raw count. This standardization allows for direct comparison of species abundance across different sampling locations or efforts.

Name: Diversity.csv

• group1: Treatment or temporal state, indicating whether sampling occurred before ("Before") or after ("After") the implementation of an ecological intervention.
• group2: Survey year, indicating the calendar year in which the sampling was conducted (e.g., ranging from 2018 to 2023).
• group3: Seasonal or hydrological period (e.g., "Wet" for the wet season, "Dry" for the dry season).
• group4: Spatial zone within the study area, identifying the specific river reach (e.g., "Middle" for mid-reach, "Lower" for downstream reach).
• group5: Specific measure group under the before or after intervention conditions, representing finer sub-categorization based on the type or intensity of the applied measures.
• Richness: Species richness, representing the number of distinct fish species observed or estimated in the sample.
• Evenness: Species evenness index, quantifying the distribution of individual abundances among the species present in the community (e.g., Pielou's evenness).
• Total_fish_abundance: Total fish abundance, expressed as the number of individuals per 10 square meters (ind/10m²).
• Total_fish_biomass: Total fish biomass, representing the combined wet weight (g/10m²) of all fish collected in the sample.
• Large_fish_abundance: Abundance of large fish, expressed as the number of large individuals per 10 square meters (ind/10m²), based on a defined size threshold.
• Small_fish_abundance: Abundance of small fish, expressed as the number of small individuals per 10 square meters (ind/10m²), based on the same size threshold.
• Large_fish_biomass: Biomass of large fish, representing the total wet weight (g/10m²) contributed by all large fish in the sample.
• Small_fish_biomass: Biomass of small fish, representing the total wet weight (g/10m²) contributed by all small fish in the sample.

Name: group.csv

• group1: Survey year, indicating the calendar year in which the sampling was conducted (e.g., ranging from 2018 to 2023).
• group2: Seasonal or hydrological period (e.g., "Wet" for the wet season, "Dry" for the dry season).

Name: Mountain Peak Map.csv

• Time：Survey year, indicating the calendar year in which the sampling was conducted (e.g., ranging from 2018 to 2023).
• SP：Abbreviation or code representing fish species
• Weight：weight(g) for the recorded group or sample
• Total: Total length (mm)

R File (.R)

Name: Box plots

Diversity, abundance, and biomass index comparison before and after fishing ban

Name: Diversity box chart - Yearly changes

Comparison of diversity, abundance and biomass indices over the years

Name: Mountain Peak Map

Graph showing the body length of fish species

Name: Wilcoxon_cohen_results

Data sensitivity verification (comparing whether there are significant differences in the combination of data from different years)

Folder3: β diversity

Description:

This folder contains all data, scripts, and results specifically related to the analysis of beta diversity (β-diversity).

The workflow encapsulated here typically involves calculating dissimilarity indices (such as Bray-Curtis or Jaccard), visualizing compositional differences, and statistically testing whether compositional differences exist between predefined groups.

Data.csv

Name: Abundance data.csv

The "Abundance data.csv" in the file represents a processed metric of species density, standardized to individuals per 10 square meters (ind/10m²), rather than a simple raw count. This standardization allows for direct comparison of species abundance across different sampling locations or efforts.

The original names of the species can be found in Raw data (Abundance(ind)/Biomass(g))

