Obtaining reliable information on the age structure of fish populations is important for making conservation and management decisions. We sought to evaluate precision and reader confidence in age estimates from scales (two body locations), sectioned fin rays (pectoral, pelvic, anal), and sectioned sagittal otoliths from Apache Trout Oncorhynchus apache (n = 78 fish) sampled from the East Fork White River, Arizona, in 2017. Two experienced readers without prior knowledge of fish length aged structures independently. Each reader provided a confidence rating of 0 (no confidence) to 3 (completely confident) as a measure of readability. Both readers were unable to estimate age from scales collected from the area just posterior to the insertion of the pectoral fin. We used scales removed from an area just dorsal to the lateral line and posterior to the dorsal fin in all analyses. Percentage of exact agreement between readers was highest for scales and otoliths (>72.0%) and lowest for fin rays (31.8–58.1%). Average confidence rating was highest for sectioned otoliths (mean ± SE, 2.1 ± 0.07), and lowest for anal fin rays (0.3 ± 0.06) and scales (0.7 ± 0.05). We compared consensus ages from otoliths to the other structures. Percentage of exact agreement with otolith age was low and varied from 21.6 to 35.7% among structures. Similarly, percentage of agreement within 1 y was also low among structures (58.0–70.2%). Scales consistently underestimated age of age-4 and older fish (based on otolith age), whereas fin rays tended to overestimate age of younger fish and underestimate age of older Apache Trout. Although sectioned otoliths require lethal sampling, they produced the most precise age estimates for Apache Trout with the highest reader confidence. Dorsal scales may be a suitable nonlethal alternative to otoliths if ages for only young fish (age 3 and younger) meet study objectives.
","language":"English","publisher":"U.S. Fish and Wildlife Mangement","doi":"10.3996/jfwm-22-021","usgsCitation":"Quist, M.C., Ulaski, M., Manuell, K., Jackson, Z., and Gatewood, T., 2023, Precision of structures used to estimate age and growth of Apache Trout from Arizona: Journal of Fish and Wildlife Management, v. 14, no. 1, p. 188-194, https://doi.org/10.3996/jfwm-22-021.","productDescription":"7 p.","startPage":"188","endPage":"194","ipdsId":"IP-139085","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3996/jfwm-22-021","text":"Publisher Index Page"},{"id":482916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":929515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ulaski, Marta","contributorId":280108,"corporation":false,"usgs":false,"family":"Ulaski","given":"Marta","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":929516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manuell, Kristy","contributorId":351806,"corporation":false,"usgs":false,"family":"Manuell","given":"Kristy","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":929517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Zachary","contributorId":338597,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":929518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gatewood, Tim","contributorId":351808,"corporation":false,"usgs":false,"family":"Gatewood","given":"Tim","affiliations":[{"id":84049,"text":"White Mountain Apache Tribe Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":929519,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70247955,"text":"70247955 - 2023 - Temporal patterns of structural sagebrush connectivity from 1985 to 2020","interactions":[],"lastModifiedDate":"2023-08-30T11:02:22.320981","indexId":"70247955","displayToPublicDate":"2023-06-02T09:08:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Temporal patterns of structural sagebrush connectivity from 1985 to 2020","docAbstract":"The sagebrush biome within the western United States has been reshaped by disturbances, management, and changing environmental conditions. As a result, sagebrush cover and configuration have varied over space and time, influencing processes and species that rely on contiguous, connected sagebrush. Previous studies have documented changes in sagebrush cover, but we know little about how the connectivity of sagebrush has changed over time and across the sagebrush biome. We investigated temporal connectivity patterns for sagebrush using a time series (1985–2020) of fractional sagebrush cover and used an omnidirectional circuit algorithm to assess the density of connections among areas with abundant sagebrush. By comparing connectivity patterns over time, we found that most of the biome experienced moderate change; the amount and type of change varied spatially, indicating that areas differ in the trend direction and magnitude of change. Two different types of designated areas of conservation and management interest had relatively high proportions of stable, high-connectivity patterns over time and stable connectivity trends on average. These results provide ecological information on sagebrush connectivity persistence across spatial and temporal scales that can support targeted actions to address changing structural connectivity and to maintain functioning, connected ecosystems.
","language":"English","publisher":"MDPI","doi":"10.3390/land12061176","usgsCitation":"Buchholtz, E.K., O’Donnell, M.S., Heinrichs, J., and Aldridge, C.L., 2023, Temporal patterns of structural sagebrush connectivity from 1985 to 2020: Land, v. 12, no. 6, 1176, 13 p., https://doi.org/10.3390/land12061176.","productDescription":"1176, 13 p.","ipdsId":"IP-149528","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":443212,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land12061176","text":"Publisher Index Page"},{"id":435296,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ED3OHH","text":"USGS data release","linkHelpText":"Sagebrush structural connectivity yearly and temporal trends based on RCMAP sagebrush products, biome-wide from 1985 to 2020"},{"id":420238,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.96080474168178,\n 38.705700643079126\n ],\n [\n -115.78518256667087,\n 34.921896948006165\n ],\n [\n -114.61161113478016,\n 36.338264497018244\n ],\n [\n -113.767664676413,\n 35.05005751349394\n ],\n [\n -112.65446218611822,\n 34.49061043886182\n ],\n [\n -112.06315236527561,\n 35.73094134678898\n ],\n [\n -109.54598209325795,\n 34.19549893805224\n ],\n [\n -106.89665758360098,\n 32.69494633725995\n ],\n [\n -104.71617700706355,\n 36.11077455150861\n ],\n [\n -104.55021627544596,\n 39.39791391643246\n ],\n [\n -102.74204247363139,\n 41.178395117310885\n ],\n [\n -101.91586719976846,\n 44.15607703673757\n ],\n [\n -102.57953583556366,\n 47.8714554984052\n ],\n [\n -104.41540160422653,\n 47.87078532552721\n ],\n [\n -105.32574816853759,\n 47.678443090909866\n ],\n [\n -105.58191871342933,\n 48.88758293756308\n ],\n [\n -111.59184312773306,\n 49.007633669026006\n ],\n [\n -111.43229696003331,\n 46.72141563224213\n ],\n [\n -113.85176301374159,\n 49.08872019311082\n ],\n [\n -115.1516486551431,\n 46.36810451906729\n ],\n [\n -115.50149965627025,\n 44.04779080867547\n ],\n [\n -118.81497419811586,\n 48.948530483008625\n ],\n [\n -120.40779607271287,\n 48.96193708211112\n ],\n [\n -121.56614731481,\n 44.386012657400386\n ],\n [\n -122.69235641752775,\n 42.28566289188129\n ],\n [\n -122.1452674395685,\n 39.40569110412574\n ],\n [\n -120.96080474168178,\n 38.705700643079126\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Buchholtz, Erin K. 0000-0002-1985-9531","orcid":"https://orcid.org/0000-0002-1985-9531","contributorId":300162,"corporation":false,"usgs":true,"family":"Buchholtz","given":"Erin","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":881232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":881233,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249478,"text":"70249478 - 2023 - Volcanic and tectonic sources of seismicity near the Tanaga Volcanic Cluster, Alaska","interactions":[],"lastModifiedDate":"2023-10-10T12:08:34.094858","indexId":"70249478","displayToPublicDate":"2023-06-02T07:06:45","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}},"title":"Volcanic and tectonic sources of seismicity near the Tanaga Volcanic Cluster, Alaska","docAbstract":"Tanaga Island in the Central Aleutian Islands includes four stratovolcanoes: Sajaka, Tanaga, and East Tanaga in the northwest, and Takawangha in the central part of the island. Of these volcanoes, only Tanaga has a confirmed record of historical eruptive activity. We use double-difference methods to relocate Tanaga Island earthquakes from the period 2003–2017 to gain insight into volcanic and tectonic activity in the region. High precision relative relocations show subsurface structures in the Tanaga region related to volcanism and crustal tectonics. In 2005, a swarm of ∼600 volcano-tectonic events located below the NW portion of the island culminated with an episode of volcanic tremor. Although there was no known eruption associated with this swarm, we suggest that this activity is associated with fluids beneath Takawangha volcano. Overall, relatively little seismicity appears to be associated with volcanism: of 5,680 earthquakes relocated in this study, only ∼700 took place within 10 km of the volcanoes themselves. Other regions appear to experience primarily, if not exclusively, tectonic seismicity. Two regions on Tanaga Island became seismically active following a M6.6 tectonic earthquake east of the island on 2 May 2008, suggesting the triggering of tectonic earthquakes by the M6.6. Seismic activity recorded offshore and below the southern part of the island is interpreted as due to the clockwise rotation of the Delarof Block in the forearc, and bookshelf faulting along the volcanic arc. This suggests a complex pattern of earthquake hypocenters governed by both volcanic and tectonic processes surrounding Tanaga and Takawangha volcanoes.
