Geology topics

Sara L. Zeigler

Publications and source records attributed to Sara L. Zeigler.

17 recordsLinked to original sources

USGS2026

Challenges and opportunities for national-scale projections of future coastal landscape change

Local to global scale projections of future coastal landscape change are essential to improve land and resource management decisions that aim to prepare for and reduce risk exposure to impending coastal hazards. However, the availability of actionable knowledge is often limited due to the complexity of drivers of change, their consequences, and uncertainties that span disciplines. Varying spatial and temporal scales of physical processes that occur on landscapes with differing levels of coastal development and modification complicate decision-making. This paper reviews advances in observational approaches, modeling, and quantification of uncertainty to support the next generation of coastal change projections. We also highlight transdisciplinary opportunities for making this information more accessible and useful to support decision-making in the coastal zone. This includes consideration of different levels of user engagement to address specific needs, as well as resources and mechanisms that can support knowledge transfer broadly. A central recommendation is the development of a coordinated framework to support research integration including three components: accounting for relevant drivers, processes, and feedbacks; working with users to identify their information needs; and generating meaningful projections and uncertainty. Actions that would support such frameworks include the evaluation of models through coordinated research approaches and multi-model comparisons; ongoing investments in observations and data-driven approaches necessary to understand this complex environment; expansion of modeling capabilities using novel techniques; prioritization of co-development efforts between researchers and users; and continued training and support for transdisciplinary research.

Alaska, California, Florida, New York↗

USGS2025

Projecting management-relevant change of undeveloped coastal barriers with the Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) v1.0

Models of coastal barrier geomorphic and ecologic change are valuable tools for understanding and predicting when, where, and how barriers evolve and transition between ecogeomorphic states. Few existing models of barrier systems are designed to operate over spatiotemporal scales congruous with effective management practices (i.e., decades/kilometers, referred to herein as “mesoscales”), incorporate important ecogeomorphic feedbacks, and provide probabilistic projections of future change. Here, we present a new numerical model designed to address these gaps by explicitly yet efficiently simulating coupled aeolian, marine, vegetation, and shoreline components of barrier evolution over spatiotemporal scales relevant to management. The Mesoscale Explicit Ecogeomorphic Barrier model (MEEB) simulates subaerial ecomorphologic change of undeveloped barrier systems over kilometers and decades using meter-scale spatial resolution and weekly time steps. MEEB applies simplified parameterizations to represent and couple key ecogeomorphic processes: dune growth, vegetation expansion and mortality, beach and foredune erosion, barrier overwash, and shoreline and shoreface change. The model is parameterized and calibrated with observed elevation, vegetation, and water level data for a case study site of North Core Banks, NC, USA. Simulated ecogeomorphic change in model hindcasts agrees well with observations, demonstrating both favorable skill scores and qualitatively correct behavior. We also describe an additional model framework for producing probabilistic projections that account for uncertainties related to future forcing conditions and intrinsic stochastic dynamics and demonstrate the probabilistic framework's utility with example forecast simulations. As a mesoscale model, MEEB is designed to investigate questions about future barrier ecogeomorphic change of moderate complexity, offering semi-qualitative predictions and semi-quantitative explanations. For example, MEEB can be used to investigate how climate-induced shifts in ecological composition may alter the likelihood of morphologic impacts or to generate probabilistic projections of ecogeomorphic state change.

Geoscientific Model Development↗

USGS2025

An expert elicitation to inform coastal management decision-making for mitigating future hazards

A scientific expert elicitation was conducted to address the feasibility of restoring coastal environments in response to future hazards to best meet management objectives. Subject matter experts produced probabilistic estimates of coastal change metrics used to evaluate decision objectives and alternatives informed by a stakeholder advisory group. Changes in salt marsh extents, storm surge flooding and barrier island morphology by the year 2050 were estimated for three scenarios of management actions (no action, interior headland restoration, beach and dune nourishment), while also considering the effects of future sea level rise (SLR). Collectively the participants were confident in their expectations of increased storm surge flooding with SLR, regardless of management interventions. Estimates of marsh response had large uncertainty, but experts generally hypothesized that marsh area would decrease with increasing SLR if no action was taken, especially in areas already experiencing marsh deterioration. There was agreement that dune heights and barrier island widths would decrease with SLR if no action was taken. Experts felt that beach and dune nourishment may reduce the amount of erosion under future SLR. All experts recognized the dynamic effects of SLR and feedback between bio-geo-physical processes that govern coastal systems. Participants agreed that size and location of management actions were important factors for influencing the coastal response. Expert elicitation is novel in the context of coastal management decision making and can be a useful tool for informing future scientific needs and providing rapid results to end users to inform reallocation of resources surrounding research and application.

