Anthropogenic inputs into the environment may serve as sources of antimicrobial resistant bacteria and alter the ecology and population dynamics of synanthropic wild animals by providing supplemental forage. In this study, we used a combination of phenotypic and genomic approaches to characterize antimicrobial resistant indicator bacteria, animal telemetry to describe host movement patterns, and a novel modeling approach to combine information from these diverse data streams to investigate the acquisition and long-distance dispersal of antimicrobial resistant bacteria by landfill-foraging gulls. Our results provide evidence that gulls acquire antimicrobial resistant bacteria from anthropogenic sources, which they may subsequently disperse across and between continents via migratory movements. Furthermore, we introduce a flexible modeling framework to estimate the relative dispersal risk of antimicrobial resistant bacteria in western North America and adjacent areas within East Asia, which may be adapted to provide information on the risk of dissemination of other organisms and pathogens maintained by wildlife through space and time.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.144551","usgsCitation":"Ahlstrom, C., van Toor, M.L., Woksepp, H., Chandler, J.C., Reed, J., Reeves, A.B., Waldenström, J., Franklin, A.B., Douglas, D.C., Bonnedahl, J., and Ramey, A.M., 2021, Evidence for continental-scale dispersal of antimicrobial resistant bacteria by landfill-foraging gulls, v. 764, 144551, 10 p., https://doi.org/10.1016/j.scitotenv.2020.144551.","productDescription":"144551, 10 p.","ipdsId":"IP-118432","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":454059,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.unl.edu/icwdm_usdanwrc/2401","text":"Publisher Index Page"},{"id":436609,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U0XGI3","text":"USGS data release","linkHelpText":"Data for Continental-Scale Dispersal of Antimicrobial Resistant 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Alaska","interactions":[],"lastModifiedDate":"2021-02-17T22:12:21.749487","indexId":"70217175","displayToPublicDate":"2020-12-17T08:18:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Identification of seasonal streamflow regimes and streamflow drivers for daily and peak flows in Alaska","docAbstract":"Alaska is among northern high‐latitude regions where accelerated climate change is expected to impact streamflow properties, including seasonality and primary flow drivers. Evaluating changes to streamflow, including flood characteristics, across this large and diverse environment can be improved by identifying the distribution and influence of flow drivers. Using metrics of mean monthly streamflow data from 253 streamgages, seasonal flow regimes were clustered to guide identification of seasonal‐flow drivers and form hydrologic groups for identification of peak‐flow populations. Nine seasonally distinct subclasses described variability within three classes dominated by (mostly fall) rainfall, (spring) snowmelt, and (summer) high‐elevation melt. The most glacierized basins exclusively grouped into high‐elevation melt subclasses, and less glacierized basins sometimes exhibited seasonal patterns aligned with rainfall‐ and snowmelt‐dominated regimes. Peak‐flow populations varied by subclass from dominant rainfall or dominant snowmelt to mixed rainfall‐snowmelt or mixed rainfall, snowmelt, and high‐elevation melt. Within subclasses, rainfall generated higher mean peak flows (relative to mean annual flow) than snowmelt or high‐elevation melt. Seasonal flow regimes showed clear but complex associations with basin characteristics, primarily elevation and winter temperature, and with geographic location. These dependencies provided elevation‐based analogies for changes associated with warming and insights for seasonal flow regime prediction and hydrologic region delineation. These results provide a spatially comprehensive perspective on seasonal streamflow drivers across Alaska from historical data and serve as an important historical basis for analysis.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR028425","usgsCitation":"Curran, J.H., and Biles, F.E., 2021, Identification of seasonal streamflow regimes and streamflow drivers for daily and peak flows in Alaska: Water Resources Research, v. 57, no. 2, ee2020WR028425, https://doi.org/10.1029/2020WR028425.","productDescription":"ee2020WR028425","ipdsId":"IP-119457","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":436611,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13TMJUP","text":"USGS data release","linkHelpText":"Selected Basin Boundaries for USGS Streamgages in Alaska through 2019"},{"id":436610,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90K2Y4R","text":"USGS data release","linkHelpText":"Streamgage Attributes, Basin Characteristics, and Seasonal Flow Regimes, Selected Streamgages in Alaska, 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Janet H. 0000-0002-3899-6275 jcurran@usgs.gov","orcid":"https://orcid.org/0000-0002-3899-6275","contributorId":690,"corporation":false,"usgs":true,"family":"Curran","given":"Janet","email":"jcurran@usgs.gov","middleInitial":"H.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":807827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biles, Frances E. 0000-0002-7298-2811","orcid":"https://orcid.org/0000-0002-7298-2811","contributorId":247517,"corporation":false,"usgs":false,"family":"Biles","given":"Frances","email":"","middleInitial":"E.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":807828,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70230052,"text":"70230052 - 2021 - Evidence of post-breeding prospecting in a long-distance migrant.","interactions":[],"lastModifiedDate":"2022-03-28T13:59:59.515137","indexId":"70230052","displayToPublicDate":"2020-12-16T08:52:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of post-breeding prospecting in a long-distance migrant.","docAbstract":"Large, severe fires are becoming more frequent in many forest types across the western United States and have resulted in tree mortality across tens of thousands of hectares. Conifer regeneration in these areas is limited because seeds must travel long distances to reach the interior of large burned patches and establishment is jeopardized by increasingly hot and dry conditions. To better inform postfire management in low elevation forests of California, USA, we collected 5‐year postfire recovery data from 1,234 study plots in 19 wildfires that burned from 2004–2012 and 18 years of seed production data from 216 seed fall traps (1999–2017). We used this data in conjunction with spatially extensive estimates of climate, topography, forest composition, and burn severity to construct taxon‐specific, spatially explicit models of conifer regeneration that incorporate estimated climate conditions and seed availability during postfire recovery windows. We found that after accounting for other predictors both postfire and historical precipitation were strong predictors of regeneration, suggesting that both direct effects of postfire moisture conditions and biological inertia from historical climate may play a role in regeneration. Alternatively, postfire regeneration may simply be driven by postfire climate and apparent relationships with historical climate could be spurious. The estimated sensitivity of regeneration to postfire seed availability was strongest in firs and all conifers combined and weaker in pines. Seed production exhibited high temporal variability with seed production varying by over two orders of magnitude among years. Our models indicate that during droughts postfire conifer regeneration declines most substantially in low‐to‐moderate elevation forests. These findings enhance our mechanistic understanding of forecasted and historically documented shifts in the distribution of trees.
