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Research about Texas

Source-linked reports with geographic coverage including Texas.

At least 19 recordsLinked to original sources
USGS2026

Incorporating wetland drowning thresholds to assess the spatiotemporal variability in potential wetland migration and submergence from sea-level rise

In the coming decades sea-level rise rates could exceed the upper bounds of coastal wetland vertical movement leading to wetland submergence. Consequently, understanding the spatiotemporal variability of wetland migration and submergence at regional and national scales can inform decision making. In this study, we developed an approach that addresses elevation error in digital elevation models for wetlands, incorporates uncertainty in current and future water levels, and utilizes recent literature on coastal wetland drowning thresholds. We used our framework to predict wetland change with sea-level rise for the middle and upper Texas coast—a region that is experiencing some of the highest relative sea-level rise rates in the United States. Our elevation-based approach produced contemporary wetland maps that had a high level of agreement (> 87–91%) with existing national wetland maps. For the intermediate relative sea-level rise scenario, extensive change is predicted within the study area by 2100, including a net decrease in coverage of irregularly oceanic-flooded wetlands (-37%) and regularly oceanic-flooded wetlands (-23%). The wetland migration space of these two wetland zones is largely made up of existing wetlands (> 70%), but also includes other upland areas, such as pasture/hay and grassland. By breaking down our results for the full region and two distinct focal areas, we highlight the spatiotemporal variability of wetland change. Our scalable approach provides natural resource managers with information for developing location-specific strategies for balancing the trade-offs associated with wetland change from sea-level rise.

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USGS2026

Continuous monitoring and temporal variability of fluorescence of dissolved organic matter in karst groundwater of the Edwards aquifer, south-central Texas, 2019–24

Widespread urbanization on the Edwards aquifer recharge zone in south-central Texas has prompted the development of new approaches and tools for evaluating the current and future status of water quality in the San Antonio and Barton Springs segments of the Edwards aquifer. The U.S. Geological Survey, in cooperation with the San Antonio Water System and the City of Austin, applied continuous monitoring of fluorescence of dissolved organic matter (fDOM) to characterize the sources and transport of dissolved organic matter and associated constituents in the Edwards aquifer. Continuous fDOM time-series data were adjusted using empirically derived temperature, turbidity, and inner-filter-effect correction factors prior to analysis and interpretation. Fully corrected fDOM time-series data from the study sites were evaluated for short- and long-term temporal variability in fDOM in the context of the hydrologic and climatic conditions that occurred during the 5-year study period to understand vulnerability of the aquifer to potential contaminants in recharge. Study results indicate that fDOM is an effective proxy for dissolved organic carbon that, in turn, is indicative of the influx of recent surface water and associated contaminants, and thus, aquifer vulnerability to those contaminants. Although other continuously monitored water-quality parameters provide insights into changes in water quality in response to varying hydrologic conditions, the quantitative relation between fDOM and dissolved organic carbon directly indicates the timing and magnitude of pulses of organic constituents derived from the land surface, whereas other water-quality parameters do not.

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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.

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USGS2026

3D Elevation Program—Texas

Using 3D Elevation Program data, a modern illustration of each State's landscape showcases its elevation differences in vivid detail. Each State has been consistently adjusted and colorized according to its highest and lowest elevations, accentuating differences even in States with low relief. To further emphasize landforms, shaded relief has been added on top of the elevation colors.

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USGS2026

Geologic framework, hydrostratigraphy, and ichnology of the Blanco, Payton, and Rough Hollow 7.5-minute quadrangles, Blanco, Comal, Hays, and Kendall Counties, Texas

