This dataset contains all the raw data belonging to the research article 'Reindeer trampling promotes vegetation changes in tundra heathlands: results from a simulation experiment', by Egelkraut, Barthelemy and Olofsson, published in Journal of Vegetation Science. 

The experiment experimentally simulated various herbivore activities (Defoliation, Moss removal, Fertilization, Trampling, FDT, FDTM) on lightly grazed tundra heath vegetation, in order to determine in what way each of these activities cntributed to change in vegetation community and structure. We recorded vegetation composition as well as soil temperature and moisture over the course of 6 years.

Field site and experimental design

This study took place in Raisduoddar (69°31’N, 21°19’E; altitude 600 m a.s.l.). The study site is above the current local treeline and average yearly temperature was 0.2°C during the experiment (2011-2015, see Appendix S1a). The area has a suboceanic climate, and reindeer husbandry is common practice. Next to reindeer, other common herbivores include ptarmigan Lagopus muta, lemmings  (Lemmus lemmus) and voles (Myodes rufocanus). The dominant vegetation type is tundra heath, dominated by  deciduous dwarf shrubs like Betula nana, Vaccinium vitis-idaea and Vaccinium uliginosum and evergreen dwarf shrubs like Empetrum nigrum ssp. hermaphroditum (hereafter: E. nigrum) and Vaccinium vitis-idaea, but also includes graminoids like Deschampsia flexuosa, Carex bigelowii and Festuca ovina and forbs like Rubus chamemorous, Linnea borealis and Pedicularis lapponica.  We located the experiment on the eastern side of a reindeer fence, which was established in the 1960s. The fence runs for several kilometers and separates the area into a side that is grazed heavily by reindeer during several weeks every summer (hereafter: grazed), and a lightly grazed side that is only occasionally visited by reindeer (hereafter: ungrazed). Importantly, the vegetation on the heavily grazed side of the fence has shifted to a graminoid-dominated vegetation type (Figure 1), (Olofsson et al. 2001), and is dominated by graminoid species such as F. ovina, D. caespitosa, Poa alpina and multiple Carex species, and forbs such as Bistorta vivipara and Viola biflora (Sitters et al. 2017; Ylänne et al. 2018). At the ungrazed side of the fence, we selected five blocks with homogenous vegetation. We ensured the blocks were similar with regards to topography (as flat as possible) and distance to the fence (approximately 10-25 m). In each block, we established seven plots of 1m² and randomly assigned one of seven treatments to each of those plots. Distance between plots was at least 50 cm, and distance between blocks was 10-50 m, depending on terrain. The experiment was started on 28 July 2011 and all treatments were applied once a year during six consecutive years in August, which is the season when the area is used by reindeer.

Treatments

The seven treatments applied were control (C), defoliation (D), feces addition (F), trampling (T), moss removal (M), F+D+T (FDT) and F+D+T+M (FDTM). We aimed for the intensity of each of the treatments to mimic the intensity of the activities observed at the heavily grazed side of the fence. In the defoliation treatment, we removed 50% of the leaves for every shoot of B. nana, 50% of all young and green shoots of Vaccinium myrtillus, and cut down all graminoids and forbs to 3 cm from the moss layer. Evergreen shrubs such as E. nigrum and V. vitis-idaea were not defoliated because they are less palatable for reindeer. The treatment is roughly similar to the level of defoliation on the different functional groups at the heavily grazed side of the fence.

Trampling was simulated using a 5 kg pointy wooden pole that we dropped from knee-height to mimic reindeer trampling (Olofsson 2006). The pole was dropped 100 times, distributed evenly over the plot. The number of hits mimics the intensity of trampling on the heavily grazed side of the fence according to trampling indicators (Olofsson et al. 2004). However, later data showed that those measurements were taken during a temporal decline in reindeer densities in the area, and a more realistic trampling intensity in the area is thus probably substantially higher (Appendix S1b).

In the feces treatment, we added 500 grams of fresh reindeer feces (approximately 100g dry feces) each plot, spread evenly over the whole surface. Although we intended to mimic the deposition on the heavily grazed side of the fence, our treatment resulted in five times more feces added compared to what has been recorded there (~20g dry feces m^-2, Sitters et al. (2017). In the plots with combined treatments feces, defoliation, trampling (FDT), and feces, defoliation, trampling and moss removal (FDTM), we dropped the pole 80-90 times, then added feces, and then added the remaining hits, to mimic the natural mixing that occurs in the field.

