Coastal and Shelf Geology
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PublicationAccuracy of shoreline forecasting using sparse data(Elsevier, 2023-04-28)Sandy beaches are important resources providing recreation, tourism, habitat, and coastal protection. They evolve over various time scales due to local winds, waves, storms, and changes in sea level. A common method used to monitor change in sandy beaches is to measure the movement of the shoreline over time. Typically, the rate of change is estimated by fitting a linear regression through a time series of shoreline positions. To best manage the valuable resources within a coastal environment, accurate forecasts of shoreline position are needed. A simple way to estimate future shoreline position is to extrapolate a linear regression into the future, this method is often used to establish management guidelines like construction setback lines. A more recently developed shoreline forecasting technique utilizes the Kalman filter to assimilate shoreline data and modify the linear regression. This paper calculates the uncertainty and accuracy of both the extrapolated linear regression and Kalman filter forecasting methods for 10- and 20-year hindcasts using data collected at five diverse study areas. These data are inherently sparse (8–10 measurements per location, collected over 150 years) and are representative of the observed historical data available for the continental United States for this timeframe. Both methods produced similar results and had regionally averaged forecast accuracies of 5–16 m. We determined that the inaccuracy of the forecasts is largely due to the effects of shorter time scale variability. This variability is roughly proportional to the standard error of the linear regression, which is a useful measure of forecast uncertainty.•Extrapolated linear regression (ELR) can provide suitable shoreline forecasts.•A new method using the Kalman filter has forecast accuracy similar to the ELR.•Standard error of the linear regression is useful to estimate forecast uncertainty.•The SE of the linear regression can be used to test usefulness of old shorelines.
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ArticleIntegrating Bayesian Networks to forecast sea‐level rise impacts on Barrier Island characteristics and habitat availability(American Geophysical Union, 2022-10-14)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 and policy decisions. BNs utilized here include a shoreline change model and two models of barrier island biogeomorphological evolution at different scales (50 and 5 m). These BNs were then linked to another BN to predict habitat availability for piping plovers (Charadrius melodus), a threatened shorebird reliant on beach habitats. We evaluated the performance of the two linked geomorphology BNs and further examined error rates by generating hindcasts of barrier island geomorphology and habitat availability for 2014 conditions. Geomorphology hindcasts revealed that model error declined with a greater number of known inputs, with error rates reaching 55% when multiple outputs were hindcast simultaneously. We also found that, although error in predictions of piping plover nest presence/absence increased when outputs from the geomorphology BNs were used as inputs in the piping plover habitat BN, the maximum error rate for piping plover habitat suitability in the fully‐linked BNs was only 30%. Our findings suggest this approach may be useful for guiding scenario‐based evaluations where known inputs can be used to constrain variables that produce higher uncertainty for morphological predictions. Overall, the approach demonstrates a way to assimilate data and model structures with uncertainty to produce forecasts to inform coastal planning and management.
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ArticleDeep learning for pockmark detection: implications for quantitative seafloor characterization(Elsevier, 2022-11-24)Occurring globally, pockmarks are seafloor depressions associated with seabed fluid escape. Pockmark ubiquity and morphologic heterogeneity result in an irregular seafloor that can be difficult to quantitatively describe. To address this challenge, we test the hypothesis that deep-learning based object detection and segmentation can be used to develop data-driven models for pockmark identification and characterization. This study describes the development, testing, and deployment of eight separate deep learning-based pockmark detection models using publicly available, gridded bathymetric data from the Belfast Bay, Maine, USA, Blue Hill Bay, Maine, USA, and Passamaquoddy Bay, New Brunswick, Canada estuarine pockmark fields. The models tested include three types of convolutional neural network architectures, as well as a generative adversarial network. We find that the data-driven models consistently resolve pockmarks from the background seafloor, allowing for quick and accurate delineation of pockmarks in a variety of seabed habitats. With these delineations we examine and compare the morphology of the muddy estuarine pockmark fields. We then compare these morphometric results to pockmark fields in two distinct settings, the sandy German Bight and the Aquitaine continental slope. We find that in all the pockmark fields a power law relationship, generally, exists between pockmark area and pockmark depth, though this relationship deteriorates with the smallest pockmarks, suggesting that there may be a minimum size needed for geomorphic stability. These results show that the training data and trained models developed here can be applied for quick detection and characterization of pockmarks where other high-resolution bathymetry is available, demonstrating the value of data-driven detection models for characterizing morphologically complex seafloors. Last, the morphologic characteristics of pockmarks identified in this study will aid future studies in relating pockmark size to environmental characteristics like seabed sediment texture and regional gradient.