During 2023, the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, revised an initial characterization completed during 2015–16 of the geologic framework, hydrostratigraphy, and ichnology of the Edwards (Balcones Fault Zone) and Trinity aquifers in the Blanco, Payton, and Rough Hollow 7.5-minute quadrangles in Blanco, Comal, Hays, and Kendall Counties, Texas. The purpose of this report is to present the updated geologic framework, hydrostratigraphy, and ichnology of the Trinity and Edwards Groups in those quadrangles. Rocks exposed in the study area are of the Lower Cretaceous Trinity Group and lower part of the Fort Terrett Formation of the Lower Cretaceous Edwards Group. The faulting and fracturing in the study area are part of the Balcones Fault Zone, an extensional system of faults active during the Paleocene to middle Eocene that generally trends southwest to northeast in south-central Texas. Hydrostratigraphically, the rocks exposed in the study area contain a section of the Edwards (Balcones Fault Zone) aquifer, upper zone of the Trinity aquifer, and middle zone of the Trinity aquifer. In the study area, the only hydrostratigraphic units of the Edwards (Balcones Fault Zone) aquifer remaining are (from top to bottom) VII and VIII, which cap several hills. The mapped hydrostratigraphic units of the upper zone of the Trinity aquifer are (from top to bottom) the cavernous, Camp Bullis, upper evaporite, fossiliferous, and lower evaporite. The mapped hydrostratigraphic units of the middle zone of the Trinity aquifer are (from top to bottom) the Bulverde, Little Blanco, Twin Sisters, Doeppenschmidt, Herff Falls (where present), Rust, Honey Creek, Hensell, and Cow Creek hydrostratigraphic units.

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USGS2026

Improving building footprint extraction using NAIP and 3DEP lidar derived features with deep learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

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USGS2026

Structure-aware unsupervised transmission corridor structure extraction from 3DEP lidar using graph attention embeddings and reinforcement-learned DBSCAN

Transmission corridors are critical components of power delivery infrastructure, and their large-area monitoring increasingly relies on national-scale airborne lidar programs. This study presents an unsupervised, scalable framework for extracting transmission corridor structures (including conductors and supporting towers) from U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) lidar point clouds. The workflow begins with height-above-ground filtering and statistical outlier removal to isolate elevated infrastructure candidates. Local Principal Component Analysis (PCA) is then used to compute fine-scale geometric descriptors. To incorporate spatial context and improve structural separability in feature space, we learn point embeddings using a Graph Attention Network (GAT) trained with a structure-consistency triplet objective, yielding representations tailored for downstream density-based grouping rather than semantic classification. To address the spatial non-stationarity of point density and noise across large scenes, we formulate Density-Based Spatial Clustering of Applications with Noise (DBSCAN) parameter selection as a reinforcement learning problem and employ Proximal Policy Optimization (PPO) to adapt 𝜀 and minPts at the block level based on embedding statistics. The final extraction is produced via block-wise DBSCAN and spatial merging to support efficient processing of multi-million-point clouds. Experiments on USGS 3DEP data over Houston, Texas, show that the proposed method produces spatially coherent candidate corridor structures from unstructured lidar. Quantitative assessment is conducted using OpenStreetMap (OSM)-referenced spatial-agreement metrics under a consistent vector-reference protocol, alongside comparative baselines and ablation studies, to examine the relative contributions of graph embedding learning and RL-based adaptive clustering.

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USGS2026

Depositional interplay between the Ancestral Rocky Mountains and Ouachita–Marathon–Sonora orogenies: Insights from provenance records in the late Paleozoic Marfa Basin, West Texas, U.S.A.

