The Native Prairie Adaptive Management initiative is a decision support framework that provides cooperators with management-action recommendations to help them conserve native species and suppress invasive species on prairie lands. We developed a Web-based decision support tool (DST) for the U.S. Fish and Wildlife Service and the U.S. Geological Survey initiative. The DST facilitates cross-organizational data sharing, performs analyses to improve conservation delivery, and requires no technical expertise to operate. Each year since 2012, the DST has used monitoring data to update ecological knowledge that it translates into situation-specific management-action recommendations (e.g., controlled burn or prescribed graze). The DST provides annual recommendations for more than 10,000 acres on 20 refuge complexes in four U.S. states. We describe how the DST promotes the long-term implementation of the program for which it was designed and may facilitate decision support and improve ecological outcomes of other conservation efforts.
","language":"English","publisher":"Informs","doi":"10.1287/inte.2015.0822","usgsCitation":"Hunt, V.M., Jacobi, S., Gannon, J., Zorn, J.E., Moore, C.T., and Lonsdorf, E.V., 2016, A decision support tool for adaptive management of native prairie ecosystems: Interfaces, v. 46, no. 4, p. 334-344, https://doi.org/10.1287/inte.2015.0822.","productDescription":"11 p.","startPage":"334","endPage":"344","ipdsId":"IP-053560","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fd7ae4b06e28e9c24ef8","contributors":{"authors":[{"text":"Hunt, Victoria M.","contributorId":200688,"corporation":false,"usgs":false,"family":"Hunt","given":"Victoria","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobi, Sarah","contributorId":149496,"corporation":false,"usgs":false,"family":"Jacobi","given":"Sarah","email":"","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":723060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gannon, Jill J.","contributorId":12722,"corporation":false,"usgs":true,"family":"Gannon","given":"Jill J.","affiliations":[],"preferred":false,"id":723061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zorn, Jennifer E.","contributorId":200689,"corporation":false,"usgs":false,"family":"Zorn","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":723062,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":718090,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":723063,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188455,"text":"70188455 - 2016 - Corrigendum to “Widespread occurrence of (per)chlorate in the Solar System” [Earth Planet. Sci. Lett. 430 (2015) 470–476]","interactions":[],"lastModifiedDate":"2017-06-12T09:45:18","indexId":"70188455","displayToPublicDate":"2016-02-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Corrigendum to “Widespread occurrence of (per)chlorate in the Solar System” [Earth Planet. Sci. Lett. 430 (2015) 470–476]","docAbstract":"The authors regret that two sets of data (Atacama (Rao et al., 2010) and Mars Meteorite Range (Kounaves et al., 2014)) in Fig. 2 of our article were plotted in the wrong units. The correction does not change the relationship between
In the four years after the 2008 eruption and burial of Kasatochi Island volcano, erosion and the return of bird activity have resulted in new and altered land surfaces and initiation of ecosystem recovery. We examined fertility characteristics of the recently deposited pyroclastic surfaces, patches of legacy pre-eruptive surface soil (LS), and a post-eruptive surface with recent bird roosting activity. Pyroclastic materials were found lacking in N, but P, K, and other macronutrients were in sufficient supply for plants. Erosion and leaching are moving mobile P and Fe downslope to deposition fan areas. Legacy soil patches that currently support plants have available-N at levels (10–22 mg N kg-1) similar to those added by birds in a recent bird roosting area. Roosting increased surface available N from <1 mg N kg-1 in the new pyroclastic surfaces to up to 42 mg N kg-1 and increased soil biological respiration of CO2 from essentially zero to a level about 40% that of the LS surface. Laboratory plant growth trials using Lupinus nootkatensis and Leymus mollis indicated that the influence of eroded and redeposited LS in amounts as little as 10% by volume mixed with new pyroclastic materials could aid plant recovery by supplying vital N and soil biota to plants as propagules are introduced to the new surface. Erosion-exposure of fertile pre-eruptive soils and erosion-mixing of pre-eruptive soils with newly erupted materials, along with inputs of nutrients from bird activities, each will exert significant influences on the surface fertility and recovery pattern of the new post-eruptive Kasatochi volcano. For this environment, these influences could help to speed recovery of a more diverse plant community by providing N (LS and bird inputs) as alternatives to relying most heavily on N-fixing plants to build soil fertility.
","language":"English","publisher":"Institute of Arctic and Alpine Research (INSTAAR), University of Colorado","doi":"10.1657/AAAR0014-089","usgsCitation":"Michaelson, G.J., Wang, B., and Ping, C., 2016, Fertility of the early post-eruptive surfaces of Kasatochi Island volcano: Arctic, Antarctic, and Alpine Research, v. 48, no. 1, p. 45-59, https://doi.org/10.1657/AAAR0014-089.","productDescription":"15 p.","startPage":"45","endPage":"59","ipdsId":"IP-061100","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":471293,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1657/aaar0014-089","text":"Publisher Index Page"},{"id":352933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kasatochi Island Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -175.5369758605957,\n 52.15708463620445\n ],\n [\n -175.48633575439453,\n 52.15708463620445\n ],\n [\n -175.48633575439453,\n 52.18829929601143\n ],\n [\n -175.5369758605957,\n 52.18829929601143\n ],\n [\n -175.5369758605957,\n 52.15708463620445\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"5afeea40e4b0da30c1bfc5d6","contributors":{"authors":[{"text":"Michaelson, G. J.","contributorId":194081,"corporation":false,"usgs":false,"family":"Michaelson","given":"G.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Bronwen 0000-0003-1044-2227 bwang@usgs.gov","orcid":"https://orcid.org/0000-0003-1044-2227","contributorId":2351,"corporation":false,"usgs":true,"family":"Wang","given":"Bronwen","email":"bwang@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":703156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ping, C. L.","contributorId":194082,"corporation":false,"usgs":false,"family":"Ping","given":"C. L.","affiliations":[],"preferred":false,"id":703158,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168661,"text":"70168661 - 2016 - Winter distribution and use of high elevation caves as foraging sites by the endangered Hawaiian hoary bat, Lasiurus cinereus semotus","interactions":[],"lastModifiedDate":"2018-01-04T12:41:10","indexId":"70168661","displayToPublicDate":"2016-01-31T22:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-068","title":"Winter distribution and use of high elevation caves as foraging sites by the endangered Hawaiian hoary bat, Lasiurus cinereus semotus","docAbstract":"We examine altitudinal movements involving unusual use of caves by Hawaiian hoary bats, Lasiurus cinereus semotus, during winter and spring in the Mauna Loa Forest Reserve (MLFR), Hawai‘i Island. Acoustic detection of hoary bat vocalizations, were recorded with regularity outside 13 lava tube cave entrances situated between 2,200 to 3,600 m asl from November 2012 to April 2013. Vocalizations were most numerous in November and December with the number of call events and echolocation pulses decreasing through the following months. Bat activity was positively correlated with air temperature and negatively correlated with wind speed. Visual searches found no evidence of hibernacula nor do Hawaiian hoary bats appear to shelter by day in these caves. Nevertheless, bats fly deep into caves as evidenced by numerous carcasses found in cave interiors. The occurrence of feeding buzzes around cave entrances and visual observations of bats flying in acrobatic fashion in cave interiors point to the use of these spaces as foraging sites. Peridroma moth species (Noctuidae), the only abundant nocturnal, flying insect sheltering in large numbers in rock rubble and on cave walls in the MLFR, apparently serve as the principal prey attracting hoary bats during winter to lava tube caves in the upper MLFR. Caves above 3,000 m on Mauna Loa harbor temperatures suitable for Pseudogymnoascus destructansfungi, the causative agent of White-nose Syndrome that is highly lethal to some species of North American cave-dwelling bats. We discuss the potential for White-nose Syndrome to establish and affect Hawaiian hoary bats.
