Data from: Responses of protected groundwater-dependent vegetation communities to prolonged flooding along a lowland stream
Data files
Sep 04, 2026 version files 401.72 KB
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Groundwater_data.csv
7.37 KB
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Initial_vegetation_data.csv
13.21 KB
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README.md
8.30 KB
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Species_abbreviations.csv
5.12 KB
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Species_data.csv
364.05 KB
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Traits.csv
3.66 KB
Abstract
This dataset contains vegetation, plant trait and groundwater data from a six-year field experiment conducted in three alkaline-rich fen sites along Kastbjerg Å in northern Denmark. The experiment comprised control plots and three treatments: prolonged flooding with stream floodwater, prolonged flooding with natural sandy sediment (NSS), and prolonged flooding with organic-enriched sediment (OES) from an agricultural catchment. In the dataset, treatment categories are coded as Control, Water, Coarse and Fine, corresponding respectively to control plots, prolonged flooding with stream floodwater, prolonged flooding with natural sandy sediment (NSS), and prolonged flooding with organic-enriched sediment (OES). The dataset includes baseline vegetation data, repeated plant species frequency data, plant functional and ecological trait information, and groundwater data. Species are represented by abbreviations in the vegetation data, and a separate lookup table is provided linking these abbreviations to the full species names. Species frequency was derived from occurrence within a fixed grid of 16 sub-quadrats and is expressed in the dataset as the proportion of occupied sub-quadrats (0–1). Plant trait variables include maximum canopy height, Grime CSR strategy components and Ellenberg indicator values for nutrients, light and moisture. Groundwater data include water-level measurements and concentrations of ammonium, nitrate and phosphate at different soil depths and sampling times. The data can be reused to investigate temporal vegetation dynamics, plant community responses to flooding and sediment deposition, recovery trajectories, responses of alkaline rich fen indicator species, and relationships between species composition and functional traits. They may also support comparative studies of wetland vegetation responses to hydrological disturbance, sedimentation and nutrient enrichment, as well as research on the conservation and restoration of alkaline rich fens. Prior to establishment of the experiment, verbal permission to conduct the fieldwork was obtained from Mariagerfjord Municipality, the relevant local authority, and from the landowner. As permission was granted verbally, no permit or license number was issued.
Dataset DOI: 10.5061/dryad.xgxd254z1
Description of the data and file structure
Data were collected during a six-year field experiment conducted in three alkaline-rich fen sites along Kastbjerg Å in northern Denmark. The experiment comprised 60 permanent plots distributed across the three fen sites, including control plots and three experimental treatments: prolonged flooding with stream floodwater, prolonged flooding followed by deposition of natural sandy sediment (NSS), and prolonged flooding followed by deposition of organic-enriched sediment (OES) from an agricultural catchment. Vegetation was surveyed before treatment application and repeatedly throughout the experiment. Groundwater levels and nutrient concentrations were measured at selected sampling times and depths, and plant functional and ecological trait information was compiled for the recorded species.
The dataset is provided as five CSV files: Groundwater_data.csv, Initial_vegetation_data.csv, Species_data.csv, Traits.csv, and Species_abbreviations.csv. Each file and its variables are described below.
Files and variables
Note: CSV files use semicolon as cell delimiter and comma as a decimal delimiter.
File: Groundwater_data.csv
Description:
Contains groundwater nutrient and water-level measurements from the three fen sites at different sampling dates and depths.
Variables
Site = Study site / fen category (Fen1, Fen2, Fen3)
Sample = Sampling point identifier
Year = Sampling year
Month = Sampling month
Year.month = Combined year and month
Depth_cm = Sampling depth (cm)
NH4N = Ammonium-N (NH₄⁺-N) concentration (mg L⁻¹)
NO3N = Nitrate-N (NO₃⁻-N) concentration (mg L⁻¹)
PO4P = Phosphate-P (PO₄³⁻-P) concentration (mg L⁻¹)
Gwlevel = Groundwater level (cm) relative to the soil surface
Blank cells indicate that no measurement was available for the corresponding variable and sampling occasion.
File: Initial_vegetation_data.csv
Description:
Contains baseline vegetation data collected in July 2008, before the experimental treatments were applied. Each row represents an experimental plot.
Variables:
PlotID = Experimental plot identifier
Year = Sampling year
Month = Sampling month
Status = Fen site (Fen1, Fen2, Fen3)
Treatm = Experimental treatment
The remaining columns represent individual plant species, identified using species abbreviations. Vegetation was recorded using a fixed grid of 16 sub-quadrats. For each species, the value represents the proportion of the 16 sub-quadrats in which the species was recorded and ranges from 0 to 1. Valid frequency values therefore occur in increments of 0.0625 (1/16). A value of 0 indicates that the species was not recorded in any sub-quadrat.