The Marfa Basin in West Texas is a late Palaeozoic synorogenic depocenter associated with regional deformation linked to the Ancestral Rocky Mountains (ARM) and Ouachita–Marathon–Sonora (OMS) orogenies in southwestern Laurentia. Basin strata range in age from Middle Pennsylvanian to the middle Permian and include the Cieneguita, Alta, Pinto Canyon, Rose Mine and Mina Grande Formations. Sandstone petrography and detrital zircon (DZ) U–Pb and (U–Th)/He double dating data from these strata reveal three tectonically driven sedimentation stages: syntectonic ARM deposition, progressive OMS foredeep deposition and an orogenic transition. The Cieneguita and lower part of the Alta Formations exhibit a Mesoproterozoic DZ age signature (~1318 and ~1076 Ma age peaks) and quartzo-feldspathic sandstone compositions sourced from the adjacent ARM-related Diablo Platform basement uplift in the Middle Pennsylvanian to earliest Permian. In contrast, the upper part of the Alta Formation, as well as the Pinto Canyon and Rose Mine Formations, have peri-Gondwanan DZ age signatures, with Mesoproterozoic (~1069–1036 Ma age peaks), Neoproterozoic–Cambrian (~700–490 Ma) and Palaeozoic (~490–300 Ma) age modes and litho-quartzose sandstone compositions derived from the OMS fold-and-thrust belt and orogenic hinterland during the early to middle Permian. The lower to middle parts of the Alta Formation have alternating DZ age signatures and sandstone compositions from both ARM and OMS sources, revealing that the transition in the sediment supply occurred during the middle Wolfcampian. This transition was not characterised by source mixing, but rather by sediment interfingering alternately sourced from the Diablo Platform uplift and the advancing OMS belt. These observations are confirmed by the DZ He ages, which reveal distinct cooling histories for both source terranes. These results document a switch from ARM- to OMS-related syntectonic deposition in southwestern Laurentia during the early Permian, demonstrating that ARM-driven deformation largely preceded the continental collision along the Marathon segment of the OMS orogen.

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USGS2026

Diverse novel and avian-associated viruses in the ileal viromes of northern mockingbird (Mimus polyglottos)

Viruses are the most abundant and diverse organisms on Earth, though only a small portion cause disease. Understanding viral diversity is key to understanding and predicting pathogen emergence and zoonotic spillover. Here, we use meta-transcriptomic sequencing to examine the viral communities in the ileum of 25 Northern Mockingbirds ( Mimus polyglottos ) from various locations across Texas. We assembled high-quality genomes of 43 viral species (40 species identified to 13 families, one to kingdom, and two to realm), 38 of which were novel. They tentatively represent avian- (n = 3), arthropod- (n = 21), plant- (n = 5) and fungi- (n = 4) associated, or other (n = 10) viruses. The arthropod-associated Dicistroviridae family was the most dominant, comprising known and potentially new species. Of potential epidemiological importance were three novel and avian-associated viruses: members of the families Hepeviridae and Picornaviridae , and a new Matryoshka RNA virus. The Matryoshka RNA virus 8 (MaRNAV-8) is sister to other Matryoshka RNA viruses, and its co-occurrence with haemosporida further supports the nested virus-parasite-vector-vertebrate host relationship of this group of viruses, with potential implications for parasite evolution, fitness and load and vector competence. The Picornaviridae virus is a member of an avian hepatovirus clade, found nested within a clade containing both the mammalian pathogens Hepatovirus A – I and the avian Tremovirus pathogens, suggestive of a newly discovered pathogen of Northern Mockingbird. Although the recovered Hepeviridae virus is of unknown pathology, its family members include the Hepatitis E viruses. With the great diversity and novelty described from ileal viromes, discriminating potential pathogens and commensal microbiota from viruses associated with food items remains challenging. A deeper understanding of virus transmission and the risk of potential zoonosis can be enhanced by tracking viruses through the food web and via inter-specific and predator-prey interactions, particular in areas subject to land-use change, where human-wildlife interactions are increased and the risks from emerging pathogens of veterinary and medical importance are more pronounced.