","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Bonaccorso, F., Montoya-Aiona, K., Pinzari, C., and Todd, C.M., 2016, Winter distribution and use of high elevation caves as foraging sites by the endangered Hawaiian hoary bat, Lasiurus cinereus semotus: Technical Report HCSU-068, no. 68, Report: ii, 24 p.","productDescription":"Report: ii, 24 p.","startPage":"1","endPage":"24","numberOfPages":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071181","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326261,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","issue":"68","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad75e4b05e859bdfbb2b","contributors":{"authors":[{"text":"Bonaccorso, Frank 0000-0002-5490-3083 fbonaccorso@usgs.gov","orcid":"https://orcid.org/0000-0002-5490-3083","contributorId":143709,"corporation":false,"usgs":true,"family":"Bonaccorso","given":"Frank","email":"fbonaccorso@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":621184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Montoya-Aiona, Kristina 0000-0002-1776-5443 kmontoya-aiona@usgs.gov","orcid":"https://orcid.org/0000-0002-1776-5443","contributorId":5899,"corporation":false,"usgs":true,"family":"Montoya-Aiona","given":"Kristina","email":"kmontoya-aiona@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":621185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pinzari, Corinna A.","contributorId":57359,"corporation":false,"usgs":true,"family":"Pinzari","given":"Corinna A.","affiliations":[],"preferred":false,"id":621186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Christopher M.","contributorId":64548,"corporation":false,"usgs":true,"family":"Todd","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":621187,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168652,"text":"70168652 - 2016 - Effects of Climate and land use on diversity, prevalence, and seasonal transmission of avian hematozoa in American Samoa","interactions":[],"lastModifiedDate":"2018-01-04T12:40:35","indexId":"70168652","displayToPublicDate":"2016-01-31T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":414,"text":"Technical Report","active":false,"publicationSubtype":{"id":9}},"seriesNumber":"HCSU-072","title":"Effects of Climate and land use on diversity, prevalence, and seasonal transmission of avian hematozoa in American Samoa","docAbstract":"The indigenous forest birds of American Samoa are increasingly threatened by changing patterns of rainfall and temperature that are associated with climate change as well as environmental stressors associated with agricultural and urban development, invasive species, and new introductions of avian diseases and disease vectors. Long term changes in their distribution, diversity, and population sizes could have significant impacts on the ecological integrity of the islands because of their critical role as pollinators and seed dispersers. We documented diversity of vector borne parasites on Tutuila and Ta‘u Islands over a 10-year period to expand earlier observations of Plasmodium, Trypanosoma, and filarial parasites, to provide better parasite identifications, and to create a better baseline for detecting new parasite introductions. We also identified potential mosquito vectors of avian Plasmodium and Trypanosoma, determined whether land clearing and habitat alterations associated with subsistence farming within the National Park of American Samoa can influence parasite prevalence, and determined whether parasite prevalence is correlated with seasonal changes in rainfall, temperature and wind speed.
\nThree taxonomically distinct lineages of Plasmodium were identified from mosquito vectors and forest birds based on partial sequence data from parasite mitochondrial genes. All three have been described from passerine and galliform birds in Australasia. Two lineages, SCEDEN01 and ORW1, had elongate gametocytes and large schizonts that were consistent with species of Plasmodium in the subgenus Giavannolaia, but were taxonomically distinct from known morphological species of Plasmodium based on a Bayesian phylogenetic analysis of a 478 bp region of the parasite cytochrome b gene. Both are candidates for description as new species. The third lineage (GALLUS02) was detected only in mosquito vectors on Tutuila and was similar in cytochrome b sequence to P. juxtanucleare, a pathogenic species of Plasmodium from chickens and other galliform birds from Australasia, Africa, and South America. Plasmodium relictum, the malarial parasite that has had such a devastating impact on Hawaiian forest birds, was not detected. We observed large, striated trypanosomes in avian hosts from both Tutuila and Ta‘u Islands that fell within the same taxonomic clade as T. corvi and T. culicavium based on 18S ribosomal DNA sequence. We also observed sheathed microfilariae with pointed tails that had some morphological similarities to microfilaria from species of Pelecitus, Struthiofilaria and Eulimdana, but identification will require recovery and examination of adult filarial worms from the connective tissue or body cavities of infected birds. We also observed one or more species of haemococcidians (Isospora, synonym = Atoxoplasma) within circulating lymphocytes from multiple avian host species.
\nOverall prevalence of Plasmodium was higher on Ta‘u (22%, 75/341) than Tutuila (9.2%, 27/294), with most infections occurring in Polynesian starlings, Samoan starlings, Wattled honeyeaters, and Cardinal honeyeaters. Prevalence was relatively constant from year to year and between seasons at individual study sites, but varied among study sites, with highest rates of infection in areas with agricultural activity at Faleasao (37.4%, 73/195, Ta‘u Island) and Amalau Valley (9.7%, 21/216, Tutuila Island). Prevalence in more remote areas of the National Park of American Samoa was lower, ranging from 1.4% (2/146) at Laufuti and Luatele on Ta‘u to 7.7% (6/78) at Olo Ridge on Tutuila. Similar trends were evident for infections with Trypanosoma and filarial worms. Overall prevalence was not influenced significantly by warmer, wet (summer) or cooler, dry (winter) season.
\nWe detected Plasmodium infections in Culex sitiens and C. quinquefasciatus through either salivary gland and midgut dissections or PCR amplification of parasite cytochrome b genes in pooled or individual samples of mosquitoes that were collected on Tutuila. Pooled or individual Aedes oceanicus, A. polynesiensis, A. tutuilae, A. upolensis, A. nocturnus, Aedes (Finlaya) (mixed pools of A. samoanus, A. oceanicus, A. tutuilae), Aedes (Stegomyia) (mixed pools of A. aegypti, A. upolensis, A. polynesiensis), and C. annulirostris were negative for Plasmodium, but we detected infections with Trypanosoma through midgut and salivary gland dissections in a single C. sitiens from Amalau Valley, Tutuila and three A. oceanicus from Faleasao, Ta‘u. Two of the A. oceanicus from Faleasao amplified successfully with Trypanosoma primers, but sequences were distinctly different from those obtained from avian hosts.
\nWe found a strong association between land use and prevalence of mosquito-transmitted parasites on Ta‘u Island with odds of being infected more than 20 times greater in agricultural plots than more remote native forest. This relationship was evident on Tutuila Island but not statistically significant because of the close proximity of study sites and observed movement of birds between native forest and agricultural land. Our data support previous studies that have suggested that Plasmodium and other vector-borne parasites are part of the indigenous parasite fauna in American Samoa. Transmission dynamics appear to be affected by environmental changes associated with land use practices.