In an investigation of pharmaceutical contamination in the Lac du Flambeau Chain of Lakes (hereafter referred to as “the Chain”), few contaminants were detected; only eight pharmaceuticals and one pesticide were identified among the 110 pharmaceuticals and other organic contaminants monitored in surface water samples. This study, conducted in cooperation with the Lac du Flambeau Tribe’s Water Resource Program, investigated these organic contaminants and potential biological effects in channels connecting lakes throughout the Chain, including the Moss Lake Outlet site, adjacent to the wastewater treatment plant lagoon. Of the 6 sites monitored and 24 samples analyzed, sample concentrations and contaminant detection frequencies were greatest at the Moss Lake Outlet site; however, the concentrations and detection frequencies of this study were comparable to other pharmaceutical investigations in basins with similar characteristics. Because established water-quality benchmarks do not exist for the pharmaceuticals detected in this study, alternative screening-level water-quality benchmarks, developed using two U.S. Environmental Protection Agency toxicological resources (ToxCast database and ECOTOX knowledgebase), were used to estimate potential biological effects associated with the observed contaminant concentrations. Two contaminants (caffeine and thiabendazole) exceeded the prioritization threshold according to ToxCast alternative benchmarks, and four contaminants (acetaminophen, atrazine, caffeine, and carbamazepine) exceeded the prioritization threshold according to ECOTOX alternative benchmarks. Atrazine, an herbicide, was the most frequently detected contaminant (79% of samples), and it exhibited the strongest potential for biological effects due to its high estimated potency. Insufficient toxicological information within ToxCast and ECOTOX for gabapentin and methocarbamol (which had the two greatest concentrations in this study) precluded alternative benchmark development. This data gap presents unknown potential environmental impacts. Future research examining the biological effects elicited by these two contaminants as well as the others detected in this study would further elucidate the ecological relevance of the water chemistry results generated though this investigation.
The Trinity River is managed in two sections: (1) the upper 64-kilometer (km) “restoration reach” downstream from Lewiston Dam and (2) the 120-km lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously constructed and calibrated for the restoration reach. In this report, we extended and parameterized S3 for the 120-km section of the lower Trinity River to the confluence with the Klamath River and then to the Pacific Ocean in northern California.
S3 is a deterministic life-stage structured-population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive (1) survival and growth within each habitat unit and (2) movement of fish among habitat units.
The physical template of the Trinity River was formed by classifying the river into 910 meso-habitat units that were designated into runs, riffles, or pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival.
We estimated key movement and survival parameters by calibrating the model to 12 years (2007–18) of weekly juvenile abundance estimates from two rotary screw traps: (1) the Pear Tree trap near the downstream end of the restoration reach and (2) the Willow Creek trap site is about 40.2 km upriver from the Trinity River’s confluence with the Klamath River. The calibration consisted of replicating historical conditions as closely as possible (for example: flow, temperature, spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated four alternative model structures that included either no density-dependence, density-independent movement and survival, density-dependent survival, or density-dependent movement. Akaike information criterion model selection was used to evaluate the strength of evidence for alternative model structures to simulate the observed abundance estimates.
Model selection supported the conclusion that the fully density-dependent model and density-dependent survival model was better supported by the data than the no density-dependence or density-dependent movement model. Because density-dependent movement was favored in past evaluations, we focus on the results from the fully density-dependent model. Parameter estimates from this model indicated that fry were less likely than parr to move downstream and that fry moved slower. Fry had a lower daily survival probability than parr. In contrast, hatchery fish had the highest probability of movement and the lowest daily survival probability.
Fitting the model to both traps individually enabled us to independently compare the fit and performance of S3 at simulating fish abundance, timing, and growth of juvenile salmon in the upper restoration reach and lower Trinity River. We obtained a better fit to the data at the Willow Creek trap site than we obtained at the Pear Tree trap site, regardless of whether we fit the model to the abundances at the Pear Tree trap or Willow Creek trap. This better fit was surprising given that the S3 input data for the upper restoration reach required fewer assumptions than fitting to the Willow Creek trap site that is farther down river. Fitting S3 to weekly abundances at the Willow Creek trap site required making assumptions about (1) extrapolating capacity-flow relationships to unmeasured habitat units; (2) spatially allocating spawners within the lower Trinity River; and (3) approximating the abundance, timing, and size of juveniles entering from tributaries. The model provided better fit to the data at the Willow Creek trap site. In the weekly abundance estimates, in relation to the S3 simulated abundances, several migration years’ (2011, 2015–17) weekly abundance estimates appeared truncated and were near or at peak annual abundances in January, suggesting that a large fraction of juveniles was migrating as early as December at the Pear Tree trap site. Some early life dynamics may not be currently incorporated into S3. For example, the estimation of abundance at the Pear Tree trap may be biased because of size selectivity. Knowing about selectivity at the Pear Tree trap could greatly improve S3’s ability to predict weekly and peak abundances each year.
Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Arctic-boreal wetlands, important ecosystems for biodiversity and ecological services, are experiencing hydrological changes including permafrost thaw, earlier snowmelt, and increased wildfire susceptibility. These changes are affecting wetland productivity, species diversity, and biogeochemical cycles. However, given the diverse forms and structures of wetland vegetation communities, traditional wetland maps generated from lower spatial and spectral resolution satellite imagery lack community-level vegetation classification and miss spatially complex patterns. In this study, we built a cloud-based workflow to map wetland vegetation community of the Peace-Athabasca Delta (PAD), Canada, by leveraging high-resolution (5-m) airborne multi-sensor datasets, namely NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), and a historical LiDAR archive. Validation of our classifications using ground references indicates that classifications derived from AVIRIS-NG have higher accuracies (≥87.9%) than either UAVSAR (65.6%) or LiDAR (75.9%) for mapping wetland vegetation communities. We also show improved classification accuracy when combining information from multiple sensors. In particular, incorporating AVIRIS-NG and UAVSAR datasets substantially reduced omission errors of wet graminoid and wet shrub classes from 29.6% to 20.5% and from 10.8% to 7.5%, respectively. Combining AVIRIS-NG and LiDAR datasets further improves overall accuracy (+2.2%) for most classifications, especially emergent vegetation, wet graminoid, and wet shrub. The best performing model, using features derived from all three sensors, achieved an overall accuracy of 93.5%. The framework established here can be used to leverage extensive airborne AVIRIS-NG and UAVSAR datasets collected across Alaska and northwest Canada to understand the spatial distribution of Arctic-Boreal wetland vegetation communities.