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USGS2026

Metalloporphyrins in the Eagle Ford Shale

Using Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), Zheng et al. (2018, Energy & Fuels 32, 10382) reported abundant iron and vanadyl porphyrins and minor amounts of gallium and nickel porphyrins in asphaltenes extracted from a single lower Eagle Ford Shale sample. This finding is most unusual as iron and gallium porphyrins have been previously found only in coal. In this study, petroporphyrins in samples of the Eagle Ford Shale previously studied by French et al. (2020, Marine Petrol. Geol. 118, 104459), were examined using atmospheric pressure photoionization (APPI) FT-ICR-MS. Vanadyl porphyrins (N4VO) dominated the asphaltenes in thermally immature (VRo < 0.56%) samples decreasing in relative abundance with increasing maturity. Only minor amounts of nickel porphyrins were detected in the immature and early oil samples. The distribution of the vanadyl porphyrins is comparable to those reported for marine oils at varying levels of maturity. Immature samples contained porphyrins that were predominantly deoxophylloerythroetio- (DPEP: DBE = 18) and di- deoxophylloerythroetio (di-DPEP: DBE = 19) porphyrins, while ETIO- (DBE = 17), rhodo- (DBE = 20, 21, and 22) and higher condensed (DBE ≥ 23) porphyrins increased with increasing maturity. The vanadyl porphyrins included species with additional one to three oxygen atoms (N4VOx, x= 1 to 4) and one sulfur atom with one to two oxygen atoms (S1N4VOx, x=1 to 3). The degree of additional oxygen and sulfur atoms is consistent with O/C and Sorg/C of associated kerogen. No iron or gallium porphyrins were detected, showing that they are not a ubiquitous feature of the Eagle Ford. We hypothesize that the previously reported iron and gallium porphyrins (Zheng et al., 2018) were present because the specific sample that was analyzed in detail was from the early onset of the Cenomanian–Turonian oceanic anoxic event (OAE-2) in contrast to the samples investigated in this study that are primarily from the lower part of the Eagle Ford pre-dating OAE-2. Submarine volcanism, associated with eruption of large igneous provinces, occurred pre-OAE-2, injecting iron and other inorganic nutrients, giving rise to algal blooms and the acidification of the seawater. At the onset of OAE-2, boreal water masses flowed into the southern Western Interior Seaway, shifting the water column to more oxygenated conditions. Low pH-high Eh (oxic) conditions enhance the availability of iron and gallium such that these events abruptly changed the seawater chemistry, specifically enriching iron and gallium relative to vanadium and nickel. These pH-Eh conditions are similar to the depositional conditions associated with coals, which are known to contain iron and gallium porphyrins, suggesting similar conditions resulted in iron and gallium metalation of porphyrins in the marine setting of the Western Interior Seaway.

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USGS2026

Inference of pattern-based geological CO2 sequestration and oil recovery potential in a commingled main pay and residual oil zone CO2-EOR flood

Several detailed studies have shown that residual oil zones (ROZs) can present significant resources for additional hydrocarbon recovery as well as subsurface carbon dioxide (CO 2 ) sequestration via enhanced oil recovery by injecting CO 2 (CO 2 -EOR). Field development strategies included new wells drilled dedicated to main pay zones (MPZ) and ROZs, or existing wells in MPZs deepened to ROZs for commingled injection-production using different well patterns. The latter presented a challenge when discerning the injection and production from each of the zones, and for subsequent quantification of CO 2 sequestration and EOR potential from different patterns and from the field. In this paper, an innovative method for analyzing commingled injections and productions from MPZs and ROZs, with application to pattern-based data from four staggered line drive patterns in Wasson Field's Denver Unit, Texas, USA, was developed. Decline curve and ratio-trend methods were used as means of history-matching and forecasting. Cumulative production-time and cumulative production-rate data for oil, gas, and water, as well as water-oil ratio (WOR) and gas-oil ratio (GOR), were analyzed along with injection data for time intervals covering major injection events in MPZ, or MPZ and ROZ combined. A combined analysis enabled inference of allocation of fluids into different zones during WAG (water alternating gas) injection and thereby estimation of CO 2 storage, utilization, and retention in different zones as a function of total injection. Results show that ROZs generally present higher CO 2 sequestration potential compared to MPZs, and a comparable incremental oil recovery factor of ∼20%, on average. Results based on ratio analysis further show that while the WOR trend of the pattern production is mostly dominated and controlled by ROZ, GOR is controlled by both intervals. Although the method relying on decline curves and the approach used in zonal fluid allocations are subject to their limitations, this study presents a practical and innovative well-pattern-based method to infer and forecast CO 2 sequestration and oil recovery quantities and fluid ratios from MPZs and ROZs in commingled operations and highlight the added potential offered by ROZs.

