Understanding the ecological mechanisms underpinning distribution patterns is vital in managing populations of mobile marine species. This study is a first step towards an integrated description of the habitats and spatial distributions of marine predators in the Natural Park of the Coral Sea, one of the world’s largest marine-protected areas at about 1.3 million km², covering the entirety of New Caledonia’s pelagic waters. The study aims to quantify the benefit of including a proxy for prey abundance in predator niche modelling, relative to other marine physical variables. Spatial distributions and relationships with environmental data were analysed using catch per unit of effort data for three fish species (albacore tuna, yellowfin tuna and dolphinfish), sightings collected from aerial surveys for three cetacean guilds (Delphininae, Globicephalinae and Ziphiidae) and foraging locations identified from bio-tracking for three seabird species (wedge-tailed shearwater, Tahiti petrel and red-footed booby). Predator distributions were modelled as a function of a static covariate (bathymetry), oceanographic covariates (sea surface temperature, chlorophyll-a concentration and 20 °C-isotherm depth) and an acoustically derived micronekton preyscape covariate. While distributions were mostly linked to bathymetry for seabirds, and chlorophyll and temperature for fish and cetaceans, acoustically derived prey abundance proxies slightly improved distribution models for all fishes and seabirds except the Tahiti petrel, but not for the cetaceans. Predicted spatial distributions showed that pelagic habitats occupied by predator fishes did not spatially overlap. Finally, predicted habitats and the use of the preyscapes in predator habitat modelling were discussed.

了解支撑分布模式的生态机制对于管理移动海洋物种的种群至关重要。这项研究是综合描述珊瑚海自然公园中海洋捕食者的栖息地和空间分布的第一步，珊瑚海是世界上最大的海洋保护区之一，面积约 130 万平方公里²，涵盖整个新喀里多尼亚的远洋水域。该研究旨在量化相对于其他海洋物理变量，在捕食者生态位建模中加入猎物丰度代理的好处。使用三种鱼类（长鳍金枪鱼、黄鳍金枪鱼和海豚鱼）的单位捕捞量数据、从三个鲸类动物协会（海豚科、圆头鱼科和银鱼科）的空中调查中收集到的目击数据以及确定的觅食地点，分析了空间分布和与环境数据的关系来自三种海鸟物种（楔尾鹬、大溪地海燕和红脚鲣鸟）的生物追踪。捕食分布进行建模为静态协变量（测深），海洋协变量（海面温度，叶绿素的功能一浓度和 20 °C 等温线深度）和声学衍生的 micronekton preyscape 协变量。虽然分布主要与海鸟的水深测量以及鱼类和鲸类的叶绿素和温度有关，但声学衍生的猎物丰度代表略微改进了除大溪地海燕以外的所有鱼类和海鸟的分布模型，但不适用于鲸类。预测的空间分布表明，捕食性鱼类占据的远洋栖息地在空间上没有重叠。最后，讨论了预测的栖息地和捕食者栖息地建模中猎物景观的使用。