Dataset DOI: 10.5061/dryad.q2bvq83xm

Description of the data and file structure

These files contain the raw data and R codes used in the manuscript for the:

1. Analyses: Multimodel analysis to test for the best mathematical function to describe the lake ISAR.
2. GLMM: Mixed model to identify the lake features related to the richness metrics.
3. Power Function: Power function fit to extract the parameters z (slope) and c (intercept).

Files and variables

File: Supporting_information_S1.pdf

Description: Additional description of the methods used in the manuscript.

File: Supp_info_S2_lakeFeat_richn.csv

Description: Table containing the lake features and richness metrics used in the analyses.

Variables

• Lake | Name of the lake.
• Catchment | River basin or drainage system to which the lake belongs.
• Long | Longitude (decimal degrees) of the lake.
• Lat | Latitude (decimal degrees) of the lake.
• Elevation_m | Elevation of the lake surface above sea level (meters).
• Surface_area_km2 | Lake surface area (square kilometers).
• Maximum_depth_m | Maximum recorded depth of the lake (meters).
• Average_depth_m | Average depth of the lake (meters).
• Volume_10.6_m3_GL | Lake volume (10^6 cubic meters; gigaliters).
• Shore_length_hydrolake | Total shoreline length of the lake (kilometers).
• Dis_avg_hydrolake | Average discharge (water outflow) from the lake (cubic meters per second).
• Wshd_area_hydrolake | Watershed (catchment) area contributing to the lake (square kilometers).
• avg_surface_temp_domischetal2015 | Average surface water temperature (°C) based on Domisch et al. (2015).
• avg_air_temperature_chelsa | Average annual air temperature (°C) from CHELSA climate data.
• air_temp_range_chelsa | Annual range of air temperatures (°C) from CHELSA climate data.
• surf_temp_range_domischetal2015 | Annual range of surface water temperatures (°C) from Domisch et al. (2015).
• distance_to_river_mouth | Distance from the lake to the nearest river mouth entering the ocean (kilometers).
• distance_to_refugium | Distance from the lake to the nearest hypothetical glacial refugium (kilometers).
• mean_steepness | Mean terrain steepness of the lake’s surrounding watershed (degrees or percent, specify if known).
• range_steepness | Or slope; range (maximum - minimum) of terrain steepness in the watershed.
• D1.Total_native_Richness | Total richness of native species originally present in the lake.
• D1.Native.Salmonidae.richness | Richness of native Salmonidae species originally present in the lake.
• D2.Total.richness | Total species richness including both native and introduced species.
• D3.Total_Native_extant.richness | Richness of extant (currently surviving) native species.
• D5.Endemic | Number of endemic species.
• D6.Total.Extant.richness | Total extant species richness, including surviving native and introduced species.
• Endemism_proportion | Proportion of endemic species among the original native community.

File: Supp_info_S3_species_list.csv

Description: List of fish species

Variables

• Class | Taxonomic class of the species (e.g., Actinopterygii for ray-finned fishes).
• Order | Taxonomic order of the species.
• Family | Taxonomic family of the species.
• Genus | Taxonomic genus of the species.
• Species | Scientific species name (binomial nomenclature: Genus + species epithet).
• Lake | Name of the lake where the species was recorded.
• Drainage | Name of the drainage basin or river system associated with the lake.
• Origin | Species' biogeographic origin relative to the lake (e.g., native, introduced).
• Endemicity | Endemism status of the species in the lake (e.g., endemic, non-endemic).
• Extinction status | Current extinction or conservation status of the species within the lake (e.g., extant, extinct, locally extinct).

File: R.code.for.Fig1.zip

Description: R code to generate the Figure 1: Map of the lakes.

This folder contains the following subfolders or files:

• Figure1.Rmd: R script with all steps to generate Figure 1.

• richness.csv: dataframe containing the lake features and richness information. That is the same as Supp_info_S2_lakeFeat_richn.csv

  Note that to run this code, one will need to download data from HydroSHEDS (Messager et al. 2016; Lehner & Grill 2013). The code for that is provided.

File: R.code.for.Fig2.zip

Description: R code to generate the Figure 2: Mixed models.

This folder contains the following files:

1. Supporting_information_S2.csv: This is the same file as in Supp_info_S2_lakeFeat_richn.csv. Please, report to the variable description provided above.
2. Supporting_informatio_S4_GLMM.Rmd. R script to run the mixed models and generate Figure 2.

File: R.code.for.Fig3.zip

Description: R code to generate the Figure 3: Parameters of the power function.

