Doctoral Dissertation Research: Habitat Mapping and Species-Environment Interactions of Rare Species using Multi-Sensor Remote Sensing: Case Study: Endangered Mangrove Finch

了解物种地理分布的限制和变化是保护生物学、景观生态学和植物地理学的一个重要研究领域。分布建模提供了有关物种分布的位置和原因的有用信息，包括生态系统服务，功能和生物多样性模式，以及对物种-环境相互作用的详细了解。确定珍稀濒危物种的关键或潜在生境对保护生物学尤为重要。用于绘制物种分布图的模型的数据要求仍然是一个重大挑战。虽然物种出现数据是以实地为基础的，但环境数据需要不断地加以表示，因此，遥感作为数据来源提供了独特的可能性。通过天基遥感绘制物种分布图面临着许多挑战，包括数据质量、图像处理和信息提取、数据融合和整合以及模型选择和变量表征。虽然许多研究使用遥感技术绘制生境图，但很少有研究使用真正适合在适当空间尺度上捕捉感兴趣的物种-环境相互作用的环境数据。本研究的主要目的是以加拉帕戈斯群岛的红树林雀为例，模拟珍稀濒危物种的潜在适宜生境和地理分布。红树林雀是厄瓜多尔加拉帕戈斯群岛伊萨贝拉岛的特有物种。为了模拟包括鸟类在内的许多动物物种的栖息地，与环境数据有关的挑战需要采用多传感器方法，不仅要描述植被覆盖和景观的空间组织，还要描述植被的垂直结构，如树冠高度、分枝特征和其他生物物理参数，包括生物量或叶面积。这项研究将使用多传感器遥感方法，结合被动光学和主动微波传感器，以现有技术可能达到的最高分辨率，按范围、物种组成、生物量和树冠高度来描述红树林的特征。这些数据将与使用物种分布模型MaxEnt对红树林雀的实地观察相结合，以预测和绘制适当的生境。本研究的结果将包括红树林树种、树冠高度、生物量、红树林雀潜在栖息地的适宜性以及详细的物种-环境关系图，有助于进一步完善物种分布图的绘制方法和技术。这项研究将展示利用空间进行稀有和濒危物种生境特征鉴定和物种分布绘图的潜力。这项研究可以作为一个模式，为未来的保护研究和应用，通过数据融合的方法来开发。这项研究的结果直接应用于加拉帕戈斯群岛，这是一个联合国教科文组织生物圈保护区和世界遗产。这项研究将产生栖息地适宜性地图的红树林雀，以协助保护生物学家与正在进行的圈养繁殖计划，以增加和维持红树林雀的人口。同样，由此产生的物种-环境关系可用于帮助保护现有的红树林。描述红树林物种组成和物理结构的地图将首次全面展示加拉帕戈斯群岛的红树林，从而作为跟踪红树林未来动态的基线。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立的研究生涯。

Understanding the limits and shifts of the geographic distribution of species is an important area of research for conservation biology, landscape ecology, and biogeography. Modeling distributions provides useful information about the where and why of species distributions including ecosystem services, functions, and patterns of biodiversity, as well as detailed understanding of species-environment interactions. Identification of critical or potential habitats of rare and endangered species is particularly important for conservation biology. The data requirements of models used to map species distributions remain a significant challenge. While species occurrence data are field based, environmental data need to be continuously represented, and therefore, remote sensing offers unique possibilities as a data source. There are many challenges to mapping species distributions through space-based remote sensing including data quality, image processing and information extraction, data fusion and integration, and model selection and variable characterization. While numerous studies have used remote sensing to map habitats, very few have done so using environmental data that are truly suitable for capturing the species-environment interactions of interest at the appropriate spatial scales. The primary objective of this research is to model the potential suitable habitat and geographic distribution of rare and endangered species using the mangrove finch in the Galapagos Islands as a case study. The mangrove finch is an endemic species to Isabela Island in the Galapagos Archipelago, Ecuador. To model habitat for many animal species including birds, the challenges related to environmental data require a multi-sensor approach that describes not only vegetation cover and the spatial organization of the landscape, but the vertical structure of vegetation, such as canopy height, branching characteristics, and other biophysical parameters, including biomass or leaf area. This study will use a multi-sensor remote sensing approach to combining passive optical and active microwave sensors to characterize mangrove forests by extent, species composition, biomass, and canopy height at the finest resolution possible given available technologies. These data will be incorporated with field observations of the mangrove finch using the species distribution model, MaxEnt, to predict and map suitable habitat. The results of this research will include maps of mangrove tree species, canopy height, and biomass, and suitability of potential mangrove finch habitat, as well as detailed species-environment relationships.The results of this study will contribute to furthering the methods and techniques of mapping species distributions. This research will demonstrate the potential for space-based habitat characterization and species distribution mapping of rare and endangered species. The research could serve as a model for future conservation research and applications through the data fusion approaches to be developed. The results of this research have a direct application in the Galapagos Islands, a UNESCO Biosphere Reserve and World Heritage Site. This research will produce habitat suitability maps of the mangrove finch to assist conservation biologists with an on-going captive breeding program to increase and maintain the mangrove finch population. Likewise, the species-environment relationships that will be generated can be used to help conserve existing mangrove forests. Maps describing the species composition and physical structure of mangrove forests will provide the first comprehensive representations of mangrove forests in the Galapagos Islands and thus serve as a baseline from which to track future dynamics of mangrove forests. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.