United States Geological Survey

The quality and quantity of organic matter (OM) in a river system directly affects ecosystem health; thus, managers benefit from an in‐depth understanding of the drivers and sources of OM. In the Snake River, a highly altered river‐reservoir system in the semi‐arid western United States, OM production and loading are key drivers of reservoir anoxia, which leads to several deleterious processes such as mercury methylation. However, sources and quantities of OM to the Snake River, and the effects of impoundment on OM moving through the river‐reservoir system, are not well understood. Particulate organic carbon (POC), dissolved organic carbon (DOC), particulate nitrogen (PN), chlorophyll a (chl‐a), and δ¹⁵N–PN and δ¹³C–POC isotopic ratios were measured bi‐weekly for over 2 years at four locations through the Snake River Hells Canyon Reservoir Complex to determine spatial and temporal patterns of OM quantities and sources. POC concentrations increased through the riverine zone upstream of the reservoirs, likely due to in situ primary production and/or inputs from tributaries and agricultural drains; then decreased through the most upstream reservoir likely due to particle settling. Isotopic ratios and other OM source indicators (δ¹⁵N–PN, δ¹³C–POC, POC:PN, chl‐a:POC) show that the dominant source of particulate OM was phytoplankton with seasonal terrestrial/macrophytic inputs. Results highlight the effects of major tributary and agricultural drain inputs, primary production, and impoundment on OM composition and concentration through a large river‐reservoir system and may inform water quality management efforts in this and similar systems.

Science is increasingly dependent on large teams working well together. Co-creating knowledge in this way, usually across disciplines and institutions, requires team members to feel comfortable taking interpersonal risks with each other; in other words, to have what is known as “psychological safety”. Although the importance of psychological safety for team functioning is increasingly well understood, the behaviours necessary to foster psychological safety are harder to define. We suggest that science facilitation expertise offers a path forward for scientific teams—particularly through the integration of outside facilitators or team members taking on the facilitation role—to identify dynamics that can promote or curtail psychological safety, interpret those dynamics accurately, and intervene appropriately to shift a group towards greater psychological safety. We describe how specific practices can support this cycle of observation, interpretation, and action to promote psychological safety across the team process and at key moments. We conclude with ideas for how research teams might embed these facilitation practices into their work, and how institutions can drive more widespread recognition and development of the expertise needed to cultivate psychologically safe scientific teams.

Public lands worldwide provide diverse resources, uses, and values, ranging from wilderness to extractive uses. Decision-making on public lands is complex as a result and is required by law to be informed by science. However, public land managers may not always have the science they need. We developed a methodology for identifying priority science needs for public land management agencies. We relied on two core data sources: environmental effects analyses conducted for agency decisions and legal challenges to those decisions. We considered needs in four categories: data, science, methods, and mitigation measures. We classified topics as primary science needs when (1) the topic was analyzed frequently in agency environmental analyses, (2) our metric of quality/defensibility was low or mitigation measures were frequently included for the topic, and (3) the agency was challenged on its use of science for the topic. We applied our methodology to the Bureau of Land Management—the largest public land manager in the United States—in Colorado, a state with abundant and diverse public lands. Primary identified needs were data on vegetation; science about effects of oil and gas development and livestock grazing on multiple resources, including terrestrial wildlife; methods for analyzing environmental effects for many topics; and mitigation measures for protecting vegetation, soils, water quality, and archaeological and historic resources. Science needs often reflect needs for facilitating and supporting the use of existing science in agency decision-making. Our method can be applied across agencies, geographies, and timeframes to help strengthen science use in public lands decision-making.

