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

海洋大型动物往往聚集在沿海地区，受许多环境因素的影响。最近出现的空中无人机为探索此类社区如何聚集并确定调节其分布的环境因素提供了新的机会。在这里，我将在生物多样性热点佛得角(大西洋)探讨这个问题。在第一章中，我将利用无人机航测和遥感，查明与岛屿范围内三个关键种群(棘鳃、海龟、鲸类)的分布有关的环境因素。在第二章中，我将测试确定的因素是否可以用来从数学模型(地理剖面图、基于个体的模型、生态位分布模型)预测未调查地区的群落组合，然后我将用航空无人机调查进行经验验证。在第三章中，我将根据第一章和第二章的结果，使用模型来构建Silico中的管理情景，包括动态管理，以及在气候变化下分布可能发生的变化。通过将经验和理论相结合，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，并为可持续管理沿海地区提供潜在的方向，这些地区在不断变化的气候下支持高度生物多样性。

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.