File: Species_data.csv
Description:
Contains vegetation monitoring data from the experimental plots over the six-year study period. Each row represents one experimental plot at one sampling time.
Variables:
PlotID = Experimental plot identifier
Year = Sampling year
Month = Sampling month
Time = Time in months relative to the baseline survey (Time 0)
Status = Fen site (Fen1, Fen2, Fen3)
Treatm = Experimental treatment
The remaining columns represent individual plant species, identified using species abbreviations. For each species, the value represents the proportion of the 16 sub-quadrats in which the species was recorded and ranges from 0 to 1. Valid frequency values therefore occur in increments of 0.0625 (1/16). A value of 0 indicates that the species was not recorded in any sub-quadrat.
Treatment codes used in both vegetation files:
Control = Untreated control plots
Water = Prolonged flooding with stream floodwater
Coarse = Prolonged flooding followed by deposition of natural sandy sediment (NSS)
Fine = Prolonged flooding followed by deposition of organic-enriched sediment (OES) from an agricultural catchment
File: Traits.csv
Description:
Contains plant functional and ecological trait information for the species recorded in the vegetation dataset.
Variables:
species = Species abbreviation
CH = Maximum canopy height (m)
ELL_L = Ellenberg indicator value for light
ELL_F = Ellenberg indicator value for moisture
ELL_N = Ellenberg indicator value for nutrients
GC = Competitive component of Grime's CSR strategy
GS = Stress-tolerant component of Grime's CSR strategy
GR = Ruderal component of Grime's CSR strategy
GC, GS and GR are expressed as proportions representing the relative contribution of the competitive, stress-tolerant and ruderal components, respectively.
Blank cells indicate that trait information was not available for the corresponding species and variable.
File: Species_abbreviations.csv
Description:
Provides the correspondence between the species abbreviations used in the vegetation and trait files and the full scientific species names.
Variables:
Species = Full scientific species name
Species Abbreviation = Abbreviation used in the vegetation and trait files
Missing values
Blank cells indicate unavailable or unmeasured values. In the vegetation files, 0 is a valid value indicating that a species was not recorded in any of the 16 sub-quadrats and should not be interpreted as missing data.
Code/software
Statistical analyses associated with the study were performed in R version 4.4.2 using RStudio version 2024.12.1.
Groundwater nutrient analyses were conducted using one-way ANOVA with the aov function in the R package stats, followed by Tukey’s HSD post-hoc tests using the HSD.test function in the R package agricolae. Temporal changes in nutrient concentrations were analysed using linear mixed-effects models fitted with the lme function in the R package nlme. Estimated marginal means and contrasts were obtained using the emmeans and contrast functions in the R package emmeans.
Groundwater-level analyses used one-way ANOVA with the aov function in the R package stats for comparisons among fen sites and linear mixed-effects models fitted with the lmer function in the R package lme4 for temporal comparisons. Estimated marginal means were obtained using the R package emmeans, with Holm-adjusted multiple comparisons implemented using the cld function in the R package multcomp.
Initial vegetation analyses included Indicator Species Analysis using the multipatt function in the R package indicspecies, with permutation schemes generated using the how function in the R package permute. Multiple testing was controlled using the Benjamini–Hochberg procedure implemented with the p.adjust function in the R package stats. Shannon diversity was calculated using the diversity function in the R package vegan. Differences in richness, diversity and total frequency among fen sites were tested using the kruskal.test and pairwise.wilcox.test functions in the R package stats.
Plant trait community-weighted means (CWMs) were calculated using the functcomp function in the R package FD.
Species- and trait-based Principal Response Curve (PRC) analyses were performed using the prc function in the R package vegan. Significance of the first constrained PRC axis was tested using the anova.cca function with permutation tests, and complementary PERMANOVA analyses were conducted using the adonis2 function, both in the R package vegan.
Treatment effects on control-adjusted PRC scores (PRC1_rel) were evaluated using no-intercept linear models fitted with the lm function in the R package stats. Multiple-testing correction was performed using the p.adjust function with the Holm method.
No code or scripts are included with this dataset, and no code is required to access or interpret the deposited data.
Access information
Other publicly accessible locations of the data:
- None. The data are not currently available in any other public repository.
Data was derived from the following sources:
- None. The dataset consists of original data collected during the field experiment.