Nathaniel Plant, Ph.D.
I am the Center Director for the Saint Petersburg Coastal and Marine Science Center, where I support scientists working on coastal research topics such as coastal hazards due to storms and sea-level rise; sediment availability and distribution; and response of coastal communities, wetlands, corals, and microbial ecosystems to extreme events and persistent changes to our coastal environment.
I have served in this capacity since October 2018, initially in an acting capacity and permanently since April 2019.
Prior to becoming Center Director, my role with the USGS was as an oceanographer. Past research projects included scientific applications to coastal management, such as assessing storm-induced and long-term coastal erosion or identification of future nesting habitat for endangered shore bird species. Throughout my research career, I have lived in a range of coastal communities in California, Mississippi, and Florida, as well as the Netherlands, and the Washington, DC area. I received my Ph.D. in Marine Geology from Oregon State University’s Oceanography program in 1998.
Science and Products
National Assessment of Coastal Change Hazards
Barrier Island Evolution
Empowering decision-makers: A dynamic web interface for running Bayesian networks
Exploring the USGS Science Data Life Cycle in the Cloud
Evaluating Sea-level Rise Impacts in the Northeastern U.S.
SERAP: Assessment of Shoreline Retreat in Response to Sea Level Rise
Southeast Regional Assessment Project (SERAP): Assessing Global Change Impacts on Natural and Human Systems in the Southeast
How will Florida’s Biodiversity Respond to Climate Change?
Coastal Topography-Assateague Island, Maryland and Virginia, Post-Hurricane Joaquin, 26 November 2015
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Gulf of Mexico Update
EAARL Coastal Topography-Chandeleur Islands, Louisiana, 12-13 February 2011: Seamless (Bare Earth and Submerged)
Cape Canaveral, Florida 2010 Single-beam Bathymetry Data
Coastal Landscape Response to Sea-Level Rise Assessment for the Northeastern United States Data Release
Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat
Combining numerical and statistical models to predict storm-induced dune erosion
Forecasts of coastal change hazards
iCoast – Did the Coast Change?: Storm-impact model verification using citizen scientists
Surrogate model development for coastal dune erosion under storm conditions
Daily to decadal variability of beach morphology at NASA-Kennedy Space Center: Storm influences across timescales
Relationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model
A review of machine learning applications to coastal sediment transport and morphodynamics
Field observations of alongshore runup variability under dissipative conditions in presence of a shoreline sandwave
Science for a risky world—A U.S. Geological Survey plan for risk research and applications
Dynamic modeling of barrier island response to hurricane storm surge under future sea level rise
Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry
Science and Products
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National Assessment of Coastal Change Hazards
Research to identify areas that are most vulnerable to coastal change hazards including beach and dune erosion, long-term shoreline change, and sea-level rise.ByNatural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Pacific Coastal and Marine Science Center, St. Petersburg Coastal and Marine Science Center, Woods Hole Coastal and Marine Science Center, Gulf of Mexico, Hurricane Harvey, Hurricane Irma, Hurricane Jose, Hurricane Maria, Hurricane Matthew, Hurricane SandyBarrier Island Evolution
The Barrier Island Evolution Project addresses a research gap between the short time scale of individual storms (hours to days) and the longer time scales associated with the historic and geologic evolution of the coastal system (decades to millennia).Empowering decision-makers: A dynamic web interface for running Bayesian networks
U.S. Geological Survey (USGS) scientists are at the forefront of research that is critical for decision-making, particularly through the development of models (Bayesian networks, or BNs) that forecast coastal change. The utility of these tools outside the scientific community has been limited because they rely on expensive, technical software and a moderate understanding of statistical analyses. WExploring the USGS Science Data Life Cycle in the Cloud
Executive Summary Traditionally in the USGS, data is processed and analyzed on local researcher computers, then moved to centralized, remote computers for preservation and publishing (ScienceBase, Pubs Warehouse). This approach requires each researcher to have the necessary hardware and software for processing and analysis, and also to bring all external data required for the workflow over the intEvaluating Sea-level Rise Impacts in the Northeastern U.S.
