Paleogenetics of Pleistocene Deep-Water Corals from the Mediterranean Sea: The Rise and Fall of Coral Populations within the Basin

地中海更新世深水珊瑚的古遗传学：盆地内珊瑚种群的兴衰

• 批准号: 0817815
• 负责人: Rhian Waller
• 金额: $ 17.61万
• 依托单位: University of Hawaii
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-12-01 至 2011-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0817815&HistoricalAwards=false
• 关键词: Paleogenetics; Pleistocene; Deep; Water; Corals

This project examines processes controlling deep-water coral dispersal through time inthe Mediterranean Sea, an area where many biogeographical barriers to gene flow impede the entrance and settlement of larvae over time. Until recently, only sub-fossil scleractinian Lophelia pertusa banks, reefs and mounds had been conclusively discovered (dated as late Pleistocene, ~11,000 years ago). Current hypotheses contend that this, and many other, species were isolated from thriving populations in the outer NE Atlantic by the Gibraltar Sill, and that the Mediterranean acted as a refuge for deep-water corals during the stresses of the Pleistocene, later becoming cut off by oceanographic conditions, and eventually dying out. However, in 2001 a thriving L. pertusa reef was discovered in the Ionian Sea, leading to many fundamental questions regarding the population dynamics and ecology of this species. In collaboration with international scientists our proposed work takes advantage of novel ancient DNA approaches on coral skeletons to investigate the genetic connectivity of sub-fossil and live deep-water coral mounds throughout the Mediterranean Sea, as well as their connection to the outer Atlantic Ocean, in order to enable us to answer fundamental questions regarding the ecology and phylogeography of deep-water corals in this region through time. This project will further our knowledge of the population dynamics of both the Mediterranean region, and of deep-water coral species and their reaction to the changes within the last 11,000 years. There are over 100,000 fishermen on 40,000 vessels that work within the confines of the Mediterranean Sea. Over the last 20 years stocks of many traditional fisheries in this area have been in rapid decline. With this decline in traditional fisheries, a move to exploit deeper water fisheries within the Mediterranean will occur soon, as already observed in the outer North Atlantic. Deep-water corals are firmly established as an important habitat for many commercial fish species, and in areas where deep-water fishing occurs (e.g. NE Atlantic, New Zealand, Australia) damage from commercial trawlers is evident. By providing essential information on the genetic connectivity, dispersal and colonization of Mediterranean deep-water corals, this project will allow a better understanding on these populations and allow for more informed decisions on designating marine protected areas. Results from this study will also be provided to the HMAP (The History of Marine Animal Populations) and FMAP (Future of Marine Animal Populations) projects, two of the major elements of the Census of Marine Life (CoML) program. This information will also provide insight into the role of climate on historic coral populations, and improve predictive models of population responses to future climate change.

该项目研究了地中海深水珊瑚随时间扩散的控制过程，在地中海地区，随着时间的推移，许多阻碍基因流动的生物地理障碍阻碍了幼虫的进入和定居。直到最近，只有亚化石才被确凿地发现(年代确定为晚更新世，约11,000年前)。目前的假说认为，这个物种和许多其他物种是由直布罗陀峡谷从东北大西洋外部繁荣的种群中分离出来的，地中海在更新世的压力期间充当了深水珊瑚的避难所，后来被海洋条件切断，最终灭绝。然而，2001年在爱奥尼亚海发现了一处欣欣向荣的Pertusa珊瑚礁，这导致了许多关于该物种种群动态和生态的基本问题。与国际科学家合作，我们拟议的工作利用对珊瑚骨骼的新的古代DNA方法来调查整个地中海的亚化石和生活的深水珊瑚丘的遗传连通性，以及它们与外大西洋的联系，以使我们能够回答关于该区域随着时间的推移的深水珊瑚的生态学和系统地理的基本问题。该项目将促进我们对地中海区域和深水珊瑚物种的种群动态以及它们对过去11,000年内变化的反应的了解。有超过10万名渔民在4万艘船只上，在地中海范围内作业。在过去20年中，该地区许多传统渔业的种群迅速减少。随着传统渔业的减少，开发地中海深水渔业的行动将很快发生，正如在北大西洋外围已经观察到的那样。深水珊瑚被牢固地确立为许多商业鱼类的重要栖息地，在发生深水捕捞的区域(例如东北大西洋、新西兰、澳大利亚)，商业拖网渔船的损害是显而易见的。通过提供关于地中海深水珊瑚遗传连通性、扩散和定居的基本信息，该项目将使人们能够更好地了解这些种群，并能够就划定海洋保护区作出更明智的决定。这项研究的结果还将提供给海洋动物种群历史(HMAP)和海洋动物种群未来(FMAP)项目，这两个项目是海洋生物普查(CoML)计划的两个主要组成部分。这些信息还将提供对气候对历史珊瑚种群的作用的洞察，并改进人口对未来气候变化反应的预测模型。