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At least 109 records · Page 6Linked to original sources
USGS1973

Bathymetry of the continental margin off Liberia, West Africa

A bathymetric map based on new data allows examination of geomorphic features on the narrow continental margin off Liberia. The continental shelf in this region is relatively flat and featureless. The northwestern part of the continental slope, off Monrovia and Cape Mount, shows complex slump features and two submarine valleys. The central part of the slope is smoother, apparently as a result of progradation. The southeastern part of the slope, near Cape Palmas, is crossed oblique to the shoreline by a structural valley that has been modified by large slumps or landslides. This valley may be the termination, at the continental margin, of an oceanic fracture zone. The major slumplike features of the Liberian continental margin appear to be surface manifestations of deep faulting which has been partially masked by sedimentation.

Journal of Research of the U.S. Geological Survey↗
USGS2016

Using smooth sheets to describe groundfish habitat in Alaskan waters, with specific application to two flatfishes

In this analysis we demonstrate how preferred fish habitat can be predicted and mapped for juveniles of two Alaskan groundfish species – Pacific halibut ( Hippoglossus stenolepis ) and flathead sole ( Hippoglossoides elassodon ) – at five sites (Kiliuda Bay, Izhut Bay, Port Dick, Aialik Bay, and the Barren Islands) in the central Gulf of Alaska. The method involves using geographic information system (GIS) software to extract appropriate information from National Ocean Service (NOS) smooth sheets that are available from NGDC (the National Geophysical Data Center). These smooth sheets are highly detailed charts that include more soundings, substrates, shoreline and feature information than the more commonly-known navigational charts. By bringing the information from smooth sheets into a GIS, a variety of surfaces, such as depth, slope, rugosity and mean grain size were interpolated into raster surfaces. Other measurements such as site openness, shoreline length, proportion of bay that is near shore, areas of rocky reefs and kelp beds, water volumes, surface areas and vertical cross-sections were also made in order to quantify differences between the study sites. Proper GIS processing also allows linking the smooth sheets to other data sets, such as orthographic satellite photographs, topographic maps and precipitation estimates from which watersheds and runoff can be derived. This same methodology can be applied to larger areas, taking advantage of these free data sets to describe predicted groundfish essential fish habitat (EFH) in Alaskan waters.

Alaska↗
USGS2013

Modeling for the SAFRR Tsunami Scenario-generation, propagation, inundation, and currents in ports and harbors: Chapter D in The SAFRR (Science Application for Risk Reduction) Tsunami Scenario

This U.S. Geological Survey (USGS) Open-File report presents a compilation of tsunami modeling studies for the Science Application for Risk Reduction (SAFRR) tsunami scenario. These modeling studies are based on an earthquake source specified by the SAFRR tsunami source working group (Kirby and others, 2013). The modeling studies in this report are organized into three groups. The first group relates to tsunami generation. The effects that source discretization and horizontal displacement have on tsunami initial conditions are examined in section 1 (Whitmore and others). In section 2 (Ryan and others), dynamic earthquake rupture models are explored in modeling tsunami generation. These models calculate slip distribution and vertical displacement of the seafloor as a result of realistic fault friction, physical properties of rocks surrounding the fault, and dynamic stresses resolved on the fault. The second group of papers relates to tsunami propagation and inundation modeling. Section 3 (Thio) presents a modeling study for the entire California coast that includes runup and inundation modeling where there is significant exposure and estimates of maximum velocity and momentum flux at the shoreline. In section 4 (Borrero and others), modeling of tsunami propagation and high-resolution inundation of critical locations in southern California is performed using the National Oceanic and Atmospheric Administration’s (NOAA) Method of Splitting Tsunami (MOST) model and NOAA’s Community Model Interface for Tsunamis (ComMIT) modeling tool. Adjustments to the inundation line owing to fine-scale structures such as levees are described in section 5 (Wilson). The third group of papers relates to modeling of hydrodynamics in ports and harbors. Section 6 (Nicolsky and Suleimani) presents results of the model used at the Alaska Earthquake Information Center for the Ports of Los Angeles and Long Beach, as well as synthetic time series of the modeled tsunami for other selected locales in southern California. Importantly, section 6 provides a comparison of the effect of including horizontal displacements at the source described in section 1 and differences in bottom friction on wave heights and inundation in the Ports of Los Angeles and Long Beach. Modeling described in section 7 (Lynett and Son) uses a higher order physical model to determine variations of currents during the tsunami and complex flow structures such as jets and eddies. Section 7 also uses sediment transport models to estimate scour and deposition of sediment in ports and harbors—a significant effect that was observed in southern California following the 2011 Tohoku tsunami. Together, all of the sections in this report form the basis for damage, impact, and emergency preparedness aspects of the SAFRR tsunami scenario. Three sections of this report independently calculate wave height and inundation results using the source specified by Kirby and others (2013). Refer to figure 29 in section 3, figure 52 in section 4, and figure 62 in section 6. All of these results are relative to a mean high water (MHW) vertical datum. Slight differences in the results are observed in East Basin of the Port of Los Angeles, Alamitos Bay, and the Seal Beach National Wildlife Refuge. However, given that these three modeling efforts involved different implementations of the source, different numerical wave propagation and runup models, and slight differences in the digital elevation models (DEMs), the similarity among the results is remarkable.