\n","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, Hi","usgsCitation":"Atkinson, C.T., Utuzurrum, R.B., Seamon, J.O., Schmaedick, M.A., Lapointe, D., Apelgren, C., Egan, A.N., and Watcher-Weatherwax, W., 2016, Effects of Climate and land use on diversity, prevalence, and seasonal transmission of avian hematozoa in American Samoa: Technical Report HCSU-072, Report: iv, 47 p.","productDescription":"Report: iv, 47 p.","startPage":"1","endPage":"47","numberOfPages":"52","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072281","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"HI","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad47e4b05e859bdfb8dd","contributors":{"authors":[{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":621154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Utuzurrum, Ruth B.","contributorId":167126,"corporation":false,"usgs":false,"family":"Utuzurrum","given":"Ruth","email":"","middleInitial":"B.","affiliations":[{"id":24621,"text":"Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seamon, Joshua O.","contributorId":25816,"corporation":false,"usgs":true,"family":"Seamon","given":"Joshua","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":621157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmaedick, Mark A.","contributorId":167127,"corporation":false,"usgs":false,"family":"Schmaedick","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":24622,"text":"Division of Community and Natural Resources, American Samoa Community College","active":true,"usgs":false}],"preferred":false,"id":621158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaPointe, Dennis A. 0000-0002-6323-263X dlapointe@usgs.gov","orcid":"https://orcid.org/0000-0002-6323-263X","contributorId":150365,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","middleInitial":"A.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":621155,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Apelgren, Chloe","contributorId":140012,"corporation":false,"usgs":false,"family":"Apelgren","given":"Chloe","email":"","affiliations":[{"id":13356,"text":"University of Hawaii, Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621159,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Egan, Ariel N.","contributorId":150954,"corporation":false,"usgs":false,"family":"Egan","given":"Ariel","email":"","middleInitial":"N.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621160,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Watcher-Weatherwax, William","contributorId":167128,"corporation":false,"usgs":false,"family":"Watcher-Weatherwax","given":"William","email":"","affiliations":[{"id":24621,"text":"Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":621161,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70177910,"text":"70177910 - 2016 - Geochemistry of formation waters from the Wolfcamp and “Cline” shales: Insights into brine origin, reservoir connectivity, and fluid flow in the Permian Basin, USA","interactions":[],"lastModifiedDate":"2019-05-24T08:19:21","indexId":"70177910","displayToPublicDate":"2016-01-30T19:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry of formation waters from the Wolfcamp and “Cline” shales: Insights into brine origin, reservoir connectivity, and fluid flow in the Permian Basin, USA","docAbstract":"
Despite being one of the most important oil producing provinces in the United States, information on basinal hydrogeology and fluid flow in the Permian Basin of Texas and New Mexico is lacking. The source and geochemistry of brines from the basin were investigated (Ordovician- to Guadalupian-age reservoirs) by combining previously published data from conventional reservoirs with geochemical results for 39 new produced water samples, with a focus on those from shales. Salinity of the Ca–Cl-type brines in the basin generally increases with depth reaching a maximum in Devonian (median = 154 g/L) reservoirs, followed by decreases in salinity in the Silurian (median = 77 g/L) and Ordovician (median = 70 g/L) reservoirs. Isotopic data for B, O, H, and Sr and ion chemistry indicate three major types of water. Lower salinity fluids (<70 g/L) of meteoric origin in the middle and upper Permian hydrocarbon reservoirs (1.2–2.5 km depth; Guadalupian and Leonardian age) likely represent meteoric waters that infiltrated through and dissolved halite and anhydrite in the overlying evaporite layer. Saline (>100 g/L), isotopically heavy (O and H) water in Leonardian [Permian] to Pennsylvanian reservoirs (2–3.2 km depth) is evaporated, Late Permian seawater. Water from the Permian Wolfcamp and Pennsylvanian “Cline” shales, which are isotopically similar but lower in salinity and enriched in alkalis, appear to have developed their composition due to post-illitization diffusion into the shales. Samples from the “Cline” shale are further enriched with NH4, Br, I and isotopically light B, sourced from the breakdown of marine kerogen in the unit. Lower salinity waters (<100 g/L) in Devonian and deeper reservoirs (>3 km depth), which plot near the modern local meteoric water line, are distinct from the water in overlying reservoirs. We propose that these deep meteoric waters are part of a newly identified hydrogeologic unit: the Deep Basin Meteoric Aquifer System. Chemical, isotopic, and pressure data suggest that despite over-pressuring in the Wolfcamp shale, there is little potential for vertical fluid migration to the surface environment via natural conduits.
\nHawai‘i Volcanoes National Park (HAVO) encompasses 1,308 km2 on Hawai‘i Island. The park harbors endemic plants and animals which are threatened by a variety of invasive species. Introduced ungulates have caused sharp declines of numerous endemic species and have converted ecosystems to novel grazing systems in many cases. Local ranchers and the Territorial Government of Hawai‘i had long conducted regional ungulate control even prior to the establishment of HAVO in 1916. In 1995 the park’s hunting team began a new hunt database that allowed managers to review hunt effort and effectiveness in each management unit. Target species included feral pigs (Sus scrofa), European mouflon sheep (Ovis gmelini musimon), feral goats (Capra hircus) and wild cattle (Bos taurus). Hunters removed 1,204 feral pigs from HAVO over a 19-year period (1996‒2014). A variety of methods were employed, but trapping, snaring and ground hunts with dogs accounted for the most kills. Trapping yielded the most animals per unit effort. Hunters and volunteers removed 6,657 mouflon from HAVO; 6,601 of those were from the 468 km2 Kahuku Unit. Aerial hunts yielded the most animals followed by ground hunt methods. Hunters completed eradications of goats in several management units over an 18- year period (1997‒2014) when they removed the last 239 known individuals in HAVO primarily with aerial hunts. There have also been seven cattle and five feral dogs (Canis familiaris) removed from HAVO.
Establishing benchmarks and monitoring the success of on-the-ground ungulate removal efforts can improve the efficiency of protecting and restoring native forest for high-priority watersheds and native wildlife. We tested a variety of methods to detect small populations of ungulates within HAVO and the Hō‘ili Wai study area in the high-priority watershed of Ka‘ū Forest Reserve on Hawai‘i Island. We conducted ground surveys, aerial surveys and continuous camera trap monitoring in both fence-enclosed units and unenclosed units where populations of introduced mouflon and feral pigs threatened sensitive native plants and forest bird habitats.
Beginning in June 2014, twenty infrared camera traps were positioned in areas occupied by ungulates. The cameras were active for at most 198 days, and then half of the cameras were baited with oats and salt blocks for 126 days. There were a total of 1,496 observations of mouflon captured on camera, totaling 2,592 individuals: 1,020 ewes, 900 rams, 276 lambs, and 396 sheep of unknown sex. There were no detections of the illegally introduced axis deer (Axis axis). There were 11 observations of feral pigs and 109 observations of other animals (birds, rats, and other small mammals), including one detection of the federally endangered Hawaiian hawk (Buteo solitarius). Mouflon detection rates did not increase near baited cameras until three months after the initial baiting.
Ground-based surveys for ungulate presence were conducted along six transects in Kahuku in October 2014. Evidence of ungulates were detected in 27.5% of plots surveyed within an unenclosed unit, while an enclosed unit had sign in only 3.6% of plots surveyed. An aerial survey by helicopter was conducted in October 2014. A total of 378 mouflon were detected during the survey: 192 in the Kahuku Paddocks, 186 in the Kahuku East unit and no mouflon were detected in the actively controlled Mauka unit.