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ArticleBolide impact effects on the West Florida Platform, Gulf of Mexico: end Cretaceous and late Eocene(Geological Society of America, 2022-03-16)This study documents seismic reflection evidence that two different bolide impacts significantly disrupted stratigraphic and depositional processes on the West Florida Platform (Gulf of Mexico). The first impact terminated the Late Cretaceous Epoch (Chicxulub impact, Mexico; ca. 66 Ma; end-Maastrichtian age). The second took place in the late Eocene (Chesapeake Bay impact, Virginia, USA, portion of the Chesapeake Bay; ca. 35 Ma; Priabonian age). Both impacts produced far-reaching seismic shaking and ground roll followed by an impact-generated tsunami, the effects of which are evident in the seismostratigraphic record. The Chicxulub seismic shaking caused collapse and shoreward retreat of the Florida Escarpment and widely disrupted (faulting, folding, slumping) normal flat-lying shelf beds. The associated tsunami currents redistributed these shelf deposits and mixed them together with collapse debris from the escarpment to form a thick wedge of sediments along the base of the escarpment. The Chesapeake Bay impact created a mounded sedimentary deposit near the outer edge of the late Eocene ramp slope. This deposit also has a bipartite origin. A lower layer is marked by en echelon faulting created in situ by seismic shaking, whereas an upper layer represents sediments redistributed from the late Eocene shelf and upper ramp slope by tsunami-driven bottom currents (debris flows, contour currents, slumps). This is the first report of seismic effects from the Chesapeake Bay impact in the Gulf of Mexico. These results further demonstrate that large-scale marine bolide impacts have widespread effects on the stratigraphic and depositional record of Earth.
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ArticlePredicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: implications for people and plovers(American Geophysical Union, 2022-03-29)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 plover (Charadrius melodus) habitat availability, and probability of storm overwash under three scenarios of shoreline change (SLC) and compared results to observed 2014/2015 conditions. Scenarios assumed increasing rates of mean SLC from 0 to 4.71 m erosion per year. We observed uncertainty in several morphological predictions (e.g., beach width, dune height), suggesting decreasing confidence that Fire Island will evolve in response to SLR as it has in the past. Where most likely conditions could be determined, models predicted that Fire Island would become flatter, narrower, and more overwash-prone with increasing rates of SLC. Beach ecosystems were predicted to respond dynamically to SLR and migrate with the shoreline, while marshes lost the most area of any landcover type compared to 2014/2015 conditions. Such morphological changes may lead to increased flooding or breaching with coastal storms. However—although modest declines in piping plover habitat were observed with SLC—the dynamic response of beaches, flatter topography, and increased likelihood of overwash suggest storms could promote suitable conditions for nesting piping plovers above what our geomorphology models predict. Therefore, Fire Island may offer a conservation opportunity for coastal species that rely on early successional beach environments if natural overwash processes are encouraged.
