Ground motions in the Los Angeles Basin during large earthquakes are modulated by earthquake ruptures, path effects into the basin, basin effects, and local site response. We analyzed the direct effect of shallow basin structures on shaking duration at a period of 2–10 s in the Los Angeles region through modeling small magnitude, shallow, and deep earthquake pairs. The source depth modulates the basin response, particularly the shaking duration, and these features are a function of path effect and not site condition. Three-dimensional simulations using the CVM-S4.26.M01 velocity model show good fitting to the initial portion of the waveforms at periods of 5 s and longer but fail to predict the long shaking duration during shallow events, especially at periods less than 5 s. Simulations using CVM-H do not match the timing of the initial arrivals as well as CVM-S4.26.M01, and the strong late arrivals in the CVM-H simulation travel with an apparent velocity slower than observed. A higher-quality factor than traditionally assumed may produce synthetics with longer durations but is unable to accurately match the amplitude and phase. Beamforming analysis using dense array data further reveals the long duration surface waves have the same back azimuth as the direct arrivals and are generated at the basin edges, while the later coda waves are scattered from off-azimuth directions, potentially due to strong, sharp boundaries offshore. Improving the description of these shallow basin structures and attenuation model will enhance our capability to predict long-period ground motions in basins.
Land use in Panama has changed dramatically with ongoing deforestation and conversion to cropland and cattle pastures, potentially altering the soil properties that drive the hydrological processes of infiltration and overland flow. We compared plot-scale overland flow generation between hillslopes in forested and actively cattle-grazed watersheds in Central Panama. Soil physical and hydraulic properties, soil moisture and overland flow data were measured along hillslopes of each land-use type. Soil characteristics and rainfall data were input into a simple, 1-D representative model, HYDRUS-1D, to simulate overland flow that we used to make inferences about overland flow response at forest and pasture sites. Runoff ratios (overland flow/rainfall) were generally higher at the pasture site, although no overall trends were observed between rainfall characteristics and runoff ratios across the two land uses at the plot scale. Saturated hydraulic conductivity (Ks) and bulk density were different between the forest and pasture sites (p < 10−4). Simulating overland flow in HYDRUS-1D produced more outputs similar to the overland flow recorded at the pasture site than the forest site. Results from our study indicate that, at the plot scale, Hortonian overland flow is the main driver for overland flow generation at the pasture site during storms with high-rainfall totals. We infer that the combination of a leaf litter layer and the activation of shallow preferential flow paths resulting in shallow saturation-excess overland flow are likely the main drivers for plot scale overland flow generation at the forest site. Results from this study contribute to the broader understanding of the delivery of freshwater to streams, which will become increasingly important in the tropics considering freshwater resource scarcity and changing storm intensities.
The prediction of wave runup, as well as its components, time-averaged setup and the time-varying swash, is a key element of coastal storm hazard assessments, as wave runup controls the transitions between morphodynamic response types such as dune erosion and overwash, and the potential for flooding by wave overtopping. While theoretically able to simulate the dominant low-frequency swash, previous studies using the infragravity-wave–resolving model XBeach (XBSB) have shown an underestimation of the observed swash variance and wave runup, which was in part related to the absence of incident-band swash motions in the model. Here, we use an incident-band wave-resolving, non-hydrostatic version of the XBeach model (XBNH) to simulate wave runup observed during the SandyDuck '97 experiment on an intermediate–reflective sandy beach. The results show that the XBNH model describes wave runup and the individual setup and swash components well. We subsequently examine differences in wave runup prediction between the XBSB and XBNH models and find that the XBNH model is a better predictor of wave runup than XBSB for this beach, which is due to better predictions of both the incident-band and infragravity-band swash. For a range of beach states from reflective to dissipative it is shown that incident-band swash is underestimated by XBSB relative to XBNH, in particular for reflective conditions. Infragravity-band swash is shown to be lower in XBSB than XBNH for most conditions, including dissipative conditions for which the mean difference is 16% of the deep water wave height. The difference in infragravity-band swash in XBNH relative to XBSB is shown to mainly be the result of processes occurring outside the swash zone, but approximately 15% of the difference is caused by explicitly resolving incident-band wave motions within the swash zone, such as swash-swash interactions, which inherently cannot be simulated by wave-averaged models.
Characterizing pre- and post-fire fuels remains a key challenge for estimating biomass consumption and carbon emissions from wildfires. Airborne laser scanning (ALS) data have demonstrated effectiveness for estimating canopy, and to a lesser degree, surface fuel components at fine-scale (i.e., 30 m) across landscapes. Using pre- and post-fire ALS data and corresponding field data, this study estimated consumption of canopy fuel (ΔCF), understory fuel (ΔUF), total fuel (ΔTF), and canopy bulk density (ΔCBD) for the 2012 Pole Creek fire in Oregon, USA (10,760 ha), and portions of the 2011 Las Conchas fire in New Mexico, USA (4,934 ha). Additionally, the feasibility of predicting fuel consumption was tested using separate pre- and post-fire models (PrePost), models combining all pre- and post-fire data (Pooled), and models using all data from both fires (Global). Estimates of ΔTF were then compared to fire radiative energy (FRE, units: MJ) derived from Fire Radiative Power (FRP, units: MW) observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA Terra and Aqua satellites to mechanistically derive a biomass combustion coefficient (BCC, units: kg MJ−1). The PrePost and Pooled approaches yielded similar results at Las Conchas, but at Pole Creek insufficient pre-fire field data resulted in erroneous fuel consumption estimates outside the fire perimeter using the PrePost models. These results demonstrated that pre-fire field data were less important for these models than having field data which represent the full range of fuel conditions likely to exist across the landscape. Estimated total biomass consumed for the PrePost, Pooled, and Global models were 226 Gg, 224 Gg, and 224 Gg at Las Conchas, and 581 Gg, 713 Gg, and 552 Gg at Pole Creek. Comparisons between estimated ΔTF and FRE yielded an average BCC for both fires of 0.367 (s.d. ± 0.049) kg MJ−1 based on pixels with at least five MODIS observations. Both higher MODIS observations per pixel and accounting for canopy occlusion of FRE improved the relationship between ΔTF and MODIS-FRE. This study suggested a practical modelling approach for future efforts using only post-fire field observations and quantified a landscape-scale relationship between MODIS-derived FRE and fine-scale fuel consumption consistent with prior experiments.
