Spatio-temporal predictions of mobulid occurrence to help combat illegal manta ray fishing in Lamakera, Indonesia

Increased demand for mobulid gill plates in Chinese medicine has driven mobulids towards extinction. Indonesia is one of the world’s biggest mobulid fisheries, and population extirpations and significant declines in CPUE are... [ view full abstract ]

Increased demand for mobulid gill plates in Chinese medicine has driven mobulids towards extinction. Indonesia is one of the world’s biggest mobulid fisheries, and population extirpations and significant declines in CPUE are apparent. Lamakera, a small village on Solor Island, is Indonesia’s largest manta fishery and has been targeting mobulids for generations, historically for subsistence but turning commercial in recent decades to supply the international gill plate trade. In 2014 the Indonesian government declared full protection for mantas, creating the world’s largest manta sanctuary. Since then the government and stakeholders have been enforcing the regulation through various methods including applied marine surveillance. This study presents a modeling approach for predicting mobulid occurrence, used to improve the effectiveness of marine surveillance in Solor. We applied both Maximum Entropy and generalized adaptive model to build a spatio-temporal predictive model of mobulid occurrence in Solor waters. GAM output of moon illumination was most strongly related to mobulid temporal sightings (45%) (P<0.05). Furthermore, the MaxEnt output performed well to characterize mobulid habitat with the AUC_Test >0.9. Since 2016, we have provided daily predictions to guide marine surveillance in Lamakera increasing the effectiveness of enforcement, resulting in a decrease in manta fishing effort and catch.