Two baseline ungulate surveys have been completed at the Hō‘ili Wai study area in the highpriority watershed of Ka‘ū Forest Reserve adjacent to Kahuku prior to the completion of an exclusionary ungulate fence. Ground-based surveys were conducted on four transects within a 4.99 km2 area on 5 August and 5–6 November 2014. In August, 20.71% of 565 plots surveyed 2 had fresh or intermediate ungulate sign. In November, 17.41% of 557 plots surveyed had fresh or intermediate ungulate sign. These surveys represent baseline levels of ungulate activity prior to management; therefore comparative inferences can be made about ungulate distribution and relative abundance, but inferences about absolute abundance cannot be made until all ungulates have been removed from the enclosed area. Additional ground-based surveys will be conducted when the fenced area has been fully enclosed, and until ungulate removals have been completed.
","language":"English","publisher":"University of Hawaii at Hilo","publisherLocation":"Hilo, HI","collaboration":"This product was prepared under Cooperative Agreement G13AC00097 for the Pacific Island Ecosystems Research Center of the U.S. Geological Survey.","usgsCitation":"Judge, S.W., Hess, S.C., Faford, J.K., Pacheco, D., Leopold, C.R., Cole, C., and Deguzman, V., 2016, Evaluating detection and monitoring tools for incipient and relictual non-native ungulate populations: Technical Report HCSU-069, v. 69, v, 44.","productDescription":"v, 44","startPage":"1","endPage":"44","numberOfPages":"49","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071779","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":326262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328010,"type":{"id":15,"text":"Index Page"},"url":"https://dspace.lib.hawaii.edu/handle/10790/2605"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hōʽili Wai Unit of Kaʽū Forest Reserve, Kahuku Unit of Hawai‘i Volcanoes National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.93994140625,\n 18.843913201134132\n ],\n [\n -155.93994140625,\n 19.49248592618279\n ],\n [\n -155.0665283203125,\n 19.49248592618279\n ],\n [\n -155.0665283203125,\n 18.843913201134132\n ],\n [\n -155.93994140625,\n 18.843913201134132\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a9ad4fe4b05e859bdfb931","contributors":{"authors":[{"text":"Judge, Seth W.","contributorId":8718,"corporation":false,"usgs":true,"family":"Judge","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":597397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hess, Steve C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":150366,"corporation":false,"usgs":true,"family":"Hess","given":"Steve","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":597396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faford, Jonathan K.J.","contributorId":16739,"corporation":false,"usgs":true,"family":"Faford","given":"Jonathan","email":"","middleInitial":"K.J.","affiliations":[],"preferred":false,"id":597398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pacheco, Dexter","contributorId":156310,"corporation":false,"usgs":false,"family":"Pacheco","given":"Dexter","email":"","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":597399,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leopold, Christina R.","contributorId":46817,"corporation":false,"usgs":true,"family":"Leopold","given":"Christina","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":597400,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cole, Colleen","contributorId":140102,"corporation":false,"usgs":false,"family":"Cole","given":"Colleen","email":"","affiliations":[{"id":13385,"text":"University of Hawaii at Hilo Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":597401,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Deguzman, Veronica vdeguzman@usgs.gov","contributorId":156311,"corporation":false,"usgs":true,"family":"Deguzman","given":"Veronica","email":"vdeguzman@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":597402,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70004161,"text":"70004161 - 2016 - Alpine and Subalpine","interactions":[],"lastModifiedDate":"2024-01-29T23:40:05.196016","indexId":"70004161","displayToPublicDate":"2016-01-29T17:37:37","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Alpine and Subalpine","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Habitat Management Guidelines for Amphibians and Reptiles of the Southwestern United States","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Partners in Amphibian and Reptile Conservation","isbn":"9780966740240","usgsCitation":"Muths, E.L., 2016, Alpine and Subalpine, chap. of Habitat Management Guidelines for Amphibians and Reptiles of the Southwestern United States, p. 104-107.","productDescription":"4 p.","startPage":"104","endPage":"107","ipdsId":"IP-025899","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":425092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Jones, Lawrence L. C.","contributorId":333683,"corporation":false,"usgs":false,"family":"Jones","given":"Lawrence","email":"","middleInitial":"L. C.","affiliations":[],"preferred":false,"id":893547,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Halama, Kenneth J.","contributorId":333684,"corporation":false,"usgs":false,"family":"Halama","given":"Kenneth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":893548,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Lovich, Robert E.","contributorId":73857,"corporation":false,"usgs":true,"family":"Lovich","given":"Robert E.","affiliations":[],"preferred":false,"id":893549,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":893550,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70162657,"text":"sir20155158 - 2016 - Water quality and hydrology of Silver Lake, Oceana County, Michigan, with emphasis on lake response to nutrient loading","interactions":[],"lastModifiedDate":"2018-01-08T12:35:15","indexId":"sir20155158","displayToPublicDate":"2016-01-29T16:45:00","publicationYear":"2016","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":"2015-5158","title":"Water quality and hydrology of Silver Lake, Oceana County, Michigan, with emphasis on lake response to nutrient loading","docAbstract":"Silver Lake is a 672-acre inland lake located in Oceana County, Michigan, and is a major tourist destination due to its proximity to Lake Michigan and the surrounding outdoor recreational opportunities. In recent years, Silver Lake exhibited patterns of high phosphorus concentrations, elevated chlorophyll a concentrations, and nuisance algal blooms. The U.S. Geological Survey (USGS), in cooperation with the Silver Lake Improvement Board and in collaboration with the Annis Water Resources Institute (AWRI) of Grand Valley State University, designed a study to assess the hydrologic and nutrient inputs to Silver Lake in order to identify the events and conditions that affect the nutrient chemistry and production of algal blooms in the lake. This information can inform water-resource managers in developing various management strategies to prevent or reduce the occurrence of future algal blooms.
\nUSGS and AWRI scientists collected data from November 2012 to December 2014 to provide information for future management decisions for Silver Lake. Silver Lake can be classified as a polymictic lake and has a residence time of approximately 223 days. Based on the mean lake Secchi depth, total phosphorus, and total nitrogen concentrations, Silver Lake is classified as a eutrophic lake. In-situ bioassay results indicate that algal growth in Silver Lake is colimited by both nitrogen and phosphorus. The nutrient budget for Silver Lake was calculated using the BATHTUB model based on 2 years of water-quality data collection. The BATHTUB model, developed by the U.S. Army Corps of Engineers, treats the lake as a well-mixed system with multiple inputs and outlets for both water and dissolved constituents, such as nutrients.
\nBased on results of the BATHTUB model, which were conditioned on observed concentrations and flows, the mean annual input of phosphorus to Silver Lake was approximately 1,342 pounds (lb); the mean annual input of nitrogen to Silver Lake was approximately 51,998 lb. The major measured sources of phosphorus loading to Silver Lake were groundwater and Hunter Creek, whereas the major measured sources of nitrogen to Silver Lake were Hunter Creek, groundwater, and atmospheric deposition. The largest loading of phosphorus and nitrogen to Silver Lake occurred during the spring. Minimal phosphorus deposition (if any) occurred in the lakebed sediment; however, of the nitrogen that entered Silver Lake, approximately 42.2 percent was deposited in the lakebed sediment as simulated by the BATHTUB model.
