A Bayesian Approach to Predict Sub-Annual Beach Change and Recovery

Wilson, Kat; Lentz, Erika E.; Miselis, Jennifer L.; Safak, Ilgar; Brenner, Owen T.

doi:10.1007/s12237-018-0444-1

Cited by 3 publications

(3 citation statements)

References 56 publications

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“…The NPS I&M program was able to collect post-storm data in a timely manner using well-established, standardized methods (Oakley et al 2003;Perkins et al 2016;Sergeant et al 2012). This effort has provided insight into understanding the natural resiliency and recovery of park systems to a powerful storm event like Hurricane Sandy (Wilson et al 2019).…”

Section: Baseline Science and Monitoringmentioning

confidence: 99%

“…As other barrier islands breach in future storms, having the experience of monitoring the water quality, geomorphic response, and ecosystem benefits documented by allowing the Fire Island breach to remain open may help shape future decision-making, as well as monitoring plans. The demonstration of geomorphic resilience at Fire Island, NY, which is modeled by Wilson et al (2019), is further explored by Psuty et al (2020), documenting dune displacement and recovery at Fort Tilden, Gateway National Recreation Area, NY, including interactions with groins and bulkheads that disrupt sediment transport.…”

Section: Overview Of Papers In Special Sectionmentioning

confidence: 99%

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Coastal Impacts, Recovery, and Resilience Post-Hurricane Sandy in the Northeastern US

BABSON

Bennett

Adamowicz

et al. 2020

Estuaries and Coasts

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Post-Hurricane Sandy research has improved our understanding of coastal resilience during major storm events, accelerated sea level rise, and other climate-related factors, helping to enhance science-based decision-making, restoration, and management of coastal systems. The central question this special section examines is: “looking across the breadth of research, natural resource management actions and restoration projects post-Hurricane Sandy, what can we say about coastal impact, recovery, and resilience to prepare for increasing impacts of future storms?” These five studies, along with lessons from other published and unpublished research, advance our understanding beyond just the documentation of hurricane impacts but also highlights both natural and managed recovery, thereby advancing the developing field of coastal resilience.

show abstract

Section: Baseline Science and Monitoringmentioning

confidence: 99%

Section: Overview Of Papers In Special Sectionmentioning

confidence: 99%

Coastal Impacts, Recovery, and Resilience Post-Hurricane Sandy in the Northeastern US

BABSON

Bennett

Adamowicz

et al. 2020

Estuaries and Coasts

View full text Add to dashboard Cite

show abstract

“…At the largest scales (e.g., 5 km shoreline segments), BNs have been used to investigate how shoreline change rates (i.e., erosion and accretion) are likely to respond to multi-decadal changes in sea level (Gutierrez et al, 2011(Gutierrez et al, , 2014. At moderate spatiotemporal scales (i.e., decadal and 30-m landscape scales), BNs have been developed to explore the potential for coastal landscape dynamic response to SLR (Lentz et al, 2016); SLR-driven evolution in barrier island characteristics (e.g., elevation, beach width along shore-normal transects spaced in 50-m intervals; Gutierrez et al, 2015); and storm-driven changes to barrier island characteristics (50-m transects; Plant & Stockdon, 2012;Plant et al, 2016;Wilson et al, 2019). Finally, BNs of seasonal habitat availability given coastal landform conditions (e.g., vegetation density, substrate type) have been developed for species like piping plovers (5-m cells; Zeigler et al, 2021) and beach mice (Peromyscus poliontus subspecies; 30-m cells; Cronin et al, 2021).…”

mentioning

confidence: 99%

Integrating Bayesian Networks to Forecast Sea‐Level Rise Impacts on Barrier Island Characteristics and Habitat Availability

Gutierrez

Zeigler

Plant

et al. 2022

Earth and Space Science

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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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Subaerial Beach Profiles: the Application of Erosion and Accretion Balanced Approach in Southwestern Maine, USA

Riazi

Türker

Slovinsky

2022

Estuaries and Coasts

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A Bayesian Approach to Predict Sub-Annual Beach Change and Recovery

Cited by 3 publications

References 56 publications

Coastal Impacts, Recovery, and Resilience Post-Hurricane Sandy in the Northeastern US

Coastal Impacts, Recovery, and Resilience Post-Hurricane Sandy in the Northeastern US

Integrating Bayesian Networks to Forecast Sea‐Level Rise Impacts on Barrier Island Characteristics and Habitat Availability

Subaerial Beach Profiles: the Application of Erosion and Accretion Balanced Approach in Southwestern Maine, USA

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