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20 recordsLinked to original sources
USGS2026

Family life is critical for migration and survival in a long-lived social bird

Extended parental care is common among birds and particularly well known among long-lived migratory species. Yet, factors influencing the duration of parental care are poorly understood, and empirical evidence for the functional importance of family life for offspring development is scarce. Using unique tracking and genetic data of 55 adult and juvenile migratory Bewick’s swans, among which 18 parent-offspring pairs and 13 sibling pairs, we quantify variation in family bond duration and identify the cause and consequences of their dissolution. Families generally broke up during the second half of the first northward migration of the offspring, when offspring were nearly one year old. Earlier separation occurred on the wintering grounds in response to disturbance ( n = 10 juveniles) and led to delayed migration and, critically, lower survival (40 vs. 86%). Our results provide rare empirical evidence that family bonds, as a pathway for social learning, are not just important, but vital to the migration and survival of young family-living birds.

Behavioral Ecology and Sociobiology↗
USGS2026

Influence of new residential construction varying in housing density on bird species, human tolerance guilds, and communities

Human population growth and changing settlement patterns fuel the development of urban fringe lands worldwide, with implications for biodiversity. We conducted a 12-year study of birds in the fast-developing urban fringe lands of the central Puget Sound region, Washington, USA, to examine the effect of development configuration on birds. We hypothesized that lower-intensity conservation developments, compared to higher-intensity planned community developments, would benefit the overall bird community, as well as native forest birds (avoiders of human development) and avian generalist species (adapters to human development), but that higher-intensity planned community developments would benefit synanthropic species (exploiters of human development). We fit single-species and multi-species occupancy models to test these hypotheses. Consistent with our hypotheses, we found that a greater proportion of the overall community, avoiders, and adapters occupied lower-intensity conservation developments compared to higher-intensity planned community developments. However, we did not detect an effect of development type on the exploiter guild, and we found that species in the exploiter guild are variable in their response to the configuration of suburban developments. We also hypothesized that human tolerance guilds would be a useful predictor of individual species responses to development type. This hypothesis was somewhat supported: we found that, for avoiders, 87% of species in the guild had the same response to development type as the overall guild; for adapters, 63% had the same response as the overall guild, and for exploiters, only 44% had the same response as the overall guild. Our results indicate that the configuration of suburban developments can have a meaningful impact on bird communities, particularly on those species that are most sensitive to any level of development.

Washington↗
USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗
USGS2026

A practical decision tool for marine bird mortality assessments

Given the rise in anthropogenic, environmental, and disease events contributing to marine bird mortality, there is a critical need to improve the rigor of mortality assessments. Deficits in data collection and mortality estimation can hinder a manager’s ability to document the scale of events and assess population level impacts. Therefore, to inform decisions required during activities, such as conservation status assessments or harvest management, organizations may choose to incorporate mortality assessments into response plans. Resources, capacity, and assets to assess mortality vary across jurisdictions (federal, state, Indigenous, local, etc.), and clear guidance to support mortality assessments is often unavailable or not clearly addressed. Here, we present a decision support tool to help managers identify and evaluate survey options to assess bird mortality in a diverse array of scenarios. The objective of the decision tool is to improve data collection and availability, which will increase the ability to estimate mortality robustly, given situation-specific attributes and constraints. This decision tool is designed to guide the response when a mortality event is initially encountered and offers suggestions for assessment and reporting procedures in the absence of other guidance or to complement existing protocols. The decision tool is also meant to inform decision making for response determination and resource allocation. The tool facilitates examination of options for further assessment and monitoring, which users determine by examining questions pertaining to species prioritization, determination of mortality minimum spatial extent, and the potential magnitude of impacts on affected species. Finally, identification of appropriate survey methods that address imperfect detection when a complete census is not possible are determined by exploring location, spatial and temporal extent, and the type of species affected. Ultimately, this decision tool aims to facilitate and improve the standardization of mortality assessments, equipping managers with a practical resource to navigate the decision-making process for marine bird mortality estimation.

