Running Reelfoot Bayou (RRB) is the outlet canal of Reelfoot Lake, the largest natural lake in Tennessee. RRB is not able to contain discharge from Reelfoot Lake greater than the bankfull discharge of 28 m3/s (1000 ft3/s), which typically occurs at the beginning of the growing season (April–June). Historically, the planting of crops has been delayed until flooding subsides and cropland has drained. The objective of this study is a preliminary quantification of cropland inundation to determine its spatial distribution in the RRB floodplain. Inundated croplands in the RRB floodplain were delineated over a range of spillway discharges from 2 to 57 m3/s (70–2000 ft3/s), using one-dimensional–two-dimensional hydrodynamic modeling and multispectral satellite images (Landsat 8 and Sentinel-2). The composite maps made by combining the simulated and image-derived flood maps were overlaid on the United States Department of Agriculture CropScape layer to determine the inundation of individual summer crops during the growing season. About 25% of the inundated croplands are flooded at discharges of RRB less than 28 m3/s, implying wetland hydrology. The results of this analysis can be used to inform operational management of the Reelfoot Lake spillway.
Estimating the material flows of rare earth elements (REEs) is essential to understanding which industries are most vulnerable to potential REE supply disruptions which, in turn, may inform policy recommendations aimed at reducing the supply risk. However, the REEs are a group of mineral commodities characterized by highly uncertain estimates of supply and demand due to the REE market's complexity, opacity, and small size. In this study, a streamlined methodology was applied to map mineral commodity first-use to final-use applications and to estimate total requirements at the national level based on available industrial data for final-use finished goods. This analysis examines REEs both as a group and individually, showing that total US requirements are between 15% and 16.5% of world requirements for the year 2015, the latest year with the most complete information available. The findings shed light on US industrial capabilities by revealing the discrepancy between the types of REEs that go into US raw material consumption and those that are contained in embedded consumption. For instance, given the United States’ large oil refining industry, US raw material consumption of lanthanum is quite high. In contrast, US raw material consumption of neodymium is relatively low, whereas embedded demand is comparatively high. This reflects the lack of industrial capacity to process REE concentrates into magnet material combined with the US's high imports of products that contain rare earth permanent magnets.
Gizzard shad (Dorosoma cepedianum) is a common freshwater fish species found throughout the central and eastern portions of North America. Within these regions, gizzard shad play several critical roles in the freshwater community such as serving as prey for other fish species and translocating nutrients from substrates into the water column. Because of this, it is important to understand gizzard shad population dynamics. Here, we introduce an integral projection model (IPM) for gizzard shad that incorporates empirical information from sources including Long Term Resource Monitoring (LTRM) upper Mississippi River restoration data. IPMs are a generalization of stage-based, matrix population models that have been used to describe a wide range of organisms, and as such are a natural choice for gizzard shad because many aspects of their life cycle have been studied. We tested model outputs against empirical patterns reported for gizzard shad from a different location along the Illinois River (La Grange Reach). Results of our work indicate that our model could serve as an important tool for predicting patterns within gizzard shad populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2022.110260","usgsCitation":"Peirce, J.P., Sandland, G., Bennie, B., and Erickson, R.A., 2023, An integral projection model for gizzard shad (Dorosoma cepedianum) utilizing density-dependent age-0 survival: Ecological Modelling, v. 477, 110260, 7 p., https://doi.org/10.1016/j.ecolmodel.2022.110260.","productDescription":"110260, 7 p.","ipdsId":"IP-138963","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":445013,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2022.110260","text":"Publisher Index Page"},{"id":427558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"477","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":898309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandland, Gregory","contributorId":332579,"corporation":false,"usgs":false,"family":"Sandland","given":"Gregory","email":"","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":898310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennie, Barb","contributorId":244792,"corporation":false,"usgs":false,"family":"Bennie","given":"Barb","email":"","affiliations":[{"id":48977,"text":"UW-La Crosse","active":true,"usgs":false}],"preferred":false,"id":898311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239211,"text":"70239211 - 2023 - Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data","interactions":[],"lastModifiedDate":"2023-01-04T13:31:11.765279","indexId":"70239211","displayToPublicDate":"2022-12-29T07:29:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data","docAbstract":"The success of long-term wildlife monitoring programs can be influenced by many factors and study designs often represent compromises between spatial scales and costs. Adaptive monitoring programs can iteratively manage this tension by adopting new cost-efficient technologies, which can provide projects the opportunity to reallocate costs to address new hypotheses, adapt to changing ecological conditions, or adjust sampling scale or resolution. If there is interest in longer time series of monitoring data, methodological transitions may necessitate integrated models to link newer data with historical data. However, data integration can be difficult if spatial or temporal scales are mismatched. Here, we develop an integrated multistate site-occupancy model and resolve sample unit spatial mismatch to link datasets from two northern spotted owl (Strix occidentalis caurina) monitoring schemes that broadly overlapped during a methodological transition. The first dataset was obtained from a decades-long spotted owl monitoring program using call-playback and mark-resight surveys on historical territories of varying size and shape. This monitoring program has recently transitioned to passive acoustic monitoring of randomly selected 5-km2 hexagons over larger spatial extents. Both monitoring datasets overlapped with areas in which barred owl (Strix varia), an invasive competitor that has played an important role in northern spotted owl declines, were being removed experimentally. Reconciling spatial mismatch substantially increased the representation of the call-playback dataset and integrating the two datasets increased precision of spotted owl use and paired occupancy estimates relative to single dataset estimates. Estimates of spotted owl pair occupancy across the study area were lower than previous territory-based estimates based on call-playback surveys. Our integrated model further showed that a concurrent barred owl removal experiment increased landscape use and site occupancy by pairs of spotted owls. Our empirical application of an integrated modelling approach demonstrates a useful analytical framework for long-term monitoring efforts undergoing methodological transitions (e.g. mark-recapture to non-invasive population monitoring). This framework allows monitoring programs to maintain continuity of monitoring objectives across methodological transitions, rigorously incorporate previous findings, and adaptively respond to changing ecological conditions.
