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At least 127 records · Page 7Linked to original sources
USGS2018

Projected 21st century coastal flooding in the Southern California Bight. Part 2: Tools for assessing climate change-driven coastal hazards and socio-economic impacts

This paper is the second of two that describes the Coastal Storm Modeling System (CoSMoS) approach for quantifying physical hazards and socio-economic hazard exposure in coastal zones affected by sea-level rise and changing coastal storms. The modelling approach, presented in Part 1, downscales atmospheric global-scale projections to local scale coastal flood impacts by deterministically computing the combined hazards of sea-level rise, waves, storm surges, astronomic tides, fluvial discharges, and changes in shoreline positions. The method is demonstrated through an application to Southern California, United States, where the shoreline is a mix of bluffs, beaches, highly managed coastal communities, and infrastructure of high economic value. Results show that inclusion of 100-year projected coastal storms will increase flooding by 9–350% (an additional average 53.0 ± 16.0 km 2 ) in addition to a 25–500 cm sea-level rise. The greater flooding extents translate to a 55–110% increase in residential impact and a 40–90% increase in building replacement costs. To communicate hazards and ranges in socio-economic exposures to these hazards, a set of tools were collaboratively designed and tested with stakeholders and policy makers; these tools consist of two web-based mapping and analytic applications as well as virtual reality visualizations. To reach a larger audience and enhance usability of the data, outreach and engagement included workshop-style trainings for targeted end-users and innovative applications of the virtual reality visualizations.

California↗
USGS2018

A regime shift in sediment export from a coastal watershed during a record wet winter, California: Implications for landscape response to hydroclimatic extremes

Small, steep watersheds are prolific sediment sources from which sediment flux is highly sensitive to climatic changes. Storm intensity and frequency are widely expected to increase during the 21st century, and so assessing the response of small, steep watersheds to extreme rainfall is essential to understanding landscape response to climate change. During record winter rainfall in 2016–2017, the San Lorenzo River, coastal California, had nine flow peaks representing 2–10‐year flood magnitudes. By the third flood, fluvial suspended sediment showed a regime shift to greater and coarser sediment supply, coincident with numerous landslides in the watershed. Even with no singular catastrophic flood, these flows exported more than half as much sediment as had a 100‐year flood 35 years earlier, substantially enlarging the nearshore delta. Annual sediment load in 2017 was an order of magnitude greater than during an average‐rainfall year, and 500‐fold greater than in a recent drought. These anomalous sediment inputs are critical to the coastal littoral system, delivering enough sediment, sometimes over only a few days, to maintain beaches for several years. Future projections of megadroughts punctuated by major atmospheric‐river storm activity suggest that interannual sediment‐yield variations will become more extreme than today in the western USA, with potential consequences for coastal management, ecosystems, and water‐storage capacity. The occurrence of two years with major sediment export over the past 35 years that were not associated with extremes of the El Niño Southern Oscillation or Pacific Decadal Oscillation suggests caution in interpreting climatic signals from marine sedimentary deposits derived from small, steep, coastal watersheds, to avoid misinterpreting the frequencies of those cycles.

California↗
USGS2011

A Bayesian network to predict vulnerability to sea-level rise: data report

During the 21st century, sea-level rise is projected to have a wide range of effects on coastal environments, development, and infrastructure. Consequently, there has been an increased focus on developing modeling or other analytical approaches to evaluate potential impacts to inform coastal management. This report provides the data that were used to develop and evaluate the performance of a Bayesian network designed to predict long-term shoreline change due to sea-level rise. The data include local rates of relative sea-level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline-change rate compiled as part of the U.S. Geological Survey Coastal Vulnerability Index for the U.S. Atlantic coast. In this project, the Bayesian network is used to define relationships among driving forces, geologic constraints, and coastal responses. Using this information, the Bayesian network is used to make probabilistic predictions of shoreline change in response to different future sea-level-rise scenarios.

Data Series↗
USGS2022

The future of coastal monitoring through satellite remote sensing

Satellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.

