Barrier island habitat map and vegetation survey—Dauphin Island, Alabama, 2015

Enwright, Nicholas M.; Borchert, Sinéad M.; Day, Richard H.; Feher, Laura C.; Osland, Michael J.; Wang, Lei; Wang, Hongqing

doi:10.3133/ofr20171083

Cited by 11 publications

(18 citation statements)

References 14 publications

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“…At the widest point, the island extends from about 30.28 • to 30.23 • latitude (Figure 2). In December of 2015, the island had a subaerial area of about 13.6 km 2 [31]. The barrier island comprises a portion of a 105-km long Mississippi-Alabama wave-dominated barrier island chain that is backed by the shallow (<4-m depth) Mississippi Sound [32].…”

Section: Study Sitementioning

confidence: 99%

“…At the widest point, the island extends from about 30.28° to 30.23° latitude (Figure 2). In December of 2015, the island had a subaerial area of about 13.6 km 2 [31]. The barrier island comprises a …”

Section: Study Sitementioning

confidence: 99%

“…The percentage of total area within the AOI below delineated as intertidal (rounded to nearest percent) is shown graphically below the map. The location of the AOI is depicted on a generalized overview map of Dauphin Island [31]. AOI, area of interest; RTK GPS, Real-Time Kinematic Global Position System.…”

Section: Intertidal Wetlandsmentioning

confidence: 99%

“…Site accessibility related to private land was one of the main factors in the spatial distribution of the points. For more information on field data collection, see Enwright et al [31]. For this study, we created two subsets from the RTK GPS points.…”

Section: Field Data Collectionmentioning

confidence: 99%

“…The habitat type was observed for each elevation observation. These observations were collected via cluster sampling to support a habitat mapping effort [31]. Site accessibility related to private land was one of the main factors in the spatial distribution of the points.…”

Section: Field Data Collectionmentioning

confidence: 99%

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The Impact of Lidar Elevation Uncertainty on Mapping Intertidal Habitats on Barrier Islands

et al. 2017

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While airborne lidar data have revolutionized the spatial resolution that elevations can be realized, data limitations are often magnified in coastal settings. Researchers have found that airborne lidar can have a vertical error as high as 60 cm in densely vegetated intertidal areas. The uncertainty of digital elevation models is often left unaddressed; however, in low-relief environments, such as barrier islands, centimeter differences in elevation can affect exposure to physically demanding abiotic conditions, which greatly influence ecosystem structure and function. In this study, we used airborne lidar elevation data, in situ elevation observations, lidar metadata, and tide gauge information to delineate low-lying lands and the intertidal wetlands on Dauphin Island, a barrier island along the coast of Alabama, USA. We compared three different elevation error treatments, which included leaving error untreated and treatments that used Monte Carlo simulations to incorporate elevation vertical uncertainty using general information from lidar metadata and site-specific Real-Time Kinematic Global Position System data, respectively. To aid researchers in instances where limited information is available for error propagation, we conducted a sensitivity test to assess the effect of minor changes to error and bias. Treatment of error with site-specific observations produced the fewest omission errors, although the treatment using the lidar metadata had the most well-balanced results. The percent coverage of intertidal wetlands was increased by up to 80% when treating the vertical error of the digital elevation models. Based on the results from the sensitivity analysis, it could be reasonable to use error and positive bias values from literature for similar environments, conditions, and lidar acquisition characteristics in the event that collection of site-specific data is not feasible and information in the lidar metadata is insufficient. The methodology presented in this study should increase efficiency and enhance results for habitat mapping and analyses in dynamic, low-relief coastal environments.

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Section: Study Sitementioning

confidence: 99%

Section: Study Sitementioning

confidence: 99%

Section: Intertidal Wetlandsmentioning

confidence: 99%

Section: Field Data Collectionmentioning

confidence: 99%

Section: Field Data Collectionmentioning

confidence: 99%

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The Impact of Lidar Elevation Uncertainty on Mapping Intertidal Habitats on Barrier Islands

et al. 2017

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Assessing Habitat Change and Migration of Barrier Islands

Enwright

Wang

Dalyander

et al. 2021

Estuaries and Coasts

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Barrier islands are dynamic environments that experience gradual change from waves, tides, and currents, and rapid change from extreme storms. These islands are expected to change drastically over the coming century due to accelerated sea-level rise and changes in frequency and intensity of storm events. The dynamic nature of barrier islands coupled with the importance of these environments make it critical for natural resource managers to understand how habitats on barrier islands are changing or may change over time to determine when and where management actions may be needed. In this study, we applied a habitat change assessment framework, which included exploring areal coverage and distribution changes and change component analysis. Change component analysis, which breaks differences into net gain/loss and allocation difference (i.e., habitat oscillation), has not previously been used to study barrier island habitat evolution. Here, we demonstrate the approach using habitat predictions from a geomorphic modeling effort on Dauphin Island, Alabama (USA). We explored differences of habitat predictions for potential island configurations with and without a beach and dune restoration action under future conditions related to sea level and storminess. We found a potential linkage between landward migration of barrier islands and exchange, an output of change component analysis. The hypothesis may be tested to explore whether this linkage applies over space and time and whether the approach is applicable to monitoring landward migration of coastal wetlands. Collectively, our results highlight the utility of change component analysis for monitoring and quantifying barrier island habitat change and migration.

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