The composition of clinopyroxene and clinopyroxene-liquid (Cpx-Liq) pairs are frequently used to calculate crystallization/equilibration pressures in igneous systems. While canonical uncertainties are often assigned to calculated pressures based on fits to calibration or test datasets, the sources of these uncertainties (and thus ways to reduce them) have not been rigorously assessed. We show that considerable uncertainties in calculated pressures arise from analytical error associated with Electron Probe Microanalyser (EPMA) measurements of Cpx. Specifically, low X-ray counts during analysis of elements with concentrations <1 wt% resulting from insufficient count times and/or low beam currents yield highly imprecise measurements (1σ errors of 10–40% for Na2O).
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egac126","usgsCitation":"Wieser, P.E., Kent, A.J., Till, C.B., Donovan, J., Neave, D.A., Blatter, D.L., and Krawczynski, M.J., 2023, Barometers behaving badly: Assessing the influence of analytical and experimental uncertainty on clinopyroxene thermobarometry calculations at crustal conditions: Journal of Petrology, v. 64, no. 2, egac126, 27 p., https://doi.org/10.1093/petrology/egac126.","productDescription":"egac126, 27 p.","ipdsId":"IP-147233","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egac126","text":"Publisher Index Page"},{"id":416850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"64","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wieser, Penny E. 0000-0002-1070-8323","orcid":"https://orcid.org/0000-0002-1070-8323","contributorId":272601,"corporation":false,"usgs":false,"family":"Wieser","given":"Penny","email":"","middleInitial":"E.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":872109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kent, Adam J.R.","contributorId":292680,"corporation":false,"usgs":false,"family":"Kent","given":"Adam","email":"","middleInitial":"J.R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":872110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Till, Christy B. 0000-0001-8924-2206","orcid":"https://orcid.org/0000-0001-8924-2206","contributorId":304971,"corporation":false,"usgs":false,"family":"Till","given":"Christy","email":"","middleInitial":"B.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":872111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, J. 0000-0001-8639-0959","orcid":"https://orcid.org/0000-0001-8639-0959","contributorId":304972,"corporation":false,"usgs":false,"family":"Donovan","given":"J.","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":872112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neave, David A.","contributorId":304973,"corporation":false,"usgs":false,"family":"Neave","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":27871,"text":"University of Manchester","active":true,"usgs":false}],"preferred":false,"id":872113,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blatter, Dawnika L. 0000-0002-7161-6844 dblatter@usgs.gov","orcid":"https://orcid.org/0000-0002-7161-6844","contributorId":4899,"corporation":false,"usgs":true,"family":"Blatter","given":"Dawnika","email":"dblatter@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":872114,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krawczynski, Michael J. 0000-0002-0710-0763","orcid":"https://orcid.org/0000-0002-0710-0763","contributorId":304974,"corporation":false,"usgs":false,"family":"Krawczynski","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":62382,"text":"Washington University St. Louis","active":true,"usgs":false}],"preferred":false,"id":872115,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240234,"text":"70240234 - 2023 - The Sukari gold deposit, Egypt: Geochemical and geochronological constraints on the ore genesis and implications for regional exploration","interactions":[],"lastModifiedDate":"2023-05-15T13:12:40.265332","indexId":"70240234","displayToPublicDate":"2022-12-28T08:32:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"The Sukari gold deposit, Egypt: Geochemical and geochronological constraints on the ore genesis and implications for regional exploration","docAbstract":"The Sukari gold deposit (>15 Moz Au) in the Eastern Desert of Egypt is hosted by a deformed granitoid stock (Sukari tonalite-trondhjemite intrusion) and mainly occurs as a network of crosscutting sulfide-bearing quartz (± carbonate) veins and intensely sulfidized-silicified-sericitized wall rock. Emplacement of the Sukari intrusion into a tectonized Neoproterozoic accretionary complex was controlled by a system of NE- to NNE-trending oblique faults that are related to a deep-seated positive flower structure. A robust genetic model has been hampered by the poorly understood relationships between gold mineralization and host rocks. In this study, zircon U-Pb ages of three samples from the Sukari intrusion define a crystallization age of ~695 ± 2 Ma. In contrast, hydrothermal sericite from the ore zone yields an 40Ar/39Ar age of ~625 ± 3 Ma, which coincides with the onset of major sinistral transpression in the region.
Features including sigmoidal morphology of gold quartz veins and abundant subhorizontal tension gashes alongside widespread brecciation and recrystallization suggest that quartz veining occurred during renewed shortening and exhumation through the brittle-ductile transition. Petrographic and micro-X-ray fluorescence (µXRF) studies indicate that disseminated gold and sulfides, commonly associated with sericite and carbonate alteration, are mostly confined to stylolitic bands in the quartz veins. Oscillatory and sector zoning patterns, irregular As-rich bands, and truncations between early- and late-genetic pyrites reflect variations in temperature and mechanism of ore deposition, demonstrated by variable As/S and Co/Ni ratios in the different pyrite generations. Laser ablation-inductively coupled plasma-mass spectrometry analysis pinpoints the covariance of gold and arsenic contents in pyrite, but free milling gold inclusions in microfractures consistently have a mercury-bearing electrum composition, depicting different ore formation stages.