The 2019 Ridgecrest, California earthquake sequence included Mw 6.4 and Mw 7.1 earthquakes that occurred on successive days beginning on 4 July 2019. These two largest earthquakes of the sequence occurred on orthogonal faults that ruptured the Earth’s surface. To better evaluate the 3D subsurface fault structure, (P- and S-wave) velocity, 3D and temporal variations in seismicity, and other important aspects of the earthquake sequence, we recorded aftershocks and ambient noise using up to 461 three-component nodal seismographs for about two months, beginning about one day after the Mw 7.1 mainshock. The ~ 30,000 Mw≥1 earthquakes that were recorded on the dense arrays provide an unusually large volume of data with which to evaluate the earthquake sequence. This report describes the recording arrays and is intended to provide metadata for researchers interested in evaluating various aspects of the 2019 Ridgecrest earthquake sequence using the nodal data set.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220200203","usgsCitation":"Catchings, R.D., Goldman, M., Steidl, J.H., Chan, J., Allam, A., Criley, C., Ma, Z., Langermann, D., Huddleston, G., McEvilly, A., Mongovin, D., and Ben-Zion, Y., 2020, Nodal seismograph recordings of the 2019 Ridgecrest Earthquake Sequence: Seismological Research Letters, v. 91, no. 6, p. 3622-3633, https://doi.org/10.1785/0220200203.","productDescription":"12 p.","startPage":"3622","endPage":"3633","ipdsId":"IP-116990","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United Staets","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.84463534796981,\n 35.703354079218656\n ],\n [\n -117.84463534796981,\n 35.534977065306975\n ],\n [\n -117.55394107005387,\n 35.534977065306975\n ],\n [\n -117.55394107005387,\n 35.703354079218656\n ],\n [\n -117.84463534796981,\n 35.703354079218656\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"91","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-09-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":927514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldman, Mark 0000-0002-0802-829X","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":205863,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":927515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steidl, Jamison Haase 0000-0003-0612-7654","orcid":"https://orcid.org/0000-0003-0612-7654","contributorId":239709,"corporation":false,"usgs":true,"family":"Steidl","given":"Jamison","email":"","middleInitial":"Haase","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chan, Joanne 0000-0002-2065-2423","orcid":"https://orcid.org/0000-0002-2065-2423","contributorId":205864,"corporation":false,"usgs":true,"family":"Chan","given":"Joanne","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allam, Amir A. 0000-0002-6447-0779","orcid":"https://orcid.org/0000-0002-6447-0779","contributorId":350962,"corporation":false,"usgs":false,"family":"Allam","given":"Amir A.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":927518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Criley, Coyn 0000-0002-0227-0165","orcid":"https://orcid.org/0000-0002-0227-0165","contributorId":223113,"corporation":false,"usgs":true,"family":"Criley","given":"Coyn","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":927519,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ma, Zhenning","contributorId":350963,"corporation":false,"usgs":false,"family":"Ma","given":"Zhenning","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":927520,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Langermann, Daniel S.","contributorId":351005,"corporation":false,"usgs":false,"family":"Langermann","given":"Daniel S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":927677,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huddleston, Garet Jax 0000-0002-2837-3947","orcid":"https://orcid.org/0000-0002-2837-3947","contributorId":350964,"corporation":false,"usgs":true,"family":"Huddleston","given":"Garet Jax","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927522,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McEvilly, Andrian T.","contributorId":351006,"corporation":false,"usgs":false,"family":"McEvilly","given":"Andrian T.","affiliations":[],"preferred":false,"id":927678,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mongovin, Daniel David Thomas 0000-0002-1623-2637","orcid":"https://orcid.org/0000-0002-1623-2637","contributorId":350965,"corporation":false,"usgs":true,"family":"Mongovin","given":"Daniel David Thomas","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927523,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ben-Zion, Yehuda 0000-0002-9602-2014","orcid":"https://orcid.org/0000-0002-9602-2014","contributorId":350966,"corporation":false,"usgs":false,"family":"Ben-Zion","given":"Yehuda","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":927525,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70214515,"text":"sir20205083 - 2020 - The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3","interactions":[],"lastModifiedDate":"2020-09-30T12:35:17.865835","indexId":"sir20205083","displayToPublicDate":"2020-09-29T12:47:07","publicationYear":"2020","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":"2020-5083","displayTitle":"The Everglades Depth Estimation Network (EDEN) Surface-Water Interpolation Model, Version 3","title":"The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3","docAbstract":"The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011.
The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies.
Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205083","collaboration":"USGS Greater Everglades Priority Ecosystems Science ProgramDirector, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
We measured food availability and diet composition of juvenile salmonids over multiple years and seasons before and during the world’s largest dam removal on the Elwha River, Washington State. We conducted these measurements over three sediment-impacted sections (the estuary and two sections of the river downstream of each dam) and compared these to data collected from mainstem tributaries not directly affected by the massive amount of sediment released from the reservoirs. We found that sediment impacts from dam removal significantly reduced invertebrate prey availability, but juvenile salmon adjusted their foraging so that the amount of energy in diets was similar before and during dam removal. This general pattern was seen in both river and estuary habitats, although the mechanisms driving the change and the response differed between habitats. In the estuary, the dietary shifts were related to changes in invertebrate assemblages following a hydrological transition from brackish to freshwater caused by sediment deposition at the river’s mouth. The loss of brackish invertebrate species caused fish to increase piscivory and rely on new prey sources such as plankton. In the river, energy provided to fish by Ephemeroptera, Plecoptera, and Trichoptera taxa before dam removal was replaced first by terrestrial invertebrates, and then by sediment-tolerant taxa such as Chironomidae. The results of our study are consistent with many others that have shown sharp declines in invertebrate density during dam removal. Our study further shows how those changes can move through the food web and affect fish diet composition, selectivity, and energy availability. As we move further along the dam removal response trajectory, we hypothesize that food web complexity will continue to increase as annual sediment load now approaches natural background levels, anadromous fish have recolonized the majority of the watershed between and above the former dams, and revegetation and microhabitats continue to develop in the estuary.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0239198","usgsCitation":"Morley, S.A., Foley, M.M., Duda, J.J., Beirne, M.M., Paradis, R.L., Johnson, R.C., McHenry, M.L., Elofson, M., Sampson, E.M., McCoy, R.E., Stapleton, J., and Pess, G.R., 2020, Shifting food web structure during dam removal—Disturbance and recovery during a major restoration action: PLoS ONE, v. 15, no. 9, e0239198, 34 p., https://doi.org/10.1371/journal.pone.0239198.","productDescription":"e0239198, 34 p.","ipdsId":"IP-117389","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":455196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0239198","text":"Publisher Index Page"},{"id":378966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River, Olympic Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.64974975585938,\n 47.81960975604292\n ],\n [\n -123.38882446289061,\n 47.81960975604292\n ],\n [\n -123.38882446289061,\n 48.16333749877855\n ],\n [\n -123.64974975585938,\n 48.16333749877855\n ],\n [\n -123.64974975585938,\n 47.81960975604292\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Morley, Sarah A.","contributorId":148956,"corporation":false,"usgs":false,"family":"Morley","given":"Sarah","email":"","middleInitial":"A.","affiliations":[{"id":17601,"text":"NOAA Fisheries, Northwest Fisheries Science Center, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":800243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Melissa M 0000-0002-5832-6404","orcid":"https://orcid.org/0000-0002-5832-6404","contributorId":238117,"corporation":false,"usgs":false,"family":"Foley","given":"Melissa","email":"","middleInitial":"M","affiliations":[{"id":47699,"text":"San