Did the salinity in the estuary change due to a hurricane ?

1. Bayesian Belief Networks and Ecosystem Management Predicting ecosystem responses due to coastal hazards is very important from social, economic, and ecological perspectives. For this project, we are interested in ecosystem responses due to coastal hazards such as estuarine inundation due to hurricane surge and precipitation, and how managers deal with, mitigate, and minimize negative ecosystem responses due to coastal hazards. Weeks Bay, Alabama was chosen as the test case for this part of the study. Weeks Bay is a partially mixed, tidal sub-estuary on the eastern side of Mobile Bay and is part of the Weeks Bay National Estuarine Research Reserve (WBNERR). The estuary has been monitored since the formation of the WBNERR in 1986. Task Objective: Provide a tool that enables resource managers to assess potential ecosystem effects from flooding. Bayesian belief networks (BBNs) are statistical models that represent the probabilistic relationship between random variables and their conditional dependencies based on expert opinion. Given a variable, BBNs compute the probability that a condition that occurred is responsible for the variable change. For the Weeks Bay case, the dependent variable may be “did the salinity in the estuary change due to a hurricane surge?” and the conditional variable might be “did the number of species X in the area change after a hurricane?”. These options can be put into a probability table that can be used to easily view the probability that any combination of these options can occur. Please note that the values shown are not the actual probabilities for this set of variables. They are present for the purpose of demonstrating the procedure. Did the salinity in the estuary change due to a hurricane? • The BBN for Weeks Bay is developed by: • Use hydrodynamic models to determine flooding levels and salinity levels in Weeks Bay due to storms. • Develop questions to present to managers. Some examples are: • What information do you need to determine how the flood level will affect different parts of the ecosystem? • What is the best way data can be presented in order to be useful for your purposes? • What information (inundation levels, surge data, flooding length, salinity visuals, etc.) can we provide you with that will be useful in managing the area? • What information can we provide you with before a storm to minimize adverse impacts to the ecosystem? • What information can we provide you with to estimate the ecosystem recovery time and to formulate a feasible ecosystem recovery plan? • Present flood and salinity level ranges to ecosystem experts to elicit a Bayesian estimate of ecosystem effects important to resource managers. • After the management questions are answered, the answers are recorded and input into the Sulis framework so that the inundation and other useful information (from steps 1 & 3) can be calculated for hypothetical or actual hurricanes and sent to the managers targeted in step 2. These events are related because a change in salinity is likely to change the number of x-species fish are in the estuary as each species may thrive within certain salinity ranges. The probability that the number of x-specieshas increased, decreased, or remained the same due to a change in salinity is often not easily quantified. However, the direction and approximate magnitude of change (fuzzy values) can usually be estimated by subject matter experts. A number of expert fuzzy estimates can then be translated into fuzzy logic probabilities that predict post-hurricane species X populations using BBNs if the salinity change is measured or modeled. A highly simplified example is shown below Did the number of species X in the estuary change after a hurricane? Jennifer Sloan Ziegler jls523@gri.msstate.edu Mississippi State University Strategy Area 2