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USGS2024

Editorial: From cold seeps to hydrothermal vents: Geology, chemistry, microbiology, and ecology in marine and coastal environments

This Research Topic compiles contemporary studies on cold seeps, hydrothermal vents, mud volcanoes, and related seafloor features that are associated with focused fluid emissions and the transfer of carbon, other chemical species, and sometimes heat from the geosphere to the ocean. Because these features sometimes tap fluids and gas originating kilometers below the seafloor, they provide an important window into deep processes that are otherwise inaccessible to scientists. At the shallow portion of their journey, migrating fluids nearing the seafloor contribute to a range of unique biological, physical, and chemical processes within the sediments themselves and at the sediment-water interface. Seafloor fluid emissions play a critical role in global biogeochemical cycles, ocean chemistry, and possibly even climate change. Seafloor leakage points often emit hydrocarbon gases (especially methane and CO 2 ) and are sometimes the loci for deposition of seafloor minerals that have economic value. A burgeoning area of research focuses on natural products generated at these features, seeking compounds with potential pharmaceutical or other applications. Multidisciplinary studies have become routine for characterization of seafloor fluid emission sites, attesting to the inseparability of geologic, physical, chemical, and biological processes in these settings. It is increasingly common for researchers to combine in a single research cruise: subbottom imaging and seafloor mapping; porewater and water column geochemistry and gas sampling; sediment retrieval for lithologic, biostratigraphic, and solid phase analyses; and studies of benthic and subseafloor communities at the microbial to macrofaunal scales. This multidisciplinary approach has the advantage of ensuring the spatial and temporal coincidence of surveys and samples, an important factor at highly dynamic seafloor fluid emission sites. In addition, researchers often use remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), or human-occupied vehicles (HOVs) to record video of the seafloor, compile photomosaics, collect targeted samples, and survey with high-resolution geophysical near-seafloor systems, providing a degree of detail about seafloor fluid emission sites that is unprecedented compared to most areas of the deep ocean. While rarer, long-term cabled observatories or shorter-term deployments of portable observatories are also used at some loci for seafloor fluid flux and are particularly helpful for capturing temporal variations at these dynamic features. Here we summarize the Research Topic’s contribution to multidisciplinary seafloor emission studies in the categories of cold seeps, mud volcanoes, and hydrothermal vents. Figure 1 shows the geographic distribution of the studies in this Research Topic and key features referred to in this Introduction.

Frontiers in Earth Science↗

USGS2026

Unraveling protracted modification of Archean and Paleoproterozoic crust in central Laurentia, Penokean orogen, with garnet and accessory mineral geochronology and microstructural analysis

Proterozoic metamorphism and deformation of the southern margin of the Superior craton in the Lake Superior region is attributed to the Penokean orogeny (1890−1830 Ma). This model includes a period of crustal inversion in which Archean basement blocks were exhumed through overlying Paleoproterozoic strata, producing the corridor of gneiss domes that parallels the trend of the Penokean orogen across the northern Midcontinent, USA. However, recent geologic mapping and 40 Ar/ 39 Ar geochronology challenge this interpretation, suggesting instead that the gneiss dome structures reflect younger episodes of tectonic activity along the southern margin of Laurentia. In absence of integrated pressure-temperature-time-deformation constraints for these rocks, interpretations are largely limited to their final cooling history, making it difficult to both identify the tectonic forces that shaped the architecture of the Penokean orogenic belt and assess the extent to which later Proterozoic tectonism modified the southern Superior craton. We address this problem with an approach joining thermodynamic modeling, garnet and accessory mineral geochronology, and microstructural analysis for several metamorphic rocks across the gneiss dome corridor. The U-Pb ages of titanite reveal that the Proterozoic geometries of exhumed basement gneiss domes are governed by preexisting Archean structures. Garnet Lu-Hf geochronology constrains the timing of prograde-to-peak metamorphism in the Penokean orogenic belt. Granulite facies metamorphism is related to the final stages of the Penokean orogeny at 1837 Ma and localized in a belt of high-grade rocks near a major Penokean suture. Garnet Lu-Hf ages of samples adjacent to gneiss domes reflect regional metamorphism following the accretionary phase of the Penokean orogeny, between 1825 Ma and 1782 Ma, which we suggest reflects continued crustal thickening related to convergence farther south during this time interval. Combination of garnet microstructures and Sm-Nd ages reflects later exhumation of gneiss domes and buried metasedimentary rocks by ca. 1750 Ma, consistent with previously published 40 Ar/ 39 Ar cooling ages across the region. Reset Lu-Hf and Sm-Nd garnet ages and U-Pb ages of syn-kinematic titanite reflect reactivation of primary Penokean structures during this period of basement uplift. These data document significant modification of the Penokean orogen and the Archean crust of the southern Superior province between 1800 Ma and 1700 Ma. Tectonic activity during this interval coincides with collisional events recognized in western Laurentia, suggesting that the period immediately following the Penokean orogeny may be a broadly important time for crustal growth and modification in proto-North America.