Francisco Estuary Institute, Richmond, CA","active":true,"usgs":false}],"preferred":false,"id":800244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":800245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beirne, Mathew M","contributorId":241958,"corporation":false,"usgs":false,"family":"Beirne","given":"Mathew","email":"","middleInitial":"M","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paradis, Rebecca L","contributorId":241960,"corporation":false,"usgs":false,"family":"Paradis","given":"Rebecca","email":"","middleInitial":"L","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800247,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":800248,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McHenry, Michael L.","contributorId":39672,"corporation":false,"usgs":false,"family":"McHenry","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":800249,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Elofson, Mel","contributorId":241966,"corporation":false,"usgs":false,"family":"Elofson","given":"Mel","email":"","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800250,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sampson, Earnest M","contributorId":241968,"corporation":false,"usgs":false,"family":"Sampson","given":"Earnest","email":"","middleInitial":"M","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800251,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCoy, Randall E","contributorId":241971,"corporation":false,"usgs":false,"family":"McCoy","given":"Randall","email":"","middleInitial":"E","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800252,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stapleton, Justin","contributorId":241974,"corporation":false,"usgs":false,"family":"Stapleton","given":"Justin","email":"","affiliations":[{"id":47700,"text":"Natural Resources Department, Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":800253,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pess, George R.","contributorId":13501,"corporation":false,"usgs":false,"family":"Pess","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":800254,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70214968,"text":"70214968 - 2020 - The distribution of woody species in relation to climate and fire in Yosemite National Park, California, USA","interactions":[],"lastModifiedDate":"2020-10-03T15:26:50.097038","indexId":"70214968","displayToPublicDate":"2020-09-29T10:24:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The distribution of woody species in relation to climate and fire in Yosemite National Park, California, USA","docAbstract":"The effects of climate on plant species ranges are well appreciated, but the effects of other processes, such as fire, on plant species distribution are less well understood. We used a dataset of 561 plots 0.1 ha in size located throughout Yosemite National Park, in the Sierra Nevada of California, USA, to determine the joint effects of fire and climate on woody plant species. We analyzed the effect of climate (annual actual evapotranspiration [AET], climatic water deficit [Deficit]) and fire characteristics (occurrence [BURN] for all plots, fire return interval departure [FRID] for unburned plots, and severity of the most severe fire [dNBR]) on the distribution of woody plant species.
Of 43 species that were present on at least two plots, 38 species occurred on five or more plots. Of those 38 species, models for the distribution of 13 species (34%) were significantly improved by including the variable for fire occurrence (BURN). Models for the distribution of 10 species (26%) were significantly improved by including FRID, and two species (5%) were improved by including dNBR. Species for which distribution models were improved by inclusion of fire variables included some of the most areally extensive woody plants. Species and ecological zones were aligned along an AET-Deficit gradient from cool and moist to hot and dry conditions.
In fire-frequent ecosystems, such as those in most of western North America, species distribution models were improved by including variables related to fire. Models for changing species distributions would also be improved by considering potential changes to the fire regime.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-020-00079-9","usgsCitation":"van Wagtendonk, J., Moore, P., Yee, J.L., and Lutz, J.A., 2020, The distribution of woody species in relation to climate and fire in Yosemite National Park, California, USA: Fire Ecology, v. 16, 22, 23 p., https://doi.org/10.1186/s42408-020-00079-9.","productDescription":"22, 23 p.","ipdsId":"IP-117438","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":455198,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-020-00079-9","text":"Publisher Index Page"},{"id":379026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.13549804687501,\n 36.94989178681327\n ],\n [\n -118.24584960937499,\n 36.94989178681327\n ],\n [\n -118.24584960937499,\n 38.272688535980976\n ],\n [\n -120.13549804687501,\n 38.272688535980976\n ],\n [\n -120.13549804687501,\n 36.94989178681327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"van Wagtendonk, Jan W.","contributorId":189573,"corporation":false,"usgs":false,"family":"van Wagtendonk","given":"Jan W.","affiliations":[],"preferred":false,"id":800466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Peggy E","contributorId":242603,"corporation":false,"usgs":false,"family":"Moore","given":"Peggy E","affiliations":[{"id":48478,"text":"retired USGS WERC employee","active":true,"usgs":false}],"preferred":false,"id":800467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":800468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lutz, James A.","contributorId":139178,"corporation":false,"usgs":false,"family":"Lutz","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":800469,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215697,"text":"70215697 - 2020 - Differences in rhizosphere microbial communities between native and non‐native Phragmites australis may depend on stand density","interactions":[],"lastModifiedDate":"2020-10-29T15:20:49.581163","indexId":"70215697","displayToPublicDate":"2020-09-29T08:35:07","publicationYear":"2020","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}},"displayTitle":"Differences in rhizosphere microbial communities between native and non‐native Phragmites australis may depend on stand density","title":"Differences in rhizosphere microbial communities between native and non‐native Phragmites australis may depend on stand density","docAbstract":"Microorganisms surrounding plant roots may benefit invasive species through enhanced mutualism or decreased antagonism, when compared to surrounding native species. We surveyed the rhizosphere soil microbiome of a prominent invasive plant, Phragmites australis, and its co‐occurring native subspecies for evidence of microbial drivers of invasiveness. If the rhizosphere microbial community is important in driving plant invasions, we hypothesized that non‐native Phragmites would cultivate a different microbiome from native Phragmites, containing fewer pathogens, more mutualists, or both. We surveyed populations of native and non‐native Phragmites across Michigan and Ohio USA, and we described rhizosphere microbial communities using culture‐independent next‐generation sequencing. We found little evidence that native and non‐native Phragmites cultivate distinct bacterial, fungal, or oomycete rhizosphere communities. Microbial community differences in our Michigan survey were not associated with plant lineage but were mainly driven by environmental factors, such as soil saturation and nutrient concentrations. Intensive sampling along transects consisting of dense monocultures of each lineage and mixed zones revealed bacterial community differences between lineages in dense monoculture, but not in mixture. We found no evidence of functional differences in the microbial communities surrounding each lineage. We extrapolate that the invasiveness of non‐native Phragmites, when compared to its native congener, does not result from the differential cultivation of beneficial or antagonistic rhizosphere microorganisms.
South Florida’s coast is a land of contrasts that appeals to almost everyone, whether they seek out quiet natural environments along the mangrove waterways and in the wilderness of the Everglades or vibrant international culture in Miami. Yet this paradise is threatened by a number of forces – changing climate, rising sea level, and too many people, to name a few. Florida’s past is filled with stories of dramatic change and resiliency, if we look at the geologic record. It also hints at the role of climate alone, in the absence of significant sea level change, in shaping the mangrove coast. Using our knowledge of present-day processes, such as impacts of storms on the mangroves, combined with our interpretation of the past geologic record, is the best way to anticipate future changes. The question is, have humans altered this landscape so much that the species and habitats have lost their natural resiliency, and if they have, what will happen to the people and the unique environments of south Florida?
