{"pageNumber":"134","pageRowStart":"3325","pageSize":"25","recordCount":10457,"records":[{"id":70157510,"text":"70157510 - 2015 - Will the effects of sea-level rise create ecological traps for Pacific Island seabirds?","interactions":[],"lastModifiedDate":"2018-01-04T12:42:46","indexId":"70157510","displayToPublicDate":"2015-09-28T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Will the effects of sea-level rise create ecological traps for Pacific Island seabirds?","docAbstract":"

More than 18 million seabirds nest on 58 Pacific islands protected within vast U.S. Marine National Monuments (1.9 million km2). However, most of these seabird colonies are on low-elevation islands and sea-level rise (SLR) and accompanying high-water perturbations are predicted to escalate with climate change. To understand how SLR may impact protected islands and insular biodiversity, we modeled inundation and wave-driven flooding of a globally important seabird rookery in the subtropical Pacific. We acquired new high-resolution Digital Elevation Models (DEMs) and used the Delft3D wave model and ArcGIS to model wave heights and inundation for a range of SLR scenarios (+0.5, +1.0, +1.5, and +2.0 m) at Midway Atoll. Next, we classified vegetation to delineate habitat exposure to inundation and identified how breeding phenology, colony synchrony, and life history traits affect species-specific sensitivity. We identified 3 of 13 species as highly vulnerable to SLR in the Hawaiian Islands and quantified their atoll-wide distribution (Laysan albatross, Phoebastria immutabilis; black-footed albatross, P. nigripes; and Bonin petrel, Pterodroma hypoleuca). Our models of wave-driven flooding forecast nest losses up to 10% greater than passive inundation models at +1.0 m SLR. At projections of + 2.0 m SLR, approximately 60% of albatross and 44% of Bonin petrel nests were overwashed displacing more than 616,400 breeding albatrosses and petrels. Habitat loss due to passive SLR may decrease the carrying capacity of some islands to support seabird colonies, while sudden high-water events directly reduce survival and reproduction. This is the first study to simulate wave-driven flooding and the combined impacts of SLR, groundwater rise, and storm waves on seabird colonies. Our results highlight the need for early climate change planning and restoration of higher elevation seabird refugia to prevent low-lying protected islands from becoming ecological traps in the face of rising sea levels.

","language":"English","publisher":"The Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0136773","collaboration":"US Fish and Wildlife Service","usgsCitation":"Reynolds, M.H., Courtot, K., Berkowitz, P., Storlazzi, C.D., Moore, J., and Flint, E., 2015, Will the effects of sea-level rise create ecological traps for Pacific Island seabirds?: PLoS ONE, v. 10, 23 p., https://doi.org/10.1371/journal.pone.0136773.","productDescription":"23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066797","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":471768,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0136773","text":"Publisher Index Page"},{"id":308655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -177.4,\n 28.15\n ],\n [\n -177.4,\n 28.25\n ],\n [\n -177.3,\n 28.25\n ],\n [\n -177.3,\n 28.15\n ],\n [\n -177.4,\n 28.15\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-23","publicationStatus":"PW","scienceBaseUri":"560a56bee4b058f706e536ac","contributors":{"authors":[{"text":"Reynolds, Michelle H. 0000-0001-7253-8158 mreynolds@usgs.gov","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":3871,"corporation":false,"usgs":true,"family":"Reynolds","given":"Michelle","email":"mreynolds@usgs.gov","middleInitial":"H.","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":573389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Courtot, Karen 0000-0002-8849-4054 kcourtot@usgs.gov","orcid":"https://orcid.org/0000-0002-8849-4054","contributorId":140002,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen","email":"kcourtot@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":573390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berkowitz, Paul pberkowitz@usgs.gov","contributorId":4642,"corporation":false,"usgs":true,"family":"Berkowitz","given":"Paul","email":"pberkowitz@usgs.gov","affiliations":[],"preferred":true,"id":573391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":573392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Janet","contributorId":147944,"corporation":false,"usgs":false,"family":"Moore","given":"Janet","email":"","affiliations":[{"id":16961,"text":"Saint Mary's University","active":true,"usgs":false}],"preferred":false,"id":573393,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flint, Elizabeth","contributorId":147945,"corporation":false,"usgs":false,"family":"Flint","given":"Elizabeth","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":573394,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157281,"text":"70157281 - 2015 - Hydrothermal alteration and diagenesis of terrestrial lacustrine pillow basalts: Coordination of hyperspectral imaging with laboratory measurements","interactions":[],"lastModifiedDate":"2019-11-12T11:23:06","indexId":"70157281","displayToPublicDate":"2015-09-28T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal alteration and diagenesis of terrestrial lacustrine pillow basalts: Coordination of hyperspectral imaging with laboratory measurements","docAbstract":"

We investigate an outcrop of ∼187 Ma lacustrine pillow basalts of the Talcott Formation exposed in Meriden, Connecticut, USA, focusing on coordinated analyses of one pillow lava to characterize the aqueous history of these basalts in the Hartford Basin. This work uses a suite of multidisciplinary measurements, including hyperspectral imaging, other spectroscopic techniques, and chemical and mineralogical analyses, from the microscopic scale up to the scale of an outcrop.

\n

The phases identified in the sample are albite, large iron oxides, and titanite throughout; calcite in vesicles; calcic clinopyroxene, aegirine, and Fe/Mg-bearing clay in the rind; and fine-grained hematite and pyroxenes in the interior. Using imaging spectroscopy, the chemistry and mineralogy results extend to the hand sample and larger outcrop. From all of the analyses, we suggest that the pillow basalts were altered initially after emplacement, either by heated lake water or magmatic fluids, at temperatures of at least 400-600°C, and the calcic clinopyroxenes and aegirine identified in the rind are a preserved record of that alteration. As the hydrothermal system cooled to slightly lower temperatures, clays formed in the rind, and, during this alteration, the sample oxidized to form hematite in the matrix of the interior and Fe3+ in the pyroxenes in the rind. During the waning stages of the hydrothermal system, calcite precipitated in vesicles within the rind. Later, diagenetic processes albitized the sample, with albite replacing plagioclase, lining vesicles, and accreting onto the exterior of the sample. This albitization or Na-metasomatism occurred when the lake within the Hartford Basin evaporated during a drier past climatic era, resulting in Na-rich brines. As Ca-rich plagioclase altered to albite, Ca was released into solution, eventually precipitating as calcite in previously-unfilled vesicles, dominantly in the interior of the pillow. Coordinated analyses of this sample permit identification of the alteration phases and help synthesize the aqueous history of pillow lavas of the Talcott formation. These results are also relevant to Mars, where volcanically-resurfaced open basin lakes have been found, and this Hartford Basin outcrop may be a valuable analog for any potential volcano-lacustrine interactions. The results can also help to inform the utility and optimization of potentially complementary, synergistic, and uniquely-suited techniques for characterization of hydrothermally-altered terrains.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2015.08.024","usgsCitation":"Greenberger, R.N., Mustard, J., Cloutis, E., Mann, P., Wilson, J.H., Flemming, R.L., Robertson, K., Salvatore, M.R., and Edwards, C., 2015, Hydrothermal alteration and diagenesis of terrestrial lacustrine pillow basalts: Coordination of hyperspectral imaging with laboratory measurements: Geochimica et Cosmochimica Acta, v. 171, p. 174-200, https://doi.org/10.1016/j.gca.2015.08.024.","productDescription":"27 p.","startPage":"174","endPage":"200","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062817","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":308675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut","city":"Meriden","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.87368774414062,\n 41.47566020027821\n ],\n [\n -72.685546875,\n 41.47566020027821\n ],\n [\n -72.685546875,\n 41.580525125613846\n ],\n [\n -72.87368774414062,\n 41.580525125613846\n ],\n [\n -72.87368774414062,\n 41.47566020027821\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"171","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560a56a8e4b058f706e5369e","contributors":{"authors":[{"text":"Greenberger, Rebecca N","contributorId":147769,"corporation":false,"usgs":false,"family":"Greenberger","given":"Rebecca","email":"","middleInitial":"N","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":572570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mustard, John F","contributorId":147770,"corporation":false,"usgs":false,"family":"Mustard","given":"John F","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":572571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cloutis, Edward A.","contributorId":147771,"corporation":false,"usgs":false,"family":"Cloutis","given":"Edward A.","affiliations":[{"id":16930,"text":"University of Winnipeg","active":true,"usgs":false}],"preferred":false,"id":572572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mann, Paul","contributorId":57729,"corporation":false,"usgs":true,"family":"Mann","given":"Paul","email":"","affiliations":[],"preferred":false,"id":572573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Janette H.","contributorId":147772,"corporation":false,"usgs":false,"family":"Wilson","given":"Janette","email":"","middleInitial":"H.","affiliations":[{"id":16931,"text":"Headwall Photonics","active":true,"usgs":false}],"preferred":false,"id":572574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flemming, Roberta L","contributorId":147773,"corporation":false,"usgs":false,"family":"Flemming","given":"Roberta","email":"","middleInitial":"L","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":572575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robertson, Kevin","contributorId":147774,"corporation":false,"usgs":false,"family":"Robertson","given":"Kevin","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":572576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Salvatore, Mark R","contributorId":147775,"corporation":false,"usgs":false,"family":"Salvatore","given":"Mark","email":"","middleInitial":"R","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":572577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Edwards, Christopher cedwards@usgs.gov","contributorId":147768,"corporation":false,"usgs":true,"family":"Edwards","given":"Christopher","email":"cedwards@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":572569,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70159641,"text":"70159641 - 2015 - Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes","interactions":[],"lastModifiedDate":"2017-01-12T11:03:29","indexId":"70159641","displayToPublicDate":"2015-09-24T06:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes","docAbstract":"

