Geology topics

Brett Patton

Publications and source records attributed to Brett Patton.

7 recordsLinked to original sources

USGS2026

Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: Implications for river diversions

Our understanding of the impacts of climate change, sea-level rise (SLR), and freshwater management on the magnitude and variability of carbon fluxes in tidal forested wetlands remains limited. In this study, we applied a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool—DeNitrification-DeComposition (WCAT-DNDC) model to explore responses of carbon fluxes in tidal swamp forests to climate change-induced alterations in hydrologic conditions and to predict impacts of planned reintroduction of river flows. We selected twelve sites in three habitats (throughput, relict, degraded) inside the Lake Maurepas swamp forests (Louisiana, USA) to represent various hydrological and salinity regimes. Environmental scenarios included dry, average, and wet conditions, SLR (low and high), and a Mississippi River (MR) diversion. Simulation results showed that the responses of net ecosystem exchange (NEE), net primary productivity (NPP), ecosystem respiration (ER), methane (CH 4 ) and nitrous oxide (N 2 O) emissions in the Lake Maurepas swamp forests varied substantially among sites. However, the overall net carbon uptake capacity of the Lake Maurepas swamp forests was high (NEE: − 1143 to − 1650 g C m −2 yr −1 ), suggesting that Lake Maurepas swamp forests are large carbon sinks. The high net carbon uptake capacity could be significantly affected by climate change induced drought, flooding, and SLR with the bi-directional changes (increase or decrease) depending on the direction and magnitude of the hydrologic regime changes. The response of the net carbon uptake capacity to MR diversion is also bi-directional and site-specific, but enhancement of the capacity of NEE of up to − 1957 g C m 2 yr −1 is possible, implying that MR diversion into the swamp forests could be beneficial in the context of carbon cycling and carbon sequestration.

Louisiana↗

USGS2025

Texas coastal wetland surface elevation static survey campaign report

Surface elevation data along the Texas Coast is limited, despite having some of the highest rates of relative sea-level rise in the country (Sweet et al., 2022). To narrow these knowledge and data gaps, the U.S. Fish and Wildlife Service (USFWS) established the first landscape-scale rod surface elevation table (RSET) monitoring project aimed at examining surface elevation dynamics of coastal marshes in Texas (Moon et al., 2022). The project, conducted cooperatively between the USFWS and the U.S. Geological Survey (USGS), has focused on 14 coastal marsh sites located within five National Wildlife Refuges (Figure 1). The main objective of this project’s RSET data collection is to quantify the impacts of sea-level rise on coastal properties owned by the USFWS and similar surrounding areas. Data from RSETs will be used to determine areas that are at the greatest risk for potential habitat loss and degradation by examining subsidence and accretion rates. However, for the RSET data to be tied into the national vertical datum of 1988 (NAVD88) and, therefore, linked to the relative sea-level change calculations, it is necessary to establish primary vertical control at each study site through highly accurate and precise global navigation satellite systems (GNSS) surveys. Having a clear methodology for standardization is important for quality data. This report focuses on the methods, with particular emphasis on post-processing, used to survey benchmarks for the RSET data collection along the Texas Coast for the USFWS. Furthermore, this report serves as a general reference guide on the technical aspects of performing and processing GNSS surveys within the Texas coastal refuges to maintain quality and consistency.

Texas↗

USGS2024

Enhancing assessments of coastal wetland migration potential with sea-level rise: Accounting for uncertainty in elevation data, tidal data, and future water levels

Sea-level rise rates are predicted to surpass rates of wetland vertical adjustment in the coming decades in many areas, increasing the potential for wetland submergence. Information on where wetland migration is possible can help natural resource managers for planning land acquisition or enhancing habitat connectivity to bolster adaptation of coastal wetlands to rising seas. Elevation-based models of wetland migration are often hampered with uncertainty associated with ground surface elevation, current water levels (i.e., tides and extreme water levels), and future water levels from sea-level rise. Here, we developed an approach that involved digital elevation model error reduction and the use of Monte Carlo simulations that utilize uncertainty assumptions regarding elevation error, contemporary water levels, and future sea levels to identify potential wetland migration areas. Our analyses were developed for Duvall and Nassau Counties in northeastern Florida (USA). We focus on the migration of regularly oceanic-flooded wetlands (i.e., flooded by oceanic water daily) and irregularly oceanic-flooded wetlands (i.e., flooded by oceanic water less frequently than daily). For two relative sea-level rise scenarios based on the 0.5 m and the 1.5 m global mean sea-level rise scenarios, we quantified migration by wetland flooding frequency class and identified land cover and land use types that are vulnerable to future exposure to oceanic waters. The variability in total coverage and relative coverage of wetland migration from our results highlights how topography and accelerated sea-level rise interact. Our wetland migration results communicate uncertainty by showing flooding frequency class as probabilistic outputs.