Alabama, Mississippi↗

USGS2024

Shaping the coast: Accounting for the human wildcard in projections of future change

Coastal change and evolution are the product of physical drivers (e.g., waves) tightly coupled with human behavior. As climate change impacts intensify, demand is increasing for information on where, when, and how coastal areas may change in the future. Although considerable research investments have been made in understanding the physical drivers and processes that modify and shape coastal environments, many do not account for human behavior, compromising the accuracy of comprehensive future change predictions. We outline four social science approaches—historic case studies, simulations, longitudinal studies, and longitudinal studies supported by experimental data—that can be coupled with physical change information to support transdisciplinary understanding of future change. A fundamental need for each approach is more and better empirical data to better gauge human behavior. In addition, foundational investments in transdisciplinary collaboration help research teams support the integration of these approaches.

Earth's Future↗

USGS2024

U.S. Geological Survey climate science plan—Future research directions

Executive Summary Climate is the primary driver of environmental change and is a key consideration in defining science priorities conducted across all mission areas in the U.S. Geological Survey (USGS). Recognizing the importance of climate change to its future research agenda, the USGS’s Climate Science Steering Committee requested the development of a Climate Science Plan to identify future research directions. Subject matter experts from across the Bureau formed the USGS Climate Science Plan Writing Team, which convened in September 2022 to identify and outline the major climate science topics of future concern and develop an integrated approach to conducting climate science in support of the USGS and U.S. Department of the Interior missions. The resulting USGS Climate Science Plan identifies three major priorities under which USGS climate science proceeds: (1) characterize climate change and associated impacts, (2) assess climate change risks and develop approaches to mitigate climate change, and (3) provide climate science tools and support. The Climate Science Plan identifies 12 specific goals to achieve the outcomes of the three priorities. Conduct long-term, broad-scale, and multidisciplinary measurements and monitoring and research activities to define, quantify, and predict the impacts of climate change on natural and human systems; Provide leadership to standardize measuring, monitoring, reporting, and verifying greenhouse gas emissions, lateral carbon fluxes, and carbon sinks across lands managed by the U.S. Department of the Interior (DOI); Provide science capacity, training, tools, and infrastructure to Tribal partners; support Tribal-led science initiatives; Conduct climate change research in partnership with the broader climate science community; Develop improved data synthesis methods through collaborative and open science across mission areas and between the USGS and agency partners; Translate climate change impacts into risk assessments in support of risk management strategies; Develop new and improved risk assessments, models, and approaches for mitigating climate change, adapting to its impacts, and reducing uncertainties; design early warning systems for risk mitigation; Investigate climate change mitigation strategies and create decision science support tools to inform climate change mitigation and adaptation; Provide a framework that facilitates knowledge co-production needed to inform policy decisions; Provide access to USGS data and information through novel integration and visualization approaches; Build capacity within USGS and DOI through development of scientific training curricula; and Coordinate science and capacity building efforts broadly across the Federal Government. To achieve these goals, the USGS Climate Science Plan also outlines climate science guidelines—key elements for conducting climate-based research—as well as emerging opportunities to support successful climate science. The USGS Climate Science Plan provided in this circular will guide future research priorities and science-support investments, as well as continued development of the climate workforce for decades to come, ensuring that the USGS continues to serve as one of the Nation’s leading climate science agencies.

Circular↗

USGS2023

Sound-side inundation and seaward erosion of a barrier island during hurricane landfall

Barrier islands are especially vulnerable to hurricanes and other large storms, owing to their mobile composition, low elevations, and detachment from the mainland. Conceptual models of barrier-island evolution emphasize ocean-side processes that drive landward migration through overwash, inlet migration, and aeolian transport. In contrast, we found that the impact of Hurricane Dorian (2019) on North Core Banks, a 36-km barrier island on the Outer Banks of North Carolina, was primarily driven by inundation of the island from Pamlico Sound, as evidenced by storm-surge model results and observations of high-water marks and wrack lines. Analysis of photogrammetry products from aerial imagery collected before and after the storm indicate the loss of about 18% of the subaerial volume of the island through the formation of over 80 erosional washout channels extending from the marsh and washover platform, through gaps in the foredunes, to the shoreline. The washout channels were largely co-located with washover fans deposited by earlier events. Net seaward export of sediment resulted in the formation of deltaic bars offshore of the channels, which became part of the post-storm berm recovery by onshore bar migration and partial filling of the washouts with washover deposits within 2 months. This event represents a volumetric setback in the overwash/rollover behavior required for barrier transgression, but the new ponds and lowland habitats may provide beneficial habit for endangered species and will likely persist for years.