California↗
USGS2024

Scalable, data-assimilated models predict large-scale shoreline response to waves and sea-level rise

Coastal change is a complex combination of multi-scale processes (e.g., wave-driven cross-shore and longshore transport; dune, bluff, and cliff erosion; overwash; fluvial and inlet sediment supply; and sea-level-driven recession). Historical sea-level-driven coastal recession on open ocean coasts is often outpaced by wave-driven change. However, future sea-level-driven coastal recession is expected to increase significantly in tandem with accelerating rates of global sea-level rise. Few models of coastal sediment transport can resolve the multitude of coastal-change processes at a given beach, and fewer still are computationally efficient enough to achieve large-scale, long-term simulations, while accounting for historical behavior and uncertainties in future climate. Here, we show that a scalable, data-assimilated shoreline-change model can achieve realistic simulations of long-term coastal change and uncertainty across large coastal regions. As part of the modeling case study of the U.S. South Atlantic Coast (Miami, Florida to Delaware Bay) presented here, we apply historical, satellite-derived observations of shoreline position combined with daily hindcasted and projected wave and sea-level conditions to estimate long-term coastal change by 2100. We find that 63 to 94% of the shorelines on the U.S. South Atlantic Coast are projected to retreat past the present-day extent of sandy beach under 1.0 to 2.0 m of sea-level rise, respectively, without large-scale interventions.

North Carolina↗
USGS2023

Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities

This report is part of the NOAA Mesophotic and Deep Benthic Communities (MDBC) Series of publications that share the results of work conducted by the Deepwater Horizon MDBC restoration projects. The 2010 Deepwater Horizon oil spill was an unprecedented event. Approximately 3.2 million barrels of oil were released into the deep ocean over nearly three months. The plume of oil moved throughout the water column, formed surface slicks that cumulatively covered an area the size of Virginia, and washed oil onto at least 1,300 miles of shoreline habitats. More than 770 square miles (2,000 square kilometers) of deep benthic habitat surrounding the Deepwater Horizon wellhead and 4-square miles of the Pinnacles mesophotic reef complex, located at the edge of the continental shelf, were injured by the oil spill. Under the Oil Pollution Act, state and federal natural resource trustees conducted a Natural Resource Damage Assessment (NRDA). The Trustees assessed damages, quantifying the unprecedented injuries to natural resources and lost services. They also developed a programmatic restoration plan to restore injured resources and compensate the public for lost services. In April 2016, a settlement was finalized that included up to $8.8 billion in funding for the Deepwater Horizon Trustees to restore the natural resource injuries caused by the oil spill as described in their programmatic restoration plan, Final Programmatic Damage Assessment and Restoration Plan and Final Programmatic Environmental Impact Statement. The Deepwater Horizon Open Ocean Trustee Implementation Group is responsible for restoring natural resources and their services within the Open Ocean Restoration Area that were injured by the oil spill. The Open Ocean Trustees include NOAA, Department of the Interior, U.S. Environmental Protection Agency, and U.S. Department of Agriculture. In 2019, the Open Ocean Trustee Implementation Group committed more than $126 million to implement four restoration projects to address the injury to MDBC. The MDBC projects are: mapping, Ground-truthing, and Predictive Habitat Modeling; Habitat Assessment and Evaluation; Coral Propagation Technique Development; and Active Management and Protection. NOAA and the Department of the Interior are implementing the projects, in cooperation with a range of partners, over eight years. Together, the projects take a phased approach to meet the challenges involved in restoring deep-sea habitats. Challenges to restoration include a limited scientific understanding of these communities, limited experience with restoration at the depths at which these communities occur, and remote locations that limit accessibility. More information about Deepwater Horizon restoration and the MDBC restoration projects is available at: www.gulfspillrestoration.noaa.gov.

Gulf of Mexico↗
USGS2025

A high-resolution 3-D P-wave velocity structure of the south-central Cascadia subduction zone from wide-angle shore-crossing seismic refraction data

This study addresses a significant gap in understanding the features of the south-central Cascadia subduction zone, a region characterized by complex geologic, tectonic, and seismic transitions both offshore and onshore. Unlike other segments along this margin, this area lacks a 3-D velocity model to delineate its structural and geological features on a fine scale. To address this void, we developed a high-resolution 3-D P-wave velocity model using active source seismic data from ship-borne seismic shots recorded on temporary and permanent onshore seismic stations and ocean-bottom seismometers. Our model shows velocity variations across the region with distinct velocity-depth profiles for the Siletz, Franciscan, and Klamath terranes in the overlying plate. We identified seaward dipping high-velocity static backstops associated with the Siletz and Klamath terranes, situated near the shoreline and further inland, respectively. Regions of reduced crustal velocity are associated with crustal faults. Moreover, there is significant along-strike depth variation in the subducting slab, which is about 4 km deeper near the thick, dense Siletz terrane and becomes shallower near the predominantly less-dense Franciscan terrane. This highlights a sudden tectonic and geologic transition at the southern boundary of the Siletz terrane. Our velocity model also indicates slightly increased hydration, though still minimal, in both the oceanic crust and the upper mantle of the subducting plate compared to other parts of the margin.

