Abstract
In this study, water flow rate and quality variables that restrict freshwater fish distribution were incorporated in species distribution modeling to evaluate the impacts of climate change. A maximum entropy model (MaxEnt) was used to predict the distribution of 76 fish species in the present (2012–2014) and in the future (2025–2035 and 2045–2055) based on representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios for five major river basins (Han, Nakdong, Geum, Seomjin, and Yeongsan) in South Korea. The accuracy of MaxEnt performance was improved from 0.905 to 0.933, and from 0.843 to 0.864 in the model training and test, respectively, by introducing flow rate, total nitrogen, total phosphorus (TP), and total suspended solids (TSS). TSS and TP were ranked as the second and fourth contributing parameters, respectively, among the 17 variables considered in this study. There was a greater decline in species richness index under scenario RCP 8.5 than under scenario RCP 4.5, and in 2050 compared with 2030. However, the tolerance guild index (TGI) was predicted to improve in the future. The increase in TGI coupled with the decrease in species richness index (SRI), indicated that climate change is likely to have adverse effects on freshwater fish. Notably, the habitat of Korean spotted barbel (Hemibarbus mylodon), an endemic species of South Korea, is expected to contract largely in 2050 based on the RCP 8.5 scenario. These findings demonstrate that the incorporation of flow rate and water quality parameters into climatic variables can improve the prediction of freshwater fish distribution under climate change.
Highlights
Climate change will affect the distribution of fish species, changing the diversity of ecosystems [1]
The habitat of Korean spotted barbel (Hemibarbus mylodon), an endemic species of South Korea, is expected to contract largely in 2050 based on the representative concentration pathway (RCP) 8.5 scenario. These findings demonstrate that the incorporation of flow rate and water quality parameters into climatic variables can improve the prediction of freshwater fish distribution under climate change
The performance of MaxEnt was evaluated by calculating training and test AUC values, which indicate the accuracy of model training and validation, respectively
Summary
Climate change will affect the distribution of fish species, changing the diversity of ecosystems [1]. Kwon et al [7] predicted the future distribution of 22 endemic freshwater fishes in the 2000s, 2040s, and 2080s under RCP 8.5 scenario using a random forest model. These authors revealed that five species have potential to be extinct in their habitat by the 2080s. Pandit et al [8] predicted the distribution of carmine shiner (Notropis percobromus) using the maximum entropy model (MaxEnt) under contemporary conditions and climate change scenarios (RCP 2.6 and 8.5) They demonstrated that distribution shifts will occur northward, and available habitat will greatly decrease, which emphasizes the need for restoration or conservation actions
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