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ArticleMature diffuse tectonic block boundary revealed by the 2020 southwestern Puerto Rico seismic sequence(American Geophysical Union, 2022-02-08)Distributed faulting typically tends to coalesce into one or a few faults with repeated deformation. The progression of clustered medium-sized (≥Mw4.5) earthquakes during the 2020 seismic sequence in southwestern Puerto Rico (SWPR), modeling shoreline subsidence from InSAR, and sub-seafloor mapping by high-resolution seismic reflection profiles, suggest that the 2020 SWPR seismic sequence was distributed across several short intersecting strike-slip and normal faults beneath the insular shelf and upper slope of Guayanilla submarine canyon. Multibeam bathymetry map of the seafloor shows significant erosion and retreat of the shelf edge in the area of seismic activity as well as slope-parallel lineaments and submarine canyon meanders that typically develop over geological time. The T-axis of the moderate earthquakes further matches the extension direction previously measured on post early Pliocene (∼>3 Ma) faults. We conclude that although similar deformation has likely taken place in this area during recent geologic time, it does not appear to have coalesced during this time. The deformation may represent the southernmost part of a diffuse boundary, the Western Puerto Rico Deformation Boundary, which accommodates differential movement between the Puerto Rico and Hispaniola arc blocks. This differential movement is possibly driven by the differential seismic coupling along the Puerto Rico—Hispaniola subduction zone. We propose that the compositional heterogeneity across the island arc retards the process of focusing the deformation into a single fault. Given the evidence presented here, we should not expect a single large event in this area but similar diffuse sequences in the future.
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ArticleMolluscan aminostratigraphy of the US Mid-Atlantic Quaternary coastal system: implications for onshore-offshore correlation, paleochannel and barrier island evolution, and local late Quaternary sea-level history(Elsevier, 2021-05-18)The Quaternary record of the US Mid-Atlantic coastal system includes onshore emergent late Pleistocene shoreline deposits, offshore inner shelf and barrier island units, and paleovalleys formed during multiple glacial stage sea-level lowstands. The geochronology of this coastal system is based on uranium series, radiocarbon, amino acid racemization (AAR), and optically stimulated luminescence (OSL) methods. We report over 600 mollusk AAR results from 93 sites between northeastern North Carolina and the central New Jersey shelf, representing samples from both onshore cores or outcrops, sub-barrier and offshore cores, and transported shells from barrier island beaches. AAR age estimates are constrained by paired 14C analyses on specific shells and associated U-series coral ages from onshore sites. AAR data from offshore cores are interpreted in the context of detailed seismic stratigraphy. The distribution of Pleistocene-age shells on the island beaches is linked to the distribution of inner shelf or sub-barrier source units. Age mixing over a range of time-scales (~1 ka to ~100 ka) is identified by AAR results from onshore, beach, and shelf collections, often contributing insights into the processes forming individual barrier islands. The regional aminostratigraphic framework identifies a widespread late Pleistocene (Marine Isotope Stage 5) aminozone, with isolated records of middle and early Pleistocene deposition. AAR results provide age estimates for the timing of formation of the three major paleochannels that underlie the Delmarva Peninsula: Persimmon Point paleochannel ≥800 ka; Exmore paleochannel ~400–500 ka (MIS 12); and Eastville paleochannel > 125 ka (MIS 6). The results demonstrate the value of synthesizing abundant AAR chronologic data across various coastal environments, integrating multiple distinct geologic studies. The ages and elevations of the Quaternary units are important for current hypotheses about relative sea-level history and crustal dynamics in the region, which was likely influenced by the Laurentide ice sheet, the margin just ~400 km to the north.