Anticoagulant rodenticides (AR) have been used globally to manage commensal rodents for decades. However their application has also resulted in primary, secondary, and tertiary poisoning in wildlife. Widespread exposure to ARs (primarily second generation ARs; SGARs) in raptors and avian scavengers has triggered considerable conservation concern over their potential effects on populations. To identify risk to extant raptor and avian scavenger populations in Oregon and potential future risk to the California condor (Gymnogyps californianus) flock recently established in northern California, we assessed AR exposure and physiological responses in two avian scavenger species (common ravens [Corvus corax] and turkey vultures [Cathartes aura]) throughout Oregon between 2013 and 2019. AR exposure was widespread with 51% (35/68) of common ravens and 86% (63/73) of turkey vultures containing AR residues. The more acutely toxic SGAR brodifacoum was present in 83% and 90% of AR exposed common ravens and turkey vultures. The odds of AR exposure in common ravens were 4.7-fold higher along the coastal region compared to interior Oregon. For common ravens and turkey vultures that were exposed to ARs, respectively, 54% and 56% had concentrations that exceeded the 5% probability of toxicosis (>20 ng/g ww; Thomas et al., 2011), and 20% and 5% exceeded the 20% probability of toxicosis (>80 ng/g ww; Thomas et al., 2011). Common ravens exhibited a physiological response to AR exposure with fecal corticosterone metabolites increasing with sum ARs (ΣAR) concentrations. Both female common raven and turkey vultures’ body condition was negatively correlated with increasing ΣAR concentrations. Our results suggest avian scavengers in Oregon are experiencing extensive AR exposure and the newly established population of California condors in northern California may experience similar AR exposure if they feed in southern Oregon. Understanding the sources of ARs across the landscape is an important first step in reducing or eliminating AR exposure in avian scavengers.
One challenge in wildlife conservation is understanding how various threats and management actions may influence long-term population viability. This is particularly evident when there is considerable uncertainty regarding population structure and vital rates. Reassessment of current knowledge and population trends is necessary for listed species to improve management actions that benefit conservation. We present an updated population viability analysis for northern Great Plains piping plovers (Charadrius melodus circumcinctus) based on the latest scientific data on survival, fecundity, and connectivity. Further, we explore the consequences of potential management actions and the stochastic effects of global climate change on population viability through changes in survival and fecundity. Our results predict elevated risks of extinction after 50 years (0.088 – 0.373) compared to previous predictions (0.033) based on assumed conditions of low connectivity among four major breeding groups structured as a metapopulation. We explored eight scenarios based on empirically-derived, higher connectivity rates and found that the northern Great Plains population never had a mean predicted population growth rate greater than one (0.946 – 0.996). Two scenarios that simulated a reduction in adult survival showed higher extinction probabilities (0.267 – 0.373), whereas two other scenarios that simulated an increase in fecundity exhibited lower extinction probabilities (0.088 – 0.103). These results indicate that viability of the northern Great Plains population of piping plovers could be improved with management actions that increase fecundity as long as adult survival is not simultaneously reduced. Lastly, breeding groups appeared to function less independently when connectivity rates were higher, as the breeding population was divided evenly among breeding groups. This indicates that the presumed metapopulation structure of our study system may need to be re-evaluated, and that empirically-based estimates of connectivity are essential to assessing population viability of mobile species that exhibit a spatially structured distribution.
Geological maps are powerful models for visualizing the complex distribution of rock types through space and time. However, the descriptive information that forms the basis for a preferred map interpretation is typically stored in geological map databases as unstructured text data that are difficult to use in practice. Herein we apply natural language processing (NLP) to geoscientific text data from Canada, the U.S., and Australia to address that knowledge gap. First, rock descriptions, geological ages, lithostratigraphic and lithodemic information, and other long-form text data are translated to numerical vectors, i.e., a word embedding, using a geoscience language model. Network analysis of word associations, nearest neighbors, and principal component analysis are then used to extract meaningful semantic relationships between rock types. We further demonstrate using simple Naive Bayes classifiers and the area under receiver operating characteristics plots (AUC) how word vectors can be used to: (1) predict the locations of “pegmatitic” (AUC = 0.962) and “alkalic” (AUC = 0.938) rocks; (2) predict mineral potential for Mississippi-Valley-type (AUC = 0.868) and clastic-dominated (AUC = 0.809) Zn-Pb deposits; and (3) search geoscientific text data for analogues of the giant Mount Isa clastic-dominated Zn-Pb deposit using the cosine similarities between word vectors. This form of semantic search is a promising NLP approach for assessing mineral potential with limited training data. Overall, the results highlight how geoscience language models and NLP can be used to extract new knowledge from unstructured text data and reduce the mineral exploration search space for critical raw materials.
Amplifications of seismic waves traveling upward through a continuous, interface‐free velocity profile are consistently smaller when computed using the square‐root‐impedance (SRI) method than when computed using full‐resonance (FR) calculations. This was found for a wide range of velocity profiles. For realistic profiles, for which the gradient of velocity decreases with depth, the differences are not large, with the ratio of FR/SRI amplifications ranging from about 1.05 to 1.3. Comparisons of the amplifications from a continuous velocity profile with those from approximations to that profile using a stack of constant‐velocity layers give some support to the hypothesis that the difference between FR and SRI amplifications for gradient profiles is because the former is controlled by the ratio of seismic impedances, whereas the latter is based on the square root of the seismic impedance ratios. This implies that gradient profiles will always have FR amplifications greater than SRI amplifications. A model‐independent, easy‐to‐implement modification of the SRI amplifications is proposed that shows promise in bringing the SRI amplifications closer to the FR amplifications.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220197","usgsCitation":"Boore, D., and Abrahamson, N., 2023, On the ratio of full‐resonance to square‐root‐impedance amplifications for shear‐wave velocity profiles that are a continuous function of depth: Bulletin of the Seismological Society of America, v. 113, no. 3, p. 1192-1207, https://doi.org/10.1785/0120220197.","productDescription":"16 p.","startPage":"1192","endPage":"1207","ipdsId":"IP-145432","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abrahamson, Norm A","contributorId":195307,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norm A","affiliations":[],"preferred":false,"id":926871,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256549,"text":"70256549 - 2023 - Global review reveals how disparate study motivations, analytical designs, and focal ions limit understanding of salinization effects on freshwater animals","interactions":[],"lastModifiedDate":"2024-08-15T23:28:49.601515","indexId":"70256549","displayToPublicDate":"2023-06-01T18:19:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Global review reveals how disparate study motivations, analytical designs, and focal ions limit understanding of salinization effects on freshwater animals","docAbstract":"Global salinization of freshwaters is adversely affecting biotic communities and ecosystem processes. We reviewed six decades (1960–2020) of literature published on animal responses to increased salinities across different taxonomic and ecological contexts and identified knowledge gaps. From 585 journal articles, we characterized 5924 responses of mollusks, crustaceans, zooplankton, non-arthropod invertebrates (NAI), insects, fishes, and amphibians to salinization. Insects and fishes were the most studied taxa; Na+ and Cl− were the most studied ions−. Collectively, concentrations of the ions examined typically spanned five orders of magnitude. Species' invasiveness was a key motivation for studying mollusks, crustaceans, and fishes; threats of urbanization and road salts were key motivations for studying NAI, zooplankton, and amphibians. Laboratory studies were more common than field studies for most taxa. Focal life stages in laboratory studies varied widely but juveniles and adults were represented similarly in field studies. Studies of mollusks, NAI, and crustacean focused on adults; studies of zooplankton, insects, fishes, and amphibians focused on juveniles. Organismal- and population-level responses measuring solute uptake, internal chemistry, body condition, or ion concentrations predominated laboratory studies; population- and assemblage-level responses measuring abundance, spatial distribution, or assemblage composition predominated field studies. Negative responses to salinization predominated but positive and unimodal responses were apparent across all taxa and organizational levels. Key topics for further research include a) salinity responses by more taxa, b) responses to especially toxic ions (i.e., potassium, bicarbonate, sulfate, magnesium), c) mechanisms causing positive and unimodal responses, d) traits underpinning responses, e) effects transcending organizational levels, f) ion-specific response thresholds, and g) interactions between salinity and other stressors. Our review suggests inter-taxa variation in sensitivity to salinization reflects occurrence of certain biological traits, including gill-breathing, semi-permeable skin, multiple life stages, and limited mobility. We propose a traits-based framework to predict salinization sensitivity from shared traits. This evolutionary approach could inform management aimed at preventing or reducing adverse impacts of freshwater salinization.
