Joanne N. Halls

Application of digital bathymetry data in an analysis of flushing times of two large estuaries

The objectives of this study were: (1) define the best method of using digital bathymetric data to compute estuarine flushing time using the fraction of freshwater method and (2) use this method to compare flushing times of two neighboring estuaries of different trophic state. We examined the sensitivity of the fraction of freshwater method to various methods of calculating estuarine volume using digital bathymetric data. Raster and vector bathymetry data are available from the National Geophysical Data Center (NGDC), and can be used to calculate estuarine volume using a geographic information system (GIS). The vector data was of higher spatial resolution than the raster data (NGDC Coastal Relief Model) and produced a higher estuarine volume, but did not produce significantly different flushing times than the raster data. Water column salinity data can be used to quantify segmented vertical freshwater volumes for integration along the estuary, thereby providing a two-dimensional freshwater distribution profile of the estuary. The vertical representation of water column salinity did not produce flushing times significantly different from a vertically averaged salinity method. Processing and analysis of the Coastal Relief Model raster data is faster and less complex than processing the vector data available from the NGDC. We conclude that the Coastal Relief Model raster data is the preferred bathymetric data source, and that representation of vertical salinity distribution is unnecessary for the analysis of estuaries with morphology similar to the Cape Fear Rivers. After using the Cape Fear River estuary as a test site for the above comparisons, we applied the preferred method to the New River estuary. In addition to having a direct connection with the ocean, the Cape Fear River has much higher freshwater inflow than the New River, and therefore has a much faster mean flushing time. The Cape Fear River estuary flushing time ranged from 1 to 22 days, while the New River estuary ranged from 8 to 187 days. Similar seasonal patterns were observed in both estuaries: short flushing times occurred during the high-flow winter months and long flushing times occurred during the low-flow summer months.

Habitat Mapping and Change Assessment of Coastal Environments: An Examination of WorldView-2, QuickBird, and IKONOS Satellite Imagery and Airborne LiDAR for Mapping Barrier Island Habitats

Habitat mapping can be accomplished using many techniques and types of data. There are pros and cons for each technique and dataset, therefore, the goal of this project was to investigate the capabilities of new satellite sensor technology and to assess map accuracy for a variety of image classification techniques based on hundreds of field-work sites. The study area was Masonboro Island, an undeveloped area in coastal North Carolina, USA. Using the best map results, a habitat change assessment was conducted between 2002 and 2010. WorldView-2, QuickBird, and IKONOS satellite sensors were tested using unsupervised and supervised methods using a variety of spectral band combinations. Light Detection and Ranging (LiDAR) elevation and texture data pan-sharpening, and spatial filtering were also tested. In total, 200 maps were generated and results indicated that WorldView-2 was consistently more accurate than QuickBird and IKONOS. Supervised maps were more accurate than unsupervised in 80% of the maps. Pan-sharpening the images did not consistently improve map accuracy but using a majority filter generally increased map accuracy. During the relatively short eight-year period, 20% of the coastal study area changed with intertidal marsh experiencing the most change. Smaller habitat classes changed substantially as well. For example, 84% of upland scrub-shrub experienced change. These results document the dynamic nature of coastal habitats, validate the use of the relatively new Worldview-2 sensor, and may be used to guide future coastal habitat mapping.

Integration of Satellite Telemetry Data and Land Cover Imagery: A Study of Migratory Cranes in Northeast Asia

The present study describes a procedure for quantitatively analyzing satellite telemetry data to identify interspecific land use differences among four threatened crane species. The inherent inaccuracy of satellite telemetry data points, the temporal autocorrelation of those points, and the resolution of two land-cover imagery products from the IGBP-DISCover Global Land-Cover Characterization Project (derived from AVHRR data) were assessed and integrated in a GIS. Satellite telemetry is a system where animals are tracked using battery-operated transmitters and locations are calculated using triangulation from satellites. Using the variable spatial inaccuracy of the telemetry locations, each point was buffered using a radius based on the accuracy of the point, and then intersected with the land cover imagery. The research concluded that the methodology is valuable for studies of birds at a regional scale, with interspecific differences clearly evident, but that diurnal and nocturnal differences were not discernable due to the coarse resolution of both satellite telemetry and land-cover data.