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ArticlePiping plovers demonstrate regional differences in nesting habitat selection patterns along the U. S. Atlantic coast(Ecological Society of America, 2021-03-11)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 compared habitat selection patterns among the three designated U.S. recovery units (New England, New York–New Jersey, and Southern). Geomorphic setting, substrate type, and vegetation type and density were determined in situ at 928 Piping Plover nests (hereafter, used resource units) and 641 random points (available resource units). Elevation, beach width, Euclidean distance to ocean shoreline, and least-cost path distance to low-energy shorelines with moist substrates (commonly used as foraging habitat) were associated with used and available resource units using remotely sensed spatial data. We evaluated multivariate differences in habitat selection patterns by comparing recovery unit-specific Bayesian networks. We then further explored individual variables that drove disparities among Bayesian networks using resource selection ratios for categorical variables and Welch’s unequal variances t-tests for continuous variables. We found that relationships among variables and their connections to habitat selection were similar among recovery units, as seen in commonalities in Bayesian network structures. Furthermore, nesting Piping Plovers consistently selected mixed sand and shell, gravel, or cobble substrates as well as areas with sparse or no vegetation, irrespective of recovery unit. However, we observed significant differences among recovery units in the elevations, distances to ocean, and distances to low-energy shorelines of used resource units. Birds also exhibited increased selectivity for overwash habitats and for areas with access to low-energy shorelines along a latitudinal gradient from north to south. These results have important implications for conservation and management, including assessment of shoreline stabilization and habitat restoration planning as well as forecasting effects of climate change.
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ArticleSeismic stratigraphic framework of the continental shelf offshore Delmarva, USA: implications for Mid-Atlantic Bight evolution since the Pliocene(Elsevier, 2020-07-10)Understanding how past coastal systems have evolved is critical to predicting future coastal change. Using over 12,000 trackline kilometers of recently collected, co-located multi-channel boomer, sparker and chirp seismic reflection profile data integrated with previously collected borehole and vibracore data, we define the upper (< 115 m below mean lower low water) seismic stratigraphic framework offshore of the Delmarva Peninsula, USA. Twelve seismic units and 11 regionally extensive unconformities (U1-U11) were mapped over 5900 km2 of North America's Mid-Atlantic continental shelf. We interpret U3, U7, U9, U11 as transgressive ravinement surfaces, while U1,2,4,5,6,8,10 are subaerial unconformities illustrating distinct periods of lower sea-level. Based on areal distribution, stratigraphic relationships and dating results (Carbon 14 and amino acid racemization estimates) from earlier vibracore and borehole studies, we interpret the infilled channels as late Neogene and Quaternary courses of the Susquehanna, Potomac, Rappahannock, York, James rivers and tributaries, and a broad flood plain. These findings indicate that the region's geologic framework is more complex than previously thought and that Pleistocene paleochannels are abundant in the Mid-Atlantic. This study synthesizes and correlates the findings of other Atlantic Margin studies and establishes a large-scale Quaternary framework that enables more detailed stratigraphic analysis in the future. Such work has implications for inner continental shelf systems tract evolution, the relationship between antecedent geology and modern coastal systems, assessments of eustacy, glacial isostatic adjustment, and other processes and forcings that play a role in passive margin evolution.
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ArticleUsing a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat(Public Library of Science, 2019-07-25)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 Sandy made landfall following the 2012 breeding season. We modeled nesting habitat using a nest presence/absence dataset that included characterizations of coastal morphology and vegetation. Using a Bayesian network, we predicted nesting habitat for each study site for the years 2010/2011, 2012, and 2014/2015 based on remotely sensed spatial datasets (e.g., lidar, orthophotos). We found that Hurricane Sandy increased piping plover habitat by 9 to 300% at 4 of 5 study sites but that one site saw a decrease in habitat by 27%. The amount, location, and longevity of new habitat appeared to be influenced by the level of human development at each site. At three of the five sites, the amount of habitat created and the time new habitat persisted were inversely related to the amount of development. Furthermore, the proportion of new habitat created in high-quality overwash was inversely related to the level of development on study areas, from 17% of all new habitat in overwash at one of the most densely developed sites to 80% of all new habitat at an undeveloped site. We also show that piping plovers exploited new habitat after the storm, with 14–57% of all nests located in newly created habitat in the 2013 breeding season. Our results quantify the importance of storms in creating and maintaining coastal habitats for beach-nesting species like piping plovers, and these results suggest a negative correlation between human development and beneficial ecological impacts of these natural disturbances.
