Geology topics

Research about southeastern United States

Source-linked reports with geographic coverage including southeastern United States.

10 recordsLinked to original sources

USGS2026

Tracking decadal changes in frequent fire activity across the southeastern U.S. (2000-2019): Insights from Southeast FireMap

Background The dominant natural habitats in the southeastern United States depend on frequent fire ignited by humans or lightning. However, fire activity has sharply declined in the region since the early 1900s, and reduced fire activity has degraded natural habitats and increased wildfire risk. Identifying changes in fire use during recent decades is necessary to guide the conservation of fire-dependent wildlife, management of hazardous fuels, and identify areas where increased fire use could improve ecosystem resilience. To address this need, we created the Southeast FireMap dataset by fine-tuning the United States Geological Survey’s Landsat Burned Area product to track burned area, and provide a fire history across the southeastern United States. We used the Southeast FireMap data to quantify changes in areas frequently burned, as measured by areas with multiple burns within a decade. We compared the periods 2000–2009 and 2010–2019 to identify where frequently burned area is increasing or declining. We examined patterns of change across ownership, land cover, and soil orders to provide geographic context, and we considered future implications of these changes for land use categories of ecological interest. Results Frequently burned area increased between decades across the region. This increase occurred on both private and public lands, in upland vegetation types, and on upland soils, though these increases were moderately offset by decreased wetland burning and its associated soil orders. However, changes varied among states, with burned area decreasing in some states. Conclusions The overall increase in frequently burned area across the region reflects a summation of positive and negative shifts associated with specific combinations of physiography, ownership class, and government jurisdiction. Southeast FireMap marks a significant advancement in our ability to identify changes in prescribed burning within the geographic and cultural contexts that will likely influence the complex future of fire in the region.

southeastern United States↗

USGS2025

Persistence of a declining anuran species across its distribution

Information on a species’ population dynamics, such as changes in abundance and distribution, can be used to identify declining populations and initiate conservation efforts and protections. For the Ornate Chorus Frog ( Pseudacris ornata ), anecdotal observations of local extirpation and population declines have been noted, but trends in its range-wide population status are generally unknown. We used 2227 verified records of Ornate Chorus Frog presence from across the species’ distribution, grouped into 407 populations, and a modified Cormack-Jolly-Seber survival analysis to estimate the probability that historical Ornate Chorus Frog populations persist in the year 2024. Our results suggested that > 36% of historical Ornate Chorus Frog populations are possibly extirpated (probability of persistence < 0.5) and that 33% of populations had a probability of persistence > 0.9. Many of these extant populations occurred in northwestern Florida, southeastern Alabama, and southern Georgia, USA. The probability of persistence was positively influenced by habitat suitability and mean winter precipitation and negatively influenced by urban imperviousness. Ornate Chorus Frogs in protected areas had a higher average probability of persistence compared to populations that were not in protected areas. Our study fills a knowledge gap by identifying regions where Ornate Chorus Frog populations are likely thriving and regions where they may be extinct.

Alabama, Florida, Georgia, Louisiana, Mississippi,↗

USGS2025

Some of these are not like the others: Relative thermal sensitivity among anuran species of the Southeast United States