North Carolina↗

USGS2023

Decision science as a framework for combining geomorphological and ecological modeling for the management of coastal systems

The loss of ecosystem services due to climate change and coastal development is projected to have significant impacts on local economies and conservation of natural resources. Consequently, there has been an increase in coastal management activities such as living shorelines, oyster reef restoration, marsh restoration, beach and dune nourishment, and revegetation projects. Coastal management decisions are complex and include challenging trade-offs. Decision science offers a useful framework to address such complex problems. Here, we provide a synthesis about how decision science can help to integrate research from multiple disciplines (physical and life sciences) with management of coastal and marine systems. Specifically, we discuss the importance of considering concepts and techniques from ecology, coastal geology, geomorphology, climate science, oceanography, and decision analysis when developing conservation plans for coastal restoration. We illustrate the process with several coastal restoration studies. Our capstone example is based on a recent barrier island restoration assessment project at Dauphin Island, Alabama, which included the development of geomorphological and ecological models. We show how decision science can be used as a framework to combine geomorphological and ecological modeling to help inform management decisions while considering uncertainty about system changes and risk tolerance. We also build on our examples through a review of recently developed techniques for spatial conservation planning for land acquisition decisions and the application of adaptive management for sequential decisions.

Alabama↗

USGS2022

Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability

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.

New York↗

USGS2021

Impacts of sediment removal from and placement in coastal barrier island systems

Executive Summary On June 24, 2019, Congressman Raul Grijalva of Arizona, Chair of the House Committee on Natural Resources, sent a letter to the directors of the U.S. Fish and Wildlife Service and the U.S. Geological Survey to request their assistance in answering questions regarding coastal sediment resource management within the Coastal Barrier Resources System as defined by the Coastal Barrier Resources Act (Public Law 97–348; 96 Stat. 1653; 16 U.S.C. 3501 et seq.). For the purposes of this response, coastal sediment resource management refers to the removal of sediment from one part of a barrier island system for placement in another part of the coastal system, for either hazard mitigation (for example, erosion or flood control) or coastal restoration (for example, expansion or restoration of beach, dune, and [or] marsh habitats). The specific topics of concern are as follows (paraphrased from Congressman Grijalva’s letter): 1. Disruption of coastal sediment supply resulting from sediment removal and placement, including the replenishment rate of removed sediments and impacts to other components of the barrier island system (discussed in sec. 3). 2. Physical and biological impacts of sediment removal and placement on benthic habitats (discussed in sec. 4). 3. Impacts of sediment removal and placement on fish and other marine species (discussed in sec. 5). 4. Changes in migratory bird nesting and foraging habitats resulting from sediment removal and placement (discussed in sec. 6). 5. Long-term impacts of sediment removal and placement on physical coastal resiliency (discussed in sec. 7).

Open-File Report↗

USGS2020

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

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.

Connecticut, Maine, Maryland, Massachusetts, New H↗

USGS2019

A pragmatic approach for comparing species distribution models to increasing confidence in managing piping plover habitat

Conservation management often requires decision-making without perfect knowledge of the at-risk species or ecosystem. Species distribution models (SDMs) are useful but largely under-utilized due to model uncertainty. We provide a case study that utilizes an ensemble modeling approach of two independently derived SDMs to explicitly address common modeling impediments and to directly inform conservation decision-making for piping plovers in a heavily populated mid-Atlantic (USA) coastal zone. We summarized previously published Bayesian network and maximum entropy modeling approaches to highlight similarities and differences in model structure, and we compared the relative importance of predictors used. Despite marked differences in analytical approach, the relative importance of factors driving nest-site selection was consistent. Comparison of raw suitability scores revealed high dissimilarity between modeling approaches, but models demonstrated considerable agreement when comparing a binary (suitable/unsuitable) measure of suitability. Instances of model consensus (i.e., overlapping areas of predicted piping plover nesting habitat between models) provide a stronger ‘signal’ in model results, reducing uncertainty related to biases or errors associated with either model. We tested model accuracy using a common dataset of plover nests initiated within the focal areas between 2013 and 2015, and we examined congruency in model outputs. Nearly 90% of all nests occurred in areas predicted suitable by at least one model, and at least 33% of the total nests were predicted in areas suitable by both. Because models predominantly agreed on what drives piping plover nest-site selection, areas predicted suitable by a single model should not be discounted. This case study demonstrates how models can effectively inform conservation planning by explicitly identifying the management objective, presenting robust evidence to allow managers to evaluate outcomes of alternative management decisions, and clearly communicating results that address real-world conservation problems. The results presented here can greatly increase the piping plover management community’s ability to prioritize candidate sites for future protection, manage existing nesting habitat appropriately, and make a compelling case for conservation actions against competing land use objectives.