Ornithological Applications↗
USGS2025

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California↗
USGS2026

Incorporating location uncertainty improves inference with stop-level North American Breeding Bird Survey data

Ecological models should account for uncertainty to be most effective and useful. Yet, uncertainty from model covariates—unlike that from other sources, such as sampling error or process variability—is seldom explicitly incorporated. This can cause underestimates of uncertainty to cascade through model parameter estimates, predictions, and downstream uses. Burner et al. proposed a method for quantifying uncertainty in covariates and incorporating it into models using informative Bayesian priors. This method was applied to stop-level Breeding Bird Survey (BBS) analyses, where land cover uncertainty at each stop arises from substantial stop location uncertainty. A limited validation of model-estimated land cover, using stops with known locations, indicated the method’s potential effectiveness, but it was not rigorously evaluated. We conduct a robust simulation-based test, generating stop locations, extracting land cover, and simulating bird communities across 210 BBS routes in the upper Midwest. We compare 3 models: a “known” model with true land cover, a “naive” model assuming consistent 800-m stop spacing, and a “full” model using informative priors to estimate land cover. Species parameter estimates and predicted prevalence patterns across gradients in land cover from the full model approached those of the known model and were substantially closer to the true values used in simulations relative to those from the naive model. Naive model parameters were more biased relative to the other models, and credible intervals of predicted species prevalence rarely included the true simulated values. The full model also produced land cover covariate estimates closer to true simulation values relative to the mean informative priors. Our results show that, for the BBS, informative priors enable more accurate stop-level analyses despite location uncertainty. In contrast, naive models that ignore this uncertainty yield poor inferences. More broadly, we demonstrate empirically the utility of informative priors to account for covariate uncertainty in ecological models.

Michigan, Minnesota, Wisconson↗
USGS2026

Black rails in Baja California

Summarizing records from 1905 to 2025, we document the presence and distribution of the California black rail ( Laterallus jamaicensis coturniculus ) in northwestern México, particularly Baja California and the Colorado River Delta. This subspecies has a restricted distribution in the western U.S. and northwestern México. We found few records over the past century: sparse detections in the early 1900s and an increase in reported records after 2000. Over 120 years, we compiled 35 documented records of California black rail occurrence in Baja California with a minimum reported count of 56 rails. Our call-broadcast survey methods reconfirmed previously occupied sites and documented the species at a previously unreported site. Surveys in the Baja California portion of the Colorado River Delta yielded 20 detections across nine survey events between 2000 and 2022. In April 2003, standardized surveys detected 12 California black rails: 7 in Bahía de San Quintín, 3 in Arroyo San Telmo, and 2 in Arroyo El Rosario. Our recent survey work (2022–2025) recorded maximum monthly counts of 31 detections at Bahía de San Quintín and 15 detections at Estero de Punta Banda, the latter representing a previously undocumented location for the subspecies. These surveys also yielded the first photographic and acoustic documentation of California black rail in México. The contribution of spatial and temporal data provided by citizen science platforms increased our understanding of the subspecies’ distribution. Enforceable protection of this subspecies’ habitat is needed to safeguard its persistence.

Baja California↗
USGS2024

U.S.-Mexico Borderland & vegetation community map

People on both sides of the United States-Mexico border need a high-resolution, binational vegetation community map that spans the entire United States-Mexico borderlands. Traditionally, mapping efforts in this region were impeded by complex logistics related to the international border, differing national needs and plans, and resource allocations and priorities. To address this need, scientists from the U.S. Geological Survey (USGS) Southwest Biological Science Center partnered with the Sonoran Joint Venture, the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program, data engineers from the Department of Biosystems Engineering at the University of Arizona, and collaborators from the Wildlands Network, the Borderlands Program to produce the first prototype land cover map within the overlapping Mojave Desert, Sonoran Desert, and the North American Bird Conservation Initiative’s Bird Conservation Region 33 (BCR33) using Landsat satellite data . BCR33 is an area of high biodiversity, providing habitat for bird species of concern and other wildlife. The land cover map supports FWS recovery plan efforts related to conservation planning activities for many species, including Yellow-billed Cuckoo ( Coccyzus americanus ), Cactus Ferruginous Pygmy-Owl ( Glaucidium brasilianum cactorum ), Southwestern Willow Flycatcher ( Empidonax traillii extimus ), Yuma Ridgway’s Rail ( Rallus obsoletus yumanensis ), Bendire’s thrasher ( Toxostoma bendirei ), LeConte’s thrasher ( Toxostoma lecontei ), Masked Bobwhite ( Colinus virginianus ridgwayi ), jaguar ( Panthera onca ), and endangered plants such as Bartram’s stonecrop ( Graptopetalum bartramii ) and the Pima pineapple cactus ( Coryphantha robustispina ssp. robustispina ). In 2024, a Phase-II map for the full BCR33 region was completed, increasing the understanding of the binational nature of natural communities. The published map and associated paper can be found here .

