The clupeid gizzard shad Dorosoma cepedianum is often the most abundant fish species in North American reservoirs, and this dominance can have cascading trophic effects on entire fish assemblages. Accordingly, a key aspect of managing reservoir fish assemblages involves controlling gizzard shad densities. We used a 33-year time series to evaluate the relative importance of parental stock density, winter temperature, and water regime on recruitment of age-0 gizzard shad in a large reservoir. Recruitment modeled with a Ricker-type curve increased with the size of the adult stock, peaked, and then decreased at high stock densities. This over-compensatory stock-recruitment relationship was made more dynamic by fluctuations in inflow, with recruitment increasing in years of high inflow, however there was no temperature effect at the latitude of the study site. The influence of stock size on recruitment was roughly twice as high as the influence of inflow. This study is the first to report stock-recruitment relationships for a clupeid species in a reservoir and concurs with analyses of marine fishes that have shown that most clupeids exhibit compensatory or over-compensatory patterns in their stock-recruitment relationships.
More than a century of dam construction and water development in the western United States has led to extensive ecological alteration of rivers. Growing interest in improving river function is compelling practitioners to consider ecological restoration when managing dams and water extraction. We developed an Ecological Response Model (ERM) for the Cache la Poudre River, northern Colorado, USA, to illuminate effects of current and possible future water management and climate change. We used empirical data and modeled interactions among multiple ecosystem components to capture system-wide insights not possible with the unintegrated models commonly used in environmental assessments. The ERM results showed additional flow regime modification would further alter the structure and function of Poudre River aquatic and riparian ecosystems due to multiple and interacting stressors. Model predictions illustrated that specific peak flow magnitudes in spring and early summer are critical for substrate mobilization, dynamic channel morphology, and overbank flows, with strong subsequent effects on instream and riparian biota that varied seasonally and spatially, allowing exploration of nuanced management scenarios. Instream biological indicators benefitted from higher and more stable base flows and high peak flows, but stable base flows with low peak flows were only half as effective to increase indicators. Improving base flows while reducing peak flows, as currently proposed for the Cache la Poudre River, would further reduce ecosystem function. Modeling showed that even presently depleted annual flow volumes can achieve substantially different ecological outcomes in designed flow scenarios, while still supporting social demands. Model predictions demonstrated that implementing designed flows in a natural pattern, with attention to base and peak flows, may be needed to preserve or improve ecosystem function of the Poudre River. Improved regulatory policies would include preservation of ecosystem-level, flow-related processes and adaptive management when water development projects are considered.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2005","usgsCitation":"Bestgen, K.R., Poff, N.L., Baker, D.W., Bledsoe, B.P., Merritt, D.M., Lorie, M., Auble, G.T., Sanderson, J.S., and Kondratieff, B.C., 2020, Designing flows to enhance ecosystem functioning in heavily altered rivers: Ecological Applications, v. 30, no. 1, e02005, 19 p., https://doi.org/10.1002/eap.2005.","productDescription":"e02005, 19 p.","ipdsId":"IP-104612","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":458644,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2005","text":"Publisher Index Page"},{"id":387388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Cache la Poudre River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.029052734375,\n 40.32351403031129\n ],\n [\n -104.48272705078124,\n 40.32351403031129\n ],\n [\n -104.48272705078124,\n 40.81796653313175\n ],\n [\n -106.029052734375,\n 40.81796653313175\n ],\n [\n -106.029052734375,\n 40.32351403031129\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bestgen, Kevin R. 0000-0001-8691-2227","orcid":"https://orcid.org/0000-0001-8691-2227","contributorId":171573,"corporation":false,"usgs":false,"family":"Bestgen","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":819651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poff, N. LeRoy","contributorId":261271,"corporation":false,"usgs":false,"family":"Poff","given":"N.","email":"","middleInitial":"LeRoy","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":819652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baker, Daniel W","contributorId":261272,"corporation":false,"usgs":false,"family":"Baker","given":"Daniel","email":"","middleInitial":"W","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":819654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bledsoe, Brian P.","contributorId":140605,"corporation":false,"usgs":false,"family":"Bledsoe","given":"Brian","email":"","middleInitial":"P.","affiliations":[{"id":13538,"text":"Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":819653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Merritt, David M.","contributorId":192229,"corporation":false,"usgs":false,"family":"Merritt","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":24595,"text":"USDA Forest Service, Fort Collins CO","active":true,"usgs":false}],"preferred":false,"id":819655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lorie, Mark","contributorId":172964,"corporation":false,"usgs":false,"family":"Lorie","given":"Mark","email":"","affiliations":[],"preferred":false,"id":819749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Auble, Gregor T. 0000-0002-0843-2751 aubleg@usgs.gov","orcid":"https://orcid.org/0000-0002-0843-2751","contributorId":2187,"corporation":false,"usgs":true,"family":"Auble","given":"Gregor","email":"aubleg@usgs.gov","middleInitial":"T.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":819656,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sanderson, John S.","contributorId":210638,"corporation":false,"usgs":false,"family":"Sanderson","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":819657,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kondratieff, Boris C.","contributorId":24868,"corporation":false,"usgs":false,"family":"Kondratieff","given":"Boris","email":"","middleInitial":"C.","affiliations":[{"id":17860,"text":"Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":819658,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70209105,"text":"70209105 - 2020 - Apatite trace element geochemistry and cathodoluminescent textures—Acomparison between regional magmatism and the Pea Ridge IOA-REE andBoss IOCG deposits, southeastern Missouri iron metallogenic province, USA","interactions":[],"lastModifiedDate":"2020-03-16T16:43:43","indexId":"70209105","displayToPublicDate":"2019-09-17T16:37:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Apatite trace element geochemistry and cathodoluminescent textures—Acomparison between regional magmatism and the Pea Ridge IOA-REE andBoss IOCG deposits, southeastern Missouri iron metallogenic province, USA","docAbstract":"The southeast Missouri iron metallogenic province contains a remarkable wealth of historically important Fe, Cu, Au, and rare earth element (REE) deposits including the Pea Ridge iron oxide-apatite-rare earth element (IOA-REE) deposit and the Boss iron oxide-copper-gold (IOCG) deposit. These deposits are coeval with silicic and intermediate composition magmatism in the St. Francois Mountains terrane. Magmatism, iron-oxide (±Cu, Au, Co) and apatite formation, and REE mineralization overlapped in space and time, but the specific role of regional magmatism in the metallogenesis of these deposits remains unclear and basic petrogenetic models are still debated. \nWe report results from high-spatial resolution textural and geochemical analyses of apatite from regional igneous and ore rocks to elucidate their petrogenetic histories and evaluate deposit models. Backscattered electron and spectral cathodoluminescence imaging of apatite reveal no primary igneous zoning, but show different domains with intricate rims and dissolution/reprecipitation textures, each with distinctive REE patterns in many samples. Apatite from all samples are nearly endmember fluorapatite containing up to ~1.3 wt% Cl and F/Cl ratios span nearly three orders of magnitude. Fresh igneous fluorapatite contain low Na2O (0.15 wt%) while most Pea Ridge ore samples contain higher Na2O (up to ~0.45 wt%), and concentrations of sulfur in fluorapatite of all types are generally moderate to low (0.3 wt% SO3). Significant amounts of Fe (60,000 ppm), Mg (30,000 ppm), Mn (7,000 ppm), and Sr (12,000 ppm) are contained in fluorapatite of all sample types, and they also have moderate amounts of As (4,000 ppm), Ba (2,000 ppm), Th (400 ppm), and U (80 ppm). Fluorapatite show an extraordinarily large range of REE (~0.1-2.0 wt%) and Y (~100-7000 ppm) concentrations. While fresh igneous fluorapatite share many geochemical features with metasomatized igneous fluorapatite and ore-stage fluorapatite from the Pea Ridge IOA and Boss IOCG ore zones, they also have distinct geochemical signatures that are indicative of unique trace element partitioning and substitution mechanisms. These distinguishing textural and geochemical signatures preclude ore-zone fluorapatite genesis directly from a magma (i.e., crystallization directly from a silicate melt) but are permissive of ore-zone fluorapatite formation by magmatic-hydrothermal fluids derived from the regional magmas. Basinal brines may play an important role in the formation of fluorapatite, especially from the Pea Ridge hematite and Boss magnetite-rich zones. Fluorapatite from different ore zones likely formed by crystallization during pulses of hydrothermal fluids with varying Cl-, Na-, and F-contents, which fundamentally controlled the carrying capacity and solubility of REE+Y and generated geochemically distinctive generations of fluorapatite. \nExploration geologists using fluorapatite trace element geochemistry to identify IOA and IOCG deposits should proceed with caution, as more high-quality data from these deposits are needed to improve multivariate discrimination analysis. Fluorapatite from IOA/IOCG deposits can be reasonably discriminated from that of other mineral deposit types (e.g., porphyry/epithermal, skarn, orogenic), but no criteria successfully discriminate yet between IOA and IOCG deposits.","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2019.103129","usgsCitation":"Mercer, C.N., Watts, K., and Gross, J., 2020, Apatite trace element geochemistry and cathodoluminescent textures—Acomparison between regional magmatism and the Pea Ridge IOA-REE andBoss IOCG deposits, southeastern Missouri iron