We developed a conceptual model and suspended sediment budget for a 38 km reach of the fifth-order South River, Virginia, for the past 75 yr. Bedrock, terraces, and alluvial fans confine 64% of the channel’s lateral boundaries, while bedrock exposures impose vertical confinement along 37% of the channel. Bedrock exposures in the bed separate pools and riffles developed in gravelly bed material, create unusual kilometer-long pools, and divide the study area into a gently sloping upstream reach and a steeply sloping downstream reach. Bedrock exposures upstream and downstream of an alluvial monitoring site limit changes in bed elevation (documented by scour chains and repeat surveys) by flows with up to 10 yr return periods. Fifty-seven islands (features rarely mentioned in previous studies), mostly created by avulsive floodplain incision, occur in the study reach. Rates of bank retreat, likely moderated by bedrock exposures, have modal values of only a few centimeters per year, while floodplain growth by lateral accretion is negligible. Overbank deposition dominates the sediment budget, but the areal of the extent of the floodplain is currently being reduced by bank erosion and channel widening. The South River stores 2.5% of its annual suspended sediment load per kilometer of downstream transport, demonstrating that suspended sediment storage along partly confined, mixed bedrock-alluvial rivers can be equivalent to storage along fully alluvial rivers. The future evolution of the South River will likely be controlled by bank stabilization designed to control mercury loading into the channel from erosion of contaminated floodplain sediments.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31759.1","usgsCitation":"Pizzuto, J.E., O’Neal, M.A., Narinesingh, P., Skalak, K., Jurk, D., Collins, S., and Calder, J., 2018, Contemporary fluvial geomorphology and suspended sediment budget of the partly confined, mixed bedrock-alluvial South River, Virginia, USA: GSA Bulletin, v. 130, no. 11-12, p. 1859-1874, https://doi.org/10.1130/B31759.1.","productDescription":"16 p.","startPage":"1859","endPage":"1874","ipdsId":"IP-097841","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":356609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia ","otherGeospatial":"South River","volume":"130","issue":"11-12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-05","publicationStatus":"PW","scienceBaseUri":"5b98a2afe4b0702d0e842fb7","contributors":{"authors":[{"text":"Pizzuto, James E.","contributorId":49424,"corporation":false,"usgs":false,"family":"Pizzuto","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":13220,"text":"The Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":742826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Neal, Michael A.","contributorId":207123,"corporation":false,"usgs":false,"family":"O’Neal","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":742827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Narinesingh, Pramenath","contributorId":207124,"corporation":false,"usgs":false,"family":"Narinesingh","given":"Pramenath","email":"","affiliations":[],"preferred":false,"id":742828,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":742825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jurk, Dajana","contributorId":207125,"corporation":false,"usgs":false,"family":"Jurk","given":"Dajana","email":"","affiliations":[],"preferred":false,"id":742829,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collins, Suzann","contributorId":207126,"corporation":false,"usgs":false,"family":"Collins","given":"Suzann","email":"","affiliations":[{"id":37457,"text":"CH2M Hill Engineers","active":true,"usgs":false}],"preferred":false,"id":742830,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Calder, Jacquelyn","contributorId":207127,"corporation":false,"usgs":false,"family":"Calder","given":"Jacquelyn","email":"","affiliations":[{"id":37458,"text":"George H. Moody Middle School","active":true,"usgs":false}],"preferred":false,"id":742831,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197994,"text":"70197994 - 2018 - Trophic compression of lake food webs under hydrologic disturbance","interactions":[],"lastModifiedDate":"2018-07-05T10:26:37","indexId":"70197994","displayToPublicDate":"2018-06-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Trophic compression of lake food webs under hydrologic disturbance","docAbstract":"The need to protect biostructure is increasingly recognized, yet empirical studies of how human exploits affect ecological networks are rare. Studying the effects of variation in human disturbance intensity from decades past can help us understand and anticipate ecosystem change under alleviated or amplified disturbance over decades to come. Here, we use stable isotopes and an innovative analytical approach to compare the food webs of two akin lake ecosystems subject to disparate water use regimes, a pervasive, yet unappreciated stressor. We show that intensive water use (persistent, early season, rapid lake‐level drawdown) can compress trophic diversity by 46%, necessitating reorganization of biostructural elements configuring lake food webs. Compression occurred over the δ13C axis indicating erosion of basal trophic diversity, but food chain length remained intact over the period and intensity of disturbance examined. This study demonstrates the potential for water use, like other disturbances (warming, eutrophication, and invasive species), to mute opportunity for benthic‐pelagic coupling and benefits to lake food webs and the inherent capacity of lake ecosystems to adapt to stress. Trophically compressed lakes may be less able to adapt to intensified water use.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2304","usgsCitation":"Hansen, A.G., Gardner, J.R., Connelly, K.A., Polacek, M., and Beauchamp, D.A., 2018, Trophic compression of lake food webs under hydrologic disturbance: Ecosphere, v. 9, no. 6, p. 1-11, https://doi.org/10.1002/ecs2.2304.","productDescription":"e02304; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-092639","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468712,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2304","text":"Publisher Index Page"},{"id":355499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-20","publicationStatus":"PW","scienceBaseUri":"5b46e575e4b060350a15d195","contributors":{"authors":[{"text":"Hansen, Adam G.","contributorId":197415,"corporation":false,"usgs":false,"family":"Hansen","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":34919,"text":"Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":739520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Jennifer R.","contributorId":175505,"corporation":false,"usgs":false,"family":"Gardner","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":739521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connelly, Kristin A.","contributorId":174523,"corporation":false,"usgs":false,"family":"Connelly","given":"Kristin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":739522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Polacek, Matt","contributorId":206126,"corporation":false,"usgs":false,"family":"Polacek","given":"Matt","email":"","affiliations":[{"id":37251,"text":"Washington Department of Fish and Wildlife 317 1/2 North Pearl St., Suite 7, Ellensburg WA 98926","active":true,"usgs":false}],"preferred":false,"id":739523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":739519,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220881,"text":"70220881 - 2018 - USGS critical minerals review","interactions":[],"lastModifiedDate":"2021-05-27T13:04:08.7805","indexId":"70220881","displayToPublicDate":"2018-05-27T08:02:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"USGS critical minerals review","docAbstract":"The United States’ supply of critical minerals has been a concern and a source of potential strategic vulnerabilities for U.S. economic and national security interests for decades (for example, see Strategic and Critical Minerals Stockpiling Act, 1939). More recently, with the rapid increase in the types of materials being used in advanced technologies (Fortier et al. 2018a), and geopolitical events surrounding the supply of rare earth elements (Ting and Seaman, 2013), among other developments, the critical minerals issue has again achieved a high level of visibility within the U.S. government (Executive Order 13817 (2017)).
The U.S. Geological Survey and Natural Resources Canada conducted a study on the net import reliance of each North American country, and the impact of North American trade on the net import reliance of 12 nonfuel mineral commodities that are associated with advanced technology products: cadmium, cobalt, gallium, germanium, graphite, indium, lithium, nickel, rare earth elements, selenium, silver and tellurium. The combined results for North America, using 2014 data, showed greatly reduced net import reliance for nearly all of the commodities evaluated, which is largely the result of pooling the resources of production and recovery in Canada and Mexico of materials that are consumed in the United States. This study highlights the mitigation of potential supply risk for critical materials that results from trade within the North American trade bloc.