","language":"English","publisher":"Springer","doi":"10.1007/978-3-030-52383-1_12","usgsCitation":"Wingard, G.L., 2020, Climate, sea level, and people - Changing South Florida's mangrove coast, p. 189-211, https://doi.org/10.1007/978-3-030-52383-1_12.","productDescription":"23 p.","startPage":"189","endPage":"211","ipdsId":"IP-112945","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":380685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.4853515625,\n 24.926294766395593\n ],\n [\n -79.89257812499999,\n 24.926294766395593\n ],\n [\n -79.89257812499999,\n 27.01998400798257\n ],\n [\n -82.4853515625,\n 27.01998400798257\n ],\n [\n -82.4853515625,\n 24.926294766395593\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":805400,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70221555,"text":"70221555 - 2020 - Timescale methods for simplifying, understanding and modeling biophysical and water quality processes in coastal aquatic ecosystems: A review","interactions":[],"lastModifiedDate":"2021-06-23T12:39:32.793452","indexId":"70221555","displayToPublicDate":"2020-09-29T06:49:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Timescale methods for simplifying, understanding and modeling biophysical and water quality processes in coastal aquatic ecosystems: A review","docAbstract":"In this article, we describe the use of diagnostic timescales as simple tools for illuminating how aquatic ecosystems work, with a focus on coastal systems such as estuaries, lagoons, tidal rivers, reefs, deltas, gulfs, and continental shelves. Intending this as a tutorial as well as a review, we discuss relevant fundamental concepts (e.g., Lagrangian and Eulerian perspectives and methods, parcels, particles, and tracers), and describe many of the most commonly used diagnostic timescales and definitions. Citing field-based, model-based, and simple algebraic methods, we describe how physical timescales (e.g., residence time, flushing time, age, transit time) and biogeochemical timescales (e.g., for growth, decay, uptake, turnover, or consumption) are estimated and implemented (sometimes together) to illuminate coupled physical-biogeochemical systems. Multiple application examples are then provided to demonstrate how timescales have proven useful in simplifying, understanding, and modeling complex coastal aquatic systems. We discuss timescales from the perspective of “holism”, the degree of process richness incorporated into them, and the value of clarity in defining timescales used and in describing how they were estimated. Our objective is to provide context, new applications and methodological ideas and, for those new to timescale methods, a starting place for implementing them in their own work.
","language":"English","publisher":"MDPI","doi":"10.3390/w12102717","usgsCitation":"Lucas, L., and Deleersnijder, E., 2020, Timescale methods for simplifying, understanding and modeling biophysical and water quality processes in coastal aquatic ecosystems: A review: Water, v. 12, no. 10, 2717, 65 p., https://doi.org/10.3390/w12102717.","productDescription":"2717, 65 p.","ipdsId":"IP-119708","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":455205,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12102717","text":"Publisher Index Page"},{"id":386640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Lisa 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":818032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deleersnijder, Eric 0000-0003-0346-9667","orcid":"https://orcid.org/0000-0003-0346-9667","contributorId":260499,"corporation":false,"usgs":false,"family":"Deleersnijder","given":"Eric","email":"","affiliations":[{"id":52602,"text":"Université catholique de Louvain, Institute of Mechanics, Materials and Civil Engineering (IMMC) & Earth and Life Institute (ELI), Louvain-la-Neuve, Belgium","active":true,"usgs":false}],"preferred":false,"id":818033,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70214236,"text":"sim3460 - 2020 - Potentiometric surfaces, 2011–12, and water-level differences between 1995 and 2011–12, in wells of the “200-foot,” “500-foot,” and “700-foot” sands of the Lake Charles area, southwestern Louisiana","interactions":[],"lastModifiedDate":"2020-09-30T12:20:54.19763","indexId":"sim3460","displayToPublicDate":"2020-09-28T10:47:44","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3460","displayTitle":"Potentiometric Surfaces, 2011–12, and Water-Level Differences Between 1995 and 2011–12, in Wells of the “200-Foot,” “500-Foot,” and “700-Foot” Sands of the Lake Charles Area, Southwestern Louisiana","title":"Potentiometric surfaces, 2011–12, and water-level differences between 1995 and 2011–12, in wells of the “200-foot,” “500-foot,” and “700-foot” sands of the Lake Charles area, southwestern Louisiana","docAbstract":"Water levels were determined in 90 wells to prepare 2011–12 potentiometric surfaces focusing primarily on the “200-foot,” 500-foot,” and “700-foot” sands of the Lake Charles area, which are part of the Chicot aquifer system underlying Calcasieu and Cameron Parishes of southwestern Louisiana. These three aquifers provided 34 percent of the total water withdrawn and 93 percent of the groundwater withdrawn in Calcasieu and Cameron Parishes in 2012 (84.5 million gallons per day [Mgal/d]). This work was completed by the U.S. Geological Survey, in cooperation with the Louisiana Department of Transportation and Development, to assist in developing and evaluating groundwater-resource management strategies. The highest water levels determined in wells screened in the “200-foot,” “500-foot,” and “700-foot” sands were about 8 feet (ft) above the National Geodetic Vertical Datum of 1929 (NGVD 29), 2 ft below NGVD 29, and 14 ft below NGVD 29, respectively, and were located in northwestern Calcasieu Parish. The lowest water levels determined in wells screened in the “200-foot,” “500-foot,” and “700-foot” sands were approximately 50, 80, and 70 ft below NGVD 29, respectively, and were located in the southern Lake Charles metropolitan area, to the west of Prien Lake, and between the cities of Lake Charles and Sulphur, respectively. The primary groundwater flow direction in these three aquifers was radially towards pumping centers overlying the water-level lows. Comparisons of water-level differences in 42 wells measured in 1995 and 2011–12 indicated that the maximum increases in water levels for wells screened in the “200-foot,” “500-foot,” and “700-foot” sands were approximately 7, 31, and 19 ft, respectively. Water-level increases coincided with a decline in total groundwater withdrawals during the period (about 25 Mgal/d from 1995 to 2012) from these sands. More specifically, withdrawals from the “500-foot” sand affected water levels in wells screened in the “200-foot” and “700-foot” sands because the three are hydraulically connected and withdrawals from the “500-foot” sand were greater by volume than withdrawals from the “200-foot” and “700-foot” sands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3460","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Griffith, J.M., 2020, Potentiometric surfaces, 2011–12, and water-level differences between 1995 and 2011–12, in wells of the “200-foot,” “500-foot,” and “700-foot” sands of the Lake Charles area, southwestern Louisiana: U.S. Geological Survey Scientific Investigations Map 3460, 4 sheets, 11-p. pamphlet, https://dx.doi.org/10.3133/sim3460.","productDescription":"Pamphlet: viii, 11 p.; 4 Sheets: 32.00 x 28.00 inches or smaller","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-055171","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":378720,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3460/sim3460_sheet4.pdf","text":"Sheet 4","size":"932 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3460 Sheet 4"},{"id":378719,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3460/sim3460_sheet3.pdf","text":"Sheet 3","size":"1.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3460 Sheet 3"},{"id":378715,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3460/coverthb.jpg"},{"id":378718,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3460/sim3460_sheet2.pdf","text":"Sheet 2","size":"1.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3460 Sheet 2"},{"id":378716,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3460/sim3460_pamphlet.pdf","text":"Pamphlet","size":"499 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3460 Pamphlet"},{"id":378717,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3460/sim3460_sheet1.pdf","text":"Sheet 1","size":"1.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3460 Sheet 1"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lake Charles area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.812255859375,\n 29.6594160549124\n ],\n [\n -92.61474609375,\n 29.6594160549124\n ],\n [\n -92.61474609375,\n 30.524413269923986\n ],\n [\n -93.812255859375,\n 30.524413269923986\n ],\n [\n -93.812255859375,\n 29.6594160549124\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Reconstructed prairies can provide habitat for pollinating insects, an important ecosystem service. To optimize reconstructions for pollinators, goals may include enhancing flowering plant cover and richness and increasing bloom availability early and late in the growing season. Resistance to invasive exotic species must also be a goal in any reconstruction, but it is unclear how increasing forb richness and dominance may affect susceptibility to invasion. We compared planted forb richness and cover, cover of planted grasses, and persistence of exotic species 10 y post-planting of reconstructions with 58 species (extra-high richness), 34 species (high), 20 species (medium), and 10 species (low) planted at the same time in the same fields, and using the same methods and overall seeding rate at Neal Smith National Wildlife Refuge in Iowa, USA. Planted forb richness and cover were higher and planted warm-season, but not cool-season, grass cover was lower in the extra-high richness plots. Mean Coefficient of Conservatism was higher and there was less cover of exotic forbs in the extra-high richness plots. Cover of exotic cool-season grasses was greater in the extra-high richness plots than in the lower-richness plots and this trend was still increasing at the last sample date. Our results are encouraging in that we increased cover of pollinator-friendly habitat, but invasive grasses are a concern as they may reduce forb cover and opportunities for ground-nesting bees in the long term.
