Development of an Autonomous Sampling Network for Plankton, Hydrography and Currents. Phase I. Incorporation of Plankton Imaging Capability into Autonomous Underwater Vehicles

这项研究项目是在国家海洋伙伴计划(NOPP)的赞助下进行的。它解决了生物海洋学中的一个主要挑战，即预测能力的发展。迫切的问题，如渔业产量、污染物转移、碳循环以及海洋中的声光传输，都需要准确的预测。绝大多数海洋物种至少在其生命的一部分是浮游的，因此它们的种群在被洋流输送的过程中增长和死亡。风暴、水团相互作用和捕食者-猎物斑块等间歇性因素是海洋种群变异性的主要来源。目前，我们的预测能力受到数据稀疏性和无法以足够的时间和空间分辨率采样来捕捉控制种群规模的周期性特征的限制。最近在浮游生物自动识别(通过光学成像)和自主水下机器人(AUV)设计方面的技术进步使得在时间和空间上以高分辨率自主采样浮游生物与其他环境变量(例如温度、盐度、光、营养物质、荧光、洋流)是可能的。最终，可以设想在世界海洋的特定区域部署配备浮游生物成像系统的AUV网络，以在时间和空间上提供准天气学高分辨率数据。该项目将通过将视频浮游生物记录器(VPR)纳入Remus AUV，将浮游生物成像技术与AUV技术相结合。VPR是一种水下视频显微镜，可以拍摄100微米到2厘米大小的浮游生物和其他颗粒物。Remus AUV的设计目的是在使用长基线导航和超短基线导航相结合的预先编程的任务中携带科学仪器的有效载荷。使用可充电铅酸电池的续航时间长达6小时，使用一次锂电池续航时间长达18小时，REMUS非常适合重复空间/时间数据采样。VPR的设计将是模块化的，这样就可以在其他AUV上通用。这一初步设计将允许使用小波压缩硬件对数字化视频进行车载实时压缩和存储。然后，压缩的视频将被上传到自动图像处理系统进行分析。新的VPR-REMUS系统将在各种生境中使用欧拉和拉格朗日采样方法进行测试，以自动量化浮游生物分类群、荧光、水文和洋流的分布模式。

0000580DavisThis research project is conducted under the auspices of the National Oceanographic Partnership Program (NOPP). It addresses a major challenge in biological oceanography, which is the development of predictive capability. Pressing issues such as fishery yields, pollutant transfer, carbon cycling, and sound and light transmission in the ocean all require accurate predictions. The vast majority of marine species are planktonic during at least a portion of their lives and therefore have populations that grow and die while being transported by ocean currents. Episodic factors such as storms, water mass interactions, and predator-prey patchiness are a major source of variability in marine populations. At present, our predictive capability is limited by the sparseness of data and the inability to sample with adequate time and space resolution to capture episodic features that control population size.Recent technological advancements in automated plankton identification (via optical imaging) and in design of autonomous underwater vehicles (AUVs) make it plausible to sample plankton in association with other environmental variables (e.g. temperature, salinity, light, nutrients, fluorescence, currents) autonomously with high resolution in both time and space. Ultimately, networks of AUVs equipped with plankton imaging systems deployed in specific regions of the world ocean can be envisioned to provide quasi-synoptic high-resolution data in time and space.This project will merge plankton-imaging technology with AUV technology by incorporating the Video Plankton Recorder (VPR) into the REMUS AUV. The VPR is an underwater video microscope that images plankton and other particulate matter in the size range of 100 microns to 2 centimeters. The REMUS AUV is designed to carry a payload of scientific instrumentation on pre-programmed missions using a combination of long and ultra-short baseline navigation. With up to 6 hours of endurance using rechargeable lead acid batteries or 18 hours from primary lithium cells, REMUS is well suited for repetitivespace/time data sampling. The VPR design will be made modular such that generic use in other AUVs will be possible. This initial design will allow for on-board real time compression and storage of digitized video using wavelet compression hardware. The compressed video then will be uploaded for analysis with an automated image processing system. The new VPR-REMUS system will be tested in a variety of habitats using Eulerian and Lagrangian sampling methods to automatically quantify distribution patterns of plankton taxa, fluorescence, hydrography, and currents.