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ArticleIdentifying salt marsh shorelines from remotely sensed elevation data and imagery(MDPI, 2019-07-31)Salt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high resolution over multiple timescales. In this study we describe two methods to calculate the location of the salt marsh shoreline. The marsh edge from elevation data (MEED) method uses remotely sensed elevation data to calculate an objective proxy for the shoreline of a salt marsh. This proxy is the abrupt change in elevation that usually characterizes the seaward edge of a salt marsh, designated the “marsh scarp.” It is detected as the maximum slope along a cross-shore transect between mean high water and mean tide level. The method was tested using lidar topobathymetric and photogrammetric elevation data from Massachusetts, USA. The other method to calculate the salt marsh shoreline is the marsh edge by image processing (MEIP) method which finds the unvegetated/vegetated line. This method applies image classification techniques to multispectral imagery and elevation datasets for edge detection. The method was tested using aerial imagery and coastal elevation data from the Plum Island Estuary in Massachusetts, USA. Both methods calculate a line that closely follows the edge of vegetation seen in imagery. The two methods were compared to each other using high resolution unmanned aircraft systems (UAS) data, and to a heads-up digitized shoreline. The root-mean-square deviation was 0.6 meters between the two methods, and less than 0.43 meters from the digitized shoreline. The MEIP method was also applied to a lower resolution dataset to investigate the effect of horizontal resolution on the results. Both methods provide an accurate, efficient, and objective way to track salt marsh shorelines with spatially intensive data over large spatial scales, which is necessary to evaluate geomorphic change and wetland vulnerability.
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ArticleRelationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model(European Geosciences Union, 2019-05-15)Understanding land loss or resilience in response to sea-level rise (SLR) requires spatially extensive and continuous datasets to capture landscape variability. We investigate the sensitivity and skill of a model that predicts dynamic response likelihood to SLR across the northeastern US by exploring several data inputs and outcomes. Using elevation and land cover datasets, we determine where data error is likely, quantify its effect on predictions, and evaluate its influence on prediction confidence. Results show data error is concentrated in low-lying areas with little impact on prediction skill, as the inherent correlation between the datasets can be exploited to reduce data uncertainty using Bayesian inference. This suggests the approach may be extended to regions with limited data availability and/or poor quality. Furthermore, we verify that model sensitivity in these first-order landscape change assessments is well-matched to larger coastal process uncertainties, for which process-based models are important complements to further reduce uncertainty.
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ArticleGeomorphic process fingerprints in submarine canyons(Elsevier, 2013-02-07)Submarine canyons are common features of continental margins worldwide. They are conduits that funnel vast quantities of sediment from the continents to the deep sea. Though it is known that submarine canyons form primarily from erosion induced by submarine sediment flows, we currently lack quantitative, empirically based expressions that describe the morphology of submarine canyon networks. Multibeam bathymetry data along the entire passive US Atlantic margin (USAM) and along the active central California margin near Monterey Bay provide an opportunity to examine the fine-scale morphology of 171 slope-sourced canyons. Log–log regression analyses of canyon thalweg gradient (S) versus up-canyon catchment area (A) are used to examine linkages between morphological domains and the generation and evolution of submarine sediment flows. For example, canyon reaches of the upper continental slope are characterized by steep, linear and/or convex longitudinal profiles, whereas reaches farther down canyon have distinctly concave longitudinal profiles. The transition between these geomorphic domains is inferred to represent the downslope transformation of debris flows into erosive, canyon-flushing turbidity flows. Over geologic timescales this process appears to leave behind a predictable geomorphic fingerprint that is dependent on the catchment area of the canyon head. Catchment area, in turn, may be a proxy for the volume of sediment released during geomorphically significant failures along the upper continental slope. Focused studies of slope-sourced submarine canyons may provide new insights into the relationships between fine-scale canyon morphology and down-canyon changes in sediment flow dynamics.
