DOI: 10.5061/dryad.wdbrv1635
title: Data from: Fishing ban halts seven decades of biodiversity decline in the Yangtze River

description: This dataset includes the attachments related to the research conducted by
 Xiong et al., titled "Fishing ban halts seven decades of biodiversity
 decline in the Yangtze River". Our study involved evaluating
 effectiveness of the Yangtze fishing ban on improving biodiversity. We
 detected trends of biological indicators before and after the fishing ban.
 We also used Generalized Least-Squares-based Structural Equation Models to
 identify drivers of biological trends. Results from the current study
 bring hope for biodiversity recovery in other large rivers globally.
description: # Data from: Fishing ban halts seven decades of biodiversity decline in
 the Yangtze River Dataset DOI:
 [10.5061/dryad.wdbrv1635](https://doi.org/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, m^3^/s * MR or
 monthly runoff, m^3^ 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).