Geology topics

Research about Alabama

Source-linked reports with geographic coverage including Alabama.

At least 55 records · Page 3Linked to original sources

USGS2021

Fine-scale weather patterns drive reproductive success in the Brown Pelican

In the northern Gulf of Mexico, island restoration and creation have been used to mitigate potential negative effects of anthropogenic and environmental stressors to breeding seabirds. The long-term success of such projects can be enhanced when data are available to elucidate how site-specific and larger-scale factors may contribute to reproductive success. Nest-specific daily survival rate (DSR) of Eastern Brown Pelicans ( Pelecanus occidentalis carolinensis ) during incubation (i.e., pre-hatch; n = 245) and brood-rearing (i.e., post-hatch; n = 185) were measured at two breeding islands in the northern Gulf of Mexico USA in 2017 and 2018 in relation to macro- and micro- scale habitat and environmental measurements. DSR of nests during incubation ranged from 91-99%, and the DSR during brood-rearing exceeded 99% each year. Regional weather variables occurred in top-performing models more often and with more significance compared to microhabitat variables. Results suggest that reproductive success of Brown Pelicans may respond at least in part to weather factors that occur outside of the scope of habitat structure as it is typically incorporated into the restoration or creation of breeding habitat, indicating that climate conditions are likely an important factor in the success of restoration efforts.

Alabama↗

USGS2021

Changes in vegetation structure and gopher tortoise population structure after 17 years of restoration management

We examined a study plot sampled in the Conecuh National Forest of southern Alabama in 1999 and again in 2016 after stand thinning and persistent prescribed fire were used to improve habitat quality. These management activities were designed, in part, to enhance habitat quality for the gopher tortoise ( Gopherus polyphemus ), a species considered for protection under the Endangered Species Act because of range-wide population declines. Comparisons of vegetation structure were made at burrows that were active in 1999 and remained active in 2016, and at burrows that were active in 1999 but were classified as abandoned in 2016. Burrows that remained active across this span of time were distinctive in retaining a greater reduction of canopy cover and lacking hardwoods while having a high percentage of longleaf pine in neighboring canopy trees. Active burrows that were abandoned in 2016 were distinctive in possessing hardwoods among neighboring canopy trees, lacking pine seedlings in the midstory, and having increased frequency of legumes and decreased bare ground in the understory. All burrows experienced a decrease in canopy cover and an increase in distance to, and dbh of, neighboring canopy trees; all burrows also had a decrease in litter and non-legume forbs as well as an increase in shrub stems in the understory and midstory. These results indicate that management activities were successful in opening canopy cover but were largely unsuccessful at reducing shrub stems and increasing understory grasses and forbs. Nevertheless, burrows of gopher tortoises increased in abundance during this time period. The size distribution of these burrows changed from a unimodal distribution dominated by adults to a bimodal distribution indicative of increased juvenile recruitment. Thus, the gopher tortoise population increased in association with vegetation changes that suggest tortoises are more sensitive to shading caused by canopy closure than they are to available forage.

Alabama↗

USGS2021

Comparing harvest management alternatives for Eastern Wild Turkeys in Alabama

Eastern wild turkey ( Meleagris gallopavo silvestris ; hereafter turkey) is an important game species that is pursued by thousands of Alabama hunters each spring. Biologists in Alabama and other parts of the southeastern U.S. believe that turkey populations have been declining for at least two decades. Managers in many state agencies and organizations believe that liberal spring bag limits and the timing of hunting seasons are contributing to this decline. We used an expert-driven approach to develop models of turkey populations that predicted the outcomes of spring harvest management alternatives. The models were based on recent research and expert judgement regarding the effects of spring hunting regulations on turkey vital rates. We then used the relationship between the expected spring density of adult males and expected harvest elicited from experts to compare the values of the alternatives over a 30-year period. Our model suggests that if later opening dates result in increased turkey productivity and increased harvest, the result will be larger turkey populations, increased harvest, and greater value to stakeholders. In 84% of deterministic projections from 27,951 different initial populations, the highest valued alternative was to open seasons later, reduce bag limits, and shorten the season. This alternative also was best in 48% of projections that included parametric uncertainty. These results were used to produce a decision-support tool, that could be used to guide decisions about spring hunting regulations for turkeys in Alabama, and updated using the results of monitoring programs. Further research is needed to more precisely estimate the causes and effects of spring hunting seasons on turkey vital rates.