Name: Diversity.csv

• group1: Treatment or temporal state, indicating whether sampling occurred before ("Before") or after ("After") the implementation of an ecological intervention.
• group2: Survey year, indicating the calendar year in which the sampling was conducted (e.g., ranging from 2018 to 2023).
• group3: Seasonal or hydrological period (e.g., "Wet" for the wet season, "Dry" for the dry season).
• group4: Spatial zone within the study area, identifying the specific river reach (e.g., "Middle" for mid-reach, "Lower" for downstream reach).
• group5: Specific measure group under the before or after intervention conditions, representing finer sub-categorization based on the type or intensity of the applied measures.
• Richness: Species richness, representing the number of distinct fish species observed or estimated in the sample.
• Evenness: Species evenness index, quantifying the distribution of individual abundances among the species present in the community.
• Total_fish_abundance: Total fish abundance, expressed as the number of individuals per 10 square meters (ind/10m²).
• Total_fish_biomass: Total fish biomass, representing the combined wet weight (g/10m²) of all fish collected in the sample.
• Large_fish_abundance: Abundance of large fish, expressed as the number of large individuals per 10 square meters (ind/10m²), based on a defined size threshold.
• Small_fish_abundance: Abundance of small fish, expressed as the number of small individuals per 10 square meters (ind/10m²), based on the same size threshold.
• Large_fish_biomass: Biomass of large fish, representing the total wet weight (g/10m²) contributed by all large fish in the sample.
• Small_fish_biomass: Biomass of small fish, representing the total wet weight (g/10m²) contributed by all small fish in the sample.

R File (.R)

Name: β-diversity calculation

Calculate the changes in β diversity before and after the fishing ban and plot it

Name:β-diversity comparison Wilcoxon

Sensitivity test of the β-diversity index (under different year combinations)

Folder4: Analysis of fish fat content

Description:

Contains R workspace files (.RData, .RDataTmp, .Rhistory) and data files for analyzing fish condition factor (S Condition_factor) and fish body fat content (F Fish fat content).

This file supports the study of fish physiological status and energy reserves.

Data.csv

Name: Condition_factor

The annual variations of Fulton's condition factor for fish species

R File (.R)

Name：Fish fat content

A box plot showing the annual changes of Fulton's condition factor for fish species

Folder5: Analysis of rare species

Description:

Contains R workspace files and analysis scripts focused on rare and endangered species in the Yangtze River, particularly the Yangtze finless porpoise and Chinese sturgeon.

The file includes data and scripts for analyzing annual population changes and conservation status of these species.

Data.csv

Name: Rare_species

• The number of rare species
• group1: Treatment or temporal state, indicating whether sampling occurred before ("Before") or after ("After") the implementation of an ecological intervention.
• group2: Survey year, indicating the calendar year in which the sampling was conducted (e.g., ranging from 2018 to 2023).
• Species include Acipenser dabryanus/Myxocyprinus asiaticus/Ochetobius elongatus

Name: Yangtze_finless_porpoise_and_Chinese_sturgeon

The number of Yangtze finless porpoises and Chinese sturgeons

Sheet1：Yangtze finless porpoises (ind)

Sheet2：Chinese sturgeon harvested (ind)

R File (.R)

Name: Annual Changes of Rare Species

Draw the annual change chart of the species

Folder6: Dominant species of a community

Description:

Contains R workspace files and scripts for analyzing and visualizing dominant species in the fish community, using the Index of Relative Importance (IRI).

The file includes scripts for calculating IRI values and generating heatmaps to display community dominance patterns.

Data.csv

Name：Heat map of community dominance

The changes of the main dominant species in the community from one year to another

R File (.R)

Name：Calculate and draw a heatmap for the dominant species of the community (IRI)

Calculate and draw a heatmap for the dominant species of the community (IRI)

Folder7: Environmental factor box plot

Description:

Contains R workspace files and scripts for analyzing environmental factors associated with the sampling data.

The file includes the dataset of environmental variables and scripts to generate box plots for visualizing the distribution of these factors across different groups or conditions.

Data.csv

Name：Environmental factor

Including data grouping, diversity, abundance, biomass data and environmental data (such as temperature, total nitrogen, total phosphorus, etc., Table S1)

R File (.R)

Name：Environmental box plot

Draw the annual change charts for each environmental factor

Folder8: River and sea migration species map

Description:

Contains R workspace files and scripts for creating spatial distribution maps of migratory fish species in the Yangtze River.

The file includes geographical coordinate data and scripts to visualize species abundance in relation to longitude and latitude.

Data.csv

Name：Sampling longitude and latitude of the Yangtze River

It includes different groups based on time period and river reach, site longitude and latitude coordinates, and biomass and abundance of four migration species.