British Columbia, California, Oregon, Washington↗
USGS2023

Field observations and long short-term memory modeling of spectral wave evolution at living shorelines in Chesapeake Bay, USA

Living shorelines as a nature-based solution for climate change adaptation were constructed in many places around the world. The success of this type of projects requires long-term monitoring for adaptive management. The paper presents a novel framework leveraging scientific machine learning methods for accurate and rapid prediction of long-term hydrodynamic forcing impacting living shorelines using short-term measurements of water levels and wind waves in the largest estuary in the U.S. Different from existing data-driven wave prediction models focusing on significant wave heights, this study is focused on the prediction of wave energy spectra in shallow water using winds and tides as the input feature and short-term measurements of wave spectra and water depths as the label. Long Short-Term Memory (LSTM) models were developed using four-month wave measurements in the stormy seasons to predict integral wave parameters and energy spectra for multiple years. The developed models accurately predicted wave heights, peak periods, and energy spectra around the living shorelines, capturing complex wave dynamics, such as wave generation by wind, nonlinear wave-wave interactions, and depth-limited wave breaking in the shallow water of a large estuary. The validated models were then used to determine the long-term wave forcing impacting the living shorelines based on the modeled wave characteristics and spectra. Model results show that the surrogate models utilizing LSTM to predict wave spectra in the frequency domain enable long-term predictions of spectral wave evolution with a minimal computational cost. Our findings provide valuable insights into the efficacy of living shorelines in attenuating wave energy and demonstrate the utility of this approach in assessing the effectiveness of such living shoreline structures.

Applied Ocean Research↗
USGS2020

The field trip that changed the course of my career

After gobbling down a breakfast of sliced papaya, scrambled eggs, refried beans, and soft flour tacos, we gathered our gear and loaded it into the red zodiac that the station manager had assigned to us. My colleagues and I were headed to a pair of islands off the coast of Belize called Twin Cays, occupied by a unique group of tropical plants and animals adapted to a wet and saline habitat. Our ride from Carrie Bow Cay, home of the Smithsonian Institution’s field station, took about twenty minutes because of the choppy water. As we crossed the three-kilometer stretch from Carrie Bow to Twin Cays, I struggled to keep my seat on the bouncing pontoon and was soon soaked by salt spray. As we neared Twin Cays, the deep blue of the lagoon gave way to the turquoise and pale green colors of the shallow sand flats in the lee of the archipelago. Finally, the zodiac slowed, and we pulled into the calm channel separating the two islands. On either side of the channel was an intimidating tangle of tree trunks, branches, leaves, and aerial roots. The trees leaned out over the water and appeared poised to topple into the sea. However, they were perfectly still in the humid morning air and anchored solidly in place by arching prop roots. I sensed that I had entered an alien world, a waterlogged Terra Incognita that looked, smelled, and sounded like nothing I had ever experienced. As we slowly motored along, I peered more closely at the trees that fringed the shoreline. They had gnarled trunks and twisted branches that supported a canopy of dark green leaves. These trees were red mangroves or Rhizophora mangle, their scientific name, and were the dominant vegetation here. These oceanic mangrove islands were intertidal, which means that the trees were inundated twice a day by the sea. Their intimate relationship with the sea, however, was most apparent along the water’s edge. Long, drop roots plunged from the canopy to dangle in the crystal-clear water. Encrusted on the submerged portions of the mangrove roots were yellow and orange sponges, white and pink anemones, sharp-edged oysters, and feathery-green algae. The mangroves, it turned out, provided the only solid substrate for these sessile creatures. There were also mobile animals that I glimpsed as I leaned over the pontoon to peer into the pellucid water. Tiny fish flashed among the partially submerged roots as each one briefly flipped its body sideways to catch the sun glinting through the water. A school of mangrove snappers swam past the boat and disappeared under the overhanging creekbank, which created a shadowy haven from predators. Ribbons of turtlegrass, uprooted from the nearby reef flat, were draped on mangrove prop roots like green and brown tinsel. As the zodiac floated closer to shore, I spotted a mangrove tree crab, which stealthily crept up a tree trunk. In the distance, I could hear the hectoring cry of an osprey, as well as the periodic cheep-cheep of a mangrove warbler deeper in the forest. A soft breeze carried the faint odor of rotten eggs, which was caused by the microbially mediated production of hydrogen sulfide in the waterlogged soil. This was my first close-up view of Belize’s mangroves. The year was 1985. The movie “Back to the Future” had just premiered, PLO terrorists had hijacked the Italian cruise ship Achille Lauro, five people had died after ingesting cyanide-laced Tylenol, and Microsoft had just released Windows 1.0. I had recently gotten a Macintosh personal computer with 128k of memory (seemed like a lot back then) and was learning how to use Cricket Graph, my first software program. Until that point, I had been creating graphs by hand with ink-filled drawing pens, T-squares, and Letraset dry-transfer sheets. This was a time when the world seemed to be on the verge of dramatic changes—many that would impact me and my career as a scientist.