\nIn addition to measured sources, a septic load model was used to estimate the likely range of septic contribution to groundwater and adjacent surface waters. The likely septic loading scenario estimates that septic systems contribute 47.8 percent of the phosphorus to groundwater and 22.3 percent of phosphorus to Hunter Creek. These results indicate that septic systems are a major source of phosphorus loading to Silver Lake. The likely septic loading scenario indicated that septic systems account for 0.95 percent of the nitrogen load to Hunter Creek and 1.1 percent of the contribution of nitrogen to groundwater.
\nThe BATHTUB model was used to estimate future nutrient loading and eutrophication scenarios based on water-quality data collected from Silver Lake, groundwater, major tributaries, and atmospheric deposition. A separate septic load model was used to estimate the septic contribution to groundwater or directly to surface water, and the nutrient load estimates were modeled using the BATHTUB model to determine subsequent water-quality changes to Silver Lake.
\nDirector, Michigan Water Science Center
U.S. Geological Survey
6520 Mercantile Way Suite 5
Lansing, MI 48911–5991
http://mi.water.usgs.gov/
Arnold Air Force Base occupies about 40,000 acres in Coffee and Franklin Counties, Tennessee. The primary mission of Arnold Air Force Base is to provide risk-reduction information in the development of aerospace products through test and evaluation. This mission is achieved in part through test facilities at Arnold Engineering Development Complex (AEDC), which occupies about 4,000 acres in the center of Arnold Air Force Base. Arnold Air Force Base is underlain by gravel and limestone aquifers, the most productive of which is the Manchester aquifer. Several volatile organic compounds, primarily chlorinated solvents, have been identified in the groundwater at Arnold Air Force Base. In 2011, the U.S. Geological Survey, in cooperation with the U.S. Air Force, Arnold Air Force Base, completed a study of groundwater flow focused on the Arnold Engineering Development Complex area. The Arnold Engineering Development Complex area is of particular concern because within this area (1) chlorinated solvents have been identified in the groundwater, (2) the aquifers are dewatered around below-grade test facilities, and (3) there is a regional groundwater divide.
\nDuring May 2011, when water levels were near seasonal highs, water-level data were collected from 374 monitoring wells; and during September 2011, when water levels were near seasonal lows, water-level data were collected from 376 monitoring wells. Potentiometric surfaces were mapped by contouring altitudes of water levels measured in wells completed in the shallow aquifer, the upper and lower parts of the Manchester aquifer, and the Fort Payne aquifer. Water levels are generally 2 to 14 feet lower in September compared to May. The potentiometric-surface maps for all aquifers indicate a groundwater depression at the J4 test cell. Similar groundwater depressions in the shallow and upper parts of the Manchester aquifer are within the main testing area at the Arnold Engineering Development Complex at dewatering facilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155165","collaboration":"Prepared in cooperation with the United States Air Force, Arnold Air Force Base","usgsCitation":"Haugh, C.J., and Robinson, J.A., 2016, Potentiometric surfaces of the Arnold Engineering Development Complex area, Arnold Air Force Base, Tennessee, May and September 2011: U.S. Geological Survey Scientific Investigations Report 2015–5165, 23 p., https://dx.doi.org/10.3133/sir20155165.","productDescription":"v, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059351","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":314981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5165/sir20155165.pdf","text":"Report","size":"1.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5165"},{"id":314980,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5165/coverthb.jpg"}],"country":"United States","state":"Tennessee","county":"Coffee County, Franklin County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.5,\n 35\n ],\n [\n -86.5,\n 35.75\n ],\n [\n -85.5,\n 35.75\n ],\n [\n -85.5,\n 35\n ],\n [\n -86.5,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
http://tn.water.usgs.gov
The U.S. Geological Survey (USGS) installed the first gage to measure the flow of water into California’s Sacramento–San Joaquin River Delta from the Sacramento River in the late 1800s. Today, a network of 35 hydro-acoustic meters measure flow throughout the delta. This region is a critical part of California’s freshwater supply and conveyance system. With the data provided by this flow-station network—sampled every 15 minutes and updated to the web every hour—state and federal water managers make daily decisions about how much freshwater can be pumped for human use, at which locations, and when. Fish and wildlife scientists, working with water managers, also use this information to protect fish species affected by pumping and loss of habitat. The data are also used to help determine the success or failure of efforts to restore ecosystem processes in what has been called the “most managed and highly altered” watershed in the country.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153061","usgsCitation":"Burau, J.R., Ruhl, C.A., and Work, P.A., 2016, Innovation in Monitoring: The U.S. Geological Survey Sacramento-San Joaquin River Delta, California, Flow-Station Network: U.S. Geological Survey Fact Sheet 2015-3061, 6 p., https://dx.doi.org/10.3133/fs20153061.","productDescription":"6 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044692","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":315073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3061/coverthb.jpg"},{"id":315074,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3061/fs20153061.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3061 PDF"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River, San Joaquin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 37.75\n ],\n [\n -122,\n 38.5\n ],\n [\n -121.25,\n 38.5\n ],\n [\n -121.25,\n 37.75\n ],\n [\n -122,\n 37.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
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Fraser et al. (Reports, 17 July 2015, p. 302) report a unimodal relationship between productivity and species richness at regional and global scales, which they contrast with the results of Adler et al. (Reports, 23 September 2011, p. 1750). However, both data sets, when analyzed correctly, show clearly and consistently that productivity is a poor predictor of local species richness.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aad6236","collaboration":"Tredennick, AT;\nAdler, PB;\nHarpole, WS;\nBorer, ET;\nSeabloom, EW;","usgsCitation":"Tredennick, A.T., Adler, P.B., Grace, J.B., Harpole, W., Borer, E.T., Seabloom, E.W., Anderson, T., Bakker, J.D., Biederman, L.A., Brown, C.S., Buckley, Y.M., Chu, C., Collins, S., Crawley, M.J., Fay, P.A., Firn, J., Gruner, D., Hagenah, N., Hautier, Y., Hector, A., Hillebrand, H., Kirkman, K.P., Knops, J.M., Laungani, R., Lind, E., MacDougall, A.S., McCulley, R.L., Mitchell, C., Moore, J.L., Morgan, J.W., Orrock, J., Peri, P., Prober, S.M., Risch, A., Schuetz, M., Speziale, K.L., Standish, R.J., Sullivan, L.L., Wardle, G.M., Williams, R.J., and Yang, L.H., 2016, Comment on \"Worldwide evidence of a unimodal relationship between productivity and plant species richness\": Science, v. 351, no. 6272, https://doi.org/10.1126/science.aad6236.","productDescription":"3 p.","startPage":"457-a","numberOfPages":"3","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069869","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471296,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://dspace.library.uu.nl/handle/1874/344412","text":"External Repository"},{"id":315065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"351","issue":"6272","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ac8d28e4b0403299f4d45a","contributors":{"authors":[{"text":"Tredennick, Andrew T.","contributorId":152688,"corporation":false,"usgs":false,"family":"Tredennick","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":18962,"text":"Dept. of Wildland Resources and the Ecology Center, Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":590223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":590224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":590222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harpole, W Stanley","contributorId":131028,"corporation":false,"usgs":false,"family":"Harpole","given":"W Stanley","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":590225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":590230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":590231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, T. 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2016 - The Lassen hydrothermal system","interactions":[],"lastModifiedDate":"2016-01-29T09:32:26","indexId":"70162466","displayToPublicDate":"2016-01-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"The Lassen hydrothermal system","docAbstract":"The active Lassen hydrothermal system includes a central vapor-dominated zone or zones beneath the Lassen highlands underlain by ~240 °C high-chloride waters that discharge at lower elevations. It is the best-exposed and largest hydrothermal system in the Cascade Range, discharging 41 ± 10 kg/s of steam (~115 MW) and 23 ± 2 kg/s of high-chloride waters (~27 MW). The Lassen system accounts for a full 1/3 of the total high-temperature hydrothermal heat discharge in the U.S. Cascades (140/400 MW). Hydrothermal heat discharge of ~140 MW can be supported by crystallization and cooling of silicic magma at a rate of ~2400 km3/Ma, and the ongoing rates of heat and magmatic CO2 discharge are broadly consistent with a petrologic model for basalt-driven magmatic evolution. The clustering of observed seismicity at ~4–5 km depth may define zones of thermal cracking where the hydrothermal system mines heat from near-plastic rock. If so, the combined areal extent of the primary heat-transfer zones is ~5 km2, the average conductive heat flux over that area is >25 W/m2, and the conductive-boundary length <50 m. Observational records of hydrothermal discharge are likely too short to document long-term transients, whether they are intrinsic to the system or owe to various geologic events such as the eruption of Lassen Peak at 27 ka, deglaciation beginning ~18 ka, the eruptions of Chaos Crags at 1.1 ka, or the minor 1914–1917 eruption at the summit of Lassen Peak. However, there is a rich record of intermittent hydrothermal measurement over the past several decades and more-frequent measurement 2009–present. These data reveal sensitivity to climate and weather conditions, seasonal variability that owes to interaction with the shallow hydrologic system, and a transient 1.5- to twofold increase in high-chloride discharge in response to an earthquake swarm in mid-November 2014.