Loess is widespread over Alaska, and its accumulation has traditionally been associated with glacial periods. Surprisingly, loess deposits securely dated to the last glacial period are rare in Alaska, and paleowind reconstructions for this time period are limited to inferences from dune orientations. We report a rare occurrence of loess deposits dating to the last glacial period, ~19 ka to ~12 ka, in the Yukon-Tanana Upland. Loess in this area is very coarse grained (abundant coarse silt), with decreases in particle size moving south of the Yukon River, implying that the drainage basin of this river was the main source. Geochemical data show, however, that the Tanana River valley to the south is also a likely distal source. The occurrence of last-glacial loess with sources to both the south and north is explained by both regional, synoptic-scale winds from the northeast and opposing katabatic winds that could have developed from expanded glaciers in both the Brooks Range to the north and the Alaska Range to the south. Based on a comparison with recent climate modeling for the last glacial period, seasonality of dust transport may also have played a role in bringing about contributions from both northern and southern sources.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2018.11","usgsCitation":"Muhs, D., Pigati, J.S., Budahn, J.R., Skipp, G.L., Bettis, E.A., and Jensen, B., 2018, Origin of last-glacial loess in the western Yukon-Tanana Upland, central Alaska, USA: Quaternary Research, v. 89, no. 3, p. 797-819, https://doi.org/10.1017/qua.2018.11.","productDescription":"23 p.","startPage":"797","endPage":"819","ipdsId":"IP-086762","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":354407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150,\n 65.5\n ],\n [\n -148.75,\n 65.5\n ],\n [\n -148.75,\n 66\n ],\n [\n -150,\n 66\n ],\n [\n -150,\n 65.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","scienceBaseUri":"5b155d78e4b092d9651e1b3e","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":736257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":736258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budahn, James R. 0000-0001-9794-8882 jbudahn@usgs.gov","orcid":"https://orcid.org/0000-0001-9794-8882","contributorId":1175,"corporation":false,"usgs":true,"family":"Budahn","given":"James","email":"jbudahn@usgs.gov","middleInitial":"R.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":736259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skipp, Gary L. 0000-0002-9404-0980","orcid":"https://orcid.org/0000-0002-9404-0980","contributorId":201777,"corporation":false,"usgs":true,"family":"Skipp","given":"Gary","email":"","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":736260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bettis, E. Arthur III 0000-0002-6137-1433","orcid":"https://orcid.org/0000-0002-6137-1433","contributorId":204005,"corporation":false,"usgs":false,"family":"Bettis","given":"E.","suffix":"III","email":"","middleInitial":"Arthur","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":736261,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jensen, Britta","contributorId":184164,"corporation":false,"usgs":false,"family":"Jensen","given":"Britta","affiliations":[],"preferred":false,"id":736262,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197234,"text":"70197234 - 2018 - Blurred lines: Multiple freshwater and marine algal toxins at the land-sea interface of San Francisco Bay, California","interactions":[],"lastModifiedDate":"2018-05-23T18:20:12","indexId":"70197234","displayToPublicDate":"2018-05-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Blurred lines: Multiple freshwater and marine algal toxins at the land-sea interface of San Francisco Bay, California","docAbstract":"San Francisco Bay (SFB) is a eutrophic estuary that harbors both freshwater and marine toxigenic organisms that are responsible for harmful algal blooms. While there are few commercial fishery harvests within SFB, recreational and subsistence harvesting for shellfish is common. Coastal shellfish are monitored for domoic acid and paralytic shellfish toxins (PSTs), but within SFB there is no routine monitoring for either toxin. Dinophysis shellfish toxins (DSTs) and freshwater microcystins are also present within SFB, but not routinely monitored. Acute exposure to any of these toxin groups has severe consequences for marine organisms and humans, but chronic exposure to sub-lethal doses, or synergistic effects from multiple toxins, are poorly understood and rarely addressed. This study documents the occurrence of domoic acid and microcystins in SFB from 2011 to 2016, and identifies domoic acid, microcystins, DSTs, and PSTs in marine mussels within SFB in 2012, 2014, and 2015. At least one toxin was detected in 99% of mussel samples, and all four toxin suites were identified in 37% of mussels. The presence of these toxins in marine mussels indicates that wildlife and humans who consume them are exposed to toxins at both sub-lethal and acute levels. As such, there are potential deleterious impacts for marine organisms and humans and these effects are unlikely to be documented. These results demonstrate the need for regular monitoring of marine and freshwater toxins in SFB, and suggest that co-occurrence of multiple toxins is a potential threat in other ecosystems where freshwater and seawater mix.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.hal.2018.02.005","usgsCitation":"Peacock, M.B., Gibble, C.M., Senn, D.B., Cloern, J.E., and Kudela, R.M., 2018, Blurred lines: Multiple freshwater and marine algal toxins at the land-sea interface of San Francisco Bay, California: Harmful Algae, v. 73, p. 138-147, https://doi.org/10.1016/j.hal.2018.02.005.","productDescription":"10 p.","startPage":"138","endPage":"147","ipdsId":"IP-086768","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":460917,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2018.02.005","text":"Publisher Index Page"},{"id":354437,"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 -122.87933349609376,\n 37.31119861382921\n ],\n [\n -121.19842529296875,\n 37.31119861382921\n ],\n [\n -121.19842529296875,\n 38.30718056188316\n ],\n [\n -122.87933349609376,\n 38.30718056188316\n ],\n [\n -122.87933349609376,\n 37.31119861382921\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b155d78e4b092d9651e1b3a","contributors":{"authors":[{"text":"Peacock, Melissa B.","contributorId":205179,"corporation":false,"usgs":false,"family":"Peacock","given":"Melissa","email":"","middleInitial":"B.","affiliations":[{"id":37042,"text":"Northwest Indian College","active":true,"usgs":false}],"preferred":false,"id":736305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibble, Corinne M.","contributorId":205180,"corporation":false,"usgs":false,"family":"Gibble","given":"Corinne","email":"","middleInitial":"M.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":736306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Senn, David B.","contributorId":205182,"corporation":false,"usgs":false,"family":"Senn","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":12703,"text":"San Francisco Estuary Institute","active":true,"usgs":false}],"preferred":false,"id":736308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":736304,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kudela, Raphael M.","contributorId":205181,"corporation":false,"usgs":false,"family":"Kudela","given":"Raphael","email":"","middleInitial":"M.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":736307,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196218,"text":"sir20105070P - 2018 - Quartz-pebble-conglomerate gold deposits","interactions":[],"lastModifiedDate":"2024-04-16T16:38:01.913558","indexId":"sir20105070P","displayToPublicDate":"2018-05-17T17:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5070","chapter":"P","title":"Quartz-pebble-conglomerate gold deposits","docAbstract":"Quartz-pebble-conglomerate gold deposits represent the largest repository of gold on Earth, largely due to the deposits of the Witwatersrand Basin, which account for nearly 40 percent of the total gold produced throughout Earth’s history. This deposit type has had a controversial history in regards to genetic models. However, most researchers conclude that they are paleoplacer deposits that have been modified by metamorphism and hydrothermal fluid flow subsequent to initial sedimentation.
The deposits are found exclusively within fault-bounded depositional basins. The periphery of these basins commonly consists of granite-greenstone terranes, classic hosts for lode gold that source the detrital material infilling the basin. The gold reefs are typically located along unconformities or, less commonly, at the top of sedimentary beds. Large quartz pebbles and heavy-mineral concentrates are found associated with the gold. Deposits that formed prior to the Great Oxidation Event (circa 2.4 giga-annum [Ga]) contain pyrite, whereas younger deposits contain iron oxides. Uranium minerals and hydrocarbons are also notable features of some deposits.
Much of the gold in these types of deposits forms crystalline features that are the product of local remobilization. However, some gold grains preserve textures that are undoubtedly of detrital origin. Other heavy minerals, such as pyrite, contain growth banding that is truncated along broken margins, which indicates that they were transported into place as opposed to forming by in situ growth in a hydrothermal setting.
The ore tailings associated with these deposits commonly contain uranium-rich minerals and sulfides. Oxidation of the sulfides releases sulfuric acid and mobilizes various metals into the environment. The neutralizing potential of the tailings is minimal, since carbonate minerals are rare. The continuity of the tabular ore bodies, such as those of the Witwatersrand Basin, has allowed these mines to be the deepest in the world. The extreme depths create engineering complications and safety issues for the miners, such as rock bursts as a result of pressure release.
