Data from: Broad-scale meta-analysis of drivers mediating adverse impacts of flow regulation on riparian vegetation
Data files
Jan 15, 2025 version files 60.78 KB
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All_species_abundance.csv
14.13 KB
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All_species_richness.csv
13.85 KB
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Non-native_species_abundance.csv
3.12 KB
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Non-native_species_richness.csv
4.07 KB
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README.md
25.61 KB
Abstract
Over two-thirds of global rivers are subjected to flow regulation. Although it is widely recognized that flow regulation can adversely affect riparian vegetation—a critical component of river ecosystems—the specific roles of various drivers remain poorly understood. To address this gap, we conducted a broad-scale meta-analysis, aiming to elucidate how different factors mediate the adverse impacts of flow regulation on riparian vegetation. This meta-analysis encompassed 59 papers, spanning 278 dams constructed on 146 rivers. We extracted data on four key indices of riparian vegetation: species richness and abundance of all riparian species, and those indices exclusively for non-native species. Indices were compared between regulated and free-flowing or pre-damming rivers to quantify the impact of flow regulation.
Our meta-analysis revealed a moderate but significant reduction in the richness and abundance of all riparian species under flow regulation, coupled with a strong increase in the abundance of non-native species. Riparian vegetation in arid and continental climate regions experienced stronger negative impacts than those in tropical and temperate climates. Furthermore, the adverse effects on riparian vegetation were more pronounced downstream of dams than upstream. Considering climate region, study identity, and relative position to the dam as random variables, it became evident that years since flow regulation emerged as the most important factor influencing species richness. Over time, richness gradually recovered from initially low levels. However, this recovery was slowed by increasing flow regulation intensity (percentage of annual runoff stored). Additionally, the impact was more evident in larger rivers. To support regulated river management, we recommend prioritizing the protection of riparian vegetation in arid and continental climates, with emphasis on areas downstream of dams, limiting flow regulation intensity, particularly in larger rivers, and monitoring non-native species to prevent disproportionate spread.
README
README for: Broad-scale meta-analysis of drivers mediating adverse impacts of flow regulation on riparian vegetation
Dataset Description
This dataset accompanies the meta-analysis titled "Broad-scale meta-analysis of drivers mediating adverse impacts of flow regulation on riparian vegetation", providing comprehensive data from 59 peer reviewed studies across 278 dams and 146 rivers. This dataset serves as a resource for exploring the roles of geographical and hydrological factors mediating adverse impacts of flow regulation on riparian vegetation.
Structure and Content
The dataset is organized into four primary tables:
1. All species richness
Contains data on species richness for all riparian plants, comparing regulated and control conditions.
2. All species abundance
Contains data on species abundance for all riparian plants, comparing regulated and control conditions.
3. Non-native species richness
Contains data on species richness for non-native riparian plants, under regulated and control conditions.
4. Non-native species abundance
Contains data on species abundance for non-native riparian plants, under regulated and control conditions.
Glossary of Variables and Abbreviations
The variables and abbreviations used in the dataset are categorized as follows:
1. Study Information
• Study: Indicates the source of the study, referencing the authors and publication year. A single study may contribute multiple comparisons and observations.
2. Geographical Information
• Country: The country where the dam is located.
• Continent: The continent where the dam is located.
• UpDownstreamDam: Indicates whether the affected riparian zone is located upstream or downstream of the dam.
3. Climate Variables
• Climate: The climate zone where the dam is located, classified using the Köppen-Geiger climate classification:
A: Tropical climate
B: Arid climate
C: Temperate climate
D: Continental climate
Bio_1: Annual Mean Temperature (℃).
Bio_4: Temperature Seasonality, expressed as the standard deviation multiplied by 100.
Bio_5: Maximum Temperature of the Warmest Month (℃).
Bio_12: Annual Precipitation (mm).
Bio_14: Precipitation of the Driest Month (mm).
Bio_15: Precipitation Seasonality, expressed as the Coefficient of Variation.
4. Flow Regulation Metrics
• DamNumber: The number of dams involved in the study. To avoid double counting, some rows may leave this field blank.
• RegulatedRiverNumber: The number of regulated rivers included in the study. Similar to DamNumber, some rows may leave this field blank.
