10.5061/DRYAD.1ZCRJDFV6
Krab, Eveline
0000-0001-8262-0198
Swedish University of Agricultural Sciences
Lundin, Erik
Swedish Polar Research Secretariat
Coulson, Stephen
University Centre in Svalbard
Dorrepaal, Ellen
Umeå University
Cooper, Elisabeth
UiT The Arctic University of Norway
Experimentally increased snow depth affects High Arctic microarthropods
inconsistently over two consecutive winters
Dryad
dataset
2022
FOS: Biological sciences
Svalbard tundra
Ecology: soil
soil fauna communities
Snow
fences
soil temperature
soil moisture
Ymer-80 stiftelse *
Arcum*
Wallenberg Academy Fellowship *
2012.0512
Swedish Research Council
https://ror.org/03zttf063
621-2011-5444
The Research Council of Norway
https://ror.org/00epmv149
230970
2022-05-13T00:00:00Z
2022-05-13T00:00:00Z
en
154950 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Climate change induced alterations to winter conditions may affect
decomposer organisms controlling the vast carbon stores in northern soils.
Soil microarthropods are abundant decomposers in Arctic ecosystems
affecting soil carbon release through their activities. We studied whether
increased snow depth affected microarthropods, and if effects were
consistent over two consecutive winters. We sampled Collembola and soil
mites from a snow accumulation experiment at Svalbard in early summer and
used soil microclimatic data to explore to which aspects of winter climate
change microarthropods are most sensitive. Community densities differed
substantially between years and increased snow depth in winter had
inconsistent effects. Increased snow depth hardly affected microarthropods
in 2015, but decreased overall abundance and altered relative abundances
of microarthropod groups and Collembola species after a milder winter in
2016. Although our increased snow depth treatment enhanced soil
temperatures by 3.2 ⁰C in the snow cover periods, the only good predictors
of microarthropod density changes were soil conditions around snowmelt.
Our study underpins that extrapolation of observations of decomposer
responses to altered winter climate conditions to future scenarios should
be avoided when communities are only sampled on a single occasion, since
effects of longer-term gradual changes in winter climate may be obscured
by inter-annual weather variability.
The published dataset encompasses: Soil invertebrate community (density,
ind. m-2) in 'Snoeco_microarhropods_Dryad.csv' Microarthropods
were identified to ‘group level’, ‘Collembola’, ‘Oribatid mites’,
‘Predatory mites’ (Prostigmata and Mesostigmata) and ‘Mite
juveniles/other’ (nymphal Oribatids and Mesostigmata and nymphal
Prostigmata) and counted. Collembola were identified to species or genus
level. Microarthropods were sampled as described: Three cores were taken
(ø 4.5 cm, 5-9 cm deep) from each fence/ambient plot from Salix
polaris-dominated patches. In increased snow depth plots, approximately 10
m west of the snow fence, in the early summer of 2015 (15th of July) and
2016 (6th of July). Cores were taken so that the samples always contained
the complete organic layer (on average approx. 5 cm thick (Semenchuk et
al. 2019) in which most microarthropods can be found, as well as a part of
the mineral soil (>1 cm), in which microarthropod densities are
generally low or absent 63. In 2015, these cores were stored at 6⁰ C and
transported to Abisko, Sweden for Tullgren extraction (12 bank Tullgren
funnel, Burkard Scientific, Uxbridge, UK) within four days after sampling.
In 2016, the cores were stored overnight at 6⁰ C and extracted in the same
type of Tullgren extractor at UNIS in Longyearbyen the day after sampling.
Both Tullgren extractions lasted for seven days to ensure the cores were
completely dry. Soil moisture (cm3 water per cm3 soil) in
'Snoeco_microarhropods_Dryad.csv' Data has been collected
according to description: Soil moisture at time of sampling (in both
sampled years) was determined gravimetrically from each plot using three
replicate (ø 4.5 cm, 5-9 cm deep) cores from Salix polaris-dominated
patches that were also used for microarthropod extraction. These cores
were weighed upon sampling, subsequently dried at ~ 35⁰C for seven days
during microarthropod extraction, and finally dried in an oven at 70 ⁰ C
for 48 hours. Water weight was assumed to correspond to volume, and soil
volumes were obtained by measuring the sampled soil depth to determine
soil moisture content (water volume/ volume). CWM: Commuity weighted mean
for Collembola body size in 'Snoeco_microarhropods_Dryad.csv'
Data has been obtained using the following calculations: Average body
size/length per Collembola species was determined for 30 randomly chosen
individuals per species (or as many individuals as available, a minimum 10
individuals) by measuring Collembola length from the head to tip of the
abdomen by a calibrated microscope (Leica, 40x magnification). The body
lengths obtained were used to calculate community weighted mean (CWM) body
size of the community. We calculate the CWM for a whole community as:
where nj is the number of species sampled in community j, Ak,j is the
relative abundance of species k in community j and FTk,j is the functional
trait of interest of species k in community j. Soil temperature (C) daily
average in 'Snoeco_Soil_temp_Dryad.csv' Soil temperature data as
used for analyses in this manuscript. Soil temperature data was obtained
as described: Each plot (F and C) had a temperature logger (Tinytag data
loggers, model TGP‐402 (Gemini)) placed just below the soil surface (in
the increased snow depth treatment where snow depth reaches ~150 cm), but
data from these loggers was not available for all plots in both years.
Analyses have been performed only for plots in which data was available
for both treatments (control and fence (deep snow area)) and years (n=6)
Presented data in file are average daily temperature means (inferred from
hourly logged data) for those plots for which a full dataset was avaialble
for both years. A complete description of methods and description of the
experimental setup can be found in the published manuscript
Corrections applied to Soil temperature data: As some temperature loggers
showed a drift in sensor readings (<20%), observed temperatures
were corrected before data analyses by defining the period before snowmelt
when soil temperatures are constantly close to 0 for multiple days (the
‘zero curtain’) . For some loggers, readings in this period were
consistently more than a degree above or below zero thus we corrected
year-round temperatures for this deviation.