","language":"English","publisher":"BioOne","doi":"10.3375/043.040.0322","usgsCitation":"Drobney, P., Larson, D.L., Larson, J.L., and Viste-Sparkman, K., 2020, Toward improving pollinator habitat: Reconstructing prairies with high forb diversity: Natural Areas Journal, v. 40, no. 3, p. 252-261, https://doi.org/10.3375/043.040.0322.","productDescription":"10 p.","startPage":"252","endPage":"261","ipdsId":"IP-102057","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":455209,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3375/043.040.0322","text":"Publisher Index Page"},{"id":436776,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PCJV5G","text":"USGS data release","linkHelpText":"High forb diversity prairie reconstruction at Neal Smith NWR 2005-2015"},{"id":389148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Neal Smith 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 -93.31581115722656,\n 41.5201457403486\n ],\n [\n -93.23444366455078,\n 41.5201457403486\n ],\n [\n -93.23444366455078,\n 41.60902513908382\n ],\n [\n -93.31581115722656,\n 41.60902513908382\n ],\n [\n -93.31581115722656,\n 41.5201457403486\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drobney, Pauline","contributorId":178447,"corporation":false,"usgs":false,"family":"Drobney","given":"Pauline","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":823156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":823157,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Jennifer L 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":257024,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":823158,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viste-Sparkman, Karen","contributorId":197593,"corporation":false,"usgs":false,"family":"Viste-Sparkman","given":"Karen","email":"","affiliations":[],"preferred":false,"id":823159,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218208,"text":"70218208 - 2020 - Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes","interactions":[],"lastModifiedDate":"2021-02-19T20:33:29.170078","indexId":"70218208","displayToPublicDate":"2020-09-27T14:28:03","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes","docAbstract":"The largest explosive volcanic eruptions produce umbrella clouds that drive ash radially outward, enlarging the area that impacts aviation and ground-based communities. Models must consider the effects of umbrella spreading when forecasting hazards from these eruptions. In this paper we test a version of the advection–dispersion model Ash3d that considers umbrella spreading by comparing its simulations with observations from three well-documented umbrella-forming eruptions: (1) the 15 June 1991 eruption of Pinatubo (Philippines); (2) the 13 February 2014 eruption of Kelud (Indonesia); and (3) phase 2 of the 22–23 April 2015 eruption of Calbuco (Chile). In volume, these eruptions ranged from several cubic kilometers dense-rock equivalent (DRE) for Pinatubo to about one tenth for Calbuco. In mass eruption rate (MER), they ranged from 108–109 kg s−1 at Pinatubo to 9–16 × 106 kg s−1 at Calbuco. For each case we ran simulations that considered umbrella growth and ones that did not. All umbrella-cloud simulations produced a cloud whose area was within ~25% of the observed cloud by the end of the eruption. By the eruption end, the simulated areas of the Pinatubo, Kelud, and Calbuco clouds were 851, 53.2, and 100 × 103 km2 respectively. These areas were 2.2, 2.2, and 1.5 times the areas calculated in simulations that ignored umbrella growth. For Pinatubo and Kelud, the umbrella simulations provided better agreement with the observed cloud area than the non-umbrella simulations. Each of these simulations extended 24 h from the eruption start. After the eruption ended, the difference in cloud area (umbrella minus non-umbrella) at Pinatubo persisted for many hours; at Kelud it diminished and became negative after 14 h and at Calbuco it became negative after ~23 h. The negative differences were inferred to result from the fact that non-umbrella simulations distributed ash over a wider vertical extent in the plume, and that wind shear spread the cloud out in multiple directions. Thus, for some smaller eruptions, wind shear can produce a larger cloud than might be produced by umbrella spreading alone.