Book chapter↗
USGS2021

Seven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs

Observational data of coastal change over much of the Arctic are limited largely due to its immensity, remoteness, harsh environment, and restricted periods of sunlight and ice-free conditions. Barter Island, Alaska, is one of the few locations where an extensive, observational dataset exists, which enables a detailed assessment of the trends and patterns of coastal change over decadal to annual time scales. Coastal bluff and shoreline positions were delineated from maps, aerial photographs, and satellite imagery acquired between 1947 and 2020, and at a nearly annual rate since 2004. Rates and patterns of shoreline and bluff change varied widely over the observational period. Shorelines showed a consistent trend of southerly erosion and westerly extension of the western termini of Barter Island and Bernard Spit, which has accelerated since at least 2000. The 3.2 km long stretch of ocean-exposed coastal permafrost bluffs retreated on average 114 m and at a maximum of 163 m at an average long-term rate (70 year) of 1.6 ± 0.1 m/yr. The long-term retreat rate was punctuated by individual years with retreat rates up to four times higher (6.6 ± 1.9 m/yr; 2012–2013) and both long-term (multidecadal) and short-term (annual to semiannual) rates showed a steady increase in retreat rates through time, with consistently high rates since 2015. A best-fit polynomial trend indicated acceleration in retreat rates that was independent of the large spatial and temporal variations observed on an annual basis. Rates and patterns of bluff retreat were correlated to incident wave energy and air and water temperatures. Wave energy was found to be the dominant driver of bluff retreat, followed by sea surface temperatures and warming air temperatures that are considered proxies for evaluating thermo-erosion and denudation. Normalized anomalies of cumulative wave energy, duration of open water, and air and sea temperature showed at least three distinct phases since 1979: a negative phase prior to 1987, a mixed phase between 1987 and the early to late 2000s, followed by a positive phase extending to 2020. The duration of the open-water season has tripled since 1979, increasing from approximately 40 to 140 days. Acceleration in retreat rates at Barter Island may be related to increases in both thermodenudation, associated with increasing air temperature, and the number of niche-forming and block-collapsing episodes associated with higher air and water temperature, more frequent storms, and longer ice-free conditions in the Beaufort Sea.

Alaska↗
USGS2018

U.S. Caribbean

Historically, the U.S. Caribbean region has experienced relatively stable seasonal rainfall patterns, moderate annual temperature fluctuations, and a variety of extreme weather events, such as tropical storms, hurricanes, and drought. However, the Caribbean climate is changing and is projected to be increasingly variable as levels of greenhouse gases in the atmosphere increase. The high percentage of coastal area relative to the total island land area in the U.S. Caribbean means that a large proportion of the region’s people, infrastructure, and economic activity are vulnerable to sea level rise, more frequent intense rainfall events and associated coastal flooding, and saltwater intrusion. High levels of exposure and sensitivity to risk in the U.S. Caribbean region are compounded by a low level of adaptive capacity, due in part to the high costs of mitigation and adaptation measures relative to the region’s gross domestic product, particularly when compared to continental U.S. coastal areas. The limited geographic and economic scale of Caribbean islands means that disruptions from extreme climate-related events, such as droughts and hurricanes, can devastate large portions of local economies and cause widespread damage to crops, water supplies, infrastructure, and other critical resources and services. The U.S. Caribbean territories of Puerto Rico and the U.S. Virgin Islands (USVI) have distinct differences in topography, language, population size, governance, natural and human resources, and economic capacity. However, both are highly dependent on natural and built coastal assets; service-related industries account for more than 60% of the USVI economy. Beaches, affected by sea level rise and erosion, are among the main tourist attractions. In Puerto Rico, critical infrastructure (for example, drinking water pipelines and pump stations, sanitary pipelines and pump stations, wastewater treatment plants, and power plants) is vulnerable to the effects of sea level rise, storm surge , and flooding. In the USVI, infrastructure and historical buildings in the inundation zone for sea level rise include the power plants on both St. Thomas and St. Croix; schools; housing communities; the towns of Charlotte Amalie, Christiansted, and Frederiksted; and pipelines for water and sewage. Climate change will likely result in water shortages due to an overall decrease in annual rainfall, a reduction in ecosystem services, and increased risks for agriculture, human health, wildlife, and socioeconomic development in the U.S. Caribbean. These shortages would result from some locations within the Caribbean experiencing longer dry seasons and shorter, but wetter, wet seasons in the future. Extended dry seasons are projected to increase fire likelihood. Excessive rainfall, coupled with poor construction practices, unpaved roads, and steep slopes, can exacerbate erosion rates and have adverse effects on reservoir capacity, water quality, and nearshore marine habitats. Ocean warming poses a significant threat to the survival of corals and will likely also cause shifts in associated habitats that compose the coral reef ecosystem . Severe, repeated, or prolonged periods of high temperatures leading to extended coral bleaching can result in colony death. Ocean acidification also is likely to diminish the structural integrity of coral habitats. Studies show that major shifts in fisheries distribution and changes to the structure and composition of marine habitats adversely affect food security, shoreline protection, and economies throughout the Caribbean. In Puerto Rico, the annual number of days with temperatures above 90°F has increased over the last four and a half decades. During that period, stroke and cardiovascular disease, which are influenced by such elevated temperatures, became the primary causes of death. Increases in average temperature and in extreme heat events will likely have detrimental effects on agricultural operations throughout the U.S. Caribbean region. Many farmers in the tropics, including the U.S. Caribbean, are considered small-holding, limited resource farmers and often lack the resources and/or capital to adapt to changing conditions. Most Caribbean countries and territories share the need to assess risks, enable actions across scales, and assess changes in ecosystems to inform decision-making on habitat protection under a changing climate. U.S. Caribbean islands have the potential to improve adaptation and mitigation actions by fostering stronger collaborations with Caribbean initiatives on climate change and disaster risk reduction.