Cambridge Prisms: Coastal Futures↗
USGS2019

The influence of shelf bathymetry and beach topography on extreme total water levels: Linking large-scale changes of the wave climate to local coastal hazards

Total water levels (TWLs) at the coast are driven by a combination of deterministic (e.g., tides) and stochastic (e.g., waves, storm surge, and sea level anomalies) processes. The contribution of each process to TWLs varies depending on regional differences in climate and framework geology, as well as local-scale variations in beach morphology, coastal orientation, and shelf bathymetry. Large-scale changes to the climate altering the frequency, direction, and intensity of storms, may therefore propagate to the nearshore differently, amplifying or suppressing local coastal hazards and changing the exposure of coastal communities to extreme TWLs. This study investigates the hydrodynamic and geomorphologic factors controlling local TWLs along high-energy United States coastlines where wave-influences dominate TWLs. Three study sites in the states of Washington, Oregon, and California are chosen to explore how regional and local differences in beach topography and wave transformation over shelf bathymetry drives variations in the magnitude and impacts of extreme TWLs. Results indicate that TWLs are most influenced by wave transformation processes in locations with steep beach slopes (which drive larger relative contributions of wave runup) and complex offshore bathymetry, while beach topography influences the severity of coastal impacts. Once the relative morphologic controls on TWLs are better understood, hypothetical future climate scenarios are explored to assess how changes to the average deepwater wave climate (height, period, and direction) may alter local TWLs when compared to estimates of likely sea level rise and future coastal management strategies. Changes to the wave climate are found to be as detrimental to the coastline as sea level rise in some locations, where small variations of the TWL drive large, nonlinear changes in hours of impact to the backshore beach. Overall, this study develops an approach for quantifying the range of hydrodynamic and morphologic controls on the magnitude of TWLs which will ultimately better prepare coastal communities for uncertain changes to the global climate.

California, Oregon, Washington↗
USGS2020

Development of a modeling framework for predicting decadal barrier island evolution

Predicting the decadal evolution of barrier island systems is important for coastal managers who propose restoration or preservation alternatives aimed at increasing the resiliency of the island and its associated habitats or communities. Existing numerical models for simulating morphologic changes typically include either long-term (for example, longshore transport under quiescent conditions) or short-term (for example, storm-driven waves) processes, with limited capacity to predict the decadal time-scale that is often most relevant in coastal planning. As part of the Alabama Barrier Island Restoration Assessment, a methodology was developed to predict barrier island evolution on decadal time scales. The developed modeling scheme uses multiple models including (1) Delft3D; (2) the empirical dune growth model (EDGR); and (3) XBeach that run sequentially to simulate evolution of barrier island geomorphology. The model framework was developed and applied to hindcast the evolution of Dauphin Island, Alabama, between 2004 and 2015, and was assessed using lidar data over the same period.

Alabama↗
USGS2026

Creating usable science: A Southwest Climate Adaptation Science Center study

The southwestern United States consists of diverse ecosystems that are experiencing increasing pressures from rising temperatures, increasing aridity, and sea level rise. To prepare this region for future uncertainty, there is a need for strong partnerships among researchers and societal partners. The Southwest Climate Adaptation Science Center (SW CASC) acts to foster engaged scholarship from diverse perspectives to produce science relevant for management and policy decisions. Here, we synthesized a subset of SW CASC-funded projects and published manuscripts to illustrate how the combination of new scientific knowledge and the research and practice of engaged scholarship produce actionable science with direct societal impacts. In the SW CASC Contributions to Regional Science section, we touch on new research produced from funded projects on the most common topics: (1) Forest Ecosystems, (2) Coastal Ecosystems, (3) Hydrometeorology, and (4) Research on Engaged Scholarship. In the SW CASC Contributions to Regional Impacts section, we outline engaged scholarship activities to demonstrate how they created societal impacts: (1) the Keepers of the Flame course and workshops, (2) the Southwest Fire Climate Adaptation Partnership and the Southern California Montane Forests Project, (3) the Coastal Managers Workshop, (4) the Colorado River Basin Wiki, and (5) the Natural Resource Workforce Development Program. In the SW CASC Publications Cited in Policy section, we used a bibliometric analysis to assess the impact of the SW CASC-funded research on policy. We analyzed how often publications were used in policy documents, finding a citation rate of 27.6%. This is high compared to similar analyses that found peer-reviewed research articles cited at a rate of 3.9% in policy documents. We conclude that coproduced science makes unique and important contributions to the resilience of the Southwest, not only by generating new knowledge but by building capacity, creating lasting relationships, and informing policy and conservation and management decisions.