Invasive plant species have substantial negative ecological and economic impacts. Geographic information on the potential and actual distributions of invasive plants is critical for their effective management. For many regions, numerous sources of predictive geographic information exist for invasive plants, often in the form of outputs from species distribution models (SDMs). The creation of a repository of consistently produced SDMs of regional- or national-scale information predicting the potential distribution of invasive plant species could provide information to managers in the prioritisation of invasive species management. Here, we present a novel set of not only habitat suitability models for occurrence for 259 manager requested invasive plant species in the contiguous United States (USA), but also habitat suitability models for abundance (≥ 5% cover) and high abundance (≥ 25% cover). These data provide an update to the Invasive Species Habitat Tool (INHABIT; gis.usgs.gov/inhabit). This tool contains information on the majority of invasive plant species in the contiguous USA with sufficient location data for model building. INHABIT provides a canonical set of predicted geographic distributions for invasive plants in the contiguous USA that can aid in the search for new populations of invasive plant species and help create watch lists for emerging invaders. As this tool contains information on nearly all of the most problematic invasive plants in the contiguous USA, it helps in prioritising management strategies by showing which plants are already present or abundant in a land management area and which may become present or abundant in the future.

Carbon fluxes in tidal brackish marshes play a critical role in determining coastal wetland carbon sequestration and storage, thus affecting carbon crediting of coastal wetland restoration. In this study, a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool DeNitrification-DeComposition was applied to nine brackish marsh sites in Mississippi River (MR) Deltaic Plain to examine the responses of gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem exchange (NEE), and emissions of methane (CH4) and nitrous oxide (N2O) to climate change. Simulations of a normal hydrologic year (2013), dry year (2011) and wet year (2021), and a hypothetical sea level rise (SLR) case were conducted as climate change scenarios. These climate change scenarios were determined by the Palmer Drought Severity Index (PDSI) for the Northeast Division of Coastal Louisiana during 2001–2021. Model results showed that GPP, ER, NEE, CH4, and N2O vary with site, and these brackish marshes lost carbon (net CO2 emission) due to large reduction in primary productivity under the climate scenarios, as well as even during the normal hydrologic year. Average cross-site NEE were 148, 140 and 132 g C m−2 yr−1 in the dry, wet, and normal years (all net loss of wetland C). Under the hypothetical SLR, NEE were reduced by -25% compared to the normal year, but GPP and NPP were declined by -40% and -70%, respectively. These results suggest that climate change induced changes in soil salinity and water table depth will exacerbate carbon loss from tidal brackish marshes.

Rationale Vein calcite in Devils Hole has been precipitating continuously in oxygen‐isotope equilibrium at a constant temperature for over 500 000 years, providing an unmatched δ ¹⁸ O paleoclimate time series. A substantial issue is that coeval calcite (based on matching δ ¹⁸ O values) has uranium‐series ages differing by 12 000 years. Methods An unparalleled high‐accuracy δ ¹⁸ O chronology series from continuously submerged calcite was used to correct the published uranium‐series ages of non‐continuously formed calcite in two cores, cyclically exposed by water‐table decline during glacial–interglacial transitions. This method relies on the premise that the δ ¹⁸ O values of coevally precipitated calcite are identical, allowing matching calcite δ ¹⁸ O values to establish formation ages. Results Exposed calcite can have apparent ages that are 12 000 years too young due to unrecognized uranium mobility and resulting mixed ages identified in over 50 mixed uranium‐series ages from previous studies. Secondary uranium in fluids, sourced from the formation or dissolution of porous carbonate deposits (folia) with high uranium‐238 ( ²³⁸ U) concentrations, has migrated up to 10 mm into vein calcite. Conclusions The continuously submerged Devils Hole δ ¹⁸ O chronology is not explained by orbital forcing. Rather, this chronology represents a regional climate record in the southern Great Basin of sea‐surface‐temperature (SST) variations off California, variations that preceded the last and penultimate deglaciations by 5000 to approximately 10 000 years. Temporal discrepancies between the continuously submerged Devils Hole chronology and other regional δ ¹⁸ O records (e.g., the Leviathan chronology) can be explained by unrecognized cryptic, pernicious uranium mobility, leading to model estimations that may be thousands of years younger than actual ages. Consequently, paleo‐moisture availability, water‐table, and groundwater recharge models based on these mixed uranium‐series ages are too young by as much as 12 000 years. The potential for post‐formation uranium addition in subaerial cores and speleothems underscores the need for caution in uranium‐series dating, highlighting δ ¹⁸ O time‐series comparisons as a method for identifying mixed ages.