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This multidisciplinary study incorporates tephrostratigraphy, radiocarbon dating, petrography, and electron microprobe analysis to characterize R tephra. Tephra samples were collected from Tipsoo Lake and a stream-cut exposure in the Cowlitz Divide area of Mount Rainier National Park. Field evidence from 25 new sites suggests that R tephra locally contains internal bedding and has a wider distribution than previously reported. Herein, we provide the first robust suite of geochemical data that characterize the tephra. Glass compositions are heterogeneous, predominantly ranging from andesite to rhyolite in ash- to lapilli-sized clasts. The mineral assemblage consists of plagioclase, orthopyroxene, clinopyroxene, and magnetite with trace apatite and ilmenite. Subaerial R tephra deposits appear more weathered in hand sample than subaqueous deposits, but weathering indices suggest negligible chemical weathering in both deposits. Statistical analysis of radiocarbon ages provides a median age for R tephra of ∼10 050 cal years BP, and a 2σ error range between 9960 and 10 130 cal years BP.
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We monitored breakdown and nitrogen dynamics in wood and bark from a native riparian tree, Fremont cottonwood (Populus deltoides subsp. wislizeni), along four North American desert streams. We placed locally-obtained, fresh, coarse material [disks or cylinders (∼500–2000 cm3)] along two cold-desert and two warm-desert rivers in the Colorado River Basin. Material was placed in both floodplain and aquatic environments, and left in situ for up to 12 years. We tested the hypothesis that breakdown would be fastest in relatively warm and moist aerobic environments by comparing the time required for 50% loss of initial ash-free dry matter (T50) calculated using exponential decay models incorporating a lag term. In cold-desert sites (Green and Yampa rivers, Colorado), disks of wood with bark attached exposed for up to 12 years in locations rarely inundated lost mass at a slower rate (T50 = 34 yr) than in locations inundated during most spring floods (T50 = 12 yr). At the latter locations, bark alone loss mass at a rate initially similar to whole disks (T50 = 13 yr), but which subsequently slowed. In warm-desert sites monitored for 3 years, cylinders of wood with bark removed lost mass very slowly (T50 = 60 yr) at a location never inundated (Bill Williams River, Arizona), whereas decay rate varied among aquatic locations (T50 = 20 yr in Bill Williams River; T50 = 3 yr in Las Vegas Wash, an effluent-dominated stream warmed by treated wastewater inflows). Invertebrates had a minor role in wood breakdown except at in-stream locations in Las Vegas Wash. The presence and form of change in nitrogen content during exposure varied among riverine environments. Our results suggest woody debris breakdown in desert riverine ecosystems is primarily a microbial process with rates determined by landscape position, local weather, and especially the regional climate through its effect on the flow regime. The increased warmth and aridity expected to accompany climate change in the North American southwest will likely retard the already slow wood decay process on naturally functioning desert river floodplains. Our results have implications for designing environmental flows to manage floodplain forest wood budgets, carbon storage, and nutrient cycling along regulated dryland rivers.
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The ILM partnership uses the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) modeling platform to facilitate regional quantifications of ecosystem services under various scenarios of land-cover change that are representative of differing conservation program and practice implementation scenarios. To date, the ILM InVEST partnership has resulted in capabilities to quantify carbon stores, amphibian habitat, plant-community diversity, and pollination services. Work to include waterfowl and grassland bird habitat quality is in progress. Initial InVEST modeling has been focused on the Prairie Pothole Region (PPR) of the United States; future efforts might encompass other regions as data availability and knowledge increase as to how functions affecting ecosystem services differ among regions.
The ILM partnership is also developing the capability for field-scale process-based modeling of depressional wetland ecosystems using the Agricultural Policy/Environmental Extender (APEX) model. Progress was made towards the development of techniques to use the APEX model for closed-basin depressional wetlands of the PPR, in addition to the open systems that the model was originally designed to simulate. The ILM partnership has matured to the stage where effects of conservation programs and practices on multiple ecosystem services can now be simulated in selected areas. Future work might include the continued development of modeling capabilities, as well as development and evaluation of differing conservation program and practice scenarios of interest to partner agencies including the USDA’s Farm Service Agency (FSA) and Natural Resources Conservation Service (NRCS). When combined, the ecosystem services modeling capabilities of InVEST and the process-based abilities of the APEX model should provide complementary information needed to meet USDA and the Department of the Interior information needs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161006","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture Natural Resources Conservation Service and Farm Service Agency","usgsCitation":"Mushet, D.M., and Scherff, E.J., 2016, The integrated landscape modeling partnership—Current status and future directions (ver. 1.1, December 2016): U.S. Geological Survey Open-File Report 2016–1006, 59 p., https://dx.doi.org/10.3133/ofr20161006.","productDescription":"72 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070297","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":314982,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1006/coverthb1.1.jpg"},{"id":332701,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1006/version_history.txt"},{"id":314983,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1006/ofr20161006.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1006"}],"country":"United States","state":"Iowa, Minnesota, Nebraska, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.82080078125,\n 48.99463598353408\n ],\n [\n -105.13916015625,\n 48.90805939965008\n ],\n [\n -104.83154296875,\n 48.44377831058805\n ],\n [\n -104.4140625,\n 47.945786463687185\n ],\n [\n -103.18359375,\n 47.87214396888731\n ],\n [\n -102.39257812499999,\n 47.502358951968596\n ],\n [\n -101.29394531249999,\n 47.010225655683485\n ],\n [\n -101.0302734375,\n 46.66451741754235\n ],\n [\n -100.96435546875,\n 45.87471224890479\n ],\n [\n -100.70068359374999,\n 45.27488643704894\n ],\n [\n -100.8544921875,\n 44.4808302785626\n ],\n [\n -100.30517578125,\n 43.929549935614595\n ],\n [\n -98.89892578125,\n 43.03677585761058\n ],\n [\n -97.22900390625,\n 42.84375132629021\n ],\n [\n -95.07568359375,\n 42.04929263868686\n ],\n [\n -93.955078125,\n 41.590796851056005\n ],\n [\n -93.05419921875,\n 41.57436130598913\n ],\n [\n -92.4169921875,\n 41.77131167976407\n ],\n [\n -92.35107421874999,\n 42.391008609205045\n ],\n [\n -92.74658203125,\n 43.34116005412307\n ],\n [\n -93.31787109374999,\n 43.929549935614595\n ],\n [\n -93.88916015625,\n 44.2294565683017\n ],\n [\n -94.68017578125,\n 45.413876460821086\n ],\n [\n -94.9658203125,\n 46.84516443029279\n ],\n [\n -96.6357421875,\n 48.472921272487824\n ],\n [\n -98.0859375,\n 48.951366470947725\n ],\n [\n -103.82080078125,\n 48.99463598353408\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted January 28, 2016; Version 1.1: December 30, 2016","contact":"Director, USGS Northern Prairie Wildlife Research Center
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A multidimensional model of geographic features has been developed and implemented with data from The National Map of the U.S. Geological Survey. The model, programmed in C++ and implemented as a feature library, was tested with data from the National Hydrography Dataset demonstrating the capability to handle changes in feature attributes, such as increases in chlorine concentration in a stream, and feature geometry, such as the changing shoreline of barrier islands over time. Data can be entered directly, from a comma separated file, or features with attributes and relationships can be automatically populated in the model from data in the Spatial Data Transfer Standard format.