Arctic land-cover changes induced by recent global climate change (e.g., expansion of woody vegetation into tundra and effects of permafrost degradation) are expected to generate further feedbacks to the climate system. Past changes can be used to assess our understanding of feedback mechanisms through a combination of process modeling and paleo-observations. The subcontinental region of Beringia (northeastern Siberia, Alaska, and northwestern Canada) was largely ice-free at the peak of deglacial warming and experienced both major vegetation change and loss of permafrost when many arctic regions were still ice covered. The evolution of Beringian climate at this time was largely driven by global features, such as the amplified seasonal cycle of Northern Hemisphere insolation and changes in global ice volume and atmospheric composition, but changes in regional land-surface controls, such as the widespread development of thaw lakes, the replacement of tundra by deciduous forest or woodland, and the flooding of the Bering–Chukchi land bridge, were probably also important. We examined the sensitivity of Beringia's early Holocene climate to these regional-scale controls using a regional climate model (RegCM). Lateral and oceanic boundary conditions were provided by global climate simulations conducted using the GENESIS V2.01 atmospheric general circulation model (AGCM) with a mixed-layer ocean. We carried out two present-day simulations of regional climate – one with modern and one with 11 ka geography – plus another simulation for 6 ka. In addition, we performed five ~ 11 ka climate simulations, each driven by the same global AGCM boundary conditions: (i) 11 ka Control, which represents conditions just prior to the major transitions (exposed land bridge, no thaw lakes or wetlands, widespread tundra vegetation), (ii) sea-level rise, which employed present-day continental outlines, (iii) vegetation change, with deciduous needleleaf and deciduous broadleaf boreal vegetation types distributed as suggested by the paleoecological record, (iv) thaw lakes, which used the present-day distribution of lakes and wetlands, and (v) post-11 ka All, incorporating all boundary conditions changed in experiments (ii)–(iv). We find that regional-scale controls strongly mediate the climate responses to changes in the large-scale controls, amplifying them in some cases, damping them in others, and, overall, generating considerable spatial heterogeneity in the simulated climate changes. The change from tundra to deciduous woodland produces additional widespread warming in spring and early summer over that induced by the 11 ka insolation regime alone, and lakes and wetlands produce modest and localized cooling in summer and warming in winter. The greatest effect is the flooding of the land bridge and shelves, which produces generally cooler conditions in summer but warmer conditions in winter and is most clearly manifest on the flooded shelves and in eastern Beringia. By 6 ka continued amplification of the seasonal cycle of insolation and loss of the Laurentide ice sheet produce temperatures similar to or higher than those at 11 ka, plus a longer growing season.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-11-1197-2015","usgsCitation":"Bartlein, P., Edwards, M.E., Hostetler, S.W., Shafer, S., Anderson, P.M., Brubaker, L.B., and Lozhkin, A., 2015, Early-Holocene warming in Beringia and its mediation by sea-level and vegetation changes: Climate of the Past, v. 11, no. 9, p. 1197-1222, https://doi.org/10.5194/cp-11-1197-2015.","productDescription":"26 p.","startPage":"1197","endPage":"1222","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062524","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-11-1197-2015","text":"Publisher Index Page"},{"id":311350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","state":"Alaska","otherGeospatial":"Beringia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -208.65234374999997,\n 42.032974332441405\n ],\n [\n -208.65234374999997,\n 76.31035754301745\n ],\n [\n -115.31249999999999,\n 76.31035754301745\n ],\n [\n -115.31249999999999,\n 42.032974332441405\n ],\n [\n -208.65234374999997,\n 42.032974332441405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-24","publicationStatus":"PW","scienceBaseUri":"564b0c45e4b0ebfbef0d3144","contributors":{"authors":[{"text":"Bartlein, P. J.","contributorId":54566,"corporation":false,"usgs":false,"family":"Bartlein","given":"P. J.","affiliations":[],"preferred":false,"id":579849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, M. E.","contributorId":29977,"corporation":false,"usgs":true,"family":"Edwards","given":"M.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":579850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":579848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":579851,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, P. M.","contributorId":71722,"corporation":false,"usgs":true,"family":"Anderson","given":"P.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":579852,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brubaker, L. B","contributorId":149867,"corporation":false,"usgs":false,"family":"Brubaker","given":"L.","email":"","middleInitial":"B","affiliations":[{"id":17844,"text":"University of Washington, Seattle, Washington, USA","active":true,"usgs":false}],"preferred":false,"id":579853,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lozhkin, A. V","contributorId":149868,"corporation":false,"usgs":false,"family":"Lozhkin","given":"A. V","affiliations":[{"id":17845,"text":"North East Interdisciplinary Research Inst, Far East Branch Russian Academy of Sciences, Magadan, Russia","active":true,"usgs":false}],"preferred":false,"id":579854,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70159964,"text":"70159964 - 2015 - A new isotopic reference material for stable hydrogen and oxygen isotope-ratio measurements of water—USGS50 Lake Kyoga Water","interactions":[],"lastModifiedDate":"2015-12-07T14:01:06","indexId":"70159964","displayToPublicDate":"2015-09-24T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3233,"text":"Rapid Communications in Mass Spectrometry","active":true,"publicationSubtype":{"id":10}},"title":"A new isotopic reference material for stable hydrogen and oxygen isotope-ratio measurements of water—USGS50 Lake Kyoga Water","docAbstract":"
Rationale
\n

As a result of the need for isotopic reference waters having high δ2HVSMOW-SLAP and δ18OVSMOW-SLAP values for daily use, especially for tropical and equatorial-zone freshwaters, a new secondary isotopic reference material for international distribution was prepared from water collected from Lake Kyoga, Uganda.

\n
Methods
\n

This isotopic reference lakewater was filtered through a membrane with 0.2-µm pore size, homogenized, loaded into glass ampoules that were sealed with a torch and autoclaved to eliminate biological activity, and measured by dual-inlet isotope-ratio mass spectrometry. This reference material is available in a case of 144 glass ampoules each containing 5 mL of water.

\n
Results
\n

The δ2H and δ18O values of this reference material are +32.8 ± 0.4 and +4.95 ± 0.02 mUr (milliurey = 0.001 = 1 ‰), respectively, relative to VSMOW, on scales normalized such that the δ2H and δ18O values of SLAP reference water are, respectively, −428 and −55.5 mUr. Each uncertainty is an estimated expanded uncertainty (U = 2uc) about the reference value that provides an interval that has about a 95 % probability of encompassing the true value.