","language":"English","publisher":"MDPI","doi":"10.3390/atmos11101038","usgsCitation":"Mastin, L.G., and Van Eaton, A.R., 2020, Comparing simulations of umbrella-cloud growth and ash transport with observations from Pinatubo, Kelud, and Calbuco volcanoes: Atmosphere, v. 11, no. 10, 1038, 21 p., https://doi.org/10.3390/atmos11101038.","productDescription":"1038, 21 p.","ipdsId":"IP-121394","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":455211,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos11101038","text":"Publisher Index Page"},{"id":436777,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NPYCRH","text":"USGS data release","linkHelpText":"Observations and model simulations of umbrella-cloud growth during eruptions of Mount Pinatubo (Philippines, June 15, 1991), Kelud Volcano (Indonesia, February 14, 2014), and Calbuco Volcano (Chile, April 22-23, 2015)"},{"id":383397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile, Indonesia, Philippines","otherGeospatial":"Calbuco volcano, Kelud volcano, Pinatubo volcano","volume":"11","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-09-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810427,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217181,"text":"70217181 - 2020 - Effects of dewatering on behavior, distribution, and abundance of larval lampreys","interactions":[],"lastModifiedDate":"2021-01-11T14:43:47.441892","indexId":"70217181","displayToPublicDate":"2020-09-27T08:34:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of dewatering on behavior, distribution, and abundance of larval lampreys","docAbstract":"Anthropogenic dewatering of aquatic habitats can cause stranding and mortality of burrowed larval lampreys; however, the effects of dewatering have not been quantified. We assessed: (a) changes in spatial distribution, abundance, and emergence of larvae dewatered at Leaburg Reservoir (OR); (b) emergence and mortality of larvae dewatered in a laboratory; and (c) bias, precision, and interpretation of field results by simulation and modeling of laboratory results. In the field, we examined the distribution, abundance (by N‐mixture model), and density of larvae by electrofishing at randomly selected sites before dewatering and after refill, and assessed the emergence rate by observation and excavation during dewatering. Due to dewatering in the field, about 42% of larvae emerged and spatial distribution changed toward sites dewatered less than 20 hours. Estimated average density decreased from 10.8 larvae/m2 before dewatering to 2.3 larvae/m2 after refilling, suggesting that abundance declined by 79%; simulation suggested this decline ranged 71–84% (interquartile range). In the laboratory, we examined the emergence and mortality rates of larvae dewatered 0–48 hrs. The emergence rate in the laboratory was similar to that in the field. Mortality rate increased with hours dewatered and was higher for emerged than burrowed larvae. Laboratory estimates of mortality rate predicted a 61% decline in abundance if only burrowed larvae survived and a 54% decline if both burrowed and emerged larvae survived. Abundance declines in the field could be from mortality (e.g., desiccation, predation) and relocation to watered habitat. Our results indicate dewatering can substantially affect spatial distribution and abundance of larval lampreys in freshwater ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3730","usgsCitation":"Harris, J.E., Skalicky, J.J., Liedtke, T.L., Weiland, L.K., Clemens, B.J., and Gray, A.E., 2020, Effects of dewatering on behavior, distribution, and abundance of larval lampreys: River Research and Applications, v. 36, no. 10, p. 2001-2012, https://doi.org/10.1002/rra.3730.","productDescription":"12 p.","startPage":"2001","endPage":"2012","ipdsId":"IP-119069","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":382054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Leaburg Reservoir, McKenzie River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.068603515625,\n 43.75522505306928\n ],\n [\n -121.36596679687499,\n 43.75522505306928\n ],\n [\n -121.36596679687499,\n 45.706179285330855\n ],\n [\n -124.068603515625,\n 45.706179285330855\n ],\n [\n -124.068603515625,\n 43.75522505306928\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-09-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Julianne E. 0000-0003-1343-5911","orcid":"https://orcid.org/0000-0003-1343-5911","contributorId":247527,"corporation":false,"usgs":false,"family":"Harris","given":"Julianne","email":"","middleInitial":"E.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":807857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skalicky, Joseph J. 0000-0002-6467-5037","orcid":"https://orcid.org/0000-0002-6467-5037","contributorId":247528,"corporation":false,"usgs":false,"family":"Skalicky","given":"Joseph","email":"","middleInitial":"J.","affiliations":[{"id":49569,"text":"U.S. Fish and Wildlife Service, Columbia River Fish and Wildlife Conservation Office, 1211 SE Cardinal Court, Suite 100, Vancouver, Washington 98683","active":true,"usgs":false}],"preferred":false,"id":807858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":807859,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiland, Lisa K. 0000-0002-9729-4062 lweiland@usgs.gov","orcid":"https://orcid.org/0000-0002-9729-4062","contributorId":3565,"corporation":false,"usgs":true,"family":"Weiland","given":"Lisa","email":"lweiland@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":807860,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":807861,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gray, Ann E.","contributorId":195113,"corporation":false,"usgs":false,"family":"Gray","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":807862,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70214530,"text":"70214530 - 2020 - Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","interactions":[],"lastModifiedDate":"2020-09-30T14:56:14.381095","indexId":"70214530","displayToPublicDate":"2020-09-26T09:49:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate","docAbstract":"Hydrology is a critical driver controlling mangrove wetlands structural and functional attributes at different spatial and temporal scales. Yet, human activities have negatively affected hydrology, causing mangrove diebacks and coverage loss worldwide. In fact, the assessment of mangrove water budgets, impacted by natural and human disturbances, is limited due to a lack of long-term data and information that hinders our understanding of how changes in hydroperiod and salinity control mangrove productivity and spatial distribution. In this study, we implemented a mass balance-based hydrological model (RHYMAN) that explicitly considers groundwater discharge in the Shark River estuary (SRE, southwestern Everglades) located in a karstic geomorphic setting and influenced by regional hydrological restoration. We used long-term hydroperiod and porewater salinity (PWS) datasets obtained from 2004 to 2016 for model calibration and validation and to determine spatiotemporal variability in water levels and PWS at three riverine mangrove sites (downstream, SRS-6; midstream, SRS-5; upstream, SRS-4) along SRE. Model results agree with a distinct PWS pattern along the estuarine salinity gradient where the highest PWS occurs at SRS-6 (mean: 25, range: 22–30 ppt), followed by SRS-5 (17, 14–25 ppt) and SRS-4 (5, 3–13 ppt). A commensurate increase in PWS over a thirteen-year period indicates a long-term reduction in freshwater inflow coupled with sea-level rise (SLR). Increasing freshwater scenario simulation results show a significant reduction (17–27%) in PWS along the estuary in contrast with a high SLR scenario when salinity increases up to 1.1 to 2.5 times that of control values. Model results show that freshwater inflow and SLR are key drivers controlling mangrove wetlands PWS in this karstic coastal region. Given its relatively simple structure, this mass balance-based hydrological model could be used in other environmental settings to evaluate potential habitat and regime shifts due to changes in hydrology and PWS under regional hydrological restoration management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2020.109292","usgsCitation":"Zhao, X., Rivera-Monroy, V.H., Wang, H., Xue, Z., Tsai, C., Willson, C.S., Castañeda-Moya, E., and Twilley, R.R., 2020, Modeling soil porewater salinity in mangrove forests (Everglades, Florida, USA) impacted by hydrological restoration and a warming climate: Ecological Modelling, v. 436, 109292, 18 p., https://doi.org/10.1016/j.ecolmodel.2020.109292.","productDescription":"109292, 18 p.","ipdsId":"IP-117526","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://repository.lsu.edu/civil_engineering_pubs/1184","text":"Publisher Index Page"},{"id":378913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.9085693359375,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 25.06072125231416\n ],\n [\n -80.3814697265625,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 26.48532391504829\n ],\n [\n -81.9085693359375,\n 25.06072125231416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"436","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhao, Xiaochen","contributorId":219696,"corporation":false,"usgs":false,"family":"Zhao","given":"Xiaochen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rivera-Monroy, Victor H. 0000-0003-2804-4139","orcid":"https://orcid.org/0000-0003-2804-4139","contributorId":200322,"corporation":false,"usgs":false,"family":"Rivera-Monroy","given":"Victor","email":"","middleInitial":"H.