LTER: Linking Pelagic Community Structure with Ecosystem Dynamics and Production Regimes on the Changing Northeast US Shelf

西北大西洋以多产的渔业而闻名，渔业依靠由浮游生物组成的复杂食物网为其提供能量。在这些水域——就像在全球沿海水域一样——人类活动、环境变化和十年尺度的变化相互交织，对浮游食物网产生了不同的影响。了解这个网络的结构、功能以及对季节性环境变化的反应是至关重要的，这样才能对该地区正在加速的长期趋势做出适当的反应。然而，由于缺乏足够时间的系统和详细的测量，我们的理解受到限制，因此我们无法观察这些网络对环境扰动的反应，并揭示潜在的原因和影响。美国东北陆架（NES）长期生态研究（LTER）项目将提供这样的观察，用各种模型分析它们，并提高我们预测浮游生物食物网如何随空间和时间变化的能力，以及这些变化如何影响高营养水平的生产力，包括商业上重要的鱼类。此外，NES- lter项目将产生多方面的更广泛的影响，包括与美国国家海洋和大气管理局（NOAA）、东北渔业科学中心合作，支持对NES进行多物种、基于生态系统的管理。该项目包括一项教育计划，该计划将为广泛的学习者提供机会，并将通过NOAA的“地球上的科学”国际网络制定影响深远的公共宣传内容。虽然该地区的生态系统在季节到几十年之间的变化模式已经被记录下来，但连接物理环境、浮游食物网和更高营养水平变化的关键机制仍然知之甚少。由于这个原因，预测能力是有限的，管理策略很大程度上是被动的。为了满足这些需求，NES-LTER策略结合了提供区域尺度背景的观测、沿高梯度跨大陆架样带的过程巡航、大陆架内外位置的高频时间序列、耦合生物-物理食物网模型和目标种群模型。研究计划以一个首要的科学问题为指导：长期环境变化如何影响远洋NES生态系统，特别是影响组成（如物种多样性和大小结构）和聚集（如初级生产力和向重要饲料鱼类转移的能量）变异性之间的关系？通过利用NES中高水平的季节性和年际变化，该研究将研究对环境变化的短期响应，以a)表征低出口和高出口食物网，b)了解浮游植物与远洋鱼类之间的联系和能量转移，以及c)确定高出口和低出口群落之间转移的机制。最终，机械知识将扩大规模，以理解和预测与生态系统中十年尺度强迫趋势相关的影响和反馈。

The northwest Atlantic is renowned for productive fisheries that depend upon a complex food web of planktonic organisms that provide them energy. In these waters -- as in coastal waters around the globe -- human activities, environmental variability, and decadal-scale change intersect to have diverse effects on the planktonic food web. It is crucial to understand the structure of this web, how it functions, and how it responds to seasonal environmental change, in order to respond appropriately to long-term trends that are accelerating in this region. Our understanding, however, has been limited by a lack of systematic and detailed measurements over a sufficient length of time so that we can observe the responses of these webs to environmental perturbations and uncover the underlying causes and implications. The Northeast US Shelf (NES) Long-Term Ecological Research (LTER) project will provide such observations, analyze them with a variety of models, and improve our ability to predict how planktonic food webs change through space and time, and how those changes impact the productivity of higher trophic levels including commercially important fish. In addition, the NES-LTER project will have multifaceted broader impacts, including collaboration with the National Oceanic and Atmospheric Administration's (NOAA), Northeast Fisheries Science Center to support multispecies, ecosystem-based management on the NES. The project includes an education plan that will provide opportunities to a broad range of learners and a far-reaching public outreach component will be developed through NOAA's international Science-On-a-Sphere network. While patterns of ecosystem change over seasons to decades have already been documented in this region, the key mechanisms linking changes in the physical environment, planktonic food webs, and higher trophic levels remain poorly understood. For this reason, predictive capability is limited and management strategies are largely reactive. To address these needs, the NES-LTER strategy combines observations that provide regional-scale context, process cruises along a high gradient cross-shelf transect, high-frequency time series at inner- and outer-shelf locations, coupled biological-physical food web models, and targeted population models. The research plan is guided by an overarching science question: How is long-term environmental change impacting the pelagic NES ecosystem and, in particular, affecting the relationship between compositional (e.g., species diversity and size structure) and aggregate (e.g., rates of primary production, and transfer of energy to important forage fish species) variability? By capitalizing on high levels of seasonal and interannual variability in the NES, the research will study short-term responses to change in the environment to a) characterize low and high export food webs, b) understand the linkages and transfer of energy from the phytoplankton to pelagic fish, and c) identify the mechanisms that underlie shifts between high and low export communities. Ultimately, mechanistic knowledge will be scaled up to understand and predict the impacts and feedbacks associated with trends in decadal-scale forcing in the ecosystem.