Using Marine Turtles to Identify Habitat and Assess Connectivity of the North and North-West Marine Park Networks and Sea Country

This project compiled marine turtle satellite tracking data for four species: green (Chelonia mydas, n=126), flatback (Natator depressus, n=164), hawksbill (Eretmochelys imbricata, n=59) and olive ridley (Lepidochelys olivacea, n=27) turtles, as well as a comprehensive dataset of modelled benthic habitat data from Northern Australia. Tracking data were used to build species-level movement network models to identify connectivity among Australian Marine Parks (AMPs), Indigenous Protected Areas (IPAs) and State Marine Protected Areas (MPAs) across the North and North-West Marine Regions. Tracking datasets were further processed to classify foraging behaviour and quantify foraging activity spaces. Foraging activity spaces were then overlayed with existing modelled benthic habitats using local entropy analysis to assess how well turtle foraging spaces can be used to identify benthic habitats.

本项目整合了4种海龟的卫星追踪数据集，涵盖绿海龟（Chelonia mydas，样本量n=126）、平背龟（Natator depressus，n=164）、玳瑁（Eretmochelys imbricata，n=59）以及榄蠵龟（Lepidochelys olivacea，n=27），同时收录了澳大利亚北部地区的全套模拟底栖生境（benthic habitat）数据集。本研究利用该追踪数据构建物种级移动网络模型，以识别北部及西北海洋区域内澳大利亚海洋公园（Australian Marine Parks, AMPs）、原住民保护区（Indigenous Protected Areas, IPAs）与州级海洋保护区（State Marine Protected Areas, MPAs）之间的连通性。追踪数据集还经过进一步处理，以分类海龟的觅食行为并量化其觅食活动空间。随后通过局部熵分析（local entropy analysis）将海龟觅食活动空间与已有的模拟底栖生境数据进行叠加，以评估海龟觅食空间用于识别底栖生境的效果。