Estimating how close a species is to its upper thermal limits (i.e., warming tolerance, a thermal sensitivity index) and how that proximity changes across space enables spatially explicit identification of species with increased extinction risk as temperatures increase. Yet, thermal sensitivity is often difficult to calculate because it is the result of many traits. We aimed to synthesize multiple traits into a single estimate of relative terrestrial thermal sensitivity for 13 anuran species in the southeastern United States. We employed models that incorporate traits and microclimate variation to (1) estimate species warming tolerance (the difference between species critical thermal maximum and modeled operative temperature, an estimate of body temperature) and (2) investigate how warming tolerance varied with latitude (whereby latitude represents different temperature regimes and external drivers of thermal sensitivity). We ran mechanistic niche models across a 12° latitudinal gradient and 10 years to estimate individual operative temperature. We calculated the minimum, 25th percentile (hottest quarter), and median daily minimum warming tolerance. Estimates of minimum warming tolerance spanned −5 to 10°C ( Lithobates palustris and Gastrophryne carolinensis respectively) and differed among species. For most species, modeled operative temperatures exceeded species' critical thermal maximum during extreme warm temperatures (i.e., heat waves) in part of their range, and warming tolerance increased with latitude. During heat waves, five species had lower warming tolerance at higher latitudes, and three species' warming tolerance did not change with latitude. We identified species that are approaching their thermal limits in the Southeast and characterized spatial patterns of warming tolerance. Increased temperatures could increase anuran extinction risk, posing an additional challenge for threatened anuran species. Spatial patterns of warming tolerance were not consistent among species in our study, highlighting that patterns identified at higher taxonomic categories could be inconsistent at lower taxonomic categories.

southeastern United States↗

USGS2024

A multi-objective approach for timber harvest scheduling to include management of at-risk species and spatial configuration objectives

Sustainable forestry typically involves integration of several economic and ecological objectives which, at times, may not be compatible with one another. Multi-objective prioritization via harvest scheduling programs can be used to elucidate these relationships and explore solutions. One such program is a spatially explicit harvest scheduler that adopts the Metropolis-Hastings algorithm to iteratively find management solutions to achieve multiple objectives (Habplan). Although this program has been used to address forest management scheduling and simulation-based tasks, its utility is constrained by time-intensive data preparation and challenges with incorporating spatial configuration objectives. To address these shortcomings, we introduce an open-source software package, HabplanR, streamlines data preparation, sets parameters, visualizes results, and assesses spatial components of ecological objectives. We developed four example objectives to incorporate into a multi-objective management problem: habitat quality indices for three species “types” (open, closed, and intermediate-canopy-associated species), and harvested pine pulpwood (revenue). We demonstrate the utility of this package to find management schedules that can accommodate potentially conflicting habitat needs of species, while achieving economic targets. We produced 100 software runs and prioritized individual objectives to select four management schedules for further comparisons. We compared outcome differences of the four schedules, including a spatial comparison of two high performing schedules. The software package makes costs and benefits of different schedules explicit and allows for consideration of the spatial configuration of management outcomes in decision-making.

southeastern United States↗

USGS2024

State of science, gap analysis, and prioritization for southeastern United States water-quality impacts from coastal storms—Fiscal year 2023 program report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes

Tropical cyclones (coastal storm events that include tropical depressions, tropical storms, and hurricanes) cause landscape-scale disturbances that can lead to impaired water quality and thus reduce water availability for use. Stakeholders and scientists at local and national scales have illustrated a need for understanding these risks to water quality. A regional and comprehensive understanding of the impacts of tropical storms and hurricanes on surface-water and groundwater quality—and thus water availability—is lacking for potentially impacted coastal and inland areas. As the U.S. Geological Survey considers development of tools to predict the extent to which water-quality impacts of hurricanes affect water availability, an assessment of the state of the science of hurricane impacts is needed, including a gap analysis and prioritization of data and science needs. This assessment focuses on the southeastern coastal States.

southeastern United States↗

USGS2024

Thermal traits of anurans database for the southeastern United States (TRAD): A database of thermal trait values for 40 anuran species