In this study, we revisit the three largest historical earthquakes in California—the 1857 Fort Tejon, 1872 Owens Valley, and 1906 San Francisco earthquakes—to review their published moment magnitudes, and compare their estimated shaking distributions with predictions using modern ground‐motion models (GMMs) and ground‐motion intensity conversion equations. Currently accepted moment magnitude estimates for the three earthquakes are 7.9, 7.6, and 7.8, respectively. We first consider the extent to which the intensity distributions of all three earthquakes are consistent with a moment magnitude toward the upper end of the estimated range. We then apply a GMM‐based method to estimate the magnitudes of large historical earthquakes. The intensity distribution of the 1857 earthquake is too sparse to provide a strong constraint on magnitude. For the 1872 earthquake, consideration of all available constraints suggests that it was a high stress‐drop event, with a magnitude on the higher end of the range implied by scaling relationships, that is, higher than moment magnitude 7.6. For the 1906 earthquake, based on our analysis of regional intensities and the detailed intensity distribution in San Francisco, along with other available constraints, we estimate a preferred moment magnitude of 7.9, consistent with the published estimate based on geodetic and instrumental seismic data. These results suggest that, although there can be a tendency for historical earthquake magnitudes to be overestimated, the accepted catalog magnitudes of California’s largest historical earthquakes could be too low. Given the uncertainties of the magnitude estimates, the seismic moment release rate between 1850 and 2019 could have been either higher or lower than the average over millennial time scales. It is further not possible to reject the hypothesis that California seismicity is described by an untruncated Gutenberg–Richter distribution with a
Campsite impacts in protected natural areas are most effectively minimized by a containment strategy that focuses use on a limited number of sustainable campsites that spatially concentrate camping activities. This research employs spatial autoregressive (SAR) modeling to evaluate the relative influence of use-related, environmental, and managerial factors on two salient measures of campsite impact. Relational analyses examined numerous field-collected and GIS-derived indicators, including several new indicators calculated using high-resolution Light Detection and Ranging (LiDAR) topographic data to evaluate the influence of terrain characteristics on the dependent variables.
Chosen variables in the best SAR models explained 35% and 30% of the variation in campsite size and area of vegetation loss on campsites. Results identified three key indicators that managers can manipulate to enhance the sustainability of campsites: campsite type, and terrain characteristics relating to landform slope and topographic roughness. Results support indirect management methods that rely on the location, design, construction, and maintenance of campsites, instead of direct regulations that restrict visitation or visitor freedoms. As visitation pressures continue to increase, this knowledge can be applied to select and promote the use of more ecologically sustainable campsites.
Dryland ecosystems play an important role in the global carbon cycle, including regulating the inter-annual global carbon sink. Dynamic global vegetation models (DGVMs) are essential tools that can help us better understand carbon cycling in different ecosystems. Currently, there is limited knowledge of the performance of these models in drylands partly due to characterizing the heterogeneity of the vegetation and hydrometeorological conditions. The aim of this study is to evaluate the performance of a DGVM for drylands to facilitate improved understanding of gross primary production (GPP) as one of the important components of the carbon cycle. We performed a sensitivity analysis and calibrated the Ecosystem Demography (EDv2.2) DGVM to simulate GPP in a dryland watershed (Reynolds Creek Experimental Watershed, Idaho) in the western US for the years 2000-2017. GPP capacity and activity were investigated by comparing model simulations with GPP estimated from eddy covariance data (available from 2015-2017) and remote sensing products (2000-2017). Our results show good performance of EDv2.2 at daily timesteps (
Stream temperature data are useful for deciphering watershed processes important for aquatic ecosystems. Accurately extracting signal trends from stream temperature is essential for predicting responses of environmental and ecological indicators to change. Missing data periods are common for various reasons, and pose a challenge for scientists using temperature signal analysis to support stream research and ecological management objectives. However, the sensitivity of estimated temperature signal patterns to missing data has not been thoroughly evaluated, despite the potentially large impact on interpretation. In this study, we explored the effects of simulated missing daily data on the characterization of annual water temperature signals measured at headwater sites in the Pacific Northwest and Mid-Atlantic regions of the USA. For each site, we used linear regressions of sine-waves fitted to complete (365-d) and partial (7–357 consecutive missing data points) annual datasets of daily mean water temperature and computed three thermal parameters (mean, phase, and amplitude), which together can indicate thermally and ecologically influential watershed processes (e.g., depth and magnitude of groundwater discharge). Expected values (derived from complete datasets) ranged from 7.0 to 12.6 °C, 205 to 254 d, and 1.9 to 9.5 °C for annual mean, phase, and amplitude, respectively. While annual phase and amplitude could be accurately estimated (i.e., within 95–99% confidence intervals of expected values) with up to approximately two months of consecutively missing data, annual mean temperature required more complete datasets. We found that datasets with less than seven weeks of consecutively missing data enabled estimation of all annual signal parameters with reasonable accuracy (>75% probability of being within the 95–99% confidence intervals of expected values). Imputation of missing data expanded this range to approximately 20 weeks, with the greatest improvements in parameter estimation between 9 and 27 weeks of imputed missing data. However, caution should be exercised when applying this technique. For example, imputation improved the accuracy of parameter estimation for most sites, but accuracy decreased for some sites exhibiting strong groundwater influence. The timing of consecutive missing data points within a year had inconsistent effects on annual thermal parameter estimates among regions, years, and individual parameters. Utilizing sites with more than approximately seven consecutive weeks of missing data or 20 weeks of imputed data increases the probability of mischaracterization of annual stream thermal regimes. Understanding this limitation is vital for identifying the potential of streams to serve as climate refugia for ecological indicator species and effective future management of stream systems.