Ore fluids with δ34
Understanding patterns of species coexistence is a fundamental challenge in ecology. The physical environment is believed to play an important role, influencing patterns of dispersal and biotic interactions across space and time. Floodplain forest species are presumed to interact strongly with their environment, as evidenced by pronounced spatial variation in forest composition associated with flood-driven abiotic constraints. Questions of how, and to what degree, fine-scale heterogeneity interacts with broad-scale hydrogeomorphology to influence patterns of functional composition remain unresolved. We examined how functional diversity (i.e. richness and range of functional traits) and ecological strategies (i.e. functional trait combinations) of floodplain forest communities varied across regional and local gradients of flooding in a northern temperate region of the United States of America. We found functional diversity of woody overstory species varied across hydrogeomorphic settings and that different settings altered associations between functional diversity and both the relative elevation above and proximity to rivers. Ecological strategies shifted over local gradients of relative elevation and distance to channel with different magnitudes and directions depending on the broader hydrogeomorphic context. We found evidence that interactions among flood regimes and landform position impose different levels of functional constraint. These results indicate patterns of community assembly are not easily discerned from landform type or position alone, but rather from filtering that operates and interacts with biota over multiple spatial scales. Our results imply that it is important to characterize flood dynamics in ways that can be clearly linked to ecological processes and that treatment of floodplain landforms as transferable units across river-valley segments is problematic, even within a single basin.
Nutrient pollution causing harmful algal blooms and eutrophication is a major threat to aquatic systems. Throughout North America, agricultural activities are the largest source of excess nutrients entering these systems. Agricultural intensification has also been a driver in the historical removal of depressional wetlands, contributing to increased hydrological connectivity across watersheds, and moving more nutrient runoff into terminal waterbodies such as the Laurentian Great Lakes and Gulf of Mexico. The Prairie Pothole Region of North America (PPR) supports grassland, cropland, wetland, and riverine systems that connect to the Missouri, Mississippi, and Red River Basins. There is a need to synthesize scientific understanding to guide more targeted conservation efforts and better understand knowledge gaps. We reviewed 200 empirical studies and synthesized results from across a minimum of 9 and maximum of 43 wetland basins (depending on the variable data available). We found an average wetland removal rate of nitrate and phosphate of 53% and 68%, respectively. Literature also showed sedimentation rates to be twice as high in wetland basins situated within croplands compared to grasslands. Our synthesis enhances understanding of nutrient processing in wetlands of the PPR and highlights the need for more empirical field-based studies throughout the region.
Conservation efforts have been implemented in agroecosystems to enhance pollinator diversity by creating grassland habitat, but little is known about the exposure of bees to pesticides while foraging in these grassland fields. Pesticide exposure was assessed in 24 conservation grassland fields along an agricultural gradient at two time points (July and August) using silicone band passive samplers (nonlethal) and bee tissues (lethal). Overall, 46 pesticides were detected including 9 herbicides, 19 insecticides, 17 fungicides, and a plant growth regulator. For the bands, there were more frequent/higher concentrations of herbicides in July (maximum: 1600 ng/band in July; 570 ng/band in August), while insecticides and fungicides had more frequent/higher concentrations in August (maximum: 110 and 65 ng/band in July; 1500 and 1700 ng/band in August). Pesticide concentrations in bands increased 16% with every 10% increase in cultivated crops. The bee tissues showed no difference in detection frequency, and concentrations were similar among months; maximum concentrations of herbicides, insecticides, and fungicides in July and August were 17, 27, and 180 and 19, 120, and 170 ng/g, respectively. Pesticide residues in bands and bee tissues did not always show the same patterns; of the 20 compounds observed in both media, six (primarily fungicides) showed a detection-concentration relationship between the two media. Together, the band and bee residue data can provide a more complete understanding of pesticide exposure and accumulation in conserved grasslands.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.2c07195","usgsCitation":"Hladik, M.L., Kraus, J.M., Smith, C., Vandever, M.W., Kolpin, D., Givens, C.E., and Smalling, K., 2023, Wild bee exposure to pesticides in conservation grasslands increases along an agricultural gradient: A tale of two sample types: Environmental Science and Technology, v. 57, no. 1, p. 321-330, https://doi.org/10.1021/acs.est.2c07195.","productDescription":"10 p.","startPage":"321","endPage":"330","ipdsId":"IP-145884","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":435530,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M3QCVW","text":"USGS data release","linkHelpText":"Pesticide residues in passive samplers and bee tissue from Conservation Reserve Program fields across an agricultural gradient in eastern Iowa, USA, 2019 (ver 2.0, October 2023)"},{"id":411113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.84229194623344,\n 43.40823254194967\n ],\n [\n -93.84229194623344,\n 40.49028000708452\n ],\n [\n -90.2987761617945,\n 40.49028000708452\n ],\n [\n -90.2987761617945,\n 43.40823254194967\n ],\n [\n -93.84229194623344,\n 43.40823254194967\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"57","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":203857,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Cassandra 0000-0003-1088-1772 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-1088-1772","contributorId":193491,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandever, Mark W. 0000-0003-0247-2629 vandeverm@usgs.gov","orcid":"https://orcid.org/0000-0003-0247-2629","contributorId":197674,"corporation":false,"usgs":true,"family":"Vandever","given":"Mark","email":"vandeverm@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":860116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":205652,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":247691,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860119,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239372,"text":"70239372 - 2023 - The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence","interactions":[],"lastModifiedDate":"2023-01-11T12:48:02.805173","indexId":"70239372","displayToPublicDate":"2022-12-27T06:42:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1816,"text":"Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"The over-prediction of seismically induced soil liquefaction during the 2016 Kumamoto, Japan earthquake sequence","docAbstract":"The rapid intensification of ecological extremes in response to climate change and human land use is perhaps nowhere more apparent than in drylands, including the semiarid region of the Colorado Plateau in the southwestern United States. Here, we describe research directions to aid in the restoration of Colorado Plateau ecosystems during the UN Decade on Ecosystem Restoration (2021–2030) that 1) address high levels of heterogeneity 2) explore simultaneous global change drivers 3) are co-produced with a broad range of partners and 4) center Indigenous ways of knowing. We highlight restoration research efforts led by early career scientists grappling with informing management actions in a region where a rapidly changing climate intersects with historic grazing and continued land use pressures to create novel ecological extremes. We highlight restoration research efforts led by early career researchers grappling with informing management actions in a region where novel ecological extremes are the result of historic grazing, continued land-use pressures, and a rapidly changing climate.