metallogenic province, USA: Ore Geology Reviews, v. 116, 103129, 22 p., https://doi.org/10.1016/j.oregeorev.2019.103129.","productDescription":"103129, 22 p.","ipdsId":"IP-102053","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":458647,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.oregeorev.2019.103129","text":"Publisher Index Page"},{"id":437217,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YIHMO8","text":"USGS data release","linkHelpText":"Geochemical data supporting a comparison of apatite between regional magmatism and the Pea Ridge Iron Oxide-Apatite-Rare Earth Element (IOA-REE) and Boss Iron Oxide-Copper-Cobalt-Gold-REE Deposits (IOCG) deposits, southeastern Missouri, USA"},{"id":373299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"St. Francois Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.944580078125,\n 36.62434536776987\n ],\n [\n -90.120849609375,\n 36.62434536776987\n ],\n [\n -90.120849609375,\n 38.363195134453846\n ],\n [\n -91.944580078125,\n 38.363195134453846\n ],\n [\n -91.944580078125,\n 36.62434536776987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"116","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mercer, Celestine N. 0000-0001-8359-4147 cmercer@usgs.gov","orcid":"https://orcid.org/0000-0001-8359-4147","contributorId":4006,"corporation":false,"usgs":true,"family":"Mercer","given":"Celestine","email":"cmercer@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":784950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":784951,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gross, Juliane 0000-0002-5288-0981","orcid":"https://orcid.org/0000-0002-5288-0981","contributorId":223401,"corporation":false,"usgs":false,"family":"Gross","given":"Juliane","email":"","affiliations":[{"id":40711,"text":"Rutgers State University of New Jersey","active":true,"usgs":false}],"preferred":false,"id":784953,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211968,"text":"70211968 - 2020 - Late Quaternary sea-level history of Saipan, Commonwealth of the Northern Mariana Islands, USA: A test of tectonic uplift and glacial isostatic adjustment models","interactions":[],"lastModifiedDate":"2020-08-12T20:53:20.311416","indexId":"70211968","displayToPublicDate":"2019-09-17T15:50:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Late Quaternary sea-level history of Saipan, Commonwealth of the Northern Mariana Islands, USA: A test of tectonic uplift and glacial isostatic adjustment models","docAbstract":"In 1979, S. Uyeda and H. Kanamori proposed a tectonic model with two end members of a subduction-boundary continuum: the “Chilean” type (shallow dip of the subducting plate, great thrust events, compression, and uplift of the overriding plate) and a “Mariana” type (steep dip of the subducting plate, no great thrust events, tension, and no uplift). This concept has been used to explain variable rates of Quaternary uplift around the Pacific Rim, yet no uplift rates have been determined for the Mariana Islands themselves, one of the end members in this model. We studied the late Quaternary Tanapag Limestone, which rims much of the eastern and southern coasts of Saipan, Northern Mariana Islands, with elevations of ∼13 m to ∼30 m. Samples from 12 well-preserved corals (Acropora, Porites, and Goniastrea) yielded U-series ages ranging from ca. 134 ka to ca. 126 ka. These ages correlate the emergent reef of the Tanapag Limestone with the last interglacial period, when sea level was several meters above present. Ages and measured reef elevations from the Tanapag Limestone, along with paleo–sea-level data, yield relatively low late Quaternary uplift rates of 0.002–0.19 m/k.y., consistent with the Uyeda-Kanamori model. A review of data from other localities near subduction zones around the Pacific Basin, however, indicates that many coastlines do not fit the model. Uplift rates along the Chilean coast are predicted to be relatively high, but field studies indicate they are low. On some coastlines, relatively high uplift rates are better explained by subduction of seamounts or submarine ridges rather than subduction zone geometry. Despite the low long-term uplift rate on Saipan, the island also hosts an emergent, low-elevation (+3.9–4.0 m) reef with corals in growth position below a notch (+4.2 m). The corals are dated to 3.9–3.1 ka. The occurrence of this young, emergent reef is likely not due to tectonic uplift; instead, it is interpreted to be the result of glacial isostatic adjustment processes after the end of the last glacial period. Our findings are consistent with similar observations on tectonically stable or slowly uplifting islands elsewhere in the equatorial Pacific Ocean and agree with numerical models of a higher-than-present Holocene sea level in this region due to glacial isostatic adjustment processes.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35162.1","usgsCitation":"Muhs, D., Schweig, E.S., and Simmons, K., 2020, Late Quaternary sea-level history of Saipan, Commonwealth of the Northern Mariana Islands, USA: A test of tectonic uplift and glacial isostatic adjustment models: Geological Society of America Bulletin, v. 132, p. 863-883, https://doi.org/10.1130/B35162.1.","productDescription":"21 p.","startPage":"863","endPage":"883","ipdsId":"IP-102631","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":377440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Mariana Islands, Saipan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 145.79887390136716,\n 15.166914868426344\n ],\n [\n 145.78445434570312,\n 15.205349599759678\n ],\n [\n 145.83663940429688,\n 15.268950303672504\n ],\n [\n 145.81260681152344,\n 15.298094191660693\n ],\n [\n 145.70960998535156,\n 15.223901791042142\n ],\n [\n 145.68214416503906,\n 15.117867306000468\n ],\n [\n 145.71578979492188,\n 15.097316980284674\n ],\n [\n 145.7549285888672,\n 15.088698509791715\n ],\n [\n 145.79887390136716,\n 15.166914868426344\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"132","noUsgsAuthors":false,"publicationDate":"2019-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":796005,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schweig, Eugene S. 0000-0003-3669-9741 schweig@usgs.gov","orcid":"https://orcid.org/0000-0003-3669-9741","contributorId":1271,"corporation":false,"usgs":true,"family":"Schweig","given":"Eugene","email":"schweig@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":796006,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simmons, Kathleen R. 0000-0002-7920-094X","orcid":"https://orcid.org/0000-0002-7920-094X","contributorId":229460,"corporation":false,"usgs":false,"family":"Simmons","given":"Kathleen R.","affiliations":[{"id":12608,"text":"USGS, retired","active":true,"usgs":false}],"preferred":false,"id":796007,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70207539,"text":"70207539 - 2020 - Local abundance of Ixodes scapularis in forests: Effects of environmental moisture, vegetation characteristics, and host abundance","interactions":[],"lastModifiedDate":"2019-12-25T08:45:05","indexId":"70207539","displayToPublicDate":"2019-09-14T11:28:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5082,"text":"Ticks and Tick-borne Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Local abundance of Ixodes scapularis in forests: Effects of environmental moisture, vegetation characteristics, and host abundance","title":"Local abundance of Ixodes scapularis in forests: Effects of environmental moisture, vegetation characteristics, and host abundance","docAbstract":"Ixodes scapularis is the primary vector of Lyme disease spirochetes in eastern and central North America, and local densities of this tick can affect human disease risk. We sampled larvae and nymphs from sites in Massachusetts and Wisconsin, USA, using flag/drag devices and by collecting ticks from hosts, and measured environmental variables to evaluate the environmental factors that affect local distribution and abundance of I. scapularis. Our sites were all forested areas with known I. scapularis populations. Environmental variables included those associated with weather (e.g., temperature and relative humidity), vegetation characteristics (at canopy, shrub, and ground levels), and host abundance (small and medium-sized mammals and reptiles). The numbers of larvae on animals at a given site and season showed a logarithmic relationship to the numbers in flag/drag samples, suggesting limitation in the numbers on host animals. The numbers of nymphs on animals showed no relationship to the numbers in flag/drag samples. These results suggest that only a small proportion of larvae and nymphs found hosts because in neither stage did the numbers of host-seeking ticks decline with increased numbers on hosts. Canopy cover was predictive of larval and nymphal numbers in flag/drag samples, but not of numbers on hosts. Numbers of small and medium-sized mammal hosts the previous year were generally not predictive of the current year’s tick numbers, except that mouse abundance predicted log numbers of nymphs on all hosts the following year. Some measures of larval abundance were predictive of nymphal numbers the following year. The mean number of larvae per mouse was well predicted by measures of overall larval abundance (based on flag/drag samples and samples from all hosts), and some environmental factors contributed significantly to the model. In contrast, the mean numbers of nymphs per mouse were not well predicted by environmental variables, only by overall nymphal abundance on hosts. Therefore, larvae respond differently than nymphs to environmental factors. Furthermore, flag/drag samples provide different information about nymphal numbers than do samples from hosts. Flag/drag samples can provide information about human risk of acquiring nymph-borne pathogens because they provide information on the densities of ticks that might encounter humans, but to understand the epizootiology of tick-borne agents both flag/drag and host infestation data are needed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ttbdis.2019.101271","usgsCitation":"Ginsberg, H., Rulison, E.L., Miller, J.L., Pang, G., Arsnoe, I.M., Hickling, G.J., Ogden, N.H., LeBrun, R.A., and Tsao, J.I., 2020, Local abundance of Ixodes scapularis in forests: Effects of environmental moisture, vegetation characteristics, and host abundance: Ticks and Tick-borne Diseases, v. 11, no. 1, 101271, 12 p., https://doi.org/10.1016/j.ttbdis.2019.101271.","productDescription":"101271, 12 p.","ipdsId":"IP-100963","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/136","text":"Publisher Index Page"},{"id":370668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, Wisconsin","otherGeospatial":"Cape Cod National Seashore, Fort McCoy","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.7470703125,\n 43.909765943908\n ],\n [\n -90.59326171875,\n 43.909765943908\n ],\n [\n -90.59326171875,\n 44.16841480642917\n ],\n [\n -90.7470703125,\n 44.16841480642917\n ],\n [\n -90.7470703125,\n 43.909765943908\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.23834228515625,\n 41.611335399441735\n ],\n [\n -69.90600585937499,\n 41.611335399441735\n ],\n [\n -69.90600585937499,\n 42.09007006868398\n ],\n [\n -70.23834228515625,\n 42.09007006868398\n ],\n [\n -70.23834228515625,\n 41.611335399441735\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":778394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rulison, Eric L.","contributorId":87478,"corporation":false,"usgs":false,"family":"Rulison","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":778395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Jasmine L.","contributorId":221487,"corporation":false,"usgs":false,"family":"Miller","given":"Jasmine","email":"","middleInitial":"L.