Identifying factors affecting the distributions of large marine vertebrates in coastal areas to predict current and future distributions

海洋巨型动物往往聚集在沿海地区，受到许多环境因素的影响。最近出现的空中无人机提供了新的机会来探索这些社区如何聚集，并确定调节其分布的环境因素。在这里，我将在佛得角（大西洋）的生物多样性热点探讨这个问题。在第一章中，我将利用无人机调查和遥感技术确定与岛屿尺度上三个关键类群（板鳃目、海龟、鲸目）分布相关的环境因素。在第2章中，我将测试确定的因素是否可以用于从数学模型（地理概况，基于个体的模型，生态位分布模型）预测未调查地区的社区组合，然后我将用空中无人机调查进行实证测试。在第3章中，我将根据第1章和第2章的结果，以及气候变化下分布如何变化，使用模型构建计算机管理场景，包括动态管理。通过实证和理论相结合的方法，我的研究有望为大型海洋脊椎动物的群落动态提供新的见解，并为气候变化下支持高生物多样性的沿海地区可持续管理提供潜在的方向。

Marine megafauna tend to aggregate in coastal areas, with many environmental factors affecting them. The recent emergence of aerial drones provides novel opportunities to explore how such communities assemble, and identify environmental factors that regulate their distributions. Here, I will explore this question at the biodiversity hotspot of Cabo Verde (Atlantic Ocean). In Chapter 1, I will identify the environmental factors associated with the distributions of three key groups (elasmobranchs, sea turtles, cetaceans) at the island scale using aerial drone surveys and remote sensing. In chapter 2, I will test whether identified factors could be used to predict community assemblages in unsurveyed areas from mathematical models (geographic profiling, individual based models, niche distribution modelling), which I will then test empirically with aerial drone surveys. In Chapter 3, I will use models to construct management scenarios in silico, including dynamic management, based on the results of chapters 1 and 2, and how distributions might shift under climate change. Through combining empirical and theoretical approaches, my study is expected to provide new insights on the community dynamics of large marine vertebrates and potential directions towards sustainably managing coastal areas supporting high biodiversity under a changing climate.