\n
Conclusions
\n

This isotopic reference material, designated as USGS50, is intended as one of two reference waters for daily normalization of stable hydrogen and oxygen isotopic analysis of water with an isotope-ratio mass spectrometer or a laser absorption spectrometer, of use especially for isotope-hydrology laboratories analyzing freshwater samples from equatorial and tropical regions.

","language":"English","publisher":"Wiley","doi":"10.1002/rcm.7369","usgsCitation":"Coplen, T.B., Wassenaar, L.I., Mukwaya, C., Qi, H., and Lorenz, J.M., 2015, A new isotopic reference material for stable hydrogen and oxygen isotope-ratio measurements of water—USGS50 Lake Kyoga Water: Rapid Communications in Mass Spectrometry, v. 29, no. 21, p. 2078-2082, https://doi.org/10.1002/rcm.7369.","productDescription":"5 p.","startPage":"2078","endPage":"2082","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068451","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":311952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Uganda","otherGeospatial":"Lake Kyoga","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 33.03314208984375,\n 2.1171328026628355\n ],\n [\n 32.9864501953125,\n 2.070472083193089\n ],\n [\n 32.93426513671875,\n 1.9002862838753904\n ],\n [\n 32.7996826171875,\n 1.8783255723852184\n ],\n [\n 32.662353515625,\n 1.8289129671536257\n ],\n [\n 32.54974365234375,\n 1.7026302136023004\n ],\n [\n 32.37396240234375,\n 1.7026302136023004\n ],\n [\n 32.3272705078125,\n 1.6147764249055092\n ],\n [\n 32.36572265625,\n 1.548883579847398\n ],\n [\n 32.49755859375,\n 1.526918838498519\n ],\n [\n 32.51953125,\n 1.4637689680642445\n ],\n [\n 32.58819580078125,\n 1.3484472784360075\n ],\n [\n 32.74749755859375,\n 1.312751340599998\n ],\n [\n 32.79144287109375,\n 1.3292264529974078\n ],\n [\n 32.75848388671875,\n 1.3896342476555246\n ],\n [\n 32.80792236328125,\n 1.3868884718166363\n ],\n [\n 32.8546142578125,\n 1.2743089918452106\n ],\n [\n 33.01940917968749,\n 1.1891846312793248\n ],\n [\n 33.06060791015625,\n 1.2166443983257476\n ],\n [\n 32.958984375,\n 1.3319722944135324\n ],\n [\n 32.88482666015625,\n 1.3951257897508365\n ],\n [\n 32.89031982421875,\n 1.4198375698213372\n ],\n [\n 32.95074462890625,\n 1.392380020302357\n ],\n [\n 33.0303955078125,\n 1.3292264529974078\n ],\n [\n 33.07708740234375,\n 1.2852925793638672\n ],\n [\n 33.1292724609375,\n 1.263325357489324\n ],\n [\n 33.16497802734375,\n 1.2825466868972577\n ],\n [\n 33.1951904296875,\n 1.2770548931316381\n ],\n [\n 33.2281494140625,\n 1.2193903597622147\n ],\n [\n 33.28033447265625,\n 1.2001685712337065\n ],\n [\n 33.30780029296874,\n 1.2715630876314767\n ],\n [\n 33.35723876953125,\n 1.3319722944135324\n ],\n [\n 33.35723876953125,\n 1.436311943390042\n ],\n [\n 33.310546875,\n 1.4582775898253464\n ],\n [\n 33.24737548828125,\n 1.425329040790274\n ],\n [\n 33.2171630859375,\n 1.4143460858068722\n ],\n [\n 33.28582763671875,\n 1.4939713066293239\n ],\n [\n 33.24462890625,\n 1.5104451350115682\n ],\n [\n 33.12652587890625,\n 1.4912256565185766\n ],\n [\n 33.167724609375,\n 1.5296644435081868\n ],\n [\n 33.4588623046875,\n 1.628503834970573\n ],\n [\n 33.50555419921875,\n 1.6367402361776193\n ],\n [\n 33.46435546875,\n 1.8042061519566792\n ],\n [\n 33.33251953125,\n 1.7273383791406443\n ],\n [\n 33.20068359375,\n 1.6971394669749607\n ],\n [\n 33.07159423828125,\n 1.6724309149453824\n ],\n [\n 32.89581298828125,\n 1.587321327409907\n ],\n [\n 32.82989501953125,\n 1.6202674001017445\n ],\n [\n 32.706298828125,\n 1.5241732299817299\n ],\n [\n 32.63214111328125,\n 1.5131907609694377\n ],\n [\n 32.60467529296875,\n 1.5653569866197157\n ],\n [\n 32.67608642578125,\n 1.6449766035527875\n ],\n [\n 32.77770996093749,\n 1.7081209445886518\n ],\n [\n 32.8216552734375,\n 1.7657726629466413\n ],\n [\n 32.92877197265625,\n 1.7740084780892118\n ],\n [\n 32.97271728515624,\n 1.7108663042007148\n ],\n [\n 33.02490234375,\n 1.7081209445886518\n ],\n [\n 33.03314208984375,\n 1.8865608717161173\n ],\n [\n 33.17596435546875,\n 1.9057764182382826\n ],\n [\n 33.20068359375,\n 1.9634217625838057\n ],\n [\n 33.12103271484375,\n 2.0265548563992843\n ],\n [\n 33.15948486328125,\n 2.111643378566517\n ],\n [\n 33.10455322265625,\n 2.1720259659849352\n ],\n [\n 33.04412841796875,\n 2.161047491275904\n ],\n [\n 33.03314208984375,\n 2.1171328026628355\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"21","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-24","publicationStatus":"PW","scienceBaseUri":"5662c73de4b06a3ea36c67a8","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - 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Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0135454","usgsCitation":"Soranno, P.A., Cheruvelil, K.S., Wagner, T., Webster, K.E., and Bremigan, M.T., 2015, Effects of land use on lake nutrients: The importance of scale, hydrologic connectivity, and region: PLoS ONE, v. 10, no. 8, p. 1-22, https://doi.org/10.1371/journal.pone.0135454.","productDescription":"22 p.","startPage":"1","endPage":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061088","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471776,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0135454","text":"Publisher Index Page"},{"id":324005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Multiple stressors threaten stream physical and biological quality, including elevated nutrients and other contaminants, riparian and in-stream habitat degradation and altered natural flow regime. Unconventional oil and gas (UOG) development is one emerging stressor that spans the U.S. UOG development could alter stream sedimentation, riparian extent and composition, in-stream flow, and water quality. We developed indices to describe the watershed sensitivity and exposure to natural and anthropogenic disturbances and computed a vulnerability index from these two scores across stream catchments in six productive shale plays. We predicted that catchment vulnerability scores would vary across plays due to climatic, geologic and anthropogenic differences. Across-shale averages supported this prediction revealing differences in catchment sensitivity, exposure, and vulnerability scores that resulted from different natural and anthropogenic environmental conditions. For example, semi-arid Western shale play catchments (Mowry, Hilliard, and Bakken) tended to be more sensitive to stressors due to low annual average precipitation and extensive grassland. Catchments in the Barnett and Marcellus-Utica were naturally sensitive from more erosive soils and steeper catchment slopes, but these catchments also experienced areas with greater UOG densities and urbanization. Our analysis suggested Fayetteville and Barnett catchments were vulnerable due to existing anthropogenic exposure. However, all shale plays had catchments that spanned a wide vulnerability gradient. Our results identify vulnerable catchments that can help prioritize stream protection and monitoring efforts. Resource managers can also use these findings to guide local development activities to help reduce possible environmental effects.