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":219641,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":799836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xue, Zuo 0000-0003-4018-0248","orcid":"https://orcid.org/0000-0003-4018-0248","contributorId":241655,"corporation":false,"usgs":false,"family":"Xue","given":"Zuo","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799837,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tsai, Cheng-Feng","contributorId":241949,"corporation":false,"usgs":false,"family":"Tsai","given":"Cheng-Feng","email":"","affiliations":[],"preferred":false,"id":799838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willson, C. S.","contributorId":90440,"corporation":false,"usgs":false,"family":"Willson","given":"C.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":799839,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Castañeda-Moya, E. 0000-0001-7759-4351","orcid":"https://orcid.org/0000-0001-7759-4351","contributorId":241657,"corporation":false,"usgs":false,"family":"Castañeda-Moya","given":"E.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":799840,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Twilley, Robert R.","contributorId":34585,"corporation":false,"usgs":false,"family":"Twilley","given":"Robert","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":799841,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216169,"text":"70216169 - 2020 - Climate- versus geographic-dependent patterns in the spatial distribution ofmacroinvertebrate assemblages in New World depressional wetlands","interactions":[],"lastModifiedDate":"2023-03-27T17:09:04.907627","indexId":"70216169","displayToPublicDate":"2020-09-26T09:44:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Climate- versus geographic-dependent patterns in the spatial distribution ofmacroinvertebrate assemblages in New World depressional wetlands","docAbstract":"Analyses of biota at lower latitudes may presage impacts of climate change on biota at higher latitudes. Macroinvertebrate assemblages in depressional wetlands may be especially sensitive to climate change because weather‐related precipitation and evapotranspiration are dominant ecological controls on habitats, and organisms of depressional wetlands are temperature‐sensitive ectotherms. We aimed to better understand how wetland macroinvertebrate assemblages were structured according to geography and climate. To do so, we contrasted aquatic‐macroinvertebrate assemblage structure (family level) between subtropical and temperate depressional wetlands of North and South America using presence–absence data from 264 of these habitats across the continents and more‐detailed relative‐abundance data from 56 depressional wetlands from four case‐study locations (North Dakota and Georgia in North America; southern Brazil and Argentinian Patagonia in South America). Both data sets roughly partitioned wetland numbers equally between the two climatic zones and between the continents. We used ordination methods (PCA and NMDS) and tests of multivariate dispersion (PERMDISP) to assess the distribution and the homogeneity in variation in the composition of macroinvertebrate assemblages across climates and continents, respectively. We found that macroinvertebrate assemblage structures in the subtropical depressional wetlands of North and South America were similar to each other (at the family level), while assemblages in the North and South American temperate wetlands were unique from the subtropics, and from each other. Tests of homogeneity of multivariate dispersion indicated that family‐level assemblage structures were more homogeneous in wetlands from the subtropical than the temperate zones. Our study suggests that ongoing climate change may result in the homogenization of macroinvertebrate assemblage structures in temperate zones of North and South America, with those assemblages becoming enveloped by assemblages from the subtropics. Biotic homogenization, more typically associated with other kinds of anthropogenic factors, may also be affected by climate change.
No abstract available.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020EO149557","usgsCitation":"Nadeau, P.A., Diefenbach, A., Hurwitz, S., and Swanson, D., 2020, From lava to water: A new era at Kīlauea: Eos, Earth and Space Science News, 11 p., https://doi.org/10.1029/2020EO149557.","productDescription":"11 p.","ipdsId":"IP-118975","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":455216,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020eo149557","text":"Publisher Index Page"},{"id":378964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.29329299926758,\n 19.39471557731923\n ],\n [\n -155.23681640625,\n 19.39471557731923\n ],\n [\n -155.23681640625,\n 19.4395612768183\n ],\n [\n -155.29329299926758,\n 19.4395612768183\n ],\n [\n -155.29329299926758,\n 19.39471557731923\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nadeau, Patricia A. 0000-0002-6732-3686","orcid":"https://orcid.org/0000-0002-6732-3686","contributorId":215616,"corporation":false,"usgs":true,"family":"Nadeau","given":"Patricia","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":800326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":800327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":800328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swanson, Donald A. 0000-0002-1680-3591","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":229682,"corporation":false,"usgs":true,"family":"Swanson","given":"Donald A.","affiliations":[],"preferred":true,"id":800329,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216653,"text":"70216653 - 2020 - Illegal killing of nongame wildlife and recreational shooting in conservation areas","interactions":[],"lastModifiedDate":"2020-11-30T12:43:39.435349","indexId":"70216653","displayToPublicDate":"2020-09-25T11:09:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Illegal killing of nongame wildlife and recreational shooting in conservation areas","docAbstract":"Illegal killing of nongame wildlife is a global yet poorly documented problem. The prevalence and ecological consequences of illegal killing are often underestimated or completely unknown. We review the practice of legal recreational shooting and present data gathered from telemetry, surveys, and observations on its association with illegal killing of wildlife (birds and snakes) within conservation areas in Idaho, USA. In total, 33% of telemetered long‐billed curlews (Numenius americanus) and 59% of other bird carcasses found with known cause of death (or 32% of total) were illegally shot. Analysis of spatial distributions of illegal and legal shooting is consistent with birds being shot illegally in the course of otherwise legal recreational shooting, but snakes being intentionally sought out and targeted elsewhere, in locations where they congregate. Preliminary public surveys indicate that most recreational shooters find abhorrent the practice of illegal killing of wildlife. Viewed through this lens, our data may imply only a small fraction of recreational shooters is responsible for this activity. This study highlights a poorly known conservation problem that could have broad implications for some species and populations of wildlife.
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.279","usgsCitation":"Katzner, T., Carlisle, J.D., Poessel, S.A., Thomason, E.C., Pauli, B.P., Pilliod, D.S., Belthoff, J.R., Heath, J.A., Parker, K.J., Warner, K.S., Hayes, H., Aberg, M., Ortiz, P., Amdor, S., Alsup, S., Coates, S.E., Miller, T.A., and Duran, Z.K., 2020, Illegal killing of nongame wildlife and recreational shooting in conservation areas: Conservation Science and Practice, v. 2, no. 11, e279, 15 p., https://doi.org/10.1111/csp2.279.","productDescription":"e279, 15 p.","ipdsId":"IP-117712","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":455217,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.279","text":"Publisher Index Page"},{"id":380846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Physical and economic data about water in many nations are becoming more widely integrated through application of the System of Environmental-Economic Accounts for Water (SEEA-Water), which enables the tracking of linkages between water and the economy. We present the first national and subnational SEEA-Water accounts for the United States. We compile accounts for water: (1) physical supply and use, (2) productivity, (3) quality, and (4) emissions for roughly the years 2000 to 2015. Total U.S. water use declined by 22% from 2000 to 2015, falling in 44 states though groundwater use increased in 21 states. Water-use reductions, combined with economic growth, led to increases in water productivity for the overall national economy (65%), mining (99%), and agriculture (68%). Surface-water quality trends were most evident at regional levels, and differed by water-quality constituent and region. This work provides (1) a baseline of recent historical water resource trends and their value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.