Faced with accelerating sea level rise and changing ocean storm conditions, coastal communities require comprehensive assessments of climate-driven hazard impacts to inform adaptation measures. Previous studies have focused on flooding but rarely on other climate-related coastal hazards, such as subsidence, beach erosion and groundwater. Here, we project societal exposure to multiple hazards along the Southeast Atlantic coast of the United States. Assuming 1 m of sea level rise, more than 70% of the coastal residents and US$1 trillion in property are in areas projected to experience shallow and emerging groundwater, 15 times higher than daily flooding. Storms increase flooding exposure by an order of magnitude over daily flooding, which could impact up to ~50$770 billion in property value. The loss of up to ~80% of present-day beaches and high subsidence rates that currently affect over 1 million residents will exacerbate flooding and groundwater hazard risks.

The Colorado River drains about 8% of the conterminous United States, provides water for 40 million people, and is one of the most overallocated rivers in the world. As the upper Colorado River Basin (UCOL) contributes an estimated 92% of the total basin natural streamflow, knowledge of the location and amount of surface water withdrawals in the UCOL is important for managing the Colorado River system. Since the UCOL encompasses portions of five states, water use data are dispersed among numerous federal and state agency databases, and there is no centralized dataset that documents surface water use within the entire UCOL at a fine spatial and temporal resolution. This article presents an inventory of 1,358 major structures that divert surface water from and within the UCOL with corresponding daily time series withdrawal records from 1980 through 2022. Data compilation efforts, processing methods, and contents of this diversion database are documented, and summary information is provided.

The Chicago Area Waterway System (CAWS) is a potential route for the migration of aquatic invasive species from the Mississippi River Basin into the Great Lakes. Electric dispersal barriers were installed in the Chicago Sanitary Ship Canal, within CAWS, to prevent invasive fish from reaching the Great Lakes. Despite the high efficiency of these barriers, occasional maintenance events create a vulnerability that fish can exploit to access the Great Lakes. This study aimed to assess the feasibility of a carbon dioxide (CO 2) infusion system to deter fish during the maintenance of the electric barriers. An algebraic slip mixture model was implemented in the OpenFOAM solver to represent the underwater CO 2 bubble plume and predict the concentration of dissolved CO 2 in the canal. Simulations under three canal flowrates and two sparger systems were conducted assuming a constant gas flowrate. Numerical results indicate that, for all simulated conditions, the CO 2 concentration is not fully mixed creating pas-sageways that invasive fish could potentially use to migrate upstream. Injecting 4-mm bubbles induces two large-scale recirculations that are expected to synergistically improve fish avoidance. On the other hand, injection of 20 μ m bubbles results on almost immediate dissolution with minimal effect on the flow pattern. To improve effectiveness, a gas pulse system was proposed and numerically evaluated. Based on the simulations, this system not only extends the operation of the CO 2 barrier but also increases efficiency creating CO 2 gradients that can promote a more responsive behaviour from fish. Moreover, the pulse concept mitigates potential effect of elevated CO 2 downstream from the treated area.

In the face of unprecedented ecological changes, the conservation community needs strategies to recover species at risk of extinction. On the Island of Maui, we collaborated with species experts and managers to assist with climate‐resilient recovery planning for 36 at‐risk native plant species by identifying priority areas for the management of recovery populations. To do this, we developed a tailored spatial conservation prioritization (SCP) approach distinguished by its emphasis on transparency, flexibility, and expert (TFE) engagement. Our TFE SCP approach consisted of 2 iterative steps: first, the generation of multiple candidate conservation footprints (i.e., prioritization solutions) with a flexible greedy algorithm that reflects conservation practitioners’ priorities and, second, the selection of an optimal conservation footprint based on the consideration of trade‐offs in expert‐agreed criteria among footprints. This process maximized buy‐in by involving conservation practitioners and experts throughout, from setting goals to reviewing optimization data, defining optimization rules, and designating planning units meaningful to practitioners. We minimized the conservation footprint area necessary to meet recovery goals while incorporating species‐specific measures of habitat suitability and climate resilience and retaining species‐specific information for guiding recovery efforts. Our approach reduced the overall necessary conservation area by 36%, compared with selecting optimal recovery habitats for each species separately, and still identified high‐quality habitat for individual species. Compared with prioritizr (an existing SCP tool), our approach identified a conservation area of equal size but with higher quality habitat. By integrating the strengths of existing techniques in a flexible and transparent design, our approach can address natural resource management constraints and provide outputs suitable for local recovery planning, consequently enhancing engagement and buy‐in from conservation practitioners and experts. It demonstrates a step forward in making conservation planning more responsive to real‐world complexities and helps reduce barriers to implementation for local conservation practitioners.

