Predicting Potential Geographic Distribution of Siganus Luridus and Siganus Rivulatus, Two Invasive Fish Species in the Mediterranean Sea

Abstract

A goal of fisheries management is to predict the probability of successful establishment of invasive fish species. To address this goal, species distribution models are used to project species distribution under different climate-change scenarios. In this study, the geographic distribution of the invasive, Red Sea migrant fish species Siganus luridus and Siganus rivulatus is predicted using the maximum entropy model MaxEnt. MaxEnt represents the study area with a set of grid cells, with the dependent variable being the known species distribution, and with independent environmental variables defined. MaxEnt then determines a function of the environmental variables to identify the degree to which each cell is suitable for each species. The main objective of this paper is to determine what factors may have led to the large-scale spreading of S. luridus and S. rivulatus upon the opening of the Suez Canal in 1869. Two possible hypotheses are that they are spreading due to warming sea surface temperature (SST) or that the building of the Suez Canal simply opened up habitat that would have been suitable even without warming. Model results show a large area of suitable habitat for both species where no current known record of the species has been collected, signifying an invasion potential not yet realized or an insufficient knowledge of the current species distribution. No significant relationship between warming SSTs and the predicted geographic distribution is found for S. rivulatus, while a slight trend is identified for S. luridus.