heir value in the U.S., and (2) a roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term water resources trends.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2020.101182","usgsCitation":"Bagstad, K.J., Ancona, Z.H., Hass, J.L., Glynn, P.D., Wentland, S., Vardon, M., and Fay, J.P., 2020, Integrating physical and economic data into experimental water accounts for the United States: Lessons and opportunities: Ecosystem Services, v. 45, 101182, 21 p., https://doi.org/10.1016/j.ecoser.2020.101182.","productDescription":"101182, 21 p.","ipdsId":"IP-104799","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455220,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoser.2020.101182","text":"Publisher Index Page"},{"id":436779,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TUTMAT","text":"USGS data release","linkHelpText":"Data release for Integrating physical and economic data into experimental water accounts for the 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Arizona","interactions":[],"lastModifiedDate":"2020-12-29T21:37:34.223766","indexId":"70214980","displayToPublicDate":"2020-09-25T09:03:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Predicting bird guilds using vegetation composition and structure on a wild and scenic river in Arizona","docAbstract":"Riparian areas are among the most ecologically diverse terrestrial ecosystems but make up <2% of landscape area in southwestern USA. Many species of resident and neotropical migratory birds utilize riparian habitats for breeding, foraging, and nesting. We quantified vegetation composition and structure to predict bird guilds on Wild and Scenic portions of the Verde River, Arizona. We grouped plant species into guilds based on similar functional traits to describe composition. We surveyed birds during the breeding and migrating season to determine abundance and categorized species into guilds using preferences of breeding habitat, foraging substrate, and nest placement. Riparian obligate and facultative breeding guilds were most common. Both vegetation composition and structure were useful predictors of birds. Vegetation structure was most complex in gallery riparian forest. Abundance of riparian-obligate birds in the breeding guild were positively associated with vegetation structure of dense, multi-canopy canopy and tall trees. Abundance of most bird guilds were positively associated with composition of tall trees (Populus fremontii, Salix gooddingii) and drought tolerant shrubs (Prosopis velutina, Celtis reticulata). Our findings show complex riparian habitat important to wildlife is created by both composition and structure of near-stream vegetation that is tied to hydrology and sensitive to flow change.
Spanning Canada, the United States, and Mexico, North America contains two populations of the migratory monarch butterfly (Danaus plexippus). The smaller “western” population overwinters in groves along the California coast and breeds west of the Rocky Mountains, while the much larger “eastern” population breeds east of the Rocky Mountains and overwinters in Oyamel fir forests in central Mexico. Both populations have declined in the last 20 to 30 years, leading to a formal petition in 2014 to list the species as threatened or endangered under the US Endangered Species Act (ESA) and a recommendation in 2016 for listing as endangered under the Canadian Species at Risk act.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2020.576281","usgsCitation":"Diffendorfer, J., Thogmartin, W.E., Drum, R.G., and Schultz, C.B., 2020, Editorial: North American monarch butterfly ecology and conservation: Frontiers in Ecology and Conservation, v. 8, 576281, 4 p., https://doi.org/10.3389/fevo.2020.576281.","productDescription":"576281, 4 p.","ipdsId":"IP-118385","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":455223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.576281","text":"Publisher Index Page"},{"id":403469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United 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Maria L.","contributorId":292974,"corporation":false,"usgs":false,"family":"Pappas","given":"Maria","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":846363,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":846331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":846332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drum, Ryan G.","contributorId":171941,"corporation":false,"usgs":false,"family":"Drum","given":"Ryan","email":"","middleInitial":"G.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":846333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Cheryl B. 0000-0003-3388-8950","orcid":"https://orcid.org/0000-0003-3388-8950","contributorId":292946,"corporation":false,"usgs":false,"family":"Schultz","given":"Cheryl","middleInitial":"B.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":846334,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216488,"text":"70216488 - 2020 - Sea‐level rise will drive divergent sediment transport patterns on fore reefs and reef flats, potentially causing erosion on atoll islands","interactions":[],"lastModifiedDate":"2020-11-23T14:12:16.975375","indexId":"70216488","displayToPublicDate":"2020-09-25T07:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7358,"text":"Journal of Geophysical Research – Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sea‐level rise will drive divergent sediment transport patterns on fore reefs and reef flats, potentially causing erosion on atoll islands","docAbstract":"Atoll reef islands primarily consist of unconsolidated sediment, and their ocean‐facing shorelines are maintained by sediment produced and transported across their reefs. Changes in incident waves can alter cross‐shore sediment exchange and, thus, affect the sediment budget and morphology of atoll reef islands. Here we investigate the influence of sea level rise and projected wave climate change on wave characteristics and cross‐shore sediment transport across an atoll reef at Kwajalein Island, Republic of the Marshall Islands. Using a phase‐resolving model, we quantify the influence on sediment transport of quantities not well captured by wave‐averaged models, namely, wave asymmetry and skewness and flow acceleration. Model results suggest that for current reef geometry, sea level, and wave climate, potential bedload transport is directed onshore, decreases from the fore reef to the beach, and is sensitive to the influence of flow acceleration. We find that a projected 12% decrease in annual wave energy by 2100 CE has negligible influence on reef flat hydrodynamics. However, 0.5–2.0 m of sea level rise increases wave heights, skewness, and shear stress on the reef flat and decreases wave skewness and shear stress on the fore reef. These hydrodynamic changes decrease potential sediment inputs onshore from the fore reef where coral production is greatest but increase potential cross‐reef sediment transport from the outer reef flat to the beach. Assuming sediment production on the fore reef remains constant or decreases due to increasing ocean temperatures and acidification, these processes have the potential to decrease net sediment delivery to atoll islands, causing erosion.
Stream fish survival and recruitment are products of a physicochemical environment that affects growth and provides refuge; yet, the drivers of spatiotemporal variation in juvenile fish abundance remain unclear. Understanding how physicochemical conditions drive spatial and temporal patterns in fish abundances provides insight into how conditions across stream networks influence fish population success, thereby providing direction to managers about the types and locations of conservation actions that would be most beneficial. Using snorkel and habitat surveys of 120 sites sampled from 2015 to 2017, we evaluated the multiscale relationships among physicochemical features, hydrology, and age-0 Smallmouth Bass (Micropterus dolomieu velox) abundance in relation to network spatial position. Abundance of age-0 bass was spatiotemporally variable in relation to a July streamflow–network position interaction, a pool depth–stream size interaction, and a stream temperature–network position interaction. High flows at the end of the nesting season were related to lower age-0 abundance, but this effect was dampened in stream reaches in close proximity to larger mainstems. In small streams, reaches with deeper pool habitat supported higher age-0 bass abundances, but this trend was not apparent in larger tributaries and mainstem systems. Generally, colder streams had lower age-0 Smallmouth Bass abundance, though this relationship was not apparent in reaches adjacent to larger streams that generally supported higher age-0 bass abundances. Conservation actions that (1) facilitate habitat connectivity within and among streams, (2) limit future anthropogenic practices that alter natural geomorphology by creating shallower stream channels, and (3) maintain adequate flow magnitude and timing to support channel complexity (e.g., deeper pools within smaller catchments) would be most beneficial to supporting rearing habitat for age-0 riverine Smallmouth Bass.