Arizona, California, Nevada, Utah↗
USGS2016

Automatic delineation of seacliff limits using lidar-derived high-resolution DEMs in southern California

Seacliff erosion is a serious hazard with implications for coastal management and is often estimated using successive hand-digitized cliff tops or bases (toe) to assess cliff retreat. Even if efforts are made to standardize manual digitizing and eliminate subjectivity, the delineation of cliffs is time-consuming and depends on the analyst's interpretation. An automatic procedure is proposed to extract cliff edges from high-resolution lidar-derived bare-earth digital elevation models, generalized coastal shoreline vectors, and approximate measurements of distance between the shoreline and the cliff top. The method generates orthogonal transects and profiles with a minimum spacing equal to the digital elevation model resolution. The method also extracts the xyz coordinates for each profile for the cliff top and toe, as well as second major inflections along the profile. Over 75% of the automated cliff top points and 78% of the toe automated points are within 95% confidence interval of the hand-digitized top and toe lines, and over 79% of the digitized top points and 84% of the digitized toe points are within the 95% confidence interval of the automated top and toe lines along a stretch of coast in Del Mar, California. Outlier errors were caused by either the failure to remove all vegetation from the bare-earth digital elevation model or errors of interpretation. The automatic method was further applied between Point Conception and Los Angeles Harbor, California. This automatic method is repeatable, takes advantage of detailed topographic information within high-resolution digital elevation models, and is more efficient than hand-digitizing.

California↗
USGS2017

Coastal circulation and water-column properties in the National Park of American Samoa, February–July 2015

There is little information on the oceanography in the National Park of American Samoa (NPSA). The transport pathways for potentially harmful constituents of land-derived runoff, as well as larvae and other planktonic organisms, are driven by nearshore circulation patterns. To evaluate the processes affecting coral reef ecosystem health, it is first necessary to understand the oceanographic processes driving nearshore circulation, residence times, exposure rates, and transport pathways. Information on how the NPSA’s natural resources may be affected by anthropogenic sources of pollution, sediment runoff, larval transport, or modifications to the marine protected areas is critical to NPSA resource managers for understanding and ultimately managing coastal and marine resources. To address this need, U.S. Geological Survey and U.S. National Park Service researchers conducted a collaborative study in 2015 to determine coastal circulation patterns and water-column properties along north-central Tutuila, American Samoa, in an area focused on NPSA’s Tutuila Unit and its coral reef ecosystem. The continuous measurements of waves, currents, tides, and water-column properties from these instrument deployments over 150 days, coupled with available meteorological measurements of wind and rainfall, provide information on nearshore circulation and the variability in these hydrodynamic properties for NPSA’s Tutuila Unit. In general, circulation was strongly driven by regional winds at longer (greater than day) timescales and by tides at shorter (less than day) timescales. Flows were primarily directed along shore, with current speeds faster offshore to the north and slower closer to shore, especially in embayments. Water-column properties exhibit strong seasonality coupled to the shift from non-trade wind season to trade wind season. During the non-trade wind season that was characterized by variable winds and larger waves in the NPSA, waters were warmer, slightly more saline, relatively less optically clear, and more stratified. When winds shifted to a more consistent trade wind pattern in the austral fall, the waters cooled and became less stratified because of decreased insolation. There are consistent spatial patterns in water column characteristics—Waters were warmer and less saline near the surface and closer to shore, especially in embayments, which tended to be more turbid, less clear, and characterized by higher chlorophyll than waters offshore. Water residence times were shorter farther offshore and longer closer to shore and in embayments, but varied spatially because of different forcing. Warmer, lower salinity, higher chlorophyll, and more turbid waters in embayments tend to reside in those locations for much greater durations, resulting in greater exposure of embayment ecosystems to those waters. This is in contrast with waters farther offshore, where the combination of shorter residence times and cooler, higher salinity water results in less exposure to land runoff. Understanding coastal circulation patterns and water-column properties in NPSA’s waters along north-central Tutuila may help to better understand how meteorological and oceanographic processes, at the regional and local scale, affect coral reef health and sustainability in this region.