Florida↗

USGS2021

Developing bare-earth digital elevation models from structure-from-motion data on barrier islands

Unoccupied aerial systems can collect aerial imagery that can be used to develop structure-from-motion products with a temporal resolution well-suited to monitoring dynamic barrier island environments. However, topographic data created using photogrammetric techniques such as structure-from-motion represent the surface elevation including the vegetation canopy . Additional processing is required for estimating bare-earth elevation, which is critical for understanding the underlying geomorphology of these islands. In this study, we used a vegetation and elevation survey to produce bare-earth digital elevation models from structure-from-motion-derived elevation products for two sites on Dauphin Island, Alabama (USA). One site was exposed to high wave energy and included a mix of beach, dune, and barrier flat habitats that were dominated by supratidal/upland herbaceous vegetation. The second site was exposed to low wave energy and was dominated by intertidal marsh. Aerial imagery was collected in late fall of 2018 and spring of 2019. We tested several machine learning algorithms for predicting and removing elevation bias for vegetated areas using predictors that included spectral indices from unoccupied aerial systems-based multispectral imagery and landscape position information (e.g., relative topography and distance from shore). Models were developed for each site and season. We also explored how well the model from one season generalized to data from a different season for the same site. For developing initial digital surface models, we found that utilizing a minimum bin algorithm, as opposed to interpolation, led to lower elevation bias. For bias removal, Gaussian process regression performed the best and led to a root mean square error for the bare-earth digital elevation models of around 0.10 m for the high energy site and 0.15 m for the low energy site. Compared to the digital surface models, the root mean square error for the bare-earth digital elevation models was reduced by at least 29 percent for the high energy site and 69 percent for the low energy site. For all models, common predictors included surface elevation, vegetation greenness, and distance from the shoreline. The models produced comparable results when trained using data from a different season. The error estimates for all analyses were within published elevation standards for lidar data for vegetated areas. With calibration, this approach could be portable to other areas or data, such as aerial lidar (conventional or unoccupied), to provide an efficient and repeatable framework for monitoring geomorphology or provide baseline elevations for predicting changes to these environments under future conditions.

Alabama↗

USGS2020

Living on the edge: Multi-scale analyses of bird habitat use in coastal marshes of Barataria Basin, Louisiana, USA

Coastal marsh loss, combined with expected sea-level rise, will cause inundation and extensive shifts to vegetation and salinity regimes that may affect the bird species dependent on coastal ecosystems worldwide. Within coastal marsh habitats, birds provide key targets for coastal management goals. However, limited information on bird-habitat relationships within coastal marshes inhibits the development of restoration projects targeted to bird species. We surveyed birds bi-monthly within Barataria Basin, LA from July 2014 to December 2015 to compare their use between fresh and saline coastal marshes. Additionally, we examined habitat use at finer spatial scales to assess preference for marsh edge microhabitats. Edge habitat supported 1.8 times more bird species (guild) richness than emergent and open water habitat. We concluded that future modelling efforts would be improved if models incorporate edge effects for birds in coastal marshes that extend 20 m from emergent vegetation into open water, with a reduced effect if marsh types convert from fresh to saline. Our data will be useful to simulate the effects of changes in marsh type, area, and edge on habitat quality for birds in coastal Louisiana and will inform habitat restoration and management decisions aimed at optimizing bird use.

Louisiana↗

USGS2019

Impacts of saltwater intrusion on wetland prey production and composition in a historically freshwater marsh

Sea level rise is a fundamental driver of ecosystem change and has the potential to shift the spatial distributions of habitats more rapidly than species can adapt. Rapid sea level rise and associated saltwater intrusion have negative impacts on coastal environments, including loss of habitat for species such as sea turtles and shorebirds. In Florida’s largest wetland, the Everglades, the availability of small fishes that are prey for wading birds serve as an indicator of ecosystem health. In the southwestern part of the ecosystem, sea level rise and a reduction in freshwater flow have converted formerly freshwater marsh into an estuarine mangrove-dominated landscape. In this study, we sampled fish communities in this southwest portion of the Everglades exposed to a range of saline conditions. Biomass of native fishes was highest at a salinity value of approximately 25 parts per thousand, while non-native biomass decreased with increasing salinity. Applying salinity change scenarios, we determined that a 10% reduction from the salinity levels recorded in this study would be optimal for biomass of native fishes. The baseline data we collected on non-native fishes at the site will be useful for monitoring as restoration progresses and for managers working on invasive species control. This region has been actively undergoing ecosystem restoration for the last decade, but restored freshwater flow closer to historical conditions is still years away. Without increased freshwater inflow from hydrologic restoration, rising sea levels and saltwater intrusion may provide conservation challenges for wading birds and their prey-base fishes.

Florida↗

USGS2015

Inundation and salinity impacts to above- and belowground productivity in Spartina patens and Spartina alterniflora in the Mississippi River Deltaic Plain: implications for using river diversions as restoration tools

Inundation and salinity directly affect plant productivity and processes that regulate vertical accretion in coastal wetlands, and are expected to increase as sea level continues to rise. In the Mississippi River deltaic plain, river diversions, which are being implemented as ecosystem restoration tools, can also strongly increase inundation in coastal wetlands. We used an in situ mesocosm approach to examine how varying salinity (two levels) and inundation rates (six levels) influenced end-of-season above- and belowground biomass of Spartina patens and Spartina alterniflora during the growing season (March–October) in 2011. Above- and belowground biomass was highest in both species at higher elevations when inundation was minimal, and decreased exponentially with decreased elevation and increased flood duration. This negative biomass response to flooding was more pronounced in S. patens than in S. alterniflora , and S. patens also showed stronger biomass reductions at higher salinities. This salinity effect was absent for belowground biomass in S. alterniflora . These findings suggest that even subtle increases in sea level may lead to substantial reductions in productivity and organic accretion, and also illustrate the importance of considering the inundation tolerance of co-dominant species in receiving areas when utilizing river diversions for delta restoration.

Louisiana↗