Report↗
USGS2007

National assessment of shoreline change, part 4: Historical coastal cliff retreat along the California coast

Coastal cliff retreat, the landward migration of the cliff face, is a chronic problem along many rocky coastlines in the United States. As coastal populations continue to grow and community infrastructures are threatened by erosion, there is increased demand for accurate information regarding trends and rates of coastal cliff retreat. There is also a need for a comprehensive analysis of cliff retreat that is consistent from one coastal region to another. To meet these national needs, the U.S. Geological Survey is conducting an analysis of historical coastal cliff retreat along open-ocean rocky coastlines of the conterminous United States and parts of Hawaii, Alaska, and the Great Lakes. One purpose of this work is to develop standard repeatable methods for mapping and analyzing coastal cliff retreat so that periodic updates of coastal erosion can be made nationally that are systematic and internally consistent. This report on the California Coast is an accompaniment to a report on long-term sandy shoreline change for California. This report summarizes the methods of analysis, interprets the results, and provides explanations regarding long-term rates of cliff retreat. Neither detailed background information on the National Assessment of Shoreline Change Project nor detailed descriptions of the geology and geomorphology of the California coastline are presented in this report. The reader is referred to the shoreline change report (Hapke et al., 2006) for this type of background information. Cliff retreat evaluations are based on comparing one historical cliff edge digitized from maps, with a recent cliff edge interpreted from lidar (Light Detection and Ranging) topographic surveys. The historical cliff edges are from a period ranging from 1920-1930, whereas the lidar cliff edges are from either 1998 or 2002. Long-term (~70- year) rates of retreat are calculated using the two cliff edges. The rates of retreat presented in this report represent conditions from the 1930s to 1998, and are not intended for predicting future cliff edge positions or rates of retreat. Due to the geomorphology of much of California's rocky coast (high-relief, steep slopes with no defined cliff edge) as well as to gaps in both the historical maps and lidar data, we were able to derive two cliff edges and therefore calculate cliff retreat rates for a total of 353 km. The average rate of coastal cliff retreat for the State of California was -0.3±0.2 m/yr, based on rates averaged from 17,653 individual transects measured throughout all areas of California's rocky coastline. The average amount of cliff retreat was 17.7 m over the 70-year time period of our analysis. Retreat rates were generally lowest in Southern California where coastal engineering projects have greatly altered the natural coastal system. California permits shoreline stabilization structures where homes, buildings or other community infrastructure are imminently threatened by erosion. While seawalls and/or riprap revetments have been constructed in all three sections of California, a larger proportion of the Southern California coast has been protected by engineering works, due, in part, to the larger population pressures in this area.

California↗
USGS1990

Growth and equilibrium in sea otter populations

(1) Counts through time were compiled for five sea otter ( Enhydra lutris ) populations in the north-east Pacific Ocean that were below equilibrium density: Attu Island, south-east Alaska, British Columbia, Washington State, and central California. Similar data were obtained from the equilibrium density population at Amchitka Island in 1971 and 1986. (2) Shorelines of Attu and Amchitka islands each were divided into forty-five segments, within which lineal (length of shore at mean higher high water) and areal (mean higher high water to the 10-fathom (18.3-m) depth contour) measures were made of the amount of habitat. (3) Rate of increase for the four northern populations was 17-20% year-1. Density- or size-dependent changes in rate of increase could not be demonstrated for any of these populations. The California population, in contrast, has undergone three apparent growth phases: the early 1900s to the mid-1970s when it increased about 5% year-1; the mid-1970s to the mid-1980s when it declined about 5% year-1; and the mid-1980s to 1988 when it increased about 7% year-1. An exponential growth model accounted for 92-98% of the variation in counts through time in all cases. (4) Population increase at Attu Island was achieved largely by range expansion as opposed to increased density. Range expansion in lineal and areal habitat occurred at 11% and 13% year-1, respectively; neither rate was lower (P > 0.25) than the observed rate of increase in numbers of animals counted. (5) Despite similarities in island size and physical environment, the most conservative estimates of population density at Amchitka Island were > 3 X greater than maximum density estimates for Attu Island. (6) Surveys of Amchitka Island from the mid-1930s through the mid-1980s indicate that the population increased to a peak in the 1940s; declined abruptly thereafter; and subsequently increased to a new and higher equilibrium in the 1960s, where it has since remained. (7) These population data, together with information on sea otter foraging and benthic community structure at Attu and Amchitka islands, suggest that multiple population equilibria exist in this system, emanating from complex trophic interactions low in the food web. I hypothesize that the lower population equilibrium is achieved largely or exclusively on an invertebrate diet consisting principally of herbivorous sea urchins. When unregulated by sea otter predation, the rocky benthos is deforested by sea urchin grazing. As growing otter populations compete increasingly for food, grazing intensity declines and the system shifts to one dominated by kelp beds, in turn leading to increased production, a shift in habitat structure, and population increases of kelp bed fishes. Apparently this new food resource elevates the sea otter population to a higher and more stable equilibrium.

