DOI: 10.5061/dryad.3tx95x6cr
title: Redefining floristic zones in the Korean Peninsula using high-resolution georeferenced specimen data and self-organizing maps

description: The use of biota to analyze the distribution pattern of biogeographic
 regions is essential to gain a better understanding of the ecological
 processes that cause biotic differentiation and biodiversity at multiple
 spatiotemporal scales. Recently, the collection of high-resolution
 biological distribution data (e.g., specimens) and advances in analytical
 theory have led to the quantitative analysis and more refined spatial
 delineation of biogeographic regions. This study was conducted to redefine
 floristic zones in the southern part of the Korean Peninsula and to better
 understand the eco-evolutionary significance of the spatial distribution
 patterns. Based on 309,333 distribution data of 2,954 vascular plant
 species in the Korean Peninsula, we derived floristic zones using
 self-organizing maps. We compared the characteristics of the derived
 regions with those of historical floristic zones and ecologically
 important environmental factors (climate, geology, and geography). In the
 clustering analysis of the floristic assemblages, four distinct regions
 were identified, namely, the cold floristic zone (Zone I) in high-altitude
 regions at the center of the Korean Peninsula, cool floristic zone (Zone
 II) in high-altitude regions in the south of the Korean Peninsula, warm
 floristic zone (Zone III) in low-altitude regions in the central and
 southern parts of the Korean Peninsula, and maritime warm floristic zone
 (Zone IV) including the volcanic islands Jejudo and Ulleungdo. Totally,
 1,099 taxa were common to the four floristic zones. Zone IV showed the
 highest abundance of specific plants (those found in only one zone), with
 404 taxa. Our study improves floristic zone definitions using
 high-resolution regional biological distribution data. It will help better
 understand and re-establish regional species diversity. In addition, our
 study provides key data for hotspot analysis required for the conservation
 of plant diversity.
description: The vascular plant distribution data based on specimen and
 coordinate data for plants collected between 2003 and 2015 in the southern
 part of the Korean Peninsula at Korea National Arboretum. The vascular
 plant distribution maps contained coordinate data for 309,333 specimens,
 corresponding to 2,954 taxa in 175 families and 919 genera. A grid system
 was overlaid on a national topographic map to combine the taxonomic groups
 located in each cell of the grid (cell size, 11.2 km × 13.9 km) with the
 location coordinates in a single data set. Using distribution
 data for the 771 grid cells and 2,954 plant taxa, a SOM training data set
 was constructed in the form of a presence-absence matrix (771 rows × 2,954
 columns). The ‘kohonen’ R package was used for the SOM algorithm, and the
 output layer was composed of 81 output nodes arranged in a square lattice.
 To determine the types, hierarchical cluster analysis was applied to the
 weight vectors of the SOM map units after conversion to Euclidean distance
 metrics (via the function hclust in R using the complete linkage method).
 The optimal number of types was calculated by applying the silhouette
 coefficient to the range of 2–15 types. In mapping the
 regionalization results, the grid cells that were empty because of
 exclusion from the survey were filled using the maximum frequency value
 from the surrounding eight cells. As some island regions (Ulleungdo Island
 and Dokdo Island) showed heterogeneous values because of their distance
 from the adjacent grid cells, mapping was performed using type values
 within the local range. The correlations in species
 composition among the floristic zones were analyzed using Venn diagrams
 (with the “VennDiagram” package) based on lists of species in each zone
 (Chen and Boutros, 2011). After listing all species in each zone, the
 common taxa (those appearing in all zones) and specific taxa (those
 appearing in only specific zones) were distinguished. Thereafter,
 floristic compositions were investigated by analyzing the identification
 of specific taxa at the family level. Geographic and climatic factors
 were analyzed as macro-environmental factors, using the defined floristic
 zones. For the geographic factors, the latitude and longitude were used,
 and for climatic factors, air temperature and precipitation data—provided
 by the Korean Meteorological Administration (2020) and collected from 583
 points between 1970 and 2010—were used. In addition to the direct
 environmental data, the warmth index (WI) and coldness index (CI) were
 calculated and used as indirect climate data (Kira, 1945). The values for
 these environmental factors were converted to values covering the entire
 southern part of the Korean Peninsula by linear interpolation, accounting
 for topography and altitude, using ArcGIS program (ver. 10.0). The mean
 value of the environmental factors in each grid cell was then calculated
 and used in the analysis. As physical
 factors affecting plant distribution, parent materials, topography,
 effective soil depth, and soil texture in the southern part of the Korean
 Peninsula were used (Rural Development Administration, 2010). Parent
 materials were categorized as acidic rock, metamorphic rock, sedimentary
 rock, quaternary deposit, volcanic ash, and other. Topography was
 categorized into mountain, hill, pediment, interrill area, fan, lava
 terrace, or other. Effective soil depth was categorized into four classes
 (&lt;20, 20–50, 50–100, and &gt;100 cm). Soil texture was
 categorized as sandy gravel, silt and sandy loam, clay loam, and
 clay. To test the effect of environmental factors on
 the floristic composition and zonation, the geographic and climatic (mean
 annual temperature, annual precipitation, warmth index, and coldness
 index) data were analyzed using the one-way analysis of variance (ANOVA)
 and Tukey’s test. The categorical physical factors (parent materials,
 topography, effective soil depth, and soil texture) were analyzed using
 box plots for each zone. The “ggplot2” R package was used for data
 visualization. Statistical analyses were performed using R.