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":778396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pang, Genevieve","contributorId":221488,"corporation":false,"usgs":false,"family":"Pang","given":"Genevieve","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":778397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arsnoe, Isis M.","contributorId":140902,"corporation":false,"usgs":false,"family":"Arsnoe","given":"Isis","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":778398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hickling, Graham J.","contributorId":140903,"corporation":false,"usgs":false,"family":"Hickling","given":"Graham","email":"","middleInitial":"J.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":778400,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":778401,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LeBrun, Roger A.","contributorId":70907,"corporation":false,"usgs":false,"family":"LeBrun","given":"Roger","email":"","middleInitial":"A.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":778402,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":778399,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70240961,"text":"70240961 - 2020 - Geoacoustic inversion for a New England mud patch sediment using the silt-suspension theory of marine mud","interactions":[],"lastModifiedDate":"2023-03-02T16:34:20.050478","indexId":"70240961","displayToPublicDate":"2019-09-13T10:28:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1941,"text":"IEEE Journal of Oceanic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Geoacoustic inversion for a New England mud patch sediment using the silt-suspension theory of marine mud","docAbstract":"This article provides an application of the silt-suspension theory to a Bayesian-inference inversion for the geo-acoustic parameters in marine mud. The theory, with consequences that have been developed recently, postulates a suspension of water and clay mineral card-houses that supports moderately dilute concentrations of silt particles. The approach is an example of a physically based model inversion, in which parameters representing physical mud-layer properties are obtained by inversion and used to produce estimates of geoacoustic properties, including their frequency dependence. The acoustic data are from a combustive source signal propagated along a track, located over several meters of fine-grained mud in the New England Mud Patch, to a single hydrophone on a receiver array during the 2017 Seabed Characterization Experiment. Data extracted from a nearby piston core inform the physical modeling, with selections of inversion parameters guided by both sensitivity analyses and bounds from archival and core measurements. Results show the feasibility of this inversion approach. The estimates of mud density and sound speed are close to values obtained independently. The frequency dependence of attenuation is estimated over the full low-frequency source band and has an approximate power exponent of 1.72.
","language":"English","publisher":"IEEE","doi":"10.1109/JOE.2019.2934604","usgsCitation":"Brown, E.M., Lin, Y., Chaytor, J., and Siegmann, W.L., 2020, Geoacoustic inversion for a New England mud patch sediment using the silt-suspension theory of marine mud: IEEE Journal of Oceanic Engineering, v. 45, no. 1, p. 144-160, https://doi.org/10.1109/JOE.2019.2934604.","productDescription":"17 p.","startPage":"144","endPage":"160","ipdsId":"IP-106813","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":413624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Elisabeth M.","contributorId":302803,"corporation":false,"usgs":false,"family":"Brown","given":"Elisabeth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":865499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Ying-Tsong","contributorId":302804,"corporation":false,"usgs":false,"family":"Lin","given":"Ying-Tsong","email":"","affiliations":[],"preferred":false,"id":865500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":865501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siegmann, William L.","contributorId":302805,"corporation":false,"usgs":false,"family":"Siegmann","given":"William","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":865502,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225149,"text":"70225149 - 2020 - Modeling strategies and evaluating success during repatriations of elusive and endangered species","interactions":[],"lastModifiedDate":"2021-10-14T12:39:18.475636","indexId":"70225149","displayToPublicDate":"2019-09-12T07:37:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":774,"text":"Animal Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Modeling strategies and evaluating success during repatriations of elusive and endangered species","docAbstract":"Wildlife repatriation is an important tool to decrease extinction risk for imperiled species, but successful repatriations require significant time, resources and planning. Because repatriations can be long and expensive processes, clear release strategies and monitoring programs are essential to efficiently use resources and evaluate success. However, monitoring can be challenging and surrounded by significant uncertainty, particularly for secretive species with extremely low detection probability. Here, we simulated how alternative repatriation strategies influence repatriation success for the eastern indigo snake Drymarchon couperi, a federally-Threatened species that is currently being repatriated in Alabama and Florida. Critically, we demonstrate how observed population growth can differ from true population growth when detection probabilities are low and mark-recapture analyses are not an option. Specifically, we built a stochastic stage-based population model to predict population growth and extinction risk under different release strategies and use information from ongoing repatriations to predict success and guide future releases. Because D. couperi is difficult to monitor, we modeled how detection probability influenced perceptions of abundance and population growth by monitoring programs. Simulated repatriation strategies releasing older, head-started snakes in greater abundance and frequency created wild populations with decreased extinction risk relative to scenarios releasing fewer and younger snakes less frequently. Ongoing repatriations currently have a 0.23 (Alabama) and 0.61 (Florida) probability of quasi-extinction, but extinction risk decreased to 0.07 and 0.10 at sites upon achieving the targeted number of releases. Abundances observed under realistic detection thresholds for D. couperi did not always predict true population growth; specifically, we demonstrate that monitoring programs during repatriations of secretive species may indicate that efforts have been unsuccessful when populations are actually growing. Overall, our modeling framework informs release strategies to maximize repatriation success while demonstrating the need to consider how detection processes influence assessment of success during conservation interventions.
Population density is an important component of wildlife management decisions, but can be difficult to estimate directly for an itinerant, wide‐ranging species such as the American black bear (Ursus americanus ). In South Carolina, USA, where there has been growth in black bear populations and bear–human‐conflict reports during the past several decades, managers need robust estimates of population size to inform management strategies. We used maximum‐likelihood capture–recapture models, using hair snares to collect DNA samples, to estimate density and abundance for a harvested population of black bear in northwestern South Carolina during 2013 to 2014. Models were tested in a spatially explicit framework using the secr package in Program R. Black bear density was estimated at 0.133 bears/km2 (SE = 0.034) in 2013 and 0.179 bears/km2 (SE = 0.043) in 2014. Black bear abundance in our study area was estimated to be 586 bears (SE = 95) in 2013 and 680 bears (SE = 128) in 2014, which are 2–3‐fold lower than previous estimates. We suggest that these estimates be considered a baseline for state biologists to employ in the population's management and in developing future harvest‐regulation strategies. Overall our study highlighted the potential for model choice to influence density estimates, and we concluded that spatially explicit models were appropriate for this study because geographic closure could not be assumed.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1007","usgsCitation":"Azad, S., McFadden, K., Clark, J.D., Wactor, T., and Jachowski, D., 2020, Applying spatially explicit capture–recapture models to estimate black bear density in South Carolina: Wildlife Society Bulletin, v. 43, no. 3, p. 500-507, https://doi.org/10.1002/wsb.1007.","productDescription":"8 p.","startPage":"500","endPage":"507","ipdsId":"IP-108028","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":499857,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/1934029e1d5c411d8e18f9f7abaa7f57","text":"External Repository"},{"id":376120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"south Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.936279296875,\n 35.10193405724606\n ],\n [\n -82.430419921875,\n 35.191766965947394\n ],\n [\n -83.1005859375,\n 35.003003395276714\n ],\n [\n -83.353271484375,\n 34.71452466170392\n ],\n [\n -83.023681640625,\n 34.49750272138159\n ],\n [\n -82.7490234375,\n 34.27083595165\n ],\n [\n -81.23291015625,\n 34.31621838080741\n ],\n [\n -81.03515625,\n 34.334364487026306\n ],\n [\n -80.936279296875,\n 35.10193405724606\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Azad, Shefali","contributorId":228811,"corporation":false,"usgs":false,"family":"Azad","given":"Shefali","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":792137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFadden, Katherine kwmcfadden@usgs.gov","contributorId":228812,"corporation":false,"usgs":false,"family":"McFadden","given":"Katherine","email":"kwmcfadden@usgs.gov","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":792138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":792139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wactor, Tammy","contributorId":228813,"corporation":false,"usgs":false,"family":"Wactor","given":"Tammy","email":"","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":792140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":792141,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206074,"text":"70206074 - 2020 - Historical changes in fish communities in urban streams of the southeastern U.S. and the relative importance of water-quality stressors","interactions":[],"lastModifiedDate":"2020-01-05T14:01:25","indexId":"70206074","displayToPublicDate":"2019-09-04T10:54:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Historical changes in fish communities in urban streams of the southeastern U.S. and the relative importance of water-quality stressors","docAbstract":"A total of 71 stream sites representing a gradient of urban land use was sampled across the Piedmont of the southeastern U.S. in 2014. Fish data collected (observed) at each site were compared to an expected community based on georeferenced historical (~1950 - ~1990) species occurrence records for stream segments (1:100,000 scale) containing the sampled stream sites. Loss of expected fish species (percent of fish species expected to occur but not observed) and homogenization (difference in Jaccard’s similarity of the fish community among sites observed and expected) were determined. On average, there was a 13.2% increase in the similarity of fish communities across sites, demonstrating evidence of community homogenization. Occurrence of Redbreast Sunfish (Lepomis auritus), Green Sunfish (L. cyanellus), and Bluegill (L. macrochirus) increased more than 50% over time (between observed and expected). Species loss increased significantly with urbanization whereas homogenization was not related to urbanization. Random forest analysis indicated that herbicides, insecticides, and centrarchid species richness were significant predictors of species loss. Of these, generalized additive model regression indicated that herbicides represented the most parsimonious model based on a single predictor. Stream base flow, elevation, and total nitrogen were significant predictors of homogenization. Generalized additive model regression indicated that decreased stream base flow was the single most important factor associated with increased homogenization. Chemical contaminants and associated ecosystem alteration and changes in stream flow may represent important regional influences on changes in fish communities in urban streams in the southeastern U.S.","language":"English","publisher":"Wiley","doi":"10.1111/eff.12503","usgsCitation":"Meador, M.R., 2020, Historical changes in fish communities in urban streams of the southeastern U.S. and the relative importance of water-quality stressors: Ecology of Freshwater Fish, v. 29, no. 1, p. 156-169, https://doi.org/10.1111/eff.12503.","productDescription":"14 p.","startPage":"156","endPage":"169","ipdsId":"IP-092961","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":368448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States ","state":"Alabama, Georgia, North Carolina, South Carolina, Tennessee, Virginia, Washington DC.","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.431396484375,\n 39.487084981687495\n ],\n [\n -79.266357421875,\n 38.70265930723801\n ],\n [\n -79.771728515625,\n 38.634036452919226\n ],\n [\n -80.343017578125,\n 37.90953361677018\n ],\n [\n -80.628662109375,\n 37.58811876638322\n ],\n [\n -81.090087890625,\n 37.49229399862877\n ],\n [\n -81.89208984375,\n 37.52715361723378\n ],\n [\n -84.1552734375,\n 36.65079252503471\n ],\n [\n -85.60546875,\n 34.994003757575776\n ],\n [\n -86.5283203125,\n 33.137551192346145\n ],\n [\n -87.29736328125,\n 32.0639555946604\n ],\n [\n -85.10009765625,\n 31.690781806136822\n ],\n [\n -83.78173828125,\n 32.1570124860701\n ],\n [\n -81.9580078125,\n 33.46810795527896\n ],\n [\n -80.947265625,\n 33.797408767572485\n ],\n [\n -80.04638671875,\n 34.17999758688084\n ],\n [\n -79.60693359375,\n 34.867904962568716\n ],\n [\n -78.22265625,\n 35.7286770448517\n ],\n [\n -77.113037109375,\n 36.54494944148322\n ],\n [\n -77.16796875,\n 37.96152331396614\n ],\n [\n -76.849365234375,\n 38.92522904714054\n ],\n [\n -77.18994140625,\n 39.06184913429154\n ],\n [\n -77.991943359375,\n 38.496593518947584\n ],\n [\n -77.82714843749999,\n 39.13006024213511\n ],\n [\n -78.431396484375,\n 39.487084981687495\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Meador, Michael R. 0000-0001-5956-3340 mrmeador@usgs.gov","orcid":"https://orcid.org/0000-0001-5956-3340","contributorId":219878,"corporation":false,"usgs":true,"family":"Meador","given":"Michael","email":"mrmeador@usgs.gov","middleInitial":"R.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":773484,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70263567,"text":"70263567 - 2020 - Regional Global Navigation Satellite System networks for crustal deformation monitoring","interactions":[],"lastModifiedDate":"2025-02-13T16:47:47.502631","indexId":"70263567","displayToPublicDate":"2019-09-04T10:45:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Regional Global Navigation Satellite System networks for crustal deformation monitoring","docAbstract":"Regional networks of Global Navigation Satellite System (GNSS) stations cover seismically and volcanically active areas throughout the United States. Data from these networks have been used to produce high‐precision, three‐component velocity fields covering broad geographic regions as well as position time series that track time‐varying crustal deformation. This information has contributed to assessing interseismic strain accumulation and related seismic hazard, revealed previously unknown occurrences of aseismic fault slip, constrained coseismic slip estimates, and enabled monitoring of volcanic unrest and postseismic deformation. In addition, real‐time GNSS data are now widely available. Such observations proved invaluable for tracking the rapidly evolving eruption of Kīlauea in 2018. Real‐time earthquake source modeling using GNSS data is being incorporated into tsunami warning systems, and a vigorous research effort is focused on quantifying the contribution that real‐time GNSS can make to improve earthquake early warnings as part of the Advanced National Seismic System ShakeAlert system. Real‐time GNSS data can also aid in the tracking of ionospheric disturbances and precipitable water vapor for weather forecasting. Although regional GNSS and seismic networks generally have been established independently, their spatial footprints often overlap, and in some cases the same institution operates both types of networks. Further integration of GNSS and seismic networks would promote joint use of the two data types to better characterize earthquake sources and ground motion as well as offer opportunities for more efficient network operations. Looking ahead, upgrading network stations to leverage new GNSS technology could enable more precise positioning and robust real‐time operations. New computational approaches such as machine learning have the potential to enable full utilization of the large amounts of data generated by continuous GNSS networks. Development of seafloor Global Positioning System‐acoustic networks would provide unique information for fundamental and applied research on subduction zone seismic hazard and, potentially, monitoring.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190113","usgsCitation":"Murray, J.R., Bartlow, N., Bock, Y., Brooks, B.A., Foster, J.H., Freymueller, J.T., Hammond, W.C., Hodgkinson, K., Johanson, I.A., Lopez-Venegas, A., Mann, D., Mattioli, G., Melbourne, T., Mencin, D., Montgomery-Brown, E.K., Murray, M.H., Smalley, R., and Thomas, V., 2020, Regional Global Navigation Satellite System networks for crustal deformation monitoring: Seismological Research Letters, v. 91, no. 2A, p. 552-572, https://doi.org/10.1785/0220190113.","productDescription":"21 p.","startPage":"552","endPage":"572","ipdsId":"IP-108083","costCenters":[{"id":237,"text":"Earthquake Science 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Kansas","active":true,"usgs":false}],"preferred":false,"id":927349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Yehuda 0000-0001-8296-6623","orcid":"https://orcid.org/0000-0001-8296-6623","contributorId":350938,"corporation":false,"usgs":false,"family":"Bock","given":"Yehuda","affiliations":[{"id":83883,"text":"University of California San Diego Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":927350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foster, James 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C.","contributorId":73735,"corporation":false,"usgs":true,"family":"Hammond","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":927354,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hodgkinson, Kathleen 0000-0001-8529-0913","orcid":"https://orcid.org/0000-0001-8529-0913","contributorId":209915,"corporation":false,"usgs":false,"family":"Hodgkinson","given":"Kathleen","email":"","affiliations":[{"id":38024,"text":"UNAVCO Inc.","active":true,"usgs":false}],"preferred":false,"id":927355,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science 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0000-0002-9117-7471","orcid":"https://orcid.org/0000-0002-9117-7471","contributorId":350941,"corporation":false,"usgs":false,"family":"Mattioli","given":"Glen","affiliations":[{"id":83886,"text":"UNAVCO, Inc.","active":true,"usgs":false}],"preferred":false,"id":927359,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Melbourne, Timothy 0000-0003-1870-3962","orcid":"https://orcid.org/0000-0003-1870-3962","contributorId":209916,"corporation":false,"usgs":false,"family":"Melbourne","given":"Timothy","email":"","affiliations":[{"id":26935,"text":"Central Washington University","active":true,"usgs":false}],"preferred":false,"id":927360,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mencin, David 0000-0001-9984-6724","orcid":"https://orcid.org/0000-0001-9984-6724","contributorId":328836,"corporation":false,"usgs":false,"family":"Mencin","given":"David","email":"","affiliations":[{"id":5114,"text":"UNAVCO","active":true,"usgs":false}],"preferred":false,"id":927361,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":927362,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Murray, Mark Hunter 0000-0003-4862-5547","orcid":"https://orcid.org/0000-0003-4862-5547","contributorId":300982,"corporation":false,"usgs":true,"family":"Murray","given":"Mark","email":"","middleInitial":"Hunter","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927363,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Smalley, Robert Jr.","contributorId":244558,"corporation":false,"usgs":false,"family":"Smalley","given":"Robert","suffix":"Jr.","email":"","affiliations":[{"id":48941,"text":"Center for Earthquake Research and Information, University of Memphis, Memphis, TN, USA","active":true,"usgs":false}],"preferred":false,"id":927364,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Thomas, Valerie 0000-0001-6170-5563","orcid":"https://orcid.org/0000-0001-6170-5563","contributorId":222022,"corporation":false,"usgs":true,"family":"Thomas","given":"Valerie","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927365,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70208108,"text":"70208108 - 2020 - A range-wide model of contemporary, omnidirectional connectivity for the threatened Mojave desert tortoise","interactions":[],"lastModifiedDate":"2020-01-27T19:26:20","indexId":"70208108","displayToPublicDate":"2019-09-03T19:22:52","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A range-wide model of contemporary, omnidirectional connectivity for the threatened Mojave desert tortoise","docAbstract":"As habitat destruction leads to species extinctions globally, conservation planning that accounts for population-level connectivity and gene flow is an urgent priority. Models that only approximate habitat potential are incomplete because areas of high habitat potential may be isolated, whereas intermixed areas of lower habitat potential may still be critical for maintaining connectivity between and among populations. We developed a range-wide, omnidirectional (‘coreless’) connectivity model and map for the threatened Mojave desert tortoise at a high spatial resolution (30 m), based on empirical movement data and a circuit-theoretic approach to estimating connectivity. Specifically, we first estimated habitat potential (i.e., quality) for tortoise movement (as distinct from habitat potential more generally) across its range using hypotheses based on the published literature, linear mixed models, multiple environmental factors derived from remotely sensed data, and recent solar and wind development footprints. The resultant raster output was used to represent landscape conductance in a circuit-theoretic model of connectivity, which relates the flow of electrical current through a circuit to the movement of tortoises through the landscape. We then modeled potential connectivity across the range of the tortoise using Circuitscape software and the Julia numerical programming language. Intermediate distances from minor roads, intermediate values of annual average maximum temperature, and increasing density of desert washes were among the strongest predictors of movement habitat quality. There was also strong evidence for increased habitat quality for movement with increasing amounts of vegetation cover. The resulting connectivity model and map was determined to accurately reflect important areas for tortoise movement, but we encourage others to do their own evaluation of the model within local areas of interest and as more data become available. Accordingly, the map can provide an important component to improve management decisions that have the potential to influence the conservation of connected desert tortoise populations throughout the range.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2847","usgsCitation":"Gray, M.E., Dickson, B.G., Nussear, K., Esque, T., and Chang, T., 2020, A range-wide model of contemporary, omnidirectional connectivity for the threatened Mojave desert tortoise: Ecosphere, v. 10, no. 9, e02847, https://doi.org/10.1002/ecs2.2847.","productDescription":"e02847","ipdsId":"IP-109686","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2847","text":"Publisher Index Page"},{"id":371617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.3946533203125,\n 33.65578083204094\n ],\n [\n -114.70275878906249,\n 33.280027811732154\n ],\n [\n -114.40612792968749,\n 35.14686290675633\n ],\n [\n -115.77941894531249,\n 35.92464453144099\n ],\n [\n -116.70227050781249,\n 35.420391545750746\n ],\n [\n -117.32299804687499,\n 34.985003130171066\n ],\n [\n -116.83959960937499,\n 34.347971491244955\n ],\n [\n -116.3946533203125,\n 33.65578083204094\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Gray, Miranda E","contributorId":221848,"corporation":false,"usgs":false,"family":"Gray","given":"Miranda","email":"","middleInitial":"E","affiliations":[{"id":40441,"text":"Conservation Science Partners, Truckee, CA","active":true,"usgs":false}],"preferred":false,"id":780491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickson, Brett G.","contributorId":221849,"corporation":false,"usgs":false,"family":"Dickson","given":"Brett","email":"","middleInitial":"G.","affiliations":[{"id":40442,"text":"Conservation Science Partners, Truckee, CA; Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":780492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nussear, Kenneth","contributorId":194538,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":780493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780490,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chang, Tony","contributorId":191992,"corporation":false,"usgs":false,"family":"Chang","given":"Tony","email":"","affiliations":[],"preferred":false,"id":780494,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211191,"text":"70211191 - 2020 - Permafrost hydrology drives the assimilation of old carbon by stream food webs in the Arctic","interactions":[],"lastModifiedDate":"2020-07-16T18:49:40.296564","indexId":"70211191","displayToPublicDate":"2019-09-03T13:44:11","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Permafrost hydrology drives the assimilation of old carbon by stream food webs in the Arctic","docAbstract":"Permafrost thaw in the Arctic is mobilizing old carbon (C) from soils to aquatic ecosystems and the atmosphere. Little is known, however, about the assimilation of old C by aquatic food webs in Arctic watersheds. Here, we used C isotopes (δ13C, Δ14C) to quantify C assimilation by biota across 12 streams in arctic Alaska. Streams spanned watersheds with varying permafrost hydrology, from ice-poor bedrock to ice-rich loess (that is, yedoma). We measured isotopic content of (1) C sources including dissolved organic C (DOC), dissolved inorganic C (DIC), and soil C, and (2) stream biota, including benthic biofilm and macroinvertebrates, and resident fish species (Arctic Grayling (Thymallus arcticus) and Dolly Varden (Salvelinus malma)). Findings document the assimilation of old C by stream biota, with depleted Δ14C values observed at multiple trophic levels, including benthic biofilm (14C ages = 5255 to 265 years before present (y BP)), macroinvertebrates (4490 y BP to modern), and fish (3195 y BP to modern). Mixing model results indicate that DOC and DIC contribute to benthic biofilm composition, with relative contributions differing across streams draining ice-poor and ice-rich terrain. DOC originates primarily from old terrestrial C sources, including deep peat horizons (39–47%; 530 y BP) and near-surface permafrost (12–19%; 5490 y BP). DOC also accounts for approximately half of fish isotopic composition. Analyses suggest that as the contribution of old C to fish increases, fish growth and nutritional status decline. We anticipate increases in old DOC delivery to streams under projected warming, which may further alter food web function in Arctic watersheds.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-019-00413-6","usgsCitation":"O'Donnell, J., Carey, M.P., Koch, J.C., Xu, X., Poulin, B., Walker, J., and Zimmerman, C.E., 2020, Permafrost hydrology drives the assimilation of old carbon by stream food webs in the Arctic: Ecosystems, v. 23, p. 435-453, https://doi.org/10.1007/s10021-019-00413-6.","productDescription":"19 p.","startPage":"435","endPage":"453","ipdsId":"IP-102831","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":437218,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NAUIQR","text":"USGS data release","linkHelpText":"Carbon Isotope Concentrations in Stream Food Webs of the Arctic Network National Parks, Alaska, 2014-2016"},{"id":376449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Land Bridge and Noatak National Preserves","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.58593749999997,\n 65.4217295985527\n ],\n [\n -156.09375,\n 65.4217295985527\n ],\n [\n -156.09375,\n 68.12248241161676\n ],\n [\n -165.58593749999997,\n 68.12248241161676\n ],\n [\n -165.58593749999997,\n 65.4217295985527\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Donnell, Jonathon A 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":222968,"corporation":false,"usgs":false,"family":"O'Donnell","given":"Jonathon A","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":793044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":793045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":793046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xu, Xiaomei","contributorId":139915,"corporation":false,"usgs":false,"family":"Xu","given":"Xiaomei","email":"","affiliations":[{"id":13312,"text":"University of California-Irvine","active":true,"usgs":false}],"preferred":false,"id":793047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":793048,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walker, Jennifer","contributorId":201558,"corporation":false,"usgs":false,"family":"Walker","given":"Jennifer","affiliations":[],"preferred":false,"id":793049,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":793050,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208375,"text":"70208375 - 2020 - Influence of a high-head dam as a dispersal barrier to fish community structure of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2020-02-05T15:56:21","indexId":"70208375","displayToPublicDate":"2019-09-01T15:50:24","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":"Influence of a high-head dam as a dispersal barrier to fish community structure of the Upper Mississippi River","docAbstract":"In river systems, high‐head dams may increase the distance‐decay of fish community similarity by creating nearly impermeable dispersal barriers to certain species from upstream reaches. Substantial evidence suggests that migratory species are impacted by dams, and most previous studies in stream/river networks have focused on small streams and headwaters. Here, we assess whether a high‐head dam (Lock and Dam 19; LD 19) on a large river, the Upper Mississippi River (UMR), substantially alters fish community structure relative to variability expected to occur independent of the dam's effect as a fish dispersal barrier. Using fish catch per unit effort data, we modelled the distance‐decay function for the UMR fish community and then estimated the similarity that would be expected to occur across LD19 and compared it with measured similarity. Measured similarity in the fish community above and below LD19 was close to the expected value based on the distance‐decay function, suggesting LD19 does not create an abrupt transition in the fish community. Although some migratory fish species no longer occur above LD19 (e.g., skipjack herring, Alosa chrysochloris), these species do not occur in high abundance below the dam and so do not drive variation in fish community structure. Instead, much of the variation in species structure is driven by the loss/gain of species across the latitudinal gradient. Lock and Dam 19 does not appear to be a clear transition point in the river's fish community, although it may function as a meaningful barrier for particular species (e.g., invasive species) and warrant future attention from a management perspective.