Name: The longitude and latitude of the Yangtze River

The latitude and longitude coordinates of the Yangtze River

R File (.R)

Name:Project the species abundance on the latitude and longitude coordinates

Display the locations where different species were collected on the map

Folder9: Shape stacked column chart (abundance and weight)

Description:

Contains R workspace files and scripts for creating stacked column charts to visualize the composition of fish functional traits.

This analysis compares trait distributions based on two different metrics: species abundance (number of individuals) and weight (biomass), highlighting how the functional structure of the community may differ when measured by count versus mass.

Data.csv

Name: Abundance-based traits

Based on the data of abundance and traits

Code(Species abbreviation)/Population resilience/History strategy/Maximum body length/Diet/Migration type/Lifespan, and different years (2018 - 2023)

Name: Weight-based traits

Based on the data of Weight and traits

Code (Species abbreviation)/Population resilience/History strategy/Maximum body length/Diet/Migration type/Lifespan, and different years (2018 - 2023)

R File (.R)

Name: Stacked column chart

Draw stacked column charts of functional traits based on abundance and biomass data for different years

Folder10: STAMP species difference analysis

Description:

Contains R workspace files and data for performing STAMP analysis.

This method is used to identify statistically significant differences in species (or genus) composition between two or more groups of samples (e.g., before vs. after fishing ban, different river sections).

The analysis is conducted separately using relative abundance data (based on individual counts) and relative weight/biomass data.

Data.csv

Name：abundance

• Abundance-based species quantity table
• Sheet1=Species abundance data
• Sheet2=Data grouping

Name: weight

Weight-based species quantity table

Sheet1=Species Weight data

Sheet2=Data grouping

R File (.R)

Name: STAMP Analysis

STAMP Analysis is used to analyze the species whose abundance and biomass have undergone significant changes before and after the fishing ban.

Folder11: Structural equation

Description:

This folder contains the complete workflow for constructing piecewise Structural Equation Models (piecewiseSEM) to investigate the causal drivers of fish community changes following the fishing ban. The analysis operates at two levels:

1.Overall community level: Modeling pathways from environmental/human drivers to total abundance/biomass and diversity indices (Richness, Evenness, β).

2.Size-based functional group level: Separately modeling the responses of large fish and small fish (in terms of abundance and biomass) to explore size-dependent mechanisms.

The models use Generalized Least Squares (GLS) regressions to account for potential spatial autocorrelation or heteroscedasticity in the data.

Name: subfolder1: Structural Equation Model

Data.csv

Name: Structural equation

Data grouping information / Diversity, abundance, biomass index / Numerous environmental factors

R File (.R)

Name: Evenness GLS: Species evenness

Name: Richness GLS: Species richness

Name: Total fish abundance GLS: Total fish count (ind/10m²)

Name: Total fish biomass GLS: Total fish biomass (g/10m²)

Name: Large fish abundance GLS: Abundance of large fish (ind/10m²)

Name: Large fish biomass GLS: Biomass of large fish (g/10m²)

Name: Small fish abundance GLS: Abundance of small fish (ind/10m²)

Name: Small fish biomass GLS: Biomass of small fish (g/10m²)

The GLS approach is specifically used to account for potential violations of independence in the data (e.g., spatial autocorrelation or temporal pseudoreplication) by specifying appropriate correlation and variance structures.

The script Structural equation is the core piecewise SEM script. It integrates the outputs from all the individual GLS models specified above to test the overall causal network, evaluate direct and indirect effects among variables, and assess the model's goodness-of-fit.

Name: subfolder2: β diversity

Data.csv

Name: Abundance data

Data grouping and species abundance data

Name: Structural equation

Data grouping information / Diversity, abundance, biomass index / Numerous environmental factors.

R File (.R)

Name:β GLS

The code for drawing the structural equation model is the same as that for other diversity indices.

Code/software

1. The data files (XLSX/XLS) can be viewed by Excel.
2. The code files (R file) can be viewed and run by R software (R 4.5.1).