","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0137416","usgsCitation":"Entrekin, S., Maloney, K.O., Kapo, K.E., Walters, A.W., Evans-White, M.A., and Klemow, K.M., 2015, Stream vulnerability to widespread and emergent stressors: a focus on unconventional oil and gas: PLoS ONE, p. 1-28, https://doi.org/10.1371/journal.pone.0137416.","productDescription":"28 p.","startPage":"1","endPage":"28","numberOfPages":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063366","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":471777,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0137416","text":"Publisher Index Page"},{"id":309372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-23","publicationStatus":"PW","scienceBaseUri":"560d07bbe4b058f706e54316","contributors":{"authors":[{"text":"Entrekin, Sally","contributorId":147949,"corporation":false,"usgs":false,"family":"Entrekin","given":"Sally","affiliations":[{"id":16964,"text":"University of Central Arkansas","active":true,"usgs":false}],"preferred":false,"id":573440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Kelly O. 0000-0003-2304-0745 kmaloney@usgs.gov","orcid":"https://orcid.org/0000-0003-2304-0745","contributorId":4636,"corporation":false,"usgs":true,"family":"Maloney","given":"Kelly","email":"kmaloney@usgs.gov","middleInitial":"O.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":573439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kapo, Katherine E.","contributorId":147950,"corporation":false,"usgs":false,"family":"Kapo","given":"Katherine","email":"","middleInitial":"E.","affiliations":[{"id":16965,"text":"Waterborne Environmental Inc.","active":true,"usgs":false}],"preferred":false,"id":573441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":573442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans-White, Michelle A.","contributorId":39635,"corporation":false,"usgs":true,"family":"Evans-White","given":"Michelle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":573443,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klemow, Kenneth M.","contributorId":50238,"corporation":false,"usgs":true,"family":"Klemow","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":573444,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160352,"text":"70160352 - 2015 - A quick SEED tutorial","interactions":[],"lastModifiedDate":"2015-12-21T11:18:10","indexId":"70160352","displayToPublicDate":"2015-09-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"A quick SEED tutorial","docAbstract":"

Introduction

\n

A number of different government-funded seismic data centers offer free open-access data (e.g., U.S. Geological Survey, National Earthquake Information Center, the Incorporated Research Institutions for Seismology (IRIS), and Data Management System), which can be freely downloaded and shared among different members of the community (Lay, 2009). To efficiently share data, it is important that different data providers follow a common format. The Standard for the Exchange of Earthquake Data (SEED) provides one such format for storing seismic and other geophysical data. The SEED format is widely used in earthquake seismology; however, SEED and its structure can be difficult for many first-time users (ourselves included). Below is a quick tutorial that outlines the basic structure of SEED format. This write-up is in no way intended to replace the comprehensive SEED manual (Ahern et al., 2009), and instead of going into the details of any specific part of the SEED format we refer the reader to the manual for additional details. The goal of this write-up is to succinctly explain the basic structure of SEED format as well as the associated jargon, as most commonly used now, in a colloquial way so that novice users of SEED can become more familiar with the format and its application quickly. Our goal is to give the reader the necessary background so that when problems or questions about SEED format arise they will have some understanding of where they should look for more details or from where the problem might be stemming. As a secondary goal, we hope to help the reader become familiar with the SEED manual (Ahern et al., 2009), which contains detailed information about all aspects of the SEED format.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220150043","usgsCitation":"Ringler, A.T., and Evans, J.R., 2015, A quick SEED tutorial: Seismological Research Letters, v. 86, no. 6, p. 1717-1725, https://doi.org/10.1785/0220150043.","productDescription":"9 p.","startPage":"1717","endPage":"1725","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067142","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":312605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-23","publicationStatus":"PW","scienceBaseUri":"567930bce4b0da412f4fb527","contributors":{"authors":[{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":582717,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, John R. jrevans@usgs.gov","contributorId":529,"corporation":false,"usgs":true,"family":"Evans","given":"John","email":"jrevans@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":582718,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157282,"text":"70157282 - 2015 - Preliminary characterization of digestive enzymes in freshwater mussels","interactions":[],"lastModifiedDate":"2015-09-21T12:17:16","indexId":"70157282","displayToPublicDate":"2015-09-21T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Preliminary characterization of digestive enzymes in freshwater mussels","docAbstract":"

Resource managers lack an effective chemical tool to control the invasive zebra mussel Dreissena polymorpha. Zebra mussels clog water intakes for hydroelectric companies, harm unionid mussel species, and are believed to be a reservoir of avian botulism. Little is known about the digestive physiology of zebra mussels and unionid mussels. The enzymatic profile of the digestive glands of zebra mussels and native threeridge (Amblema plicata) and plain pocketbook mussels (Lampsilis cardium) are characterized using a commercial enzyme kit, api ZYM, and validated the kit with reagent-grade enzymes. A linear correlation was shown for only one of nineteen enzymes, tested between the api ZYM kit and a specific enzyme kit. Thus, the api ZYM kit should only be used to make general comparisons of enzyme presence and to observe trends in enzyme activities. Enzymatic trends were seen in the unionid mussel species, but not in zebra mussels sampled 32 days apart from the same location. Enzymatic classes, based on substrate, showed different trends, with proteolytic and phospholytic enzymes having the most change in relative enzyme activity.

","language":"English","publisher":"National Shellfisheries Association","doi":"10.2983/035.034.0225","collaboration":"University of Wisconsin-La Crosse","usgsCitation":"Sauey, B., Amberg, J.J., Cooper, S.T., Grunwald, S.K., Newton, T.J., and Haro, R.J., 2015, Preliminary characterization of digestive enzymes in freshwater mussels: Journal of Shellfish Research, v. 34, no. 2, p. 415-422, https://doi.org/10.2983/035.034.0225.","productDescription":"8 p.","startPage":"415","endPage":"422","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061084","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":308311,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56011c74e4b03bc34f5443df","contributors":{"authors":[{"text":"Sauey, Blake W. bsauey@usgs.gov","contributorId":4748,"corporation":false,"usgs":true,"family":"Sauey","given":"Blake W.","email":"bsauey@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":572578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amberg, Jon J. jamberg@usgs.gov","contributorId":147776,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":572579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Scott T.","contributorId":147777,"corporation":false,"usgs":false,"family":"Cooper","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":16932,"text":"University of Wisconsin–La Crosse, Biology Department","active":true,"usgs":false}],"preferred":false,"id":572580,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grunwald, Sandra K.","contributorId":147778,"corporation":false,"usgs":false,"family":"Grunwald","given":"Sandra","email":"","middleInitial":"K.","affiliations":[{"id":16933,"text":"University of Wisconsin–La Crosse, Chemistry & Biochemistry Department","active":true,"usgs":false}],"preferred":false,"id":572581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newton, Teresa J. 0000-0001-9351-5852 tnewton@usgs.gov","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":2470,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa","email":"tnewton@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":572582,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":572583,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175782,"text":"70175782 - 2015 - Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution","interactions":[],"lastModifiedDate":"2016-08-19T10:31:38","indexId":"70175782","displayToPublicDate":"2015-09-18T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution","docAbstract":"

High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV <15%). Satellite imagery may be an effective monitoring tool in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

