The dataset of Liquidambar orientalis for species distribution models

The primary objective of this study was to predict the existing geographic range of Liquidambar orientalis, commonly known as the oriental sweetgum. To gain insights into the potential effects of climate change on the oriental sweetgum, the study employed species distribution models to project the model to future periods. Considering two Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5), the ensemble modeling approach utilized the biomod2 package in the R programming language to analyze the alterations in the spatial distribution of the species in forthcoming periods (namely, for the years 2035s, 2055s, and 2070s). , 1. Occurrence data
81 occurrence data were obtained from two reputable sources: the Global Biodiversity Information Facility (GBIF 2023, www.gbif.org) and the European Forest Genetic Resources Program (EUFORGEN 2023). In the dataset obtained from the Global Biodiversity Information Facility (GBIF), erroneous and redundant records were removed.
2. Environmental data
The dataset used in this study consisted of nineteen bioclimatic variables (BIO1 to BIO19) obtained from the CHELSA version 2.1 (https://chelsa-climate.org/). These variables as .tiff format represented climatic and environmental factors and were downloaded at a spatial resolution of 30-arc seconds. The dataset covered four temporal ranges: 1981-2010, 2011-2040, 2041-2070, and 2071-2100. The bioclimatic variable values of the grid cell were obtained using QGIS 3.18.2. The data utilized in this study were obtained from two Global Circulation Models (GCMs), namely the Max Planck Institute Earth System Model (MPI-ESM1-2-HR) and ..., , # The dataset of Liquidambar orientalis for species distribution models

[https://doi.org/10.5061/dryad.1ns1rn914](https://doi.org/10.5061/dryad.1ns1rn914)
The dataset includes
1\. Occurrence points of Liquidambar orientalis obtained from GBIF and EUFORGEN\,
2\. Bioclimate data of the occurrences obtained from CHELSA\,
3\. Variance Inflation Factors \(VIF\) results of four variables \(bio1\, bio2\, bio13\, and bio18\)\,
4\. The Area Under the Curve \(AUC\) of the Receiving Operator Characteristics \(ROC\) and the True Skill Statistic \(TSS\) results of the modeling\,
5\. Bioclimate variables' importance scores after modeling
6\. The ROC graph \(including each algorithm's total scores\)
7\. \"Suitability\.xls\" contains the area calculation of suitable habitats\.

## Description of the data and file structure

1\. \"occurence\_points\.xls\" contains 81 geographical coordinates \(latitude and longitude\) of Liquidambar orientalis in Anatolia and Rhodos Island\.
2\. \"bioclim\_variables\.xls\" c...