","language":"English","publisher":"John Wiley and Sons, Inc.","doi":"10.1002/rra.3534","usgsCitation":"Anderson, R.L., Anderson, C.A., Larson, J.H., Knights, B.C., Vallazza, J.M., Jenkins, S.E., and Lamer, J.T., 2020, Influence of a high-head dam as a dispersal barrier to fish community structure of the Upper Mississippi River: River Research and Applications, v. 36, no. 1, p. 47-56, https://doi.org/10.1002/rra.3534.","productDescription":"10 p.","startPage":"47","endPage":"56","ipdsId":"IP-095942","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":458682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3534","text":"Publisher Index Page"},{"id":372095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.8125,\n 37.52715361723378\n ],\n [\n -88.79150390625,\n 37.52715361723378\n ],\n [\n -88.79150390625,\n 44.68427737181225\n ],\n [\n -92.8125,\n 44.68427737181225\n ],\n [\n -92.8125,\n 37.52715361723378\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Rebekah L.","contributorId":218832,"corporation":false,"usgs":false,"family":"Anderson","given":"Rebekah","email":"","middleInitial":"L.","affiliations":[{"id":39921,"text":"Illinois Deptment of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":781660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Cory A.","contributorId":196305,"corporation":false,"usgs":false,"family":"Anderson","given":"Cory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":781661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781663,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenkins, Sean E.","contributorId":199666,"corporation":false,"usgs":false,"family":"Jenkins","given":"Sean","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":781665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lamer, James T. 0000-0003-1155-1548","orcid":"https://orcid.org/0000-0003-1155-1548","contributorId":196307,"corporation":false,"usgs":false,"family":"Lamer","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":48847,"text":"Illinois River Biological Station, Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":781664,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70212604,"text":"70212604 - 2020 - Porphyry copper potential of the U.S. Southern Basin and Range using ASTER data integrated with geochemical and geologic datasets to assess potential near-surface deposits in well-explored permissive tracts","interactions":[],"lastModifiedDate":"2020-08-24T12:21:59.418909","indexId":"70212604","displayToPublicDate":"2019-09-01T15:21:04","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Porphyry copper potential of the U.S. Southern Basin and Range using ASTER data integrated with geochemical and geologic datasets to assess potential near-surface deposits in well-explored permissive tracts","docAbstract":"ArcGIS was used to spatially assess and rank potential porphyry copper deposits using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data together with geochemical and geologic datasets in order to estimate undiscovered deposits in the southern Basin and Range Province in the southwestern United States. The assessment was done using a traditional expert opinion three-part method and a prospectivity model developed using weights of evidence and logistic regression techniques to determine if ASTER data integrated with other geologic datasets can be used to find additional areas of prospectivity in well-explored permissive tracts. ASTER hydrothermal alteration data were expressed as 457 alteration polygons defined from a low-pass filtered alteration density map of combined argillic, phyllic, and propylitic rock units. Sediment stream samples were plotted as map grid data and used as spatial information in ASTER polygons. Gravity and magnetic data were also used to define basins greater than 1 km in depth. Each ASTER alteration polygon was ranked for porphyry copper potential using alteration types, spatial amounts of alteration, stream sediment geochemistry, lithology, polygon shape, proximity to other alteration polygons, and deposit and prospects data. Permissive tracts defined for the assessment in the southern Basin and Range Province include the Laramide Northwest, Laramide Southeast, Jurassic, and Tertiary tracts. Expert opinion estimates using the three-part assessment method resulted in a mean estimate of 17 undiscovered porphyry copper deposits, whereas the prospectivity modeling predicted a mean estimate of nine undiscovered deposits. In the well-explored Laramide Southeast tract, which contains the most deposits and has been explored for over 100 years, an average of 4.3 undiscovered deposits was estimated using ASTER alteration polygon data versus 2.8 undiscovered deposits without ASTER data. The Tertiary tract, which contains the largest number of ASTER alteration polygons not associated with known Tertiary deposits, was predicted to contain the most undiscovered resources in the southern Basin and Range Province.
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matching","docAbstract":"Over the past decade, Oklahoma became the most seismically active region of the mid-Continental USA as a result of industry operations. However, seismic network limitations and completeness of earthquake catalogs have restricted the types of analyses that can be performed. By applying multi-station template matching on the 23,889 cataloged earthquakes in Oklahoma and Southern Kansas between late-2008 and 2016, we increased the number of detected earthquakes to 209,409 events. While the improved catalog produced an order of magnitude events than the original catalog, the frequency-magnitude distribution remains similar to the original catalog. We found that the coefficient of variation of interevent times in small spatial bins tends to spatially correlate with the location of M ≥ 4 earthquakes. The improved catalog reveals the pervasiveness of swarm-like patterns in seismicity across the entire study region. The rapid increase in seismicity rate of these swarms in 2013 coincided with a reduction in the calculated p values (power law decay rates) before and after larger events. We also used the catalog to revisit the temporal patterns in the four M ≥ 5 sequences, finding more active foreshock behavior than previously recognized and variations in aftershock behavior. When compared against poroelastic stress models for the Pawnee and Fairview sequences, the catalog shows an improved correlation with stress that accounts for variable-rate injection, supporting the conclusion that injection rate is an important contributor to seismic hazard.
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University","active":true,"usgs":false}],"preferred":false,"id":773611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Currie, Brian S.","contributorId":207881,"corporation":false,"usgs":false,"family":"Currie","given":"Brian","email":"","middleInitial":"S.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":773612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ries, Rosamiel","contributorId":211773,"corporation":false,"usgs":false,"family":"Ries","given":"Rosamiel","email":"","affiliations":[{"id":38316,"text":"Miami University, Oxford, Ohio","active":true,"usgs":false}],"preferred":false,"id":773613,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215204,"text":"70215204 - 2020 - Understanding melt evolution and eruption dynamics of the 1666 C.E. eruption of Cinder Cone, Lassen Volcanic National Park, California: Insights from olivine-hosted melt inclusions","interactions":[],"lastModifiedDate":"2020-10-12T14:39:09.465819","indexId":"70215204","displayToPublicDate":"2019-08-27T09:33:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Understanding melt evolution and eruption dynamics of the 1666 C.E. eruption of Cinder Cone, Lassen Volcanic National Park, California: Insights from olivine-hosted melt inclusions","docAbstract":"Cinder Cone is the youngest scoria cone volcano in the continental United States. Erupted in 1666 C.E. within what is now Lassen Volcanic National Park, Cinder Cone is an un-vegetated scoria cone with well-preserved lava flows and tephra deposits that display complex geochemical variability. In this study, we utilize the volatile (H2O, CO2, Cl), major, and trace element chemistry of olivine-hosted melt inclusions from the tephra deposit of Cinder Cone to better understand the sub-surface evolution of magmas that erupt to produce scoria cones. High-Fo olivine phenocrysts from all erupted units contain melt inclusions that are more primitive in composition than the erupted material. The evolved compositions of the lava and bulk tephra and the abundance of quartz xenocrysts within the deposits suggest the basaltic parental magmas were rapidly contaminated by granitic material in the middle to upper crust, after melt inclusion entrapment. Distinct compositional variability between early and late erupted units suggests two different mantle-derived basaltic magmas were tapped and erupted sequentially as two distinct eruptive phases. The CO2 concentrations in the melt inclusions, after correction for the presence of vapor bubbles, suggest minimum entrapment depths of ~9.5–20 km and show no resolvable differences between early and late erupted units at the time of olivine crystallization. Diffusion modeling of Ni and Fo gradients in olivine rims indicates that olivine residence times in an evolving magma were on the order of weeks to years, similar to those calculated for longer-lived scoria cone eruptions, such as Jorullo, in Mexico. Additionally, geochemical evidence suggests that the evolution of parental magmas was likely driven by the partial melting, disaggregation, and assimilation of granitic material in the upper crust. Our combined results provide new insight into the complexities of short-lived monogenetic eruptions.