Borderland↗
USGS2026

GST-1: A high-resolution global sediment thickness model

Global Sediment Thickness 1 (GST-1) is a high-resolution sedimentary thickness model calculated on a 0.125° x 0.125° grid. It modifies the sediment thickness of the 1° x 1° Earth Crustal Model 1 (ECM1) by means of 3D inversions of free air gravity anomalies. GST-1 is calculated by performing structural inversions on high-density contrasts across two crustal boundaries: the sediment – basement interface and the crystalline crust – upper mantle interface. The inversions are calculated in each of ten overlapping 3D models that span the globe. These ten models are merged to obtain the GST-1 global model, providing an eight-fold increase in lateral spatial resolution in comparison with ECM1 and CRUST 1.0. Our sediment thickness model exploits the nearly continuous sampling of gravity data when compared to the irregular, sparse sampling of seismic refraction data. Sediment thickness values in GST-1 are in excellent agreement with independently derived cross sections from well-studied sedimentary basins, and within expected resolution limits of seismic refraction data. GST-1 offers a robust, high resolution global model of sedimentary thickness to support studies of sedimentary basins.

Tectonophysics↗
USGS2026

Age and colony variation in Adélie penguin metapopulation vital rates: Insights from a 25-year mark–recapture study

Understanding how vital rates vary with age, life-history stage, and among populations is fundamental for predicting the demographic consequences of environmental change, especially in longer-lived species with complex life histories. These species often exhibit delayed maturity and iteroparity, making nuanced demographic insights critical for assessing their long-term viability. This study investigated age- and colony-related variation in Adélie penguin vital rates including survival, recruitment, and breeding propensity. We used mark–recapture data collected over 25 years (1996–2020) from three Adélie penguin breeding colonies that differed in population sizes and trends but comprised a metapopulation located at capes Royds, Bird, and Crozier on Ross Island, Antarctica. We used multi-state models to estimate survival and detection rates relative to reproductive state and breeding colony and estimated transition probabilities reflecting movements between reproductive states and colonies. Apparent survival varied by reproductive state, colony, and age and averaged 0.80 (SD = 0.02) at Bird, and 0.72 (SD = 0.03) and 0.73 (SD = 0.03) at Crozier and Royds, respectively, for pre-breeders age 2–7 years with strong declines in pre-breeder survival after age 8. We observed less age-related variation in survival of breeders and non-breeders, but we observed differences between colonies with lower survival for breeders (0.72 to 0.80) compared to non-breeders (0.75 to 0.82). The average probability of surviving the first 2 years after fledging ranged from 0.43 (SD = 0.14) at Royds and Crozier (0.43, SD = 0.10) to 0.55 (SD = 0.15) at Bird. Movement between colonies was highest for pre-breeders (0.00%–12.00% depending on age and colony) and lowest for breeders (<0.20%). We observed the lowest age-related recruitment rates at Royds, with recruitment at Crozier almost twice as high, and intermediate at Bird. Breeding propensity was highest at Crozier and lowest at Bird. Colony-specific variation in vital rates likely contributed differently to population trajectories, suggesting that care must be taken to extrapolate vital rate estimates across colonies even within a metapopulation. These findings also highlight the importance of considering age, life-history stage, and geographic variation when assessing population vital rates in species with complex life histories.

Frontiers in Ecology and Environment↗
USGS2026

Cotton farming pesticides affect ileal microbiota activity expressions of virulome but not resistome or metabolic pathways in a sedentary wild passerine

The increased use of agrochemicals to enhance crop production has had detrimental environmental effects including implication in the sharp decline of North American farmland-breeding birds. Here, using a combination of deep shotgun metatranscriptomics and pesticide exposure data, we sought to assess whether exposure to cotton ( Gossypium spp.) production had a differential effect on ileum multi-kingdom microbial activity, metabolism, anti-microbial resistance, and virulence factors of sedentary northern mockingbirds ( Mimus polyglottos ) sampled from two cotton-producing areas (16 birds in total) and one uncultivated area (7 birds) in Texas, USA. Both Shannon Index values (Adj. r 2 = 0.174, F (1,21) = 5.633, p = 0.027) and a Mantel test (Spearman ρ = 0.184, p = 0.013) supported a relationship between metabolically active microbiota Bray–Curtis dissimilarities and differences in pesticide mixtures among study areas. Virulence factor richness (Adj. r 2 = 0.182, F (1,21) = 5.890, p = 0.024), Shannon Index (Adj. r 2 = 0.231, F (1,21) = 7.612, p = 0.012), and load (sum of virulence factor abundances; Adj. r 2 = 0.160, F (1,21) = 5.194, p = 0.033) were related to total pesticide load (total quantity of pesticides). We found no pesticide effects on expression of either antimicrobial resistance genes or metabolic pathways.