Grasslands cover a third of Earth's landmass and provide critical ecosystem services. Anticipating how perennial C3 (cool-season) and C4 (warm-season) grasses respond to climate change will be key to predicting future composition and functioning of grasslands. Here, we evaluate environmental drivers of C3 and C4 perennial distributions and assess how C3 and C4 grass distributions shift in response to future climate change.
Western United States.
We developed integrated species distribution models to identify climate and soil drivers of relative abundance of C3 and C4 perennial grasses. We then created projections of species abundances under future climate and evaluated when and where projected shifts in relative abundance were robust across climate models.
Historically, C3 grasses occupied areas with lower temperature and more variable precipitation regimes, while C4 grasses occupied areas of higher temperature, greater temperature variability and greater warm-season precipitation. C4 species also occupied narrower soil texture niches. In response to future climate change, C3 grass abundance declined across 74% of areas, while C4 abundance increased across 66% of areas. C3 grasses expanded in mid- to higher-latitude areas with increasing temperature and decreasing seasonality of precipitation. In contrast, C4 grasses increased in higher-latitude regions, but declined in lower-latitude, dryer regions. Results were surprisingly robust across climate scenarios, suggesting high confidence in the direction of these future changes.
Findings imply C3 and C4 perennial grasses will have highly divergent responses to climate change that may result in grassland functional compositional changes. Increasing temperatures and precipitation variability may favour some C4 grasses, but C4 habitat expansion may be constrained by soil conditions in western USA. Results provide actionable insights for anticipating the impacts of climate change on grass-dominated and co-dominated ecosystems and improving large-scale conservation and restoration efforts.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13669","usgsCitation":"Havrilla, C., Bradford, J., Yackulic, C., and Munson, S.M., 2023, Divergent climate impacts on C3 versus C4 grasses imply widespread 21st century shifts in grassland functional composition: Diversity and Distributions, v. 29, no. 3, p. 379-394, https://doi.org/10.1111/ddi.13669.","productDescription":"16 p.","startPage":"379","endPage":"394","ipdsId":"IP-143038","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445039,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13669","text":"Publisher Index Page"},{"id":435532,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99EGD2E","text":"USGS data release","linkHelpText":"Bioclimatic suitability for 11 dominant Colorado Plateau perennial grass species (ver. 2.0, November 2022)"},{"id":413999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.54030283521868,\n 49.526621871576566\n ],\n [\n -125.54030283521868,\n 28.895094929809844\n ],\n [\n -101.38064109224445,\n 28.895094929809844\n ],\n [\n -101.38064109224445,\n 49.526621871576566\n ],\n [\n -125.54030283521868,\n 49.526621871576566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-12-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Havrilla, Caroline A.","contributorId":303002,"corporation":false,"usgs":false,"family":"Havrilla","given":"Caroline A.","affiliations":[{"id":65592,"text":"Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, CO 80524","active":true,"usgs":false}],"preferred":false,"id":866173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866176,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239839,"text":"70239839 - 2023 - Determining seasonal recharge, storage changes, and specific yield using repeat microgravity and water-level measurements in the Mesilla Basin alluvial aquifer, New Mexico, 2016–2018","interactions":[],"lastModifiedDate":"2023-01-23T13:10:50.979932","indexId":"70239839","displayToPublicDate":"2022-12-24T07:06:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2165,"text":"Journal of Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Determining seasonal recharge, storage changes, and specific yield using repeat microgravity and water-level measurements in the Mesilla Basin alluvial aquifer, New Mexico, 2016–2018","docAbstract":"Increasing water demand and multi-year drought conditions within the Mesilla/Conejos-Médanos Basin near the New Mexico-Texas- Chihuahua border have resulted in diminished surface-water supplies and increased groundwater withdrawals. To better understand recharge to the shallow aquifer, the spatial and temporal groundwater storage changes, and the variability of specific yield (Sy) in the aquifer, seasonal groundwater elevation and repeat microgravity measurements were made during the irrigation release and non-release seasons of 2016, 2017, and 2018 at a network of locations near Las Cruces, New Mexico.
The data collected during this investigation were able to capture seasonal change in groundwater elevations and storage from various sources of recharge at multiple sites in the shallow aquifer. Seasonal recharge in the study area was attributed to streamflow, the application and conveyance of irrigation water, and large or sustained precipitation events. However, increasing groundwater gradients in recent decades between piezometers close to the river and those more than a kilometer from the river suggests that recharge from river seepage has become localized at the seasonal scale. Overall, there was a net increase in storage of almost 8.4 cubic hectometers in the study reach between the start and end of the study, largely following the increased surface-water availability and above average precipitation in 2017. Specific yield, estimated by comparing the groundwater-level changes and storage changes at six sites in the study area, ranged from 0.14 (+/− 0.05) to 0.30 (+/− 0.06), which is slightly greater than previously reported estimates (0.10 to 0.25), but still within the error of the estimates. Most of the variability in the estimated storage change, that was not well-correlated with groundwater elevation change, is thought to be from soil moisture in the unsaturated zone.