New Jersey, New York↗

USGS2019

Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat

Coastal 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.

New Jersey, New York, Virginia↗

USGS2019

Evaluating barrier island characteristics and piping plover (Charadrius melodus) habitat availability along the U.S. Atlantic Coast—Geospatial approaches and methodology

Policy makers, individuals from government agencies, and natural resource managers face increasing demands to manage coastal areas in a way that meets economic, social, and ecological needs as sea levels rise. Scientific knowledge of how coastal processes drive beach and barrier island changes and how those changes affect habitat use can support decision makers as they balance sometimes conflicting human and ecological needs. However, uncertainties in the knowledge of the cumulative results of coastal processes make it challenging to forecast specific changes for a particular location and time. The U.S. Geological Survey is developing tools for identifying and forecasting barrier island characteristics as well as suitable coastal habitats for species of concern (such as piping plovers, Charadrius melodus ) given ongoing sea-level rise. As part of this effort, we use three Bayesian networks to calculate probabilities of shoreline change rates, changes in barrier island biogeomorphic characteristics, and piping plover habitat availability, which together forecast the effects of different sea-level-rise rates and storm regimes. This report details the methodology used to derive geospatial biogeomorphic datasets that are used as inputs for two of these Bayesian networks, which forecast barrier island geomorphology and piping plover habitat availability at sites along the U.S. Atlantic coast (Maine to North Carolina). Further information about the project, including specific study sites, can be found at https://woodshole.er.usgs.gov/project-pages/beach-dependent-shorebirds/ .

Connecticut, Maine, Maryland, Massachusetts, North↗

USGS2017

Smartphone technologies and Bayesian networks to assess shorebird habitat selection

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.

U.S Atlantic Coast↗

USGS2017

Effects of climate change and anthropogenic modification on a disturbance-dependent species in a large riverine system

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.

Iowa, Nebraska, South Dakota↗

USGS2016

Smartphone-based distributed data collection enables rapid assessment of shorebird habitat suitability

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.

PLoS ONE↗

USGS2016

Metapopulation viability of an endangered shorebird depends on dispersal and human-created habitats: Piping plovers ( Charadrius melodus ) and prairie rivers

Background Many species are distributed as metapopulations in dynamic landscapes, where habitats change through space and time. Individuals locate habitat through dispersal, and the relationship between a species and landscape characteristics can have profound effects on population persistence. Despite the importance of connectivity in dynamic environments, few empirical studies have examined temporal variability in dispersal or its effect on metapopulation dynamics. In response to this knowledge gap, we studied the dispersal, demography, and viability of a metapopulation of an endangered, disturbance-dependent shorebird. We examined three subpopulations of piping plovers ( Charadrius melodus ) on the lower Platte and Missouri rivers from 2008–2013. High flow events from an upstream dam on the Missouri River in 2010 and 2011 allowed us to assess the effect of total habitat loss and the subsequent creation of new habitat associated with a large disturbance at one ‘natural’ study location. The other two sites within the metapopulation, which were maintained by anthropogenic activities (e.g., mining, development, habitat restoration), were largely unaffected by this disturbance, resulting in a controlled natural experiment. Results High flow events were associated with increased emigration, decreased immigration, and decreased survival in the subpopulation that experienced high flows. Following the high flow event, immigration into that subpopulation increased. Dispersal rates among subpopulations were negatively correlated with distance. The metapopulation had a low probability of extinction over 100 years (0%) under the current disturbance interval and associated dispersal and survival rates. However, persistence depended on relatively stable, human-created habitats, not the dynamic, natural habitat (47.7 % extinction probability for this subpopulation). Conclusions We found that functional connectivity, as measured by the rate of dispersal among subpopulations, increased as a result of the high flow event in our study metapopulation. Plovers also increased reproductive output following this event. Although the study metapopulation had a low overall probability of extinction, metapopulation persistence depended on anthropogenically created habitats that provided a small but stable source of nesting habitat and dispersers through time. However, all subpopulations remained small, even if persistent, making them individually vulnerable to extinction through stochastic events. Given the highly dynamic nature of habitat availability in this system, maintaining several subpopulations within the metapopulation and stable sources of habitat will be critical, and this species will likely remain conservation-reliant.

Nebraska↗