","language":"English","publisher":"Wiley","doi":"10.1002/wsb.596","usgsCitation":"LaRue, M.A., Stapleton, S.P., Porter, C., Atkinson, S.N., Atwood, T.C., Dyck, M., and Lecomte, N., 2015, Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution: Wildlife Society Bulletin, v. 39, no. 4, p. 772-779, https://doi.org/10.1002/wsb.596.","productDescription":"7 p.","startPage":"772","endPage":"779","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063293","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":500053,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/52601c9e182c489182032129672f748f","text":"External Repository"},{"id":326931,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Rowley Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.44238281249999,\n 69.21525256928653\n ],\n [\n -78.3544921875,\n 69.18404149599671\n ],\n [\n -78.2391357421875,\n 69.2425255645653\n ],\n [\n -78.1842041015625,\n 69.3086176331298\n ],\n [\n -78.1787109375,\n 69.35127582255352\n ],\n [\n -78.2830810546875,\n 69.3899830007604\n ],\n [\n -78.44238281249999,\n 69.39964894620636\n ],\n [\n -78.519287109375,\n 69.40931055535233\n ],\n [\n -78.64562988281249,\n 69.39191653683379\n ],\n [\n -78.7884521484375,\n 69.34740128319982\n ],\n [\n -78.717041015625,\n 69.29114227947211\n ],\n [\n -78.782958984375,\n 69.26976435077849\n ],\n [\n -78.8818359375,\n 69.20940390181205\n ],\n [\n -78.9312744140625,\n 69.15083065920365\n ],\n [\n -78.9422607421875,\n 69.12344255014861\n ],\n [\n -79.0411376953125,\n 69.13518451752405\n ],\n [\n -79.07958984375,\n 69.12148494192485\n ],\n [\n -79.21142578125,\n 69.12148494192485\n ],\n [\n -79.43115234375,\n 68.932736060549\n ],\n [\n -79.4146728515625,\n 68.83180177092166\n ],\n [\n -79.189453125,\n 68.81394200526994\n ],\n [\n -78.9093017578125,\n 68.87341871078524\n ],\n [\n -78.760986328125,\n 68.932736060549\n ],\n [\n -78.6016845703125,\n 69.03321086259241\n ],\n [\n -78.49731445312499,\n 69.08621799303475\n ],\n [\n -78.49731445312499,\n 69.12735724054714\n ],\n [\n -78.4259033203125,\n 69.17037257214531\n ],\n [\n -78.44238281249999,\n 69.21525256928653\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-18","publicationStatus":"PW","scienceBaseUri":"57b82dece4b03fd6b7da3a22","contributors":{"authors":[{"text":"LaRue, Michelle A.","contributorId":20634,"corporation":false,"usgs":true,"family":"LaRue","given":"Michelle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":646378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapleton, Seth P. sstapleton@usgs.gov","contributorId":3979,"corporation":false,"usgs":true,"family":"Stapleton","given":"Seth","email":"sstapleton@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":646379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Porter, Claire","contributorId":131120,"corporation":false,"usgs":false,"family":"Porter","given":"Claire","email":"","affiliations":[],"preferred":false,"id":646380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atkinson, Stephen N.","contributorId":12365,"corporation":false,"usgs":false,"family":"Atkinson","given":"Stephen","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":646381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":646343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dyck, Markus","contributorId":173868,"corporation":false,"usgs":false,"family":"Dyck","given":"Markus","affiliations":[],"preferred":false,"id":646382,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lecomte, Nicolas","contributorId":131119,"corporation":false,"usgs":false,"family":"Lecomte","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":646383,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157224,"text":"70157224 - 2015 - Age estimations of wild pallid sturgeon (Scaphirhynchus albus, Forbes & Richardson 1905) based on pectoral fin spines, otoliths and bomb radiocarbon: inferences on recruitment in the dam-fragmented Missouri River","interactions":[],"lastModifiedDate":"2015-09-17T11:04:44","indexId":"70157224","displayToPublicDate":"2015-09-17T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Age estimations of wild pallid sturgeon (Scaphirhynchus albus, Forbes & Richardson 1905) based on pectoral fin spines, otoliths and bomb radiocarbon: inferences on recruitment in the dam-fragmented Missouri River","docAbstract":"

An extant stock of wild pallid sturgeon Scaphirhynchus albus persists in the fragmented upper Missouri River basin of Montana and North Dakota. Although successful spawning and hatch of embryos has been verified, long-term catch records suggest that recruitment has not occurred for several decades as the extant stock lacks juvenile size classes and is comprised exclusively of large, presumably old individuals. Ages of 11 deceased (death years 1997–2007) wild S. albus (136–166 cm fork length) were estimated based on pectoral fin spines, sagittal otoliths and bomb radiocarbon (14C) assays of otoliths to test the hypothesis that members of this stock are old and to provide inferences on recruitment years that produced the extant stock. Age estimations based on counts of presumed annuli were about 2 years greater for otoliths (mean = 51 years, range = 43–57 years) than spines (mean = 49 years, range = 37–59 years). Based on 14C assays, confirmed birth years for all individuals occurred prior to 1957, thus establishing known longevity of at least 50 years. Estimated age based on presumed otolith annuli for one S. albus was validated to at least age 49. Although 14C assays confirmed pre-1957 birth years for all S. albus, only 56% of estimated ages from spines and 91% of estimated ages from otoliths depicted pre-1957 birth years. Both ageing structures were subject to under-ageing error (up to 15 years). Lack of or severe curtailment of S. albus recruitment in the upper Missouri River basin since the mid-1950s closely parallels the 1953–1957 timeframe when a mainstem reservoir was constructed and started to fill. This reservoir may function as a system-wide stressor to diminish recruitment success of S. albus in the upper Missouri River basin.

","language":"English","publisher":"Wiley","doi":"10.1111/jai.12873","collaboration":"Fisheries and Oceans Canada; Montana Fish, Wildlife and Parks; Wisconsin Department of Natural Resources; U. S. Fish and Wildlife Service","usgsCitation":"Braaten, P., Campana, S.E., Fuller, D.B., Lott, R.D., Bruch, R.M., and Jordan, G.R., 2015, Age estimations of wild pallid sturgeon (Scaphirhynchus albus, Forbes & Richardson 1905) based on pectoral fin spines, otoliths and bomb radiocarbon: inferences on recruitment in the dam-fragmented Missouri River: Journal of Applied Ichthyology, v. 31, no. 5, p. 821-829, https://doi.org/10.1111/jai.12873.","productDescription":"9 p.","startPage":"821","endPage":"829","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060218","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":471788,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.12873","text":"Publisher Index Page"},{"id":308241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Missouri River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.973876953125,\n 46.20264638061019\n ],\n [\n -106.973876953125,\n 48.180738507303836\n ],\n [\n -100.887451171875,\n 48.180738507303836\n ],\n [\n -100.887451171875,\n 46.20264638061019\n ],\n [\n -106.973876953125,\n 46.20264638061019\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-08","publicationStatus":"PW","scienceBaseUri":"55fbd636e4b05d6c4e5028c1","contributors":{"authors":[{"text":"Braaten, P. J. pbraaten@usgs.gov","contributorId":2724,"corporation":false,"usgs":true,"family":"Braaten","given":"P. J.","email":"pbraaten@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":572297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campana, S. E.","contributorId":147671,"corporation":false,"usgs":false,"family":"Campana","given":"S.","email":"","middleInitial":"E.","affiliations":[{"id":16891,"text":"Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada","active":true,"usgs":false}],"preferred":false,"id":572298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, D. B.","contributorId":58196,"corporation":false,"usgs":true,"family":"Fuller","given":"D.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":572299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lott, R. D.","contributorId":147672,"corporation":false,"usgs":false,"family":"Lott","given":"R.","email":"","middleInitial":"D.","affiliations":[{"id":16892,"text":"Montana Fish, Wildlife and Parks, Fort Peck, Montana","active":true,"usgs":false}],"preferred":false,"id":572300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bruch, R. M.","contributorId":147673,"corporation":false,"usgs":false,"family":"Bruch","given":"R.","email":"","middleInitial":"M.","affiliations":[{"id":16893,"text":"Wisconsin Department of Natural Resources, Oshkosh, Wisconsin","active":true,"usgs":false}],"preferred":false,"id":572301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jordan, G. R.","contributorId":147674,"corporation":false,"usgs":false,"family":"Jordan","given":"G.","email":"","middleInitial":"R.","affiliations":[{"id":16894,"text":"U. S. Fish and Wildlife Service, Billings, Montana","active":true,"usgs":false}],"preferred":false,"id":572302,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174883,"text":"70174883 - 2015 - Strongly-sheared wind-forced currents in the nearshore regions of the central Southern California Bight","interactions":[],"lastModifiedDate":"2016-10-11T16:42:54","indexId":"70174883","displayToPublicDate":"2015-09-15T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Strongly-sheared wind-forced currents in the nearshore regions of the central Southern California Bight","docAbstract":"

