Ben Gutierrez is a Research Geologist with the Coastal Change Project at the Woods Hole Coastal and Marine Science Center
Science and Products
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...
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...
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...
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
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
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
Filter Total Items: 21
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
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
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.
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
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
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
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
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
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
A Bayesian network to predict coastal vulnerability to sea level rise
Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term sho
Long-term oceanographic observations in Massachusetts Bay, 1989-2006
This data report presents long-term oceanographic observations made in western Massachusetts Bay at long-term site A (LT-A) (42 deg 22.6' N., 70 deg 47.0' W.; nominal water depth 32 meters) from December 1989 through February 2006 and long-term site B (LT-B) (42 deg 9.8' N., 70 deg 38.4' W.; nominal water depth 22 meters) from October 1997 through February 2004 (fig. 1). The observations were coll
Science and Products
- Science
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...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...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...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 - Data
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-leveBarrier 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 - Publications
Filter Total Items: 21
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 conflictinUsing 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 SaSmartphone 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.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 uncUsing 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 erosionA 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 chEffects 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 suiBridging 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 makeA 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 BayesA Bayesian network to predict coastal vulnerability to sea level rise
Sea level rise during the 21st century will have a wide range of effects on coastal environments, human development, and infrastructure in coastal areas. The broad range of complex factors influencing coastal systems contributes to large uncertainties in predicting long-term sea level rise impacts. Here we explore and demonstrate the capabilities of a Bayesian network (BN) to predict long-term shoLong-term oceanographic observations in Massachusetts Bay, 1989-2006
This data report presents long-term oceanographic observations made in western Massachusetts Bay at long-term site A (LT-A) (42 deg 22.6' N., 70 deg 47.0' W.; nominal water depth 32 meters) from December 1989 through February 2006 and long-term site B (LT-B) (42 deg 9.8' N., 70 deg 38.4' W.; nominal water depth 22 meters) from October 1997 through February 2004 (fig. 1). The observations were coll - News