This investigation demonstrates the value of adding repeat microgravity measurements to conventional groundwater monitoring to better understand the sources and extent of recharge as well as the variability of Sy in the aquifer. Continued monitoring, under a variety of available surface water and meteorological conditions, could provide a more comprehensive understanding of the water budget and reduce the specific yield estimation uncertainty. Evaluating water-levels and storage conditions prior to, and following, local recharge events may help managers identify threshold conditions for aquifer storage depletions and recoveries.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jappgeo.2022.104916","usgsCitation":"Robertson, A.J., Kennedy, J.R., Wildermuth, L.M., Bell, M., Fuchs, E.H., Rinehart, A., and Fernald, I., 2023, Determining seasonal recharge, storage changes, and specific yield using repeat microgravity and water-level measurements in the Mesilla Basin alluvial aquifer, New Mexico, 2016–2018: Journal of Applied Geophysics, v. 209, 104916, 18 p., https://doi.org/10.1016/j.jappgeo.2022.104916.","productDescription":"104916, 18 p.","ipdsId":"IP-126256","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":445042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jappgeo.2022.104916","text":"Publisher Index Page"},{"id":412211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Mesilla Basin alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.92776690707147,\n 32.36758313268733\n ],\n [\n -106.92776690707147,\n 32.11679945449248\n ],\n [\n -106.55988114871217,\n 32.11679945449248\n ],\n [\n -106.55988114871217,\n 32.36758313268733\n ],\n [\n -106.92776690707147,\n 32.36758313268733\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Andrew J. 0000-0003-2130-0347 ajrobert@usgs.gov","orcid":"https://orcid.org/0000-0003-2130-0347","contributorId":4129,"corporation":false,"usgs":true,"family":"Robertson","given":"Andrew","email":"ajrobert@usgs.gov","middleInitial":"J.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":176478,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":862099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wildermuth, Libby M. 0000-0001-5333-0968 lwildermuth@usgs.gov","orcid":"https://orcid.org/0000-0001-5333-0968","contributorId":210459,"corporation":false,"usgs":true,"family":"Wildermuth","given":"Libby","email":"lwildermuth@usgs.gov","middleInitial":"M.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bell, Meghan T. 0000-0003-4993-1642","orcid":"https://orcid.org/0000-0003-4993-1642","contributorId":209712,"corporation":false,"usgs":true,"family":"Bell","given":"Meghan T.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862101,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuchs, Erek H. 0000-0001-9170-9469","orcid":"https://orcid.org/0000-0001-9170-9469","contributorId":270989,"corporation":false,"usgs":false,"family":"Fuchs","given":"Erek","email":"","middleInitial":"H.","affiliations":[{"id":56244,"text":"Elephant Butte Irrigation District","active":true,"usgs":false}],"preferred":false,"id":862102,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rinehart, Alex 0000-0002-9642-1461","orcid":"https://orcid.org/0000-0002-9642-1461","contributorId":301120,"corporation":false,"usgs":false,"family":"Rinehart","given":"Alex","email":"","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":862103,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fernald, Irene 0000-0001-7584-3844","orcid":"https://orcid.org/0000-0001-7584-3844","contributorId":301121,"corporation":false,"usgs":false,"family":"Fernald","given":"Irene","email":"","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":862104,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70242086,"text":"70242086 - 2023 - Fracture-mesh faulting in the swarm-like 2020 Maacama sequence revealed by high-precision earthquake detection, location, and focal mechanisms","interactions":[],"lastModifiedDate":"2023-04-06T12:03:37.41351","indexId":"70242086","displayToPublicDate":"2022-12-24T07:01:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Fracture-mesh faulting in the swarm-like 2020 Maacama sequence revealed by high-precision earthquake detection, location, and focal mechanisms","docAbstract":"In August of 2020, an earthquake sequence initiated within the Maacama fault zone in northern California, raising questions about its relationship with the larger-scale fault. To investigate the faulting geometry and its implications for physical processes driving seismicity, we applied an integrated, multi-faceted seismic analysis including waveform-correlation-based event detection, relative relocation, and high-precision focal mechanisms. To determine mechanisms for a large population of very small earthquakes (predominantly M < 1), we combined correlation-derived polarity analysis with a recently developed technique to determine S/P amplitude ratios from single seismic components. Finally, we applied an iterative stress inversion to distinguish between the likely fault and auxiliary planes. This analysis reveals that although the sequence initiated on a right-lateral fault, plausibly a strand of the Maacama Fault, it also activated numerous en echelon left-lateral conjugate faults. Together, these interlocking faults form a fracture mesh, consistent with structures associated elsewhere with fluid-induced faulting and earthquake swarms.