Avian reproduction is a process that requires extensive energetic input by parents, particularly in pelagic seabirds. Parental infanticide has rarely been reported in pelagic seabirds, and its frequency among taxa is therefore difficult to determine. Using data from remote cameras, two cases of probable parental infanticide in Red-billed Tropicbirds Phaethon aethereus were captured on Sint Eustatius in the 2021–2022 breeding season. Both cases are presented with images collected from remote cameras as evidence. While appearing counterproductive, parental infanticide may provide an alternative reproduction strategy that favors lifetime reproductive success over short term success.
","language":"English","publisher":"Marine Ornithology","usgsCitation":"Danielson-Owczynsky, H., Madden, H., and Jodice, P.G., 2023, Parental infanticide by egg destruction in Red-billed Tropicbirds Phaethon aethereus on the Caribbean island of Sint Eustatius, v. 51, p. 261-264.","productDescription":"4 p.","startPage":"261","endPage":"264","ipdsId":"IP-142986","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":432214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":432213,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://www.marineornithology.org/article?rn=1543","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Sint Eustatius","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -62.948417049587604,\n 17.47103830623317\n ],\n [\n -62.94469941406847,\n 17.48607063683737\n ],\n [\n -62.95027712961014,\n 17.493081965059403\n ],\n [\n -62.970022237168905,\n 17.502171326137145\n ],\n [\n -62.97179686663267,\n 17.50113097404507\n ],\n [\n -62.98037200306398,\n 17.50761358142786\n ],\n [\n -62.97887198769814,\n 17.513853526816845\n ],\n [\n -62.9820022287205,\n 17.517753747929973\n ],\n [\n -62.989206557899905,\n 17.516285014310455\n ],\n [\n -62.99139741625572,\n 17.525155934946795\n ],\n [\n -62.99965464512201,\n 17.526236492388534\n ],\n [\n -63.001609276540904,\n 17.514637968270975\n ],\n [\n -63.000091975250285,\n 17.51370943845272\n ],\n [\n -63.00471344727944,\n 17.504110870698966\n ],\n [\n -62.99834159465455,\n 17.48801708555095\n ],\n [\n -62.988396678596345,\n 17.481539841887752\n ],\n [\n -62.98363611326876,\n 17.46879566952495\n ],\n [\n -62.972344622468256,\n 17.463240631776415\n ],\n [\n -62.95681196777767,\n 17.46450906367292\n ],\n [\n -62.948417049587604,\n 17.47103830623317\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Danielson-Owczynsky, Hailley","contributorId":340742,"corporation":false,"usgs":false,"family":"Danielson-Owczynsky","given":"Hailley","email":"","affiliations":[{"id":81655,"text":"Utrecht University, Utrecht, Netherlands","active":true,"usgs":false}],"preferred":false,"id":907502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madden, Hannah","contributorId":340743,"corporation":false,"usgs":false,"family":"Madden","given":"Hannah","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":907503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907504,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256465,"text":"70256465 - 2023 - Spatial and individual factors mediate the tissue burden of polycyclic aromatic hydrocarbons in adult and chick brown pelicans in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2024-08-05T21:14:44.014001","indexId":"70256465","displayToPublicDate":"2023-06-01T16:07:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10963,"text":"Frontiers in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and individual factors mediate the tissue burden of polycyclic aromatic hydrocarbons in adult and chick brown pelicans in the northern Gulf of Mexico","docAbstract":"The northern Gulf of Mexico supports a substantial level of oil and gas extraction in marine waters and experiences acute and chronic exposure to marine pollution events. The region also supports a diverse array of breeding and migratory seabirds that are exposed to these pollutants during foraging and other activities. Among the pollutants of highest concern within the region are polycyclic aromatic hydrocarbons (PAHs) which tend to be toxic, carcinogenic, mutagenic, or teratogenic. We assessed PAH loads in blood from adult brown pelicans and from feathers of adults and chicks of brown pelicans in relation to individual (e.g., body condition, sex) and spatial (e.g., breeding location within the Gulf, home range size, migration distance) factors. Of the 24 PAHs assessed, 17 occurred at least once among all samples. There were no PAHs found in chicks that were not also found in adults. Alkylated PAHs occurred more commonly and were measured at higher summed concentrations compared to parent PAHs in all samples, indicating that exposure to oil and/or byproducts of oil may have been a substantial source of PAH contamination for brown pelicans during this study. Within adults, PAHs were more likely to occur, and to increase in concentration, in blood samples of females compared to males, although no difference was found in feather samples. We also found that occurrence of and concentration of PAHs increased in adults that migrated longer distances. In adults and chicks, the background levels of oil and gas development within the region of the colony was not a consistent predictor of the presence of or concentration of PAHs. We also found correlations of PAHs with hematological and biochemical biomarkers that suggested compromised health. Our results indicate that both short- and long-term exposure (i.e., blood and feathers, respectively) are occurring for this species and that even nest-bound chicks can accumulate high levels of PAHs. Long-term tracking of PAHs, as well as an assessment of sublethal effects of PAHs on pelicans, could enhance our understanding of the persistence and effects of this contaminant in the northern Gulf as could increasing the breadth of species studied.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1185659","usgsCitation":"Jodice, P.G., Lamb, J., Satgé, Y., and Perkins, C., 2023, Spatial and individual factors mediate the tissue burden of polycyclic aromatic hydrocarbons in adult and chick brown pelicans in the northern Gulf of Mexico: Frontiers in Ecology and Conservation, v. 11, 1185659, 18 p., https://doi.org/10.3389/fevo.2023.1185659.","productDescription":"1185659, 18 p.","ipdsId":"IP-151107","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":443231,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1185659","text":"Publisher Index Page"},{"id":432212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98,\n 30.4\n ],\n [\n -98,\n 25\n ],\n [\n -82,\n 25\n ],\n [\n -82,\n 30.4\n ],\n [\n -98,\n 30.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamb, Juliet S.","contributorId":340736,"corporation":false,"usgs":false,"family":"Lamb","given":"Juliet S.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":907496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Satgé, Yvan G.","contributorId":340737,"corporation":false,"usgs":false,"family":"Satgé","given":"Yvan G.","affiliations":[{"id":81653,"text":"South Carolina Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":907497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perkins, Christopher","contributorId":340739,"corporation":false,"usgs":false,"family":"Perkins","given":"Christopher","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":907498,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241067,"text":"sir20215142 - 2023 - Groundwater residence times in glacial aquifers—A new general simulation-model approach compared to conventional inset models","interactions":[],"lastModifiedDate":"2026-02-23T18:29:12.962569","indexId":"sir20215142","displayToPublicDate":"2023-06-01T13:55:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5142","displayTitle":"Groundwater Residence Times in Glacial Aquifers—A New General Simulation-Model Approach Compared to Conventional Inset Models","title":"Groundwater residence times in glacial aquifers—A new general simulation-model approach compared to conventional inset models","docAbstract":"Groundwater is important as a drinking-water source and for maintaining base flow in rivers, streams, and lakes. Groundwater quality can be predicted, in part, by its residence time in the subsurface, but the residence-time distribution cannot be measured directly and must be inferred from models. This report compares residence-time distributions from four areas where groundwater flow and travel time were simulated with conventional simulation-inset models (IMs) and with a new automated model-construction method called general simulation models (GSMs). The comparison provides an opportunity to explore controls on travel time and improve the methods used in the creation of GSMs. These models can be useful for three main-use cases: (1) rapid testing of relationships that govern groundwater flow and age, (2) generation of consistent examples for training a machine-learning metamodel, and (3) serving as a starting point for more detailed models.