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PreprintTransient coastal landscapes : rising sea level threatens salt marshes( 2018-05)Salt marshes are important coastal environments that provide key ecological services. As sea level rise has accelerated globally, concerns about the ability of salt marshes to survive submergence are increasing. Previous estimates of likely survival of salt marshes were based on ratios of sea level rise to marsh platform accretion. Here we took advantage of an unusual, long-term (1979-2015), spatially detailed comparison of changes in a representative New England salt marsh to provide an empirical estimate of habitat losses based on actual measurements. We show prominent changes in habitat mosaic within the marsh, consistent and coincident with increased submergence and coastal erosion. Model results suggest that at current rates of sea level rise, marsh platform accretion, habitat loss, and with the limitation of the widespread “coastal squeeze”, the entire ecosystem might disappear by the beginning of the next century, a fate that might be likely for many salt marshes elsewhere.
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ArticleRemotely sensing the morphometrics and dynamics of a cold region dune field using historical aerial photography and airborne LIDAR data(MDPI AG, 2018-05-19)This study uses an airborne Light Detection and Ranging (LiDAR) survey, historical aerial photography and historical climate data to describe the character and dynamics of the Nogahabara Sand Dunes, a sub-Arctic dune field in interior Alaska’s discontinuous permafrost zone. The Nogahabara Sand Dunes consist of a 43-km2 area of active transverse and barchanoid dunes within a 3200-km2 area of vegetated dune and sand sheet deposits. The average dune height in the active portion of the dune field is 5.8 m, with a maximum dune height of 28 m. Dune spacing is variable with average crest-to-crest distances for select transects ranging from 66–132 m. Between 1952 and 2015, dunes migrated at an average rate of 0.52 m a−1. Dune movement was greatest between 1952 and 1978 (0.68 m a−1) and least between 1978 and 2015 (0.43 m a−1). Dunes migrated predominantly to the southeast; however, along the dune field margin, net migration was towards the edge of the dune field regardless of heading. Better constraining the processes controlling dune field dynamics at the Nogahabara dunes would provide information that can be used to model possible reactivation of more northerly dune fields and sand sheets in response to climate change, shifting fire regimes and permafrost thaw.
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ArticleCharacterizing storm response and recovery using the beach change envelope : Fire Island, New York(Elsevier, 2017-08-03)Hurricane Sandy at Fire Island, New York presented unique challenges in the quantification of storm impacts using traditional metrics of coastal change, wherein measured changes (shoreline, dune crest, and volume change) did not fully reflect the substantial changes in sediment redistribution following the storm. We used a time series of beach profile data at Fire Island, New York to define a new contour-based morphologic change metric, the Beach Change Envelope (BCE). The BCE quantifies changes to the upper portion of the beach likely to sustain measurable impacts from storm waves and capture a variety of storm and post-storm beach states. We evaluated the ability of the BCE to characterize cycles of beach change by relating it to a conceptual beach recovery regime, and demonstrated that BCE width and BCE height from the profile time series correlate well with established stages of recovery. We also investigated additional applications of this metric to capture impacts from storms and human modification by applying it to several post-storm historical datasets in which impacts varied considerably; Nor'Ida (2009), Hurricane Irene (2011), Hurricane Sandy (2012), and a 2009 community replenishment. In each case, the BCE captured distinctive upper beach morphologic change characteristic of these different beach building and erosional events. Analysis of the beach state at multiple profile locations showed spatial trends in recovery consistent with recent morphologic island evolution, which other studies have linked with sediment availability and the geologic framework. Ultimately we demonstrate a new way of more effectively characterizing beach response and recovery cycles to evaluate change along sandy coasts.
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ArticleSmartphone technologies and Bayesian networks to assess shorebird habitat selection(John Wiley & Sons, 2017-09-28)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. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, >30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection from many locations and sources, which can be used in management and decision-making applications. © 2017 The Authors. Wildlife Society Bulletin published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.
