Data from: Drivers of amphibian richness in European ponds

López-de Sancha, Alejandro 1 ; Benejam, Lluís1; Boix, Daniel2; Briggs, Lars3; Cuenca-Cambronero, Maria1; Davidson, Thomas Alexander4; De Meester, Luc5; Fahy, Julie6; Lemmens, Pieter5; Martin, Beatriz7; Mehner, Thomas8; Oertli, Beat6; Rasmussen, Marzenna3; Graves, Helen9; Sayer, Carl9; Beklioğlu, Meryem10; Brys, Rein11; Brucet, Sandra1

Published Dec 16, 2024 on Dryad. https://doi.org/10.5061/dryad.hdr7sqvtq

Data files

Dec 16, 2024 version files 38.58 KB

Drivers_of_amphibian_richness_in_European_ponds.csv

32.11 KB
README.md
6.47 KB

Abstract

Amphibians are commonly occurring inhabitants of most lentic freshwater ecosystems, yet their global populations are in alarming decline. Ponds in particular play a crucial role in supporting amphibian biodiversity. In this study, we identified the main drivers influencing amphibian species richness by conducting a comprehensive ecological characterization in 201 ponds across seven European countries spanning a large latitudinal and longitudinal gradient. The amphibian species richness in each of these ponds was assessed using environmental DNA metabarcoding on water samples. The relative influence of climatic, local abiotic and biotic, and land use variables on variation in species richness across ponds was quantified using Boosted Regression Trees. Our results suggest that local factors, particularly chlorophyll-a concentration, but also pond area and depth, are the main drivers of amphibian richness, together with climatic variables such as annual mean precipitation and temperature. The highest richness was observed in low-nutrient, fishless, intermediate-sized, shallow ponds, located in warmer regions with higher precipitation rates. These potential drivers of amphibian richness should be considered in the planning and implementation of amphibian conservation and management actions.

README: Drivers of amphibian richness in European ponds

https://doi.org/10.5061/dryad.hdr7sqvtq

Description of the data and file structure

Project Description

This dataset explores the drivers of amphibian species richness across 201 European ponds in seven countries. It includes ecological characterizations derived from environmental DNA metabarcoding and environmental variables (climatic, land use, abiotic, and biotic). The aim is to identify key factors influencing amphibian biodiversity to inform conservation and management practices.

This dataset is associated with manuscript ECOG-07347 from the Ecography journal (DOI: 10.1111/ecog.07347).

Dataset Overview

File Name: Drivers_of_amphibian_richness_in_European_ponds.csv
Sheet Structure: The dataset includes columns for pond identifiers, country, environmental variables, amphibian species richness, and metadata on sampling conditions.
Variable Descriptions:
- Latitude and Longitude: Coordinates of ponds.
- Annual Temperature, Precipitation: Climatic data.
- Pond Area, Depth: Abiotic measurements.
- Chlorophyll-a, Fish Richness: Local biotic factors.

For more details, see the documentation in the dataset or the publication.

Usage Notes

Researchers should cite the original manuscript when using this data.
Ensure proper acknowledgment of the authors and institutions.

Contact Information

For inquiries about the dataset, please contact:

Alejandro López-de Sancha
Aquatic Ecology Group
University of Vic - Central University of Catalonia
Email: 93lopez.alejandro@gmai.com

Files and variables

Variables Included in the Dataset

The dataset contains the following variables, their descriptions, units, and summary statistics:

Variable Name	Description	Units/Categories	Minimum	Maximum	Average	Standard Deviation
Latitude	Distance of the pond from the Equator	Degrees (°)	40.13	56.28	48.68	5.48
Longitude	Distance of the pond from the Greenwich Meridian	Degrees (°)	-2.92	32.73	9.85	10.07
Mean annual temperature	Annual mean of the monthly mean temperature	Celsius degrees (°C)	7.74	15.47	10.62	1.81
Mean annual precipitation	Annual mean precipitation rate (both liquid and solid)	Meters per second (m/s)	1.38e-8	5.12e-8	2.83e-8	1.04e-8
Aridity index	Monthly potential evaporation divided by precipitation	Dimensionless	0.08	0.51	0.22	0.13
Precipitation seasonality	Annual coefficient of variation of precipitation sums	Percentage (%)	0.39	0.82	0.50	0.11
Pond area	Area of the pond	Square meters (m²)	12.9	14689	1526	2463
Pond depth	Mean depth of the pond	Meters (m)	0.12	5.30	1.02	0.90
Turbidity	Turbidity of the pond water	Nephelometric Turbidity Units (NTU)	0.00	2359	66.98	267.26
Total nitrogen	Total nitrogen concentration in the pond water	Milligrams per liter (mg/L)	0.33	10.10	1.83	1.48
Total phosphorus	Total phosphorus concentration in the pond water	Milligrams per liter (mg/L)	0.01	3.94	0.36	0.61
Chlorophyll-a concentration	Proxy for phytoplankton biomass	Milligrams per liter (mg/L)	0.05	314.04	33.91	52.46
Fish species richness	Number of fish species detected	Number of species	0.00	12	1.86	2.52
Emersed vegetation (pond)	Coverage of the pond by emersed vegetation	Percentage (%)	0.00	100	38.93	29.05
Emersed vegetation (perimeter)	Coverage of the pond perimeter by emersed vegetation	Percentage (%)	0.00	100	60.61	36.16
Open water	Percentage of open water within the pond	Percentage (%)	0.00	100	54.30	33.93
Arable land use (0-100m)	Percentage of arable land within a 100 m radius	Percentage (%)	0.00	100	26.38	32.95
Urban land use (0-100m)	Percentage of urban land use within a 100 m radius	Percentage (%)	0.00	50	2.48	6.93

Missing Values

Missing values are indicated as blank cells.
No other special characters (e.g., "NA") are used to represent missing data.

Code/software

To assess the effect of climatic, land use, and local abiotic and biotic variables on amphibian richness we used Boosted Regression Trees (BRTs). BRTs were implemented using the gbm package (Ridgeway 2007) in R, with additional functions outlined in Elith et al. (2008).

Elith, J., Leathwick, J.R. and Hastie, T. 2008. A working guide to bossted regression trees. – J. Anim. Ecol. 77: 802 – 813.