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Ben Gutierrez, PhD

Ben Gutierrez is a Research Geologist with the Coastal Change Project at the Woods Hole Coastal and Marine Science Center

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Coastal Change Hazards Program Triangle Logo

Coastal Change Hazards

Natural processes such as waves, tides, and weather, continually change coastal landscapes. The integrity of coastal homes, businesses, and infrastructure can be threatened by hazards associated with event-driven changes, such as extreme storms and their impacts on beach and dune erosion, or longer-term, cumulative changes associated with coastal and marine processes, such as sea-level rise...
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Natural 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
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Coastal Change Hazards

Natural processes such as waves, tides, and weather, continually change coastal landscapes. The integrity of coastal homes, businesses, and infrastructure can be threatened by hazards associated with event-driven changes, such as extreme storms and their impacts on beach and dune erosion, or longer-term, cumulative changes associated with coastal and marine processes, such as sea-level rise...
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Photograph of storm overwash, Surf Drive Beach, Falmouth, MA

Sea-Level Rise Hazards and Decision Support

The Sea-Level Rise Hazards and Decision-Support project assesses present and future coastal vulnerability to provide actionable information for management of our Nation’s coasts. Through multidisciplinary research and collaborative partnerships with decision-makers, physical, biological, and social factors that describe landscape and habitat changes are incorporated in a probabilistic modeling...
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Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center
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Sea-Level Rise Hazards and Decision Support

The Sea-Level Rise Hazards and Decision-Support project assesses present and future coastal vulnerability to provide actionable information for management of our Nation’s coasts. Through multidisciplinary research and collaborative partnerships with decision-makers, physical, biological, and social factors that describe landscape and habitat changes are incorporated in a probabilistic modeling...
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Adult and juvenile Piping Plovers (Kaiti Titherington/USFWS)

Beach-dependent Shorebirds

Policy-makers, individuals from government agencies, and natural resource managers are under increasing pressure to manage changing coastal areas to meet social, economic, and natural resource demands, particularly under a regime of sea-level rise. Scientific knowledge of coastal processes and habitat-use can support decision-makers as they balance these often-conflicting human and ecological...
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Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center
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Beach-dependent Shorebirds

Policy-makers, individuals from government agencies, and natural resource managers are under increasing pressure to manage changing coastal areas to meet social, economic, and natural resource demands, particularly under a regime of sea-level rise. Scientific knowledge of coastal processes and habitat-use can support decision-makers as they balance these often-conflicting human and ecological...
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USGS science for a changing world logo

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. W
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Community for Data Integration (CDI)
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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. W
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Barrier island geomorphology and shorebird habitat metrics: 16 sites on the U.S. Atlantic Coast, 2013-2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-leve
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Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center

Barrier island geomorphology and shorebird habitat metrics: Four sites in New York, New Jersey, and Virginia, 2010-2014

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-leve
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Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center
Filter Total Items: 24

Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability

Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management a
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Coastal and Marine Hazards and Resources Program, St. Petersburg Coastal and Marine Science Center, Woods Hole Coastal and Marine Science Center

Predicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: Implications for people and plovers

Forecasting biogeomorphological conditions for barrier islands is critical for informing sea-level rise (SLR) planning, including management of coastal development and ecosystems. We combined five probabilistic models to predict SLR-driven changes and their implications on Fire Island, New York, by 2050. We predicted barrier island biogeomorphological conditions, dynamic landcover response, piping
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St. Petersburg Coastal and Marine Science Center, Woods Hole Coastal and Marine Science Center

Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast

Habitat studies that encompass a large portion of a species’ geographic distribution can explain characteristics that are either consistent or variable, further informing inference from more localized studies and improving management successes throughout the range. We identified landscape characteristics at Piping Plover nests at 21 sites distributed from Massachusetts to North Carolina and compar
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St. Petersburg Coastal and Marine Science Center

Evaluating barrier island characteristics and piping plover (Charadrius melodus) habitat availability along the U.S. Atlantic Coast—Geospatial approaches and methodology

Policy makers, individuals from government agencies, and natural resource managers face increasing demands to manage coastal areas in a way that meets economic, social, and ecological needs as sea levels rise. Scientific knowledge of how coastal processes drive beach and barrier island changes and how those changes affect habitat use can support decision makers as they balance sometimes conflictin
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Coastal and Marine Hazards and Resources Program, Woods Hole Coastal and Marine Science Center

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 Sa
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Natural Hazards Mission Area, Coastal and Marine Hazards and Resources Program, St. Petersburg Coastal and Marine Science Center, Woods Hole Coastal and Marine Science Center

Smartphone technologies and Bayesian networks to assess shorebird habitat selection

Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies.
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Woods Hole Coastal and Marine Science Center

Using a Bayesian network to predict barrier island geomorphologic characteristics

Quantifying geomorphic variability of coastal environments is important for understanding and describing the vulnerability of coastal topography, infrastructure, and ecosystems to future storms and sea level rise. Here we use a Bayesian network (BN) to test the importance of multiple interactions between barrier island geomorphic variables. This approach models complex interactions and handles unc
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Woods Hole Coastal and Marine Science Center

Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States

Sea-level rise is an ongoing phenomenon that is expected to continue and is projected to have a wide range of effects on coastal environments and infrastructure during the 21st century and beyond. Consequently, there is a need to assemble relevant datasets and to develop modeling or other analytical approaches to evaluate the likelihood of particular sea-level rise impacts, such as coastal erosion
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Coastal and Marine Hazards and Resources Program, St. Petersburg Coastal and Marine Science Center

A Bayesian network approach to predicting nest presence of thefederally-threatened piping plover (Charadrius melodus) using barrier island features

Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat ch
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Woods Hole Coastal and Marine Science Center

Effects of sea-level rise on barrier island groundwater system dynamics: ecohydrological implications

We used a numerical model to investigate how a barrier island groundwater system responds to increases of up to 60 cm in sea level. We found that a sea-level rise of 20 cm leads to substantial changes in the depth of the water table and the extent and depth of saltwater intrusion, which are key determinants in the establishment, distribution and succession of vegetation assemblages and habitat sui
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Water Resources Mission Area, Earth Resources Observation and Science Center, Earth Resources Observation and Science (EROS) Center , New England Water Science Center, Coastal Changes and Impacts

Bridging groundwater models and decision support with a Bayesian network

Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make
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Water Resources Mission Area, New England Water Science Center, Woods Hole Coastal and Marine Science Center, St. Petersburg Coastal and Marine Science Center, Upper Midwest Environmental Sciences Center, Upper Midwest Water Science Center

A Bayesian network to predict vulnerability to sea-level rise: data report

During the 21st century, sea-level rise is projected to have a wide range of effects on coastal environments, development, and infrastructure. Consequently, there has been an increased focus on developing modeling or other analytical approaches to evaluate potential impacts to inform coastal management. This report provides the data that were used to develop and evaluate the performance of a Bayes
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Woods Hole Coastal and Marine Science Center

LinkedBNs_4Habitat - Matlab files to link Bayesian networks to generate habitat predictions

Matlab m-files that were used to generate performance tests and hindcasts for geomorphologic characteristics and piping plover habitat probabilities for Fire Island New York
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Woods Hole Coastal and Marine Science Center
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Optimizing the Intern Experience: A Woods Hole Workshop

Woods Hole Coastal and Marine Science Center staff, including Center Chief, Rob Thieler, and Woods Hole Diversity Committee Member and Research...

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