Alabama↗

USGS2020

Development and application of an empirical dune growth model for evaluating barrier island recovery from storms

Coastal zone managers require models that predict barrier island change on decadal time scales to estimate coastal vulnerability, and plan habitat restoration and coastal protection projects. To meet these needs, methods must be available for predicting dune recovery as well as dune erosion. In the present study, an empirical dune growth model (EDGR) was developed to predict the evolution of the primary foredune of a barrier island. Within EDGR, an island is represented as a sum of Gaussian shape functions representing dunes, berms, and the underlying island form. The model evolves the foredune based on estimated terminal dune height and location inputs. EDGR was assessed against observed dune evolution along the western end of Dauphin Island, Alabama over the 10 years following Hurricane Katrina (2005). The root mean square error with EDGR (ranging from 0.18 to 0.74 m over the model domain) was reduced compared to an alternate no-change model (0.69–0.96 m). Hindcasting with EDGR also supports the study of dune evolution processes. At Dauphin Island, results suggest that a low-lying portion of the site was dominated by overwash for ~5 years after Katrina, before approaching their terminal height and becoming growth-limited after 2010. EDGR’s computational efficiency allows dune evolution to be rapidly predicted and enables ensemble predictions to constrain the uncertainty that may result if terminal dune characteristics are unknown. In addition, EDGR can be coupled with an external model for estimating dune erosion and/or the long-term evolution of other subaerial features to allow decadal-scale prediction of barrier island evolution.

Alabama↗

USGS2020

Sensitivity of storm response to antecedent topography in the XBeach model

Antecedent topography is an important aspect of coastal morphology when studying and forecasting coastal change hazards. The uncertainty in morphologic response of storm-impact models and their use in short-term hazard forecasting and decadal forecasting is important to account for when considering a coupled model framework. This study provided a methodology to investigate uncertainty of profile response within the storm impact model XBeach related to varying antecedent topographies. A parameterized island Gaussian fit (PIGF) model generated an idealized baseline profile and a suite of idealized profiles that vary specific characteristics based on collated observed LiDAR data from Dauphin Island, AL, USA. Six synthetic storm scenarios were simulated on each of the idealized profiles with XBeach in both 1- and 2-dimensional setups and analyzed to determine the morphological response and uncertainty related to the varied antecedent topographies. Profile morphologic response tends to scale with storm magnitude but among the varied profiles there is greater uncertainty in profile response to the medium range storm scenarios than to the low and high magnitude storm scenarios. XBeach can be highly sensitive to morphologic thresholds, both antecedent and time-varying, especially with regards to beach slope.

Alabama↗

USGS2020

Methods for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in Alabama

Streamflow data and statistics are vitally important for proper protection and management of the water quality and water quantity of Alabama streams. Such data and statistics are generally available at U.S. Geological Survey streamflow-gaging stations, also referred to as streamgages or stations, but are often needed at ungaged stream locations. To address this need, the U.S. Geological Survey, in cooperation with numerous Alabama State agencies and organizations, developed regional regression equations for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in Alabama that are not substantially affected by tides, regulation, diversions, or other anthropogenic influences. A small percentage of the streamgages included in this study experience zero flows during certain periods; thus, the final low-flow frequency regression equations were developed by using weighted left-censored regression analyses to analyze the flow data in an unbiased manner, with weights based on number of years of record. The equations developed include the annual minimum 1- and 7-day average streamflows with a 10-year recurrence interval (referred to as the 1Q10 and 7Q10 flows), the annual minimum 7-day average streamflow with a 2-year recurrence interval (referred to as the 7Q2 flow), and the mean annual flow using data from 174 streamgages from Alabama and surrounding States. For the 1Q10, 7Q2, and 7Q10 low-flow frequency statistics, the regional regression equations are functions of drainage area, streamflow-variability index, mean annual precipitation, and percentage of the drainage basin located in the Piedmont and Southeastern Plains ecoregions. The mean annual flow regression equation is a function of drainage area, mean annual precipitation, and percentage of the drainage basin located in the Southeastern Plains ecoregion. For the mean annual flow regression equation, the average standard error of estimate was 11.2 percent. For the selected low-flow frequency equations, the average standard errors of estimate ranged from 18.1 to 38.8 percent. The regional regression equations developed from this investigation have been incorporated into the U.S. Geological Survey StreamStats application for Alabama. StreamStats ( https://streamstats.usgs.gov/ss/ ) is a web-based geographic information system application that delineates drainage basins at selected stream locations and then generates the needed basin characteristics for available regional regression equations. Along with the low-flow frequency equations developed in this investigation, the StreamStats application also has regional regression equations for estimating flood-frequency statistics at locations on rural and urban streams in Alabama.