Habitat loss and degradation are leading causes of biodiversity declines, therefore assessing the capacity of created mitigation wetlands to replace habitat for wildlife has become a management priority. We used single season occupancy models to compare the occurrence of larvae of four species of pond‐breeding amphibians in wetlands created for mitigation, wetlands impacted by road construction, and unimpacted reference wetlands along a highway corridor in the Greater Yellowstone Ecosystem, United States. Created wetlands were shallow and had less aquatic vegetation and surface area than impacted and reference wetlands. Occupancy of barred tiger salamander (Ambystoma mavortium) and boreal chorus frog (Pseudacris maculata) larvae was similar across wetland types, whereas boreal toads (Anaxyrus boreas) occurred more often in created wetlands than reference and impacted wetlands. However, the majority of created wetlands (>80%) dried partially or completely before amphibian metamorphosis occurred in both years of our study, resulting in heavy mortality of larvae and, we suspect, little to no recruitment. Columbia spotted frogs (Rana luteiventris), which require emergent vegetation that is not common in newly created wetlands, occurred commonly in impacted and reference wetlands but were found in only one created wetland. Our results show that shallow created wetlands with little aquatic vegetation may be attractive breeding areas for some amphibians, but may result in high mortality and little recruitment if they fail to hold water for the entire larval period.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13031","usgsCitation":"Swartz, L., Lowe, W., Muths, E.L., and Hossack, B.R., 2020, Species-specific responses to wetland mitigation among amphibians in the Greater Yellowstone Ecosystem: Restoration Ecology, v. 28, no. 1, p. 206-214, https://doi.org/10.1111/rec.13031.","productDescription":"9 p.","startPage":"206","endPage":"214","ipdsId":"IP-103888","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":368638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Yellowstone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.7694091796875,\n 43.40903821777055\n ],\n [\n -108.9129638671875,\n 43.40903821777055\n ],\n [\n -108.9129638671875,\n 45.32897866218559\n ],\n [\n -111.7694091796875,\n 45.32897866218559\n ],\n [\n -111.7694091796875,\n 43.40903821777055\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Swartz, LK","contributorId":220046,"corporation":false,"usgs":false,"family":"Swartz","given":"LK","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":773968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, WH","contributorId":220047,"corporation":false,"usgs":false,"family":"Lowe","given":"WH","email":"","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":773969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":773970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":773967,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204933,"text":"70204933 - 2020 - Maximum entropy derived statistics of sound speed structure in a fine-grained sediment inferred from sparse broadband acoustic measurements on the New England continental shelf","interactions":[],"lastModifiedDate":"2020-01-20T12:25:57","indexId":"70204933","displayToPublicDate":"2019-08-23T10:55:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1941,"text":"IEEE Journal of Oceanic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Maximum entropy derived statistics of sound speed structure in a fine-grained sediment inferred from sparse broadband acoustic measurements on the New England continental shelf","docAbstract":"Marginal probability distributions for parameters representing an effective sound-speed structure of a fine-grained sediment are inferred from a data ensemble maximum entropy method that utilizes a sparse spatially distributed set of received pressure time series resulting from multiple explosive sources in a shallow-water ocean environment possessing significant spatial variability of the seabed. A remote sensing seabed acoustics experiment undertaken in March 2017 off the New England Shelf was designed so that multiple independent analyses could infer the statistical properties of the seabed. The current analysis incorporates the measured horizontal variability from interpretations of a subbottom profiling survey of the experimental area. An idealized range- and azimuth-dependent parameterization of the seabed is derived from identification of horizons within the seabed that define multiple sediment layers. A sparse set of explosive charges were deployed on circular tracks with radii of about 2, 4, and 6.5 km with an acoustic array at the center to correlate a set of random measurements to physical acoustic processes that characterize the seabed. The mean values of a surface sound speed ratio and a linear sound speed gradient for the fine-grained sediment layer derived from 12 data samples processed in the 25–275-Hz band provide an estimate of the effective sound-speed structure in a 130-km $^2$ area. The inferred sediment sound speed values are evaluated by predicting measured time series data not used in the statistical inference, and are also compared to historical measurements. Finally, the low-frequency maximum entropy estimate of the sediment sound speed along with physical measurements derived from piston core measurements are utilized to estimate the sediment grain bulk modulus.\npredictions made by the viscous grain shearing model.","language":"English","publisher":"IEEE","doi":"10.1109/JOE.2019.2922717","usgsCitation":"Knobles, D.P., Wilson, P.S., Goff, J., Wan, L., Buckingham, M., Chaytor, J., and Badiey, M., 2020, Maximum entropy derived statistics of sound speed structure in a fine-grained sediment inferred from sparse broadband acoustic measurements on the New England continental shelf: IEEE Journal of Oceanic Engineering, v. 45, no. 1, p. 161-173, https://doi.org/10.1109/JOE.2019.2922717.","productDescription":"9 p.","startPage":"161","endPage":"173","ipdsId":"IP-102085","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":366851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, Vermont, New Hampshire, Massachusetts, Rhode Island, 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\"}}]}","volume":"45","issue":"1","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Knobles, David P.","contributorId":218392,"corporation":false,"usgs":false,"family":"Knobles","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":769154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Preston S.","contributorId":139561,"corporation":false,"usgs":false,"family":"Wilson","given":"Preston","email":"","middleInitial":"S.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":769155,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goff, J.A.","contributorId":17004,"corporation":false,"usgs":true,"family":"Goff","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":769156,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wan, L.","contributorId":218393,"corporation":false,"usgs":false,"family":"Wan","given":"L.","email":"","affiliations":[],"preferred":false,"id":769157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckingham, M.J.","contributorId":28772,"corporation":false,"usgs":true,"family":"Buckingham","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":769158,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769159,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Badiey, Mohsen","contributorId":218394,"corporation":false,"usgs":false,"family":"Badiey","given":"Mohsen","email":"","affiliations":[],"preferred":false,"id":769160,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208109,"text":"70208109 - 2020 - Social attraction used to establish Caspian tern nesting colonies in San Francisco Bay","interactions":[],"lastModifiedDate":"2020-01-27T19:22:21","indexId":"70208109","displayToPublicDate":"2019-08-14T19:21:25","publicationYear":"2020","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":"Social attraction used to establish Caspian tern nesting colonies in San Francisco Bay","docAbstract":"Conservation of colonial waterbird breeding populations often includes restoring historic nesting habitat or establishing new nesting habitat in protected areas. However, colonization of new or restored nesting habitat may be hindered by the lack of social cues from nesting conspecifics to attract prospecting birds. Social attraction, whereby decoys and colony sound recordings are used to mimic active nesting colonies, has been used successfully to establish waterbird nesting colonies throughout the world. We constructed islands, modified the substrate so that it was attractive to nesting Caspian terns (Hydroprogne caspia), and then used social attraction to establish nesting colonies within two managed ponds in San Francisco Bay, California where Caspian terns had not previously nested. During the 2015–2017 breeding seasons, we deployed decoys of adult Caspian terns, broadcasted colony sound recordings, and monitored Caspian tern response. Caspian terns formed nesting colonies within weeks of social attraction deployment at each of the two ponds in 2015, and the size of these colonies increased in each subsequent year of the study. In 2017, the final year of the study, we estimated a minimum of 501 breeding pairs between the two colonies, making them two of the three largest Caspian tern colonies in the San Francisco Bay estuary. In total, these two colonies produced 1343 nests and 531 fledglings over the three-year study period. Nest densities were low (mean: 0.29 nests/m2 of active colony area) compared to other studies, and greater than 80% of the modified island habitat remained unused by nesting Caspian terns in 2017, suggesting that there is additional space for future colony growth. The successful establishment of two of the largest Caspian tern nesting colonies in the San Francisco Bay estuary in just three years demonstrates the potential of using island construction and habitat modifications, combined with social attraction measures to establish waterbird nesting colonies.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2019.e00757","usgsCitation":"Hartman, C.A., Ackerman, J., Herzog, M.P., Strong, C., and Trachtenbarg, D.A., 2020, Social attraction used to establish Caspian tern nesting colonies in San Francisco Bay: Global Ecology and Conservation, v. 20, e00757, https://doi.org/10.1016/j.gecco.2019.e00757.","productDescription":"e00757","ipdsId":"IP-110956","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458697,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2019.e00757","text":"Publisher Index Page"},{"id":371616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California ","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.04687499999999,\n 37.21283151445594\n ],\n [\n -121.6845703125,\n 37.21283151445594\n ],\n [\n -121.6845703125,\n 38.30718056188316\n ],\n [\n -123.04687499999999,\n 38.30718056188316\n ],\n [\n -123.04687499999999,\n 37.21283151445594\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":780495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":780497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strong, Cheryl","contributorId":149428,"corporation":false,"usgs":false,"family":"Strong","given":"Cheryl","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":780498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trachtenbarg, David A","contributorId":146351,"corporation":false,"usgs":false,"family":"Trachtenbarg","given":"David","email":"","middleInitial":"A","affiliations":[{"id":16680,"text":"U.S. Army Corps of Engineers, Walla Walla District, Walla Walla, WA 99362","active":true,"usgs":false}],"preferred":false,"id":780499,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208101,"text":"70208101 - 2020 - Sampling and analysis frameworks for inference in ecology","interactions":[],"lastModifiedDate":"2020-01-27T19:43:27","indexId":"70208101","displayToPublicDate":"2019-08-02T19:41:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Sampling and analysis frameworks for inference in ecology","docAbstract":"1. Reliable statistical inference is central to ecological research, much of which seeks to estimate population attributes and their interactions. The issue of sampling design and its relationship to inference has become increasingly important due to rapid proliferation of modeling methodology (line transect modeling, capture-recapture, estimation of occurrence, model selection procedures, hierarchical modeling) and new sampling approaches (adaptive sampling, other specialized designs). It is important for ecologists using these advanced methods to be aware of how the linkages between sample selection and data analysis can potentially affect inference. 2. We examine design-based and model-based inference frameworks for ecological data collected randomly, purposively, or opportunistically. We elucidate differences in the probability structures for data arising from these frameworks, clarify the assumptions that underlie them, and demonstrate their differences. 