Data from: Ecotonal gradients shape biodiversity of multiple estuarine taxa
Data files
Jun 16, 2026 version files 1.89 GB
-
Alpha.R
21.43 KB
-
Beta.R
45.80 KB
-
Env.csv
22.65 KB
-
EnvGradients.R
31.24 KB
-
Flooding.csv
38.52 MB
-
ID.csv
4.69 KB
-
MarshSalinities.csv
3.86 MB
-
Master.csv
7.15 MB
-
README.md
6.64 KB
-
RiverSalinities.csv
1.84 GB
Abstract
Estuaries are dynamic transition zones linking terrestrial, freshwater, and marine environments. Their steep environmental gradients govern the distribution and diversity of multiple taxonomic groups. Yet, how these gradients jointly shape biodiversity across terrestrial-aquatic interfaces remains underexplored. Here we analyzed α- and β-diversity across twelve taxonomic groups of microbiota, plants, and animals spanning marsh and riverine habitats along the Elbe Estuary (Germany). Principal component analyses identified salinity as a major axis of environmental variation across land and water, while flooding frequency in marshes and suspended particulate matter in the river were important environmental factors in the marshes and the river, respectively. Different taxa showed distinct associations with these gradients: α-diversity of mainly for small-bodied groups correlated with environmental gradients, whereas community composition varied strongly along estuarine gradients across most taxa. Salinity-related gradients explained the largest share of compositional variation, indicating characteristic halophilic taxa near the river mouth, for example Spartina anglica. This multi-taxon assessment captures parallel yet differing biodiversity patterns across the terrestrial-aquatic boundary, with salinity emerging as the most consistent organizing axis for both spatial turnover and nestedness of community composition. Together, these findings demonstrate how steep ecotonal gradients shape biodiversity across multiple taxonomic groups and habitat boundaries. In transitional ecosystems shaped by freshwater inflow and salinity regimes, such gradients are especially consequential as global change is projected to shift habitat boundaries. Considering these responses is essential for informing adaptive management and conservation in estuarine systems.
Dataset DOI: 10.5061/dryad.8cz8w9h6c
Description of the data and file structure
Estuaries are dynamic transition zones linking terrestrial, freshwater, and marine environments. Their steep environmental gradients govern the distribution and diversity of multiple taxonomic groups. Yet, how these gradients jointly shape biodiversity across terrestrial-aquatic interfaces remains underexplored. Here we analyzed α- and β-diversity across twelve taxonomic groups of microbiota, plants and animals spanning marsh and riverine habitats along the Elbe Estuary (Germany).
Files and variables
Overview
Data files:
- Master.csv: Biodiversity data (period decimal notation, delimiter: comma)
- Env.csv: Environmental data (period decimal notation, delimiter: comma)
- ID.csv: Location data (period decimal notation, delimiter: semicolon)
- RiverSalinities.csv: Detailed salinity data of the Elbe River (period decimal notation, delimiter: comma)
- MarshSalinities.csv: Detailed salinity data of the Elbe marsh sites (period decimal notation, delimiter: comma)
- Flooding.csv: Detailed flooding data of the Elbe marsh sites (period decimal notation, delimiter: comma)
R scripts:
- EnvGradients.R: Analysis of environmental gradients and extraction of PCA scores
- Alpha.R: Analysis of alpha-diversity patterns along the Elbe estuarine gradients
- Beta.R: Analysis of community composition and beta-diversity
File: Env.csv
Description: Data on environmental parameters collected in the study locations. Needed for: EnvGradients.R
Variables
- ID_SiteZone: Unique identifier for study location. Levels: “HH HM", "HH LM" ,"HH PZ","HW HM" ,"HW LM" ,"HW PZ","KW HM" ,"KW LM", "KW PZ", "BH", "ML", "TF", "ST", "BB", "MG"))
- Year: Year in which observation was recorded
- Season: Season in which observation was recorded
- Marsh_River: Distinction if observation stems from marsh or river sites. Levels: “river”, “marsh”
- Site_Paramerter: Description of the environmental parameter (see EnvGradients.R file for more details)