Texas↗
USGS2026

King Rails in southeastern Arkansas are majority resident

King Rails ( Rallus elegans ), a declining species of secretive marsh bird, have a mixed migratory strategy, with some individuals migrating and some being year-round residents. Determining the distribution of migratory versus resident King Rails is critical to guiding habitat management and assessing risks to populations. We examined the migratory status of adult King Rails at the Choctaw West Wildlife Management Area in southeastern Arkansas, the only known site in Arkansas with multiple breeding pairs. Of the 23 adult King Rails we tagged in 2022 and 2023, two birds migrated away from the local area, one in each year. One migrated 145 km, and the other 450 km. Our findings suggest that the line between the migratory and resident range of Arkansas King Rails could be north of our site.

Arkansas↗
USGS2026

Biome-scale spatial patterns of avian abundance reveal proactive conservation opportunities in North American grasslands

North American grassland birds have experienced steeper population declines than any other avian guild, yet conservation efforts remain largely reactive and fragmented. We used nearly four decades of North American Breeding Bird Survey data to identify biome-scale spatial patterns (clustering) of grassland bird abundance for the Great Plains. Our results reveal an ecological core in the north-central Plains where community-level abundance is either increasing by >100% or remains high and stable, providing a strategic roadmap for a “Defend the Core” conservation approach. This approach flips the script from reactive triage centered on isolated population fragments to a proactive strategy of maintaining large-scale ecosystem integrity. Conversely, we found that population losses are more spatially clustered than wins, reflecting the relentless, one-way movement of woody encroachment and agricultural conversion. This asymmetry supports prioritizing intact landscapes, as current restoration rates are often outpaced by the scale of habitat loss. Notably, we found that community-level spatial clustering is a more robust indicator of biome condition than trends of individual flagship species, suggesting that managing for ecosystem integrity provides a more effective multi-species umbrella. Given our results, there is an opportunity for operationalizing a Great Plains Conservation Design that is ecosystem-centric and rooted in the sustainability of the private-land cattle production that maintains these open spaces. By leveraging avian abundance as a biological sensor, managers and producers can deploy a shared vision that matches the spatial scale of the threats, moving from reactive triage to proactive defense of core working grasslands in North America.

Great Plains biome↗
USGS2026

End-user needs for remote sensing wetlands of the Prairie Pothole Region of North America

The Prairie Pothole Region (PPR) of North America comprises globally important grassland and wetland ecosystems critical for numerous populations of migratory birds. Due to the importance of this region for migratory birds, and particularly waterfowl, and the threats of habitat loss due to intensifying agriculture, there is a mature and diverse system of conservation organizations, agencies, and partnerships that spends hundreds of millions of dollars annually on habitat conservation to support migratory bird populations. Remote sensing can be a powerful tool for observing and evaluating global change at large scales as well as expanding inferences from field studies to the broader landscape with statistical models. However, development and utilization of these tools has lagged behind their demand for several reasons, including concerns over spatial and temporal resolution and accuracy of products; perception of a misalignment with decision-maker needs; technological barriers such as skill sets of conservation professionals, computing resources, data access, and usability. In this report, we summarize the needs of conservation professionals and scientists who use or want to use remote sensing data products to inform science about wetland change and conservation of wetlands in the PPR. We assembled this information through several methods leading up to, during, and following a January 2026 PPR Wetland Remote Sensing Workshop. The workshop included United States and Canadian scientists, conservation professionals, and policy experts. Our goal was to bring together end-users and remote sensing product developers jointly to explore reducing the lag between product development and utilization of products to inform science and conservation. Specifically, we aimed to identify gaps in wetland remote sensing that limit effective monitoring, management, and conservation in the PPR, and to develop a framework that outlines pathways to address these gaps by fostering collaboration, improving communication networks, encouraging discussion, and building on existing and ongoing efforts. This report summarizes our participants’ descriptions of end-user needs and the outcomes of the workshop.

Prairie Pothole region↗
USGS2026

Creation of aerial camera system boresight installations in Bangor, Maine; Monroe, Louisiana; and Bassville Park, Florida

Aerial camera systems rely on boresights for defining internal and external metrics. The U.S. Fish and Wildlife Service’s Migratory Bird Surveys Branch required boresights to calibrate their camera systems for creating georeferenced imagery that can then be used in geographic information systems. The U.S. Geological Survey created high-accuracy boresight installations in Bangor, Maine, in July 2024; Monroe, Louisiana, in September 2024; and Bassville Park, Florida, in January 2025 to provide this metric-defining capacity to the U.S. Fish and Wildlife Service. This U.S. Geological Survey Data Report details the methods and results of the boresight installation process and provides camera operators with the data needed to use each of the installations.