3. Design-based inference builds on a probability structure inherited from randomized data collection, whereas model-based inference relies on an assumed stochastic model of the data. By itself, a design-based approach is of limited value for inferences about causal hypotheses. In contrast, model-based inference is dependent on a conditionality principle that can seldom be shown to be met for an ecological system. We describe the conditions under which one can safely ignore sampling design in model-based analysis, along with inferential implications if these conditions are not met. The special case of opportunistic sampling is discussed. 4. We present a combined framework that takes advantage of both approaches to inference, and provides a robust methodology that can deal with the modeling of sampling problems such as nondetection and misclassification, as well as the exploration of causal hypotheses. The combined framework can be useful for identifying optimal sampling strategies. 5. Each approach to inference has its strengths and weaknesses, and practitioners should be aware of these in order to tailor designs and analyses to specific questions. We use the approaches and their underlying rationales to provide guidelines for choosing designs and estimators for reliable inference.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.13279","usgsCitation":"Williams, B.K., and Brown, E., 2020, Sampling and analysis frameworks for inference in ecology: Methods in Ecology and Evolution, v. 11, no. 10, p. 1832-1842, https://doi.org/10.1111/2041-210X.13279.","productDescription":"11 p.","startPage":"1832","endPage":"1842","ipdsId":"IP-105921","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":458716,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13279","text":"Publisher Index Page"},{"id":371624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":780468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Ellie 0000-0001-7798-830X ebrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7798-830X","contributorId":200491,"corporation":false,"usgs":true,"family":"Brown","given":"Ellie","email":"ebrown@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":780467,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208934,"text":"70208934 - 2020 - Planners tool up for the next big one","interactions":[],"lastModifiedDate":"2020-03-06T09:19:59","indexId":"70208934","displayToPublicDate":"2019-08-01T09:17:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5940,"text":"Planning","active":true,"publicationSubtype":{"id":10}},"title":"Planners tool up for the next big one","docAbstract":"Data, modeling, risk analysis, and hazard scenario resources can help put earthquake mitigation efforts on firmer ground. Article discusses general earthquake information and findings of the HayWired scenario for a planner audience.","language":"English","publisher":"American Planning Association","usgsCitation":"Johnson, L., and Wein, A.M., 2020, Planners tool up for the next big one: Planning, v. 85, p. 40-44.","productDescription":"5 p.","startPage":"40","endPage":"44","ipdsId":"IP-108944","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":372991,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372977,"type":{"id":15,"text":"Index Page"},"url":"https://www.planning.org/planning/2019/aug/"}],"volume":"85","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Laurie","contributorId":223094,"corporation":false,"usgs":false,"family":"Johnson","given":"Laurie","email":"","affiliations":[{"id":40672,"text":"Laurie Johnson Consulting/Research","active":true,"usgs":false}],"preferred":false,"id":784097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne M. 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":192951,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":784096,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204664,"text":"70204664 - 2020 - Using carbon isotope ratios to verify predictions of a model simulating the interaction between coastal plant communities and their effect on ground water salinity","interactions":[],"lastModifiedDate":"2020-06-04T16:34:54.718128","indexId":"70204664","displayToPublicDate":"2019-07-31T13:28:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Using carbon isotope ratios to verify predictions of a model simulating the interaction between coastal plant communities and their effect on ground water salinity","docAbstract":"As sea level rises in low-lying coastal islands, salt-tolerant (halophytic) coastal vegetation communities may be able to migrate inland, replacing the freshwater vegetation that is unable to tolerate salt stress. The pace of such shifts may be accelerated by a self-reinforcing feedback between the halophytic vegetation and salinity, as well as by frequent and intensified salinity pulses associated with the increasing impact of storm surges as a consequence of sea-level rise. We used a modification of a previously published spatially explicit individual-based model that simulates impacts on upland freshwater hammock communities from sea-level rise and storm surge to predict the interaction between three coastal communities: mangroves, hammocks, and pinelands. The model simulation predicted two qualitative characteristics regarding the interaction between these three different coastal communities: (1) mangroves and hammock communities tend to have ground water with high salinities, while at the same time pineland ground water salinity is low, and (2) pineland located at lower elevation relative to adjacent hammock will be negatively influenced by higher ground water salinities in hammocks, as it flows toward the lower elevation pineland. We tested these predictions using foliar δ13C of Conocarpus erectus collected from Big Pine Key as a proxy for ground water salinity. Measurements of ground water salinity via this proxy confirmed the two predictions of the model. Our approach provides an approximation of the impacts of sea-level rise on terrestrial vegetation communities, including threatened pineland communities, and can be used as a tool for management decisions.","language":"English","publisher":"Springer","doi":"10.1007/s10021-019-00423-4","usgsCitation":"Subedi, S.C., Sternberg, L., DeAngelis, D.L., Ross, M.S., and Ogarcak, D., 2020, Using carbon isotope ratios to verify predictions of a model simulating the interaction between coastal plant communities and their effect on ground water salinity: Ecosystems, v. 23, p. 570-585, https://doi.org/10.1007/s10021-019-00423-4.","productDescription":"16 p.","startPage":"570","endPage":"585","ipdsId":"IP-101860","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":437219,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QO2Y7J","text":"USGS data release","linkHelpText":"Carbon-13 values in tree leaves in Florida (2018)"},{"id":366394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Subedi, Suresh C. 0000-0001-8689-0689","orcid":"https://orcid.org/0000-0001-8689-0689","contributorId":217984,"corporation":false,"usgs":false,"family":"Subedi","given":"Suresh","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":767973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sternberg, Leonel","contributorId":217985,"corporation":false,"usgs":false,"family":"Sternberg","given":"Leonel","affiliations":[],"preferred":false,"id":767974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":767972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ross, Michael S.","contributorId":202431,"corporation":false,"usgs":false,"family":"Ross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":36434,"text":"Florida International University, Miami, FL","active":true,"usgs":false}],"preferred":false,"id":767975,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogarcak, Danielle","contributorId":217987,"corporation":false,"usgs":false,"family":"Ogarcak","given":"Danielle","email":"","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":767976,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206828,"text":"70206828 - 2020 - Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape","interactions":[],"lastModifiedDate":"2020-08-27T15:29:37.417951","indexId":"70206828","displayToPublicDate":"2019-07-30T06:48:22","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":"Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape","docAbstract":"Many natural wetlands around the world have disappeared or been replaced, resulting in the dependence of many wildlife species on small, artificial earthen stock ponds. These ponds provide critical wildlife habitat, such that the accurate detection of water and assessment of inundation extent is required. We applied a full (linear spectral mixture analysis; LSMA) and partial (matched filtering; MF) spectral unmixing algorithm to a 2007 Landsat 5 and a 2014 Landsat 8 satellite image to determine the ability of a time-intensive (i.e., more spectral input; LSMA) vs. a more efficient (less spectral input; MF) spectral unmixing approach to detect and estimate surface water area of stock ponds in southern Arizona, USA and northern Sonora, Mexico. Spearman rank correlations (rs) between modeled and actual inundation areas less than a single Landsat pixel (< 900 m2) were low for both techniques (rs range = 0.22 to 0.62), but improved for inundation areas >900 m2 (rs range = 0.34 to 0.70). Our results demonstrate that the MF approach can model ranked inundation extent of known pond locations with results comparable to or better than LSMA, but further refinement is required for estimating absolute inundation areas and mapping wetlands <1 Landsat pixel.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-019-01201-7","usgsCitation":"Jarchow, C., Sigafus, B.H., Muths, E.L., and Hossack, B.R., 2020, Using full and partial unmixing algorithms to estimate the inundation extent of small, isolated stock ponds in an arid landscape: Wetlands, v. 40, p. 563-575, https://doi.org/10.1007/s13157-019-01201-7.","productDescription":"13 p.","startPage":"563","endPage":"575","ipdsId":"IP-092489","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437220,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95ZFPT1","text":"USGS data release","linkHelpText":"Surface water data for isolated stock ponds in southern Arizona, USA and northern Sonora, Mexico"},{"id":369519,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarchow, Christopher 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":196069,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":775953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sigafus, Brent H. 0000-0002-7422-8927 bsigafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":4534,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent","email":"bsigafus@usgs.gov","middleInitial":"H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":775952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":775954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":775955,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227115,"text":"70227115 - 2020 - Harvest–release decisions in recreational fisheries","interactions":[],"lastModifiedDate":"2021-12-30T16:41:44.505518","indexId":"70227115","displayToPublicDate":"2019-07-29T10:37:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Harvest–release decisions in recreational fisheries","docAbstract":"Most fishery regulations aim to control angler harvest. Yet, we lack a basic understanding of what actually determines the angler’s decision to harvest or release fish caught. We used XGBoost, a machine learning algorithm, to develop a predictive angler harvest–release model by taking advantage of an extensive recreational fishery data set (24 water bodies, 9 years, and 193 523 fish). We were able to successfully predict the harvest–release outcome for 99% of fish caught in the training data set and 96% of fish caught in the test data set. Unsuccessful predictions were mostly attributed to predicting harvest of fish that were released. Fish length was the most essential feature examined for predicting angler harvest. Other important predictive harvest–release features included the number of individuals of the same species caught, geographic location of an angler’s residence, distance traveled, and time spent fishing. The XGBoost algorithm was able to effectively predict the harvest–release decision and revealed hidden and intricate relationships that are often unaccounted for with classical analysis techniques. Exposing and accounting for these angler–fish intricacies is critical for fisheries conservation and management.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2019-0119","usgsCitation":"Kaemingk, M.A., Hurley, K.L., Chizinski, C.J., and Pope, K.L., 2020, Harvest–release decisions in recreational fisheries: Canadian Journal of Fisheries and Aquatic Sciences, v. 77, no. 1, p. 194-201, https://doi.org/10.1139/cjfas-2019-0119.","productDescription":"8 p.","startPage":"194","endPage":"201","ipdsId":"IP-107097","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":500808,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/96908","text":"External Repository"},{"id":393653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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