DOI: 10.6084/m9.figshare.21947012.v1
title: Data for "Does ungulate herbivory translate into diversity of woody plants? A long-term study in a montane forest ecosystem in Austria"

description: <strong>Study area</strong> Regeneration dynamics were monitored on the mountain massif “Höllengebirge” (highest peak at 1,862 m), which comprises a forest area of 90 km2. It is part of the northern Limestone Alps in Upper Austria, Central Europe (47°49′ N, 13°30′ E). The investigation is focused on areas with natural forest regeneration. For further information on the study area and estimated mean ungulate density, we refer to the publication "Does ungulate herbivory translate into diversity of woody plants? A long-term study in a montane forest ecosystem in Austria". <br> <strong>Data acquisition</strong> We initially established 100 pairs of ungulate exclosures (excluding the occurring red deer, roe deer and chamois) and unfenced control plots at altitudes between 500–1,100 m a.s.l. in 1989, and we completed the survey in 2019. Until this point of time, several fence or control plots had been destroyed or disturbed by natural abiotic disturbance events like storm throw, snow loading or rock falls. Plots that experienced other disturbances than ungulate herbivory were omitted. Thus, a final number of 14 plot pairs could be surveyed over the entire 30-year time span. The minimum distance between plot pairs was 200 m. Smaller mammals like hares (<em>Lepus europaeus</em>) or herbivore voles and mice were able to enter the exclosures. The type of treatment (fencing vs. control) was randomly attributed with a coin toss. Exclosures were constructed with a 2 m tall, galvanized fence outlining an area of 6 × 6 m. Distances between exclosures and corresponding control plots ranged from 5 m up to max. 20 m with largest possible congruence of site and stand conditions between exclosures and control plots. The entire sampling procedure was optimized to capture effects of ungulate herbivory and to keep other driving factors as constant as possible. Within the 6 × 6 m area of each fence and control plot, we recorded plant data within the central 5 × 5 m square (i.e., survey area without “edge effects”), which was permanently marked with metal rods. Data were first recorded in the year of establishment of exclosure/control pairs and afterwards in a three-year cycle, except for the last phase of the survey, which covered a 6-year time span (summing up 9 survey cycles for the longest lasting surveys); in 2016, we did not record the regeneration on the plots. Considering the gap‐maker–gap‐filler approach, we dynamically recorded the height of the largest trees per tree species in paired plots with and without exclosures, as this allowed us to assess herbivore impacts on those individuals, which have a high probability of attaining reproductive stages. We thus recorded the six highest individuals per tree species and plot or, in case of lower stem numbers, all occurring individuals per tree species and sampling plot (25 m2, each fenced and unfenced) [see 30]. We used the following height classes: ≤ 10 cm, 11–25 cm, 26–40 cm, 41–70 cm, 71–100 cm, 101–130 cm, 131–160 cm, 161–200 cm, 201–250 cm, 251–300 cm, ... (continuing 50 cm classes). No animal experiments were carried out. The ungulates were neither caught nor influenced by medication. They were only denied access to small patches within forests by means of a fence. The fencing was carried out in accordance with all relevant guidelines and regulations. For further information on data acquisition, we refer to the publication "Does ungulate herbivory translate into diversity of woody plants? A long-term study in a montane forest ecosystem in Austria". <br> <strong>Data preparation</strong> As the height class distribution of the sampled trees might distinctly deviate even within the collective of the highest six individuals per tree species, we additionally defined a group of “top height individuals”, which reach or exceed the 66%-height-level of the highest tree individual per exclosure/control pair. The threshold of 66% was set arbitrarily, representing the upper third of the height range. This subsample of tree individuals represents the collective of dominant stems (hereinafter termed “top height individuals”) with presumed highest competitive power. Due to a delay in height growth between some plot pairs, tree individuals of one plot did not reach the 66% threshold of the maximum value of the paired plot in several cases. These plot pairs had to be omitted from the analysis of top height individuals. Addressing structural diversity of tree species, we looked at the occurrence of different height classes in the exclosures and on