Alabama↗

USGS2020

The roles of storminess and sea level rise in decadal barrier island evolution

Models of alongshore sediment transport during quiescent conditions, storm‐driven barrier island morphology, and poststorm dune recovery are integrated to assess decadal barrier island evolution under scenarios of increased sea levels and variability in storminess (intensity and frequency). Model results indicate barrier island response regimes of keeping pace, narrowing, flattening, deflation (narrowing and flattening), and aggradation. Under lower storminess scenarios, more areas of the island experienced narrowing due to collision. Under higher storminess scenarios, more areas experienced flattening due to overwash and inundation. Both increased sea levels and increased storminess resulted in breaching when the majority of the island was not keeping pace and deflation was the dominant regime due to increased overtopping. Under the highest storminess scenario, the island was unable to recover elevation after storms and drowned in just 10 years.

Alabama↗

USGS2020

Magnitude and frequency of floods in Alabama, 2015

To improve flood-frequency estimates at rural streams in Alabama, annual exceedance probability flows at gaged locations and regional regression equations used to estimate annual exceedance probability flows at ungaged locations were developed by using current geospatial data, new analytical methods, and annual peak-flow data through September 2015 at 242 streamgages in Alabama and surrounding States. The regional regression equations were derived from statistical analyses of annual peak-flow data and basin characteristics for a subset of 217 streamgages. Four flood regions were identified based on residuals from the regional regression analyses and contain sites with similar basin characteristics. A separate set of equations was derived for estimating flood frequency and magnitude for small rural streams using a subset of 40 small basin streamgages. A large river analysis was also completed for 14 selected large-river streamgages in Alabama. Annual exceedance probability flows presented in this report reflect additional streamflow data collected since the previous study of flood magnitude and frequency in Alabama, which included streamflow through September 2003.

Alabama↗

USGS2020

Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama

Barrier islands, such as Dauphin Island, Alabama, provide numerous invaluable ecosystem services including storm damage reduction and erosion control to the mainland, habitat for fish and wildlife, carbon sequestration in marshes, water catchment and purification, recreation, and tourism. These islands are dynamic environments that are gradually shaped by currents, waves, and tides under quiescent conditions yet can evolve in the time scale of hours to days during hurricanes and other extreme storms. The ecosystems associated with these islands also face numerous other hazards, including accelerated sea-level rise, oil spills, and anthropogenic stressors. Hurricane Katrina in 2005 and the Deepwater Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Ala. The latter event prompted a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers to investigate viable, sustainable restoration measures that reduce degradation and enhance the natural resources of Dauphin Island, Ala. In collaboration with the State of Alabama and the National Fish and Wildlife Foundation, the overarching goal of the Alabama Barrier Island Restoration Feasibility Assessment project was to document baseline conditions and forecast potential conditions under varying sea-level change and storm scenarios for a no-action alternative along with a variety of restoration measures including beach and dune restoration, marsh and back-barrier restoration, and placement of sand in the littoral zone. The modeling component of this project used decadal hydrodynamic geomorphic, water quality, and habitat modeling to better understand how the various restoration measures may influence the habitat composition, sustainability, and resiliency of Dauphin Island under potential future conditions, benchmarked against the no-action case. The report covers the habitat modeling efforts associated with the Alabama Barrier Island Restoration Feasibility Assessment project. For various potential future island configurations for Dauphin Island, we predicted coverage of habitat types (for example, beach, dune, intertidal marsh, and woody vegetation) using a spatially explicit habitat model based on landscape-position information (for example, elevation and distance from shore) extracted from the hydrodynamic geomorphic outputs. Similarly, we forecasted habitat suitability for oysters and seagrass using habitat suitability index models. Another component of the Alabama Barrier Island Restoration Feasibility Assessment project, presented separately, integrates these habitat model results into a structured decision-making framework that accounts for competing objectives. Collectively, this information provides insights to natural resource managers and planners on how a restoration measure may maintain or impede natural coastal processes and provide information critical for making future-focused decisions regarding barrier island restoration.