Open-File Report↗
USGS2019

Extreme coastal water level in Washington state: Guidance to support sea level rise planning

This document provides guidelines for assessing exposure to future coastal flooding during extreme coastal water level events – whether these are due to tides, surge, wave run-up, or, more likely, a combination of the three. These guidelines provide information about the current and future magnitude of extreme coastal water levels across Washington State and the underlying processes that influence them. This information is intended to be combined with sea level projections to assess future exposure to coastal flooding along Washington’s coastline. Although the results of our analyses can be combined with any available sea level projections, this report is intended as a companion to the localized sea level rise projections (Miller et al., 2018) developed as part of the Washington Coastal Resilience Project. The Washington Coastal Resilience Project was a three-year effort to rapidly increase the state’s capacity to prepare for sea level rise. The project aimed to improve risk projections, provide better guidelines for land use planners and strengthen capital investment programs for coastal restoration and infrastructure. Partners in the Washington Coastal Resilience Project included Washington Sea Grant, Washington Department of Ecology, Island County, King County, NOAA Office for Coastal Management, Pacific Northwest National Laboratory, Padilla Bay National Estuary Research Reserve, The City of Tacoma, The Nature Conservancy, U.S. Geological Survey, University of Oregon, University of Washington Climate Impacts Group, University of Washington Department of Earth and Space Sciences, Washington Department of Fish and Wildlife and Western Washington University. The 2018 sea level projections are described in an accompanying technical report, along with a review of the science related to sea level rise (Miller et al., 2018). The report and all associated supporting information are available on the Washington Coastal Hazards Resilience Network website (http://www.wacoastalnetwork.com/).

Washington↗
USGS2014

Utilizing dimensional analysis with observed data to determine the significance of hydrodynamic solutions in coastal hydrology

In this paper, the authors present an analysis of the magnitude of the temporal and spatial acceleration (inertial) terms in the surface-water flow equations and determine the conditions under which these inertial terms have sufficient magnitude to be required in the computations. Data from two South Florida field sites are examined and the relative magnitudes of temporal acceleration, spatial acceleration, and the gravity and friction terms are compared. Parameters are derived by using dimensionless numbers and applied to quantify the significance of the hydrodynamic effects. The time series of the ratio of the inertial and gravity terms from field sites are presented and compared with both a simplified indicator parameter and a more complex parameter called the Hydrodynamic Significance Number (HSN). Two test-case models were developed by using the SWIFT2D hydrodynamic simulator to examine flow behavior with and without the inertial terms and compute the HSN. The first model represented one of the previously-mentioned field sites during gate operations of a structure-managed coastal canal. The second model was a synthetic test case illustrating the drainage of water down a sloped surface from an initial stage while under constant flow. The analyses indicate that the times of substantial hydrodynamic effects are sporadic but significant. The simplified indicator parameter correlates much better with the hydrodynamic effect magnitude for a constant width channel such as Miami Canal than at the non-uniform North River. Higher HSN values indicate flow situations where the inertial terms are large and need to be taken into account.

Florida↗
USGS2007

Management applications of lidar-derived mean high water shorelines in North Carolina

The accuracy of shoreline change analysis is dependent on how the shoreline is defined and the consistency of the techniques(s) used to define it. Using the concurrent lidar (light detection and ranging) and orthophotography dataset from August and September of 2004 covering North Carolina's 516 kilometers of barrier island oceanfront, Limber et al. (2007) examined the spatial relationship between two common shoreline definitions used in shoreline change analysis, mean high water [MHW] derived from lidar data and the wet/dry line digitized from orthophotography. Here, we summarize this work and extend the analysis with a comparison between two different methods of MHW shoreline extraction from liar data: a profile-based method (Stockdon et al., 2002) and a method based on correction of the lidar data to a MHW datum (Hess et al., 2005). Potential bias generated by using these different shoreline types together can affect not only the accuracy of shoreline change analysis, but also the coastal management policies and decision that rely on it. Therefore, the implications of this study potential extend far beyond North Carolina and Atlantic Coast of the United States.

