Data from: Rapid shifts in bryophyte phenology revealed by airborne eDNA
Data files
Sep 24, 2025 version files 246.50 KB
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Data_Rel_abundance_Bengtsson_et_al_2025.csv
73.63 KB
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Data_Weekly_weather_Bengtsson_et_al_2025.csv
170.08 KB
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README.md
2.79 KB
Abstract
In our publication, “Rapid shifts in bryophyte phenology revealed by airborne eDNA”, we report on multi-decadal shifts in the phenology of spore dispersal in 16 bryophyte taxa based on the data deposited here. The dataset represents a subset of a unique 35-year time series of airborne environmental DNA (eDNA ) collected in Kiruna, northern Sweden. The observed phenological shifts indicate strong perturbations in bryophyte phenology, consistent with ongoing climate change, and demonstrate that the use of airborne particles analysed by eDNA methodology is a valuable complement to other monitoring methods. The main dataset provided here consists of pivot coordinates of relative abundance data for the selected taxa between 1974 and 2008. The time series comprises data for every week when mean temperatures reached 0 °C, for every second year. Environmental DNA was extracted from archived samples of air filters that had been collected weekly since the 1960s and stored in air-tight containers. The samples were shotgun sequenced, and the reads matched across all major organism groups, with a high proportion identified as bryophytes. We interpret the relative abundance of airborne bryophyte eDNA as a proxy for spore dispersal, because most mosses are wind-dispersed. We used these data to describe phenological change during the time series. To analyse relationships between the phenological shifts and climate, we used local weather data from the same years (weekly precipitation and temperature), obtained from the Swedish Meteorological Institute (SMHI, Griddad nederbörd- och temperaturdata — SMHI). These data are also provided here.
Dataset DOI: 10.5061/dryad.x95x69pxs
Description of the data and file structure
We provide two data sheets. The first contains a time-series (1974-2008) of weekly pivot coordinates representing eDNA based relative abundance data from 16 bryophyte taxa. The dataset is a subset of that used in the preprint Sullivan et al. (2023; https://doi.org/10.1101/2023.12.06.569882) that includes all organism groups detected in the samples. The eDNA was obtained from airborn particles captured in air filters collected in northern Sweden and subsequently sequenced. The second file contains local weather data from the site for the same period as the eDNA time series. Variables include weekly precipitation and temperature, obtained from the Swedish Meteorological and Hydrological Institute (SMHI).
Files and variables
File: Data_Rel_abundance_Bengtsson_et_al_2025.csv
Description: For every second year in the time series (1974-2008) the pivot coordinates are given for each measured week (weeks with mean temperature above °C) for each of the 16 bryophyte taxa. Pivot coordinates are transformed values that express the relative abundances as independent values between taxa allowing the use of standard statistical analyses without the bias introduced when using compositional data.
Variables
- genus: bryophyte taxon
- All other columns consist of relative abundance pivot coordinates with the column name format: yyyy_week number, e.g., 1974_21, i.e., the filter data from week 21 in 1974.
File: Data_Weekly_weather_Bengtsson_et_al_2025.csv
Description: The precipitation (mm) and temperature (°C) data for each week during 1997-2008 from the closest weather station to the filter collection site. The data were obtained fromSMHI: PTHBV - en areellt hgupplst klimatdatabas fr hydrologiska modellberakningar:
https://www.smhi.se/kunskapsbanken/hydrologi/pthbv-en-areellt-hogupplost-klimatdatabas-for-hydrologiska-modellberakningar-1.190268 Accessed 04 March 2024.
Variables
- year.week: year and week number
- year: year number
- week: week number
- temp.mean: mean temperature (°C)
- temp.max: maximum temperature (°C)
- temp.min: minimum temperature (°C)
- precip.mean: mean precipitation (mm)
- precip.sum: summed precipitation (mm)
- precip.max: maximum precipitation (mm)
- precip.min: minimum precipitation (mm)
Code/software
These data are in csv-format and can be read by the likes excel, any text processor and R, for example.