Borealization is a type of community reorganization where Arctic specialists are replaced by species with more boreal distributions in response to climatic warming. The process of borealization is often exemplified by the northward range expansions and subsequent proliferation of boreal species on the Pacific and Atlantic inflow Arctic shelves (i.e., Bering/Chukchi and Barents seas, respectively). But the circumpolar nearshore distribution of Arctic-boreal fishes that predates recent warming suggests borealization is possible beyond inflow shelves. To examine this question, we revisited two nearshore lagoons in the eastern Alaska Beaufort Sea (Kaktovik and Jago lagoons, Arctic National Wildlife Refuge, Alaska, USA), a High Arctic interior shelf. We compared summer fish species assemblage, catch rate, and size distribution among three periods that spanned a 30-year record (baseline conditions, 1988–1991; moderate sea ice decline, 2003–2005; rapid sea ice decline, 2017–2019). Fish assemblages differed among periods in both lagoons, consistent with borealization. Among Arctic specialists, a clear decline in fourhorn sculpin (Myoxocephalus quadricornis, Kanayuq in Iñupiaq) occurred in both lagoons with 86%–90% lower catch rates compared with the baseline period. Among the Arctic-boreal species, a dramatic 18- to 19-fold increase in saffron cod (Eleginus gracilis, Uugaq) occurred in both lagoons. Fish size (length) distributions demonstrated increases in the proportion of larger fish for most species examined, consistent with increasing survival and addition of age-classes. These field data illustrate borealization of an Arctic nearshore fish community during a period of rapid warming. Our results agree with predictions that Arctic-boreal fishes (e.g., saffron cod) are well positioned to exploit the changing Arctic ecosystem. Another Arctic-boreal species, Dolly Varden (Salvelinus malma, Iqalukpik), appear to have already responded to warming by shifting from Arctic nearshore to shelf waters. More broadly, our findings suggest that areas of borealization could be widespread in the circumpolar nearshore.
Wildlife translocation facilitates conservation efforts, including recovering imperiled species, reducing human–wildlife conflict, and restoring degraded ecosystems. Beaver (American, Castor canadensis; Eurasian, C. fiber) translocation may mitigate human–wildlife conflict and facilitate ecosystem restoration. However, few projects measure outcomes of translocations by monitoring beaver postrelease, and translocation to desert streams is relatively rare. We captured, tagged, and monitored 47 American beavers (hereafter, beavers) which we then translocated to two desert rivers in Utah, USA, to assist in passive river restoration. We compared translocated beaver site fidelity, survival, and dam-building behavior to 24 resident beavers. We observed high apparent survival (i.e., survived and stayed in the study site) for eight weeks postrelease of resident adult beavers (0.88 ± 0.08; standard error) and lower but similar apparent survival rates between resident subadult (0.15 ± 0.15), translocated adult (0.26 ± 0.12), and translocated subadult beavers (0.09 ± 0.08). Neither the pre- nor the post-translocation count of river reaches with beaver dams were predicted well by the Beaver Restoration Assessment Tool, which estimates maximum beaver dam capacity by river reach, suggesting beaver-related restoration is not maximized in these rivers. Translocated beavers exhibited similar characteristics as resident subadult beavers during dispersal; they were more vulnerable to predation and many emigrated from the study sites. High mortality and low site fidelity should be anticipated when translocating beavers, but even so, translocation may have contributed to additional beaver dams in the restoration sites, which is the common goal of beaver-assisted river restoration. Multiple releases at targeted restoration sites may eventually result in establishment and meet conservation objectives for desert rivers.
Addressing ongoing biodiversity loss requires collaboration between conservation scientists and practitioners. However, such collaboration has proved challenging. Despite the potential importance of tracking animal movements for conservation, reviews of the tracking literature have identified a gap between the academic discipline of movement ecology and its application to biodiversity conservation. Through structured conversations with movement ecologists and conservation practitioners, we aimed to understand whether the identified gap is also perceived in practice, and if so, what factors hamper collaboration and how these factors can be remediated. We found that both groups are motivated and willing to collaborate. However, because their motivations differ, there is potential for misunderstandings and miscommunications. In addition, external factors such as funder requirements, academic metrics, and journal scopes may limit the applicability of scientific results in a conservation setting. Potential solutions we identified included improved communication and better presentation of results, acknowledging each other's motivations and desired outputs, and adjustment of funder priorities. Addressing gaps between science and implementation can enhance collaboration and support conservation action to address the global biodiversity crisis more effectively.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12870","usgsCitation":"Nuijten, R.J., Katzner, T., Allen, A.M., Bijleveld, A.I., Boorsma, T., Borger, L., Cagnacci, F., Hart, T., Henley, M., Herren, R.M., Kok, E., Maree, B., Nebe, B., Shohami, D., Vogel, S.M., Walker, P., Heitkonig, I.M., and Milner-Gulland, E., 2023, Priorities for translating goodwill between movement ecologists and conservation practitioners into effective collaboration: Conservation Science and Practice, v. 5, no. 1, e12870, 14 p., https://doi.org/10.1111/csp2.12870.","productDescription":"e12870, 14 p.","ipdsId":"IP-137484","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445056,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12870","text":"Publisher Index Page"},{"id":411489,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Nuijten, Rascha J. M.","contributorId":222016,"corporation":false,"usgs":false,"family":"Nuijten","given":"Rascha","email":"","middleInitial":"J. M.","affiliations":[{"id":40471,"text":"Department of Animal Ecology, Netherlands Institute for Ecology","active":true,"usgs":false}],"preferred":false,"id":861020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":860965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Andrew M.","contributorId":205057,"corporation":false,"usgs":false,"family":"Allen","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":861021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bijleveld, Allert