Data from: Tracking the phenology of riverine insect communities using environmental DNA
Data files
Feb 05, 2026 version files 778.34 KB
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Data_and_Script.zip
773.63 KB
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README.md
4.71 KB
Abstract
The data contains three datasets and one R scripts used in the article "Tracking the phenology of riverine insect communities using environmental DNA". The three datasets contain the following:
- Presence/absence of aquatic insects based on eDNA sampling
- Information on the sampling sites
- Permutation tests
Aquatic insects are iconic and ecologically highly relevant inhabitants of riverine ecosystems. They are also often the target of monitoring programs to assess the ecological status of these lotic habitats. Environmental DNA (eDNA) techniques have been widely and successfully implemented to investigate freshwater insects and other macroinvertebrates. Commonly, such monitoring is conducted at one or two timepoints per year, despite the known phenology of aquatic insects' life history strongly affecting species presence—or detection—and population dynamics through the seasons. Here, we assessed if and to which extent eDNA can capture the temporal changes of the orders Ephemeroptera (mayflies), Plecoptera (stoneflies), Trichoptera (caddisflies), and Diptera (true flies). We carried out eDNA sampling at roughly monthly intervals from April to October at 25 sites across a whole river catchment in the northeastern part of Switzerland. We found pronounced, cyclic phenological trends in all orders but Trichoptera: the communities diverged from spring to summer and then in fall gradually returned closer to the spring state. The four orders exhibited different predominance in gains or losses of species detection throughout this time interval. Lastly, we found that field replicates, despite showing a relatively high local stochasticity, were able to provide a more complete assessment of aquatic communities. Field replicates, when used as a proxy for the frequency of observation of a species through the seasons, yielded comparable temporal patterns to the ones extracted from the Global Biodiversity Information Facility (GBIF) for about 35% of the investigated species. Overall, our findings demonstrate that eDNA techniques can be used to reveal intra-annual dynamics of aquatic insects. Given the current necessity to assess and monitor the biodiversity status of ecosystems, we therefore show that eDNA methods are a viable option to obtain a deeper understanding of the structuring of freshwater communities over time.
Dataset DOI: 10.5061/dryad.ffbg79d8m
Description of the data and file structure
This folder, Data_and_Script.zip, contains all the datasets and R scripts used in the study "Tracking the phenology of riverine insect communities using environmental DNA"
0_data folder contains the following datasets:
- EPTD_long_presence.txt
- sites_Necker.txt
- median_jaccard_permutation.rda
See below information on the dataset metadata.
1_R_script folder contains the R script used to run the data analysis.
In order for the R script to run without issues, do not rename or move the two folders.
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EPTD_long_presence.txt
Dataset containing information on the insect communities at the Necker.
Contains the following variables:
- taxon: ID of the organism at the highest taxonomic resolution available
- order: taxonomic rank, order
- family: taxonomic rank, family
- genus: taxonomic rank, genus
- species: taxonomic rank, species
- replicate: eDNA field replicate ID
- date: sampling date
- site_ID: unique site ID
- week_number: week number associated to the sampling date
- readnr: number of reads
- presence: presence (= 1) or absence (= 0) of the speciment. Only presences are reported here.
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sites_Necker.txt
Dataset containing information on the sampling sites at the Necker river.
Contains the following variables:
- site_ID: unique site ID
- Location: name of the location associated with the site_ID
- x: longitudinal coordinates of the site (coordinate system CH1903)
- y: latitudinal coordinates of the site (coordinate system CH1903)
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median_jaccard_permutation.rda
Dataset contains the output of the Jaccard permutations run at L231-249 of the R script
Code/software
Analysis was performed in R version 4.3.3. The analysis steps are described in the script.