Exploration of secondary resources for isolation of valuable constituents, such as rare earth elements (REEs) and trace elements (TEs), is of importance owing to the need to identify new domestic sources and reduce reliance on imports. The present study systematically discusses the distribution of REEs and TEs in core samples from the coal block of Bhalukasba Surni {(B1(125 m)-B9 (409 m)} located in Rajmahal coalfield, Jharkhand, India, which has not been investigated previously for its geochemistry. The studied coal samples were found to be enriched in TEs whose abundances were in the order of Mn > Mo > Zr > Ni > Cr > V > Cu > Zn > Pb, and REEs (La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Er, Tm, Yb, Lu) along with Sc and Y. The average concentration of REEs with yttrium (ΣREY) on an ash basis was 528 ppm, which is significantly higher than the world average for coal ash (435 ppm). Of the samples investigated, B3 (182–184 m) and B8 (396–399 m) demonstrated relatively higher concentrations of potentially economic elements, with B3 containing a higher proportion of middle to heavy REEs Gd, Dy, Ho and Er, and B8 showing relative enrichment in Nd and Y. On dry whole coal basis, B6 (275–278 m) showed a considerably higher concentration of Ge (55 ppm) than other samples, whereas the concentration of Zr varied in the range of 90–160 ppm in the whole coal block. X-ray diffraction studies revealed the presence of quartz, keatite, hematite, zircon, anatase and orthoclase in the coal ash samples prepared at 815 °C. REEs exhibited prominent positive correlation with Al 2 O 3 (0.4 < r > 0.9) which is supportive of their residence in primary clay minerals such as kaolinite and illite-smectite. Additionally, a positive correlation of REEs with P 2 O 5 (0.4 < r > 0.9) suggests their association with phosphate minerals (such as monazite, xenotime, apatite). Positive correlation with TiO 2 ( r > 0.7) corroborates the possible association of REEs with anatase. The morphology of the coal ash samples viewed in SEM showed the presence of Al 2 O 3 and SiO 2 enriched irregular-sponge particles likely derived from partly-fused clay minerals, which accounted for the lower extent of REE encapsulation. The Bhalukasba Surni coal block is potentially of economic importance due to its enrichment in Ge, Zr, and the REEs.

Lateral variability is a fundamental feature of channel-shoal estuaries, and exchanges between the channel and shoal can play an important role in the dynamics of the ecosystem in each region. This lateral exchange of biomass interacts with vertical structure and variability, particularly in the channel, to define algal biomass accumulation in the estuary. In this paper, we investigate how time-variable lateral exchange affects phytoplankton dynamics with a biophysical model that links two water columns via intermittent exchange. We find that time variability in the exchange influences biomass by increasing concentrations in the shoals and decreasing them in the channel when the time variability happens on a timescale greater than the timescales of biological processes, and the strength of the effect increases with the period of the intermittency. At timescales of variability comparable to the spring-neap cycle, however, the interplay between lateral exchange and the ecosystem response is complicated by the fortnightly development of stratification in the channel and the role that channel-shoal interaction plays in defining that stratification. As a result, for lateral exchange variability with periods of 7 and 14 days, the influence of the shoal ecosystem on the channel ecosystem is sensitive to the phasing of exchange relative to the spring-neap cycle, due to the fact that neap tide exchanges can create stratification events that are larger in magnitude and duration than would occur in the absence of lateral exchange, causing the channel to transition into net positive growth conditions. We conclude that lateral exchange influences the estuarine ecosystem both directly, through the exchange of biomass between shoals with net positive growth and adjoining channels and indirectly through its role in defining stratification events that allow the channel itself to have net positive growth.