Thermal traits, or how an animal responds to changing temperatures, impacts species persistence and thus biodiversity. Trait databases, as repositories of consolidated, measured organismal attributes, allow researchers to link study species with specific trait values, enabling comparisons within and among species. Trait databases also help lay the groundwork to build mechanistic linkages between organisms and the environment. However, missing or hidden physiological trait data preclude building mechanistic estimates of climate change vulnerability for many species. Thus, physiologically focused trait databases present an opportunity to consolidate data and enable species-specific or multispecies, mechanistic evaluations of climate change vulnerability. Here, we present TRAD: thermal traits of anurans database for the southeastern United States, a database of thermal trait values related to physiological thermoregulation (critical thermal minima and maxima, preferred temperature), behavioral thermoregulation (activity period, retreat emergence temperature, basking temperature, minimum and maximum foraging temperatures), and body mass for 37 anuran species found within the southeastern United States. In total, TRAD contains 858 reported trait values for 37 of 40 species found in the region from 267 peer-reviewed papers, dissertations, or theses and is easily linked with trait data available in ATraiU, an ecological trait database for anurans in the United States. TRAD contains trait values for multiple life stages and a summarization of interspecific adult trait values. Availability of trait data varied widely among traits and species. Estimates of mass were the most common trait values reported, with values available for 32 species. Behavioral trait values comprised 23% of our database, with activity period available for 34 species. We found the most trait values for Cope's Gray Treefrog ( Dryophytes chrysoscelis ), with at least one trait value for eight traits in the database. Conversely, species in the genus Pseudacris generally had the fewest trait values available. Species with the largest geographic range sizes also had the greatest coverage of data across traits (rho 5 0.75, P , 0.001). TRAD can aid studies of anuran response to changing temperatures, physiological niche space and limitations, and potential drivers of anuran geographic range limits, influencing our understanding of other ecological and evolutionary patterns and processes and enabling multispecies comparisons of potential risk and resilience in the face of climate change.

southeastern United States↗

USGS2007

Sub-sampling genetic data to estimate black bear population size: A case study

Costs for genetic analysis of hair samples collected for individual identification of bears average approximately US$50 [2004] per sample. This can easily exceed budgetary allowances for large-scale studies or studies of high-density bear populations. We used 2 genetic datasets from 2 areas in the southeastern United States to explore how reducing costs of analysis by sub-sampling affected precision and accuracy of resulting population estimates. We used several sub-sampling scenarios to create subsets of the full datasets and compared summary statistics, population estimates, and precision of estimates generated from these subsets to estimates generated from the complete datasets. Our results suggested that bias and precision of estimates improved as the proportion of total samples used increased, and heterogeneity models (e.g., M h [ C hao] ) were more robust to reduced sample sizes than other models (e.g., behavior models). We recommend that only high-quality samples (>5 hair follicles) be used when budgets are constrained, and efforts should be made to maximize capture and recapture rates in the field.

southeastern United States↗

USGS2006

Habitat use by an endangered riverine fish and implications for species protection

We investigated habitat specificity of the amber darter ( Percina antesella Williams & Etnier 1977), an imperiled fish from restricted portions of 2 rivers in the southeastern United States. Foraging amber darters occupied a narrow range of riffle habitat, consistently avoiding areas < 20 cm deep and with velocity < 10 cm. s −1 near the substrate, occupying areas with cobble or gravel substrate and average water-column velocity of 30 to 70 cm. s −1 . During low to moderate flows, approximately 20% or more of the study areas contained suitable habitat for the species. Amber darters appeared rare, and the numbers of individuals were uncorrelated with the concurrent availability of suitable habitat. Protecting the amber darter may require more than maintaining adequate depths and velocities over gravel-cobble substrates. Until we understand the potential importance of migration and dispersal for maintaining small populations, suitable habitat should be maintained over the longest contiguous stream segments possible.

southeastern United States↗

USGS1998

Ground-water quality in three urban areas in the Coastal Plain of the southeastern United States, 1995

