Zeigler
Sara L.
Zeigler
Sara L.
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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) Zeigler, Sara L. ; Gutierrez, Benjamin T. ; Lentz, Erika E. ; Plant, Nathaniel G. ; Sturdivant, Emily ; Doran, Kara S.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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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) Zeigler, Sara L. ; Gutierrez, Benjamin T. ; Sturdivant, Emily ; Catlin, Daniel H. ; Fraser, James D. ; Hecht, Anne ; Karpanty, Sarah M. ; Plant, Nathaniel G. ; Thieler, E. RobertCoastal 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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ArticleEffects of climate change and anthropogenic modification on a disturbance-dependent species in a large riverine system(John Wiley & Sons, 2017-01-11) Zeigler, Sara L. ; Catlin, Daniel H. ; Brown, Mary Bomberger ; Fraser, James D. ; Dinan, Lauren R. ; Hunt, Kelsi L. ; Jorgensen, Joel G. ; Karpanty, Sarah M.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.
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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) Zeigler, Sara L. ; Gutierrez, Benjamin T. ; Hecht, Anne ; Plant, Nathaniel G. ; Sturdivant, EmilyHabitat 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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ArticleSmartphone technologies and Bayesian networks to assess shorebird habitat selection(John Wiley & Sons, 2017-09-28) Zeigler, Sara L. ; Thieler, E. Robert ; Gutierrez, Benjamin T. ; Plant, Nathaniel G. ; Hines, Megan K. ; Fraser, James D. ; Catlin, Daniel H. ; Karpanty, Sarah M.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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ArticleSmartphone-based distributed data collection enables rapid assessment of shorebird habitat suitability(Public Library of Science, 2016-11-09) Thieler, E. Robert ; Zeigler, Sara L. ; Winslow, Luke A. ; Hines, Megan K. ; Read, Jordan S. ; Walker, Jordan I.Understanding and managing dynamic coastal landscapes for beach-dependent species requires biological and geological data across the range of relevant environments and habitats. It is difficult to acquire such information; data often have limited focus due to resource constraints, are collected by non-specialists, or lack observational uniformity. We developed an open-source smartphone application called iPlover that addresses these difficulties in collecting biogeomorphic information at piping plover (Charadrius melodus) nest sites on coastal beaches. This paper describes iPlover development and evaluates data quality and utility following two years of collection (n = 1799 data points over 1500 km of coast between Maine and North Carolina, USA). We found strong agreement between field user and expert assessments and high model skill when data were used for habitat suitability prediction. Methods used here to develop and deploy a distributed data collection system have broad applicability to interdisciplinary environmental monitoring and modeling.
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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) Gutierrez, Benjamin T. ; Zeigler, Sara L. ; Lentz, Erika ; Sturdivant, Emily J. ; Plant, Nathaniel G.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.