Synthesis of marine time series to detect, understand, and predict benthic community responses to a rapidly warming Arctic

综合海洋时间序列来检测、理解和预测底栖群落对快速变暖的北极的反应

• 批准号: 2232596
• 负责人: Matthew Fitzpatrick
• 金额: $ 61.27万
• 依托单位: University of Maryland Center for Environmental Sciences
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2232596&HistoricalAwards=false
• 关键词: Synthesis; marine; time; series; detect

1. The Arctic is one of the fastest warming regions of the planet and long-term observations have revealed that natural systems in this region are undergoing substantial changes. Observed changes have been especially pronounced in the Pacific Arctic, where increases in ocean temperature, decreases in sea ice extent, and changes in currents have been observed alongside changes in the composition of ecologically important biological communities that live in sediments on the seafloor. Changes in these communities likely will have cascading impacts on fisheries and seabird and marine mammal populations that rely on food from the seafloor. The goal of this project is to examine coincident changes in seafloor biological communities and physical environments as recorded in samples collected over the last several decades to understand relationships between environmental change and ecological responses in the Pacific Arctic. In particular, this project will test how well observational data collected annually for decades can be used to make forecasts of how marine systems are likely to change in response to environmental change. A secondary goal is to assess how well ongoing sampling efforts may be able to detect biological changes in these systems. Ecological and environmental changes in the Pacific Arctic also will have immediate economic and social implications, especially for Indigenous communities that rely on subsistence harvests of walruses and bearded seals. By helping to improve our ability to detect, explain, and predict changes in these systems, this project will support effective management and sustainable use of marine resources, while mitigating social impacts on local communities. This project also will combine research and education by providing interdisciplinary training in polar biology, modeling, statistics, and data science to students at all levels and from backgrounds that are historically underrepresented in these fields, including interns from rural Appalachia, undergraduates, and an early career scientist. Lastly, we will share research outcomes and acquire shared knowledge from Indigenous communities in the region.2. Biological communities found in seafloor sediments of the Pacific Arctic are highly productive, influence ecosystem processes, and are critical food resources for marine mammals and birds. These seafloor communities are also sensitive to environmental change, and recent observations indicate shifts in taxonomic composition associated with increases in ocean temperature, decreases in sea ice extent, and changes in currents. Changes in Pacific Arctic seafloor communities are likely to have cascading impacts on seabird and marine mammal populations, ecosystem function, and fisheries. However, improving our ability to explain and predict responses of Arctic marine systems to rapid climate change remains a substantial challenge. In remote, data-limited ecosystems like the Arctic seafloor, where direct observation and experimentation are difficult, correlative models are often used to link biological patterns to environmental gradients and to make forecasts of ecosystem trajectories. However, few studies have performed rigorous tests of the ability of these so-called “space-for-time substitution” approaches to predict changes in community composition, in large part due to a lack of contemporary datasets with sufficient spatial and temporal coverage. At the same time, we lack a basic understanding of the role of thresholds, where incremental changes in the physical environment result in sudden and fundamental changes to community composition and ecosystem function, in driving biological responses to environmental change. To address these hurdles, this project will (1) analyze multi-decadal time series of paired biological and physical observations that have been collected in the northern Bering and Chukchi seas since the 1980s to characterize relationships between the physical environment and responses of ecologically important marine seafloor communities; (2) test the extent to which observational time series can inform forecasts of changes in these systems; and (3) evaluate the efficiency of ongoing sampling efforts to detect biological changes. In doing so, this project will improve our ability to explain, detect, and predict biological responses in changing Arctic environments and address associated knowledge gaps using novel modeling methods. The Arctic is one of the most rapidly warming regions on the planet and associated impacts on high biomass seafloor communities in the northern Bering and Chukchi seas will have immediate economic and social implications for potential northward fisheries expansion as well as co-management of subsistence harvests of walruses and bearded seals by Indigenous communities. Our goal is to improve our ability to detect, explain, and predict changes in these systems, and in doing so we will support effective management and sustainable use of marine resources, while mitigating social impacts on local communities. In addition, we will integrate research and education in multiple ways by: (i) mentoring summer interns from underrepresented groups attending a local college in rural Appalachia; (ii) providing research experiences to undergraduates through an existing Research Experiences for Undergraduates program; and (iii) training of a graduate student in spatial modeling, marine science, and global change ecology. These programs will provide interdisciplinary training that spans polar biology, spatial modeling, statistics, and data science for students from backgrounds that are historically underrepresented in these fields. Lastly, we will share research outcomes and acquire shared knowledge from Indigenous communities in the Bering Strait region.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

