Incorporating in situ prey distribution into foraging habitat modelling for marine megafauna in the Solor waters of the Savu Sea, Indonesia

Many marine animals aggregate seasonally at predictable locations to exploit their prey in oligotrophic environments, making them vulnerable to human disturbance. The foraging strategies and habitats of manta rays and Stenella spp. in the Solor waters were largely unknown, despite the importance of this information for their effective management, e.g. through the establishment of marine protected areas in this region. Over the last few decades, the use of foraging habitat models in describing the foraging strategy and delineating the predicted habitats has grown in popularity. However, most of these studies have relied on remotely sensed data such as sea surface chlorophyll‐a to estimate prey distribution. Very few studies have used the distribution of in situ prey, which is that closer to the trophic level of modelled species, although such a strategy would improve model performance. The study compares foraging habitat model performance for manta rays and Stenella spp. in the waters of Solor using remotely sensed sea surface chlorophyll‐a concentrations and in situ zooplankton biomass as proxies for prey quantities and distribution. A Maximum Entropy model that integrated species sightings with environmental predictors was used to quantify the importance of predictors in explaining habitat preference and distribution of manta rays and Stenella spp. and to compare model performance and predict foraging habitats. Results indicate that the use of prey proxy closer to the trophic level of examined species improve model performance, ecological explanations, and spatial predictions. The zooplankton biomass distribution performed much better in explaining the manta rays' habitats compared to that of Stenella spp., indicating that a trophic level gap might influence the zooplankton's ability to predict foraging habitats of Stenella spp. This study highlights the importance of integrating foraging habitat models into marine protected area design to ensure the effectiveness of species management.