Relationships between regional coastal land cover distributions and
elevation reveal data uncertainty in a sea-level rise impacts model

Lentz, Erika E.; Plant, Nathaniel G.; Thieler, E. Robert

doi:10.5194/esurf-2018-79

Cited by 4 publications

(7 citation statements)

References 30 publications

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“…We forced connections from the substrate type, vegetation density, and distance to MOSH nodes to the resource type node and from the geomorphic setting to the distance to MOSH node because prior studies have found prominent relationships among similar variables (Patterson 1988, MacIvor 1990, Patterson et al 1991, Jones 1997, Cohen et al 2008, Maslo et al 2011). We also forced connections among elevation, distance to ocean, and geomorphic setting because of known inherent correlations among these variables in coastal systems (Young et al 2011, Halls et al 2018, Enwright et al 2019, Lentz et al 2019).…”

Section: Methodsmentioning

confidence: 99%

Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast

et al. 2021

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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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Section: Methodsmentioning

confidence: 99%

Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast

et al. 2021

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“…Here it is important to note the inherent relationship between coastal land cover and elevation variables, wherein elevation acts as an important control on land cover distributions (Zinnert et al 2017;Lentz et al 2019). For example, sites that supported a higher percentage of forests also had a higher percentage area that was unlikely to be inundated (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…For example, sites that supported a higher percentage of forests also had a higher percentage area that was unlikely to be inundated (Fig. 5); however, sites with forests also tend to contain higher elevation zones that make those sites less vulnerable to SLR (Zinnert et al 2016b;Lentz et al 2019). The correlated relationship between land cover, elevation zone, and SLR vulnerability makes it difficult to separate whether it's the higher elevations or ecosystem feedbacks that make a site better able to respond dynamically to SLR-although it is likely that both affect inundation vulnerability through time (Corenblit et al 2011;Brantley et al 2014;Zinnert et al 2017 and references therein).…”

Section: Discussionmentioning

confidence: 99%

“…For example, marshes and beaches tend to be found at lower elevations than forests and uplands. Doing so allowed better resolution of uncertainties tied to these data inputs and to reduce error (Lentz et al 2019). The likelihood of inundation assigned to different land cover types compared AE with the generalized SLR tipping points (i.e.…”

Section: Methodsmentioning

confidence: 99%

“…In this analysis, 'land cover diversity' was used to indicate the number and proportion of land cover types within the site boundary up to the 10-m elevation contour. As demonstrated in Lentz et al (2019) and Zinnert et al (2017), elevation and land cover data in the coastal zone have an inherent correlation. For example, marshes and beaches tend to be low-lying, whereas, by comparison, upland environments occur at higher elevations.…”

Section: Site-specific Determination and Diversity Assessmentmentioning

confidence: 97%

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Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast

et al. 2020

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Context Coastal landscapes evolve in response to sea-level rise (SLR) through a variety of geologic processes and ecological feedbacks. When the SLR rate surpasses the rate at which these processes build elevation and drive lateral migration, inundation is likely. Objectives To examine the role of land cover diversity and composition in landscape response to SLR across the northeastern United States. Methods Using an existing probabilistic framework, we quantify the probability of inundation, a measure of vulnerability, under different SLR scenarios on the coastal landscape. Resistant areas—wherein a dynamic response is anticipated—are defined as unlikely (p < 0.33) to inundate. Results are assessed regionally for different land cover types and at 26 sites representing varying levels of land cover diversity. Results Modeling results suggest that by the 2050s, 44% of low-lying, habitable land in the region is unlikely to inundate, further declining to 36% by the 2080s. In addition to a decrease in SLR resistance with time, these results show an increasing uncertainty that the coastal landscape will continue to evolve in response to SLR as it has in the past. We also find that resistance to SLR is correlated with land cover composition, wherein sites containing land cover types adaptable to SLR impacts show greater potential to undergo biogeomorphic state shifts rather than inundating with time. Conclusions Our findings support other studies that have highlighted the importance of ecological composition and diversity in stabilizing the physical landscape and suggest that flexible planning strategies, such as adaptive management, are particularly well suited for SLR preparation in diverse coastal settings.

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Quantifying the impacts of future sea level rise on nesting sea turtles in the southeastern United States

Lyons

Holle

Caffrey

et al. 2020

Ecological Applications

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Sandy beaches, a necessary habitat for nesting sea turtles, are increasingly under threat as they become squeezed between human infrastructure and shorelines that are changing as a result of rising sea levels. Forecasting where shifting sandy beaches will be obstructed and how that directly impacts coastal nesting species is necessary for successful conservation and management. Predicting changes to coastal nesting areas is difficult because of a lack of consensus on the physical attributes used by females in nesting site choice. In this study, we leveraged long‐term data sets of nesting localities for two sea turtle species, loggerhead sea turtle, Caretta caretta, and green sea turtle, Chelonia mydas , within four barrier island National Seashores in the southeastern United States to predict future nesting beach area based on where these species currently nest in relation to mean high water. We predicted the future location of nesting areas based on a sea level rise scenario for 2100 and quantified how impervious surfaces will inhibit future beach movement, which will impact both the total available nesting area and the percentage of nesting area predicted to flood following a hurricane‐related storm surge. Contrary to our expectations, those barrier islands with the greatest levels of human infrastructure were not projected to experience the greatest percentage of sea turtle nesting area loss due to sea level rise or storm surge events. Notably, loss of nesting beach areas will not have equal impacts across the four Seashores; the Seashore projected to have the least amount of total nesting area lost and percentage nesting area lost currently has the highest nesting densities of our two study species, suggesting that even low levels of beach loss could have substantial impacts on future nesting densities and disproportionate impacts on the population growth of these species. Our novel method of estimating current and future nesting beach area can be broadly applied to studies requiring a bounded area that encompasses the part of a beach used by nesting coastal species and will be useful in comparing future global nesting densities and population trajectories under projected future sea level rise and storm surge activity.

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Relationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model

Cited by 4 publications

References 30 publications

Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast

Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast

Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast

Quantifying the impacts of future sea level rise on nesting sea turtles in the southeastern United States

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