Maryland Sea Grant seeks to hire a Legal Fellow and a Graduate Assistant. More details.
OBJECTIVES The overall objective is to understand the role of nutrient inputs and cycles in the recent sharp increase of submersed aquatic vegetation (SAV) in upper Bay by using field observations and models of nutrient pools and fluxes. This study focuses on the historically important Susquehanna Flats SAV bed, which has experienced a dramatic, but unexplained, resurgence. We will use detailed nutrient budget analysis (across bed) to quantify effects of dissolved and particulate N and P uptake and trapping and to explain how SAV resurgence is related to recent declines in nutrient inputs and levels. We hypothesize that initial SAV recovery was stimulated by reduced nutrient loading but reinforced by bed feedbacks (sequestering nutrients). Data from field studies will be used to refine and apply an SAV ecosystem model to address how nutrient-climate interactions affect SAV bed recovery and to identify strategies for SAV restoration that exploit these feedback processes. METHODOLOGY Along a transect from outside the SAV bed to its center, we will collect water quality data at high frequency in spring and summer using automated water samplers (ISCO) and data sondes (YSI 6600). Samples will also be collected seasonally for nutrient levels in plant species tissues, pore-waters and suspended plus bottom sediments, along with rates of sediment burial and denitrification. Seasonal and annual nutrient (N & P) input-output budgets will be constructed (with error estimates) for transect regions and for the whole bed. These data will be combined with statistical analyses of water quality, plant and climate variables (from a related ongoing study) to interpret trends and controls on historical changes in the bed. All field data will also be used in refining and applying an existing SAV simulation model to interpret mechanistic controls on historical patterns. RATIONALE Restoration of SAV beds in Chesapeake Bay requires improved quantitative understanding and modeling of factors controlling observed trends. We proposed to distinguish relative contributions of Bay-scale changes in N & P inputs and bed-scale feedback processes in SAV trends. Although current models fail to simulate observed SAV recovery, results of this study will produce refined SAV model formulations that will enhance simulation performance and thus effectiveness of strategies for water quality management and SAV restoration.
This section describes how this project has advanced scientific knowledge and/or made a difference in the lives of coastal residents, communities, and environments. Maryland Sea Grant has reported these details to the National Oceanic and Atmospheric Administration (NOAA), one of our funding sponsors.
RELEVANCE: Effective management of submerged aquatic vegetation (SAV) beds in Chesapeake Bay requires improved understanding of how water quality, climate, and other factors influence the beds' growth and survival. Early SAV simulation models have failed to reproduce observed trends of SAV recovery. One research project by this investigator was undertaken to help refine SAV simulation models and improve site selection for restoration. Another research project by the same investigator focused on the Susquehanna Flats' SAV bed in the upper Chesapeake Bay. The bed experienced a dramatic, but unexplained, resurgence and then was disrupted by back-to-back tropical storms in 2011. Restoration of SAV is important for improving water quality and fish habitat in the Chesapeake Bay.
RESPONSE: The principal investigator on this project is W. Michael Kemp, University of Maryland Center for Environmental Science, Horn Point Laboratory. The researchers have conducted aerial photo surveys and have collected samples for water quality and plant biomass analyses during several field visits. They also measured temperature, salinity, oxygen, chlorophyll, and turbidity.
RESULTS: Strong feedback processes are likely important in hastening recovery, according to time-series data about water quality that were collected inside and outside SAV beds. The growth of SAV improved water clarity within SAV beds, which in turn facilitated the further growth of SAV. This growth was influenced by high river discharge from the Susquehanna River caused by storms; the sediment-laden discharges tended to degrade water quality, but only extreme storms tended to overwhelm the feedback processes. During drought years, river flow declined; water quality improved, providing favorable growth conditions; and the bed expanded.
Researchers have met with colleagues from numerous agencies who have expressed interest in the study's implications for improving water quality models. A better understanding of the processes affecting the bed's growth may influence computation of TMDL (total maximum daily load) allocations, which restrict the loads of nutrients and sediments that may be released into the Bay. The researchers also presented their results to teachers and high-school and college biology students.
Gurbisz, C; Kemp, WM; Sanford, LP; Orth, RJ. 2016. Mechanisms of Storm-Related Loss and Resilience in a Large Submersed Plant Bed. Estuaries and Coasts39(4):951 -966. doi:10.1007/s12237-016-0074-4. UM-SG-RS-2016-16.