As part of the update of the 2018 National Seismic Hazard Model (NSHM) for the conterminous United States (CONUS), new ground motion and site effect models for the central and eastern United States were incorporated, as well as basin depths from local seismic velocity models in four western US (WUS) urban areas. These additions allow us, for the first time, to calculate probabilistic seismic hazard curves for an expanded set of spectral periods (0.01 to 10 s) and site classes (VS30 = 150 to 1500 m/s) for the CONUS, as well as account for amplification of long-period ground motions in deep sedimentary basins in the Los Angeles, San Francisco Bay, Seattle, and Salt Lake City areas. Two sets of 2018 NSHM hazard data (hazard curves and uniform-hazard ground motions) are available: (1) 0.05°-latitude-by-0.05°-longitude gridded data for the CONUS and (2) higher resolution 0.01°-latitude-by-0.01°-longitude gridded data for the four WUS basins. Both sets of data contain basin effects in the WUS deep sedimentary basins. Uniform-hazard ground motion data are interpolated for 2, 5, and 10% probability of exceedance in 50 years from the hazard curves. The gridded data for the hazard curves and uniform-hazard ground motions, for all periods and site classes, are available for download at the U.S. Geological Survey ScienceBase Catalog (https://doi.org/10.5066/P9RQMREV). The design ground motions derived from the hazard curves have been accepted by the Building Seismic Safety Council for adoption in the 2020 National Earthquake Hazard Reduction Program Recommended Seismic Provisions.
","language":"English","publisher":"Sage Journals","doi":"10.1177/8755293020970979","usgsCitation":"Shumway, A., Petersen, M.D., Powers, P.M., Rezaeian, S., Rukstales, K.S., and Clayton, B., 2021, The 2018 update of the US National Seismic Hazard Model: Additional period and site class data: Earthquake Spectra, v. 37, no. 2, p. 1145-1161, https://doi.org/10.1177/8755293020970979.","productDescription":"17 p.","startPage":"1145","endPage":"1161","ipdsId":"IP-121790","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":385635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Utah, Washington","city":"San Francisco, Los Angeles, Seattle, Salt Lake City","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": 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mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":815625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":815626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 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bclayton@usgs.gov","orcid":"https://orcid.org/0000-0003-0502-7184","contributorId":197196,"corporation":false,"usgs":true,"family":"Clayton","given":"Brandon","email":"bclayton@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":815629,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216892,"text":"70216892 - 2021 - The impact of ventilation patterns on calcite dissolution rates within karst conduits","interactions":[],"lastModifiedDate":"2020-12-30T14:53:23.957547","indexId":"70216892","displayToPublicDate":"2020-12-10T08:47:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"The impact of ventilation patterns on calcite dissolution rates within karst conduits","docAbstract":"Erosion rates in streams vary dramatically over time, as differences in streamflow and sediment load enhance or inhibit erosion processes. Within cave streams, and other bedrock channels incising soluble rocks, changes in water chemistry are an important factor in determining how erosion rates will vary in both time and space. Prior studies in surface streams, springs, and caves suggest that variation in dissolved CO2 is the strongest control on variation in calcite dissolution rates. However, the controls on CO2 variation remain poorly quantified. Limited data suggest that ventilation of karst systems can substantially influence dissolved CO2 within karst conduits. However, the interactions among cave ventilation, air-water CO2 exchange, and dissolution dynamics have not been studied in detail. In this study, three years of time series measurements of dissolved and gaseous CO2, cave airflow velocity, and specific conductance from Blowing Springs Cave, Arkansas, were analyzed and used to estimate continuous calcite dissolution rates and quantify the correlations between those rates and potential physical and chemical drivers. We find that chimney effect airflow creates temperature-driven switches in airflow direction, and that the resulting seasonal changes in airflow regulate both gaseous and dissolved CO2 within the cave. As in previous studies, partial pressure of CO2 (pCO2) is the strongest chemical control of dissolution rate variability. However, we also show that cave airflow direction, rather than streamflow, is the strongest physical driver of changes in dissolution rate, contrary to the typical situation in surface channel erosion where floods largely determine the timing and extent of geomorphic work. At the study site, chemical erosion is typically active in the summer, during periods of cave downdraft (airflow from upper to lower entrances), and inactive in the winter, during updraft (airflow from lower to upper entrances). Storms provide only minor perturbations to this overall pattern. We also find that airflow direction modulates dissolution rate variation during storms, with higher storm variability during updraft than during downdraft. Finally, we compare our results with the limited set of other studies that have examined dissolution rate variation within cave streams and draw an initial hypothesis that evolution of cave ventilation patterns strongly impacts how dissolution rate dynamics evolve over the lifetime of karst conduits.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.125824","usgsCitation":"Covington, M.D., Knierim, K.J., Young, H.H., Rodriguez, J., and Gnoza, H., 2021, The impact of ventilation patterns on calcite dissolution rates within karst conduits: Journal of Hydrology, v. 593, 125824, 17 p., https://doi.org/10.1016/j.jhydrol.2020.125824.","productDescription":"125824, 17 p.","ipdsId":"IP-118284","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":381252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","city":"Bella Vista","otherGeospatial":"Blowing Springs Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.47624206542969,\n 36.380937621825886\n ],\n [\n -94.13360595703125,\n 36.380937621825886\n ],\n [\n -94.13360595703125,\n 36.61111838494165\n ],\n [\n -94.47624206542969,\n 36.61111838494165\n ],\n [\n -94.47624206542969,\n 36.380937621825886\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"593","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Covington, Matthew D.","contributorId":192015,"corporation":false,"usgs":false,"family":"Covington","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":806758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Holly H","contributorId":222433,"corporation":false,"usgs":false,"family":"Young","given":"Holly","email":"","middleInitial":"H","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodriguez, Josue","contributorId":245654,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Josue","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":806761,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gnoza, Hannah","contributorId":245655,"corporation":false,"usgs":false,"family":"Gnoza","given":"Hannah","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":806762,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217253,"text":"70217253 - 2021 - Examining the potential conflict between sea otter recovery and Dungeness crab fisheries in California","interactions":[],"lastModifiedDate":"2021-01-14T13:38:15.995228","indexId":"70217253","displayToPublicDate":"2020-12-10T07:34:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Examining the potential conflict between sea otter recovery and Dungeness crab fisheries in California","docAbstract":"Human exploitation of marine mammals led to precipitous declines in many wild populations within the last three centuries. Legal protections enacted throughout the 20th century have enabled the recovery of many of these species and some recoveries have resulted in conflict with humans for shared resources. With legal protections and reintroduction programs, the southern sea otter (Enhydra lutris nereis) has returned to portions of its former range from which it had been extirpated for decades, causing concern that the Dungeness crab (Cancer magister) fishery could be negatively affected by increasing otter range and population size. The Dungeness crab fishery is one of the most valuable in California, and these crabs are a known prey item of sea otters. We examine sea otter population growth by port region in relation to Dungeness crab catch using landing receipts since the early 1980s. We find Dungeness crab landings and fishing success, as measured by landings per trip receipt, increased across all ports. In the most recent decade, we observed slower growth in fishing success in northern ports where otters were absent, relative to southern ports where sea otters exist and their populations have grown. In ports where otters were present, fishing success was positively correlated with otter population size over time. Further, an extensive dataset of 83,000 sea otter foraging dives identified Dungeness crab to be less than 2% of the total diet. Though we find no evidence that sea otter populations impact the Dungeness crab fishery in California, other potential conflicts could be considered before expanding reintroduction programs.
Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.
Rangelands cover 70% of the world's land surface, and provide critical ecosystem services of primary production, soil carbon storage, and nutrient cycling. These ecosystem services are governed by very fine-scale spatial patterning of soil carbon, nutrients, and plant species at the centimeter-to-meter scales, a phenomenon known as “islands of fertility”. Such fine-scale dynamics are challenging to detect with most satellite and manned airborne platforms. Remote sensing from unmanned aerial vehicles (UAVs) provides an alternative option for detecting fine-scale soil nutrient and plant species changes in rangelands tn0020 smaller extents. We demonstrate that a model incorporating the fusion of UAV multispectral and structure-from-motion photogrammetry classifies plant functional types and bare soil cover with an overall accuracy of 95% in rangelands degraded by shrub encroachment and disturbed by fire. We further demonstrate that employing UAV hyperspectral and LiDAR fusion greatly improves upon these results by classifying 9 different plant species and soil fertility microsite types (SFMT) with an overall accuracy of 87%. Among them, creosote bush and black grama, the most important native species in the rangeland, have the highest producer's accuracies at 98% and 94%, respectively. The integration of UAV LiDAR-derived plant height differences was critical in these improvements. Finally, we use synthesis of the UAV datasets with ground-based LiDAR surveys and lab characterization of soils to estimate that the burned rangeland potentially lost 1474 kg/ha of C and 113 kg/ha of N owing to soil erosion processes during the first year after a prescribed fire. However, during the second-year post-fire, grass and plant-interspace SFMT functioned as net sinks for sediment and nutrients and gained approximately 175 kg/ha C and 14 kg/ha N, combined. These results provide important site-specific insight that is relevant to the 423 Mha of grasslands and shrublands that are burned globally each year. While fire, and specifically post-fire erosion, can degrade some rangelands, post-fire plant-soil-nutrient dynamics might provide a competitive advantage to grasses in rangelands degraded by shrub encroachment. These novel UAV and ground-based LiDAR remote sensing approaches thus provide important details towards more accurate accounting of the carbon and nutrients in the soil surface of rangelands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.112223","usgsCitation":"Sankey, J.B., Sankey, T.T., Li, J., Ravi, S., Wang, G., Caster, J., and Kasprak, A., 2021, Quantifying plant-soil-nutrient dynamics in rangelands: Fusion of UAV hyperspectral-LiDAR, UAV multispectral-photogrammetry, and ground-based LiDAR-digital photography in a shrub-encroached desert grassland: Remote Sensing of Environment, v. 253, 112223, 18 p., https://doi.org/10.1016/j.rse.2020.112223.","productDescription":"112223, 18 p.","ipdsId":"IP-110017","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":454141,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.112223","text":"Publisher Index Page"},{"id":381413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Sevilleta National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.80770874023438,\n 34.301471780404476\n ],\n [\n -106.63192749023438,\n 34.301471780404476\n ],\n [\n -106.63192749023438,\n 34.412574601595\n ],\n [\n -106.80770874023438,\n 34.412574601595\n ],\n [\n -106.80770874023438,\n 34.301471780404476\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"253","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":806946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Junran","contributorId":202740,"corporation":false,"usgs":false,"family":"Li","given":"Junran","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":806947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravi, Sujith","contributorId":202738,"corporation":false,"usgs":false,"family":"Ravi","given":"Sujith","email":"","affiliations":[{"id":36520,"text":"Department of Earth and Environmental Science, Temple University","active":true,"usgs":false}],"preferred":false,"id":806948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Guan","contributorId":202741,"corporation":false,"usgs":false,"family":"Wang","given":"Guan","email":"","affiliations":[{"id":36521,"text":"Department of Geosciences, University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":806949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":806950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":806951,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217235,"text":"70217235 - 2021 - Shifts in the wintering distribution and abundance of Emperor Geese in Alaska","interactions":[],"lastModifiedDate":"2021-01-13T14:23:04.369546","indexId":"70217235","displayToPublicDate":"2020-12-07T08:20:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Shifts in the wintering distribution and abundance of Emperor Geese in Alaska","docAbstract":"For wildlife species that winter at northern latitudes, harsh overwinter conditions can play an important role in population dynamics. Recent changes in global temperatures have resulted in distributional shifts of wildlife species, as well as amelioration of winter climates in northern landscapes. The emperor goose (Anser canagicus), an endemic migratory bird of the Bering Sea region, winters across a large area of the subarctic, with potential differences in migration strategies and costs among individuals. As a long-standing species of conservation concern due to decreased population size, understanding the response of emperor geese to changing conditions has become critical to on-going management. We sought to evaluate changes in wintering distribution and arrival/departure dates over time, by comparing spatial and temporal patterns of wintering emperor geese from 2015 to 2017 (using geolocator data) to satellite telemetry data collected from 1999 to 2004. Further, we quantified changes in spatial patterns of winter abundance by comparing historical and contemporary aerial and ground surveys at three island complexes encompassing most of their winter distribution. Our results indicate that emperor geese are arriving at wintering areas earlier and spending more time at these areas than in the past. Our comparisons among historical aerial and ground surveys suggests that increasing numbers of emperor geese are wintering closer to breeding areas in western Alaska; a change likely related to increasing habitat availability due to shifting environmental conditions. Our results also showed that fewer emperor geese are using an area in the core of their wintering range, suggesting either decreased habitat quality or a reduction in migration distance via alternative wintering locations. Overall, our study highlights a rapid response to apparent habitat change likely due to warming temperatures and a reduction in ice cover and emphasizes the importance of understanding complex interactions among migration distance, the environment, and habitat in interpreting site selection.