This folder contains the following files:

1. richness.csv: This file also contains the same data available in Supp_info_S2_lakeFeat_richn.csv.  Report to the variable description provided above.
2. Figure3_Power_f.Rmd: This R script contains de code to generate Figure 3.

File: R.code.multimodel.zip

Description: R code to test for the best mathematical function for the distinct richness metrics.

This folder contains the following files:

1. R.code.for.multimodel_analyses_S5.Rmd: This is a R script to test for the best mathematical function to describe the relationship between lake area and species richness. 

2. R.code.for.multimodel_analyses_S5Ext.Rmd: In this R script we extended the analyses of the previous script to include sensitive tests, where a subset of the lakes were used.

3. multimodel_equations.csv: This file contains a list of the mathematical functions tested.

   Note that this is an adaptation of the R package developed by Rampal Etienne for this work (https://github.com/rsetienne/isars)

File: R.code.HydroLakes_CHELSA_EarthEnv.zip

Description: R code to extract lake features from HydroLakes, CHELSA bioclimatic data, and freshwater EarthEnv bioclimatic data.

This folder contains the following files:

1. Lake_list.csv: List of the 79 peri-Alpine lakes with their geographical coordinates in decimal degrees.

2. Data_from_Hydrolakes.Rmd. R script to obtain the bioclimatic variables for each peri-Alpine lake.

   Note that to run this script, one needs to obtain extra data from CHELSA (Karger et al. 2017), EarthEnv (Domisch et al. 2015), and HydroLAKES (Messager et al. 2016). The script is equipped with the code to download the necessary data.

File: R.code.Refugium_Ocean_Steepness.zip

Description: R code to calculate lake isolation metrics: distance to the ocean, distance to hypothetical glacial refugia, and steepness (aka slope).

This folder contains the following files:

1. R_code_Distance_To_Glacial_Refugia.Rmd. R script used to compute distance of the peri-Alpine lakes to the ocean, to glacial refugia, and their steepness (i.e., slope).

2. lakes_coords.csv: list of the peri-Alpine lakes with their geographical coordinates in decimal degrees.

   To run this script, it will be necessary to download an elevation map of Europe (European Environment Agency, 2023), a shapefile of the European Rivers (Copernicus, 2023), and a shape file of the lakes (Messager et al. 2016).

Code/software

Language and Environment

R Environment for Statistical Computing

Version

R 4.3.3

Dependencies

• AICcmodavg
• car
• corrplot
• cowplot
• DHARMa
• dplyr
• ggeffects
• ggnewscale
• ggplot2
• glmmTMB
• isars
• knitr
• MuMIn
• raster
• readxl
• rmarkdown
• rnaturalearth
• riverdist
• sars
• scales
• sf
• sjPlot
• terra

Access information

Data used here derivesfrom the following sources:

Bioclimatic variables: CHELSA v1.2 and EarthEnv:

• Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria‐Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. Scientific Data, 4, 170122. https://doi.org/10.1038/sdata.2017.122
• Domisch, S., Amatulli, G., and Jetz, W. (2015) Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution. Scientific Data 2:150073 doi:10.1038/sdata.2015.73.

Lake features: HydroLAKES, HydroBASINS and HydroRIVERS

• Messager, M. L., Lehner, B., Grill, G., Nedeva, I., & Schmitt, O. (2016). Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature Communications, 7, 13603. https://doi.org/10.1038/ncomms13603
• Lehner, B., Grill G. (2013): Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrological Processes, 27(15): 2171–2186.

Fish species richness

• Alexander, T. and Seehausen, O. 2021. Diversity, distribution and community composition of fish in perialpine lakes. “Projet Lac” synthesis report.: 282.
• Freyhof, J. and Kottelat, M. 2007. Handbook of European freshwater fishes.
• Gassner, H., Achleitner, D. and Luger, M. 2015. Guidance on srveying the biological quality elements Part B1 – Fish.: 40.
• Luger, M., Kammerlander, B., Pamminger-Lahnsteiner, B., Achleitner, D. and Gassner, H. 2025. Die Fischgemeinschaften in österreichischen Seen >50 ha: Erhebung und Bewertung nach EU-WRRL und ALFI (Austrian Lake Fish Index). - Österr. Wasser- Abfallwirtsch. in press.

Other dataset that were used in the process

• Copernicus, European Union's Copernicus Land Monitoring Service information. 2023. EU-Hydro River Network Database 2006-2012. European Union's Copernicus Land Monitoring Service information, DOI: 10.2909/393359a7-7ebd-4a52-80ac-1a18d5f3db9c.
• European Environment Agency, 2023. Elevation map of Europe, 1 km grid. d9cd252baa831ac4469ae055dbd8a8c1.