Offset geomorphic markers are commonly used to interpret slip history of strike‐slip faults and have played an important role in forming earthquake recurrence models. These data sets are typically analyzed using cumulative probability methods to interpret average amounts of slip in past earthquakes. However, interpretation of the geomorphic record to infer surface slip history is complicated by slip variability, measurement uncertainty, and modification of offset features in the landscape. To investigate how well geomorphic data record surface slip, we use offset measurements from recent strike‐slip surface ruptures (n = 39), faults with geomorphic evidence of multiple strike‐slip earthquakes (n = 29), and synthetic slip distributions with added noise (n> ${ >}$10,000) to examine the constraints of the geomorphic record and the underlying assumptions of the cumulative offset probability distribution analysis method. We find that the geomorphic record is unlikely to resolve more than two paleo‐slip distributions, except in specific cases with low slip variability, high slip‐per‐event, and semiarid climate. In cases where site‐specific conditions allow for interpretation of more than two earthquakes, lateral extrapolation along a fault is not straightforward because on‐fault displacement and distributed deformation may be spatially variable in each earthquake. We also find that average slip in modern earthquakes is adequately recovered by probability methods, but the reported prevalence of strike‐slip faults with characteristic slip history is not supported by geomorphic data. We also propose updated methods to interpret slip history and construct uncertainty bounds for paleo‐slip distributions.

Introduction The long-distance, seasonal migrations of birds make them an effective ecological bridge for the movement of ticks. The introduction of exotic tick species to new geographical regions can cause the emergence of novel tick-borne pathogens. This study examined the prevalence of exotic tick species parasitizing migratory songbirds at stopover sites along the northern Gulf of Mexico using the mitochondrial 12S rRNA gene. Methods Overall, 421 individual ticks in the genera Amblyomma, Haemaphysalis, and Ixodes were recorded from 28 songbird species, of which Amblyomma and Amblyomma longirostre were the most abundant tick genera and species, respectively. A high throughput 16S ribosomal RNA sequencing approach characterized the microbial communities and identified pathogenic microbes in all tick samples. Results and discussion Microbial profiles showed that Proteobacteria was the most abundant phylum. The most abundant pathogens were Rickettsia and endosymbiont Francisella, Candidatus Midichloria, and Spiroplasma. Permutation multivariate analysis of variance revealed that the relative abundance of Francisella and Rickettsia drives microbial patterns across the tick genera. We also noted a higher percentage of positive correlations in microbe-microbe interactions among members of the microbial communities. Network analysis suggested a negative correlation between a) Francisella and Rickettsia and, b) Francisella and Cutibacterium. Lastly, mapping the distributions of bird species parasitized during spring migrations highlighted geographic hotspots where migratory songbirds could disperse ticks and their pathogens at stopover sites or upon arrival to their breeding grounds, the latter showing mean dispersal distances from 421–5003 kilometers. These findings spotlight the potential role of migratory birds in the epidemiology of tick-borne pathogens.

The loss of phosphorous (P) from the land to aquatic systems has polluted waters and threatened food production worldwide. Systematic trend analysis of P, a nonrenewable resource, has been challenging, primarily due to sparse and inconsistent historical data. Here, we leveraged intensive hydrometeorological data and the recent renaissance of deep learning approaches to fill data gaps and reconstruct temporal trends. We trained a multitask long short-term memory model for total P (TP) using data from 430 rivers across the contiguous United States (CONUS). Trend analysis of reconstructed daily records (1980–2019) shows widespread decline in concentrations, with declining, increasing, and insignificantly changing trends in 60%, 28%, and 12% of the rivers, respectively. Concentrations in urban rivers have declined the most despite rising urban population in the past decades; concentrations in agricultural rivers however have mostly increased, suggesting not-as-effective controls of nonpoint sources in agriculture lands compared to point sources in cities. TP loss, calculated as fluxes by multiplying concentration and discharge, however exhibited an overall increasing rate of 6.5% per decade at the CONUS scale over the past 40 y, largely due to increasing river discharge. Results highlight the challenge of reducing TP loss that is complicated by changing river discharge in a warming climate.