Contrary to many previous reports, winds do drive currents along the shelf in the central portion of the Southern California Bight (SCB). Winds off Huntington Beach CA are the dominant forcing for currents over the nearshore region of the shelf (water depths less than 20 m). Winds control about 50–70% of the energy in nearshore alongshelf surface currents. The wind-driven current amplitudes are also anomalously high. For a relatively weak 1 dyne/cm2 wind stress, the alongshelf surface current amplitudes in this region can reach 80 cm/s or more. Mid-depth current amplitudes for the same wind stress are around 30–40 cm/s. These wind-driven surface current amplitudes are much larger than previously measured over other nearshore shelf regions, perhaps because this program is one of the few that measured currents within a meter of the surface. The near-bed cross-shelf currents over the nearshore region of the Huntington Beach shelf have an Ekman response to winds in that they upwell (downwell) for down (up) coast winds. This response disappears further offshore. Hence, there is upwelling in the SCB, but it does not occur across the entire shelf. Subthermocline water in the nearshore region that may contain nutrients and plankton move onshore when winds are southeastward, but subthermocline water over the shelf break is not transported to the beach. The currents over the outer shelf are not predominately controlled by winds, consistent with previous reports. Instead, they are mainly driven by cross-shelf pressure gradients that are independent of local wind stress.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2015.04.019","usgsCitation":"Noble, M.A., Rosenberger, K.J., and Robertson, G.L., 2015, Strongly-sheared wind-forced currents in the nearshore regions of the central Southern California Bight: Continental Shelf Research, v. 106, p. 1-16, https://doi.org/10.1016/j.csr.2015.04.019.","productDescription":"16 p.","startPage":"1","endPage":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056503","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":325471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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thermal infrared imaging and Structure-from-Motion photogrametry to map apparent temperature and radiant hydrothermal heat flux at Mammoth Mountain, CA USA","docAbstract":"

This work presents a method to create high-resolution (cm-scale) orthorectified and georeferenced maps of apparent surface temperature and radiant hydrothermal heat flux and estimate the radiant hydrothermal heat emission rate from a study area. A ground-based thermal infrared (TIR) camera was used to collect (1) a set of overlapping and offset visible imagery around the study area during the daytime and (2) time series of co-located visible and TIR imagery at one or more sites within the study area from pre-dawn to daytime. Daytime visible imagery was processed using the Structure-from-Motion photogrammetric method to create a digital elevation model onto which pre-dawn TIR imagery was orthorectified and georeferenced. Three-dimensional maps of apparent surface temperature and radiant hydrothermal heat flux were then visualized and analyzed from various computer platforms (e.g., Google Earth, ArcGIS). We demonstrate this method at the Mammoth Mountain fumarole area on Mammoth Mountain, CA. Time-averaged apparent surface temperatures and radiant hydrothermal heat fluxes were observed up to 73.7 oC and 450 W m-2, respectively, while the estimated radiant hydrothermal heat emission rate from the area was 1.54 kW. Results should provide a basis for monitoring potential volcanic unrest and mitigating hydrothermal heat-related hazards on the volcano.

","language":"English","publisher":"ScienceDirect","usgsCitation":"Lewis, A., Hilley, G., and Lewicki, J.L., 2015, Integrated thermal infrared imaging and Structure-from-Motion photogrametry to map apparent temperature and radiant hydrothermal heat flux at Mammoth Mountain, CA USA: Journal of Volcanology and Geothermal Research, v. 303, p. 16-24.","productDescription":"7 p.","startPage":"16","endPage":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064910","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":308336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":308274,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.jvolgeores.2015.07.025"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.11582946777342,\n 37.60117623656667\n ],\n [\n -119.11582946777342,\n 37.69088430259205\n ],\n [\n -118.9441680908203,\n 37.69088430259205\n ],\n [\n -118.9441680908203,\n 37.60117623656667\n ],\n [\n -119.11582946777342,\n 37.60117623656667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"303","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56012a5de4b03bc34f544409","contributors":{"authors":[{"text":"Lewis, Aaron","contributorId":147792,"corporation":false,"usgs":false,"family":"Lewis","given":"Aaron","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":572669,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hilley, George","contributorId":147793,"corporation":false,"usgs":false,"family":"Hilley","given":"George","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":572670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":572668,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159606,"text":"70159606 - 2015 - Molecular tracing of confiscated pangolin scales for conservation and illegal trade monitoring in Southeast Asia","interactions":[],"lastModifiedDate":"2018-08-13T09:50:11","indexId":"70159606","displayToPublicDate":"2015-09-14T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Molecular tracing of confiscated pangolin scales for conservation and illegal trade monitoring in Southeast Asia","docAbstract":"

Despite being protected by both international and national regulations, pangolins are threatened by illegal trade. Here we report mitochondrial DNA identification and haplotype richness estimation, using 239 pangolin scale samples from two confiscations in Hong Kong. We found a total of 13 genetically distinct cytochrome c oxidase I (COI) haplotypes in two confiscations (13 and ten haplotypes respectively, with ten shared haplotypes between confiscations). These haplotypes clustered in two distinct clades with one clade representing the Sunda pangolin (Manisjavanica). The other clade did not match with any known Asian pangolin sequences, and likely represented a cryptic pangolin lineage in Asia. By fitting sample coverage and rarefaction/regression models to our sample data, we predicted that the total number of COI haplotypes in two confiscations were 14.86 and 11.06 respectively, suggesting that our sampling caught the majority of haplotypes and that we had adequately characterized each confiscation. We detected substantial sequence divergence among the seized scales, likely evidencing that the Sunda pangolins were harvested over wide geographical areas across Southeast Asia. Our study illustrates the value of applying DNA forensics for illegal wildlife trade monitoring.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2015.08.002","usgsCitation":"Zhang, H., Miller, M.P., Yang, F., Chan, K., Gaubert, P., Ades, G., and Fischer, G.A., 2015, Molecular tracing of confiscated pangolin scales for conservation and illegal trade monitoring in Southeast Asia: Global Ecology and Conservation, v. 4, p. 414-422, https://doi.org/10.1016/j.gecco.2015.08.002.","productDescription":"9 p.","startPage":"414","endPage":"422","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066335","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2015.08.002","text":"Publisher Index 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Hong Kong SAR","active":true,"usgs":false}],"preferred":false,"id":579692,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fischer, Gunter A.","contributorId":149822,"corporation":false,"usgs":false,"family":"Fischer","given":"Gunter","email":"","middleInitial":"A.","affiliations":[{"id":17833,"text":"Kadoorie Farm and Botanic Garden, Lam Kam Road, Tai Po, N.T. Hong Kong SAR","active":true,"usgs":false}],"preferred":false,"id":579693,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157154,"text":"70157154 - 2015 - Challenges of establishing big sgebrush (Artemisia tridentata) in rangeland restoration: effects of herbicide, mowing, whole-community seeding, and sagebrush seed sources","interactions":[],"lastModifiedDate":"2017-11-22T17:49:16","indexId":"70157154","displayToPublicDate":"2015-09-10T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Challenges of establishing big sgebrush (Artemisia tridentata) in rangeland restoration: effects of herbicide, mowing, whole-community seeding, and sagebrush seed sources","docAbstract":"

The loss of big sagebrush (Artemisia tridentata Nutt.) on sites disturbed by fire has motivated restoration seeding and planting efforts. However, the resulting sagebrush establishment is often lower than desired, especially in dry areas. Sagebrush establishment may be increased by addressing factors such as seed source and condition or management of the plant community. We assessed initial establishment of seeded sagebrush and four populations of small outplants (from different geographies, climates, and cytotypes) and small sagebrush outplants in an early seral community where mowing, herbicide, and seeding of other native plants had been experimentally applied. No emergence of seeded sagebrush was detected. Mowing the site before planting seedlings led to greater initial survival probabilities for sagebrush outplants, except where seeding also occurred, and these effects were related to corresponding changes in bare soil exposure. Initial survival probabilities were > 30% greater for the local population of big sagebrush relative to populations imported to the site from typical seed transfer distances of ~320–800 km. Overcoming the high first-year mortality of outplanted or seeded sagebrush is one of the most challenging aspects of postfire restoration and rehabilitation, and further evaluation of the impacts of herb treatments and sagebrush seed sources across different site types and years is needed.

