Assessing the vulnerability of the coastal zone to sea-level rise (SLR) requires integrating a variety of physical, biological, and social factors. These include landscape and habitat changes, as well as the ability of society and its institutions to adapt. For example, the range of physical and biological responses associated with SLR is poorly understood at some of the critical time and space scales required for decision making. Although the general nature of the changes that can occur on ocean coasts in response to SLR are widely recognized, predicting specific changes at a particular point in time is difficult. Similarly, the cumulative impacts of physical and biological change on the quantity and quality of coastal habitats are not well understood. Potential societal responses to SLR, and particularly those associated with natural resource management, are also uncertain. Limitations in the ability to quantitatively predict outcomes at local, regional, and national scales affect whether, when, and how some decisions will be made. Thus, coastal managers require improved tools to understand and anticipate the magnitude and likelihood of future SLR impacts, as well as to evaluate the consequences of different actions (or inaction).
This Mendenhall Research Opportunity will allow a strong scientist to improve the capability to evaluate the effect of coastal change on piping plover habitat availability and utilization, through field data collection, and testing and application of models. The barrier beaches that comprise the piping plover’s breeding, migration, and wintering habitat are dynamic systems that respond to fluctuations in sea level by changing their morphology and distribution of landscape elements (e.g., beaches, dunes, tidal flats). Piping plovers are uniquely suited as an indicator species for understanding SLR impacts to beach habitats. Plovers have closely-defined habitat tolerances. Both the habitat and the birds respond rapidly to coastal processes such as overwash, inlet formation, and island migration that are sensitive to changes in the rate of sea-level rise.
Research under this opportunity is expected to focus on the integration of plover ecology with coastal landscape evolution. Although the research focus is to be on the effects on piping plovers, results are expected to inform management of other sensitive beach-strand species, including (but not limited to) least terns, American oystercatchers, Wilson’s plovers, and seabeach amaranth (a federally threatened plant species). Thus, postdoctoral research under this Mendenhall project can provide the scientific underpinning for a broadly-applicable strategic habitat conservation approach.
The opportunity will be supported by a focused research effort that will consider the past and future response of the U.S. Atlantic coast to sea-level rise. This location has advantages including extensive historical data sets, an ongoing research effort, and explicit interest and collaboration with managers and landowners. In addition to developing new data sets through field and lab work, the successful candidate is expected to use existing and updated data sets to test and train predictive models, leading to improved scientific understanding of the impacts of climate change and sea-level rise on plover habitat availability and utilization. Currently, data-driven predictive models including linear regression and Bayesian networks are being applied to this problem. The Bayesian network approach has had very broad application to integrate ecologic, morphologic, and hydrologic processes (e.g., Gutierrez et al., 2011; Fienen et al., 2013; Masterson et al., 2013; Gieder et al., 2014). Therefore, some understanding of Bayesian network methods (or willingness to learn) is desirable. Competing hypotheses regarding the relationships between forcing, the responses, and their interrelationships need to be evaluated and their uncertainties compared.The successful candidate will work closely with scientists at the USGS as well as at Virginia Tech, and will have an opportunity to interact with coastal managers in order to develop specific decision guidance by evaluating the risk of adverse conditions and/or predicting the probability of future occurrence of various coastal response scenarios. Because of the explicit multi-disciplinary objective of this research, strong candidates may have a background in the fields of biology, ecology, geography, or geology. It is expected that they will have skills in statistical data analysis and quantitative modeling.
Fienen, M. N., J. P. Masterson, N. G. Plant, B. T. Gutierrez, and E. R. Thieler (2013), Bridging groundwater models and decision support with a Bayesian network, Water Resources Research, 49(10), 6459-6473, doi 10.1002/wrcr.20496.
Gieder, K. D., S. M. Karpanty, J. D. Fraser, D. H. Catlin, B. T. Gutierrez, N. G. Plant, A. M. Turecek, and E. R. Thieler (2014), A Bayesian network approach to predicting nest presence of the federally-threatened piping plover (Charadrius melodus) using barrier island features, Ecological Modelling, 276, 38-50, doi 10.1016/j.ecolmodel.2014.01.005.
Gutierrez, B. T., N. G. Plant, and E. R. Thieler (2011), A Bayesian network to predict coastal vulnerability to sea level rise, Journal of Geophysical Research: Earth Surface, 116(F2), F02009, doi 10.1029/2010JF001891.
Masterson, J. P., M. N. Fienen, E. R. Thieler, D. B. Gesch, B. T. Gutierrez, and N. G. Plant (2013), Effects of sea-level rise on barrier island groundwater system dynamics – ecohydrological implications, Ecohydrology, doi 10.1002/eco.1442.
Proposed Duty Station: Blacksburg, VA; Woods Hole, MA
Areas of Ph.D.: Ecology, biology, geography, geology, statistics (candidates holding a Ph.D. in other disciplines but with knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet one of the following qualifications: Research Biologist, Research Ecologist, Research Geographer, Research Geologist, Research Oceanographer. (This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant’s background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)
Research Advisors: Rob Thieler, 508-457-2350, email@example.com; Nathaniel Plant, 727-502-8072, firstname.lastname@example.org; Sarah Karpanty (Virginia Polytechnic Institute and State University), 540-231-4586, email@example.com.
Human Resources Office Contact: Junell Norris, (303) 236-9557, firstname.lastname@example.org.
|Summary of Opportunities|