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

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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.