Multi-geophysical parameter classification can help to reduce the uncertainties of interpretations that often rely on one geophysical technique. Integrating these varying datasets requires a more robust classification approach rather than traditional qualitative methods. In this study, we applied the Fuzzy c-means (FCM) method to quantitatively classify similarities in a high resolution seismic tomography, a magnetotellurics and gravity datasets obtained in Montserrat. To group similar datapoints, this application uses a Euclidean distance measure and a membership function. Assigned membership values indicate the degree to which a datapoint belongs to a specific class. The spatial distribution of the derived classes, each classified with distinct geophysical parameters, helped to provide new structural and petrological information of the Montserrat geothermal system. In comparison to previous models, our new cluster model highlights two major improvements. These include the resolution and assessment of the spatial extension and 3D geometry of previously undetected features within the Montserrat geothermal system and the constrain and characterization of earlier identified anomalies. We additionally utilized geological and petrological data obtained from three geothermal wells in the Montserrat geothermal system to help validate our classifications. Based on a semi-quantitative approach we assessed the reliability of the FCM technique in relation to the likely uncertainties of the different geophysical models.
Niche breadth and position can influence diversification among closely related species or populations, yet limited empirical data exist concerning the predictability of the outcomes. We explored the effects of these factors on the evolution of the Emoia atrocostata species group, an insular radiation of lizards in the western Pacific Ocean and Indo-Australasia composed of both endemic and widespread species that differ in niche occupancy. We used molecular data and phylogeographical diffusion models to estimate the timing and patterns of range expansion, and ancestral reconstruction methods to infer shifts in ecology. We show evidence of multidirectional spread from a centre of origin in western Micronesia, and that the phyletic diversity of the group is derived from a putative habitat specialist that survives in the littoral zone. This species is composed of paraphyletic lineages that represent stages or possible endpoints in the continuum toward speciation. Several descendant species have transitioned to either strand or interior forest habitat, but only on remote islands with depauperate terrestrial faunas. Our results suggest that the atrocostata group might be in the early phases of a Wilsonian taxon cycle and that the capacity to tolerate salt stress has promoted dispersal and colonization of remote oceanic islands. Divergence itself, however, is largely driven by geographical isolation rather than shifts in ecology.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biolinnean/blaa172","usgsCitation":"Richmond, J.Q., Ota, H., Grismer, L., and Fisher, R., 2021, Influence of niche breadth and position on the historical biogeography of seafaring scincid lizards: Biological Journal of the Linnean Society, v. 132, no. 1, p. 74-92, https://doi.org/10.1093/biolinnean/blaa172.","productDescription":"19 p.","startPage":"74","endPage":"92","ipdsId":"IP-123408","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":454152,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biolinnean/blaa172","text":"Publisher Index Page"},{"id":391914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 104.23828125,\n -47.04018214480665\n ],\n [\n 165.76171875,\n -47.04018214480665\n ],\n [\n 165.76171875,\n 5.61598581915534\n ],\n [\n 104.23828125,\n 5.61598581915534\n ],\n [\n 104.23828125,\n -47.04018214480665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":827039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ota, Hidetoshi","contributorId":147501,"corporation":false,"usgs":false,"family":"Ota","given":"Hidetoshi","email":"","affiliations":[],"preferred":false,"id":827040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grismer, L Lee","contributorId":269404,"corporation":false,"usgs":false,"family":"Grismer","given":"L Lee","affiliations":[{"id":41086,"text":"La Sierra University","active":true,"usgs":false}],"preferred":false,"id":827041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":827042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220115,"text":"70220115 - 2021 - Monitoring volcanic deformation","interactions":[],"lastModifiedDate":"2021-04-20T12:46:38.791152","indexId":"70220115","displayToPublicDate":"2020-12-02T07:42:30","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Monitoring volcanic deformation","docAbstract":"Deformation signals recorded at volcanoes have long been used to infer the processes behind subsurface magma intrusions. Monitoring strategies vary greatly depending on several factors such as the activity of the individual volcano, access, available personnel, and funding.
Certain geodetic monitoring methods, such as Electronic Distance Measurements, are inexpensive but require that scientists be dangerously close to active areas. Other techniques, such as telemetered geodetic measurements (Electronic Tiltmeters and Global Navigation Satellite System), or deformation images from Interferometric Synthetic Aperture Radar, can be collected remotely and with less risk. Observed surface deformation can be fit to the predictions of mathematical source models to obtain quantitative estimates of their parameters (e.g., location, depth, volume change and more). Combined deformation and gravity change measurements can be used to infer the density of subsurface intrusions and better constrain the source of unrest.
To be effective, geodetic monitoring must be done before, during, and after eruptions and must be integrated with other monitoring techniques (e.g., seismology, geochemistry, physical volcanology, remote sensing). It requires the long-term commitment of time and resources.
