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Modeling Species Distributions to Predict Seasonal Habitat Range of Invasive Fish in the Urban Stream via Environmental DNA

Proceedings of the National Institute of Ecology of the Republic of Korea / Proceedings of the National Institute of Ecology of the Republic of Korea, (P)2765-2203; (E)2765-2211
2022, v.3 no.1, pp.54-65
https://doi.org/10.22920/PNIE.2022.3.1.54
Yujin Kang (Graduate School of Environmental Studies, Seoul National University)
Wonhyeop Shin (Integrated Major in Smart City Global Convergence, Seoul National University)
Jiweon Yun (Graduate School of Environmental Studies, Seoul National University)
Yonghwan Kim (Graduate School of Environmental Studies, Seoul National University)
Youngkeun Song (Graduate School of Environmental Studies, Seoul National University)

Abstract

Species distribution models are a useful tool for predicting future distribution and establishing a preemptive response of invasive species. However, few studies considered the possibility of habitat for the aquatic organism and the number of target sites was relatively small compared to the area. Environmental DNA (eDNA) is the emerging tool as the methodology obtaining the bulk of species presence data with high detectability. Thus, this study applied eDNA survey results of Micropterus salmoides and Lepomis macrochirus to species distribution modeling by seasons in the Anyang stream network. Maximum Entropy (MaxEnt) model evaluated that both species extended potential distribution area in October compared to July from 89.1% (12,110,675 m2) to 99.3% (13,625,525 m2) for M. salmoides and 76.6% (10,407,350 m2) to 100% (13,724,225 m2) for L. macrochirus. The prediction value by streams was varied according to species and seasons. Also, models elucidate the significant environmental variables which affect the distribution by seasons and species. Our results identified the potential of eDNA methodology as a way to retrieve species data effectively and use data for building a model.

keywords
DNA, environmental, Ecological parameter monitoring, Introduced species, Model, statistical, River
Submission Date
2021-10-07
Revised Date
2021-12-13
Accepted Date
2021-12-14

Proceedings of the National Institute of Ecology of the Republic of Korea