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As popularity of positional acoustic telemetry systems increases, so does the need to better understand how they perform in real-world applications, where variation in performance can bias study conclusions. Studies assessing variability in positional telemetry system performance have focused primarily on position accuracy, or comparing performance inside and outside the array. Here, we explored spatial and temporal variation in positioning probability within a 140-receiver Vemco Positioning System (VPS) array used to monitor lake trout,Salvelinus namaycush, spawning behavior over 23 km2 in Lake Huron, North America.
\nVariability in VPS positioning probability was assessed between August and November from 2012 to 2014 using 43 stationary transmitters distributed throughout the array. Various analyses were used to relate positioning probability to number of fish transmitters in the array, wave height, and thermal stratification. We also assessed the prevalence of ‘close proximity detection interference’ (CPDI) in our array by analyzing detection probability of 35 transmitters on collocated receivers.
\nPositioning probability of the VPS array varied greatly over time and space. Number of fish transmitters present in the array was a significant driver of reduced positioning probability, especially during lake trout spawning period when the fish were aggregated. Relationships between positioning probability and environmental variables were complex and varied over small spatial and temporal scales. One possible confounding variable was the large range of water depth over which receivers were deployed. Another confounding factor was the high prevalence of CPDI, which decreased exponentially with water depth and was less evident when wave heights were higher than normal.
\nSome variables that negatively influenced positioning can be minimized through careful planning (e.g., number of tagged fish released, transmitter power level). However, results suggested that the acoustic environment was highly variable over small spatial and temporal scales in response to complex interactions between many variables. Therefore, models that predict positioning or detection efficiencies as a function of environmental variables may not be attainable in most systems. The best defense against biased study conclusions is incorporation of in situ measures of system performance that allow for retrospective analysis of array performance after a study is completed.
\nSustaining natural levels of base flow is critical to maintaining ecological function as stream catchments are urbanized. Research shows a variable response of stream base flow to urbanization, with base flow or water tables rising in some locations, falling in others, or elsewhere remaining constant. The variable baseflow response is due to the array of natural (e.g., physiographic setting and climate) and anthropogenic (e.g., urban development and infrastructure) factors that influence hydrology. Perhaps as a consequence of this complexity, few simple tools exist to assist managers to predict baseflow change in their local urban area. This paper addresses this management need by presenting a decision support tool. The tool considers the natural vulnerability of the landscape, together with aspects of urban development in predicting the likelihood and direction of baseflow change. Where the tool identifies a likely increase or decrease it guides managers toward strategies that can reduce or increase groundwater recharge, respectively. Where the tool finds an equivocal result, it suggests a detailed water balance be performed. The decision support tool is embedded within an adaptive-management framework that encourages managers to define their ecological objectives, assess the vulnerability of their ecological objectives to changes in water table height, and monitor baseflow responses to urbanization. We trial our framework using two very different case studies: Perth, Western Australia, and Baltimore, Maryland, USA. Together, these studies show how pre-development water table height, climate and geology together with aspects of urban infrastructure (e.g., stormwater practices, leaky pipes) interact such that urbanization has overall led to rising base flow (Perth) and falling base flow (Baltimore). Greater consideration of subsurface components of the water cycle will help to protect and restore the ecology of urban freshwaters.
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Managing the complex effects of urbanization on base flow: Freshwater Science, v. 35, no. 1, p. 293-310, https://doi.org/10.1086/685084.","productDescription":"18 p.","startPage":"293","endPage":"310","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064036","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":488407,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/685084","text":"Publisher Index Page"},{"id":314947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, United States","state":"Maryland, Western Australia","city":"Baltimore, Perth","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.79855346679688,\n 39.12153746241925\n ],\n [\n -76.79855346679688,\n 39.41073305508498\n ],\n [\n -76.41403198242188,\n 39.41073305508498\n ],\n [\n -76.41403198242188,\n 39.12153746241925\n ],\n [\n -76.79855346679688,\n 39.12153746241925\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 114.9609375,\n -32.43561304116276\n ],\n [\n 114.9609375,\n -30.939924331023445\n ],\n [\n 116.993408203125,\n -30.939924331023445\n ],\n [\n 116.993408203125,\n -32.43561304116276\n ],\n [\n 114.9609375,\n -32.43561304116276\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ab3bb3e4b07ca61bfe3bf8","contributors":{"authors":[{"text":"Bhaskar, Aditi abhaskar@usgs.gov","contributorId":146249,"corporation":false,"usgs":true,"family":"Bhaskar","given":"Aditi","email":"abhaskar@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":566737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beesley, Leah","contributorId":146250,"corporation":false,"usgs":false,"family":"Beesley","given":"Leah","email":"","affiliations":[{"id":16644,"text":"Centre of Excellence in Natural Resource Management, University of Western Australia,","active":true,"usgs":false}],"preferred":false,"id":566738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Matthew J.","contributorId":146251,"corporation":false,"usgs":false,"family":"Burns","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":16645,"text":"Waterway Ecosystem Research Group, School of Ecosystem and Forest Sciences, The","active":true,"usgs":false}],"preferred":false,"id":566739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fletcher, T. 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In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295 nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10 nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (ΔR2 = 0.12), transpiration (ΔR2 = 0.17), and soil evaporation (ΔR2 = 0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong (R2 = 0.51), but the hyperspectral equivalent was superior (R2 = 0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R2 = 0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953 nm (R2 = 0.72) or 428 and 1518 nm (R2 = 0.69).