Done effectively, geodetic monitoring not only can provide timely warnings of escalating volcano hazards but may also lead to improved understanding of how volcanoes work. Even when a volcano is not active, monitoring generates baseline information against which changes in volcano behavior can be compared. Preserving the integrity and accessibility of geodetic data archives is thus essential if future volcanologists are to benefit from the decades-long records of geodetic data gathered by volcano observatories.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-08-102908-4.00132-6","usgsCitation":"Battaglia, M., Alpala, J., Alpala, R., Angarita, M., Arcos, D., Euillades, L., Euillades, P., Muller, C., and Narvaez, L., 2021, Monitoring volcanic deformation, chap. of Encyclopedia of geology, p. 774-804, https://doi.org/10.1016/B978-0-08-102908-4.00132-6.","productDescription":"31 p.","startPage":"774","endPage":"804","ipdsId":"IP-119768","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglia, Maurizio 0000-0003-4726-5287 mbattaglia@usgs.gov","orcid":"https://orcid.org/0000-0003-4726-5287","contributorId":204742,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":814512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpala, Jorge","contributorId":139634,"corporation":false,"usgs":false,"family":"Alpala","given":"Jorge","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alpala, Rosa","contributorId":215654,"corporation":false,"usgs":false,"family":"Alpala","given":"Rosa","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angarita, Mario","contributorId":215655,"corporation":false,"usgs":false,"family":"Angarita","given":"Mario","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":814515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arcos, Dario","contributorId":139636,"corporation":false,"usgs":false,"family":"Arcos","given":"Dario","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Euillades, Leonardo","contributorId":225157,"corporation":false,"usgs":false,"family":"Euillades","given":"Leonardo","email":"","affiliations":[{"id":41053,"text":"Universidad Nacional de Cuyo, Facultad de Ingeniería, Instituto CEDIAC & CONICET","active":true,"usgs":false}],"preferred":false,"id":814516,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euillades, Pablo","contributorId":225156,"corporation":false,"usgs":false,"family":"Euillades","given":"Pablo","affiliations":[{"id":41053,"text":"Universidad Nacional de Cuyo, Facultad de Ingeniería, Instituto CEDIAC & CONICET","active":true,"usgs":false}],"preferred":false,"id":814517,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muller, Cyril","contributorId":205255,"corporation":false,"usgs":false,"family":"Muller","given":"Cyril","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":814519,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Narvaez, Lourdes","contributorId":215659,"corporation":false,"usgs":false,"family":"Narvaez","given":"Lourdes","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814520,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70219582,"text":"70219582 - 2021 - Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","interactions":[],"lastModifiedDate":"2021-04-15T12:53:09.492694","indexId":"70219582","displayToPublicDate":"2020-12-01T07:52:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","docAbstract":"The PHREEQ-N-AMDTreat aqueous geochemical modeling tools described herein simulate changes in pH and solute concentrations resulting from passive and active treatment of acidic or alkaline mine drainage (AMD). The “user-friendly” interactive tools, which are publicly available software, utilize PHREEQC equilibrium aqueous and surface speciation models and kinetics models for O2 ingassing and CO2 outgassing, iron and manganese oxidation and precipitation, limestone dissolution, and organic carbon oxidation combined with reduction of nitrate, sulfate, and ferric iron. Reactions with synthetic caustic chemicals (CaO, Ca(OH)2, NaOH, Na2CO3) or oxidizing agents (H2O2) also may be simulated separately or combined with sequential kinetic steps. A user interface facilitates input of water chemistry data for one or two (mixed) influent AMD solutions and adjustment of kinetic variables. Graphical and tabular output indicates the changes in pH, metals and other solute concentrations, total dissolved solids, and specific conductance of treated effluent plus the cumulative quantity of precipitated solids as a function of retention time or the amount of caustic agent added. By adjusting kinetic variables or chemical dosing, the effects of independent or sequential treatment steps that have different retention time (volume/flow rate), aeration rate, quantities of reactive solids, and temperature can be simulated for the specified influent quality. The size (land area) of a treatment system can then be estimated using reaction time estimates (volume for a corresponding treatment step is the product of reaction time and flow rate; area is volume divided by depth). Given the estimated system size, the AMDTreat cost-analysis model may be used to compute approximate costs for installation (capital) and annual operations and maintenance. Thus, various passive and/or active treatment strategies can be identified that could potentially achieve the desired effluent quality, but require different land area, equipment, and costs for construction and operation.