The following packages and versions were used:
# RColorBrewer 1.1.3
# rstudioapi 0.16.0
# jsonlite 1.8.8
# wk 0.9.1
# magrittr 2.0.3
# farver 2.1.1
# adegraphics 1.0.21
# fields 15.2
# vctrs 0.6.5
# spdep 1.3.3
# base64enc 0.1.3
# terra 1.7.71
# htmltools 0.5.8.1
# forcats 1.0.0
# progress 1.2.3
# itertools 0.1.3
# plotrix 3.8.4
# betapart 1.6
# raster 3.6.26
# s2 1.1.6
# adegenet 2.1.10
# spData 2.3.0
# KernSmooth 2.23.22
# htmlwidgets 1.6.4
# adephylo 1.1.16
# plyr 1.8.9
# lubridate 1.9.3
# uuid 1.2.0
# traudem 1.0.3
# igraph 2.0.3
# mime 0.12
# lifecycle 1.0.4
# minpack.lm 1.2.4
# iterators 1.0.14
# pkgconfig 2.0.3
# elevatr 0.99.0
# Matrix 1.6.5
# R6 2.5.1
# fastmap 1.1.1
# shiny 1.8.1.1
# magic 1.6.1
# digest 0.6.35
# colorspace 2.1.0
# patchwork 1.2.0
# phylobase 0.8.12
# vegan 2.6.4
# labeling 0.4.3
# progressr 0.14.0
# fansi 1.0.6
# timechange 0.3.0
# httr 1.4.7
# abind 1.4.5
# mgcv 1.9.1
# compiler 4.3.3
# proxy 0.4.27
# withr 3.0.0
# DBI 1.2.2
# maps 3.4.2
# MASS 7.3.60.0.1
# base 4.3.3
# stats 4.3.3
# classInt 0.4.10
# permute 0.9.7
# tools 4.3.3
# units 0.8.5
# rncl 0.8.7
# ape 5.8
# httpuv 1.6.15
# glue 1.7.0
# graphics 4.3.3
# rcdd 1.6
# nlme 3.1.164
# promises 1.3.0
# grid 4.3.3
# sf 1.0.16
# cluster 2.1.6
# reshape2 1.4.4
# ade4 1.7.22
# generics 0.1.3
# snow 0.4.4
# seqinr 4.2.36
# gtable 0.3.4
# tzdb 0.4.0
# class 7.3.22
# tidyr 1.3.1
# hms 1.1.3
# sp 2.1.3
# xml2 1.3.6
# utf8 1.2.4
# foreach 1.5.2
# pillar 1.9.0
# adespatial 0.3.23
# stringr 1.5.1
# spam 2.10.0
# later 1.3.2
# splines 4.3.3
# dplyr 1.1.4
# lattice 0.22.5
# deldir 2.0.4
# tidyselect 1.2.1
# knitr 1.46
# xfun 0.43
# datasets 4.3.3
# stringi 1.8.3
# boot 1.3.29
# codetools 0.2.19
# interp 1.1.6
# tibble 3.2.1
# cli 3.6.2
# xtable 1.8.4
# geometry 0.4.7
# munsell 0.5.1
# OCNet 1.2.2
# Rcpp 1.0.12
# doSNOW 1.0.20
# rnaturalearth 1.0.1
# tidyverse 2.0.0
# utils 4.3.3
# png 0.1.8
# XML 3.99.0.16.1
# parallel 4.3.3
# picante 1.8.2
# RNeXML 2.4.11
# rgl 1.3.1
# ggplot2 3.5.0
# readr 2.1.5
# methods 4.3.3
# prettyunits 1.2.0
# dotCall64 1.1.1
# latticeExtra 0.6.30
# jpeg 0.1.10
# viridisLite 0.4.2
# rivnet 0.4.2
# scales 1.3.0
# grDevices 4.3.3
# e1071 1.7.14
# purrr 1.0.2
# crayon 1.5.2
# rlang 1.1.3
# cowplot 1.1.3
# fastmatch 1.1.4
Access information
GBIF data was derived from the following sources:
- GBIF.org. (15 November 2024) GBIF Occurrence Download. https://doi.org/10.15468/dl.gfqxj9