Alabama↗

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↗

USGS2020

Application of decadal modeling approach to forecast barrier island evolution, Dauphin Island, Alabama

Forecasting barrier island evolution provides coastal managers and stakeholders the ability to assess the resiliency of these important coastal environments that are home to both established communities and existing natural habitats. This study uses an established coupled model framework to assess how Dauphin Island, Alabama, responds to various storm and sea-level change scenarios, along with a suite of restoration measures, over the course of a decade. The coupled model framework uses validated models for long-term alongshore sediment transport (Delft 3D), short-term storm induced impacts (XBeach), as well as dune building and recovery (empirical dune growth model). This model framework was simulated with the various storm and sea-level change scenarios on a non-restored Dauphin Island, then a subset of the storm and sea-level change scenarios were applied to a suite of seven different restoration measures to determine how they would influence the morphologic evolution over a decadal period. Topographic and bathymetric changes captured in post-simulation digital elevation models were then passed on to partners for various simulations to determine the effects on habitat evolution and water quality as it relates to oyster reef and submerged aquatic vegetation.

Alabama↗

USGS2020

Development of a process-based littoral sediment transport model for Dauphin Island, Alabama

Dauphin Island, Alabama, located in the Northern Gulf of Mexico just outside of Mobile Bay, is Alabama’s only barrier island and provides an array of historical, natural, and economic resources. The dynamic island shoreline of Dauphin Island evolved across time scales while constantly acted upon by waves and currents during both storms and calm periods. Reductions in the vulnerability and enhancements to the resiliency of Dauphin Island—through offshore sand placement, breach closure, berm construction, and other means—have been used to protect the island and its vital resources. Planning for a resilient Dauphin Island requires predicting the long-term evolution of the barrier island system and the dominant, temporally varying processes that influence it, including littoral alongshore sediment transport under typical wave conditions, beach and dune erosion, the island overwash and breaching that occur rapidly during storm events, and the recovery of primary sand dunes through Aeolian transport over decadal time scales. Littoral sediment transport within the Dauphin Island decadal-scale framework was simulated using the Delft-3D modeling software suite. The influences of wind, waves, water levels, and sediment transport are incorporated into the model. Model skill in the prediction of waves, water levels, currents, volumetric flow rates through inlets, and shoreline position was assessed by using a set of deterministic and statistical hindcast simulations. The Delft-3D modeling application described here can be coupled with validated models of storm-response and dune recovery to predict the evolution of Dauphin Island on decadal time scales.

Alabama↗

USGS2020

Estimating nitrogen removal services of eastern oyster (Crassostrea virginica) in Mobile Bay, Alabama

Eastern oysters have been acknowledged for their important contribution to human well-being by providing goods and services including nitrogen removal from water bodies. In this study, we integrated daily environmental data (2008–2016) and filtration rate model parameter uncertainty to estimate nitrogen removal from denitrification and nitrogen burial services provided by the current extent of oyster ( Crassostrea virginica ) reefs in Mobile Bay, Alabama. Oyster landing data (2008–2016) in the Bay were also used to estimate nitrogen removal through oyster harvest. A replacement cost method using an engineering solution from wastewater treatment plants was implemented to quantify the economic benefit of the nitrogen removal. The estimated total nitrogen removal services provided by oyster reefs in Mobile Bay was 34,911 ± 5,032 kg N yr −1 (mean ± 1sd), in which 22,095 ± 3,305 kg N yr −1 from denitrification, 11,047 ± 1,652 kg N yr −1 from burial of nitrogen into sediments and 1,769 ± 876 kg N yr −1 by oyster harvest. The mean economic benefit was $76,455 ± 11,020 yr −1 which was estimated as $73.2 ± 11.5 ha −1 yr −1 . This method could be used for any time period to estimate the nitrogen removal service in Mobile Bay. With proper modification of model parameters, this method could also be used elsewhere to estimate nitrogen removal services provided by oysters.

Alabama↗

USGS2020

Quantifying harvestable fish and crustacean production and associated economic values provided by oyster reefs

Quantifying ecosystem services can provide information to justify conservation and restoration decisions so as to allocate limited resources effectively. Consequently, decision makers and public typically ask for simple and understandable information with confidence regarding the availability of the services and the probable economic value. Here, we compiled published information on density enhancement and species life-history information to quantify fish and crustacean production and its uncertainty associated with the current extent of oyster ( Crassostrea virginica ) reefs in Mobile Bay, Alabama. We applied Alabama fishing size limits as a cutoff to exclude the production of non-harvestable size individuals. Fishery landing (2005–2015) and Willingness-To-Pay information were used to quantify the economic benefit of the harvestable production enhancement (commercial and recreational production). Sixteen species were found to be production-enhanced in the bay with a mean of 354 ± 182 g m −2 year −1 , of which 170 ± 112 g m −2 year −1 was economically quantifiable based on their harvestable production and landing information. The mean economic value was $509,000 year −1 in direct economic value for commercial fishers and $19.59 million year −1 estimated by the willingnesstopay value from recreational anglers. The results demonstrated a substantial positive economic benefit of ecosystem services from oyster reefs associated with fishery production in Mobile Bay, Alabama. The method could be applied elsewhere to estimate the economic return from the investment of conserving and restoring of similar structured habitats.