The richness of these deposits makes them a desirable exploration target. However, the likelihood of future discoveries is minimal. Small deposits found in the United States include those found at Nemo in the Black Hills of South Dakota and Deep Lake in the Sierra Madre of Wyoming.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070P","usgsCitation":"Taylor, R.D., and Anderson, E.D., 2018, Quartz-pebble-conglomerate gold deposits: U.S. Geological Survey Scientific Investigations Report 2010–5070–P, 34 p., https://doi.org/10.3133/sir20105070P","productDescription":"v, 34 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-086517","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":354221,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/p/sir20105070p.pdf","text":"Report","size":"6.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010–5070–P"},{"id":354220,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5070/p/coverthb.jpg"}],"contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS–973
Denver, CO 80225
Raptor nest–site use in relation to the proximity of coalbed–methane development. Energy development such as coalbed–methane (CBM) extraction is a major land use with largely unknown consequences for many animal species. Some raptor species may be especially vulnerable to habitat changes due to energy development given their ecological requirements and population trajectories. Using 12,977 observations of 3,074 nests of 12 raptor species across nine years (2003–2011) in the Powder River Basin, Wyoming, USA, we evaluated relationships between raptor nest–site use and CBM development. Our objectives were to determine temporal trends in nest–use rates, and whether nest–site use was related to the proximity of CBM development. Across the study area, nest–use rates varied across species and years in a non–linear fashion. We developed a novel randomization test to assess differences in use between nests at developed and undeveloped sites, while controlling for annual variation in nest–site use. Red–tailed hawks (Buteo jamaicensis), burrowing owls (Athene cunicularia), and long–eared owls (Asio otus) used nests in undeveloped areas more than nests in developed areas (i.e. nests near CBM development). Differences between development groups were equivocal for the remaining nine species; however, we caution that we likely had lower statistical power to detect differences for rarer species. Our findings suggest potential avoidance of nesting in areas near CBM development by some species and reveal that CBM effects may be fairly consistent across distances between 400–2,415 m from wells. Future work should consider habitat preferences and fitness outcomes, and control for other key factors such as local prey availability, raptor densities, and weather.
","language":"English","publisher":"Museu de Ciències Naturals de Barcelona","doi":"10.32800/abc.2018.41.0227","usgsCitation":"Carlile, J., Sanders, L.E., Chalfoun, A.D., and Gerow, K., 2018, Raptor nest-site use in relation to the proximity of coalbed methane development: Animal Biodiversity and Conservation, v. 41, no. 2, p. 227-243, https://doi.org/10.32800/abc.2018.41.0227.","productDescription":"17 p.","startPage":"227","endPage":"243","ipdsId":"IP-079243","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.32800/abc.2018.41.0227","text":"Publisher Index Page"},{"id":354276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Powder River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.87451171875,\n 44.99588261816546\n ],\n [\n -108.43505859374999,\n 44.55916341529182\n ],\n [\n -107.75390625,\n 44.22945656830167\n ],\n [\n -107.60009765625,\n 43.96119063892024\n ],\n [\n -107.46826171874999,\n 43.75522505306928\n ],\n [\n -107.666015625,\n 43.40504748787035\n ],\n [\n -108.25927734375,\n 42.71473218539458\n ],\n [\n -104.56787109374999,\n 42.69858589169842\n ],\n [\n -104.5458984375,\n 44.98034238084973\n ],\n [\n -108.87451171875,\n 44.99588261816546\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6b9e4b0da30c1bfbd68","contributors":{"authors":[{"text":"Carlile, J.D.","contributorId":205000,"corporation":false,"usgs":false,"family":"Carlile","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":735713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanders, Lindsey E.","contributorId":173998,"corporation":false,"usgs":false,"family":"Sanders","given":"Lindsey","email":"","middleInitial":"E.","affiliations":[{"id":6656,"text":"University of Wyoming, Renewable Resources","active":true,"usgs":false}],"preferred":false,"id":735714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":735373,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerow, K.G.","contributorId":17003,"corporation":false,"usgs":true,"family":"Gerow","given":"K.G.","email":"","affiliations":[],"preferred":false,"id":735715,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197087,"text":"70197087 - 2018 - Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques","interactions":[],"lastModifiedDate":"2019-01-28T09:34:55","indexId":"70197087","displayToPublicDate":"2018-05-16T00:00:00","publicationYear":"2018","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":"Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques","docAbstract":"The American marten Martes americana is a species of conservation concern in the northeastern United States due to widespread declines from over‐harvesting and habitat loss. Little information exists on current marten distribution and how landscape characteristics shape patterns of occupancy across the region, which could help develop effective recovery strategies. The rarity of marten and lack of historical distribution records are also problematic for region‐wide conservation planning. Expert opinion can provide a source of information for estimating species–landscape relationships and is especially useful when empirical data are sparse. We created a survey to elicit expert opinion and build a model that describes marten occupancy in the northeastern United States as a function of landscape conditions. We elicited opinions from 18 marten experts that included wildlife managers, trappers and researchers. Each expert estimated occupancy probability at 30 sites in their geographic region of expertise. We, then, fit the response data with a set of 58 models that incorporated the effects of covariates related to forest characteristics, climate, anthropogenic impacts and competition at two spatial scales (1.5 and 5 km radii), and used model selection techniques to determine the best model in the set. Three top models had strong empirical support, which we model averaged based on AIC weights. The final model included effects of five covariates at the 5‐km scale: percent canopy cover (positive), percent spruce‐fir land cover (positive), winter temperature (negative), elevation (positive) and road density (negative). A receiver operating characteristic curve indicated that the model performed well based on recent occurrence records. We mapped distribution across the region and used circuit theory to estimate movement corridors between isolated core populations. The results demonstrate the effectiveness of expert‐opinion data at modeling occupancy for rare species and provide tools for planning marten recovery in the northeastern United States.
","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.12417","usgsCitation":"Aylward, C., Murdoch, J., Donovan, T.M., Kilpatrick, C., Bernier, C., and Katz, J., 2018, Estimating distribution and connectivity of recolonizing American marten in the northeastern United States using expert elicitation techniques: Animal Conservation, v. 21, no. 6, p. 483-495, https://doi.org/10.1111/acv.12417.","productDescription":"13 p.","startPage":"483","endPage":"495","ipdsId":"IP-090408","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-16","publicationStatus":"PW","scienceBaseUri":"5afee6bae4b0da30c1bfbd74","contributors":{"authors":[{"text":"Aylward, C.M.","contributorId":204950,"corporation":false,"usgs":false,"family":"Aylward","given":"C.M.","email":"","affiliations":[],"preferred":false,"id":735540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murdoch, J.D.","contributorId":204951,"corporation":false,"usgs":false,"family":"Murdoch","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":735541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":735528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kilpatrick, C.W.","contributorId":24188,"corporation":false,"usgs":true,"family":"Kilpatrick","given":"C.W.","email":"","affiliations":[],"preferred":false,"id":735542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernier, C.","contributorId":204952,"corporation":false,"usgs":false,"family":"Bernier","given":"C.","email":"","affiliations":[],"preferred":false,"id":735543,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Katz, J.","contributorId":204953,"corporation":false,"usgs":false,"family":"Katz","given":"J.","email":"","affiliations":[],"preferred":false,"id":735544,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196935,"text":"70196935 - 2018 - Examining speed versus selection in connectivity models using elk migration as an example","interactions":[],"lastModifiedDate":"2018-06-04T16:00:34","indexId":"70196935","displayToPublicDate":"2018-05-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Examining speed versus selection in connectivity models using elk migration as an example","docAbstract":"Context
Landscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity.
Objective
To compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection.
Methods
Using movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements.
Results
All connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models.
Conclusions
CTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.