Journal of Animal Ecology↗
USGS1988

Large-scale bedforms in boulder gravel produced by giant waves in Hawaii

Approximately 105,000 yr ago (based on uranium-series dating), waves in a giant wave train swept up to an elevation of about 375 m on the island of Lanai. The waves deposited the Hulopoe Gravel, which near the present shoreline consists of basalt boulders, coral fragments, and calcareous beachrock slabs, and near the upper limit of the deposit consists of sand and shell fragments. The maximum heights of similar but lower deposits on nearby islands, when adjusted for their estimated subsidence due to volcanic loading during the past 105,000 yr, indicate that the source of the wave was about 50 km southwest of Lanai. We hypothesize that failure and downward movement of the huge Lanai submarine landslide created an ocean disturbance, which produced waves that rushed across the Lanai reef and beach, picked up limestone and lava fragments, and deposited them high on the island as the Hulopoe Gravel. Backwash from the waves stripped soil and rock from the islands and carried much of it to the sea. The Hulopoe Gravel is 8 m thick in a gulch 200 m inland from the Lanai shoreline, where it consists of three beds, successively, 2, 4, and 2 m thick. These beds are considered to have been laid down by successive waves in the wave train. Each bed consists of two units: a lower unit of basalt and limestone boulders, cobbles, and sand, and an upper bimodal unit of large basalt boulders with a pebbly sand matrix. These subunits are inferred to be deposited from the runup and backwash of each wave. At the upper surface of the Hulopoe Gravel, basalt boulders averaging 0.5 m in diameter are arranged in dunelike ridges about 1 m high and 10 m apart. Nearby, where young streams have cut into and exposed the lower beds of the Hulopoe, clasts at the boundaries between the beds are locally imbricated and dip landward. We interpret these features as aspects of torrential flow and crossbedding created during the high-speed backwash of the great waves.

Hawaii↗
USGS1975

Mechanism of Formation of Pillow Lava

Much of the ocean floor is covered by lava of a distinctive character. The lava appears to be made up of closely packed ellipsoidal masses about the size and shape of pillows - hence the term pillow lava. Only within the last few years has the abundance of pillow lava on the ocean floor been fully recognized. Ocean-bottom photographs and dredge samples have shown that the great bulk of new ocean floor created at diverging plate boundaries (such as the Mid-Atlantic Ridge) is composed of pillowed basaltic lava flows. Closeup observations from submarines at depths of 2.7 km in the rift valley of the Mid-Atlantic Ridge have verified that virtually all the lavas erupted at this plate boundary are pillowed. The submarine portions of the great oceanic volcanoes, such as the ridge beneath the Hawaiian Islands, are also known to be built largely of pillow lava, and it is widespread in outcrops of uplifted ancient lava. Pillow lava is probably the most abundant form of volcanic rock on earth, though most of it is hidden beneath the world's oceans and mantled by younger sediments. Most investigators agree that the pillows form when fluid lava chills in contact with water, either when it erupts directly into water (or beneath ice) or when it flows across a shoreline and into a body of water. However, prior to our study, the process of pillow formation had never been directly observed. The recent eruptions of Kilauea Volcano in Hawaii provided an unparalleled opportunity to study the movement and cooling of lava beneath the sea. In June 1969, lava from the new Mauna Ulu vent on the east rift zone of Kilauea spilled into the sea after flowing 12 km down the south flank of the volcano. This pattern was repeated, with lava flowing into the sea for a few weeks each year through 1973. In April 1971 scuba divers for the first time investigated lava flowing underwater and learned that in favorable circumstances the lava could be approached closely. Despite heated water, explosive concussions, vigorous convective currents, and poor visibility due to suspended sediment, valuable observations were made.

American Scientist↗
USGS2023

Modeling surface wave dynamics in upper Delaware Bay with living shorelines

Living shorelines gain increasing attention because they stabilize shorelines and reduce erosion. This study leverages physics-based models and bagged regression tree (BRT) machine learning algorithm to simulate wave dynamics at a living shoreline composed of constructed oyster reefs (CORs) in upper Delaware Bay. The physics-based models consist of coupled Delft3D-FLOW and SWAN in four-level nested domains. The model accuracy converges with increasing mesh resolution. The simulated wave-induced current circulation substantiates the effectiveness of CORs in trapping sediments. The simulated yearly-averaged wave power correlates qualitatively with historical shoreline retreat rates. BRT is adopted to improve the model accuracy, identify key processes responsible for simulation errors in wave height ( H 8 ) and wave period ( T p ), and quantify their importance. In the CORs sheltered area, BRT reveals that simulation errors of wind seas mainly arise from wind forcing, wave breaking and wave triad interactions. Wave breaking is seven times more important than wind forcing for simulating H 8 , while wind forcing and triad interactions are of equal importance for simulating T p . Simulation errors of swells mostly stem from bottom friction and offshore wave boundary conditions. Results from this study can help the assessment and adaptive management of CORs-based living shoreline restoration projects under climate change.