1.北极是地球上变暖最快的地区之一，长期观测表明，该地区的自然系统正在发生重大变化。观察到的变化在太平洋北极地区特别明显，在那里，海洋温度上升，海冰范围减少，海流发生变化，同时生活在海底沉积物中的具有重要生态意义的生物群落的组成也发生变化。这些群落的变化可能会对依赖海底食物的渔业、海鸟和海洋哺乳动物种群产生连锁反应。该项目的目标是研究过去几十年收集的样本中记录的海底生物群落和物理环境的同步变化，以了解太平洋北极地区环境变化与生态反应之间的关系。特别是，该项目将测试如何利用几十年来每年收集的观测数据来预测海洋系统可能如何因环境变化而发生变化。第二个目标是评估正在进行的取样工作在多大程度上能够检测到这些系统中的生物变化。太平洋北极地区的生态和环境变化也将产生直接的经济和社会影响，特别是对依赖海象和须海豹生存的土著社区。通过帮助提高我们检测、解释和预测这些系统变化的能力，该项目将支持海洋资源的有效管理和可持续利用，同时减轻对当地社区的社会影响。该项目还将联合收割机研究和教育相结合，通过提供极地生物学，建模，统计学和数据科学的跨学科培训，为各级学生和来自历史上在这些领域代表性不足的背景，包括来自阿巴拉契亚农村的实习生，本科生和早期职业科学家。最后，我们将分享研究成果，并从该地区的土著社区获得共享知识。在太平洋北极海底沉积物中发现的生物群落具有很高的生产力，影响生态系统进程，是海洋哺乳动物和鸟类的重要食物资源。这些海底生物群落对环境变化也很敏感，最近的观察表明，分类组成的变化与海洋温度的上升、海冰范围的减少和海流的变化有关。太平洋北极海底群落的变化很可能对海鸟和海洋哺乳动物种群、生态系统功能和渔业产生级联影响。然而，提高我们解释和预测北极海洋系统对快速气候变化的反应的能力仍然是一项重大挑战。在像北极海底这样的偏远、数据有限的生态系统中，直接观察和实验很困难，相关模型往往被用来将生物模式与环境梯度联系起来，并对生态系统轨迹进行预测。然而，很少有研究进行严格的测试，这些所谓的“空间时间替代”的方法来预测社区组成的变化，在很大程度上是由于缺乏足够的空间和时间覆盖的当代数据集的能力。与此同时，我们对阈值的作用缺乏基本的了解，在阈值中，物理环境的增量变化导致群落组成和生态系统功能的突然和根本性变化，从而推动生物对环境变化的反应。为了克服这些障碍，该项目将：（1）分析自1980年代以来在北方白令海和楚科奇海收集的成对生物和物理观测的数十年时间序列，以说明物理环境与具有重要生态意义的海洋海底群落的反应之间的关系;（2）测试观测时间序列在多大程度上能够为预测这些系统的变化提供信息;以及（3）评估正在进行的取样工作的效率，以检测生物变化。在这样做的过程中，该项目将提高我们解释，检测和预测北极环境变化中生物反应的能力，并使用新的建模方法解决相关的知识缺口。北极是地球上变暖最快的地区之一，对北方白令海和楚科奇海高生物量海底群落的相关影响将对潜在的向北渔业扩张以及土著社区共同管理海象和须海豹的自给性捕捞产生直接的经济和社会影响。我们的目标是提高我们检测、解释和预测这些系统变化的能力，在此过程中，我们将支持海洋资源的有效管理和可持续利用，同时减轻对当地社区的社会影响。此外，我们将通过多种方式整合研究和教育：（一）指导夏季实习生从代表性不足的群体参加当地大学在农村阿巴拉契亚;（二）通过现有的本科生研究经验计划提供研究经验给本科生;和（三）在空间建模，海洋科学和全球变化生态学的研究生培训。这些计划将为来自历史上在这些领域代表性不足的背景的学生提供跨学科的培训，涵盖极地生物学，空间建模，统计学和数据科学。最后，我们将分享研究成果，并从白令海峡地区的土著社区获得共享知识。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。