A Spatial Sensitivity Analysis of Land Use Characteristics and Phosphorus Levels in Small Tidal Creek Estuaries of North Carolina, USA

ABSTRACT Small tidal creek estuaries provide important ecological habitats that are increasingly under pressure from urban expansion. In south-eastern North Carolina these coastal counties are among the fastest growing counties in the state. In New Hanover County alone, urbanized land use has increased by 100% between 1976 and 1999. This urbanization has led to an encroachment and loss of these valuable resources. To study the impacts of urbanization, five tidal creeks were analyzed for land use characteristics and phosphorus compounds in sediments. The goals of this study were: a) identify the land use characteristics of the five tidal creek watersheds within New Hanover County; b) compare and contrast these watershed land use characteristics with concentrations of phosphorus measured from sediment samples taken at various locations within these watersheds; and c) perform a spatial sensitivity analysis of the contributing area to these sample locations to determine the relationships between land use and concentrations of inorganic phosphorus. The tidal influences and minimal topographic relief within these watersheds made it impossible to accurately map the drainage area for each sampling site and therefore a spatial sensitivity analysis method was developed to analyze the land use adjacent to each sampling site. The land use potentially contributing to each sampling site was calculated using three radius measurements (0.25, 0.5, and 0.75 mile). Results indicate that the there is no significant statistical relationship between the various types of land use development (e.g. commercial, industrial, transportation, etc.) and the percentage of inorganic phosphorus in the tidal creeks. In comparing simply developed versus undeveloped land, there is a nonlinear relationship between the percentage of developed land and the percentage of inorganic phosphorus. In comparing the buffer sizes, the level of geographic analysis is most closely related to the percent inorganic phosphorus at the 0.25 and 0.5 mile radii and less at 0.75 mile radius. Results from this study illustrate the usefulness for careful geographic scrutiny and robust spatial analysis.

An Automated Model to Classify Barrier Island Geomorphology Using Lidar Data and Change Analysis (1998–2014)

Previous research has documented the usefulness of Lidar data to derive a variety of topographic products (e.g., DEM, DTM, canopy and forest structure, and urban infrastructure). Lidar has been used to map coastal environments and geomorphology; however, there is no comprehensive model to derive coastal geomorphology. Therefore, the purpose of this project was to build on existing research and develop an automated modeling approach to classify coastal geomorphology across barrier islands. The model was developed and tested at four sites in North Carolina including two undeveloped and two developed islands. Barrier island geomorphology is shaped by natural coastal processes, such as storms and longshore sediment transport, as well as human influences, such as beach nourishment and urban development. The model was developed to classify ten geomorphic features over four time-steps from 1998 to 2014. Model results were compared to compute change through time and derived the rate and direction of feature movement. Tropical storms and hurricanes had the most influence in geomorphic change and movement. On the developed islands, there was less influence of storms due to the inability of features to move because of coastal infrastructure. From 2005 to 2010, beach nourishment was the dominant influence on developed beaches because this activity ameliorated the natural tendency for an island to erode. Understanding how natural and anthropogenic processes influence barrier island geomorphology is critical to predicting an island’s future response to changing environmental factors such as sea-level rise. The development of an automated model enables it to be replicated in other locations where policy makers and coastal managers may use this information to make development and conservation decisions.

Submerged and Emergent Land Cover and Bathymetric Mapping of Estuarine Habitats Using WorldView-2 and LiDAR Imagery

Tidal creeks are small estuarine watersheds characterized by low freshwater input, marine to brackish salinity, and subtidal, intertidal, and supratidal habitats. Most people are familiar with large rivers and estuaries, but the smaller tidal watersheds comprise a greater percentage of the coastline. As the population along coasts rises there is growing concern about water quality and increased sedimentation rates. Therefore, these smaller tidal creek watersheds are at risk to pollution, decreased environmental health, and deterioration of protective salt marshes. The purpose of this study was to test methods for high spatial resolution mapping of benthic (submerged) and emergent habitats as well as the derivation of bathymetry using DigitalGlobe’s WorldView-2 imagery. An intensive field effort was conducted to test and assess several image processing techniques. Results concluded that: (1) supervised habitat classification produced the highest map accuracy (95%); (2) sand, water, scrub/shrub, and docks/rubble were mapped the most accurately at greater than 95%; (3) saltmarsh habitats (high and low density cordgrass, Spartina alterniflora, and black needlerush, Juncus roemerianus), mud, and oyster beds were between 80 and 85% accurate; (4) pan-sharpening and atmospheric correction did not improve map accuracy; (5) LiDAR (light detection and ranging) data increased habitat map accuracy; and (6) WorldView-2 imagery was capable of deriving water depth and these data increased the map accuracy of benthic habitats. The project produced habitat maps for benthic and emergent species at high spatial resolution (4 m2) which will be useful for studying the dynamic processes in this tidal environment. The data and methods developed here could be used by state and local government planning agencies to assess potential long-term changes and develop appropriate management strategies.