- Mean_Site_Parameter: Average value of this parameter at this study location
- Unit_Site_Parameter: Unit of this parameter
- SD_Site_Parameter: Standard deviation of this parameter
- N_Site_Parameter: Number of replicates to calculate the average value of this parameter
- YearSeason: he year and season in which this observation was recorded
File: ID.csv
Description: Data on additional information on the study locations. Needed for: EnvGradients.R
Variables
- Station: Name of the study location
- StationNumber: Number of the study location
- Stromkilometer: Number of the kilometer along the Elbe River
File: MarshSalinities.csv
Description: Data on salinity values in the marsh locations besides the Elbe River. Needed for: EnvGradients.R
Variables
- Location: Name of the study location
- Site: Name of the study location, specified
- TimeStamp: Time of observation
- CollDate: Date of observation collection
- Source: Indication of which source the observation stems
- Value: Value of Temperature In °C or Salinity in ‰
- Variable: Indication of which variable was observed
- day: Day of the observation
File: Master.csv
Description: Content: Data on the biodiversity of twelve different taxonomic groups in the Elbe estuary. Needed for: EnvGradients.R , Alpha.R and Beta.R
Variables
- ID_SiteZone: Unique identifier for study location. Levels: “HH HM", "HH LM" ,"HH PZ","HW HM" ,"HW LM" ,"HW PZ","KW HM" ,"KW LM", "KW PZ", "BH", "ML", "TF", "ST", "BB", "MG"))
- Marsh_River: Distinction if observation stems from marsh or river sites. Levels: “river”, “marsh”
- Taxon_Group: Twelve taxon group names. Levels: "soil microbiota", "microphytobenthos", "herbs" ,"arthropods", "mammals", "trees", "prokaryota", "eukaryota", "fish microbiota", "phytoplankton", "zooplankton", "fish"
- Taxon: Name of the taxon of this observation
- Mean_Abundance: Average abundance of this taxon at this study location
- Unit_Abundance: Unit of abundance
- SD_Abundance: Standard deviation of the abundance
- N_Abundance: Number of replicates to calculate the average abundance
- YearSeason: The year and season in which this observation was recorded
File: Flooding.csv
Description: Content: Data on the flooding frequency and duration in the marsh locations. Needed for: EnvGradients.R
Variables
- Location: Study Site (HH, KWK, HW)
- Site: Study Zone (HM, LM, PZ)
- TimeStamp: Date
- Rep: Number of Replicate
- metric: The parameter quantified
- Value: The Value of this parameter
File: RiverSalinities.csv
Description: Data on salinity values in the Elbe River. Needed for: EnvGradients.R
Variables
- Station: Name of the study location
- Date: Date of sampling
- Salinity: Measured salinity value in ‰
- Chloride: Chloride value (NA)
- Stromkm: Number of kilometers along the Elbe River
- Salinity_pred: predicted Salinity value (NA)
- Date2: Second date of sampling
- Stromkilometer: Number of kilometers along the Elbe River
File: EnvGradients.R
Description: This is the first script to be run as here we analyze the major environmental gradients structuring the river and marsh environments and it produces the PCA gradients “Scores.csv”, which are needed for Alpha.R and Beta.R.
Datafiles needed:
- Master.csv: Biodiversity data
- Env.csv: Environmental data
- ID.csv: Location data
- RiverSalinities.csv: Detailed salinity data of the Elbe River
- MarshSalinities.csv: Detailed salinity data of the Elbe marsh sites
- Flooding.csv: Detailed flooding data of the Elbe marsh sites
File: Alpha.R
Description: Here we analyze alpha-diversity patterns for all taxonomic groups.
Datafiles needed:
- Master.csv: Biodiversity data
- Scores.csv: Environmental gradients (produced in Env.Gradients.R)
File: Beta.R
Description: Here we analyze beta-diversity patterns for all taxonomic groups. We first carry out community composition analyses and then in a second step, distinguish nestedness and turnover.
Datafiles needed:
- Master.csv: Biodiversity data
- Scores.csv: Environmental gradients (produced In Env.Gradients.R)
Code/software
All analyses were conducted in R (v4.5.1; R Core Team, 2024) and the data and code to fully reproduce our analyses are openly accessible