New Jersey↗
USGS2007

Effect of storms on barrier island dynamics, Core Banks, Cape Lookout National Seashore, North Carolina, 1960-2001

The effect of storms on long-term dynamics of barrier islands was evaluated on Core Banks, a series of barrier islands that extend from Cape Lookout to Okracoke Inlet in the Cape Lookout National Seashore, North Carolina. Shoreline and elevation changes were determined by comparing 77 profiles and associated reference markers established by the U.S. Army Corps of Engineers (USACE) on Core Banks from June 1960 to July 1962 to a follow-up survey by Godfrey and Godfrey (G&G) in 1971 and a survey by the Department of Geology at East Carolina University (ECU) in 2001, in which 57 of the original 77 profiles were located. Evaluation of the baseline data associated with the USACE study supplies an important record of barrier island response to two specific storm events—Hurricane Donna in September 1960 and the Ash Wednesday extra-tropical cyclone in March 1962. The 1962 USACE survey was followed by 9 years characterized by no major storms; this low-energy period was captured by the G&G survey in 1971. The G&G survey was followed by 22 years characterized by occasional small to moderate storms. Starting in 1993, however, and continuing through 1999, the North Carolina coast experienced a major increase in storm activity, with seven major hurricanes impacting Core Banks. Both the USACE 1960–1962 and G&G 1962–1971 surveys produced short-term data sets that reflected very different sets of weather conditions. The ECU 2001 survey data were then compared with the USACE 1960 survey data to develop a long-term (41 years) data set for shoreline erosion on Core Banks. Those resulting long-term data were compared with the long-term (52 years) data sets by the North Carolina Division of Coastal Management (NCDCM) from 1940–1992 and 1946–1998; a strong positive correlation and very similar rates of average annual erosion resulted. However, the ECU and NCDCM long-term data sets did not correlate with either of the USACE and G&G short-term survey data and had very different average annual erosion rates. The average annual long-term rate of shoreline erosion for all of Core Banks and for both the ECU 1960–2001 and the NCDCM 1946–1998 surveys was -5 feet per year (ft/yr). These long-term rates of shoreline recession are in strong contrast with the short-term, storm-dominated rates of shoreline erosion for all of Core Banks developed by the USACE 1960–1961 and USACE 1961–1962 surveys, which have average annual erosion rates of -40 ft/yr and -26 ft/yr, respectively, and range from -226 feet (ft) to +153 ft. The combined short-term, storm-dominated shoreline erosion rate for the USACE surveys (1960–1962) was -36 ft/yr. In contrast, the average annual short-term, non-stormy period G&G 1962–1971 survey demonstrated shoreline accretion for all of Core Banks with an average annual rate of +12 ft/yr. In general, North Core Banks has higher erosion and accretion rates than South Core Banks. In the 1961 survey, the USACE installed 231 reference markers (RM-0 is closest to the ocean and RM-2 is farthest from the ocean) along the 77 profiles, as well as 33 reference markers labeled RM-4, RM-6, and RM-8 in the wider portions of the islands. The G&G survey recovered a total of 141 reference markers (61 percent), and the ECU survey recovered a total of 83 reference markers (36 percent) of the RM-0, RM-1, and RM-2 markers. The average ground elevation measured by the USACE in 1961 was RM-0 = +5.8 ft, RM-1 = +5.2 ft, and RM-2 = +4.8 ft. The G&G 1970 survey measured average ground elevations of RM-0 = +6.7 ft, RM-1 = +6.4 ft, and RM-2 = +6.1 ft, and the average ground elevation measured by ECU in 2001 was RM-0 = +10.1 ft, RM-1 = +9.1 ft, and RM-2 = +8.5 ft. The latter numbers represent approximately an overall 72-percent increase in island elevation from 1961 to 2001. Based on aerial photographic time-slice analyses, it is hypothesized that this increase in island elevation occurred during the post-1962 period with storm overwash systematically raising the island elevation through time, which in turn led to decreased numbers of overwash events. The latter processes and responses in turn led to a substantial increase in vegetative growth on the barrier island, as well as submerged aquatic vegetation on the back-barrier sand shoals. Integration of the USACE, G&G, ECU, and NCDCM shoreline erosion data for Core Banks shows several important points about shoreline recession. (1) The ECU and NCDCM data sets demonstrate that there is an ongoing net, long-term, but small-scale shoreline recession associated with Core Banks; (2) the USACE short-term data sets demonstrate that processes associated with individual storm events or sets of events produce extremely large-scale changes that include both erosion and accretion; (3) the short-term, non-stormy period data set of G&G demonstrates that if given enough time between storm events, barriers can rebuild to their pre-storm period conditions; and (4) the post-storm response generally tends to approach the pre-storm location, but rarely reaches it before the next storm or stormy period sets in. The result is the net long-term change documented by both the ECU 1960–2001 and NCDCM 1946–1998 Core Banks data sets that resulted in erosion rates ranging from 0 to -30 ft/yr with net annual average recession rates of -5 ft/yr. Analysis and comparison of these data sets supply important information for understanding the dynamics and responses of barrier island systems through time. In addition, the results of the present study on Core Banks supply essential process-response information that can be used to design and implement management plans for the Cape Lookout and Cape Hatteras National Seashores and for other seashores in the U.S. National Park Service system.