","language":"English","publisher":"Science Direct","doi":"10.1016/j.rama.2015.07.001","usgsCitation":"Brabec, M., Germino, M., Shinneman, D.J., Pilliod, D., McIlroy, S.K., and Arkle, R., 2015, Challenges of establishing big sgebrush (Artemisia tridentata) in rangeland restoration: effects of herbicide, mowing, whole-community seeding, and sagebrush seed sources: Rangeland Ecology and Management, v. 68, no. 5, p. 432-435, https://doi.org/10.1016/j.rama.2015.07.001.","productDescription":"4 p.","startPage":"432","endPage":"435","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060370","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":308052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":308034,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S1550742415000950"}],"volume":"68","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55f29ba7e4b0dacf699ec691","contributors":{"authors":[{"text":"Brabec, Martha M. mbrabec@usgs.gov","contributorId":147542,"corporation":false,"usgs":true,"family":"Brabec","given":"Martha M.","email":"mbrabec@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":571972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. mgermino@usgs.gov","contributorId":146934,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":571971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147059,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":571973,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":147050,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":571974,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIlroy, Susan K. 0000-0001-5088-3700 smcilroy@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3700","contributorId":4649,"corporation":false,"usgs":true,"family":"McIlroy","given":"Susan","email":"smcilroy@usgs.gov","middleInitial":"K.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":571975,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arkle, Robert S. 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":147051,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert S.","email":"rarkle@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":571976,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155252,"text":"70155252 - 2015 - Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa","interactions":[],"lastModifiedDate":"2017-05-16T16:17:28","indexId":"70155252","displayToPublicDate":"2015-09-09T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1841,"text":"Global Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa","docAbstract":"

This paper examined the relationship between birth weight, precipitation, and temperature in 19 African countries. We matched recorded birth weights from Demographic and Health Surveys covering 1986 through 2010 with gridded monthly precipitation and temperature data derived from satellite and ground-based weather stations. Observed weather patterns during various stages of pregnancy were also used to examine the effect of temperature and precipitation on birth weight outcomes. In our empirical model we allowed the effect of weather factors to vary by the dominant food production strategy (livelihood zone) in a given region as well as by household wealth, mother's education and birth season. This allowed us to determine if certain populations are more or less vulnerable to unexpected weather changes after adjusting for known covariates. Finally we measured effect size by observing differences in birth weight outcomes in women who have one low birth weight experience and at least one healthy birth weight baby. The results indicated that climate does indeed impact birth weight and at a level comparable, in some cases, to the impact of increasing women's education or household electricity status.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloenvcha.2015.06.010","usgsCitation":"Grace, K., Davenport, F., Hanson, H., Funk, C.C., and Shukla, S., 2015, Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa: Global Environmental Change, v. 35, p. 125-137, https://doi.org/10.1016/j.gloenvcha.2015.06.010.","productDescription":"13 p.","startPage":"125","endPage":"137","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064651","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":310208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -19.072265625,\n -32.990235559651055\n ],\n [\n -19.072265625,\n 29.53522956294847\n ],\n [\n 55.8984375,\n 29.53522956294847\n ],\n [\n 55.8984375,\n -32.990235559651055\n ],\n [\n -19.072265625,\n -32.990235559651055\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5628b730e4b0d158f5926c17","contributors":{"authors":[{"text":"Grace, Kathryn","contributorId":145815,"corporation":false,"usgs":false,"family":"Grace","given":"Kathryn","email":"","affiliations":[{"id":7215,"text":"University of Utah Dept. of Geography","active":true,"usgs":false}],"preferred":false,"id":565375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davenport, Frank","contributorId":145816,"corporation":false,"usgs":false,"family":"Davenport","given":"Frank","email":"","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":565376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanson, Heidi","contributorId":149327,"corporation":false,"usgs":false,"family":"Hanson","given":"Heidi","email":"","affiliations":[],"preferred":false,"id":577984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565374,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shukla, Shraddhanand","contributorId":140735,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","email":"","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565377,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157080,"text":"70157080 - 2015 - The Palos Verdes Fault offshore southern California: late Pleistocene to present tectonic geomorphology, seascape evolution and slip rate estimate based on AUV and ROV surveys","interactions":[],"lastModifiedDate":"2015-09-08T13:34:42","indexId":"70157080","displayToPublicDate":"2015-09-08T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The Palos Verdes Fault offshore southern California: late Pleistocene to present tectonic geomorphology, seascape evolution and slip rate estimate based on AUV and ROV surveys","docAbstract":"

The Palos Verdes Fault (PVF) is one of few active faults in Southern California that crosses the shoreline and can be studied using both terrestrial and subaqueous methodologies. To characterize the near-seafloor fault morphology, tectonic influences on continental slope sedimentary processes and late Pleistocene to present slip rate, a grid of high-resolution multibeam bathymetric data, and chirp subbottom profiles were acquired with an autonomous underwater vehicle (AUV) along the main trace of PVF in water depths between 250 and 600 m. Radiocarbon dates were obtained from vibracores collected using a remotely operated vehicle (ROV) and ship-based gravity cores. The PVF is expressed as a well-defined seafloor lineation marked by subtle along-strike bends. Right-stepping transtensional bends exert first-order control on sediment flow dynamics and the spatial distribution of Holocene depocenters; deformed strata within a small pull-apart basin record punctuated growth faulting associated with at least three Holocene surface ruptures. An upper (shallower) landslide scarp, a buried sedimentary mound, and a deeper scarp have been right-laterally offset across the PVF by 55 ± 5, 52 ± 4 , and 39 ± 8 m, respectively. The ages of the upper scarp and buried mound are approximately 31 ka; the age of the deeper scarp is bracketed to 17–24 ka. These three piercing points bracket the late Pleistocene to present slip rate to 1.3–2.8 mm/yr and provide a best estimate of 1.6–1.9 mm/yr. The deformation observed along the PVF is characteristic of strike-slip faulting and accounts for 20–30% of the total right-lateral slip budget accommodated offshore Southern California.

","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB011938","usgsCitation":"Brothers, D., Conrad, J.E., Maier, K., Paull, C.K., McGann, M., and Caress, D.W., 2015, The Palos Verdes Fault offshore southern California: late Pleistocene to present tectonic geomorphology, seascape evolution and slip rate estimate based on AUV and ROV surveys: Journal of Geophysical Research B: Solid Earth, v. 120, no. 7, p. 4734-4758, https://doi.org/10.1002/2015JB011938.","productDescription":"25 p.","startPage":"4734","endPage":"4758","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063656","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palos Verdes Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.39691162109375,\n 33.30987251398259\n ],\n [\n -118.39691162109375,\n 33.8430453147447\n ],\n [\n -117.75421142578125,\n 33.8430453147447\n ],\n [\n -117.75421142578125,\n 33.30987251398259\n ],\n [\n -118.39691162109375,\n 33.30987251398259\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-30","publicationStatus":"PW","scienceBaseUri":"55eff8a9e4b0dacf699e9fe2","chorus":{"doi":"10.1002/2015jb011938","url":"http://dx.doi.org/10.1002/2015jb011938","publisher":"Wiley-Blackwell","authors":"Brothers Daniel S., Conrad James E., Maier Katherine L., Paull Charles K., McGann Mary, Caress David W.","journalName":"Journal of Geophysical Research: Solid Earth","publicationDate":"7/2015"},"contributors":{"authors":[{"text":"Brothers, Daniel S. dbrothers@usgs.gov","contributorId":140096,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","email":"dbrothers@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":571527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":571528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":571529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":571530,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGann, Mary L. 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":147188,"corporation":false,"usgs":true,"family":"McGann","given":"Mary L.","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":571531,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caress, David W.","contributorId":147392,"corporation":false,"usgs":false,"family":"Caress","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":571532,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157010,"text":"70157010 - 2015 - Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development","interactions":[],"lastModifiedDate":"2015-09-03T13:01:44","indexId":"70157010","displayToPublicDate":"2015-09-03T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development","docAbstract":"

Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus), a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs) from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn—the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as ‘risk from turbines is highest in habitats between hoary bat summering and wintering grounds’. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.

