DOI: 10.5061/dryad.t3g68
title: Data from: Short-term climate change manipulation effects do not scale up to long-term legacies: effects of an absent snow cover on boreal forest plants

description: 1. Despite time lags and non-linearity in ecological processes, the
 majority of our knowledge about ecosystem responses to long-term changes
 in climate originates from relatively short-term experiments. 2. We
 utilized the longest ongoing snow removal experiment in the world and an
 additional set of new plots at the same location in northern Sweden to
 simultaneously measure the effects of long-term (11 winters) and
 short-term (1 winter) absence of snow cover on boreal forest understorey
 plants, including effects on root growth and phenology. 3. Short-term
 absence of snow reduced vascular plant cover in the understorey by 42%,
 reduced fine root biomass by 16%, reduced shoot growth by up to 53%, and
 induced tissue damage on two common dwarf shrubs. In the long-term
 manipulation, more substantial effects on understorey plant cover (92%
 reduced) and standing fine root biomass (39% reduced) were observed,
 whereas other response parameters, such as tissue damage, were observed
 less. Fine root growth was generally reduced, and its initiation delayed
 by c. 3 (short-term) to 6 weeks (long-term manipulation). 4. Synthesis We
 show that one extreme winter with a reduced snow cover can already induce
 ecologically significant alterations. We also show that long-term changes
 were smaller than suggested by an extrapolation of short-term manipulation
 results (using a constant proportional decline). In addition, some of
 those negative responses, such as frost damage and shoot growth, were even
 absolutely stronger in the short-term compared to the long-term
 manipulation. This suggests adaptation or survival of only those
 individuals that are able to cope with these extreme winter conditions,
 and that the short-term manipulation alone would over-predict long-term
 impacts. These results highlight both the ecological importance of snow
 cover in this boreal forest, and the value of combining short- and
 long-term experiments side by side in climate change research.
description: damagedamage.csv - measured on
 one occasion - 'plot' shows plot number - 'treatment'
 shows treatment, 'contr' = control, 'new' = short-term
 manipulation (1 yr), 'old' = long-term manipulation (11 yrs) -
 'species' shows species, 'myrt'=Vaccinium myrtillus,
 'vitis'=Vaccinium vitis-idaea - 'individual' damage is
 measured on 5 individuals per plot (the same as shoot elongation),
 averaged per plot for statistical analysis - 'damage.percent'
 shows visible frost damage in % of tissues of individual
 affectedelongationelongation.csv - 'Plot_nr' shows plot number - 'Plot' shows treatment, 'contr' = control, 'new' = short-term manipulation (1 yr), 'old' = long-term manipulation (11 yrs) - 'individual' shoot elongation (growth) is measured on 5 individuals per plot , averaged per plot for statistical analysis - 'replicate' for Vaccinium myrtillus, elongation of several shoots per individual, averaged per individual for statistical analysis - 'growth[mm]' shoot growth in mmphenologyphenology.csv - 'date'shows the different days, 1= 18th May, 2= 26th May, 3= 1st June, 4= 8th June - 'plot' shows plot number - 'treatment' shows treatment, 'contr' = control, 'new' = short-term manipulation (1 yr), 'old' = long-term manipulation (11 yrs) - 'species' shows species, 'myrt'=Vaccinium myrtillus, 'vitis'=Vaccinium vitis-idaea - bbch.leaf refers to the categories of leaf of the BBCH scale, bbch.flower to flower stages (not included in analysis as this was a year of particulalry few flowers) - we focused in our analysis on when species earliest reached at least 2 steps: 7 (bud burst) and 10 (leaf unfolded), as those were the most clear onesroot length and growthroot length and growth.csv - 'plotnr' shows plot number - 'manip' 1=control, 2=short-term manipulation, 3=long-term manipulation - 'length' is root length at sampling occasion (average out of 3 minirhizotron tubes per plot) - 'growth' is root growth from that sampling occasion to the next (average out of 3 minirhizotron tubes per plot; NA for last sampling, as the growth is always the change between two dates) - 'sampling' sampling occasion - 'doy' day of year of sampling occasionroot_biomassroot_biomass.csv - 'plot' is plot number - 'treatment' shows treatment, 'contr' = control, 'new' = short-term manipulation (1 yr), 'old' = long-term manipulation (11 yrs) - 'depth' (shallow=0-20 cm depth, deep=20-40 cm depth) - 'diameter' root diameter (1= &lt;1 mm, 2= 1-2 mm), summed up for analysis - 'biomass' in g per sample (3 samples pooled of each plot, 20 cm depth, 4 cm diameter of corer) - 'mg_cm3' is biomass converted to mg/cm3Root_length_depth_classesRoot_length_depth_classes.csv - 'plotnr' shows plot number - 'manip' 1=control, 2=short-term manipulation, 3=long-term manipulation - 'Window' shows depth class: shallow (0-20 cm depth), medium (20-40 cm depth) and deep (deeper than 40 cm) - 'manip' 1=control, 2=short-term manipulation, 3=long-term manipulation - 'length' is per plot summed up length in a certain depth - 'growth' is per plot summed up length in a certain depth - 'sampling' sampling occasion - 'doy' day of year of sampling occasionspecies_coverspecies_cover.csv - 'Plot_nr' shows plot number - 'treatment' 'control' = control, 'new_roof' = short-term manipulation (1 yr), 'old_roof' = long-term manipulation (11 yrs) , 'gradient' is not part of this study - 'species' - 'type'= plant functional type - columns from 1-100 show each inividual pin, 'total' shows total number of hits