North Carolina↗
USGS2016

Effects of climate change on tidal marshes along a latitudinal gradient in California

Public Summary The coastal region of California supports a wealth of ecosystem services including habitat provision for wildlife and fisheries. Tidal marshes, mudflats, and shallow bays within coastal estuaries link marine, freshwater and terrestrial habitats, and provide economic and recreational benefits to local communities. Climate change effects such as sea-level rise (SLR) are altering these habitats, but we know little about how these areas will change over the next 50–100 years. Our study examined the projected effects of three recent SLR scenarios produced for the West Coast of North America on tidal marshes in California. We compiled physical and biological data, including coastal topography, tidal inundation, plant composition, and sediment accretion to project how SLR may alter these ecosystems in the future. The goal of our research was to provide results that support coastal management and conservation efforts across California. Under a low SLR scenario, all study sites remained vegetated tidal wetlands, with most sites showing little elevation and vegetation change relative to sea level. At most sites, mid SLR projections led to increases in low marsh habitat at the expense of middle and high marsh habitat. Marshes at Morro Bay and Tijuana River Estuary were the most vulnerable to mid SLR with many areas becoming intertidal mudflat. Under a high SLR scenario, most sites were projected to lose vegetated habitat, eventually converting to intertidal mudflats. Our results suggest that California marshes are vulnerable to major habitat shifts under mid or high rates of SLR, especially in the latter part of the century. Loss of vegetated tidal marshes in California due to SLR is expected to impact ecosystem services that are dependent on coastal wetlands such as wildlife habitat, carbon sequestration, improved water quality, and coastal protection from storms.

California↗
USGS2005

Simulating the evolution of coastal morphology and stratigraphy with a new morphological-behaviour model (GEOMBEST)

A new morphological-behaviour model is used to simulate evolution of coastal morphology associated with cross-shore translations of the shoreface, barrier, and estuary. The model encapsulates qualitative principles drawn from established geological concepts that are parameterized to provide quantitative predictions of morphological change on geological time scales (order 10 3 years), as well as shorter time scales applicable for long-term coastal management (order 101 to 102 years). Changes in sea level, and sediment volume within the shoreface, barrier, and estuary, drive the model behaviour. Further parameters, defining substrate erodibility, sediment composition, and time-dependent shoreface response, constrain the evolution of the shoreface towards an equilibrium profile. Results from numerical experiments are presented for the low-gradient autochthonous setting of North Carolina and the steep allochthonous setting of the Washington shelf. Simulations in the Currituck region of North Carolina examined the influence of sediment supply, substrate composition, and substrate erodibility on barrier transgression. Results demonstrate that the presence of a lithified substrate reduces the rate of barrier transgression compared to scenarios where an erodible, sand-rich substrate exists. Simulations of the Washington coast, 20 km north of the Columbia River, confirmed that the model can reproduce complex stratigraphy involving regressive and transgressive phases of coastal evolution. Results suggest that the first major addition of sediment to the shelf occurred around 12 900 years ago and resulted from the rapid addition of sediment volume from the Columbia River attributed to the Missoula floods. This was followed by a period where little or no sediment was added (12 400-9100 BP) and a third period when most sediment was added to the shelf (9100 BP to present) from the Columbia River. Comparing results from each setting demonstrates an indirect control that substrate slope has on shoreface transgression rates. Shoreface transgression is shown to be sensitive to the rate of estuarine sedimentation, with the sensitivity increasing as substrate slope decreases.

North Carolina↗
USGS2013

Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression

Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007–Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.

Estuarine, Coastal and Shelf Science↗
USGS2018

A Bayesian approach to predict sub-annual beach change and recovery

The upper beach, between the astronomical high tide and the dune-toe, supports habitat and recreation along many beaches, making predictions of upper beach change valuable to coastal managers and the public. We developed and tested a Bayesian network (BN) to predict the cross-shore position of an upper beach elevation contour (Z l D) following 1 month to 1-year intervals at Fire Island, New York. We combine hydrodynamic data with series of island-wide topographic data and spatially limited cross-shore profiles. First, we predicted beach configuration of Z l D positions at high spatial resolution (50 m) over intervals spanning 2005–2014. Compared to untrained model predictions, in which all six outcomes are equally likely (prior likelihood = 0.16), our prediction metrics (skill = 0.52; log likelihood ratio = 0.14; accuracy = 0.56) indicate the BN confidently predicts upper beach dynamics. Next, the BN forecasted three intervals of beach recovery following Hurricane Sandy. Results suggest the pre-Sandy training data is sufficiently robust to require only periodic updates to beach slope observations to maintain confidence for forecasts. Finally, we varied input data, using observations collected at a range of temporal (1–12 months) and spatial (50 m to > 1 km) resolutions to evaluate model skill. This experiment shows that data collection techniques with different spatial and temporal frequencies can be used to inform a single modeling framework and can provide insight to BN training requirements. Overall, results indicate that BNs and inputs can be developed for broad coastal change assessment or tailored to a set of predictive requirements, making this methodology applicable to a variety of coastal prediction scenarios.

