In-situ sustained monitoring and eDNA techniques for determining responses of intertidal species to environmental change

关键词：环境变化，海洋生态，eDNA，潮间带，全球变化，气候变化，物种分布摘要：气候变化是全球安全，人类健康和生物多样性的最大威胁。它通过气候条件和气候变异性的普遍变化、极端事件的频率增加和海平面上升影响海洋生态系统。有必要了解气候变化影响的生态动态，以确定脆弱性和复原力的热点，并确定可能有助于生物圈适应气候变化的管理干预措施。持续观测监测可以跟踪和量化变化，对于预测未来变化至关重要，然而，目视调查并不总是记录所有存在的物种，特别是稀有或隐藏的物种。这将测试热亲和力和热栖息地之间的匹配是否在具有不同生活史和栖息地偏好的物种之间存在差异。该项目将使用全球数据库、英国调查的高质量数据以及使用eDNA技术生成的新数据。气候变化正在引起海洋社区前所未有的反应。然而，由于缺乏长期数据集以及自然和人为驱动因素的小规模变异，难以量化空间和时间趋势。了解这些变化需要一种多学科的方法，将长期数据集中识别的模式与使用生物相关信息来归因因果的驱动这些模式的过程相结合。潮间带物种是气候变化影响的早期指标，其地理范围每十年移动高达10公里，是任何自然系统中最快的。许多物种的范围边界发生在英国海岸线周围，将较冷的北方和较温暖的卢西塔尼亚省之间的边界一分为二，对生态系统结构和功能产生影响。该博士项目将结合联合收割机宏观生态学，生理学和分子技术，以解决如何快速是气候驱动的范围扩张发生在英国潮间带栖息地的问题？博士将使用MarClim时间序列，这是世界上最时空广泛的潮间带系统时间序列。对岩石潮间带物种的持续观察可以追溯到20世纪50年代，已经显示出任何自然系统中物种丰度和分布的最快变化。该数据集包括87种无脊椎动物和北方，卢西塔尼亚和入侵起源的大型藻类。博士学位还将纳入环境DNA（eDNA）分析，以测试早期发现向北的范围传播和识别物种存在于南极生命阶段。该博士学位将采用最先进的综合视角，探讨生态系统如何应对气候变化，如何增强生态系统的复原力，以及生态系统如何帮助应对气候变化的挑战。该项目将把这一观测数据集与eDNA技术和统计建模联系起来，以评估环境变化对潮间带生境物种分布的时空影响程度。

Key words: Environmental change, marine ecology, eDNA, intertidal, global change, climate change, species distributionsAbstract: Climate change is the biggest threat to global security, human health, and biodiversity. It is affecting marine ecosystems through pervasive changes in climatic conditions and climate variability, increased frequency of extreme events and sea level rise. There is a need to understand the ecological dynamics of climate change impacts to identify hotspots of vulnerability and resilience and to identify management interventions that may assist biosphere resilience to climate change. Sustained observations monitoring can track and quantify changes, and is critical for predicting future changes, however, visual surveys do not always record all species present, especially rare or cryptic species. This will test whether the match between thermal affinity and thermal habitat differs between species with different life histories and habitat preferences. The project will use global databases, high quality data from UK surveys, and new data generated using eDNA techniques. Climate change is causing unprecedented responses in marine communities. Spatial andtemporal trends are difficult to quantify, however, due to the lack of long-term datasets and the occurrence of small-scale variability from natural and anthropogenic drivers. Understanding these changes requires a multidisciplinary approach combining patterns identified within long-term datasets and the processes driving those patterns using biologically relevant information to attribute cause and effect. Intertidal species are early indicators of climate change impacts, with biogeographic range shifts of up to 10km per decade, some of the fastest in any natural system. Range boundaries of many species occur around the UK coastline, which bisects the boundary between the cooler Boreal and warmer Lusitanian provinces, with implications for ecosystem structure and functioning. The PhD project will combine macroecology, physiology and molecular techniques to address the question of how fast is climate-driven range expansion occurring in UK intertidal habitats?The PhD will use the MarClim time-series, which is the most spatio-temporally extensive time-series for intertidal systems in the world. Sustained observations of rocky intertidal species date back to the 1950s have shown some of the fastest shifts in abundance and distribution of species in any natural system. This dataset includes 87 species of invertebrate and macroalgae of boreal, lusitanian and invasive origins. The PhD will also incorporate environmental DNA (eDNA) analysis to test for early detection of northwards range spread and identification of species presence at planktonic life stages. This PhD will take a state-of-the-art, integrated perspective on how ecosystems respond to climate change, how ecosystem resilience can be enhanced and how ecosystems can assist in addressing the challenge of a changing climate. The project will link this observational dataset with eDNA techniques and statistical modelling to assess the spatial and temporal extent of environmental change on species' distributions in intertidal habitats.