A challenge for making conservation decisions is predicting how wildlife populations respond to multiple, concurrent threats and potential management strategies, usually under substantial uncertainty. Integrated modeling approaches can improve estimation of demographic rates necessary for making predictions, even for rare or cryptic species with sparse data, but their use in management applications is limited. We developed integrated models for a population of diamondback terrapins (Malaclemys terrapin) impacted by road-associated threats to (i) jointly estimate demographic rates from two mark-recapture datasets, while directly estimating road mortality and the impact of management actions deployed during the study; and (ii) project the population using population viability analysis under simulated management strategies to inform decision-making. Without management, population extirpation was nearly certain due to demographic impacts of road mortality, predators, and vegetation. Installation of novel flashing signage increased survival of terrapins that crossed roads by 30%. Signage, along with small roadside barriers installed during the study, increased population persistence probability, but the population was still predicted to decline. Management strategies that included actions targeting multiple threats and demographic rates resulted in the highest persistence probability, and roadside barriers, which increased adult survival, were predicted to increase persistence more than other actions. Our results support earlier findings showing mitigation of multiple threats is likely required to increase the viability of declining populations. Our approach illustrates how integrated models may be adapted to use limited data efficiently, represent system complexity, evaluate impacts of threats and management actions, and provide decision-relevant information for conservation of at-risk populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.03.023","usgsCitation":"Crawford, B.A., Moore, C.T., Norton, T., and Maerz, J.C., 2018, Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species: Biological Conservation, v. 222, p. 33-43, https://doi.org/10.1016/j.biocon.2018.03.023.","productDescription":"11 p.","startPage":"33","endPage":"43","ipdsId":"IP-083097","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"222","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdc0","contributors":{"authors":[{"text":"Crawford, Brian A.","contributorId":204802,"corporation":false,"usgs":false,"family":"Crawford","given":"Brian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norton, Terry M.","contributorId":71020,"corporation":false,"usgs":true,"family":"Norton","given":"Terry M.","affiliations":[],"preferred":false,"id":735036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maerz, John C.","contributorId":171763,"corporation":false,"usgs":false,"family":"Maerz","given":"John","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":735037,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197444,"text":"70197444 - 2018 - Characterization of Plasmodium relictum, a cosmopolitan agent of avian malaria","interactions":[],"lastModifiedDate":"2018-06-05T10:13:20","indexId":"70197444","displayToPublicDate":"2018-05-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2650,"text":"Malaria Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Characterization of Plasmodium relictum, a cosmopolitan agent of avian malaria","title":"Characterization of Plasmodium relictum, a cosmopolitan agent of avian malaria","docAbstract":"Background
Microscopic research has shown that Plasmodium relictum is the most common agent of avian malaria. Recent molecular studies confirmed this conclusion and identified several mtDNA lineages, suggesting the existence of significant intra-species genetic variation or cryptic speciation. Most identified lineages have a broad range of hosts and geographical distribution. Here, a rare new lineage of P. relictum was reported and information about biological characters of different lineages of this pathogen was reviewed, suggesting issues for future research.
Methods
The new lineage pPHCOL01 was detected in Common chiffchaff Phylloscopus collybita,and the parasite was passaged in domestic canaries Serinus canaria. Organs of infected birds were examined using histology and chromogenic in situ hybridization methods. Culex quinquefasciatus mosquitoes, Zebra finch Taeniopygia guttata, Budgerigar Melopsittacus undulatus and European goldfinch Carduelis carduelis were exposed experimentally. Both Bayesian and Maximum Likelihood analyses identified the same phylogenetic relationships among different, closely-related lineages pSGS1, pGRW4, pGRW11, pLZFUS01, pPHCOL01 of P. relictum. Morphology of their blood stages was compared using fixed and stained blood smears, and biological properties of these parasites were reviewed.
Results
Common canary and European goldfinch were susceptible to the parasite pPHCOL01, and had markedly variable individual prepatent periods and light transient parasitaemia. Exo-erythrocytic and sporogonic stages were not seen. The Zebra finch and Budgerigar were resistant. Neither blood stages nor vector stages of all examined P. relictum lineages can be distinguished morphologically.
Conclusion
Within the huge spectrum of vertebrate hosts, mosquito vectors, and ecological conditions, different lineages of P. relictum exhibit indistinguishable, markedly variable morphological forms. Parasites of same lineages often develop differently in different bird species. Even more, the variation of biological properties (parasitaemia dynamics, blood pathology, prepatent period) in different isolates of the same lineage might be greater than the variation in different lineages during development in the same species of birds, indicating negligible taxonomic value of such features. Available lineage information is excellent for parasite diagnostics, but is limited in predictions about relationships in certain host-parasite associations. A combination of experiments, field observations, microscopic and molecular diagnostics is essential for understanding the role of different P. relictum lineages in bird health.
Major and trace element and radiogenic isotopic characteristics of primitive mafic Pleistocene and Holocene lavas from Newberry Volcano, Oregon, define two groups. The first consists of dry tholeiitic high-alumina olivine basalts that are slightly enriched in highly incompatible elements. The second group consists of calc-alkaline basalts that contained 2–4 wt % H2O prior to eruption and shows strong enrichment in the light rare earth elements, Ba, and Sr, and deficits in Nb, Ta, Hf, and Zr. The tholeiitic basalts reflect 6–11% anhydrous adiabatic decompression melting of spinel peridotite. The calc-alkaline basalts derived from compositionally distinct sources with strong LIL enrichment and relative depletion in HFSE, but with Sr, Nd, Hf, and Pb isotopic composition only slightly distinct from the sources of the tholeiitic magmas. Radiogenic Os correlates with LREE enrichment in the calc-alkaline magmas, which indicates that their source materials include a contribution from a mafic component that was melted in the garnet stability field. The calc-alkaline magmas were derived by melting of peridotite metasomatized by a fluid/melt that originated by melting of a mixture of the sediment plus MORB basalt/mantle in the underlying subducting oceanic plate. While the trace element characteristics of the calc-alkaline magmas were determined by the subduction component, their isotopic characteristics were modified during transit through the mantle by interaction with the highly magmatically processed mantle wedge beneath Newberry Volcano that, without the slab component, serves as the source of the tholeiitic magmas.
The projected rapid changes in climate will affect the unique vegetation assemblages of the Northern Rockies region in myriad ways, both directly through shifts in vegetation growth, mortality, and regeneration, and indirectly through changes in disturbance regimes and interactions with changes in other ecosystem processes, such as hydrology, snow dynamics, and exotic invasions (Bonan 2008; Hansen and Phillips 2015; Hansen et al. 2001; Notaro et al. 2007). These impacts, taken collectively, could change the way vegetation is managed by public land agencies in this area. Some species may be in danger of rapid decreases in abundance, while others may undergo range expansion (Landhäusser et al. 2010). New vegetation communities may form, while historical vegetation complexes may simply shift to other areas of the landscape or become rare. Juxtaposed with climate change concerns are the consequences of other land management policies and past activities, such as fire exclusion, fuels treatments, and grazing. A thorough assessment of the responses of vegetation to projected climate change is needed, along with an evaluation of the vulnerability of important species, communities, and vegetation-related resources that may be influenced by the effects, both direct and indirect, of climate change. This assessment must also account for past management actions and current vegetation conditions and their interactions with future climates.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Climate change vulnerability and adaptation in the Northern Rocky Mountains - Part 1","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Forest Service","usgsCitation":"Keane, R.E., Mahalovich, M.F., Bollenbacher, B.L., Manning, M., Loehman, R.A., Jain, T.B., Holsinger, L.M., Larson, A.J., and Webster, M.M., 2018, Effects of climate change on forest vegetation in the Northern Rockies Region: General Technical Report RMRS-GTR-374, 46 p.","productDescription":"46 p.","startPage":"128","endPage":"173","ipdsId":"IP-072292","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":353420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353337,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/treesearch/pubs/55991"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.00439453125,\n 42.309815415686664\n ],\n [\n -96.45996093749999,\n 42.309815415686664\n ],\n [\n -96.45996093749999,\n 49.009050809382046\n ],\n [\n -117.00439453125,\n 49.009050809382046\n ],\n [\n -117.00439453125,\n 42.309815415686664\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6dce4b0da30c1bfbeca","contributors":{"authors":[{"text":"Keane, Robert E.","contributorId":200723,"corporation":false,"usgs":false,"family":"Keane","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":733254,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahalovich, Mary Frances","contributorId":200724,"corporation":false,"usgs":false,"family":"Mahalovich","given":"Mary","email":"","middleInitial":"Frances","affiliations":[{"id":27110,"text":"U.S. Dept of Agriculture, Forest Service","active":true,"usgs":false}],"preferred":false,"id":733255,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bollenbacher, Barry L.","contributorId":200725,"corporation":false,"usgs":false,"family":"Bollenbacher","given":"Barry","email":"","middleInitial":"L.","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733256,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manning, Mary E.","contributorId":177570,"corporation":false,"usgs":false,"family":"Manning","given":"Mary E.","affiliations":[],"preferred":false,"id":733257,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":733253,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jain, Terrie B.","contributorId":200727,"corporation":false,"usgs":false,"family":"Jain","given":"Terrie","email":"","middleInitial":"B.