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USGS2026

Water-budget simulations for selected watersheds in Cameron County, Texas, 2022–23

The U.S. Geological Survey, in cooperation with the City of Brownsville, Texas, configured and calibrated a set of hydrologic models for a 217-square-mile study area in Cameron County in south Texas during 2022–23. The models were used for estimating runoff and quantities of water diverted from the Rio Grande/Rio Bravo del Norte (hereinafter referred to as the “Rio Grande”) to maintain water-surface elevations in the canals and resacas (former distributary channels cut off from the main channel of the Rio Grande). Resacas provide habitat to aquatic species and help reduce the effects of flooding. Because of the large size of the study area and diversity of hydrologic conditions, the study area was divided into 11 watersheds, and separate hydrologic models were developed for 9 of the watersheds. Six of the nine modeled watersheds are drained mostly by canals (canal watersheds), and three of the modeled watersheds drain to resacas (resaca watersheds). The Hydrological Simulation Program—FORTRAN was selected for modeling the study area watersheds because it is flexible in simulating a wide variety of watershed conditions. The models were calibrated with streamflow data collected during 2022–23. The calibrated models were used to simulate water budgets (streamflow, evapotranspiration, water-storage volumes, and water diversions and withdrawals) during 2022–23. Model simulations showed that the resaca watersheds required more diversions from the Rio Grande and released less runoff than did the canal watersheds. Management practices maintaining resaca water levels constrained their runoff.

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USGS2026

Cotton farming affects ileal virome in a sedentary wild passerine

Although a few studies have focused on avian gut virome variation in response to environmental stressors, none have assessed virome in relation to the production of chemically intensive crop-based agriculture that alters food resources and detrimentally affects various aspects of avian health and fitness. In this study, we used shotgun metatranscriptomics to assess whether exposure to cotton ( Gossypium spp.) production had a deleterious effect on the ileal virome 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. We recovered 43 viruses representing 13 virus families, which included two viruses that appear to be potential vertebrate pathogens. Individual sample richness varied from 25 to 33 viruses. Both virome richness (Adj. r 2 = 0.247, F (2, 20) = 4.615, P = 0.022) and composition (r 2 = 0.370, F (2, 20) = 5.883, P = 0.001) differed among three sampling regions. Cotton production was associated with the increase of virome richness (Adj. r 2 = 0.283, df = 22, P = 0.005). Pesticide occurrence data collected using silicone bands at the three sites suggest that virome compositional changes are not only associated with total pesticide exposure but are also particularly sensitive to the pesticide combinations detected at each location.

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USGS2026

Year-round daytime pCO2 undersaturation in an instream series of urban reservoirs with a history of harmful algal blooms

Daytime water quality was determined monthly over two years in an instream series of four urban reservoirs with recurring blooms of Prymnesium parvum —a cool-season toxigenic species. Temperature, pH, and laboratory-measured total alkalinity were used to estimate p CO 2 . System-wide, p CO 2 was negatively associated with dissolved oxygen. Chlorophyll- a , phycocyanin (cyanobacterial pigment), and P. parvum were negatively associated with p CO 2 and positively with dissolved oxygen. Three reservoirs were productive and, during daytime, p CO 2 -undersaturated year-round or near-year-round, while a fourth (third in the series) was unproductive and mostly p CO 2 -oversaturated. Seasonal phycocyanin and chlorophyll- a patterns indicated that cyanobacterial and eukaryotic ( P. parvum included) phytoplankton growth drives daytime CO 2 depletion in the productive reservoirs during the warm and cool seasons, respectively. The system’s moderate alkalinity (HCO 3 − ) may serve as an alternative carbon source for photosynthesis; however, the persistent depletion of CO 2 and the energetic cost of using HCO 3 − are consistent with a scenario where phytoplankton growth is CO 2 -limited. Daytime p CO 2 undersaturation across seasons has been rarely reported, but this study indicated it occurs more often than recognized. The non-monotonic spatial patterns in productivity and carbonate system conditions across the study reservoirs indicate that localized influences from a heterogeneous urban landscape may help shape individual lake metabolism.