Alabama↗

USGS2020

Final Alabama Barrier Island restoration assessment report, appendix A: Data management plan

The Alabama Barrier Island Restoration Assessment project focused exclusively on Dauphin Island, a significant barrier island along the northern Gulf of Mexico. This restoration feasibility study effort required data collection and analysis of many data types (e.g., hydro, sediment, currents, etc.) through the project’s life cycle to assess restoration measures and their effects on the sustainability of Dauphin Island. As such, the project requires a data management plan (DMP) to address issues such as data delivery format, organizational strategies, internal data sharing, archival processes, and product dissemination.

Alabama↗

USGS2020

Decision analysis of restoration actions for faunal conservation and other stakeholder values: Dauphin Island, Alabama

Dauphin Island is a barrier island located in the northern Gulf of Mexico and serves as the only barrier island providing protection to much of the State of Alabama’s coastal natural resources. The ecosystem spans over 3,500 acres of barrier island habitat including, beach, dune, overwash fans, intertidal wetlands, maritime forest and freshwater ponds. In addition, Dauphin Island provides protection to approximately one-third of the Mississippi Sound estuarine habitats in its lee including oyster reefs, mainland marshes and seagrasses. The habitat supports a variety of species including at least 347 species of birds, some of which are Federally or State listed species that either pass through or reside on the island. The island enhances the region’s recreational and commercial fishery habitat through maintenance and protection of water quality in the sound and adjacent nearshore habitats. Dauphin Island also serves as the location for cultural resources, the United States Air Force’s (USAF) early warning radar station, the State’s marine education facilities, infrastructure for the oil and gas industry, and a vibrant tourism economy. Consequently, anthropogenic actions (e.g., structural changes) and externally driven natural factors (e.g., storms and sea level rise) that impact Dauphin Island could affect both the conservation and economic value of the island.

Alabama↗

USGS2019

Combining numerical and statistical models to predict storm-induced dune erosion

Dune erosion is an important aspect to consider when assessing coastal flood risk, as dune elevation loss makes the protected areas more susceptible to flooding. However, most advanced dune erosion numerical models are computationally expensive, which hinders their application in early-warning systems. Based on a combination of probabilistic and process-based numerical modeling, we develop an efficient statistical tool to predict dune erosion during storms. The analysis focuses on Dauphin Island, AL in the northern Gulf of Mexico, where we combine synthetic sea storms with a calibrated and validated XBeach model to develop and test a range of different surrogate models for their ability to predict barrier-island geometric parameters under storm conditions. Surrogate models are developed by combining the oceanographic forcing from 100 optimally sampled sea-storm events covering the entire multivariate parameter space (used as XBeach input) and associated changes in the dune system (XBeach output). We test four surrogate models using a k-fold approach for validation. All models perform well in predicting changes in dune elevation, barrier-island area, and width, but are less accurate in predicting alterations in the cross-shore locations of dune morphological features. Multivariate adaptive regression splines are identified as the best surrogate model based on their fast development and good performance, attaining a modified Mielke index of 0.81 for dune crest height. As demonstrated at Dauphin Island, our approach shows potential to be used in an operational framework to predict dune response (in particular crest elevation change) when water level and wave forecasts are available.

Alabama↗

USGS2019

Surrogate model development for coastal dune erosion under storm conditions

Early coastal dune erosion predictions are essential to avoid potential flood consequences but most dune erosion numerical models are computationally expensive, hence their application in Early Warning Systems is limited. Here, based on a combination of optimally sampled synthetic sea storms with a calibrated and validated XBeach model, we develop a surrogate model capable of producing fast and accurate dune erosion predictions under storm conditions when water level and wave forecasts are available. The analysis is performed on Dauphin Island, AL, where we train Multiple Linear Regression Models with oceanographic forcing from the selected sea storms (i.e., XBeach input) and predicted changes in the dune system (i.e., XBeach output). Surrogate model performance is assessed with a rigorous k-fold cross validation. Although changes in the location of dune features are not well predicted, the model attains good performance when predicting changes in dune elevation, barrier-island width and volume.

Alabama↗