Application of acoustical remote sensing techniques for ecosystem monitoring of a seagrass meadow

声学遥感技术在海草甸生态系统监测中的应用

• 批准号: 2023211
• 负责人: Megan Ballard
• 金额: $ 85.16万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2023211&HistoricalAwards=false
• 关键词: Application; acoustical; remote; sensing; techniques

This research focuses on the design and testing of a system capable of long-term field deployment that uses sound to monitor seagrass biomass and productivity with significantly improved temporal resolution compared to traditional techniques. Long-term continuous measurements of relevant parameters of ecosystem production are of primary importance for ecosystem health assessment and sustainable management. Dissolved oxygen measurements made with optical sensors are the most widely used method for estimating seagrass photosynthesis in relation to underwater irradiance. Oxygen evolution is also critical in maintaining aerobic conditions for below ground seagrass roots and rhizomes that constitute 60-80% of total plant biomass. However, under oxygen saturation conditions, which occurs frequently in summer under high light conditions, free gas bubbles are continuously released by the plants. Optical sensors are unable to detect bubbles under such supersaturated conditions, leading to underestimates in seagrass photosynthetic carbon production. Since oxygen saturation occurs more readily at higher temperatures and light conditions that are most prevalent from the late spring to early fall months, accurate determinations of productivity are only possible under low light conditions or in the early morning hours. Since sound propagation in water is very sensitive to the presence of bubbles, acoustic methods provide an alternative measure of true photosynthetic oxygen production in seagrass meadows with high temporal resolution. The researchers will engage in outreach activities including the Freshman Research Initiative (FRI) at University of Texas at Austin (UT), which gives first-year students the opportunity to initiate and engage in real-world research experience with faculty and graduate students. The project will also engage grades K-16 through the development of a Data Nugget based on the long-term data set collected through the proposed research.The stand-alone field-deployed system will use broadband acoustic measurements to remotely sense both seagrass biomass and gas ebullition. The system will consist of three main components: 1) an acoustic source projector and a set of receiving hydrophones, 2) an instrumentation pressure vessel (IPV) that houses the electronics controlling the acoustic data acquisition and data storage, and 3) a suite of environmental sensor-loggers. The proposed measurement system will be made compact and lightweight enough that it can be hand-deployed in the seagrass meadow from a small watercraft that is capable of accessing the shallow bays of the Texas Gulf of Mexico coast. The target deployment water depth is 2-3 m, which reflects the maximum depths of seagrass distribution in Texas coastal waters. Geoacoustic inference techniques will be applied to quantify the void fraction of gas in the seawater as well as the gas volume present within the seagrass tissue. Bayesian techniques will be used to assess parameter uncertainties and reveal parameter correlations. Low-frequency sound (3 kHz) is most sensitive to gas entrained within the seagrass tissue, and an effective medium model which accounts for the seagrass tissue elasticity and structure of seagrass leaves is being developed to quantify the gas volume present within the seagrass leaves, roots, and rhizomes. Mid-frequency sound (3.5 to 35 kHz) is most sensitive to free bubbles in the water resulting from seagrass photosynthesis. The void fraction of gas in the water can be related to oxygen production by accounting for vertical transport of oxygen bubbles to the sea surface. The data from this system will be used to build new connections between seagrass condition indicators and environmental stressors. This research will lead to predictions of seagrass responses to climate change by accounting for both trend- and event-driven perturbations that affect physical forcing factors such as light transmission, water circulation, temperature, and salinity.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.

本研究的重点是设计和测试一个能够长期现场部署的系统，该系统使用声音来监测海草生物量和生产力，与传统技术相比，该系统的时间分辨率显着提高。生态系统生产相关参数的长期连续测量对生态系统健康评价和可持续管理至关重要。利用光学传感器进行的溶解氧测量是估计海草光合作用与水下辐照度关系的最广泛使用的方法。氧演化对于维持占植物总生物量60-80%的地下海草根和根茎的有氧条件也至关重要。然而，在氧饱和条件下，这种情况在夏季强光条件下经常发生，植物不断释放自由气泡。在这种过饱和条件下，光学传感器无法检测到气泡，导致海草光合作用碳产量被低估。由于氧饱和度在较高的温度和光照条件下更容易发生，在春末到初秋的几个月里最为普遍，因此只有在低光照条件下或在清晨才能准确测定生产力。由于声音在水中的传播对气泡的存在非常敏感，声学方法提供了一种具有高时间分辨率的海草草甸中真正光合作用氧气产生的替代测量方法。研究人员将参与外展活动，包括德克萨斯大学奥斯汀分校（UT）的新生研究计划（FRI），该计划为一年级学生提供了与教师和研究生一起发起和参与现实世界研究经验的机会。该项目还将通过根据拟议研究收集的长期数据集开发数据块，让K-16年级的学生参与其中。独立的现场部署系统将使用宽带声学测量来远程感知海草生物量和气体沸腾。该系统将由三个主要部件组成：1)声源投影仪和一组接收水听器，2)容纳控制声学数据采集和数据存储的电子设备的仪表压力容器（IPV），以及3)一套环境传感器记录仪。拟议的测量系统将足够紧凑和轻便，可以在能够进入德克萨斯州墨西哥湾沿岸浅海湾的小型船只上手动部署在海草草地上。目标部署水深为2 ~ 3 m，反映了德克萨斯州沿海海域海草分布的最大深度。地球声推断技术将用于量化海水中气体的空隙率以及海草组织中存在的气体体积。贝叶斯技术将用于评估参数不确定性和揭示参数相关性。低频声（3khz）对海草组织内携带的气体最敏感，目前正在开发一种有效的介质模型，该模型可以解释海草组织的弹性和海草叶片的结构，以量化海草叶片、根和根茎内存在的气体体积。中频声音（3.5至35千赫）对海草光合作用产生的水中自由气泡最敏感。通过计算氧气气泡向海面的垂直输送，水中气体的空隙部分可以与氧气的产生有关。该系统的数据将用于在海草状况指标和环境压力因素之间建立新的联系。这项研究将通过考虑影响物理强迫因子（如光透射、水循环、温度和盐度）的趋势和事件驱动的扰动，预测海草对气候变化的响应。该奖项反映了美国国家科学基金会的法定使命，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。

项目成果

Inter-seasonal comparison of acoustic propagation in a Thalassia testudinum seagrass meadow in a shallow sub-tropical lagoon

亚热带浅泻湖龟龟海草草甸声波传播的季节间比较

• DOI: 10.1121/10.0016752
• 发表时间: 2022
• 期刊: JASA Express Letters
• 影响因子: 1
• 作者: Lee, Kevin M.;Ballard, Megan S.;McNeese, Andrew R.;Wilson, Preston S.;Venegas, Gabriel R.;Zeh, Mathew C.;Rahman, Abdullah F.
• 通讯作者: Rahman, Abdullah F.

Characterizing the acoustic response of Thalassia testudinum leaves using resonator measurements and finite element modeling

使用谐振器测量和有限元建模表征 Thalassia testudinum 叶片的声学响应

• DOI: 10.1121/10.0017000
• 发表时间: 2023
• 期刊: The Journal of the Acoustical Society of America
• 作者: Torres, Nicholas A.;Ballard, Megan S.;Lee, Kevin S.;Wilson, Preston S.;Naify, Christina J.;Ben-avi, Aytahn
• 通讯作者: Ben-avi, Aytahn