I.","contributorId":300637,"corporation":false,"usgs":false,"family":"Bijleveld","given":"Allert","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":861022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boorsma, Tjalle","contributorId":300638,"corporation":false,"usgs":false,"family":"Boorsma","given":"Tjalle","email":"","affiliations":[],"preferred":false,"id":861023,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Borger, Luca","contributorId":300639,"corporation":false,"usgs":false,"family":"Borger","given":"Luca","email":"","affiliations":[],"preferred":false,"id":861024,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cagnacci, Francesca","contributorId":205070,"corporation":false,"usgs":false,"family":"Cagnacci","given":"Francesca","email":"","affiliations":[],"preferred":false,"id":861025,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hart, Tom","contributorId":300640,"corporation":false,"usgs":false,"family":"Hart","given":"Tom","email":"","affiliations":[],"preferred":false,"id":861026,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Henley, Michelle","contributorId":300641,"corporation":false,"usgs":false,"family":"Henley","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":861027,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Herren, Richard M.","contributorId":46409,"corporation":false,"usgs":true,"family":"Herren","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":861028,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kok, Eva","contributorId":225537,"corporation":false,"usgs":false,"family":"Kok","given":"Eva","email":"","affiliations":[{"id":36570,"text":"NIOZ Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":861029,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Maree, Bronwyn","contributorId":300642,"corporation":false,"usgs":false,"family":"Maree","given":"Bronwyn","email":"","affiliations":[],"preferred":false,"id":861030,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nebe, Bruno","contributorId":300643,"corporation":false,"usgs":false,"family":"Nebe","given":"Bruno","email":"","affiliations":[],"preferred":false,"id":861031,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shohami, David","contributorId":300644,"corporation":false,"usgs":false,"family":"Shohami","given":"David","email":"","affiliations":[],"preferred":false,"id":861032,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Vogel, Susanne Marieke","contributorId":300646,"corporation":false,"usgs":false,"family":"Vogel","given":"Susanne","email":"","middleInitial":"Marieke","affiliations":[],"preferred":false,"id":861033,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Walker, Paul","contributorId":300645,"corporation":false,"usgs":false,"family":"Walker","given":"Paul","email":"","affiliations":[],"preferred":false,"id":861034,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Heitkonig, Ignas M. A.","contributorId":300647,"corporation":false,"usgs":false,"family":"Heitkonig","given":"Ignas","email":"","middleInitial":"M. A.","affiliations":[],"preferred":false,"id":861035,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Milner-Gulland, E. J.","contributorId":169226,"corporation":false,"usgs":false,"family":"Milner-Gulland","given":"E. J.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":861036,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70239202,"text":"70239202 - 2023 - Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2023-02-02T17:57:35.332175","indexId":"70239202","displayToPublicDate":"2022-12-23T07:07:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Pesticide prioritization by potential biological effects in tributaries of the Laurentian Great Lakes","docAbstract":"Watersheds of the Great Lakes Basin (USA/Canada) are highly modified and impacted by human activities including pesticide use. Despite labeling restrictions intended to minimize risks to nontarget organisms, concerns remain that environmental exposures to pesticides may be occurring at levels negatively impacting nontarget organisms. We used a combination of organismal-level toxicity estimates (in vivo aquatic life benchmarks) and data from high-throughput screening (HTS) assays (in vitro benchmarks) to prioritize pesticides and sites of concern in streams at 16 tributaries to the Great Lakes Basin. In vivo or in vitro benchmark values were exceeded at 15 sites, 10 of which had exceedances throughout the year. Pesticides had the greatest potential biological impact at the site with the greatest proportion of agricultural land use in its basin (the Maumee River, Toledo, OH, USA), with 72 parent compounds or transformation products being detected, 47 of which exceeded at least one benchmark value. Our risk-based screening approach identified multiple pesticide parent compounds of concern in tributaries of the Great Lakes; these compounds included: eight herbicides (metolachlor, acetochlor, 2,4-dichlorophenoxyacetic acid, diuron, atrazine, alachlor, triclopyr, and simazine), three fungicides (chlorothalonil, propiconazole, and carbendazim), and four insecticides (diazinon, fipronil, imidacloprid, and clothianidin). We present methods for reducing the volume and complexity of potential biological effects data that result from combining contaminant surveillance with HTS (in vitro) and traditional (in vivo) toxicity estimates. Environ Toxicol Chem 2022;00:1–18. Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
No abstract available.
","language":"English","publisher":"AAAS","doi":"10.1126/science.adf2993","usgsCitation":"Flinders, A.F., 2023, The Pāhala swarm of earthquakes in Hawai‘i: Science, v. 379, no. 6631, p. 434-435, https://doi.org/10.1126/science.adf2993.","productDescription":"2 p.","startPage":"434","endPage":"435","ipdsId":"IP-146369","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":419303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.2406746623263,\n 20.328514811681515\n ],\n [\n -156.2406746623263,\n 18.87313735827118\n ],\n [\n -154.76152573414413,\n 18.87313735827118\n ],\n [\n -154.76152573414413,\n 20.328514811681515\n ],\n [\n -156.2406746623263,\n 20.328514811681515\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"379","issue":"6631","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Flinders, Ashton F. 0000-0003-2483-4635","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":271052,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":878915,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70263790,"text":"70263790 - 2023 - Detailed 40Ar/39Ar geochronology of the Loyalty and Three Kings Ridges clarifies the extent and sequential development of Eocene to Miocene southwest Pacific remnant volcanic arcs","interactions":[],"lastModifiedDate":"2025-02-24T15:47:37.98325","indexId":"70263790","displayToPublicDate":"2022-12-22T09:37:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Detailed 40Ar/39Ar geochronology of the Loyalty and Three Kings Ridges clarifies the extent and sequential development of Eocene to Miocene southwest Pacific remnant volcanic arcs","title":"Detailed 40Ar/39Ar