Predicting Invasion Risk of Invasive Coptodon zillii on a Global Scale Using Ecological Niche Models

Coptodon zillii is one of the most dangerous invasive fishes in the world. To develop management plans to effectively prevent its further spread in global aquatic ecosystems requires an understanding of the change in suitable habitat under future climate scenarios. In this study, we develop a Maximum Entropy Model (MaxEnt model) based on the current distribution data of C. zillii and the current WorldClim ecological database to generate a global habitat suitability model for C. zillii . This model was then used to predict the future habitat suitability for C. zillii based on the SSP3‐7.0, SSP5‐8.5 future climate scenarios. We found that the mean temperature of the coldest Quarter (Bio11) was the environmental variable limiting the distribution of C. zillii . Under the current climatic conditions, the global range of suitable area for C. zillii was mainly concentrated in the tropical and subtropical regions (with a total area of about 40,862,654 km 2 ). Among them, the projected suitable habitat areas reached 304.12 × 10 4 , 933.05 × 10 4 , 66.29 × 10 4 , 845.85 × 10 4 , 1412.58 × 10 4 and 407.13 × 10 4 km 2 in North America, South America, Europe, Asia, Africa and Oceania, respectively. Under the SSP3‐7.0 climate scenario, the global areas of suitable habitat for C. zillii in the 2030s and 2050s expanded by 13.84% (315.47 × 10 4 km 2 ) and 20.78% (408.76 × 10 4 km 2 ), respectively. Under the SSP5‐8.5 climate scenario, the global areas of suitable habitat for C. zillii in the 2030s and 2050s expanded by 16.55% (383.33 × 10 4 km 2 ) and 21.26% (460.97 × 10 4 km 2 ), respectively. These findings will help the governments of countries and regions at high risk of C. zillii invasion to develop biological invasion management plans, such as prioritizing enhanced border quarantine measures, strictly regulating potential introduction pathways, and establishing early monitoring and warning systems in predicted suitable habitats.