Quantifiable estimates of predator–prey interactions and relationships in aquatic habitats are difficult to obtain and rare, especially when individuals cannot be readily observed. To overcome this observational impediment, imaging sonar was used to assess the cooccurrence of predator‐size fish and juvenile salmonids, Oncorhynchus spp., at the entrance to a floating surface collector (FSC) in the forebay of North Fork Dam on the Clackamas River, Oregon (USA). Imaging sonar can be used to transform active sound waves into visual data, making it possible to obtain continuous underwater observations on the presence and interspecific interactions between predator‐size fish and prey (juvenile salmonids). Hourly counts of smolt‐size fish tracks, diel phase, water clarity and river discharge were used as covariates within a zero‐inflated Poisson model to determine how these factors may influence the number of predators in front of the FSC. Both the number of smolt‐size fish tracks and diel phase had the strongest effects on the number of predator‐size fish tracks, with more predator‐size fish tracks observed during the daytime, and as the number of smolt‐size fish tracks increased. Additionally, the presence of predator‐size fish may affect the abundance and direction of travel of juvenile salmonids, as fewer smolt‐size fish were observed when predators were present, and a greater proportion of smolt‐size fish were observed travelling away from the FSC when predator‐size fish were present. This study provides estimates of predator and prey fish abundance in the vicinity of surface collection systems at moderate‐sized hydropower projects and could help resource managers better understand mechanisms that can influence the survival and passage behaviour of juvenile salmonids using surface collection structures at dams.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12465","usgsCitation":"Smith, C.D., Plumb, J., Adams, N.S., and Wyatt, G.J., 2021, Predator and prey events at the entrance of a surface‐oriented fish collector at North Fork Dam, Oregon: Fisheries Management and Ecology, v. 28, no. 2, p. 172-182, https://doi.org/10.1111/fme.12465.","productDescription":"11 p.","startPage":"172","endPage":"182","ipdsId":"IP-097283","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":384347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","city":"Estacada","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38632202148438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.273920035433605\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wyatt, Garth J","contributorId":214904,"corporation":false,"usgs":false,"family":"Wyatt","given":"Garth","email":"","middleInitial":"J","affiliations":[{"id":39135,"text":"Portland General Electric, 33831 Faraday Rd., Estacada, Oregon 97023","active":true,"usgs":false}],"preferred":false,"id":811725,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217365,"text":"70217365 - 2021 - Climate and Ecological Disturbance Analysis of Engelmann spruce and Douglas fir in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2021-01-20T13:53:14.893644","indexId":"70217365","displayToPublicDate":"2020-11-30T07:51:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7512,"text":"Trees, Forests, and People","active":true,"publicationSubtype":{"id":10}},"title":"Climate and Ecological Disturbance Analysis of Engelmann spruce and Douglas fir in the Greater Yellowstone Ecosystem","docAbstract":"The effects of anthropogenic climate change are apparent in the Greater Yellowstone Ecosystem (GYE), USA, with forest die-off, insect outbreaks, and wildfires impacting forest ecosystems. A long-term perspective would enable assessment of the historical range of variability in forest ecosystems and better determination of recent forest dynamics and historical thresholds. The objectives of this study were to (1) develop tree-ring chronologies for Engelmann spruce and Douglas fir growing at the study location, (2) correlate the annual ring widths of each species to monthly climate variables, (3) examine the instrumental climate data for regimes shifts in the mean state of variables, and (4) determine when ecological disturbances occurred through a quantification of growth releases. Finally, we discuss both climate-growth relationships and growth releases in the context of climate regime shifts and known forest disturbances. Engelmann spruce and Douglas fir showed some similar climate responses using moving correlation analysis including negative correlations between ring width and June – August current year temperature and previous growing season temperature. Regime shift analysis indicated significant (p < 0.05) shifts in minimum and maximum GYE temperature in the latter half of the 20th century. Disturbance analysis indicated that both tree species responded to wildfire and insect outbreak events with growth releases in up to 25% of the trees. Disentangling the influence of climate regime shifts and forest disturbances on the climate-growth relationships can be difficult because climate and forest disturbances are intricately linked. Our evidence indicates that regime shifts in monthly climate variables and forest disturbances as recorded by growth releases can influence the ring width response to climate over time. Trees are key to providing a long-term perspective on climate and ecological health across the GYE because they integrate both climate and ecology in their annual ring widths.
Climate change is causing rapid warming and altered precipitation patterns in mountain watersheds, both of which influence the timing of ice breakup in mountain lakes. To enable predictions of ice breakup in the future, we analyzed a dataset of mountain lake ice breakup dates derived from remote sensing and historical downscaled climate data. We evaluated drivers of ice breakup, constructed a predictive statistical model, and developed projections of mountain lake ice breakup date with global climate models. Using Random Forest analysis, we determined that winter and spring cumulative snow fraction (portion of precipitation falling as snow) and air temperature are the strongest predictors of ice breakup on mountain lakes. Interactions between precipitation, cumulative winter air temperature and lake surface area indicate that shifts in air temperature and precipitation affect smaller lakes (< 2 km2) more than larger lakes (> 2–10 km2). A linear mixed effects model (RMSE of 18 d), applied with an ensemble of 15 global climate models, projected that end-of-century ice breakup in mountain lakes will be earlier by 25 ± 4 and 61 ± 5 (mean ± SE) days for representative concentration pathways 4.5 and 8.5, respectively.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11656","usgsCitation":"Caldwell, T.J., Chandra, S., Albright, T., Harpold, A., Dills, T., Greenberg, J., Sadro, S., and Dettinger, M.D., 2021, Drivers and projections of ice phenology in mountain lakes in the western United States: Limnology and Oceanography, v. 66, no. 3, p. 995-1008, https://doi.org/10.1002/lno.11656.","productDescription":"14 p.","startPage":"995","endPage":"1008","ipdsId":"IP-104573","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.11656","text":"Publisher Index Page"},{"id":387042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, Washington","otherGeospatial":"Cascade Mountains, northern Rocky Mountains, Sierra Nevada Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.136474609375,\n 48.07807894349862\n ],\n [\n -116.378173828125,\n 49.001843917978526\n ],\n [\n -119.36645507812499,\n 49.001843917978526\n ],\n [\n -119.20166015625,\n 48.52388120259336\n ],\n [\n -117.191162109375,\n 47.66538735632654\n ],\n [\n -116.42211914062499,\n 47.65058757118734\n ],\n [\n -116.114501953125,\n 47.71715357016648\n ],\n [\n -116.136474609375,\n 48.07807894349862\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.76171875,\n 46.475699386607516\n ],\n [\n -119.84985351562499,\n 48.96579381461063\n ],\n [\n -121.78344726562499,\n 49.01625665778159\n ],\n [\n -122.1240234375,\n 47.04766864046083\n ],\n [\n -122.58544921875,\n 45.506346901083425\n ],\n [\n -123.1787109375,\n 42.73087427928485\n ],\n [\n -122.54150390625,\n 42.04113400940807\n ],\n [\n -122.27783203125,\n 41.1290213474951\n ],\n [\n -120.87158203125,\n 41.393294288784865\n ],\n [\n -120.9814453125,\n 42.08191667830631\n ],\n [\n -121.62963867187499,\n 43.98491011404692\n ],\n [\n -121.14624023437499,\n 45.18978009667531\n ],\n [\n -120.76171875,\n 