geochronology of the Loyalty and Three Kings Ridges clarifies the extent and sequential development of Eocene to Miocene southwest Pacific remnant volcanic arcs","docAbstract":"The 2015 VESPA voyage (Volcanic Evolution of South Pacific Arcs) was a seismic and rock dredging expedition to the Loyalty and Three Kings Ridges and South Fiji Basin. In this paper we present 33 40Ar/39Ar, 22 micropaleontological, and two U/Pb ages for igneous and sedimentary rocks from 33 dredge sites in this little-studied part of the southwest Pacific Ocean. Igneous rocks include basalts, dolerites, basaltic andesites, trachyandesites, and a granite. Successful Ar/Ar dating of altered and/or low-K basalts was achieved through careful sample selection and processing, detailed petrographic and element mapping of groundmass, and incremental heating experiments on both phenocryst and groundmass separates to interpret the complex spectra produced by samples having multiple K reservoirs. The 40Ar/39Ar ages of most of the sampled lavas, irrespective of composition, are latest Oligocene to earliest Miocene (25–22 Ma); two are Eocene (39–36 Ma). The granite has a U/Pb zircon age of 23.6 ± 0.3 Ma. 40Ar/39Ar lava ages are corroborated by microfossil ages from associated sedimentary rocks. The VESPA lavas are part of a >3,000 km long disrupted belt of Eocene to Miocene subduction-related volcanic rocks. The belt includes arc rocks in Northland New Zealand, Northland Plateau, Three Kings Ridge, and Loyalty Ridge and, speculatively, D’Entrecasteaux Ridge. This belt is the product of superimposed Eocene and Oligocene-Miocene remnant volcanic arcs that were stranded along and near the edge of Zealandia while still-active arc belts migrated east with the Pacific trench.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GC010670","usgsCitation":"Gans, P., Mortimer, N., Patriat, M., Turnbull, R., Crundwell, M., Agranier, A., Calvert, A.T., Seward, G., Etienne, S., Durance, P., Campbell, H., and Collot, J., 2023, Detailed 40Ar/39Ar geochronology of the Loyalty and Three Kings Ridges clarifies the extent and sequential development of Eocene to Miocene southwest Pacific remnant volcanic arcs: Geochemistry, Geophysics, Geosystems, v. 24, no. 2, e2022GC010670, 33 p., https://doi.org/10.1029/2022GC010670.","productDescription":"e2022GC010670, 33 p.","ipdsId":"IP-145966","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":489950,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gc010670","text":"Publisher Index 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Caledonia","active":true,"usgs":false}],"preferred":false,"id":928301,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70247139,"text":"70247139 - 2023 - Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions","interactions":[],"lastModifiedDate":"2023-07-25T14:31:36.964032","indexId":"70247139","displayToPublicDate":"2022-12-22T09:14:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions","docAbstract":"Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13093","usgsCitation":"Zwart, J.A., Oliver, S.K., Watkins, W., Sadler, J.M., Appling, A.P., Corson-Dosch, H.R., Jia, X., Kumar, V., and Read, J., 2023, Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions: Journal of the American Water Resources Association, v. 59, no. 2, p. 317-337, https://doi.org/10.1111/1752-1688.13093.","productDescription":"21 p.","startPage":"317","endPage":"337","ipdsId":"IP-135607","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.13093","text":"Publisher Index Page"},{"id":419302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-12-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - 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At warmer temperatures, fish require more energy to sustain growth; changes in their metabolic rates and consuming prey with potentially higher Hg concentrations could result in increased Hg accumulation. To examine the potential implications of climate warming on forage fish Hg accumulation in Arctic lakes, we quantified growth and Hg accumulation in Ninespine Stickleback Pungitius pungitius under different temperature and diet scenarios using bioenergetics models. Four scenarios were considered that examined the role of climate, diet, climate × diet, and climate × diet × elevated prey Hg. As expected, annual fish growth increased with warmer temperatures, but growth rates and Hg accumulation were largely diet dependent. Compared to current growth rates of 0.3 g⋅y−1, fish growth increased at least 200% for fish consuming energy-dense benthic prey and decreased at least 40% for fish consuming pelagic prey. Compared to baseline levels, the Hg burden per kilocalorie of Ninespine Stickleback declined up to 43% with benthic consumption – indicating strong somatic growth dilution – but no more than 4% with pelagic consumption; elevated prey Hg concentrations led to moderate Hg declines in benthic-foraging fish and Hg increases in pelagic-foraging fish. Bioenergetics models demonstrated the complex interaction of water temperature, growth, prey proportions, and prey Hg concentrations that respond to climate change. Further work is needed to resolve mechanisms and rates linking climate change to Hg availability and uptake in Arctic freshwater systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2022.114851","usgsCitation":"Laske, S.M., Burke, S.M., Carey, M.P., Swanson, H.K., and Zimmerman, C.E., 2023, Investigating effects of climate-induced changes in water temperature and diet on mercury concentrations in an Arctic freshwater forage fish: Environmental Research, v. 218, 114851, 13 p., https://doi.org/10.1016/j.envres.2022.114851.","productDescription":"114851, 13 p.","ipdsId":"IP-144262","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":445064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envres.2022.114851","text":"Publisher Index Page"},{"id":417911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.67980839183957,\n 70.52713703737254\n ],\n [\n -157.67980839183957,\n 70\n ],\n [\n -156.79804904275505,\n 70\n ],\n [\n -156.79804904275505,\n 70.52713703737254\n ],\n [\n -157.67980839183957,\n 70.52713703737254\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"218","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":874844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burke, Samantha M.","contributorId":203348,"corporation":false,"usgs":false,"family":"Burke","given":"Samantha","email":"","middleInitial":"M.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":874845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":874846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swanson, Heidi K.","contributorId":203350,"corporation":false,"usgs":false,"family":"Swanson","given":"Heidi","email":"","middleInitial":"K.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":874847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":874848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}