CoPe RCN: New Technology to Inform Coastal Science and Management

这笔赠款用于规划和发展区域生态系统服务观测网络。RESON是以区域为重点的传感器和数据源网络，是测量沿海生态系统脉搏所必需的，涵盖了它们的结构、功能和为人们提供的服务。它们扩展了区域海洋观测系统的框架，在渔业和沿海基础设施需求的背景下明确考虑生物多样性、生态系统功能和物种迁徙。这个研究协调网络(RCN)将汇集来自学术界和工业界的海洋科学家、模型师、工程师、空间统计学家和计算机科学家，并与利益攸关方和管理人员合作。为了扩大对这些活动的参与，该团队将与NSF黄金积极社会参与研究和教育计划(ASPIRE)协调，该计划旨在培养一代具有领导知识和技能、学术和物质支持的地球科学家，以重塑地球科学的社会相关性。他们还将与UCSB Engineering Capstone项目合作，这是一门为期一年的基于项目的课程，面向学生，将四年级工程学学生与研究项目配对，为机械、电气和计算机工程学科的实际和有意义的问题创造工程解决方案。UCSB是一家拉美裔服务机构，也是一家亚裔美国人和美洲原住民太平洋岛民服务机构，拥有超过40%的第一代大学生，直接位于海岸，这一独特的地理位置，加上其在海洋科学、工程、环境科学和管理方面的优势，使其成为包容性的国家沿海科学网络枢纽的理想位置。之所以需要这一区域网络，是因为在沿海系统收集时间序列数据花费巨大，但这些监测工作的空间和时间尺度不足以应对气候变化、污染和捕鱼导致的沿海社区、生物多样性和生态系统服务的区域和全球变化。迫切需要更便宜、更快、更高质量的方法来收集具有广泛空间覆盖面的时间序列数据，以捕捉生态系统过程和移动的海洋动物的时间尺度。满足这一需求将大大加快在海洋生态系统的生命规则和气候变化研究方面的进展，并使管理对策和社区适应能够发生变化。这项工作将以加州当前大型海洋生态系统(CC LME)为初始模型，重点关注三个数据目标：生物多样性、生态系统功能和物种迁移，并将利用现有的网络，包括南加州海岸OOS、LTER、MBON(海洋生物多样性观测网络)和ATN(动物遥测网络)。考虑的变量将包括声音、图像、环境DNA、生物量、运动和生理表现。区域生态网络的目标将是：1)开展一系列研讨会，以确定传感器和测量的有效组合，并计划建立和验证足以预测未来生态系统变化的模型所需的空间和时间采样制度；2)确定消除差距所需的具体数据产品、传感器和传感器平台，使利益攸关方和管理人员参与确保与政策相关；以及3)与侧重于沿海生态系统健康的技术部门建立持续的协作网络。该奖项反映了NSF的法定使命，通过使用基金会的智力优势和更广泛的影响审查标准进行评估，认为值得支持。

This grant is for the planning and development of Regional Ecosystem Services Observation Networks. RESONs are regionally-focused networks of sensors and data sources necessary to take the pulse of coastal ecosystems, spanning their structure, function, and services provided to people. They extend the framework of the regional Ocean Observing Systems (OOSs) to explicitly consider biodiversity, ecosystem function, and species migration in the context of fisheries and coastal infrastructure needs. This Research Coordination Network (RCN) will bring together marine scientists, modelers, engineers, spatial statisticians, and computer scientists from academia and industry in collaboration with stakeholders and managers. In order to broaden participation in these activities, the team will coordinate with the NSF GOLD Active Societal Participation In Research and Education (ASPIRE) program, which aims to cultivate a generation of geoscientists with the leadership knowledge and skills, scholarship, and material support to reframe and rebrand the geosciences as socially relevant. They will also work with the UCSB Engineering Capstone program, a year-long, project-based course offered to students that pairs fourth-year engineering students with research projects to create an engineered solution for real and meaningful problems across the disciplines of mechanical, electrical and computer engineering. UCSB is a Hispanic Serving Institution and an Asian American and Native American Pacific Islander Serving Institution with a population of over 40 percent first generation college students that is uniquely located directly on the coast, which, together with its strengths in marine science, engineering, and environmental science and management, makes it an ideal location as an inclusive national network hub for coastal science. This RCN is needed because time series data have been collected in coastal systems at great expense, but the spatial and temporal scales of these monitoring efforts are inadequate to address regional and global shifts in coastal communities, biodiversity and ecosystem services that result from climate change, pollution, and fishing. Urgently needed are cheaper, faster, higher-quality ways to collect time series data with broad spatial coverage that captures time scales of ecosystem processes and moving marine animals. Filling this need will greatly accelerate progress on Rules of Life and climate change research in marine ecosystems and enable management responses and community adaptation to change. This effort will focus on three data targets: biodiversity, ecosystem function, and species migration, using the California Current Large Marine Ecosystem (CC LME) as an initial model, and will leverage existing networks including Southern California Coastal OOS, LTER, MBON (Marine Biodiversity Observation Network) and ATN (Animal Telemetry Network). Variables considered will include sound, imagery, environmental DNA, biomass, movement, and physiological performance. The goals of the RCN will be to 1) develop a series of workshops to identify effective combinations of sensors and measurements and plan spatial and temporal sampling regimes necessary for building and validating models adequate to forecast future ecosystem change; 2) identify specific data products, sensor and sensor platforms needed to address gaps, engaging stakeholders and managers to ensure relevance to policy; and 3) build a sustained collaborative network with the technology sector focused on coastal ecosystem health.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.