In 2010, 39 percent of the U.S.population lived near the coast. This population is expected to increase by 8 percent from 2010 to 2020. Coastal regions are also home to species and habitats that provide critical services to humans, such as wetlands that buffer coasts from storms. Therefore, sea-level rise and the associated changes in coastlines challenge both human communities and ecosystems. UndSERAP: Assessment of Shoreline Retreat in Response to Sea Level Rise
The broad range of complex factors influencing coastal systems contribute to large uncertainties in predicting long-term sea level rise impacts. Researchers demonstrated the capabilities of a Bayesian network (BN) to predict long-term shoreline change associated with sea level rise and make quantitative assessments for predicting uncertainty. A BN was used to define relationships between driving fSoutheast Regional Assessment Project (SERAP): Assessing Global Change Impacts on Natural and Human Systems in the Southeast
The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conservHow will Florida’s Biodiversity Respond to Climate Change?
Florida is home to 50 endangered species, 23 National Wildlife Refuges, 9 national parks, and 119 state parks. Straddling both temperate and sub-tropical zones, the state is also unique in that it is a long and narrow peninsula, surrounded on three sides by warm water, creating a dynamic environment. The impacts of climate change, such as sea-level rise and severe storms, threaten the state’s uniq - Data
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Coastal Topography-Assateague Island, Maryland and Virginia, Post-Hurricane Joaquin, 26 November 2015
Lidar-derived bare-earth topography Digital Elevation Model (DEM) mosaic and classified point-cloud datasets were produced from remotely sensed, geographically referenced elevation measurements collected post-Hurricane Joaquin on November 26, 2015.National Assessment of Hurricane-Induced Coastal Erosion Hazards: Gulf of Mexico Update
These data sets contain information on the probabilities of hurricane-induced erosion (collision, inundation and overwash) for each 1-km section of the Gulf of Mexico coast for category 1-5 hurricanes. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct lEAARL Coastal Topography-Chandeleur Islands, Louisiana, 12-13 February 2011: Seamless (Bare Earth and Submerged)
This XYZ dataset, prepared by the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center, provides lidar-derived seamless (bare earth and submerged) topography for the Chandeleur Islands in Louisiana. Elevation measurements were acquired by the first-generation Experimental Advanced Airborne Research Lidar (EAARL) on February 12 and 13, 2011. The data were collected as part of a sCape Canaveral, Florida 2010 Single-beam Bathymetry Data
Single-beam bathymetric surveys were conducted on July 27-29, 2010 along 37 cross-shore transects offshore from Cape Canaveral, Fla. The transects were spaced 500 m apart in the alongshore direction and each was approximately 5 km long in the cross-shore.Coastal Landscape Response to Sea-Level Rise Assessment for the Northeastern United States Data Release
As part of the USGS Sea-Level Rise Hazards and Decision-Support project, this assessment seeks to predict the response to sea-level rise across the coastal landscape under a range of future scenarios by evaluating the likelihood of inundation as well as dynamic coastal change. The research is being conducted in conjunction with resource managers and decision makers from federal and state agencies, - Multimedia
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Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat
Coastal storms have consequences for human lives and infrastructure but also create important early successional habitats for myriad species. For example, storm-induced overwash creates nesting habitat for shorebirds like piping plovers (Charadrius melodus). We examined how piping plover habitat extent and location changed on barrier islands in New York, New Jersey, and Virginia after Hurricane SaAuthorsSara L. Zeigler, Benjamin T. Gutierrez, Emily J. Sturdivant, Daniel H. Catlin, James D. Fraser, A. Hecht, Sarah M. Karpanty, Nathaniel G. Plant, E. Robert ThielerCombining numerical and statistical models to predict storm-induced dune erosion
Dune erosion is an important aspect to consider when assessing coastal flood risk, as dune elevation loss makes the protected areas more susceptible to flooding. However, most advanced dune erosion numerical models are computationally expensive, which hinders their application in early-warning systems. Based on a combination of probabilistic and process-based numerical modeling, we develop an effiAuthorsVictor Malagon-Santos, Thomas Wahl, Joseph W Long, Davina Passeri, Nathaniel G. PlantForecasts of coastal change hazards
Model predictions of severe storm impacts provide coastal residents, emergency managers, and partner organizations valuable predictive information for planning and response to extreme storm events. The foundation of this work is a USGS-developed numerical model to forecast storm-induced coastal water levels and expected coastal change, including dune erosion, overwash, and inundation. The model isAuthorsKara S. Doran, Hilary F. Stockdon, Joseph Long, Nathaniel G. PlantiCoast – Did the Coast Change?: Storm-impact model verification using citizen scientists