46.475699386607516\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.45507812500001,\n 36.19109202182454\n ],\n [\n -119.794921875,\n 39.01064750994083\n ],\n [\n -120.498046875,\n 40.49709237269567\n ],\n [\n -120.52001953124999,\n 40.94671366508002\n ],\n [\n -121.6845703125,\n 40.56389453066509\n ],\n [\n -120.73974609374999,\n 38.47939467327645\n ],\n [\n -118.23486328125,\n 35.47856499535729\n ],\n [\n -116.87255859374999,\n 35.65729624809628\n ],\n [\n -116.45507812500001,\n 36.19109202182454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Timothy J","contributorId":146463,"corporation":false,"usgs":false,"family":"Caldwell","given":"Timothy","email":"","middleInitial":"J","affiliations":[{"id":16704,"text":"University of Nevada - Reno","active":true,"usgs":false}],"preferred":false,"id":818862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandra, Sudeep 0000-0002-9297-8211","orcid":"https://orcid.org/0000-0002-9297-8211","contributorId":224786,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","email":"","affiliations":[{"id":32871,"text":"University of Nevada at Reno","active":true,"usgs":false}],"preferred":false,"id":818863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albright, Thomas","contributorId":260809,"corporation":false,"usgs":false,"family":"Albright","given":"Thomas","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harpold, Adrian","contributorId":207118,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":818865,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dills, Thomas","contributorId":260810,"corporation":false,"usgs":false,"family":"Dills","given":"Thomas","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818866,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greenberg, Jonathan","contributorId":260811,"corporation":false,"usgs":false,"family":"Greenberg","given":"Jonathan","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":818868,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":818869,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70217180,"text":"70217180 - 2021 - Is there enough water? How bearish and bullish outlooks are linked to decision-maker perspectives on environmental flows","interactions":[],"lastModifiedDate":"2021-01-11T14:32:11.466282","indexId":"70217180","displayToPublicDate":"2020-11-26T08:27:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Is there enough water? How bearish and bullish outlooks are linked to decision-maker perspectives on environmental flows","docAbstract":"Policies that mandate environmental flows (e-flows) can be powerful tools for freshwater conservation, but implementation of these policies faces many hurdles. To better understand these challenges, we explored two key questions: (1) What additional data are needed to implement e-flows? and (2) What are the major socio-political barriers to implementing e-flows? We surveyed water and natural resource decision makers in the semi-arid Red River basin, Texas-Oklahoma, USA, and used social network analysis to analyze their communication patterns. Most respondents agreed that e-flows can provide important benefits and identified the same data needs. However, respondents sharply in their beliefs on other issues, and a clustering analysis revealed two distinct groups of decision makers. One cluster of decision makers tended to be bearish, or pessimistic, and believed that: current flow conditions are not adequate, there are many serious socio-political barriers to implementation, water conflicts will likely increase in the future, and climate change is likely to exacerbate these issues. The other cluster of respondents was bullish, or optimistic: they foresaw fewer future water conflicts and fewer socio-political barriers to implementation. Despite these differences, both clusters largely identified the same data needs and barriers to e-flows implementation. Our social network analysis revealed that the frequency of communication between clusters was not significantly different than the frequency of communication within clusters. Overall, our results suggest that the different perspectives of decision-makers could complicate efforts to implement e-flows and proactively plan for climate change. However, there are opportunities for collaboration on addressing common data needs and barriers to implementation. Overall, our study provides a key socio-environmental perspective on e-flows implementation from a semi-arid and socio-politically complex river basin and contextualizes the many challenges facing e-flows implementation in river basins globally.
Occupancy methods propelled the quantitative study of species distributions forward by separating the observation process, or the imperfect detectability of species, from the ecological processes of interest governing species distributions. Occupancy studies come at a cost, however: the collection of additional data to account for nondetections at sites where the species is present. The most common occupancy designs (repeated measures designs) require repeat visits to sites or the use of multiple observers or detection methods. Time‐to‐detection methods have been identified as a potentially efficient alternative, requiring only one visit to each site by a single observer. A comparison of time‐to‐detection methods to repeated measures designs for visual encounter surveys would allow researchers to evaluate whether time‐to‐detection methods might be appropriate for their study system and can inform optimal survey design. We collected time‐to‐detection data during two different repeated measures design occupancy surveys for four amphibians and compared the performance of time‐to‐detection methods to the other designs using the location (potential bias) and precision of posterior distributions for occurrence parameters. We further used results of time‐to‐detection surveys to optimize survey design. Time‐to‐detection methods performed best for species that are widespread and have high detection probabilities and rates, but performed less well for cryptic species with lower probability of occurrence or whose detection was strongly affected by survey conditions. In all cases single surveys were most efficient in terms of person‐hours expended, but under some conditions the survey duration required to achieve high detection probabilities would be prohibitively long for a single survey. Regardless of occupancy survey design, time‐to‐detection methods provide important information that can be used to optimize surveys, allowing researchers and resource managers to efficiently achieve monitoring and conservation goals. Collecting time‐to‐detection data while conducting repeated measures occupancy surveys requires only small modifications to field methods but could have large benefits in terms of time spent surveying in the long‐term.
In the past two decades, Salt Plains National Wildlife Refuge has been increasingly recognized as important habitat for both breeding and migratory shorebirds. North American snowy plovers Charadrius nivosus in particular rely on the nearly 5,000-ha salt flat at Salt Plains National Wildlife Refuge, which thousands use as breeding and stopover habitat. Elsewhere on the Southern Great Plains, decadal declines up to 75% within snowy plover subpopulations have been documented and attributed to vegetation encroachment, increased rates of nest predation, and decreased availability of fresh surface water. Despite many attempts to estimate this species' abundance across the continent, to date, no known attempt at distance sampling of snowy plovers has occurred. To address this paucity of data, we assessed feasibility of distance sampling methods to accurately estimate snowy plover abundance and detectability. Distance sampling surveys (2017–2018) indicated high detection probability (P = 0.80) and the population abundance estimate across the salt flat extrapolated to 3,307 individuals. The distance-sampling population abundance estimate is lower than population abundance estimates determined by two previous studies within the past decade but far greater than 2,105 estimated for a study in 2006. Overall, distance sampling snowy plovers at Salt Plains National Wildlife Refuge proved to be an effective addition to pre-established survey protocols but further investigation is needed to compare accuracy and precision of methods used in this study, annual surveys conducted by Salt Plains National Wildlife Refuge, and other potential snowy plover surveys.
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