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ArticleUAS-SfM for coastal research : geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery(MDPI AG, 2017-10-03)The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.
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ArticleInner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy(Elsevier, 2017-02-17)Hurricane Sandy was one of the most destructive hurricanes in US history, making landfall on the New Jersey coast on October 30, 2012. Storm impacts included several barrier island breaches, massive coastal erosion, and flooding. While changes to the subaerial landscape are relatively easily observed, storm-induced changes to the adjacent shoreface and inner continental shelf are more difficult to evaluate. These regions provide a framework for the coastal zone, are important for navigation, aggregate resources, marine ecosystems, and coastal evolution. Here we provide unprecedented perspective regarding regional inner continental shelf sediment dynamics based on both observations and numerical modeling over time scales associated with these types of large storm events. Oceanographic conditions and seafloor morphologic changes are evaluated using both a coupled atmospheric-ocean-wave-sediment numerical modeling system that covered spatial scales ranging from the entire US east coast (1000 s of km) to local domains (10 s of km). Additionally, the modeled response for the region offshore of Fire Island, NY was compared to observational analysis from a series of geologic surveys from that location. The geologic investigations conducted in 2011 and 2014 revealed lateral movement of sedimentary structures of distances up to 450 m and in water depths up to 30 m, and vertical changes in sediment thickness greater than 1 m in some locations. The modeling investigations utilize a system with grid refinement designed to simulate oceanographic conditions with progressively increasing resolutions for the entire US East Coast (5-km grid), the New York Bight (700-m grid), and offshore of Fire Island, NY (100-m grid), allowing larger scale dynamics to drive smaller scale coastal changes. Model results in the New York Bight identify maximum storm surge of up to 3 m, surface currents on the order of 2 ms−1 along the New Jersey coast, waves up to 8 m in height, and bottom stresses exceeding 10 Pa. Flow down the Hudson Shelf Valley is shown to result in convergent sediment transport and deposition along its axis. Modeled sediment redistribution along Fire Island showed erosion across the crests of inner shelf sand ridges and sedimentation in adjacent troughs, consistent with the geologic observations.
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ArticleEffects of climate change and anthropogenic modification on a disturbance-dependent species in a large riverine system(John Wiley & Sons, 2017-01-11)Humans have altered nearly every natural disturbance regime on the planet through climate and land-use change, and in many instances, these processes may have interacting effects. For example, projected shifts in temperature and precipitation will likely influence disturbance regimes already affected by anthropogenic fire suppression or river impoundments. Understanding how disturbance-dependent species respond to complex and interacting environmental changes is important for conservation efforts. Using field-based demographic and movement rates, we conducted a metapopulation viability analysis for piping plovers (Charadrius melodus), a threatened disturbance-dependent species, along the Missouri and Platte rivers in the Great Plains of North America. Our aim was to better understand current and projected future metapopulation dynamics given that natural disturbances (flooding or high-flow events) have been greatly reduced by river impoundments and that climate change could further alter the disturbance regime. Although metapopulation abundance has been substantially reduced under the current suppressed disturbance regime (high-flow return interval ~ 20 yr), it could grow if the frequency of high-flow events increases as predicted under likely climate change scenarios. We found that a four-year return interval would maximize metapopulation abundance, and all subpopulations in the metapopulation would act as sources at a return interval of 15 yr or less. Regardless of disturbance frequency, the presence of even a small, stable source subpopulation buffered the metapopulation and sustained a low metapopulation extinction risk. Therefore, climate change could have positive effects in ecosystems where disturbances have been anthropogenically suppressed when climatic shifts move disturbance regimes toward more historical patterns. Furthermore, stable source populations, even if unintentionally maintained through anthropogenic activities, may be critical for the persistence of metapopulations of early-successional species under both suppressed disturbance regimes and disturbance regimes where climate change has further altered disturbance frequency or scope.