The USGS provides model predictions of severe storm impacts prior to landfall based on pre-storm morphology and predicted total water levels, including waves and surge. Presented in near real time on the USGS Coastal Change Hazard Portal, they provide coastal residents, scientists, and emergency managers valuable coastal response information. iCoast – Did the Coast Change?, an online tool for compAuthorsKaren L. M. Morgan, Nathaniel G. Plant, Hilary F. Stockdon, Richard J. SnellSurrogate model development for coastal dune erosion under storm conditions
Early coastal dune erosion predictions are essential to avoid potential flood consequences but most dune erosion numerical models are computationally expensive, hence their application in Early Warning Systems is limited. Here, based on a combination of optimally sampled synthetic sea storms with a calibrated and validated XBeach model, we develop a surrogate model capable of producing fast and acAuthorsVictor Malagon-Santos, Thomas Wahl, Joseph W Long, Davina Passeri, Nathaniel G. PlantDaily to decadal variability of beach morphology at NASA-Kennedy Space Center: Storm influences across timescales
Shoreline variability over timescales ranging from days to decades is examined at NASA-Kennedy Space Center on the Atlantic coast of Florida. Three sources of shoreline position data are utilized to complete this analysis: hourly video-image observations, monthly Real Time Kinematic GPS observations, and historical aerial imagery dating back to 1943. We find that shoreline positions tend to responAuthorsMatthew P. Conlin, Peter N. Adams, Nathaniel Plant, John M. Jaeger, Richard MackenzieRelationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model
Understanding land loss or resilience in response to sea-level rise (SLR) requires spatially extensive and continuous datasets to capture landscape variability. We investigate sensitivity and skill of a model that predicts dynamic response likelihood to SLR across the northeastern U.S. by exploring several data inputs and outcomes. Using elevation and land cover datasets, we determine where datAuthorsErika Lentz, Nathaniel G. Plant, E. Robert ThielerA review of machine learning applications to coastal sediment transport and morphodynamics
A range of computer science methods under the heading of machine learning (ML) enables the extraction of insight and quantitative relationships from multidimensional datasets. Here, we review some common ML methods and their application to studies of coastal morphodynamics and sediment transport. We examine aspects of ‘what’ and ‘why’ ML methods contribute, such as ‘what’ science problems ML toolsAuthorsEvan Goldstein, Giovanni Coco, Nathaniel G. PlantField observations of alongshore runup variability under dissipative conditions in presence of a shoreline sandwave
Video measurements of runup were collected at low tide along several profiles covering an alongshore distance of 500 m. The morphology displayed a complex shape with a shoreline sandwave in the lower beach face of about 250 m long mirrored in the inner sandbar. Wave conditions were stationary and moderate (offshore height of 2 m and peak period of nearly 13 s) but yet dissipative. Runup energy wasAuthorsNadia Senechal, Giovanni Coco, Nathaniel G. Plant, Karin R. Bryan, Jennifer Brown, Jamie MacMahanScience for a risky world—A U.S. Geological Survey plan for risk research and applications
Executive SummaryNatural hazards—including earthquakes, tsunamis, volcanic eruptions, landslides, hurricanes, droughts, floods, wildfires, geomagnetic storms, and pandemics—can wreak havoc on human communities, the economy, and natural resources for years following an initial event. Hazards can claim lives and cause billions of dollars in damage to homes and infrastructure as well as lost or comprAuthorsK. A. Ludwig, David W. Ramsey, Nathan J. Wood, A.B. Pennaz, Jonathan W. Godt, Nathaniel G. Plant, Nicolas Luco, Todd A. Koenig, Kenneth W. Hudnut, Donyelle K. Davis, Patricia R. BrightDynamic modeling of barrier island response to hurricane storm surge under future sea level rise
Sea level rise (SLR) has the potential to exacerbate the impacts of extreme storm events on the coastal landscape. This study examines the coupled interactions of SLR on storm-driven hydrodynamics and barrier island morphology. A numerical model is used to simulate the hydrodynamic and morphodynamic impacts of two Gulf of Mexico hurricanes under present-day and future sea levels. SLR increased surAuthorsDavina Passeri, Matthew V. Bilskie, Nathaniel G. Plant, Joseph W. Long, Scott C. HagenRapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry
Timely assessment of coastal landforms and structures after storms is important for evaluating storm impacts, aiding emergency response and restoration, and initializing and assessing morphological models. Four-dimensional multiview photogrammetry, also known as structure from motion (4D SfM), provides a method for generating three-dimensional reconstructions of landscapes at two times (before andAuthorsChristopher R. Sherwood, Jonathan Warrick, Andrew D. Hill, Andrew C. Ritchie, Brian D. Andrews, Nathaniel G. Plant - Software
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