Florida, Louisiana, Maine↗
USGS2026

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗
USGS2024

Hydrologic investigations and a preliminary conceptual model of the groundwater system at North Penn Area 1 Superfund Site, Souderton, Montgomery County, Pennsylvania

The U.S. Geological Survey (USGS) conducted hydrogeologic investigations, reviewed existing data, and developed a preliminary conceptual model of the groundwater system as part of technical support of the U.S. Environmental Protection Agency (EPA) at the North Penn Area 1 Superfund Site (hereafter, the NP1 Site) located within the Borough of Souderton in Montgomery County, Pennsylvania. Field work and monitoring took place during 2012–18. The area is underlain by sedimentary formations that form a fractured-rock aquifer used for drinking water and industrial supply. The EPA placed the Site on the National Priorities List in 1989, identifying tetrachloroethylene (PCE) and trichloroethylene (TCE) as contaminants of concern. During 2012–18, the USGS conducted field activities that included drilling an 82-foot (ft)-deep monitoring well (MG 2220) in 2016, reconstructing a 208-ft-deep former industrial production well (MG 668 [Granite Knitting Mill]), and collecting borehole geophysical and video logs and water levels from those and five additional wells, which ranged in depth from about 50 to 200 ft below land surface. Continuous water levels were collected during 2014–17, and a synoptic set of water levels were measured in April 2018 in the seven wells. The borehole geophysical logs (caliper, acoustic televiewer, natural gamma, single-point resistance, vertical flow, and fluid temperature and resistivity) and borehole video logs in the seven wells were evaluated to assess potential for lithologic correlation and to identify and describe water-bearing features, which included both low- and high-angle fractures and other openings oriented along dipping bedding planes, joints, or possible faults. Borehole geophysical logs collected by USGS in 1992 in a 300-ft-deep former production well near the Site were also evaluated. Few to no distinctive features were identified on geophysical logs (natural gamma and single-point resistance) that could be used for correlation, thus limiting this approach to determining local geologic structure. Extensive fracturing in the upper 62 ft of monitoring well MG 2220 indicates that the well was likely drilled through a zone of faulting, and other evidence of faulting is present in the area near the Site. Assessment of continuous water levels showed hydraulic connections among some wells as indicated by rising or falling water levels in response to changes in pumping rates at nearby wells. A map of water levels measured in April 2018 indicates potential for groundwater flow generally toward the stream to the south and southwest of the Site, but the limited water-level data are insufficient to describe vertical groundwater gradients or lateral gradients in any detail. Review of 1999–2022 volatile organic compound (VOC) monitoring data collected by the Pennsylvania Department of Environmental Protection for five monitoring wells indicates that the highest groundwater concentrations of PCE and TCE were found in samples from extraction well MG 2201 (S-1) downgradient from, and nearest to, the previously identified Site contaminant source area, and these concentrations fluctuated through time. PCE concentrations were higher than TCE concentrations in samples from all five monitoring wells and were much higher than TCE concentrations in samples from extraction well MG 2201 (S-1). Temporally variable recharge is a possible factor affecting observed fluctuations in PCE concentrations in groundwater samples from well extraction MG 2201 (S-1), as indicated by a general inverse relation between PCE concentrations and water levels in a nearby long-term observation well. The PCE concentration of 1,830 micrograms per liter (μg/L) in a May 2018 water sample from monitoring well MG 2220 was more than four times the PCE concentration of 444 μg/L in a December 2017 sample from the nearby extraction well MG 2201 (S-1), which is open to fewer fractures. Low concentrations of VOCs were measured in surface water at two stream sites downgradient from wells with the highest groundwater VOC concentrations at the Site, indicating that discharge of contaminated groundwater to the stream is likely. Development of a conceptual model of the groundwater system was constrained by limited data. In areas with no pumping, groundwater-flow directions generally are thought to be controlled by topography and geologic structure (bedding orientation) and likely to the south and southwest of the Site, with local flow directions affected by orientations of fractures, joints, and local faults. Additional investigations that could help improve the conceptual model of the groundwater system and help delineate the extent of groundwater contamination and its transport are discussed.

Pennsylvania↗
USGS2022

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina↗