Data from: Cascading effects of earthworm invasion in tundra increase graminoid density and rodent grazing intensities
Cite this dataset
Jonsson, Hanna; Olofsson, Johan; Blume-Werry, Gesche; Klaminder, Jonatan (2023). Data from: Cascading effects of earthworm invasion in tundra increase graminoid density and rodent grazing intensities [Dataset]. Dryad. https://doi.org/10.5061/dryad.zpc866tbm
Abstract
Earthworms are being introduced to numerous ecosystems through human activities. Some non-native earthworm species have the potential to ‘geoengineer’ soils and increase plant nitrogen (N) uptake, but if the increased plant N concentrations can cause increased rodent grazing is not well known. In this study, we present findings from a common garden experiment with two tundra communities, meadow (forb dominated) and heath (shrub dominated), half of them subjected to four years of earthworm presence (Lumbricus spp. and Aporrectodea spp.). Within four summers, our earthworm treatment changed plant community composition by increasing graminoid density by on average 94 % in the heath vegetation and by 49 % in the meadow. Rodent winter grazing were more intense on plants growing in soils with earthworms, an effect that coincided with higher nitrogen concentrations in plants indicating a higher palatability. Moreover, although the earthworms decreased soil moisture, our proxy for plant community photosynthesis (greenness) was not negatively affected. We conclude that earthworm-induced changes in plant composition and trophic interactions may radically alter the functioning of tundra ecosystems.
README: Cascading effects of earthworm invasion in tundra increase graminoid density and rodent grazing intensities
https://doi.org/10.5061/dryad.zpc866tbm
The data set is from a common garden mesocosm experiment in Abisko, sub-Arctic Sweden running between 2017-2020.
More information about each variable is provided in the manuscript methods.
Description of the data and file structure
File ‘Data.xlsx’
Contains variables:
Variables of Mesocosm_properties:
“Plot_nr” = Number ID of each mesocosm
“Block_nr” = Number ID of the sand beds in which the mesocosm monoliths were placed.
“Treatment” = Worm /No worm whether the mesocosm plot had earthworm treatment or not
“Vegetationtype” = Mesocosm vegetation type (Heath or Meadow)
Variables from Vegetation inventory 2020 [hits/pin]:
“FORBS” = Pin intercept inventory of vegetation functional groups, the number of forb hits per pin for each mesocosm.
“GRAMINOIDS” = Pin intercept inventory of vegetation functional groups, the number of graminoid hits per pin for each mesocosm.
“DECIDUOUS_SHRUB” = Pin intercept inventory of vegetation functional groups, the number of deciduous shrub hits per pin for each mesocosm.
“EVERGREEN_SHRUB” = Pin intercept inventory of vegetation functional groups, the number of evergreen shrub hits per pin for each mesocosm.
“LICHEN” = Pin intercept inventory of vegetation functional groups, the number of lichen hits per pin for each mesocosm.
“MOSS” = Pin intercept inventory of vegetation functional groups, the number of moss hits per pin for each mesocosm.
Variables from Grazing inventory 16 june 2019:
“proportion_grids_grazed[%]”= Proportion of each mesocosm surface
“nr_grids_grazed”= Number of grid cells with traces of rodent grazing, out of 12 cells in total.
“nr_grids_ungrazed” = Number of grid cells without traces of rodent grazing, out of 12 cells in total.
Variable from Foliar Nitrogen:
“Total N%” = Percent total N in above ground plant biomass. We sampled plant biomass in 12 plots, three from each treatment. The rest of the rows lack data and this is indicated by "NA".
Variables from Soil water content [%]:
“June”= Soil water content in each mesocosm collected 29th of June 2019.
“July”= Soil water content in each mesocosm collected 23th of July 2019.
“August”= Soil water content in each mesocosm collected 31th of August 2019. Plot 1 is missing soil water content due to loss of data during the sampling. This row is indicated by "NA".
Dendrobaena octaedra
“D_oct_present”= Mesocosms where and individual of *Dendrobaena octaedr*a (a native earthworm species that was not a part of the earthworm treatment) was identified at the end of the experiment 2020 (0=no, 1=yes)
File ’NDVI_rawdata.xlsx’
Contains variables:
“Date_Time” = Date and time stamp when the NDVI was recorded.
“Plot_nr” = Number ID of each mesocosm and sensor
“NDVI_uncalibrated” = continuous measurements of normalized difference vegetation index (NDVI) from 23 sensors.
Comment:
For optimal light conditions (angle of the sun and shading) you should only use measurements sampled between 11am-2pm for analysis.
File ’NDVI_calibration.xlsx’
Contains variables:
“Plot_nr” = Number ID of each mesocosm
“Treatment” = Worm /No worm whether the mesocosm plot had earthworm treatment or not
“Vegetationtype” = Mesocosm vegetation type (Heath or Meadow)
“slope” = the slope calculated from the difference between continuous logged NDVI (as in NDVI_rawdata) and hand held measurements of NDVI.
“intercept” = the intercept calculated from the difference between continuous logged NDVI (as in NDVI_rawdata) and hand held measurements of NDVI.
Comment:
Use the calibration terms in the data file to calibrate the raw NDVI data for each sensor (Plot_nr): NDVIplot_nr = NDVI_uncalibratedplot_nr * slopeplot_nr + interceptplot_nr
Funding
Swedish Research Council for Environment Agricultural Sciences and Spatial Planning, Award: 2018-01312