Estuaries and Coasts↗
USGS2021

Potential for carbon and nitrogen sequestration by restoring tidal connectivity and enhancing soil surface elevations in denuded and degraded south Florida mangrove ecosystems

Mangroves are tidally dependent wetlands that are influenced often by alterations in hydrology associated with coastal developments that impact their distribution, health, and function. Alteration in frequency, depth, duration, and seasonality of tidal inundation can lead to changes in forest condition, although these stress-adapted ecosystems may persist for many years before succumbing to mortality. However, arresting this decline through hydrological restoration can significantly improve ecosystem condition and the provision of ecosystem services. Much of the mangrove resource on Marco Island, Florida, USA, is unhealthy if not already dead or dying due to soil structural shifts, permanent flooding, and peat compression resulting from road construction, tidal restriction, and delays in restoration actions. In order to determine the impact of restricted hydrology on these mangrove forests, we examined soil surface elevation change and soil carbon (C) and nitrogen (N) content along a degradation gradient and within a small-scale, community-driven restoration area. Using a space-for-time substitution approach, we found that the restoration of regular tidal inundation to Marco Island mangroves has the potential to increase C sequestration in surface soils alone from 0 to 360 g C/m 2 /yr (3.60 Mg C/ha/yr) and increase N sequestration from 0 to 24 g N/m2/yr (0.24 Mg N/ha/yr). Additional sequestration benefits would be realized with aboveground forest recovery. Successful mangrove restoration trials and small community-based projects such as those on Marco Island could serve as a model for larger efforts and empower stakeholders and policy makers to restore other wetlands and better manage coastal carbon.

Florida↗
USGS2023

The blue carbon reservoirs from Maine to Long Island, NY

In response to the New England Governor and Eastern Canadian Premier 2017 Climate Change Action Plan recommendation to “manage blue carbon resources to preserve and enhance their existing carbon reservoirs,” the U.S. Environmental Protection Agency (EPA) convened a New England Blue Carbon Inventory Workgroup, comprised of a variety of federal, state, academic, and non-profit organizations to develop an inventory of blue carbon stocks from Maine to Long Island, New York. The Workgroup focused its inventory efforts on salt marshes and eelgrass meadows, leveraging existing habitat maps for geographic data. Existing data for soil organic carbon stocks were then used to calculate blue carbon stock estimates. For visual display purposes, sediment carbon heat maps were developed to highlight areas of greatest carbon accumulation. The habitat distribution and sediment carbon heat maps can be accessed on the Northeast Ocean Data Portal (www.northeastoceandata.org/eelgrass) which is a public source of expert-reviewed, interactive maps and data on the ocean ecosystem, economy, and culture of the northeastern United States and can be used to facilitate decision making by government agencies, tribal nations, businesses, non-governmental organizations (NGOs), academic institutions, and individuals. Based on available data and Workgroup calculations, the target geographic area has an estimated 218,222 acres of eelgrass meadows, salt marsh and saline Phragmites, which are estimated to provide a reservoir of 7,523,568 megagrams of blue carbon, or the equivalent to the annual carbon emissions from over 5,944,024 passenger vehicles. Due to data limitations, the carbon stock estimate represents a mere fraction of the actual quantity of accumulated carbon in these habitats. The findings from the Workgroup’s efforts and the resulting map products can help inform land and coastal management policies, fisheries management, and climate change mitigation practices. Further refinements and expansion of data are needed, including more detailed habitat maps, deeper soil core data for soil organic carbon content, and inclusion of more marine flora into calculations.

Connecticut, Maine, Massachusetts, New Hampshire, ↗