Michigan, Wisconsin↗

USGS2025

ShakeAlert® version 3: Expected performance in large earthquakes

The ShakeAlert earthquake early warning (EEW) system partners along with U.S. Geological Survey (USGS) licensed operators deliver EEW alerts to the public and trigger automated systems when a significant earthquake is expected to impact California, Oregon, or Washington. ShakeAlert’s primary goal is to provide usable warning times before the arrival of damaging shaking. EEW is most likely to achieve this goal in large‐magnitude earthquakes. In recent years, ShakeAlert has gone through a series of upgrades to its underlying scientific algorithms aimed at improved performance during large earthquakes. Version 3 of this software recently went live in the production system and includes improvements to all algorithms. The main seismic algorithms that detect an earthquake and characterize its location, magnitude, and fault rupture orientation are faster than older versions. Other key changes include: using real‐time geodetic data to characterize the magnitude growth in large earthquakes; the introduction of an alert pause procedure to compromise between speed near the epicenter and improved accuracy at larger distances; and the inclusion of a nonergodic site‐response model in the ground‐motion predictions. ShakeAlert has achieved its primary goal of usable warning times before strong shaking at some locations in real‐time operations in recent M 6 earthquakes. Using offline tests, we demonstrate usable warning times are possible for many sites with peak shaking values of modified Mercalli intensity (MMI) 7–8 in M 7+ earthquakes and also for many MMI 8–9 sites in M 8+ earthquakes. ShakeAlert partners use a variety of MMI and magnitude thresholds in deciding when to alert their users within bounds set by the USGS. Our study shows that there is room to raise the magnitude thresholds up to about M 5.5 without adversely affecting performance in large earthquakes. The ground‐motion criteria are more complex owing to a significant drop‐off in warning times between the MMI 4 and 5 levels of predicted shaking. However, widely used ShakeAlert products, such as the MMI 3 and 4 contour products, can provide sufficiently long warning times before strong shaking in moderate‐to‐great earthquakes to enable a range of protective actions.

Bulletin of the Seismological Society of America↗

USGS2024

Mesoproterozoic to Paleozoic tectonics, Pleistocene landforms, and Holocene seismicity in the Blue Ridge: Results from integrated studies of the 9 August 2020, Mw 5.1 earthquake area near Sparta, North Carolina, USA

This field trip examines the results of integrated geologic studies of the 9 August 2020, M w 5.1 earthquake near Sparta, North Carolina, USA. The earthquake generated ~4 km of coseismic surface rupture of the Little River fault and uplifted a surface area of ~11 km 2 . The Little River fault is a thrust fault oriented 110–130°/45–70°SW, and mapped fault segments are en echelon with scarp heights from <5–30 cm. The epicenter is in polydeformed rocks of the Ashe and Alligator Back Metamorphic Suites in the eastern Blue Ridge. Bedrock structure formed during multiple Paleozoic orogenies; the regional foliation strikes NE-SW and dips SE (mean orientation 063°/52°SE). Mapping identified late Paleozoic veins and shear zones, a regional joint set striking 330–340° and 250–240°, and brittle faults that cut the Paleozoic foliation. Brittle faults oriented similar to the Little River fault are mapped up to 4 km along strike from the coseismic rupture along Bledsoe Creek valley, and the combined length of the Little River fault system is ~8 km. Paleoseismic trenches across the Little River fault corroborate the reactivation of an older fault by the 2020 earthquake and reveal two events during late Pleistocene (<50 ka). Surficial mapping identified several terrace deposits, including a deposit along Bledsoe Creek that yielded a 26 Al/ 10 Be isochron burial age of 0.46 ± 0.13 Ma and overlies a brittle fault, thus constraining the timing of movement of the fault at that location. Paleoliquefaction studies document soft-sediment deformation features in alluvium that may represent paleoseismic events. Collectively, these results highlight long-lived paleoseismicity of the Blue Ridge and that the 9 August 2020 earthquake reactivated an older, suitably oriented brittle fault in the bedrock. The Little River fault is an example of a previously unknown but active fault lying outside of known seismic zones with demonstrated recurrence of paleo-ruptures, raising questions about the assumption that damaging earthquakes are limited to areas of ongoing background seismicity, which is counter to seismic hazard assessments in the eastern United States. Bedrock mapping separates eastern Blue Ridge lithostratigraphy of the Lynchburg Group and Ashe and Alligator Back Metamorphic Suites into separate fault-bound packages juxtaposed over various 1.3–1.0 Ga basement rocks of the northern French Broad massif by the Gossan Lead fault.

North Carolina↗

USGS2026

Tectonic implications of transitional melting regimes from petrological, geochronological, and compositional characterization of the ophiolitic Seventymile terrane, Alaska, USA

New geochemical, U-Pb geochronology, and Sr-Nd-Hf isotope data provide evidence for the tectonic evolution of the Seventymile terrane in interior Alaska, USA. Ultramafic and mafic rocks of the Seventymile terrane are thought to represent components of a dismembered ophiolite and provide unique constraints on regional terrane evolution and accretion. The Seventymile ophiolite represents fragments of the Devonian to Permian Slide Mountain Ocean (SMO) that separated allochthonous and parautochthonous continental fragments of western North America. It now occurs as multiple thrust sheets containing Permian mafic and ultramafic rocks overlying and/or possibly imbricated with amphibolite-facies supracrustal rocks of allochthonous Yukon-Tanana terrane and parautochthonous North America. Seventymile klippen contain variably serpentinized peridotite, primarily harzburgite, low-grade meta-mafic rocks, and minor oceanic sedimentary rocks (argillite, chert, limestone, and metasandstone). Mafic rocks include gabbro to diabase, typically as dikes, veinlets, or rare massive stocks intruding peridotite. Mafic rocks also include greenstones of the Seventymile assemblage in klippen structurally underlying, and in shear zone contact with, ultramafic klippen. New trace element and radiogenic isotope data from mafic magmatic rocks associated with the Seventymile ultramafic bodies show evidence for a weakly subduction-modified mantle source, like the mantle source of normal mid-ocean-ridge basalt (N-MORB) or back-arc basin basalt (BABB). Seventymile assemblage greenstones are more heterogeneous. They range from N-MORB to enriched mid-ocean-ridge basalt (E-MORB) and ocean-island basalt (OIB), with a subset of samples indicative of continental arc affinity. These geochemistry results indicate that distinct tectonic environments are represented by at least two, and possibly three, lithological and structural units comprising the Seventymile terrane. Hf-Nd isotope systematics are consistent with a depleted MORB mantle (DMM)−like component that overlaps with Pacific MORB. Primary zircon is rare, but new in situ U-Pb data for gabbro and greenstone indicate ca. 274−272 Ma peak zircon and titanite crystallization. Scattered younger zircons define a ca. 255 Ma zircon peak and correspond to secondary crystallization associated with baddeleyite reaction of high-Si fluids during low-grade metamorphism. If Seventymile suites are contemporaneous, obduction associated with the closure of the SMO resulted in the stacking of ophiolitic packages representing distinct tectonomagmatic settings across the transition from pericontinental, to epicontinental, to distal ocean back-arc. Intrusions hosted in klippe of ultramafic rocks, plus the least subduction-modified greenstones underlying them, geologically and compositionally resemble Slide Mountain rocks of the Campbell Range formation in eastern Yukon and may provide a new piercing point across the Tintina fault.

Alaska, British Columbia↗

USGS2025

Base-flow sampling to enhance understanding of the groundwater flow component of nitrogen loading in small watersheds draining into Long Island Sound

Excessive nitrogen discharge is a major concern for the Long Island Sound. Programs have been implemented to reduce point sources of nitrogen to the sound, but little is known about the nonpoint sources. This study aims to better understand the current groundwater contributions of nitrogen from nonpoint sources in the Long Island Sound watershed. During the spring and summer of 2022, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, collected water-quality samples to analyze nutrients (nitrogen and phosphorus), chloride, and bromide at 45 stations in the Long Island Sound watershed in Connecticut, New York, and Rhode Island. The stations were in small drainage watersheds (5 to 30 square kilometers) in the southern part of the Long Island Sound watershed. During two separate synoptic sampling events, water-quality samples and instantaneous streamflow measurements were collected under base-flow conditions (where the streamflow is dominated by groundwater inputs rather than overland flow or runoff flow). One sampling event was in the nongrowing season (April 24–25, 2022), and the other was in the growing season (June 30–July 1, 2022). To calculate instantaneous nitrogen loads and yields, streamflow was measured at the time of sample collection. Nitrogen concentrations, loads, and yields varied among sampling stations and by season. Total filtered nitrogen concentrations were generally lower in the nongrowing season (from less than 0.14 to 1.9 milligrams per liter) than in the growing season (from less than 0.23 to 3.0 milligrams per liter). Nitrate plus nitrite concentrations showed little variation between the nongrowing and growing seasons. Unfiltered ammonia plus organic nitrogen concentrations were generally lower in the nongrowing season (from less than 0.07 to 0.83 milligram per liter) than in the growing season (from 0.11 to 0.98 milligram per liter). In contrast, total filtered and unfiltered nitrogen loads and yields were higher in the nongrowing season than during the growing season, likely because streamflows were higher during the nongrowing season. Total unfiltered nitrogen yields during the nongrowing season ranged from less than 0.15 to 5.0 kilograms per square kilometer per day. Total unfiltered nitrogen yields during the growing season ranged from less than 0.12 to 2.5 kilograms per square kilometer per day. Total filtered nitrogen yields during the nongrowing season ranged from less than 0.13 to 5.2 kilograms per square kilometer per day. Total filtered nitrogen yields during the growing season ranged from less than 0.06 to 2.5 kilograms per square kilometer per day.

Connecticut, New York, Rhode Island↗

USGS2023

Explosive trachyte eruptions from the Al Efairia volcanic center in northern Harrat Rahat, Kingdom of Saudi Arabia

Harrat Rahat is an alkali basalt, continental, intraplate volcanic field located within the central-western part of the Kingdom of Saudi Arabia. The northern quarter of Harrat Rahat contains evolved volcanic products that achieve trachyte compositions (>60 weight percent SiO 2 ). Within the Al Efairia volcanic center, pyroclastic-flow and -surge deposits that reflect explosive trachyte volcanism (and minor exposed lava domes that reflect effusive trachyte eruptions) sit at the surface as the youngest expression of volcanic activity within this part of the Harrat Rahat volcanic field. Five trachyte deposits emplaced explosively have been identified within the Al Efairia volcanic center based on geologic mapping, petrography, geochemistry, and paleomagnetism. These units are the trachytes of Um Rgaibah, Gura 5, Gura 4, Al Efairia, and Al Qayf, in descending stratigraphic order. Here, we present 14 40 Ar/ 39 Ar analyses from four of these units, which yield eruption ages of 4.2±5.2 thousand years (ka) for the trachyte of Um Rgaibah, 79.7±1.6 ka for the trachyte of Gura 5, 84.3±1.6 ka for the trachyte of Gura 4, and 88.0±1.8 ka for the trachyte of Al Efairia. The eruption age of the trachyte of Al Qayf has been constrained to between 410.3±3.4 and 418.8±1.9 ka using paleomagnetic correlations and 40 Ar/ 39 Ar ages from overlying and underlying intermediate composition lava flows. Most of these trachytes have distinct geochemical compositions, petrographic characteristics, and directions of remanent magnetization. The exceptions are for the trachytes of Gura 4 and Gura 5, which overlap in their geochemical, petrographic, paleomagnetic, and geochronologic affinities. Based on these similarities, we interpret the trachytes of Gura 4 and Gura 5 to have erupted during a closely spaced (a few decades) time interval from the same magma batch but from craters that are >2 kilometers (km) apart. The eruption of the trachyte of Al Efairia at 88.0±1.8 ka is the result of a different magma batch that erupted a few thousand years prior to the trachytes of Gura 4 and Gura 5. The Al Efairia volcanic center is remarkably different from the Matan volcanic center located ~10 km to the north, which has also erupted young (<150 ka) trachytes. The Matan volcanic center has been shown to produce trachyte compositions only after eruption of basalt followed by intermediate lava flows, whereas only trachyte compositions have erupted within the Al Efairia volcanic center over this same time interval.

Al Efairia volcanic center, Harrat Rahat↗

USGS2025

Gravity and magnetic surveys of the Skaergaard intrusion, East Greenland

Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland were carried out in July–August 1971 as part of a grant to the University of Oregon Center for Volcanology to refine the models of crystallization and differentiation of the intrusion, specifically to test whether the intrusion is underlain by dense rocks of a reservoir 20 kilometers (km) thick (referred to as a “hidden zone”). The Skaergaard intrusion is a source of platinum group elements that are critical mineral resources for many technologies, and because no new data have been collected these legacy datasets remain a valuable asset. The total-intensity aeromagnetic survey was flown in early July 1971 with a proton precession magnetometer at a constant barometric altitude of 1.5 km (5,000 feet) with a nominal line spacing of 1 km. Two gravimeters were used to acquire 168 stations of which 86 were at known altitudes (mainly sea level) and 82 had altitudes measured by altimetry in late July–August 1971. Finally, a north-south ground vertical-intensity magnetic traverse was completed across the intrusion together with collection of oriented hand specimens. The hand specimens were measured for remnant magnetization and density, along with density measurements of more specimens collected by expedition geologists for other purposes. The intrusion is composed of layered gabbro with extensive crystal fractionation that is dense and strongly reversely polarized. After terrain correction and standard Bouguer gravity reduction, the gravity anomaly dataset was corrected for all rock above sea level using the density measurements of the various zones of the intrusion and the topographic and geologic maps (variable density Bouguer gravity reduction). A large regional gradient in the gravity anomaly data was removed using orthogonal polynomial fitting to the gridded data. The zonal volumes of rock below sea level were calculated from the dipping polygonal layer gravity model of the intrusion below sea level and combined with elliptic cross–section cylinders for the various zones above sea level to approximate the original zonal volumes of the intrusion. The residual gravity anomaly of 18–20 milligals (mGal) was only about half of the expected anomaly if a large hidden zone proposed from petrologic considerations were present, and both two-dimensional and three-dimensional models imply that the exposed series of intrusion zones explain the gravity anomaly by their down-dip extension below sea level together with a small hidden-zone volume. A three-dimensional model of the exposed rocks and their down-dip extension below sea level also can account for the aeromagnetic anomaly with little or no requirement for hidden-zone rock. The middle and upper zone units of the intrusion contain the most magnetite and account for most of the aeromagnetic anomaly.

Skaergaard intrusion↗

USGS2025

Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)

Residual oil zones (ROZs) can offer significant oil resources via enhanced oil recovery (EOR) as well as subsurface carbon dioxide (CO 2 ) retention during injection. If injected CO 2 is anthropogenic, the ROZs can offer a substantial geologic storage potential. The ROZs below the oil/water contact (OWC) of main pay zones (MPZ) in conventional reservoirs or brownfields, are more commonly developed for CO 2 injection and oil production and reported in the literature. However, CO 2 -EOR in greenfield ROZs, reservoirs without a MPZ present, have rarely been developed for CO 2 -EOR operation. The Tall Cotton Field of West Texas, Permian Basin, which started production in 2015 (Phase 1) and expanded in 2017 (Phase 2) from the San Andres Limestone, is one of the first examples of greenfield ROZs developed for EOR by injecting CO 2 . This paper analyses EOR and CO 2 retention performance of Tall Cotton Field using allocated injection and production data from inverted 5-spot well patterns of Phase-1 and -2 developments. Production and injection data allocated to each of the 28 identified patterns (nine 20-acre patterns for Phase-1, three 20-acre and sixteen 10-acre patterns for Phase-2) were analyzed for historical and forecasted oil recovery using ratio-trend decline analysis, and for CO 2 retention performance of the patterns. The allocated data were further used to calculate injected reservoir pore volume and void replacement ratios (VRR) for the analysis period. Quantitative results indicated that oil recovery factors of the 5-spot patterns varied between 4–10 %, and 5–30 % between the end of injection and the forecast periods, respectively. Storage of CO 2 , on the other hand, increased to a mean value of ∼7130 MMscf per pattern in Phase-1 and to a mean storage of 3700 MMscf per pattern in Phase-2 until the end of injection, followed by a decline after the end of injection and into the forecast period. Resulting CO 2 utilization factors ∼6–50 Mscf/bbl were estimated at the end of injection. Overall, presented results suggested that developing greenfield ROZs for CO 2 -EOR can be as promising as brownfield ROZs and mature MPZs for EOR and underground storage of injected CO 2 . For Tall Cotton Field, results suggest that Phase-2 patterns generally outperformed Phase-1 for oil recovery factors, while Phase-1 performed better in CO 2 retention performance metrics. This is the first study in the literature that reports a detailed CO 2 -EOR performance analysis of a greenfield ROZ in the Permian Basin, which can potentially allow for comparison with MPZs and brownfield ROZs.

Texas↗

USGS2024

The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates

LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.

Fire↗

USGS2026

Conventional hydrothermal power-producing systems of the Great Basin, USA

As part of the update to the electric-grade conventional hydrothermal assessment of the Great Basin, USA, Monte Carlo analyses of identified resources within explored regions will be performed to make estimates of discovered resources and associated uncertainty. Analyses use conditional statistics where estimates are conditioned upon a hydrothermal favorability map, allowing for the likelihood that more resources exist in regions of higher hydrothermal favorability. For these analyses, a dataset of identified hydrothermal systems is compiled, and the new compilation is described herein. Recognizing that a single hydrothermal system may be developed with multiple power plants, and that the hydrothermal upflow zone may be several kilometers across with many measurements characterizing a single hydrothermal system, a procedure was developed and employed to create clusters of points (power plants, measurements, etc.) that are associated with a single system, and a new central point was defined as the best estimator of the center of the hydrothermal system. Hydrothermal systems were uniquely identified by grouping electric-grade hydrothermal measurements and operating power plants within a distance of 10 km. Groups that are >10 km apart are assumed to be different electric-grade hydrothermal systems. While 10 km was used as the threshold, most systems were significantly further apart, and most points within groups were typically within 5 km of each other. A well measurement was considered an electric-grade measurement of a hydrothermal system if it had two properties: a measured temperature of >85 °C and evidence of hydrothermal convection. Other points that were added to the dataset are locations of operating powerplants or locations that have been classified as an electric-grade hydrothermal resource by either the U.S Geological Survey (USGS) or the Great Basin Center for Geothermal Energy. After all points are assigned to systems, new points were computed with the goal of identifying the center of the throat of the hydrothermal upflow zone. If operating powerplants exist for a system, then the arithmetic average of all power plant locations is used. Otherwise, if USGS made an estimate, that location is used. In the absence of both powerplants or USGS estimates, the arithmetic average of all electric-grade measurement locations is used. An example is shown of how these newly compiled locations might be ranked for uncertainty analyses, where higher confidence is assumed if measured temperature is higher and there are many supporting measurements indicating an electric-grade resource. In summary, 28 systems have operating power plants, an additional 78 systems are known identified electric-grade hydrothermal resources, and 99 new systems were identified as probable electric-grade systems with varying levels of confidence. These 205 locations are shown as a function of a recent hydrothermal favorability map, conceptually illustrating the conditional statistics that can be used to make estimates of the undiscovered resources of the Great Basin. An accompanying data release provides summaries of developed capacity by system and USGS estimates of likely total capacity and associated uncertainty.

Arizona, California, Idaho, Nevada, Oregon, Utah↗

USGS2025

Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy

The Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked by section 7002 (“Mineral Security”) of title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Congress) with reviewing and revising the methodology used to evaluate mineral commodity supply risk and the U.S. List of Critical Minerals (LCM) no less than every 3 years. Following two previous LCM assessments, this analysis represents the latest technical input for evaluating each mineral commodity’s supply risk and determining their recommended status on the LCM. We evaluated mineral commodity supply risk using two criteria: (1) an economic effects assessment that quantified the potential effects of various trade disruption scenarios on the U.S. economy, and (2) an examination of whether the mineral commodity’s U.S. supply chain relied on a sole domestic producer that represented a single point of failure. For the first criterion, postdisruption equilibrium quantities and prices for each mineral commodity were calculated based on their price elasticities of supply and demand and the availability of excess production capacity for each yearlong foreign trade disruption scenario. Subsequently, a nonlinear optimization routine was used with detailed economic input-output tables to estimate the potential economic effects on the U.S. economy of over 1,200 scenarios for 84 mineral commodities. After accounting for the probability of each scenario’s occurrence, the overall results are presented in terms of changes in U.S. gross domestic product (GDP) by individual industry and the economy overall. The results, which ranged from a net decrease in U.S. GDP of nearly $4.5 billion to a net increase of $33 million, largely reflect U.S. import dependency and world production concentration. Using the Jenks natural breaks optimization method, a statistical classification technique, we categorized the mineral commodities into several classes based on this overall risk quantification. Mineral commodities with annualized probability-weighted net decreases in U.S. GDP greater than $2 million were recommended for inclusion on the LCM. If a mineral commodity did not meet the threshold for inclusion on the LCM under the first criterion, its domestic supply chain was examined under the second criterion, which recommended a mineral commodity for inclusion on the LCM if there was only a single domestic producer. Ultimately, the two criteria resulted in the recommendation of the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the LCM. By using an economic effects assessment, the results of this analysis provide a prioritization that can also be compared directly against other risk analyses and the cost of various risk mitigation strategies.

Open-File Report↗

USGS2024

Effective site coefficients for the 2024 International Building Code (IBC)

The U.S. National Seismic Hazard Models (NSHMs), developed by the U.S. Geological Survey (USGS), have long been the scientific foundation of seismic design guidelines and have been used to compute design ground motions for construction of new buildings and retrofit of existing buildings in the United States and its territories. The 2018 NSHM is adopted by the 2024 International Building Code (IBC). Prior to the 2018 NSHM update, hazard calculations were required only at one reference site condition defined by V S30 =760 m/s (where V S30 is the time-averaged shear wave velocity from the surface to a depth of 30 m) and three periods (peak ground acceleration, PGA, and pseudo spectral accelerations at periods of 0.2 and 1 s, S s and S 1 ). Site coefficients, F PGA , F a , and F v , were then defined by the Building Seismic Safety Council (BSSC) Provisions Update Committee (PUC) in the site-specific procedures of National Earthquake Hazard Reduction Program (NEHRP) Recommended Seismic Provisions to calculate ground motions for other site classes with different V S30 values at the given periods. The design ground motions at other periods were then estimated using a generic spectral shape that was also defined by the BSSC PUC in NEHRP provisions. In recent years, the engineering community has realized there were deficiencies with the F a and F v site coefficients and the generic spectral shape. To avoid potentially dangerous underestimations of design ground motions for long period structures on soft site conditions in high seismicity regions, the BSSC PUC recommended the use of multi-period response spectra (MPRS) in 2017. As a result, the USGS produced multi-period and multi-V S30 response spectral values in the 2018 NSHM for calculations of design ground motions and the site coefficients F a and F v were eliminated from the 2020 NEHRP Provisions. As these site coefficients were widely used inside and outside of the United States, in this study we back-calculate the “effective” site coefficients F a,eff , and F v,eff by comparing MPRS for various site classes with the MPRS for the reference site condition, and discuss the changes that are observed in the 2024 IBC compared to its previous version in 2021. The effective site coefficients are presented for test site locations and their dependence on various factors including period, ground motion intensity, and regional models are discussed. Ratio maps between the new effective site coefficients and the old ones are then presented for soft site classes and for short and long periods. For soft site classes at short periods, the new effective site coefficients are lower than the old site coefficients for high seismicity regions and higher for low seismicity regions. As it was expected, for soft site classes at long periods and high seismicity regions, the new effective site coefficients are much larger than the old site coefficients without imposing the 50% increase as a penalty that was suggested in the 2021 IBC, whereas they could be much smaller if the 50% increase would have been imposed particularly around New Madrid and Charleston high seismicity regions. For low seismicity regions, the long period effective site coefficients can be smaller or larger by 20% compared to the 2021 IBC coefficients.

Conference Paper↗

USGS2025

Phase 1 technical implementation plan for the expansion of the ShakeAlert earthquake early warning system to Alaska

Executive Summary The conference report accompanying the fiscal year (FY) 2022 Consolidated Appropriations Act (Public Law 117–103) for the U.S. Department of the Interior and related agencies directed the U.S. Geological Survey (USGS) to “work with the State of Alaska to develop an implementation plan to be completed within two years in order to put ShakeAlert/Earthquake Early Warning in Alaska” (p. 29). Congress included $1 million in the FY 2022 appropriation to conduct this effort. The USGS Earthquake Hazards Program, along with partner organizations, has developed the ShakeAlert earthquake early warning (EEW) system for the West Coast, which currently operates in California, Oregon, and Washington. The purpose of the system and its alert delivery partners is to reduce the impact of earthquakes and save lives and property by delivering ShakeAlert-powered alerts that are transmitted to the public via mass notification technologies, and by providing more detailed data streams to institutional users and commercial service providers to trigger automated, user-specific, protective actions. ShakeAlert was designed in such a way that it could be expanded to other U.S. regions with high earthquake risk, after the build-out of seismic and geodetic networks to support ShakeAlert in a specified region is completed and the necessary funding is secured for long-term operation and maintenance. When an earthquake occurs, seismic waves radiate from the rupturing fault like waves on a pond. It is these waves that people feel as earthquake shaking and that can cause damage to structures. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Early warnings of impending shaking are then sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. There will almost always be a region near the earthquake epicenter where alerts arrive after damaging shaking has begun. The ShakeAlert system updates its ground-motion estimates as an earthquake grows larger. In response to the FY 2022 congressional direction, the USGS worked with the State of Alaska to devise this implementation plan for ShakeAlert expansion to Alaska. The USGS engaged with the Alaska Division of Homeland Security and Emergency Management (DHS&EM) and the Alaska Division of Geological and Geophysical Surveys (DGGS). A cooperative agreement was awarded to the Alaska Earthquake Center (AEC) at the University of Alaska Fairbanks (UAF) for their contributions to the plan and their work coordinating with other networks in Alaska. The USGS engaged with the Alaska Seismic Hazards Safety Commission (ASHSC) throughout the process. The USGS also held a series of Alaska stakeholder engagements. The process of developing the implementation plan was facilitated by contracted staff from Corner Alliance, which is a government consulting firm. This implementation plan describes the details and estimates the costs for a Phase 1 expansion of the ShakeAlert system to Alaska. A geographically limited Phase 1 goal was chosen that covers the highest risk and most populated areas of Alaska. The areas proposed encompass the State’s main population centers and 90 percent of the State’s population. This Phase 1 design is considered very challenging and ambitious from the viewpoint of network operators. The lessons learned if this plan is implemented could be used to consider subsequent phases to expand EEW beyond Phase 1 in Alaska in the future. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System (ANSS). This implementation plan calls for a total of 450 high-quality, real-time EEW-capable ANSS seismic stations in Alaska: 270 new stations, 160 upgraded stations, and 20 existing stations. These seismic station numbers are based on a station spacing of 10 kilometers (km) in urban areas, 20 km in seismic source areas that endanger population centers, and 40 km in other areas. The associated costs also include support for some EEW-capable global navigation satellite system (GNSS) stations, with a focus on improving warnings for large subduction zone earthquakes. For effective EEW, ShakeAlert requires low-latency, high-availability, robust telemetry links to deliver continuous, real-time data from field stations to the data centers. The Alaska data processing hardware infrastructure would follow the general design for fail-safe operation that is used for the ShakeAlert system on the West Coast. The ShakeAlert architecture uses two independent layers: the production layer for earthquake processing and the alert layer to make alerting decisions and serve alerts to users. This implementation plan includes two geographically separated data centers in Alaska, each with two fully independent production and alert layers using the same system design developed for the West Coast. As of March 2024, the ShakeAlert system is at version 3.0.1, with more advanced versions in the development and testing pipeline. ShakeAlert originally used two algorithms to determine the location and magnitude of earthquakes using seismic data. A third algorithm that can calculate very large magnitudes of very large earthquakes with geodetic data was added in March 2024. ShakeAlert publishes several data and alert products to meet the needs of different users. All messages include the location of the earthquake, either as a point or a line, and its magnitude. Ground-shaking estimates are published in two forms, as ground-motion contours and a map grid. Providing adequate warning time for strong shaking (the “target threshold”) requires sending alerts at a threshold lower than that strong shaking level (the “alert threshold”). The thresholds for public alerting in Alaska would be a joint USGS and State decision. To have the greatest benefit, ShakeAlert-powered alerts would be delivered to institutional users and individuals by all practical pathways. The USGS alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission nor the infrastructure and expertise to perform mass notifications to the public or implement automatic actions for end users of the alerts. To meet this need, ShakeAlert recruits private sector “technology enablers” that have the necessary expertise to develop end-user implementations using EEW alerts with the goal of stimulating an EEW industry. Earthquake early warning alerts are useless if people do not know how to respond to them. Although the alert messages include instructions about what to do (drop, cover, and hold on), alerts are more effective if people have been trained in advance. Messages about ShakeAlert’s capabilities, limitations, and benefits could be integrated with existing earthquake education programs, including State-run programs. Therefore, ShakeAlert would coordinate with both public and private partners and stakeholders through various partnerships and agreements to accomplish consistent and ongoing public earthquake hazard education. The estimated capital cost of completing the computing infrastructure and sensor networks for the Phase 1 ShakeAlert expansion to Alaska is approximately $66 million in 2024 dollars. The annual operation and maintenance cost of the completed system is estimated to be $12 million per year in 2024 dollars when fully built out.

Alaska↗

USGS2025

Refining the earthquake history of south-central Alaska through lake records

The Alaska–Aleutian subduction zone (AASZ) is one of the world's most seismically active plate boundaries and the source of the 1964 M w 9.2 Great Alaska earthquake–the second largest instrumentally recorded earthquake in the world. Understanding the nature and frequency of such earthquakes is necessary for seismic and tsunami hazard assessment, but instrumental and historical records that span less than 150 years are too short to allow a statistically reliable analysis of earthquake recurrence times. This calls for studies of evidence of past earthquakes, extending the earthquake catalog further back in time. Subduction-zone paleoseismology in south-central Alaska is predominantly based on coastal evidence of land-level changes and tsunamis generated by megathrust earthquakes and preserved in the geological record. A complementary approach is lacustrine paleoseismology, which is still a relatively young discipline in Alaska. However, globally, lake basins are well-established high-resolution and continuous recorders of paleoseismic activity along subduction zones, relying on the identification of underwater landslide deposits and turbidites generated by seismic shaking. As a result, lake basins not only register ground shaking from megathrust earthquakes, but also from intraslab and crustal earthquakes, which are typically not accompanied by significant land-level changes. In this review paper, we combine coastal and lacustrine paleoseismology approaches to refine the south-central Alaskan earthquake history by comparing the paleoseismic records from two lakes (i.e., Eklutna Lake, located in the Chugach Mountain Range, and Skilak Lake, situated on the Kenai Peninsula) with the coastal and crustal earthquake catalog in Alaska. The resulting age ranges of all known megathrust earthquakes involving the Alaskan megathrust between the Kodiak and Prince William Sound (PWS) sections are more precise and accurate for the last 1.3 kyrs BP than the previously published age ranges from coastal records. As a result, this study supports the following key conclusions: (1) The 1964 CE earthquake was an exceptionally strong and unique event in the last 2000 years, rupturing the PWS, Kenai, Barren Islands, and Kodiak sections simultaneously. (2) The high-resolution and seasonal markings of the varved lake records now disentangle for the first time closely timed earthquakes, which was not possible based on the coastal evidence alone. (3) No persistent megathrust rupture boundaries exist. So, the possibility of a full rupture of the entire eastern AASZ, from PWS to Semidi cannot be excluded. (4) The rupture pattern in the eastern AASZ reveals superimposed cycles of multi-asperity ruptures (1964 earthquake) and clustered complementary partial ruptures, or rupture cascades. (5) The PWS section hosts the largest asperity in the eastern AASZ. (6) The shaking record of megathrust earthquakes indicates a time-dependent (quasiperiodic) behavior for the study area, but the observation of complementary clusters means that the hazards will not drop to zero but instead may even increase for a neighboring section. (7) The time-independent behavior of intraplate earthquakes implies that the intraslab hazard did not decrease following the 2016 and 2018 earthquakes. This study utilizes an integrated approach for subduction zone paleoseismology as a solution for unraveling recurrence and rupture patterns in Alaska, which can be applied worldwide.

Alaska↗

USGS2024

Greater sage-grouse habitat of Nevada and northeastern California—Integrating space use, habitat selection, and survival indices to guide areas for habitat management

Executive Summary Greater sage-grouse populations ( Centrocercus urophasianus ; hereafter sage-grouse) are threatened by a suite of disturbances and anthropogenic factors that have contributed to a net loss of sagebrush-dominant shrub cover in recent decades. Declines in sage-grouse populations are largely linked to habitat loss across their range. A key component of conservation and land use planning efforts for sage-grouse involves the continued monitoring and modeling of habitat requirements and suitability across its range. The Bureau of Land Management (BLM) is addressing the management of sage-grouse habitats on BLM-authorized public lands throughout the western United States through a land use planning amendment and associated environmental impact statement (86 FR 66331). More than 25 percent of the range-wide distribution of sage-grouse is within Nevada and northeastern California, and information on sage-grouse distribution and habitat requirements is important to guide appropriate management decisions. Therefore, the BLM has identified the need for updated spatially explicit information on sage-grouse habitat in Nevada and northeastern California to guide the land use planning amendment and associated management decisions. To address this need, researchers with the U.S. Geological Survey, in close cooperation with multiple State and Federal resource agency partners, including BLM, Nevada Department of Wildlife (NDOW) and California Department of Fish and Wildlife (CDFW), sought to map sage-grouse distribution and produce example habitat designations in these states. Herein, we report results of our primary study objective, which was to map sage-grouse habitat and create example habitat management areas, based on more than a decade of location and survival data collected from marked sage-grouse across the study region coupled with lek count survey data managed by the NDOW and the CDFW. We expanded on previously developed methodology to incorporate information on habitat selection and survival during reproductive life stages and specific seasons with updated sage-grouse location and known fate datasets, while also including brood-rearing areas that are understood to be threatened and important for population persistence. We combined predictive habitat map surfaces for each life stage and season with updated information on current occupancy patterns to classify habitat based on its suitability and probability of occupancy. We carried out additional steps to delineate specific example habitat management areas, specifically (1) incorporated corridors connecting key nesting and brood-rearing habitat, (2) corrected outputs for pre-wildfire habitat conditions within areas burned in the last 16 years, and (3) masked out areas of anthropogenic development. Our methodological example of deriving habitat management areas was intended to help inform decisions by BLM and other land managers regarding conservation and management of sage-grouse. Associated data products in the form of habitat maps provide updated, detailed, and comprehensive information about the status of habitats and can be useful to partner agencies in their efforts to designate and rank habitats for this species of high conservation concern in Nevada and California, with full recognition that on-the-ground field data and local sources of information and expertise should be used in conjunction with inferences from these models.

California, Idaho, Nevada↗

USGS2026

Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state

Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.

Louisiana↗

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↗