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Immunosuppressed populations are at increased risk of aggressive cutaneous squamous cell carcinoma (SCC). Individuals who are treated with rapamycin, (sirolimus, a classical mTOR inhibitor) have significantly decreased rates of developing new cutaneous SCCs compared to those that receive traditional immunosuppression. However, systemic rapamycin use can lead to significant adverse events. Here we explored the use of topical rapamycin as a chemopreventive agent in the context of solar simulated light (SSL)-induced skin carcinogenesis. In SKH-1 mice, topical rapamycin treatment decreased tumor yields when applied after completion of 15 weeks of SSL exposure compared to controls. However, applying rapamycin during SSL exposure for 15 weeks, and continuing for 10 weeks after UV treatment, increased tumor yields. We also examined whether a combinatorial approach might result in more significant tumor suppression by rapamycin. We validated that rapamycin causes increased Akt (S473) phosphorylation in the epidermis after SSL, and show for the first time that this dysregulation can be inhibited in vivo by a selective PDK1/Akt inhibitor, PHT-427. Combining rapamycin with PHT-427 on tumor prone skin additively caused a significant reduction of tumor multiplicity compared to vehicle controls. Our findings indicate that patients taking rapamycin should avoid sun exposure, and that combining topical mTOR inhibitors and Akt inhibitors may be a viable chemoprevention option for individuals at high risk for cutaneous SCC.
","language":"English","publisher":"American Association for Cancer Research","doi":"10.1158/1940-6207.CAPR-15-0419","usgsCitation":"Dickinson, S.E., Janda, J., Criswell, J., Blohm-Mangone, K., Olson, E.R., Liu, Z., Barber, C., Rusche, J.J., Petricoin, E., Calvert, V., Einspahr, J.G., Dickinson, J.E., Stratton, S.P., Curiel-Lewandrowski, C., Saboda, K., Hu, C., Bode, A.M., Dong, Z., Alberts, D.S., and Bowden, G.T., 2016, Inhibition of Akt enhances the chemopreventive effects of topical rapamycin in mouse skin: Cancer Prevention Research, v. 9, p. 215-224, https://doi.org/10.1158/1940-6207.CAPR-15-0419.","productDescription":"10 p.","startPage":"215","endPage":"224","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070816","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471302,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4777684","text":"Publisher 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Restricted gene flow associated with adaptive divergence across an altitudinal gradient","docAbstract":"Evolutionary theory predicts that divergent selection pressures across elevational gradients could cause adaptive divergence and reproductive isolation in the process of ecological speciation. Although there is substantial evidence for adaptive divergence across elevation, there is less evidence that this restricts gene flow. Previous work in the boreal chorus frog (Pseudacris maculata) has demonstrated adaptive divergence in morphological, life history and physiological traits across an elevational gradient from approximately 1500–3000 m in the Colorado Front Range, USA. We tested whether this adaptive divergence is associated with restricted gene flow across elevation – as would be expected if incipient speciation were occurring – and, if so, whether behavioural isolation contributes to reproductive isolation. Our analysis of 12 microsatellite loci in 797 frogs from 53 populations revealed restricted gene flow across elevation, even after controlling for geographic distance and topography. Calls also varied significantly across elevation in dominant frequency, pulse number and pulse duration, which was partly, but not entirely, due to variation in body size and temperature across elevation. However, call variation did not result in strong behavioural isolation: in phonotaxis experiments, low-elevation females tended to prefer an average low-elevation call over a high-elevation call, and vice versa for high-elevation females, but this trend was not statistically significant. In summary, our results show that adaptive divergence across elevation restricts gene flow in P. maculata, but the mechanisms for this potential incipient speciation remain open.
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Poor water quality, degradation of rearing habitat, and toxic levels of microcystin are hypothesized to contribute to low juvenile survival. Studies of wild juvenile suckers are limited in that capture rates are low and compromised individuals are rarely captured in passive nets. The goal of this study was to assess the use of a mesocosm for learning about juvenile survival, movement, and health. Hatchery-raised juvenile Lost River suckers were PIT (passive integrated transponder) tagged and monitored by three vertically stratified antennas. Fish locations within the mesocosm were recorded at least every 30 minutes and were assessed in relation to vertically stratified water-quality conditions. Vertical movement patterns were analyzed to identify the timing of mortality for each fish. Most mortality occurred from July 28 to August 16, 2014. Juvenile suckers spent daylight hours near the benthos and moved throughout the entire water column during dark hours. Diel movements were not in response to dissolved-oxygen concentrations, temperature, or pH. Furthermore, low dissolved-oxygen concentrations, high temperatures, high pH, high un-ionized ammonia, or high microcystin levels did not directly cause mortality, although indirect effects may have occurred. However, water-quality conditions known to be lethal to juvenile Lost River suckers did not occur during the study period. Histological assessment revealed severe gill hyperplasia and Ichthyobodo sp. infestations in most moribund fish. For these fish, Ichthyobodo sp. was likely the cause of mortality, although it is unclear if this parasite originated in the rearing facility because fish were not screened for this parasite prior to introduction. This study has demonstrated that we can effectively use a mesocosm equipped with antennas to learn about the timing of mortality, movement, and health of PIT-tagged hatchery-raised juvenile Lost River suckers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161012","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hereford, D.M., Burdick, S.M., Elliott, D.G., Dolan-Caret, Amari, Conway, C.M., and Harris, A.C., 2016, Survival, movement, and health of hatchery-raised juvenile Lost River suckers within a mesocosm in Upper Klamath Lake, Oregon: U.S. Geological Survey Open-File Report 2016–1012, 48 p., https://dx.doi.org/10.3133/ofr20161012.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070117","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":314949,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1012/ofr20161012.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1012 Report PDF"},{"id":314948,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1012/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.09518432617186,\n 42.379850764344134\n ],\n [\n -122.09518432617186,\n 42.50450285299051\n ],\n [\n -121.9482421875,\n 42.50450285299051\n ],\n [\n -121.9482421875,\n 42.379850764344134\n ],\n [\n -122.09518432617186,\n 42.379850764344134\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
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VS30, the time-averaged shear-wave velocity (VS) to a depth of 30 meters, is a key index adopted by the earthquake engineering community to account for seismic site conditions. VS30 is typically based on geophysical measurements of VS derived from invasive and noninvasive techniques at sites of interest. Owing to cost considerations, as well as logistical and environmental concerns, VS30 data are sparse or not readily available for most areas. Where data are available, VS30 values are often assembled in assorted formats that are accessible from disparate and (or) impermanent Web sites. To help remedy this situation, we compiled VS30 measurements obtained by studies funded by the U.S. Geological Survey (USGS) and other governmental agencies. Thus far, we have compiled VS30 values for 2,997 sites in the United States, along with metadata for each measurement from government-sponsored reports, Web sites, and scientific and engineering journals. Most of the data in our VS30 compilation originated from publications directly reporting the work of field investigators. A small subset (less than 20 percent) of VS30 values was previously compiled by the USGS and other research institutions. Whenever possible, VS30 originating from these earlier compilations were crosschecked against published reports. Both downhole and surface-based VS30 estimates are represented in our VS30 compilation. Most of the VS30 data are for sites in the western contiguous United States (2,141 sites), whereas 786 VS30 values are for sites in the Central and Eastern United States; 70 values are for sites in other parts of the United States, including Alaska (15 sites), Hawaii (30 sites), and Puerto Rico (25 sites). An interactive map is hosted on the primary USGS Web site for accessing VS30 data (https://earthquake.usgs.gov/data/vs30/us/).
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Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/