Ground-water quality is generally good in three urban areas studied in the Coastal Plain of the southeastern United States涌cala and Tampa, Florida, and Virginia Beach, Virginia. The hydrology of these areas differs in that Ocala has many karst depressions but virtually no surface-water features, and Tampa and Virginia Beach have numerous surface-water features, including small lakes, streams, and swamps. Samples were collected in early 1995 from 15 wells in Ocala (8 in the surficial aquifer and 7 in the Upper Floridan aquifer), 17 wells in Tampa (8 in the surficial aquifer and 9 in the Upper Floridan aquifer), and in the summer of 1995 from 15 wells in Virginia Beach (all in the surficial aquifer). In the surficial aquifer in Ocala, the major ion water type was calcium bicarbonate in five samples and mixed (no dominant ions) in three samples, with dissolved-solids concentrations ranging from 78 to 463 milligrams per liter. In Tampa, the water type was calcium bicarbonate in one sample and mixed in seven samples, with dissolved-solids concentrations ranging from 38 to 397 milligrams per liter. In Virginia Beach, water types were primarily calcium and sodium bicarbonate water, with dissolved-solids concentrations ranging from 89 to 740 milligrams per liter. The water types and dissolved-solids concentrations reflect the presence of carbonates in the surficial aquifer materials in the Ocala and Virginia Beach areas. The major ion water type was calcium bicarbonate for all 16 samples from the upper Floridan aquifer in both Florida cities. Dissolved-solids concentrations ranged from 210 to 551 milligrams per liter in Ocala, with a median of 287 milligrams per liter, and from 187 to 362 milligrams per liter in Tampa, with a median of 244 milligrams per liter. Concentrations of nitrate nitrogen were highest in the surficial aquifer in Ocala, and one sample ex-ceeded 10 milligrams per liter, the U.S. Environmental Protection Agency maximum contaminant level for drinking water. Median nitrate concentrations were 1.2 milligrams per liter in Ocala and only 0.06 and 0.05 milligram per liter in Tampa and Virginia Beach, respectively. In Florida, some background water-quality data were available for comparison. The median nitrate concentration in Ocala was much higher than the median nitrate concentration of 0.05 milligram per liter in the background data. Median nitrate concentrations were 0.33 and 0.05 milligram per liter in samples from the Upper Floridan aquifer in Ocala and Tampa, respectively, and 0.05 milligram per liter in background samples. Of the 47 pesticides and 60 volatile organic compounds analyzed, only five pesticides and five volatile organic compounds were detected. The most commonly detected pesticide was prometon, a broad-scale herbicide, detected in samples from eight wells in Ocala (at concentrations ranging from 0.009 to 1.8 micrograms per liter), three wells in Virginia Beach (at concentrations ranging from 0.19 to 10 micrograms per liter), and from one well in Tampa (0.01 microgram per liter). The most commonly detected volatile organic compound was chloroform, which was d etected four times at concentrations ranging from 0.3 to 2.2 micrograms per liter in Ocala and Tampa. Seven volatile organic compounds were detected in one sample in Virginia Beach; most were compounds associated with petroleum and coal tar.

southeastern United States↗

USGS1981

Pattern-recognition program modified and applied to southeastern United States seismicity

The pattern-recognition technique of Bongard and others (1966), Gelfand and others (1976), and Briggs and others (1977) was modified and applied in Southeastern United States to try to detect combinations or interactions of geologic, geophysical, and topographic parameters characteristic of areas with moderate and large earthquakes. The modification involved replacing the operator-defined criteria for significance of association of parameters and earthquakes with statistical estimates of significance. This was done in order to decrease the probability of random associations and to increase the flexibility of the pattern-recognition technique. The binomial distribution was used to determine the probability that each particular association could have occurred by chance. Bonferroni's inequality was invoked to determine a conservative significance level for each of the binomial tests. However, without being able to quantify the dependence among the associations, it is not possible to statistically evaluate the group of binomial tests as a whole. Preliminary results identify four independent associations characterizing spatially independent earthquake epicenters, or "dangerous" points, and seven independent associations characterizing the intervening "safe" points. When all points were reclassified using these traits, all epicenters were correctly classified as dangerous. In addition, three "safe" points were reclassified as dangerous and appear to be potential sites for future earthquakes. However, it is not possible to determine the degree of dangerousness of the points using this reclassification scheme. Two dangerous zones emerge in the northeast and southwest portions of the study area. Epicenters outside of these zones, including those of the large historic earthquakes (MMI > VIII) in Giles County, Virginia, and Charleston, South Carolina, have not been well characterized by the significant associations and may have fundamentally different causes.

southeastern United States↗