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":733258,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holsinger, Lisa M.","contributorId":187607,"corporation":false,"usgs":false,"family":"Holsinger","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":733259,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larson, Andrew J.","contributorId":197832,"corporation":false,"usgs":false,"family":"Larson","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":7089,"text":"University of Montana, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":733260,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Webster, Meredith M.","contributorId":204163,"corporation":false,"usgs":false,"family":"Webster","given":"Meredith","email":"","middleInitial":"M.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":733261,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196497,"text":"70196497 - 2018 - Effects of climate change on ecological disturbance in the Northern Rockies Region [Chapter 8]","interactions":[],"lastModifiedDate":"2018-04-13T12:40:12","indexId":"70196497","displayToPublicDate":"2018-04-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"RMRS-GTR-374","title":"Effects of climate change on ecological disturbance in the Northern Rockies Region [Chapter 8]","docAbstract":"This chapter describes the ecology of important disturbance regimes in the Forest Service, U.S. Department of Agriculture (USFS) Northern Region and the Greater Yellowstone Area, hereafter called the Northern Rockies region, and potential shifts in these regimes as a consequence of observed and projected climate change. The term disturbance regime describes the general temporal and spatial characteristics of a disturbance agent - insect, disease, fire, weather, even human activity - and the effects of that agent on the landscape (table 8.1). More specifically, a disturbance regime is the cumulative effect of multiple disturbance events over space and time (Keane 2013). Disturbances disrupt an ecosystem, community, or population structure and change elements of the biological environment, physical environment, or both (White and Pickett 1985). The resulting shifting mosaic of diverse ecological patterns and structures in turn affects future patterns of disturbance, in a reciprocal, linked relationship that shapes the fundamental character of landscapes and ecosystems. Disturbance creates and maintains biological diversity in the form of shifting, heterogeneous mosaics of diverse communities and habitats across a landscape (McKinney and Drake 1998), and biodiversity is generally highest when disturbance is neither too rare nor too frequent on the landscape (Grime 1973).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Climate change vulnerability and adaptation in the Northern Rocky Mountains - Part 2","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Forest Service","usgsCitation":"Loehman, R.A., Bentz, B.J., DeNitto, G.A., Keane, R.E., Manning, M., Duncan, J.P., Egan, J.M., Jackson, M.B., Kegley, S., Lockman, I.B., Pearson, D.E., Powell, J., Shelly, S., Steed, B.E., and Zambino, P.J., 2018, Effects of climate change on ecological disturbance in the Northern Rockies Region [Chapter 8]: General Technical Report RMRS-GTR-374, 36 p.","productDescription":"36 p.","startPage":"317","endPage":"352","ipdsId":"IP-072091","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":353421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353336,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.usda.gov/treesearch/pubs/55993"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.00439453125,\n 42.309815415686664\n ],\n [\n -96.45996093749999,\n 42.309815415686664\n ],\n [\n -96.45996093749999,\n 49.009050809382046\n ],\n [\n -117.00439453125,\n 49.009050809382046\n ],\n [\n -117.00439453125,\n 42.309815415686664\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6dce4b0da30c1bfbecc","contributors":{"authors":[{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":733249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bentz, Barbara J.","contributorId":200734,"corporation":false,"usgs":false,"family":"Bentz","given":"Barbara","email":"","middleInitial":"J.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":733250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeNitto, Gregg A.","contributorId":200735,"corporation":false,"usgs":false,"family":"DeNitto","given":"Gregg","email":"","middleInitial":"A.","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keane, Robert E.","contributorId":200723,"corporation":false,"usgs":false,"family":"Keane","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":733252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Manning, Mary E.","contributorId":177570,"corporation":false,"usgs":false,"family":"Manning","given":"Mary E.","affiliations":[],"preferred":false,"id":733433,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duncan, Jacob P.","contributorId":200736,"corporation":false,"usgs":false,"family":"Duncan","given":"Jacob","email":"","middleInitial":"P.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":733434,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Egan, Joel M.","contributorId":200737,"corporation":false,"usgs":false,"family":"Egan","given":"Joel","email":"","middleInitial":"M.","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733435,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jackson, Marcus B.","contributorId":200738,"corporation":false,"usgs":false,"family":"Jackson","given":"Marcus","email":"","middleInitial":"B.","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733436,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kegley, Sandra","contributorId":200739,"corporation":false,"usgs":false,"family":"Kegley","given":"Sandra","email":"","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733437,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lockman, I. Blakey","contributorId":200740,"corporation":false,"usgs":false,"family":"Lockman","given":"I.","email":"","middleInitial":"Blakey","affiliations":[{"id":27245,"text":"USDA Forest Service, Pacific Northwest Regional Office","active":true,"usgs":false}],"preferred":false,"id":733438,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pearson, Dean E.","contributorId":200741,"corporation":false,"usgs":false,"family":"Pearson","given":"Dean","email":"","middleInitial":"E.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":733439,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Powell, James A.","contributorId":53514,"corporation":false,"usgs":true,"family":"Powell","given":"James A.","affiliations":[],"preferred":false,"id":733440,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Shelly, Steve","contributorId":200742,"corporation":false,"usgs":false,"family":"Shelly","given":"Steve","email":"","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733441,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Steed, Brytten E.","contributorId":200743,"corporation":false,"usgs":false,"family":"Steed","given":"Brytten","email":"","middleInitial":"E.","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733442,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Zambino, Paul J.","contributorId":200744,"corporation":false,"usgs":false,"family":"Zambino","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":35842,"text":"U.S. Forest Service Northern Region, Missoula","active":true,"usgs":false}],"preferred":false,"id":733443,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70196499,"text":"70196499 - 2018 - New insights into the phylogenetics and population structure of the prairie falcon (Falco mexicanus)","interactions":[],"lastModifiedDate":"2018-04-24T14:12:57","indexId":"70196499","displayToPublicDate":"2018-04-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":956,"text":"BMC Genomics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"New insights into the phylogenetics and population structure of the prairie falcon (Falco mexicanus)","title":"New insights into the phylogenetics and population structure of the prairie falcon (Falco mexicanus)","docAbstract":"Background
Management requires a robust understanding of between- and within-species genetic variability, however such data are still lacking in many species. For example, although multiple population genetics studies of the peregrine falcon (Falco peregrinus) have been conducted, no similar studies have been done of the closely-related prairie falcon (F. mexicanus) and it is unclear how much genetic variation and population structure exists across the species’ range. Furthermore, the phylogenetic relationship of F. mexicanus relative to other falcon species is contested. We utilized a genomics approach (i.e., genome sequencing and assembly followed by single nucleotide polymorphism genotyping) to rapidly address these gaps in knowledge.
Results
We sequenced the genome of a single female prairie falcon and generated a 1.17 Gb (gigabases) draft genome assembly. We generated maximum likelihood phylogenetic trees using complete mitochondrial genomes as well as nuclear protein-coding genes. This process provided evidence that F. mexicanus is an outgroup to the clade that includes the peregrine falcon and members of the subgenus Hierofalco. We annotated > 16,000 genes and almost 600,000 high-quality single nucleotide polymorphisms (SNPs) in the nuclear genome, providing the raw material for a SNP assay design featuring > 140 gene-associated markers and a molecular-sexing marker. We subsequently genotyped ~ 100 individuals from California (including the San Francisco East Bay Area, Pinnacles National Park and the Mojave Desert) and Idaho (Snake River Birds of Prey National Conservation Area). We tested for population structure and found evidence that individuals sampled in California and Idaho represent a single panmictic population.
Conclusions
Our study illustrates how genomic resources can rapidly shed light on genetic variability in understudied species and resolve phylogenetic relationships. Furthermore, we found evidence of a single, randomly mating population of prairie falcons across our sampling locations. Prairie falcons are highly mobile and relatively rare long-distance dispersal events may promote gene flow throughout the range. As such, California’s prairie falcons might be managed as a single population, indicating that management actions undertaken to benefit the species at the local level have the potential to influence the species as a whole.
Dams and their impoundments disrupt river habitat connectivity to the detriment of migratory fishes. Removal of dams improves riverine connectivity and lotic habitat, which benefits not only these fishes but also resident fluvial specialist species. Restoration efforts on the Penobscot River, Maine, are among the largest recently completed in the United States and include the removal of the two lowermost dams and improvements to fish passage at several remaining barriers. We assessed fish assemblages in the main‐stem river and several major tributaries before (2010–2012) and after (2014–2016) dam removal using boat electrofishing surveys and a stratified random sampling design. In total, we sampled 303 km of shoreline and captured 107,335 individual fish representing 39 species. Similarity indices and rarefaction curves indicated that significant changes in fish assemblage composition occurred in reaches that underwent both habitat and connectivity changes (i.e., directly above removed dams). The newly connected reaches became more similar in fish assemblage composition, as demonstrated by an average increase of 31% in similarity scores. The changes in similarity score in these reaches were driven by increasing access for anadromous fishes and decreasing abundances of slow‐water specialist species. For example, we observed a marked reduction in lacustrine species in former impoundments. These assemblage shifts were further illustrated by nonmetric multidimensional scaling in which sites directly above former dams exhibited the largest ordinal shifts immediately following dam removal. We also found all anadromous species in greatest abundance below the lowermost dam during each respective sampling period, though we did find some anadromous species above the lowermost dam during postremoval sampling. Our results demonstrate the potential for large dam removal projects to restore both fluvial and anadromous fish assemblages.
","language":"English","publisher":"American Fisheries Society ","doi":"10.1002/tafs.10053","usgsCitation":"Watson, J.M., Coghlan, S.M., Zydlewski, J.D., Hayes, D.B., and Kiraly, I.A., 2018, Dam Removal and Fish Passage Improvement Influence Fish Assemblages in the Penobscot River, Maine: Transactions of the American Fisheries Society, v. 147, no. 3, p. 525-540, https://doi.org/10.1002/tafs.10053.","productDescription":"16 p.","startPage":"525","endPage":"540","ipdsId":"IP-088581","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":356606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.82659912109375,\n 45.583289756006316\n ],\n [\n -68.5382080078125,\n 45.59290020826985\n ],\n [\n -68.45855712890625,\n 45.56502536350451\n ],\n [\n -68.47366333007812,\n 45.468799075209894\n ],\n [\n -68.64120483398438,\n 45.32801318215748\n ],\n [\n -68.69888305664062,\n 45.29421101337773\n ],\n [\n -68.9007568359375,\n 45.27488643704894\n ],\n [\n -69.18228149414062,\n 45.30000710263142\n ],\n [\n -69.3621826171875,\n 45.31256326358576\n ],\n [\n -69.37179565429688,\n 45.155895559488265\n ],\n [\n -68.79364013671875,\n 45.258455371422535\n ],\n [\n -68.66867065429688,\n 45.17235628126675\n ],\n [\n -68.70574951171875,\n 45.059941562221226\n ],\n [\n -68.73870849609375,\n 44.84029065139799\n ],\n [\n -68.8623046875,\n 44.75453548416007\n ],\n [\n -68.895263671875,\n 44.65107027453459\n ],\n [\n -68.8623046875,\n 44.52588470040996\n ],\n [\n -68.78814697265625,\n 44.4808302785626\n ],\n [\n -68.719482421875,\n 44.56503415498704\n ],\n [\n -68.8018798828125,\n 44.72917434046452\n ],\n [\n -68.62884521484375,\n 44.85586880735725\n ],\n [\n -68.58489990234375,\n 45.01918507438176\n ],\n [\n -68.5931396484375,\n 45.27488643704894\n ],\n [\n -68.36242675781249,\n 45.44086267178177\n ],\n [\n -68.302001953125,\n 45.52944081525666\n ],\n [\n -68.411865234375,\n 45.62172169252446\n ],\n [\n -68.6151123046875,\n 45.70234306798271\n ],\n [\n -68.807373046875,\n 45.68123916702059\n ],\n [\n -68.82659912109375,\n 45.583289756006316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-12","publicationStatus":"PW","scienceBaseUri":"5b98a2d9e4b0702d0e842ffb","contributors":{"authors":[{"text":"Watson, Jonathan M.","contributorId":207174,"corporation":false,"usgs":false,"family":"Watson","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":743029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coghlan, Stephen M. Jr.","contributorId":169678,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","suffix":"Jr.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":743030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":742808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Daniel B.","contributorId":16799,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":743031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kiraly, Ian A.","contributorId":169709,"corporation":false,"usgs":false,"family":"Kiraly","given":"Ian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":743032,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196360,"text":"70196360 - 2018 - Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity","interactions":[],"lastModifiedDate":"2018-04-03T14:09:14","indexId":"70196360","displayToPublicDate":"2018-04-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity","docAbstract":"One of the primary goals of biological assessment of streams is to identify which of a suite of chemical stressors is limiting their ecological potential. Elevated metal concentrations in streams are often associated with low pH, yet the effects of these two potentially limiting factors of freshwater biodiversity are rarely considered to interact beyond the effects of pH on metal speciation. Using a dataset from two continents, a biogeochemical model of the toxicity of metal mixtures (Al, Cd, Cu, Pb, Zn) and quantile regression, we addressed the relative importance of both pH and metals as limiting factors for macroinvertebrate communities. Current environmental quality standards for metals proved to be protective of stream macroinvertebrate communities and were used as a starting point to assess metal mixture toxicity. A model of metal mixture toxicity accounting for metal interactions was a better predictor of macroinvertebrate responses than a model considering individual metal toxicity. We showed that the direct limiting effect of pH on richness was of the same magnitude as that of chronic metal toxicity, independent of its influence on the availability and toxicity of metals. By accounting for the direct effect of pH on macroinvertebrate communities, we were able to determine that acidic streams supported less diverse communities than neutral streams even when metals were below no-effect thresholds. Through a multivariate quantile model, we untangled the limiting effect of both pH and metals and predicted the maximum diversity that could be expected at other sites as a function of these variables. This model can be used to identify which of the two stressors is more limiting to the ecological potential of running waters.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.12.097","usgsCitation":"Fornaroli, R., Ippolito, A., Tolkkinen, M.J., Mykra, H., Muotka, T., Balistrieri, L.S., and Schmidt, T., 2018, Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity: Environmental Pollution, v. 235, p. 889-898, https://doi.org/10.1016/j.envpol.2017.12.097.","productDescription":"10 p.","startPage":"889","endPage":"898","ipdsId":"IP-079637","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":437964,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7R20ZJW","text":"USGS data release","linkHelpText":"Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity: datasets"},{"id":353113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"235","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6e9e4b0da30c1bfbf3d","contributors":{"authors":[{"text":"Fornaroli, Riccardo","contributorId":201354,"corporation":false,"usgs":false,"family":"Fornaroli","given":"Riccardo","email":"","affiliations":[],"preferred":false,"id":732575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ippolito, Alessio","contributorId":201355,"corporation":false,"usgs":false,"family":"Ippolito","given":"Alessio","email":"","affiliations":[],"preferred":false,"id":732576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tolkkinen, Mari J.","contributorId":201357,"corporation":false,"usgs":false,"family":"Tolkkinen","given":"Mari","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":732578,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mykra, Heikki","contributorId":201358,"corporation":false,"usgs":false,"family":"Mykra","given":"Heikki","email":"","affiliations":[],"preferred":false,"id":732579,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Muotka, Timo","contributorId":201359,"corporation":false,"usgs":false,"family":"Muotka","given":"Timo","email":"","affiliations":[],"preferred":false,"id":732580,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":732574,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":1300,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis S.","email":"tschmidt@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":732577,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70211579,"text":"70211579 - 2018 - Risk factors associated with mortality of age-0 Smallmouth Bass in the Susquehanna River basin, Pennsylvania","interactions":[],"lastModifiedDate":"2020-07-31T15:23:15.144007","indexId":"70211579","displayToPublicDate":"2018-03-29T08:50:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2177,"text":"Journal of Aquatic Animal Health","active":true,"publicationSubtype":{"id":10}},"title":"Risk factors associated with mortality of age-0 Smallmouth Bass in the Susquehanna River basin, Pennsylvania","docAbstract":"Evidence of disease and mortalities of young of the year (age‐0) Smallmouth Bass Micropterus dolomieu has occurred during the late spring and summer in many parts of the Susquehanna River watershed since 2005. To better understand contributing factors, fish collected from multiple areas throughout the watershed as well as out‐of‐basin reference populations (Allegheny and Delaware River basins; experimental ponds, Kearneysville, West Virginia) were examined grossly and histologically for abnormalities. Tissue contaminant concentrations were determined from whole‐body homogenates, and water contaminant concentrations were estimated using time‐integrated passive samplers at selected sites. Observed or isolated pathogens included bacteria, predominantly motile Aeromonas spp. and Flavobacterium columnare ; largemouth bass virus, and parasites, including trematode metacercariae, cestodes, and the myxozoan Myxobolus inornatus . Although these pathogens were found in age‐0 Smallmouth Bass from multiple sites, no one pathogen was consistently associated with mortality. Chemicals detected in tissue included polychlorinated biphenyl (PCB) congeners, organochlorine, and current‐use pesticides. Pyraclostrobin, PCB congeners 170 and 187, cis‐chlordane and trans‐nonachlor were detected in all Susquehanna watershed samples but rarely in samples from the reference site. The findings support the idea that there is no single cause for disease of age‐0 Smallmouth Bass; rather the cumulative effects of co‐infections and potential immunomodulation by environmental stressors during a sensitive developmental life stage may lead to mortality. Identifying the most important risk factors will be necessary for more in‐depth analyses of individual stressors and better management of the habitat and fish populations.
","language":"English","publisher":"Wiley","doi":"10.1002/aah.10009","usgsCitation":"Walsh, H.L., Blazer, V., Smith, G., Lookenbill, M., Alvarez, D.A., and Smalling, K., 2018, Risk factors associated with mortality of age-0 Smallmouth Bass in the Susquehanna River basin, Pennsylvania: Journal of Aquatic Animal Health, v. 30, no. 1, p. 65-80, https://doi.org/10.1002/aah.10009.","productDescription":"16 p.","startPage":"65","endPage":"80","ipdsId":"IP-088555","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":468883,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aah.10009","text":"Publisher Index Page"},{"id":376952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Susquehanna River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.475341796875,\n 39.74943369178247\n ],\n [\n -75.443115234375,\n 39.74943369178247\n ],\n [\n -75.443115234375,\n 41.95131994679697\n ],\n [\n -78.475341796875,\n 41.95131994679697\n ],\n [\n -78.475341796875,\n 39.74943369178247\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Walsh, Heather L. 0000-0001-6392-4604","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":213348,"corporation":false,"usgs":false,"family":"Walsh","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":794683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Geoffrey","contributorId":199064,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey","affiliations":[],"preferred":false,"id":794685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lookenbill, Michael 0000-0001-5857-8276","orcid":"https://orcid.org/0000-0001-5857-8276","contributorId":236910,"corporation":false,"usgs":false,"family":"Lookenbill","given":"Michael","email":"","affiliations":[{"id":17703,"text":"Pennsylvania Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":794686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez, David A. 0000-0002-6918-2709","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":220763,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":794687,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794688,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191014,"text":"sir20175111 - 2018 - Review of the geochemistry and metallogeny of approximately 1.4 Ga granitoid intrusions of the conterminous United States","interactions":[],"lastModifiedDate":"2020-10-05T16:15:21.750634","indexId":"sir20175111","displayToPublicDate":"2018-03-27T15:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5111","title":"Review of the geochemistry and metallogeny of approximately 1.4 Ga granitoid intrusions of the conterminous United States","docAbstract":"The conterminous United States hosts numerous volumetrically significant and geographically dispersed granitoid intrusions that range in age from 1.50 to 1.32 billion years before present (Ga). Although previously referred to as A-type granites, most are better described as ferroan granites. These granitoid intrusions are distributed in the northern and central Rocky Mountains, the Southwest, the northern midcontinent, and a swath largely buried beneath Phanerozoic cover across the Great Plains and into the southern midcontinent. These intrusions, with ages that are bimodally distributed between about 1.455–1.405 Ga and 1.405–1.320 Ga, are dispersed nonsystematically with respect to age across their spatial extents. Globally, although A-type or ferroan granites are genetically associated with rare-metal deposits, most U.S. 1.4 Ga granitoid intrusions do not contain significant deposits. Exceptions are the light rare-earth element deposit at Mountain Pass, California, and the iron oxide-apatite and iron oxide-copper-gold deposits in southeast Missouri.
Most of the U.S. 1.4 Ga granitoid intrusions are composed of hornblende ± biotite or biotite ± muscovite monzogranite, commonly with prominent alkali feldspar megacrysts; however, modal compositions vary widely. These intrusions include six of the eight commonly identified subtypes of ferroan granite: alkali-calcic and calc-alkalic peraluminous subtypes; alkalic, alkali-calcic, and calc-alkalic metaluminous subtypes; and the alkalic peralkaline subtype. The U.S. 1.4 Ga granitoid intrusions also include variants of these subtypes that have weakly magnesian compositions. Extreme large-ion lithophile element enrichments typical of ferroan granites elsewhere are absent among these intrusions. Chondrite-normalized rare-earth element patterns for these intrusions have modest negative slopes and moderately developed negative europium anomalies. Their radiogenic isotopic compositions are consistent with mixing involving primitive, mantle-derived components and evolved, crust-derived components.
Each compositional subtype can be ascribed to a relatively unique petrogenetic history. The numerically dominant ferroan, peraluminous granites probably represent low-degree, relatively high-pressure partial melting of preexisting, crust-derived, intermediate-composition granitoids. The moderately numerous, weakly magnesian, peraluminous granites probably reflect similar partial melting but at a higher degree and in a lower pressure environment. In contrast, the ferroan but metaluminous granites may be the result of extensive differentiation of tholeiitic basalt. Finally, the peralkaline igneous rocks at Mountain Pass have compositions potentially derived by differentiation of alkali basalt. The varying alkalic character of each subtype probably reflects polybaric petrogenesis and the corresponding effect of diverse mineral stabilities on ultimate melt compositions. Mantle-derived mafic magma and variably assimilated partial melts of mainly juvenile Paleoproterozoic crustal components are required to generate the relatively low initial strontium (87Sr/86Sr) and distinctive neodymium isotope compositions characteristic of the U.S. 1.4 Ga granitoid intrusions. The characteristics of these intrusions are consistent with crustal melting in an extensional/decompressional, intracratonic setting that was triggered by mantle upwelling and emplacement of tholeiitic basaltic magma at or near the base of the crust. Composite magmas, formed by mingling and mixing mantle components with partial melts of Paleoproterozoic crust, produced variably homogenized storage reservoirs that continued polybaric evolution as intrusions lodged at various crustal depths.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175111","usgsCitation":"du Bray, E.A., Holm-Denoma, C.S., Lund, Karen, and Premo, W.R., 2018, Review of the geochemistry and metallogeny of approximately 1.4 Ga granitoid intrusions of the conterminous United States: U.S. Geological Survey Scientific Investigations Report 2017–5111, 34 p., https://doi.org/sir20175111.","productDescription":"vi, 34 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-084161","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":352708,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5111/coverthb.jpg"},{"id":352709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5111/sir20175111.pdf","text":"Report","size":"38.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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\"}}]}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 973
Denver, CO 80225
Fecal DNA collected noninvasively can provide valuable information about genetic and ecological characteristics. This approach has rarely been used for equids, despite the need for conservation of endangered species and management of abundant feral populations. We examined factors affecting the efficacy of using equid fecal samples for conservation genetics. First, we evaluated two fecal collection methods (paper bag vs. ethanol). Then, we investigated how time since deposition and month of collection impacted microsatellite amplification success and genotyping errors. Between May and November 2014, we collected feral horse fecal samples of known age each month in a feral horse Herd Management Area in western Colorado and documented deterioration in the field with photographs. Samples collected and dried in paper bags had significantly higher amplification rates than those collected and stored in ethanol. There was little difference in the number of loci that amplified per sample between fresh fecal piles and those that had been exposed to the environment for up to 2 months (in samples collected in paper bags). After 2 months of exposure, amplification success declined. When comparing fresh (0–2 months) and old (3–6 months) fecal piles, samples from fresh piles had more matching genotypes across samples, better amplification success and less allelic dropout. Samples defecated during the summer and collected within 2 months of deposition had highest number of genotypes matching among samples, and lowest rates of amplification failure and allelic dropout. Due to the digestive system and amount of fecal material produced by equids, as well as their occurrence in arid ecosystems, we suggest that they are particularly good candidates for noninvasive sampling using fecal DNA.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3956","usgsCitation":"King, S., Schoenecker, K.A., Fike, J.A., and Oyler-McCance, S.J., 2018, Long-term persistence of horse fecal DNA in the environment makes equids particularly good candidates for non-invasive sampling: Ecology and Evolution, v. 8, no. 8, p. 4053-4064, https://doi.org/10.1002/ece3.3956.","productDescription":"12 p.","startPage":"4053","endPage":"4064","ipdsId":"IP-092556","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3956","text":"Publisher Index Page"},{"id":373554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Grand Junction","otherGeospatial":"Little Book Cliffs Wild Horse Herd Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.37051391601562,\n 39.12366825402605\n ],\n [\n -108.28811645507812,\n 39.17478791493289\n ],\n [\n -108.38699340820312,\n 39.28223089949212\n ],\n [\n -108.47763061523438,\n 39.29604824402406\n ],\n [\n -108.51058959960938,\n 39.22480659786848\n ],\n [\n -108.46939086914062,\n 39.16201148082406\n ],\n [\n -108.37051391601562,\n 39.12366825402605\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"King, Sarah R.B.","contributorId":127791,"corporation":false,"usgs":false,"family":"King","given":"Sarah R.B.","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":785637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823 fikej@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":140875,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785638,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196105,"text":"ofr20171164 - 2018 - Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model","interactions":[],"lastModifiedDate":"2018-03-21T10:52:15","indexId":"ofr20171164","displayToPublicDate":"2018-03-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1164","displayTitle":"Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model","title":"Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model","docAbstract":"The giant gartersnake (Thamnophis gigas) is a state and federally threatened species precinctive to California. The range of the giant gartersnake has contracted in the last century because its wetland habitat has been drained for agriculture and development. As a result of this habitat alteration, giant gartersnakes now largely persist in and near rice agriculture in the Sacramento Valley, because the system of canals that conveys water for rice growing approximates historical wetland habitat. Many aspects of the demography of giant gartersnakes are unknown, including how individuals grow throughout their life, how size influences reproduction, and how survival varies over time and among populations. We studied giant gartersnakes throughout the Sacramento Valley of California from 1995 to 2016 using capture-mark-recapture to study the growth, reproduction, and survival of this threatened species. We then use these data to construct an Integral Projection Model, and analyze this demographic model to understand which vital rates contribute most to the growth rate of giant gartersnake populations. We find that giant gartersnakes exhibit indeterminate growth; growth slows as individuals’ age. Fecundity, probability of reproduction, and survival all increase with size, although survival may decline for the largest female giant gartersnakes. The population growth rate of giant gartersnakes is most influenced by the survival and growth of large adult females, and the size at which 1 year old recruits enter the population. Our results indicate that management actions benefitting these influential demographic parameters will have the greatest positive effect on giant gartersnake population growth rates, and therefore population persistence. This study informs the conservation and management of giant gartersnakes and their habitat, and illustrates the effectiveness of hierarchical Bayesian models for the study of rare and elusive species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171164","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Rose, J.P., Ersan, J.S.M., Wylie, G.D., Casazza, M.L., and Halstead, B.J., 2018, Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model: U.S. Geological Survey Open-File Report 2017–1164, 98 p., https://doi.org/10.3133/ofr20171164.","productDescription":"viii, 98 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-090465","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":352644,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1164/ofr20171164.pdf","text":"Report","size":"8.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1164"},{"id":352643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1164/coverthb.jpg"}],"contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Molecular studies have revealed that social groups composed mainly of nonrelatives may be widespread in group-living vertebrates, but the benefits favoring such sociality are not well understood. In the Old World, birds often form conspecific foraging groups that are maintained year-round and offspring usually disperse to other social groups. We tested the hypothesis that nonbreeding group members are largely unrelated and gain direct fitness benefits through breeding opportunities (males) and brood parasitism (females) in the tropical gray-throated babbler, Stachyris nigriceps, in Malaysian Borneo. Babblers foraged in social groups containing one or more breeding pairs (median = 8 group members of equal sex ratio), but group members rarely assisted with breeding (9% of 67 breeding pairs had a third helper; exhibiting facultative cooperative breeding). Although 20% of 266 group member dyads were first-order relatives of one or both members of the breeding pairs, 80% were unrelated. Male group members gained direct fitness benefits through extrapair and extra-group paternity (25% of 73 offspring), which was independent of their relatedness to the breeding pair and increased with decreasing group size. In contrast, females did not gain direct fitness benefits through brood parasitism. The low levels of relatedness and helping in social groups suggest that most group members do not gain indirect fitness benefits by helping to raise unrelated offspring. These findings highlight the importance of examining benefits of sociality for unrelated individuals that largely do not help and broaden the direct fitness benefits of group foraging beyond assumed survival benefits.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/beheco/arx196","usgsCitation":"Kaiser, S.A., Martin, T.E., Oteyza, J.C., Armstad, C.E., and Fleischer, R.C., 2018, Direct fitness benefits and kinship of social foraging groups in an Old World tropical babbler: Behavioral Ecology, v. 29, no. 2, p. 468-478, https://doi.org/10.1093/beheco/arx196.","productDescription":"11 p.","startPage":"468","endPage":"478","ipdsId":"IP-081140","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468918,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/beheco/arx196","text":"Publisher Index Page"},{"id":352726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5afee6fee4b0da30c1bfc036","contributors":{"authors":[{"text":"Kaiser, Sara A.","contributorId":203454,"corporation":false,"usgs":false,"family":"Kaiser","given":"Sara","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":731543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":731535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oteyza, Juan C.","contributorId":166761,"corporation":false,"usgs":false,"family":"Oteyza","given":"Juan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Armstad, Connor E.","contributorId":201088,"corporation":false,"usgs":false,"family":"Armstad","given":"Connor","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":731545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fleischer, Robert C.","contributorId":105421,"corporation":false,"usgs":true,"family":"Fleischer","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":731546,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195955,"text":"70195955 - 2018 - Raptor interactions with wind energy: Case studies from around the world","interactions":[],"lastModifiedDate":"2018-03-12T10:18:04","indexId":"70195955","displayToPublicDate":"2018-03-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Raptor interactions with wind energy: Case studies from around the world","docAbstract":"The global potential for wind power generation is vast, and the number of installations is increasing rapidly. We review case studies from around the world of the effects on raptors of wind-energy development. Collision mortality, displacement, and habitat loss have the potential to cause population-level effects, especially for species that are rare or endangered. The impact on raptors has much to do with their behavior, so careful siting of wind-energy developments to avoid areas suited to raptor breeding, foraging, or migration would reduce these effects. At established wind farms that already conflict with raptors, reduction of fatalities may be feasible by curtailment of turbines as raptors approach, and offset through mitigation of other human causes of mortality such as electrocution and poisoning, provided the relative effects can be quantified. Measurement of raptor mortality at wind farms is the subject of intense effort and study, especially where mitigation is required by law, with novel statistical approaches recently made available to improve the notoriously difficult-to-estimate mortality rates of rare and hard-to-detect species. Global standards for wind farm placement, monitoring, and effects mitigation would be a valuable contribution to raptor conservation worldwide.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-100.1","usgsCitation":"Watson, R.T., Kolar, P.S., Ferrer, M., Nygard, T., Johnston, N., Hunt, W.G., Smit-Robinson, H.A., Farmer, C.J., Huso, M.M., and Katzner, T., 2018, Raptor interactions with wind energy: Case studies from around the world: Journal of Raptor Research, v. 52, no. 1, p. 1-18, https://doi.org/10.3356/JRR-16-100.1.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-082079","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-16-100.1","text":"Publisher Index Page"},{"id":352368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Egypt, Lesotho, Morocco, Norway, South Africa, Spain, United 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