Comparison of the GSMs to IMs indicated a qualified pattern of agreement for residence-time distributions as indicated by the Nash-Sutcliffe efficiency and Spearman’s correlation coefficient. The agreement was best for the median values of the simulated residence times in young fractions of groundwater (defined as the fractions of groundwater in samples less than 65 years old) at the scale of the eight-digit hydrologic-unit code. Generally, the median values of the young fractions in the IMs were correlated with the median values from the GSMs. The relative trends across the four areas also were similar for the other residence-time metrics. The medians of residence-time metrics at finer scales show a fair degree of scatter. The GSM results compared most poorly for median travel times in the older fraction of groundwater (older than 65 years).
The GSM approach is intended as a flexible framework for developing models that can be useful individually as screening tools or collectively to support projects in statistical learning. Although one set of GSM algorithms was presented here, the approach can accommodate many types of data and also different categories of prior information. Comparison of GSMs and IMs suggests ways in which the GSMs, while remaining easy to construct and calibrate, can be improved for estimating groundwater travel times. IMs do not yield exact travel times, and matching GSMs to IMs does not guarantee an improvement; however, IMs provide a convenient benchmark against which to explore relations between physical characteristics of watersheds and the distribution of travel times within them.
This effort was undertaken as part of the National Water Quality Program of the U.S. Geological Survey to assist in determining the susceptibility of groundwater in glacial aquifers to a variety of natural and anthropogenic contaminants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215142","programNote":"National Water Quality Program","usgsCitation":"Starn, J.J., Kauffman, L.J., and Feinstein, D.T., 2023, Groundwater residence times in glacial aquifers—A new general simulation-model approach compared to conventional inset models: U.S. Geological Survey Scientific Investigations Report 2021–5142, 37 p., https://doi.org/10.3133/sir20215142.","productDescription":"Report: v, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112499","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":500447,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114759.htm","linkFileType":{"id":5,"text":"html"}},{"id":413862,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5142/images/"},{"id":413858,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5142/coverthb.jpg"},{"id":413859,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5142/sir20215142.pdf","text":"Report","size":"6.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5142"},{"id":413861,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5142/sir20215142.XML"},{"id":413863,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HS83JL","text":"USGS data release","linkHelpText":"MODPATH-NWT and MODPATH6 models used to compare a new general simulation model approach with a conventional inset model approach for groundwater residence time in glacial aquifers"},{"id":413860,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215142/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5142"}],"country":"United States","state":"Illinois, Indiana, Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.5,\n 46\n ],\n [\n -89,\n 46\n ],\n [\n -89,\n 41.5\n ],\n [\n -84.5,\n 41.5\n ],\n [\n -84.5,\n 46\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Digital flood-inundation maps for an 8-mile reach of Papillion Creek near Offutt Air Force Base, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Air Force, Offutt Air Force Base. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgages Papillion Creek at Fort Crook, Nebr. (station 06610795), and Papillion Creek at Harlan Lewis Road near La Platte, Nebr. (station 06610798). Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System database at https://doi.org/10.5066/F7P55KJN or from the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/.
Flood profiles were computed for the 8-mile stream reach by means of a one-dimensional step-backwater model. The model was calibrated by adjusting roughness coefficients to best represent the current (2022) stage-streamflow relation at the Papillion Creek at Fort Crook (station 06610795) streamgage.
The hydraulic model then was used to compute water-surface profiles for 157 scenarios using a combination of stage values in 1-foot (ft) stage intervals that ranged from 27 to 39 ft at the Papillion Creek at Fort Crook (station 06610795) streamgage and from 13.9 to 30.9 ft at the Papillion Creek at Harlan Lewis Road near La Platte (station 06610798) streamgage, as referenced to the local datums. The simulated water-surface profiles then were combined by a geographic information system with a digital elevation model, which had a 3.281-ft grid to delineate the area flooded and water depths at each stage. The availability of these flood-inundation maps, along with information regarding current stage from the USGS streamgages, can provide emergency management personnel and residents with information that is critical for flood response activities and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235054","collaboration":"Prepared in cooperation with the U.S. Air Force, Offutt Air Force Base","usgsCitation":"Strauch, K.R., and Hobza, C.M., 2023, Flood-inundation maps for an 8-mile reach of Papillion Creek near Offutt Air Force Base, Nebraska, 2022: U.S. Geological Survey Scientific Investigations Report 2023–5054, 12 p., https://doi.org/10.3133/sir20235054.","productDescription":"Report: vi, 12 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-135851","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":417490,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5054/images"},{"id":417652,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235054/full"},{"id":417492,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XQIXMN","text":"USGS data release","linkHelpText":"Flood inundation geospatial datasets for Papillion Creek near Offutt Air Force Base, Nebraska"},{"id":417489,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5054/sir20235054.XML"},{"id":417491,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":417486,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5054/sir20235054.pdf","text":"Report","size":"3.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5054"},{"id":417485,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5054/coverthb.jpg"},{"id":500933,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114763.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nebraska","otherGeospatial":"Offutt Air Force Base, Papillion Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.966667,\n 41.15\n ],\n [\n -95.966667,\n 41.05\n ],\n [\n -95.8667,\n 41.05\n ],\n [\n -95.8667,\n 41.15\n ],\n [\n -95.966667,\n 41.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Impoundments can drastically change the physical and biological characteristics of fluvial systems. Changes in the physical characteristics, such as reductions in flow, increased sediment deposition, and increased surface area, often influence the system’s biological components, including plant, macroinvertebrate, and fish assemblages. In addition to having direct effects on impounded waterbodies, impoundments can also have wide-ranging effects at the watershed scale, particularly on upstream tributary streams. The purpose of this study was to assess the magnitude of these effects. We analyzed historical data from 26 streams distributed across five sub-basins in the Bluff Hills region of the Yazoo Basin, MS, USA. All five major tributary rivers in this region are impounded by large (11,240–26,143 hectares) reservoirs for flood control. We compared fish assemblages in streams located upstream and downstream of the four reservoirs using PERMANOVA, and contrary to expectations, we found no significant differences between the upstream and downstream assemblages. We explore several possible explanations for this discrepancy and suggest that stream assemblage response to impoundment may be nuanced by the regional species pool, the history of stream conditions in the watershed, and the resistance of the streams to periodic disturbances.
","language":"English","publisher":"MDPI","doi":"10.3390/d15060728","usgsCitation":"Faucheux, N.M., Miranda, L.E., Taylor, J.M., and Farris, J.L., 2023, Impact of dams on stream fish diversity: A different result: Diversity, v. 15, no. 6, 728, 14 p., https://doi.org/10.3390/d15060728.","productDescription":"728, 14 p.","ipdsId":"IP-152946","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":443234,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d15060728","text":"Publisher Index Page"},{"id":432156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"eastern Yazoo River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.8,\n 35\n ],\n [\n -91,\n 35\n ],\n [\n -91,\n 33\n ],\n [\n -88.8,\n 33\n ],\n [\n -88.8,\n 35\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Faucheux, Nicky M.","contributorId":271194,"corporation":false,"usgs":false,"family":"Faucheux","given":"Nicky","email":"","middleInitial":"M.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":907448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Jason M.","contributorId":212809,"corporation":false,"usgs":false,"family":"Taylor","given":"Jason","email":"","middleInitial":"M.","affiliations":[{"id":38685,"text":"USDA, ARS Sedimentation Lab","active":true,"usgs":false}],"preferred":false,"id":907450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farris, Jerry L.","contributorId":340681,"corporation":false,"usgs":false,"family":"Farris","given":"Jerry","email":"","middleInitial":"L.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907451,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266183,"text":"70266183 - 2023 - Pilot study for invasive brown treesnake baiting in residential areas","interactions":[],"lastModifiedDate":"2025-04-29T15:28:10.63814","indexId":"70266183","displayToPublicDate":"2023-06-01T10:20:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Pilot study for invasive brown treesnake baiting in residential areas","docAbstract":"The nocturnal brown treesnake (Boiga irregularis; BTS) was accidentally introduced to the island of Guam, USA, in the Western Pacific in 1945. The BTS has spread throughout all terrestrial habitats, causing wildlife loss and economic damage. Several tools and techniques have been developed to locally reduce BTS numbers and prevent their spread to other islands. The common analgesic acetaminophen has been registered as a low-risk pesticide to manage BTS in non-residential areas. Prior to a more intensive toxic baiting campaign on Andersen Air Force Base, Guam, as part of a larger study to evaluate the effects of BTS control on native bird survival, we conducted a pilot study from May 18 to October 6, 2020, to assess the efficacy and safety of BTS baiting within a residential area. We administered large and small domesticated mouse (Mus musculus) and bird chick (Coturnix japonica and Gallus domesticus) nontoxic carrion baits (without acetaminophen) in bait stations to evaluate BTS and nontarget bait take rates, bait preferences, movements following nighttime bait uptakes, and interactions of humans and domestic animals with baits. We monitored baits with cameras and implanted them with radio-transmitters to verify the species taking the bait and to track BTS to their daytime sheltering locations. Successful BTS bait take rates were low at 20 of 482 baits (4.1%), as were nontarget bait take rates (4 baits; 0.8%). No preference among bait types was discernible, though power to detect differences was limited due to low overall uptake. All first daytime refugia were within vegetation except for 1 location on the roof of a house. No evidence of bait removal or human tampering was found at any of the bait stations. Based on our pilot study, there appeared to be little human or nontarget risk from acetaminophen baiting in this relatively uniform and sparsely vegetated residential area. Because most of the residential areas on Guam are much more variable, similar assessments within a broader diversity of residential areas may be advisable before promoting large-scale use of acetaminophen for managing BTS in close contact with human habitations.