In the moss removal treatment, we removed as much of the top layer of bryophytes as possible, focusing mostly on the green parts and taking care not to damage small plant shoots growing between them. This approximates the dramatic decline of moss biomass by 80-90% in the heavily grazed side of the fence (Ylänne et al. 2018). 

Field measurements

Each year in August, we recorded the vegetation composition, soil temperature and moisture, before adding the treatments to the plots. Vegetation and soil properties were measured in a subplot of 50 cm × 50 cm to avoid edge effects, whilst each treatment was added to the full square meter plot. For the vegetation survey using point frequency recording, we used a point frame with 10 pins (pin diameter 2.5 mm and distance between pins 5.5 cm) which we placed in the subplot at 10 evenly spaced intervals, resulting in a grid of 100 points per plot. We recorded the living leaves and stems of all vascular plants touching each pin. In the bottom layer (mosses and lichens), we counted only one hit per species, but more than one moss or lichen species could be recorded. Nomenclature follows Mossberg & Stenberg (2008) for vascular plants, and Hallingbäck & Holmåsen (1985); Moberg (1990) for mosses and lichens, respectively. We measured soil temperature using a rugged thermometer (10 cm depth) with a HI-765BL probe with a resolution of 0.1°C (Hanna Instruments) and soil moisture (10 cm depth) using a ML3-ThetaProbe soil moisture sensor connected to a HH2 moisture meter. The ThetaProbe sensor measures volumetric soil moisture content in the topsoil, and the thermometer measured soil temperatures at 12 cm depth. We recorded three readings per plot for both these methods, aiming for an overcast but dry day to achieve stable values.

Data handling and statistical analyses

We used a non-metric multidimensional scaling (NMDS; the metaMDS function, Oksanen and others 2017) in the statistical package R (R Core Team 2017) to analyze the development of vegetation composition in each treatment over the years, based on the point frequency species counts in each individual plot (n = five replicates per treatment) in 2011 and 2016. We made several adjustments to the dataset before analyzing. Firstly, all species with a total of one or two counts in the whole dataset were discarded to make the analyses more robust. Furthermore, a number of species were merged in the collective taxa ‘Cladina’ (C. mitis, C. rangiferina, C. spp.), ‘Cladonia’ (Cladonia gracilis, C. spp.), ‘Barbilophozia’ (Barbilophozia spp., Lophozia spp. and other liverworts) and ‘PleuHylo’ (Pleurozium schreberi and Hylocomium splendens) to remove inconsistencies in species identification among years. Appendix S2 provides an overview of the recorded species, grouped per functional type, and their range of abundance in 2011.

In order to better understand the changes in vegetation composition over time, we grouped all recorded species into plant functional types (bryophytes, deciduous dwarf shrubs, evergreen dwarf shrubs, forbs, graminoids, lichens, see Appendix S2). We then calculated the percentage change (% change) over time per functional type, based on the total number of hits of all species per functional type per treatment per year. The percentage change of species counts was calculated as follows:

F 1.     

This allowed us to express the change in abundance relative to the start of the experiment (2011) in each of the treatments, per functional type, throughout the experiment. The resulting values for 2016 were analyzed using one-way ANOVA, testing for differences amongst treatments per functional type (n=5). Block was not included in analyses, due to missing values that would have made tests less robust. The data for forbs, graminoids and lichens were log-transformed to avoid heteroscedasticity. Because each dataset contained positive and negative values, absolute values were logged, after which we added a minus to originally negative values. Lastly, we used repeated measures ANOVAs to test the effect of treatment on soil temperature and soil moisture (3 repeated measurements per plot per year), comparing the years 2011 and 2016. All tests were carried out in the statistical package R (R Core Team 2013).

Numbers in the species abundance sheet represent hits (touches) per 100 pins in that plots (50x50 cm). 

Soil moisture is in percentage and soil temperature in degrees Celcius.

Data collectors abbreviations: