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Estimated average annualized losses from potential building damage and fatalities due to earthquake-generated tsunamis in the United States
Earthquake-generated tsunamis represent substantial economic threats to states and territories in the United States (U.S.), but we are unaware of any effort to quantify potential impacts at the national level. This gap is partially due to the lack of nationally consistent data on tsunamigenic sources and associated return periods. This study addresses this issue and provides estimates of average annualized losses (AAL) for potential residential fatalities and capital stock losses associated with building damage (i.e., structural, non-structural, contents, and inventory damage) in the U.S. by curating tsunami-hazard information based on deterministic scenarios and probabilistic approaches, calculating potential losses, and estimating return periods where necessary. This assessment was done for the U.S. West Coast, Alaska, Hawaii, U.S. Pacific Territories, and U.S. Atlantic Territories. We estimate that earthquake-generated tsunamis that could affect these states and territories collectively represent $1 billion in potential AAL with 79 % of losses due to residential fatalities and 21 % of losses due to capital stock losses from building damage. We identify AAL variations based on county and county equivalents, states and territories, geographic regions, return periods, and departure-delay assumptions for evacuating residents. Results include high AAL values for potential fatalities in Puerto Rico and the U.S. Pacific Northwest region, high AAL values for potential building-related damage in Hawaii and California, and high building- and population-loss ratios for county equivalents in Alaska and U.S. territories.
Continental-scale prediction of hydrologic signatures and processes
Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures.
Determination of per- and polyfluoroalkyl substances in water by direct injection of matrix-modified centrifuge supernatant and liquid chromatography/tandem mass spectrometry with isotope dilution
A direct-injection liquid chromatography/tandem mass spectrometry method was developed to determine 34 per- and polyfluoroalkyl substances (PFAS), including selected branched isomers, in centrifuge supernatant of matrix-modified (amended with approximately 50 percent methanol) water samples. The method has been validated in reagent water, surface water, groundwater, and wastewater effluent. Other water types (for example, drinking water, untreated wastewater, and landfill leachate) have been analyzed by the method but not systematically validated. Recovery of isotope-dilution standards, added to each sample, may be used to assess method performance in nonvalidated matrices on a sample-by-sample basis. Using this method, PFAS concentrations were determined in the range of 2–2,000 nanograms per liter in water samples. This range can be extended by diluting concentrated samples. At circumneutral pH, most compounds are present in the environment in their ionized form, and data are reported as such (for example, perfluorooctanoic acid is referred to as “perfluorooctanoate” [PFOA], perfluorooctane sulfonic acid is referred to as “perfluorooctane sulfonate” [PFOS]). Sample preparation procedures were designed without the use of filtration and with minimum sample handling steps to mitigate procedural losses of target compounds due to sorption to surfaces. Further, isotope-dilution quantification allowed for the correction of bias that may result from procedural losses, matrix-induced signal suppression or enhancement, and other factors. Validation experiments to characterize bias and variability, method detection level, and holding time were done in four distinct water matrices—reagent water, surface water, treated wastewater effluent, and groundwater—at multiple concentration levels. Mean PFAS recoveries met data quality objectives of bias and variability studies in all four validation matrices except for two compounds with low and variable recovery in the reagent water matrix only. Isotope-dilution standards, treated as surrogate compounds, were analyzed in more than 1,500 customer-submitted environmental samples with aggregate recovery of 102.5±6.5 percent (mean±standard deviation). Maximum holding times for all target compounds in the four validation matrices were 28 days for refrigerated samples and 90 days for frozen samples.
Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA
Recent mapping of the underexplored Clementine prospect in southwestern Montana has revealed evidence of hydrothermal alteration and mineralized breccia vein gossan interpreted to represent the upper expression of a Cretaceous, sediment-hosted copper porphyry system. The prospect is at the nexus of several Cretaceous granites, including the pre-mineralization Butte Granite and Big Hole Canyon plutons and local pre- to post-mineralization granite intrusions. Here, 3D magnetic inversions and stable isotope data are used to evaluate the spatial and genetic relationship of mineralization and Cretaceous magmatism. Magnetic inversions reveal a zone of high magnetic susceptibility beneath the prospect that is related to an exposure of unaltered, likely post-mineralization granite. The granite appears to connect to the Big Hole Canyon pluton at depth, suggesting it is a late-stage differentiate of the cooling, pre-mineralization pluton that may have been one of several potential heat sources for the mineral system at Clementine. This is supported by carbon isotope values of graphite that indicate organic material in shale of the Cretaceous Kootenai Formation was subject to metamorphism. Preliminary light hydrogen isotope values of actinolite hydrothermal orbs suggest formation following magmatic outgassing during thermal advection from an underlying intrusion.
Nutrients and pesticides in ground water of the Ozark Plateaus in Arkansas, Kansas, Missouri, and Oklahoma
A total of 229 ground-water samples were collected from 215 sites as part of the Ozark Plateaus study unit of the National Water-Quality Assessment Program. These samples were collected from 1993 through 1995 using a network of springs and wells with three scale-dependent components. The first component, the study-unit survey, consisted of 99 randomly selected springs and domestic wells in the Springfield Plateau and Ozark aquifers. The second component, two land-use studies, consisted of 42 springs and domestic wells in a poultry-dominated agricultural area and 40 springs and domestic wells in a cattle-dominated agricultural area overlying the Springfield Plateau aquifer. The third component, the small-watershed study, consisted of 4 springs, 18 domestic wells, and 11 monitoring wells in a small basin within the poultry land-use study area. Samples were analyzed for major ions, nutrients, dissolved organic carbon, methylene blue active substances, tritium, and 88 pesticides and metabolites.The water-quality data from these samples were analyzed with descriptive and statistical methods. Nitrite plus nitrate, which was detected more often and in greater concentrations than any of the other nutrients, ranged from less than 0.05 to 25 milligrams per liter as nitrogen. Nitrite plus nitrate concentrations positively correlated to percent agricultural land use around each site. Median nitrite plus nitrate concentrations generally were greater in samples from springs than in samples from wells. Concentrations of nitrite, ammonia, and ammonia plus organic nitrogen were also affected by land use and also by concentrations of dissolved oxygen in the ground water. Concentrations of phosphorus and orthophosphate probably were affected by land use and also by phosphorus solubility. Pesticides were detected in 80 of 229 samples from 73 of 215 sites. A total of 20 pesticides were detected with a maximum of 5 pesticides detected in any 1 sample. The most commonly detected pesticides were tebuthiuron, atrazine, prometon, desethylatrazine, and simazine. Maximum concentrations ranged from 0.003 to 1.0 microgram per liter. The occurrence and distribution of pesticides were related to land use. Percent agricultural land use was greater for samples with pesticides detected than for samples with no pesticides detected. Pesticides were detected more often in samples from springs than in samples from wells. The occurrence of pesticides also was related to seasonality and chemical characteristics, such as solubility and persistence, of the compounds.
Forecasting storm-induced coastal flooding for 21st century sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands
Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian, Mariana, and American Samoan Islands as a result of climate change and sea-level rise. We followed a hybrid (dynamical and statistical) downscaling approach to map flooding due to waves and storm surge at 10-square meter resolution along all 1,870 kilometers of these islands’ coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.00 meter (m), +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios. We quantified the coastal flood depths and extents using the latest climate forcing from Intergovernmental Panel for Climate Change’s Sixth Assessment Report Coupled Model Intercomparison Project. The data generated using these methods provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when climate change and sea-level rise increase coastal storm-induced flooding to help identify areas where management and (or) restoration could potentially help reduce the risk to, and increase the resiliency of, the coastal communities in the populated Hawaiian, Mariana, and American Samoan Islands.
Noble and base metal distribution and processes affecting ore tenors in the disrupted lower stratigraphy of the Stillwater Complex, USA
Exploration continues for contact-style Ni-Cu sulfide and chromitite-associated PGE mineralization in ultramafic rocks of the Stillwater Complex. At the Iron and Chrome Mountain areas, massive sulfides occur along the complex’s footwall contact and anomalous concentrations of PGE+Au are associated with the three lowermost chromitite seams. Southeast of Chrome Mountain, magmatic layering is highly disrupted by the presence of faults, magmatic breccias, serpentinized discordant dunites, pyroxenite pegmatoids, and disaggregated chromitite seams. The bulk rock chemistry, sulfide chemistry, and noble metal mineralogy of samples from this area were examined to determine the deportment of PGE and processes that led to enrichments in PGE, Au, Cu, Co and Ni. Results show that a sulfide liquid was the principal collector of PGE. If sulfide liquid was initially deposited with chromite, it was disaggregated or redistributed by subsequent melt or fluid infiltration, which may have resulted in the offset of peak PGE(+Cu, Ni) from peak Cr 2 O 3 concentrations, and upgraded PGE tenors. Upon cooling, PGE exsolved from sulfides to form discrete bismuth tellurides, arsenides, arsenic sulfides, antimonides, and alloys, commonly along the margins of sulfide globules. Calculated metal tenors are highest in the disseminated sulfides southwest of Chrome Mountain, whereas massive and net-textured sulfides near the Iron Mountain-Camp zone represent monosulfide solid solution cumulates. At progressively shallower levels, higher metal tenors combined with lower S/Se ratios are consistent with increasing R-factors from 100 to 100,000. Serpentinization and talc-tremolite alteration resulted in S loss through partial replacement of sulfides by secondary silicate+carbonate+magnetite+sulfide assemblages, further upgrading Ni-Cu-PGE tenors. The present work shows that processes responsible for the disruption of magmatic layering and post-magmatic fluid alteration along the intrusion’s lower contact led to noble and base metal enrichments.
A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States
Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.
Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California
The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.
Lunar grid systems, coordinate systems, and map projections for the Artemis missions and lunar surface navigation
Foreward This document contains design specifications of a navigational standard for the Moon, including a Lunar Transverse Mercator system, a Lunar Polar Stereographic system, a Lunar Grid Reference System, and a unique coordinate structure, Artemis Condensed Coordinates, for Artemis mission navigation and lunar surface science. The National Aeronautics and Space Administration (NASA) Artemis campaign seeks to place humans on the Moon for the first time since the Apollo missions. Early Artemis missions are heavily focused on the lunar south pole, which promises to return valuable data on the Moon’s geologic record, amongst other mission objectives. Coordinate systems in use today for the lunar south pole provides crew members on the surface neither an efficient nor intuitive means to communicate their position and orientation. A novel grid coordinate system, the Lunar Grid Reference System, is proposed to address these concerns for use in real-time extravehicular activity operations on the lunar surface. The many stakeholders involved in the Artemis missions will need a common system to communicate position and orientation while astronauts are operating on the lunar surface. To that end, Artemis crew members will need that system to be efficient and intuitive to promote efficient extravehicular activity timelines and reduce confusion. In the context of this document, these characteristics are addressed on the design of lunar coordinate systems: Efficient.—The number of characters required to communicate a location within a desired precision level in both local and global contexts, and how many steps are required for a recipient or sender to interpret a location. Intuitive.—How well the system aligns with human perceptual abilities, and whether the system yields distances that have the same relationship to actual lunar surface distance in all directions from the point where a person is located. Technological systems are currently being investigated to supplement the crew members’ ability to locate and orient themselves and other assets on the lunar surface; however, it is unlikely that those systems will be fully operational for the first few landed missions. Even with future positional aids, crew members will still need an efficient and intuitive means to communicate position and orientation. In addition, if technological systems fail, the crews will require land navigation skills and have maps available, thus providing further motivation for a crew-centric coordinate system. The contents of this U.S. Geological Survey (USGS) document detail a comprehensive framework for standardizing lunar crewed surface navigation within NASA and outlines the protocols, methods, and designs necessary for achieving consistency and interoperability across relevant space mission teams and lunar surface navigators. Key components of this document include designs of map projections, projected coordinate reference systems (Lunar Transverse Mercator and Lunar Polar Stereographic systems), and a grid system (Lunar Grid Reference System and Artemis Condensed Coordinates) for the Moon. The work proposed in this document seeks to accomplish something similar to the National Geospatial-Intelligence Agency (NGA) document SIG 0012 (NGA, 2014a), but for using grid systems for the Moon. This report incorporates initial feedback and input from NASA’s Artemis Geospatial Data Team, NASA’s Flight Operations Directorate, National Geodetic Survey, USGS Astrogeology Science Center, and NGA and is intended to serve as a resource for all involved with the Artemis missions, as well as for engineers designing and operating lunar infrastructure.
Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning
We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.
Afterslip and creep in the rate-dependent framework: Joint inversion of borehole strain and GNSS displacements for the Mw 7.1 Ridgecrest earthquake
The elusive transition toward afterslip following an earthquake is challenging to capture with typical data resolution limits. A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub-nanostrain precision and sub-second sampling rate of BSMs bridges a gap between conventional seismologic and geodetic methods, exemplified by atypical postseismic shear strain reversals observed at nearfield (<2 km) station B921 that remain unexplained. We jointly invert GNSS displacements and BSM strains for coseismic and postseismic slip spanning hours to months over 7 independent periods. Cosiesmically, our model resolves the largest slip magnitudes of up to 6.6 m on the mainshock rupture plane, with similar patterns to other inferred slip distributions. The foreshock fault appears to slip coincidently with mainshock, revealing potential asperities activated during the preceding Mw 6.4 event. Postseismically, the best-fitting models adhere to mechanical rate-and-state expectations of logarithmically decaying slip adjacent to the coseismic rupture terminus, and where deep rheologic conditions favor creep. Most spatial variation occurs in the early postseismic timeframe (<1–2 weeks), with evidence for regional rheologic control and static stress dependence. Triggered creep on the neighboring Garlock Fault unexpectedly persists for >178 days—further highlighting the importance of fault networks in postseismic stress redistribution, critical to assessing future hazard.
Predictions of anthropogenic background PFAS concentrations in soil and relation to bedrock lithology and groundwater quality
Detectable concentrations of per- and polyfluoroalkyl substances (PFAS) have been observed in soils in remote areas and presumably originate from atmospheric deposition. These anthropogenic background concentrations may enable some PFAS to leach to groundwater at levels that exceed regulatory criteria for drinking water. However, anthropogenic background soil concentrations and their connection to groundwater are not well characterized. We developed a boosted regression tree model to predict perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations in shallow soils across northern New England. Low soil pH was the most important predictor of elevated anthropogenic PFOS and PFOA concentrations in background soils, rather than potential PFAS sources, land use, or population density. Total organic carbon (TOC) was also an important predictor for PFOS soil concentrations. Model predictions indicate that 73% of the shallow soils within Maine, Vermont, and New Hampshire exceed New Hampshire’s Soil Remediation Standard for PFOS (0.5 ng/g) and 41% exceed the PFOA standard (0.4 ng/g). Analysis of soil model results and groundwater data suggests that areas with high soil pH are associated with higher groundwater detection frequencies, illustrating how areas with less retention in soil are, conversely, also areas with potentially greater groundwater vulnerability. Further analysis indicates that groundwater may be more vulnerable in calcareous lithologies.
Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes
Groundwater flow paths and processes that govern metal mobility and transport are difficult to characterize in mountainous bedrock watersheds. Despite the difficulty in holistic characterization, conceptual understanding of subsurface hydrologic and geochemical processes is key to developing remediation plans for locations affected by acid mine drainage, such as the Upper Animas River watershed in southwestern Colorado, USA. Stable isotopes of water and rare earth elements were utilized to evaluate groundwater flow and metal sources within this complex catchment. Stable isotope samples collected from draining mine adits and springs display systematic spatial variation wherein sample sites at higher elevations have greater seasonal variability than sites at lower elevations. The Upper Cement Creek watershed, where multiple draining mines are present, displays the lowest seasonal variation in stable isotopic signatures, potentially indicating the presence of a large, well-mixed volume of groundwater storage or interbasin groundwater flow. Rare earth elements display statistically significant variation between different alteration styles in the catchment. Overprinting of regional propylitic alteration is evident based on enrichment of middle rare earth elements in acidic springs and mines that are not spatially associated with surficial exposures of acid generating alteration styles. Europium anomaly and middle rare earth enrichment signatures from two flooded mine tunnels on opposite sides of a watershed divide indicate connections to the same subsurface flooded mine workings.
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.
Age and colony variation in Adélie penguin metapopulation vital rates: Insights from a 25-year mark–recapture study
Understanding how vital rates vary with age, life-history stage, and among populations is fundamental for predicting the demographic consequences of environmental change, especially in longer-lived species with complex life histories. These species often exhibit delayed maturity and iteroparity, making nuanced demographic insights critical for assessing their long-term viability. This study investigated age- and colony-related variation in Adélie penguin vital rates including survival, recruitment, and breeding propensity. We used mark–recapture data collected over 25 years (1996–2020) from three Adélie penguin breeding colonies that differed in population sizes and trends but comprised a metapopulation located at capes Royds, Bird, and Crozier on Ross Island, Antarctica. We used multi-state models to estimate survival and detection rates relative to reproductive state and breeding colony and estimated transition probabilities reflecting movements between reproductive states and colonies. Apparent survival varied by reproductive state, colony, and age and averaged 0.80 (SD = 0.02) at Bird, and 0.72 (SD = 0.03) and 0.73 (SD = 0.03) at Crozier and Royds, respectively, for pre-breeders age 2–7 years with strong declines in pre-breeder survival after age 8. We observed less age-related variation in survival of breeders and non-breeders, but we observed differences between colonies with lower survival for breeders (0.72 to 0.80) compared to non-breeders (0.75 to 0.82). The average probability of surviving the first 2 years after fledging ranged from 0.43 (SD = 0.14) at Royds and Crozier (0.43, SD = 0.10) to 0.55 (SD = 0.15) at Bird. Movement between colonies was highest for pre-breeders (0.00%–12.00% depending on age and colony) and lowest for breeders (<0.20%). We observed the lowest age-related recruitment rates at Royds, with recruitment at Crozier almost twice as high, and intermediate at Bird. Breeding propensity was highest at Crozier and lowest at Bird. Colony-specific variation in vital rates likely contributed differently to population trajectories, suggesting that care must be taken to extrapolate vital rate estimates across colonies even within a metapopulation. These findings also highlight the importance of considering age, life-history stage, and geographic variation when assessing population vital rates in species with complex life histories.
Water-quality assessment of the Ozark Plateaus study unit, Arkansas, Kansas, Missouri, and Oklahoma: Analysis of information on nutrients, suspended sediment, and suspended solids, 1970-92
Water-quality data collected during water years 1970-90 (October 1 to September 30) for 83 surface-water sites and during 1970-92 for 395 ground-water sites in the 48,000 square mile Ozark Plateaus study unit of the National Water Quality Assessment Program were analyzed using selected descriptive and statistical methods. The water- quality data include nutrient (nitrogen and phosphorus), suspended sediment, and suspended- solids data, and ancillary information such as fertilizer use, animal waste, sewage treatment plant, and land use. Statistically significant differences exist in surface-water quality that can be attributed to physiography, land use, and other effects. The sites that were considered to be substantially affected by sewage treatment plants had the largest concentrations of nutrients. Nutrient concentrations generally were larger at sites associated with agricultural basins than at sites associated with forested basins. Statistically significant differences existed in the quality of ground water that can be attributed to hydrogeologic and land-use effects. Nutrient concentrations generally were largest where the water source is indicated to be shallow in origin and where parts of the hydrogeologic units are in agricultural land-use areas. Water quality has changed at several surface-water sites since 1970. Nutrient concentrations appear to have increased at some sites and decreased at other sites. Causes of these apparent trends are not known, but many of the sites with apparent trends are in agricultural areas. Surface-water loads of nutrients and suspended sediment were affected by several factors including streamflow, climate, drainage area, reservoir operation, and inputs from point and nonpoint sources. Annual loads were largest in large basins, with large inputs of nutrients or sediment during periods of high streamflows at locations where reservoir operation effects are not substantial.