Potential for a Simple GPS-Based Binary Logit Model to Predict Fishing Effort in a Vertical Hook-and-Line Reef Fish Fishery

Abstract Accurate fishing effort information is fundamental to the successful management of fisheries resources. Automated, independent, and reliable methods for quantifying fishing effort are needed. The use of vessel speed from Global Positioning System (GPS) data to identify fishing activity has worked well for trawl fisheries but has been less successful in stationary fisheries. Therefore, five trips on four vessels from a vertical hook-and-line reef fish fishery were used to examine the efficacy of GPS (speed and time) and electronic video monitoring (EVM) sensor (drum and video) data to corroborate an observers account of effort using binary logistic regression classification (logit) models as well as a simple speed and time filter (filter). One minute was the minimum data collection interval examined that documented 100% of fishing events. As no fishing occurred at night, opportunistically defined as the 7 h between 2200 and 0500 hours, these records were excluded from analyses. During the day, vessels spent on average 45.2% of the time fishing. Classification success of the approaches examined ranged from 82.4% to 89.5%. Models that included both GPS and EVM sensor data outperformed the filter and GPS-only models. In general, the filter and most model results can be used as a proxy for observer effort data, at least for the trips examined here. The GPS-based speed + time logit model was chosen as the preferred approach because of its discriminatory power compared with the filter and the existing widespread use and lower costs of GPS data collection relative to EVM systems and sensors. The speed + time logit model outlined here may have broad utility in this and similar vertical-line fisheries, including the offshore marine recreational fishing sector.

Nesting Patterns of Loggerhead Sea Turtles (Caretta caretta): Development of a Multiple Regression Model Tested in North Carolina, USA

Numerous environmental conditions may influence when a female Loggerhead sea turtle (Caretta caretta) selects a nesting site. Limited research has used Geographic Information Systems (GIS) and statistical analysis to study sea turtle spatial patterns and temporal trends. Therefore, the goals of this research were to identify areas that were most prevalent for nesting and to test social and environmental variables to create a nesting suitability predictive model. Data were analyzed at all barrier island beaches in North Carolina, USA (515 km) and several variables were statistically significant: distance to hardened structures, beach nourishment, house density, distance to inlets, and beach elevation, slope, and width. Interestingly, variables that were not significant were population density, proximity to the Gulf Stream, and beach aspect. Several statistical techniques were tested and Negative Binomial Distribution produced good regional results while Geographically Weighted Regression models successfully predicted the number of nests with an average of 75% of the variance explained. Therefore, the combination of traditional and spatial statistics provided insightful predictive modeling results that may be incorporated into management strategies and may have important implications for the designation of critical Loggerhead nesting habitats.

Distribution Pattern of Red Fox (Vulpes vulpes) Dens and Spatial Relationships with Sea Turtle Nests, Recreation, and Environmental Characteristics

Although sea turtles are formidable prey as adults, their nests are highly vulnerable to terrestrial predation. Along the Southeastern coast of the United States, a primary predator of sea turtle nests is the red fox (Vulpes vulpes). Examining the relationship between fox populations and nest predation is often difficult due to coastal development. Masonboro Island, North Carolina is an undeveloped, natural, 13-km-long barrier island complex that is a component of the North Carolina National Estuarine Research Reserve (NERR). Masonboro Island consists of beaches, a dune ridge, back barrier flats, an expansive salt marsh, a lagoon, and spoil islands seaward of the Intracoastal Waterway. A field survey, which was conducted each spring from 2009 through 2012, recorded den entrance coordinates based upon recent use by foxes. Sea turtle nests were located using a similar survey methodology, which identifies viable and predated nests as well as false crawls. A series of spatial-temporal pattern analysis techniques were used to identify trends through time. The results indicated that: (1) fox den entrances and predated sea turtle nests were clustered throughout the island (p = 0.01); (2) den entrances in the northern part of the island were closer to the sea turtle nests than other locations on the island; (3) fox den entrances were positively correlated (p = 0.01) with dune height, (4) fox den entrances were located closer to the island boat access sites than expected (p = 0.01). A variety of spatial sensitivity tests were used to test the validity of the statistically significant cluster analyses. A Geographically Weighted Regression model was created to predict the location of fox dens using dune elevation, the distance to predated sea turtle nests, and the distance to boat access sites. The model accounted for 40% of the variance and had a small residual error, which indicates that the independent variables were statistically valid. Results from this project will be used by the NC NERR staff to develop management plans and to further study fox-related impacts on the island. For example, given the higher density of fox den entrances on the northern part of the island, managers may consider targeted wildlife control measures during the sea turtle nesting season to diminish predation.