• YearsSinceRegulation: The duration (in years) of flow regulation by the dam, calculated as the time from the dam's commissioning to the year the study was conducted.
• DOR (Degree of Regulation): Quantifies how dam storage alters the natural flow regime of downstream river reaches and affects upstream reservoir water levels.
5. Hydrological Metrics
• DIS: Long-term (1971–2000) naturalized discharge, expressed in cubic meters per second (m³/s), simulated using the global hydrological model WaterGAP.
6. Vegetation Metrics
• RegulatedMean: Mean values of riparian vegetation indices in regulated zones.
• RegulatedSD: The standard deviation of the vegetation indices in regulated zones.
• RegulatedN: The number of replicates used to calculate the mean vegetation indices in regulated zones.
• ControlMean: Mean values of riparian vegetation indices in control zones.
• ControlSD: The standard deviation of the vegetation indices in control zones.
• ControlN: The number of replicates used to calculate the mean vegetation indices in control zones.
• HedgesG: The standardized mean difference (Hedge’s g) used to measure the effect size of flow regulation on riparian vegetation.
• Vi_HedgesG: Represents the variance of the effect size (Hedges' g) for the impacts of flow regulation on riparian vegetation, specifically reflecting the precision and uncertainty of the effect size estimates.
7. Other Information
• NA: Indicates missing data.
ReadMe for R code
Code Description
This repository contains the code used for the meta-analysis titled "Broad-scale meta-analysis of drivers mediating adverse impacts of flow regulation on riparian vegetation." The code is organized into four main parts, each addressing different aspects of the study.
01-Code for Meta-analysis
Section 1: “Meta-analysis_All species richness” analyzes the effects of flow regulation on the richness of all riparian species.
Section 2: “Meta-analysis_All species abundance” examines the effects of flow regulation on the abundance of all riparian species.
Section 3: “Meta-analysis_Non-native species richness” investigates the effects of flow regulation on the richness of non-native riparian species.
Section 4: “Meta-analysis_Non-native species abundance” evaluates the effects of flow regulation on the abundance of non-native riparian species.
Analytical Aspects Covered in Each Script:
Overall Effect Sizes of Flow Regulation (Figure 2):
Aggregates data from all studies to estimate the overall impact of flow regulation on the vegetation index.
Effect Sizes Across Different Climate Regions (Figure 3):
Groups studies by climate regions to compare the effects of flow regulation on the vegetation index among climate regions.
Effect Sizes Upstream vs. Downstream of Dams (Figure 4):
Compares the effects of flow regulation on the vegetation index in riparian zones located upstream and downstream of dams.
02-Code for Model Fitting
This section focuses on analyzing the effects of bioclimatic variables on the responses of four vegetation indices to flow regulation. Specifically, it covers:
• The influence of bioclimatic variables such as annual precipitation, temperature seasonality, and precipitation seasonality (Table 2).
• Analyzing the richness and abundance of non-native species in riparian vegetation in response to key drivers:
Degree of Regulation (DOR)
Years Since Regulation
Discharge (DIS)
03-Code for Multilevel Mixed-effects Meta-regression
This section includes scripts for performing multilevel mixed-effects meta-regression models (Table 3). Specifically, these models analyze the effects of flow regulation metrics on all-species richness and all-species abundance by including key drivers such as:
Degree of Regulation (DOR)
Years Since Regulation
Discharge (DIS)
Note:
This analysis was not applied to non-native species richness or abundance due to a limited number of data points for these indices.
04-Code for Supplementary Information
This section provides additional analyses and visualizations that supplement the main findings of the study. The following subsections are included:
Bioclimatic Variable Comparisons Across Climate Regions (Table S5):
Compares bioclimatic variables for four vegetation indices across climate regions.
Distribution of Flow Regulation Metrics (Figure S2):
Analyzes the distribution of degree of regulation (DOR), years since regulation, and discharge (DIS) across climate regions for all vegetation indices.
Spearman’s Rank Correlation Analysis (Table S7):
Examines correlations among key drivers:
Degree of Regulation (DOR)
Years Since Regulation
Discharge (DIS)
Publication Bias Assessment (Figure S3):
Includes funnel plots and fail-safe N calculations to assess potential publication bias in the meta-analyses.
Data was derived from the following sources:
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