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USGS2026

Comparative assessment of STIC sensors, streamflow and rain gauges for quantifying river connectivity in intermittent systems

In intermittent stream systems, including those occurring in Texas, USA, the severity of low-flow conditions, duration of seasonal disconnection, and frequency of no-flow events have been amplified by drought. Documentation of these no-flow events is necessary to evaluate ecosystem health. However, many intermittent reaches remain un-gauged given that perennial river sec-tions are often prioritized for gauge placement. Our objectives were to 1) document stream flow using Stream Temperature, Intermittency, and Conductivity (STIC) loggers to determine the frequency and duration of no-flow events in intermittent tributaries of the Colorado River, Texas and 2) compare logger data to publicly available data from streamflow discharge and precipitation gauge networks to understand differences among these data types for drying event characterization. We use these comparisons to summarize benefits and limitations of the application of in-stream data loggers. STIC loggers were deployed at 19 sites, one in each pool and riffle habitat of a stream reach. STIC loggers recorded a measurement of relative conductance every six hours from June 2022 to March 2024, which was used to determine the presence or absence of flow connectivity in a reach. No-flow duration among intermittent reaches varied between 37 and 270 days across tributaries during an ongoing drought in the study area. Overall, logger data was more precise than discharge data for characterizing no-flow events or precipitation data when documenting presence of water in the stream channel due to runoff. Lack of discharge gauges in intermittent tributaries left large sections of stream reaches undocumented and resulted in mischaracterization of flow patterns. Drought severity across the tributaries did not follow longitudinal patterns that would be expected by the climatic precipitation gradient of the study area. More research is needed to determine if factors such as population size affect severity. Likewise, precipitation data did not correlate well with logger water presence data, lacking consideration for groundwater recharge, soil hydrophobicity, and surface compaction. This study shows that to monitor no-flow events, detailed spatial datasets are necessary and that STIC loggers are useful tools that provide data to fill spatial information gaps and facilitate more accurate flow characterization and water presence data in intermittent systems.

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USGS2026

Inland habitat selection model for wintering whooping cranes

Inland habitat use by wintering Aransas-Wood Buffalo whooping cranes ( Grus americana ) is expected to increase given projected population growth and observations of some whooping cranes using inland winter habitat in addition to coastal marshes. We developed resource utilization functions using ‘random forests’ to model whooping crane use as a function of environmental covariates considered important for whooping crane use. Covariates associated with distance to cropland, distance to development, and wetness or standing water were the most influential in model prediction. The model estimated that the 50% predicted use contour encompassed 34,925 hectares (ha) and the 95% predicted use contour encompassed 328,928 ha within the study area. While presently limited by the small sample size of inland wintering areas observations ( n = 7 cranes with ≥50 locations), this model provides an initial tool for identifying potential impacts to whooping crane inland habitat use in proximity to anthropogenic development. The model can be expanded to incorporate future data to reduce uncertainty.

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USGS2025

How high? Identifying elevation thresholds to guide coastal marsh restoration

Introduction Coastal marshes are highly valuable ecosystems facing threats from rising sea levels and intensifying storm events. To elevate marsh surfaces and prevent loss of ecosystem services, the beneficial use of dredged material (BUDM) is increasingly being implemented across the United States. Objectives The objective of this study was to aid decision-makers and restoration practitioners by identifying elevation thresholds that control the optimal function of Spartina patens -dominated marshes along the Texas Coast. Methods This study was conducted in the coastal marshes of the J.D. Murphree Wildlife Management Area (Texas). We collected elevation and vegetation cover data along ecological transition zones in marshes nourished with BUDM to identify elevation thresholds that define zones of optimal plant survivorship and growth. Results We identified lower (−0.05 m mean high water, MHW) and upper (0.26 m MHW) elevation thresholds that defined transitions to open water and unvegetated bare ground, respectively. Elevation targets ( T ) and elevation target zones, which defined areas with the greatest vegetation cover, were determined for S. patens ( T : 0.11 m, target zone: −0.06 to 0.26 m MHW), S. alterniflora ( T : 0.00 m, target zone: −0.12 to 0.10 m MHW), and Distichlis spicata ( T : 0.17 m, target zone: 0.07–0.25 m MHW). Conclusions Our analyses provide species-specific elevation targets for coastal marsh restoration through BUDM, which can improve restoration outcomes for coastal wetlands.

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