","language":"English","publisher":"Berryman Institute","doi":"10.26077/24f0-f415","usgsCitation":"Siers, S.S., Mungaray, J., Barcinas, J., Calaor, J., Volsteadt, R.M., Kastner, M., Goetz, S.M., Nafus, M.G., and Hall, T., 2023, Pilot study for invasive brown treesnake baiting in residential areas: Human-Wildlife Interactions, v. 17, p. 255-270, https://doi.org/10.26077/24f0-f415.","productDescription":"16 p.","startPage":"255","endPage":"270","ipdsId":"IP-136666","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":485139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Andersen Air Force Base, Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.8913495244862,\n 13.582051190040545\n ],\n [\n 144.8913495244862,\n 13.544330986862349\n ],\n [\n 144.9383036027404,\n 13.544330986862349\n ],\n [\n 144.9383036027404,\n 13.582051190040545\n ],\n [\n 144.8913495244862,\n 13.582051190040545\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","noUsgsAuthors":false,"publicationDate":"2023-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Siers, Shane S","contributorId":228869,"corporation":false,"usgs":false,"family":"Siers","given":"Shane","email":"","middleInitial":"S","affiliations":[{"id":41523,"text":"USDA NWRC","active":true,"usgs":false}],"preferred":false,"id":934817,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mungaray, Juan-Carlos","contributorId":353955,"corporation":false,"usgs":false,"family":"Mungaray","given":"Juan-Carlos","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":934818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barcinas, Jordan I","contributorId":353956,"corporation":false,"usgs":false,"family":"Barcinas","given":"Jordan I","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":934819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calaor, Jeried E","contributorId":353957,"corporation":false,"usgs":false,"family":"Calaor","given":"Jeried E","affiliations":[{"id":54632,"text":"Research Corporation of the University of Guam","active":true,"usgs":false}],"preferred":false,"id":934820,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Volsteadt, Rachel M.","contributorId":257490,"corporation":false,"usgs":false,"family":"Volsteadt","given":"Rachel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":934821,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kastner, Martin","contributorId":293508,"corporation":false,"usgs":false,"family":"Kastner","given":"Martin","email":"","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":934822,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goetz, Scott Michael 0000-0002-8705-5316","orcid":"https://orcid.org/0000-0002-8705-5316","contributorId":228868,"corporation":false,"usgs":true,"family":"Goetz","given":"Scott","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934823,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934824,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hall, Thomas C","contributorId":353958,"corporation":false,"usgs":false,"family":"Hall","given":"Thomas C","affiliations":[{"id":84534,"text":"USDA APHIS Wildlife Services Operational Support Staff","active":true,"usgs":false}],"preferred":false,"id":934825,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70268746,"text":"70268746 - 2023 - Controlling invasive grass carp in Lake Erie","interactions":[],"lastModifiedDate":"2025-07-07T15:22:06.772904","indexId":"70268746","displayToPublicDate":"2023-06-01T10:20:31","publicationYear":"2023","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":21988,"text":"Newswave","active":true,"publicationSubtype":{"id":30}},"title":"Controlling invasive grass carp in Lake Erie","docAbstract":"No abstract available.
","language":"English","publisher":"Department of Interior","usgsCitation":"Wamboldt, J.J., Acre, M.R., Mueller, A.T., Nathan, L., Weimer, E., Calfee, R.D., and Young, R., 2023, Controlling invasive grass carp in Lake Erie: Newswave, no. Summer.","productDescription":"1 p.","startPage":"9","ipdsId":"IP-139089","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":491649,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://edit.doi.gov/sites/doi.gov/files/nw-summer2023.pdf"},{"id":491737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"Summer","noUsgsAuthors":false,"publicationDate":"2023-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wamboldt, James J. 0000-0003-3043-5198","orcid":"https://orcid.org/0000-0003-3043-5198","contributorId":219060,"corporation":false,"usgs":true,"family":"Wamboldt","given":"James","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":941830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Acre, Matthew Ross 0000-0002-5417-9523","orcid":"https://orcid.org/0000-0002-5417-9523","contributorId":268034,"corporation":false,"usgs":true,"family":"Acre","given":"Matthew","email":"","middleInitial":"Ross","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":941831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller, Andrew T. 0000-0001-8566-8023","orcid":"https://orcid.org/0000-0001-8566-8023","contributorId":238278,"corporation":false,"usgs":true,"family":"Mueller","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":941832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nathan, Lucas","contributorId":236997,"corporation":false,"usgs":false,"family":"Nathan","given":"Lucas","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":941833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weimer, Eric","contributorId":244720,"corporation":false,"usgs":false,"family":"Weimer","given":"Eric","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":941834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":941835,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Young, Ryan","contributorId":272036,"corporation":false,"usgs":false,"family":"Young","given":"Ryan","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":941836,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248413,"text":"70248413 - 2023 - Coastal acidification trends and controls in a subtropical estuary, Tampa Bay, Florida USA","interactions":[],"lastModifiedDate":"2023-09-13T13:17:10.1477","indexId":"70248413","displayToPublicDate":"2023-06-01T09:32:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1672,"text":"Florida Scientist","active":true,"publicationSubtype":{"id":10}},"title":"Coastal acidification trends and controls in a subtropical estuary, Tampa Bay, Florida USA","docAbstract":"Many coastal estuaries have experienced declines in pH over the past few decades due to coastal acidification. However, mean monthly water column pH values (collected during daylight hours) have increased in Tampa Bay, Florida over recent decades concurrent with seagrass recovery. We measured changes in carbonate system and water quality variables in Tampa Bay and the near-coastal Gulf of Mexico environment to quantify diurnal to seasonal trends, drivers, and controls of carbonate chemistry; identify exposure periods to low pH conditions; and to examine the potential for seagrasses to buffer acidification in Tampa Bay. Autonomous sensor packages deployed in Tampa Bay and the Gulf of Mexico from December 2017 to June 2020 recorded hourly measurements of seawater temperature, salinity, pressure, pHT (total scale), carbon dioxide (pCO2), dissolved oxygen (DO), and photosynthetically active radiation. Results indicated strong temperature and biological influence on DO, pHT, and pCO2 in Tampa Bay during the dry season, and only weak to moderate correlation of these variables with temperature and salinity during the wet season. Strong influence from biological processes during the wet season was coincident with spring-to-summer periods of maximum seagrass growth rates. Gulf of Mexico results indicated higher pHT and DO, and lower pCO2 than in Tampa Bay, with similar but attenuated seasonal variation. Results suggest potential benefits from seagrass photosynthesis increasing pHT, DO, and decreasing pCO2 in Tampa Bay, and delivery of high pHT, low pCO2 Gulf of Mexico water to Tampa Bay during flood tides. Approximately 30% of pHT and pCO2 data records collected in Tampa Bay were below pHT 7.900 and above pCO2 of 600 μatm, primarily during the wet season, indicating potential for dissolution of carbonate sediments that may also help buffer acidification conditions in Tampa.