the corresponding open control plots. As height classes cover smaller height ranges at the seedling stage and change to larger range values for higher tree individuals, this height class diversity does not reflect absolute differences in height growth between the exclosure/control pairs, but depicts potential differences in terms of observed height class numbers. To additionally cover the issue of potentially impacted height growth patterns of woody plants due to ungulate herbivory, we also analyzed height trajectories of the highest six individuals per tree species. As tree heights had been recorded in terms of height classes, we used the mid-point height per height class interval as representative per individual tree (e.g. 85 cm for the 71–100 cm height class). Woody plants (trees and shrubs) of the same species are often spatially aggregated and individuals should not be interpreted or modeled as independent sampling units [Chao et al. 2020]. Accounting for this potential impact on woody plant species distribution and assemblages, we converted abundance data of tree and shrub species and height classes of trees in each study plot into incidence-based (detection versus non-detection) data. <br> <strong>File description</strong> <strong>csv-files</strong> are separated by semicolons ';'. <strong>RData-files</strong> can be loaded via the load()-function within the software environment 'R'. Each RData-file contains a list of incidence raw data. Each element of the lists is a species-by-sampling-unit incidence matrix [Chao et al. 2020, Chao et al. 2014]. The name of each matrix is three characters long, describing if the assemblage was fenced (name begins with 'Z') or an unfenced control plot (name begins with 'U') and includes information about the timing of the survey (coded with '04' = 9 years after establishment, '07' = 18 years after establishment and '10' = 30 years after establishment). Filenames starting with 'HO14' contain datasets for a study duration of 30 years of ungulate exclosure-control plot pairs. Files starting with 'HO43' include data for plots that could be sampled for 18 years. The matrices of the 'HO43'-files contain more samples (columns) compared to the 'HO14'-files because some plot pairs could not be sampled for the whole 30-year period (see `Data acquisition`). - 'shrub_species_names.csv': This look-up table includes the scientific and english names of shrub species and abbreviations that were used in the manuscript. - 'tree_species_names.csv': This look-up table includes the scientific and english names of tree species and abbreviations that were used in the manuscript. - 'HO14_tree_species.RData': 30-year dataset for the analysis of tree species diversity.The row names of each matrix contain the abbreviation of the shrub species (see 'tree_species_names.csv'). - 'HO43_tree_species.RData': 18-year dataset for the analysis of tree species diversity. Data format and structure is comparable to the dataset 'HO14_tree_species.RData'. - 'HO14_tree_species_topheight.RData': 30-year dataset for the analysis of tree species diversity of top height individuals. The row names of each matrix contain the abbreviation of the tree species (see 'tree_species_names.csv') for the top height individuals. - 'HO43_tree_species_topheight.RData': 18-year dataset for the analysis of tree species diversity of top height individuals. Data format and structure is comparable to the dataset 'HO14_tree_species_topheight.RData'. - 'HO14_tree_heightclass.RData': 30-year dataset for the analysis of height class diversity of tree species. The row names of each matrix contain the labels for 35 tree height classes. - 'HO43_tree_heightclass.RData': 18-year dataset for the analysis of height class diversity of tree species. Data format and structure is comparable to the dataset 'HO14_tree_heightclass.RData'. - 'HO14_shrub_species.RData': 30-year dataset for the analysis of shrubspecies diversity.The row names of each matrix contain the abbreviation of the shrub species (see 'shrub_species_names.csv'). - 'HO43_shrub_species.RData': 18-year dataset for the analysis of shrubspecies diversity. Data format and structure is comparable to the dataset 'HO14_shrub_species.RData'. <br> <strong>References</strong> <br> Chao, A.; Kubota, Y.; Zelený, D.; Chiu, C.H.; Li, C.F.; Kusumoto, B.; Yasuhara, M.; Thorn, S.; Wei, C.L.; Costello, M.J., et al. Quantifying sample completeness and comparing diversities among assemblages. Ecol. Res. 2020, 35, 292-314, doi:10.1111/1440-1703.12102. <br> Chao, A.; Gotelli, N.J.; Hsieh, T.C.; Sander, E.L.; Ma, K.H.; Colwell, R.K.; Ellison, A.M. Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecol. Monogr. 2014, 84, 45-67, doi:10.1890/13-0133.1. <br>