North Carolina↗
USGS1992

Map showing bottom topography of the Pacific Continental Margin, Cape Mendocino to Point Conception

All contours, geographic outlines, and political boundaries shown on this map of the bottom topography, or bathymetry, of the Pacific continental margin between 34? and 41? N. latitudes were plotted from digital data bases in the library of the U.S. Geological Survey (USGS)-National Oceanic and Atmospheric Administration (NOAA) Joint Office for Mapping and Research (JOMAR). These digital data were obtained and compiled from many sources; consequently, data quality varies within particular data bases as well as from one data base to another. Bathymetric contours were digitized from a map compiled by Chase and others (1981) and from the unpublished large scale versions of that map (T.E. Chase, unpub. maps, 1981). Data for the area seaward of the continental slope (~2000 m depth) were obtained primarily from the U.S. Coast and Geodetic Survey (C&GS) 1955 Pacific Exploratory Survey, a systematic and detailed (~8 -nmi trackline spacing) survey between Mexico and Canada. The USGS provided data from cruises S3-78-NC, S15-79-NC, L2-77-NC, Ll0-76-NC, and Bartlett 72. Data were also obtained from Scripps Institution of Oceanography cruises Merazine, Blue Flash, Kayak B, Scan I, and Seven Tow (Chase and Menard, 1971; Chase and others, 1975; Wilde and others, 1976; Wilde and others, 1978). The 200-m contour was derived from the National Ocean Survey charts 1306N-20 (1975), 1307N-l1B (1974a), 1307N-18B (1974b), and C&GS chart 1308N-12 (1969). Sea-floor depths were corrected for sound velocity in sea water using Matthew's (1939) tables. Onshore topographic contours were generated by computer from a modified version of 3-arc-second elevation data provided by the Defense Mapping Agency. The United States digital shoreline was obtained from the NOAA, NOS, Nautical Charting Division, National Atlas files. The coastline of Canada was digitized from Canadian Hydrographic Service bathymetric maps. The primary source of names of the sea floor features was the "Gazetteer of Undersea Features" (Defense Mapping Agency, 1990). Acknowledgments Christopher Hines assisted in the construction and verification of the digital data bases. Reviews and suggestions by Edward C. Escowitz and Florence Wong and advice provided by Will Stettner regarding the cartographic design substantially improved the quality of this map. References Cited Chase, T.E., and Menard, H.W., 1971, Bathymetric atlas of the northeastern Pacific Ocean: U.S. Naval Oceanographic Office Publication 1303, scale 1:2,000,000 at 33° latitude, 48 p. Chase, T.E., Wilde, Pat, and Normark, W.R., 1975, Oceanographic data of the Monterey Deep Sea Fan: San Diego, University of California, Institute of Marine Resources Publication TR 58, scale 1:898,524 at 35° latitude. Chase, T.E., Wilde, Pat, Normark, W.R., Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Coast and Geodetic Survey, 1969, Point St. George to Point Delgada: Coast and Geodetic Survey Bathymetric Map 1308N-12, scale 1:250,000. Defense Mapping Agency, 1990, Gazetteer of undersea features (4th ed.): Washington, D.C., Defense Mapping Agency. Matthews, D.J., 1939, Tables of the velocity of sound in pure water and sea water (2d ed.): London, Admiralty, Hydrographic Department, H.D. 282, 52 p. National Ocean Survey, 1974a, Vicinity Pt. Sur to Pt. Reyes: National Ocean Survey Bathymetric Map 1307N-11B, scale 1:250,000. National Ocean Survey, 1974b, Pt. Reyes to Tolo Bank: National Ocean Survey Bathymetric Map 1307N-18B, scale 1:250,000. National Ocean Survey, 1975, Cape San Martin to Point Conception: National Ocean Survey Bathymetric Map 1306N-20, scale 1:250,000. Wilde, Pat, Normark, W.R., and Chase, T.E., 1976, Oceanographic data off central California 37° to 40° North including the Delgada Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 92, scale 1 :864,581 at 38° latitude. Wilde, Pat, Chase, T.E., Holmes, M.L., Normark, W.R., Thomas, J.A., McCulloch, D.S., and Kulm, L.D., 1978, Oceanographic data off northern California-southern Oregon 40° to 43° North including the Gorda Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 251, scale 1:815,482 at 42° latitude.

IMAP↗
USGS2023

Modeling extreme water levels in the Salish Sea: The importance of including remote sea level anomalies for application in hydrodynamic simulations

Extreme water-level recurrence estimates for a complex estuary using a high-resolution 2D model and a new method for estimating remotely generated sea level anomalies (SLAs) at the model boundary have been developed. The hydrodynamic model accurately resolves the dominant physical processes contributing to extreme water levels across the Washington State waters of the Salish Sea, including the relative contribution of remote SLA and other non-tidal residual processes that drive extreme water levels above the predicted tide. The model’s predictions have errors of less than 15 cm (<5% of 3–4 m tidal range) at eight tide gauge locations across the model domain. The influence of remote SLAs at the seaward boundary of the model was implemented using a multivariate regression of readily available and locally relevant wind, sea surface temperature, and pressure anomaly data, combined with El Niño Index data (R 2 = 0.76). The hydrodynamic model simulations using the remote SLA predictor compared well with simulations using the widely used data-assimilative global ocean model HYCOM SLA data (root mean square difference of 5.5 cm). Extreme water-level recurrence estimates with and without remote SLA show that remote forcing accounts for 50–60% of the total water level anomaly observed along Salish Sea shorelines. The resulting model simulations across decadal timescales provide estimates of extreme water level recurrence across the Salish Sea, capturing climate variability important to long-term coastal hazard planning. This approach has widespread applications for other complex estuarine systems.

Water↗