Collaborative Research: Diel, Seasonal, and Interannual Patterns in Zooplankton and Micronekton Species Composition in the Subtropical Atlantic

浮游生物群落由种类繁多的生物组成，这些生物构成了海洋食物网的基础。我们建议在百慕大大西洋时间系列研究(BATS)站对浮游动物和微型浮游动物进行多物种调查，该研究站位于北大西洋副热带环流或马尾藻海西部，持续11年的海洋学时间序列。该计划将提供涵盖昼夜、季节、年际和年代际时间尺度的高分辨率物种数据。已从BATS邮轮获得的详细配套环境数据(例如，水柱温度、氧气、营养物质和植物色素浓度)为数据集增添了额外的价值。物种和环境“元数据”将使用BATS已经开发和使用的技术进行格式化，以便将感兴趣的数据汇编并提供给OBIS。我们建议的项目将涉及学术界(百慕大生物研究所、伍兹霍尔海洋研究所、俄罗斯科学院动物研究所)和政府(史密森研究所国家自然历史博物馆)的参与。我们建立了伙伴关系，在研究亚热带北大西洋系统方面拥有重要的集体经验，并在识别(和生态)所有主要的浮游动物和微型动物分类群方面拥有专门知识。该项目将提供高质量的浮游动物和微型浮游动物物种组成的时间序列，使我们能够剖析浮游生物群落多样性的自然变异性和实际‘变化’之间的差异。这对于测试和验证生态系统模型以及了解长期气候变化对生态系统的影响至关重要。

Planktonic communities comprise an incredibly wide diversity of organisms that form the basis of marine food webs. We propose a multi?species inventory of zooplankton and micronekton at the Bermuda Atlantic Time?series Study (BATS) station, an 11 ?year, ongoing oceanographic time series situated in the western North Atlantic subtropical gyre or Sargasso Sea. The program will provide high?resolution species data that covers diel, seasonal, interannual, and decadal time scales. Detailed accompanying environmental data already available from BATS cruises (e.g., water column temperature, oxygen, nutrients, and plant pigment concentration) add additional value to the data set. Both species and environmental "metadata" will be formatted using techniques already well developed and in use at BATS for compilation and provision of data of interest into OBIS. Our proposed project will involve participation from both academia (Bermuda Biological Station for Research, Woods Hole Oceanographic Institution, Russian Academy of Sciences' Zoological Institute) and government (the Smithsonian Institution's National Museum of Natural History). We have developed a partnership with significant collective experience in the study of the subtropical North Atlantic system and expertise in the identification (and ecology of) all major taxa of zooplankton and micronekton. This project will provide a high quality time series of zooplankton and micronekton species composition enabling us to dissect the difference between natural variability and real 'change' in the diversity of plankton communities. This will be critical for testing and validation of ecosystem models, and for understanding the effects of long term climate change on ecosystems.