","language":"English","publisher":"Florida Academy of Sciences","usgsCitation":"Yates, K.K., Moore, C., Lemon, M.K., Moyer, R.P., Tomasko, D.A., Masserini, R., and Sherwood, E.T., 2023, Coastal acidification trends and controls in a subtropical estuary, Tampa Bay, Florida USA: Florida Scientist, v. 86, no. 2, p. 214-228.","productDescription":"15 p.","startPage":"214","endPage":"228","ipdsId":"IP-122626","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":420720,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Gulf of Mexico, Tampa Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.34603301937987,\n 28.090560342743913\n ],\n [\n -83.31697141493213,\n 28.090560342743913\n ],\n [\n -83.31697141493213,\n 27.425867242036304\n ],\n [\n -82.34603301937987,\n 27.425867242036304\n ],\n [\n -82.34603301937987,\n 28.090560342743913\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"86","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yates, Kimberly K. 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":214349,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":882816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Christopher 0000-0003-3210-4878 csmoore@usgs.gov","orcid":"https://orcid.org/0000-0003-3210-4878","contributorId":149727,"corporation":false,"usgs":true,"family":"Moore","given":"Christopher","email":"csmoore@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":882884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lemon, Mitchell K","contributorId":329645,"corporation":false,"usgs":false,"family":"Lemon","given":"Mitchell","email":"","middleInitial":"K","affiliations":[{"id":33877,"text":"CNTS","active":true,"usgs":false}],"preferred":false,"id":882885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moyer, Ryan P.","contributorId":198993,"corporation":false,"usgs":false,"family":"Moyer","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":13560,"text":"Florida Fish and Wildlife Conservation Commission, Eustis, FL","active":true,"usgs":false}],"preferred":false,"id":882817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tomasko, David A.","contributorId":172728,"corporation":false,"usgs":false,"family":"Tomasko","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":882818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Masserini, R. 0000-0002-2841-1819","orcid":"https://orcid.org/0000-0002-2841-1819","contributorId":329644,"corporation":false,"usgs":false,"family":"Masserini","given":"R.","email":"","affiliations":[{"id":78677,"text":"University of Tampa","active":true,"usgs":false}],"preferred":false,"id":882819,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sherwood, Edward T. 0000-0001-5330-302X","orcid":"https://orcid.org/0000-0001-5330-302X","contributorId":150472,"corporation":false,"usgs":false,"family":"Sherwood","given":"Edward","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":882820,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244080,"text":"70244080 - 2023 - Establishing big sagebrush seedlings on the Colorado Plateau","interactions":[],"lastModifiedDate":"2023-06-01T14:15:44.894946","indexId":"70244080","displayToPublicDate":"2023-06-01T09:09:40","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Establishing big sagebrush seedlings on the Colorado Plateau","docAbstract":"Factors such as soil type and precipitation vary across rangeland landscapes, and these factors affect restoration outcomes and ultimately mean that “one size fits all” management strategies are not effective across large, complex landscapes. Big sagebrush (Artemisia tridentata) is a foundational rangeland species that is important to wildlife habitat across the western U.S. On the Colorado Plateau, sagebrush is important browse for ungulates, such as mule deer and pronghorn, which motivates a great deal of restoration effort. However, most scientific knowledge of big sagebrush comes from the Great Basin, and we know much less about how to restore sagebrush on the Colorado Plateau, where soils and precipitation patterns are different and conditions are warmer and drier. This fact sheet describes research about establishing and restoring sagebrush seedlings on the Colorado Plateau.
","language":"English","publisher":"Utah State University Extension","usgsCitation":"Veblen, K.E., Thacker, E., Larese-Casanova, M., Nehring, K.C., Duniway, M.C., and Brungard, C.C., 2023, Establishing big sagebrush seedlings on the Colorado Plateau, 4 p.","productDescription":"4 p.","ipdsId":"IP-151998","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":417647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417628,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.usu.edu/extension_curall/2339/"}],"country":"United States","state":"Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.32812794769814,\n 38.79667654480113\n ],\n [\n -110.32812794769814,\n 37.40419615629527\n ],\n [\n -109.08137175800505,\n 37.40419615629527\n ],\n [\n -109.08137175800505,\n 38.79667654480113\n ],\n [\n -110.32812794769814,\n 38.79667654480113\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Veblen, Kari E.","contributorId":76872,"corporation":false,"usgs":false,"family":"Veblen","given":"Kari","email":"","middleInitial":"E.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":874426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thacker, Eric","contributorId":268205,"corporation":false,"usgs":false,"family":"Thacker","given":"Eric","email":"","affiliations":[{"id":55594,"text":"Department of Wildland Resources and the Ecology Center, Utah State University, 5230 Old Main Hill, Logan, UT 84322","active":true,"usgs":false}],"preferred":false,"id":874427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larese-Casanova, Mark","contributorId":306023,"corporation":false,"usgs":false,"family":"Larese-Casanova","given":"Mark","email":"","affiliations":[{"id":66350,"text":"Utah State University Dept. of Wildland Resources","active":true,"usgs":false}],"preferred":false,"id":874428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nehring, Kyle C.","contributorId":210415,"corporation":false,"usgs":false,"family":"Nehring","given":"Kyle","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":874474,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":874429,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brungard, Colby C.","contributorId":248822,"corporation":false,"usgs":false,"family":"Brungard","given":"Colby","email":"","middleInitial":"C.","affiliations":[{"id":50029,"text":"New Mexico State University, Department of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":874430,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260395,"text":"70260395 - 2023 - Modeling, mapping, and measuring the risk of freshwater invasive species across Alaska","interactions":[],"lastModifiedDate":"2024-10-31T13:49:21.623893","indexId":"70260395","displayToPublicDate":"2023-06-01T08:39:58","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Modeling, mapping, and measuring the risk of freshwater invasive species across Alaska","docAbstract":"Freshwater ecosystems of the Alaskan Arctic and Subarctic provide resources that are culturally, ecologically, and economically invaluable. Presently, these regions are relatively free of the impacts from invasive species compared to southern latitudes. To date, there have been relatively few verified introductions of aquatic invasive species (AIS) to freshwater ecosystems in Alaska. The expanding list and distribution of AIS has led to significant negative ecological and economic impacts (e.g., waterweed Elodea nuttalli; E. canadensis and northern pike Esox Lucius introduced outside its native range in Alaska). Escalating human activity across Alaskan lands and waters, coupled with rapidly shifting environmental conditions, increases the potential for new species introductions and subsequent establishment. Creating a proactive framework for well-informed decision-making and action can improve the effectiveness of prevention efforts and bolster decision support tools that help resource managers direct limited resources. Prioritizing AIS that may be introduced and become established, as well as the locations at highest risk of invasion, is foundational to building a proactive invasive species management framework in Alaska.
This project sought to identify and prioritize AIS known to be invasive in the contiguous United States, evaluate current and future habitat suitability for AIS in Alaska, and assess potential for AIS to be transported to habitats across Alaska, utilizing similar assessment methods as implemented for Bering Sea marine invasive species and non-native plants in Alaska. To accomplish this goal, the objectives of the project were to: 1) develop a formal ranked list of potential AIS to freshwater systems of Alaska; 2) assess the level of establishment risk for potential AIS by developing habitat suitability models for waterbodies across Alaska; and 3), identify potential pathways and specific vectors for high-risk AIS to invade Alaska and develop a framework for how vector analysis will be completed to understand transport risk. Overall, our goal is horizon scanning which is defined by Roy et al. (2019) as “a systematic examination of potential threats and opportunities, within a given context, and likely future developments, which are at the margin of current thinking and planning.” The scans include pathway analyses and risk screening of species present at pathway origin points, with a focus on identifying species at high risk of being introduced, becoming established, spreading, and causing harm.
