Integration of remote sensing with ground-based observation to investigate plant diversity

该项目应对与环境(生物信息学、热带森林、监测)有关的全球挑战。应对这些全球挑战将使更有效的管理做法能够促进植物生物多样性的弹性，这反过来又支撑着从生态系统服务(水净化、碳循环等)到粮食安全的几乎所有人类福祉方面。生物多样性管理正在经历实施规模的阶段性变化。联合国等国际机构制定的目标需要全球响应，但目前对生物多样性和组成物种的调查通常是在非常局部的范围内进行的。该项目将开发、演示和测试一种方法，使其能够将全球范围的地球观测与地方尺度的地面观测联系起来。在此过程中，我们将在中央空间的STFC技术专长与植物种群生物学和地理参考植物采集生物信息的国际数据库之间建立新的联系。遥感能力和技术的进步为监测一系列物种和空间尺度的植物种群提供了新的机会。这在生态系统层面的碳固存能力、确定气候和其他干扰对农业生产力的影响、在景观尺度上的植物疾病流行病学等专题问题上具有潜在的重要意义。代表全球覆盖面和数十年时间尺度的多个卫星图像数据库现已可用。此外，无人机技术的进步使得用更详细的本地图像补充基于卫星的观测成为可能，从而使基于卫星的观测能够被广泛地“地面真实”。这与植物物种分布特别相关，因为卫星图像提供了潜在有用但未经测试的信息。我们建议测试一种多方面的遥感方法，以分析植物物种的分布，并最终分析生物多样性的空间分布。我们的总体目标是完善植物物种范围分析的方法，以加强大规模的保护评估，以促进对STFC全球环境挑战和其他广泛的社会挑战(如千年发展目标)的科学投入。我们将在一个示范项目中应用这一方法，分析马达加斯加豆科植物的空间分布。豆科植物是一个物种非常丰富的植物科，它们的生物多样性格局已被证明反映了生物地理学和生态学中更广泛的植物多样性格局。20多年来，RBG Kew的科学家们对马达加斯加的豆科植物进行了广泛的调查，因此，基于经科学专家验证的地理参考收集数据，存在着关于其分布的广泛数据库。该项目的预期成果将是将遥感数据应用于范围建模的经验证的新应用，可用于(全球)大范围的植物物种分布和保护评估。此外，在该项目过程中开发和改进的方法将加强监测植物种群的其他应用，如监测植物病害和农业生产的遥感应用。全球挑战资金将使STFC re-Space、植物种群生物学方面的科学专长(圣安德鲁斯)和植物分类和分布方面的专门知识(RBG Kew)之间建立新的协作联系。因此，STFC的研究能力将与一个对全球生物多样性管理具有潜在影响的新应用相联系，这样做可以展示其对其他全球挑战的适用性。

This project addresses Global Challenges related to Environment (bioinformatics, tropical forests, monitoring). Meeting these Global Challenges will enable more effective management practices to promote resilience of plant biodiversity, which in turn underpins almost every aspect of human well-being from ecosystem services (water purification, C cycles, etc) to food security. Biodiversity management is undergoing a phase change in scale of implementation. Goals set by international bodies such as the UN require a global response, but investigations of biodiversity and constituent species are often currently conducted at a very local scale. This project will develop, demonstrate and test an approach that will make it possible to connect Earth Observation at global scale to ground-based observation at local scales. In so doing, we will establish a new link between STFC technical expertise at RAL-Space with plant population biology and international databases on georeferenced plant collection bioinformatics.Advances in remote sensing capacity and technology provide new opportunities for monitoring plant populations across a range of species and spatial scales. This is potentially important in terms of topical issues like ecosystem level capacity for C sequestration, determining effects of climate and other disturbances on agricultural productivity, epidemiology of plant diseases at landscape-scale, etc. Indeed, there is a broad range of potential applications of remote sensing technology to plants which would have significant impacts on human wellbeing. Multiple databases of satellite images that represent global coverage and a multi-decade timescale are now available. Moreover, advances in UAV technology have made it feasible to complement satellite-based observation with much more detailed local imagery so that satellite-based observation can be extensively 'ground-truthed'. This is particularly relevant to plant species distributions where satellite images provide potentially useful but untested information.We propose to test a multifaceted remote-sensing approach to analyse distributions of plant species and ultimately spatial distribution of biodiversity. Our overall objective is to refine methods for plant species range analysis in order to enhance large-scale conservation assessment in order to facilitate scientific input into STFC Global Challenges related to Environment and other broad social challenges such as the Millennium Development Goals. We will be applying this approach in a demonstration project analysing spatial distributions of legumes in Madagascar. Legumes are a very species-rich plant family, and their patterns of biodiversity have been demonstrated to mirror broader patterns of plant biodiversity in biogeography and ecology. The legumes of Madagascar have been extensively investigated over more than 20 years by scientists at RBG Kew, and as such an extensive database of their distribution, based on georeferenced collection data validated by scientific experts, exists.The anticipated output of this project would be a validated novel application of remote sensing data to range modelling that could be applied for plant species distribution and conservation assessment at a large (global) scale. Moreover, the methods developed and refined over the course of this project will enhance other applications for monitoring plant populations, such as remote sensing applications to monitoring plant disease and agricultural productivity.The Global Challenges funding will enable a new collaborative link between STFC RAL-Space, scientific expertise in plant population biology (St Andrews), and expertise in plant taxonomy and distributions (RBG Kew). Thus, STFC research capacity will be linked to a new application that has potential impact on global biodiversity management, and in so doing can demonstrate applicability to other global challenges.