Environmental niche models improve species identification in DNA barcoding

Recent advances in DNA barcoding have immeasurably advanced global biodiversity research in the last two decades. However, inherent limitations in barcode sequences, such as hybridization, introgression, or incomplete lineage sorting can lead to misidentifications when relying solely on barcode sequences. Here, we propose a new Niche-model-Based Species Identification (NBSI) method based on the idea that species distribution information is a potential complement to DNA barcoding species identifications. NBSI performs species membership inference by incorporating niche modeling predictions and traditional DNA barcoding identifications. Systematic tests across diverse scenarios show significant improvements in species identification success rates under the newly proposed NBSI framework, where the largest increase is from 4.7% (95%CI: 3.51%-6.25%) to 94.8% (95%CI: 93.19%-96.06%). Additionally, obvious improvements were observed when using NBSI on potentially ambiguous sequences whose genet..., , , # Environmental niche models improve species identification in DNA barcoding

[https://doi.org/10.5061/dryad.rbnzs7h96](https://doi.org/10.5061/dryad.rbnzs7h96)

## Description of the data and file structure

The software package and the supplementary materials of this research article:

Environmental Niche Models Improve Species Identification in DNA Barcoding

### Files and variables

#### File: Appendix\_S1\_Simulated\_datasets.zip

**Description:** All generated simulated datasets.

* Files starting with \"Sim_\": These are simulated datasets generated with species numbers of 20, 50, and 100, all with 100 individuals each. The fundamental coalescent parameter *θ* was set to 0.05, 0.01, and 0.2 for the respective datasets. Consequently, in the dataset with 20 species, each species contains 5 individuals; in the dataset with 50 species, each species contains 2 individuals; and in the dataset with 100 species, each species contains 1 individual.
* Files starting with \"SimAmbSeqs_\": Based...