We refined a list of 28 AIS from a list of hundreds based on characterizations of species’ invasiveness and species’ proximity to Alaska (USGS 2020; GBIF 2022). Next, we evaluated the relative invasiveness of individual species to create an initial AIS ranking. We sought to characterize habitat suitability of AIS by selecting variables that were continental in scale, covering North America to include Alaska as well as the lower 48 states comparing natural discharge, sub-basin average terrain slope (degrees), average silt fraction, average organic carbon, lithological class, and human footprint in sub-basin in 2009. We estimated AIS habitat suitability across the entire state of Alaska using the physiological tolerances of the AIS (Appendix 2). We also evaluated pathways and vectors for the introduction of AIS (Appendix 2). Many pathways and vectors considered did not meet the criteria for Alaska or freshwater systems.
Of the 28 ranked species that we categorized as very high, high, and moderate levels of invasiveness; all three risk groups included fish and mollusks (Appendix 2). One commonality of the very high-invasiveness-ranked species was the availability of Ecological Risk Screening Summary documents (USFWS, 2022) produced by U.S. Fish and Wildlife Service (USFWS), except for the goldfish (Carassius auratus) and the New Zealand mudsnail (Potamopyrgus antipodarum). The Ecological Risk Screening Summary is now available for New Zealand mudsnails. In general, fish species often ranked very high or high in invasiveness and included sportfish and aquarium fish, suggesting the importance of pathways such as aquarium trade, fishing industry, intentional (but illegal) introductions of sportfishes and aquarium fishes for establishment. The technique we used for habitat suitability models necessitated aquatic environmental datasets that were continental in scale, which was often interpolated from very coarse resolution source data layers, particularly in Alaska. Better spatial data representing aquatic environments would likely improve this approach. While the lack of introductions in Alaska and nearby provinces and states is encouraging, the lack of occurrence data for the focal species also created complications for habitat suitability modeling. Despite the challenges, the habitat suitability models indicated limited suitability for warmwater species while some species, such as Brook trout (Salvelinus fontinalis), have high habitat suitability across Alaska no matter what threshold approach is taken. Some environmental predictors were more important than others. Specifically, the most important predictor variable, ‘frost free days,’ was critical for 15 out of 28 species as expected due to harsh winter conditions in Arctic and Subarctic regions. The second most important predictor was ‘subbasin land surface runoff’, a variable that indicates the amount of discharge and runoff, while the third most important predictor was ‘snow cover’ another indication of winter conditions.
Overall, the ability to understand the effect of future climate scenarios on the establishment of AIS was challenging. A detailed dataset of freshwater temperatures and water chemistry (e.g., pH, calcium) would greatly improve the ability to predict invasiveness of freshwater species to Alaska’s ecosystems on a regional basis. Future studies may benefit from a more focused geographic scope examining a group of subbasins or a regional basin rather than the entire state. These drainages could be selected based upon the mostly likely locations of introduction pathways. The two most prevalent pathway risks for AIS are in-state transfer and stowaways/contaminants. Although there are examples of introductions from other pathways, the risk is somewhat mitigated by Alaska’s climate and regulations. However, variable application of protocols for inspection and cleaning of fishing gear, watercraft, and other similar items while traveling into Alaska as well as transferring from waterbody to waterbody within the state creates a substantial risk in introducing invasive species. We plot cumulative invasive vulnerability for all subbasins and for the top 10% of subbasins (Appendix 3).
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to foster innovative thinking in Earth system science through collaborative analysis and synthesis of existing data and information. The Powell Center supports working groups that address some of the most pressing and complex questions facing society, such as climate change, biodiversity loss, water scarcity, natural hazards, and human-environment interactions.\n\nIn this newsletter, we highlight some of the recent activities of the Powell Center and its working groups.","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Baron, J., and Bingham, D.J., 2023, John Wesley Powell Center for Analysis and Synthesis Newsletter, volume 7, issue 1: John Wesley Powell Center for Analysis and Synthesis Newsletter, 2 p.","productDescription":"2 p.","ipdsId":"IP-149901","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":417908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417907,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.usgs.gov/media/files/powell-center-newsletter-v-7-no-1"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Liford, Amanda N. 0000-0002-6992-2543","orcid":"https://orcid.org/0000-0002-6992-2543","contributorId":257671,"corporation":false,"usgs":true,"family":"Liford","given":"Amanda","email":"","middleInitial":"N.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":873671,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":873669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bingham, Demi Jasmine 0009-0001-9597-8882","orcid":"https://orcid.org/0009-0001-9597-8882","contributorId":305721,"corporation":false,"usgs":true,"family":"Bingham","given":"Demi","email":"","middleInitial":"Jasmine","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":873670,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70244082,"text":"70244082 - 2023 - Impacts and uncertainties of climate-induced changes in watershed inputs on estuarine hypoxia","interactions":[],"lastModifiedDate":"2023-06-01T13:06:59.504336","indexId":"70244082","displayToPublicDate":"2023-06-01T07:57:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Impacts and uncertainties of climate-induced changes in watershed inputs on estuarine hypoxia","docAbstract":"Multiple climate-driven stressors, including warming and increased nutrient delivery, are exacerbating hypoxia in coastal marine environments. Within coastal watersheds, environmental managers are particularly interested in climate impacts on terrestrial processes, which may undermine the efficacy of management actions designed to reduce eutrophication and consequent low-oxygen conditions in receiving coastal waters. However, substantial uncertainty accompanies the application of Earth system model (ESM) projections to a regional modeling framework when quantifying future changes to estuarine hypoxia due to climate change. In this study, two downscaling methods are applied to multiple ESMs and used to force two independent watershed models for Chesapeake Bay, a large coastal-plain estuary of the eastern United States. The projected watershed changes are then used to force a coupled 3-D hydrodynamic–biogeochemical estuarine model to project climate impacts on hypoxia, with particular emphasis on projection uncertainties. Results indicate that all three factors (ESM, downscaling method, and watershed model) are found to contribute substantially to the uncertainty associated with future hypoxia, with the choice of ESM being the largest contributor. Overall, in the absence of management actions, there is a high likelihood that climate change impacts on the watershed will expand low-oxygen conditions by 2050 relative to a 1990s baseline period; however, the projected increase in hypoxia is quite small (4 %) because only climate-induced changes in watershed inputs are considered and not those on the estuary itself. Results also demonstrate that the attainment of established nutrient reduction targets will reduce annual hypoxia by about 50 % compared to the 1990s. Given these estimates, it is virtually certain that fully implemented management actions reducing excess nutrient loadings will outweigh hypoxia increases driven by climate-induced changes in terrestrial runoff.
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Individual tree growth response phenotypes appeared to be linked to genotypic variation in climate-associated loci, suggesting that some genotypes can take better advantage of local climatic conditions than others. We speculate that reduced snowpack during the 2012 to 2015 drought years may have lengthened the growing season while retaining sufficient moisture to maintain growth at most study sites. Growth responses may differ under future warming, however, particularly if drought severity increases and modifies interactions with pests and pathogens.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10072","usgsCitation":"van Mantgem, P., Milano, E.R., Dudney, J., Nesmith, J., Vandergast, A.G., and Zald, H.S., 2023, Growth, drought response, and climate-associated genomic structure in whitebark pine in the Sierra Nevada of California: Ecology and Evolution, v. 13, no. 5, e10072, 20 p., https://doi.org/10.1002/ece3.10072.","productDescription":"e10072, 20 p.","ipdsId":"IP-128278","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":443243,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10072","text":"Publisher Index Page"},{"id":435298,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EKZR4C","text":"USGS data release","linkHelpText":"Growth, Drought Response, and Genomic Structure Data for Whitebark Pine in the Sierra Nevada of California (ver. 2.0, May 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