","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0132599","collaboration":"Prepared in collaboration with University of Colorado Denver","usgsCitation":"Hayes, M.A., Cryan, P.M., and Wunder, M., 2015, Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development: PLoS ONE, v. 10, no. 7, e0132599; 20 p., https://doi.org/10.1371/journal.pone.0132599.","productDescription":"e0132599; 20 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1950-01-01","temporalEnd":"2000-12-31","ipdsId":"IP-066454","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0132599","text":"Publisher Index 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PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-24","publicationStatus":"PW","scienceBaseUri":"55e96127e4b0dacf699e785e","contributors":{"authors":[{"text":"Hayes, Mark A. hayesm@usgs.gov","contributorId":147339,"corporation":false,"usgs":true,"family":"Hayes","given":"Mark","email":"hayesm@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":571312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":571311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wunder, Michael B.","contributorId":80599,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":571313,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157006,"text":"70157006 - 2015 - Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?","interactions":[],"lastModifiedDate":"2015-09-03T13:09:46","indexId":"70157006","displayToPublicDate":"2015-09-03T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":629,"text":"Acta Chiropterologica","active":true,"publicationSubtype":{"id":10}},"title":"Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?","docAbstract":"

Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.

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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e96126e4b0dacf699e785b","contributors":{"authors":[{"text":"Hayes, Mark A. hayesm@usgs.gov","contributorId":147339,"corporation":false,"usgs":true,"family":"Hayes","given":"Mark","email":"hayesm@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":571308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ozenberger, Katharine","contributorId":147340,"corporation":false,"usgs":false,"family":"Ozenberger","given":"Katharine","email":"","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":571309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":571307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wunder, Michael B.","contributorId":80599,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":571310,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156871,"text":"70156871 - 2015 - Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA","interactions":[],"lastModifiedDate":"2015-09-02T09:00:25","indexId":"70156871","displayToPublicDate":"2015-09-02T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA","docAbstract":"

Understanding the efficacy of revised watershed management methods is important to mitigating the impacts of urbanization on streamflow. We evaluated the influence of land use change, primarily as urbanization, and stormwater control measures on the relationship between precipitation and stream discharge over an 8-year period for five catchments near Clarksburg, Montgomery County, Maryland, USA. A unit-hydrograph model based on a temporal transfer function was employed to account for and standardize temporal variation in rainfall pattern, and properly apportion rainfall to streamflow at different time lags. From these lagged relationships, we quantified a correction to the precipitation time series to achieve a hydrograph that showed good agreement between precipitation and discharge records. Positive corrections appeared to include precipitation events that were of limited areal extent and therefore not captured by our rain gages. Negative corrections were analysed for potential causal relationships. We used mixed-model statistical techniques to isolate different sources of variance as drivers that mediate the rainfall–runoff dynamic before and after management. Seasonal periodicity mediated rainfall–runoff relationships, and land uses (i.e. agriculture, natural lands, wetlands and stormwater control measures) were statistically significant predictors of precipitation apportionment to stream discharge. Our approach is one way to evaluate actual effectiveness of management efforts in the face of complicating circumstances and could be paired with cost data to understand economic efficiency or life cycle aspects of watershed management. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10505","usgsCitation":"Rhea, L., Jarnagin, T., Hogan, D.M., Loperfido, J., and Shuster, W., 2015, Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA: Hydrological Processes, v. 29, no. 20, p. 4413-4426, https://doi.org/10.1002/hyp.10505.","productDescription":"14 p.","startPage":"4413","endPage":"4426","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1998-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-053400","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":307802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Montgomery County","otherGeospatial":"Clarksburg","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.32315063476562,\n 39.17771552084858\n ],\n [\n -77.32315063476562,\n 39.32101883236063\n ],\n [\n -77.16865539550781,\n 39.32101883236063\n ],\n [\n -77.16865539550781,\n 39.17771552084858\n ],\n [\n -77.32315063476562,\n 39.17771552084858\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"20","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-11","publicationStatus":"PW","scienceBaseUri":"55e80f98e4b0dacf699e663a","chorus":{"doi":"10.1002/hyp.10505","url":"http://dx.doi.org/10.1002/hyp.10505","publisher":"Wiley-Blackwell","authors":"Rhea Lee, Jarnagin Taylor, Hogan Dianna, Loperfido J. V., Shuster William","journalName":"Hydrological Processes","publicationDate":"5/11/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Rhea, Lee","contributorId":147260,"corporation":false,"usgs":false,"family":"Rhea","given":"Lee","affiliations":[{"id":16813,"text":"Sustainable Environments Branch, National Risk Management Research Laboratory, Office of Research and Development, EPA","active":true,"usgs":false}],"preferred":false,"id":570900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnagin, Taylor","contributorId":131140,"corporation":false,"usgs":false,"family":"Jarnagin","given":"Taylor","email":"","affiliations":[{"id":7258,"text":"Landscape Ecology Branch, U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":570901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hogan, Dianna M. 0000-0003-1492-4514 dhogan@usgs.gov","orcid":"https://orcid.org/0000-0003-1492-4514","contributorId":131137,"corporation":false,"usgs":true,"family":"Hogan","given":"Dianna","email":"dhogan@usgs.gov","middleInitial":"M.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":570899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loperfido, J. V. jloperfido@usgs.gov","contributorId":131139,"corporation":false,"usgs":true,"family":"Loperfido","given":"J. V.","email":"jloperfido@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":570902,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shuster, William","contributorId":147261,"corporation":false,"usgs":false,"family":"Shuster","given":"William","affiliations":[{"id":16813,"text":"Sustainable Environments Branch, National Risk Management Research Laboratory, Office of Research and Development, EPA","active":true,"usgs":false}],"preferred":false,"id":570903,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159739,"text":"70159739 - 2015 - Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus","interactions":[],"lastModifiedDate":"2021-09-01T16:05:43.950398","indexId":"70159739","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus","title":"Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus","docAbstract":"

Islands provide refuges for populations of many species where they find safety from predators, but the introduction of predators frequently results in elimination or dramatic reductions in island-dwelling organisms. When predators are removed, re-colonization for some species occurs naturally, and inter-island phylogeographic relationships and current movement patterns can illuminate processes of colonization. We studied a case of re-colonization of common eiders Somateria mollissima following removal of introduced arctic foxes Vulpes lagopus in the Aleutian Archipelago, Alaska. We expected common eiders to resume nesting on islands cleared of foxes and to re-colonize from nearby islets, islands, and island groups. We thus expected common eiders to show limited genetic structure indicative of extensive mixing among island populations. Satellite telemetry was used to record current movement patterns of female common eiders from six islands across three island groups. We collected genetic data from these and other nesting common eiders at 14 microsatellite loci and the mitochondrial DNA control region to examine population genetic structure, historical fluctuations in population demography, and gene flow. Our results suggest recent interchange among islands. Analysis of microsatellite data supports satellite telemetry data of increased dispersal of common eiders to nearby areas and little between island groups. Although evidence from mtDNA is suggestive of female dispersal among island groups, gene flow is insufficient to account for recolonization and rapid population growth. Instead, near-by remnant populations of common eiders contributed substantially to population expansion, without which re-colonization would have likely occurred at a much lower rate. Genetic and morphometric data of common eiders within one island group two and three decades after re-colonization suggests reduced movement of eiders among islands and little movement between island groups after populations were re-established. We predict that re-colonization of an island group where all common eiders are extirpated could take decades.

","language":"English","publisher":"Wiley","doi":"10.1111/jav.00626","usgsCitation":"Petersen, M.R., Sonsthagen, S.A., and Sexson, M.G., 2015, Re-colonization by common eiders Somateria mollissima in the Aleutian Archipelago following removal of introduced arctic foxes Vulpes lagopus: Journal of Avian Biology, v. 46, no. 5, p. 538-549, https://doi.org/10.1111/jav.00626.","productDescription":"12 p.","startPage":"538","endPage":"549","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054807","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":311558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Andreanof Islands, Near Islands, Rat Islands,","volume":"46","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-12","publicationStatus":"PW","scienceBaseUri":"564f00c9e4b064dd1d09558c","contributors":{"authors":[{"text":"Petersen, Margaret R. 0000-0001-6082-3189 mrpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-6082-3189","contributorId":167729,"corporation":false,"usgs":true,"family":"Petersen","given":"Margaret","email":"mrpetersen@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":580290,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":580291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sexson, Matthew G. 0000-0002-1078-0835 msexson@usgs.gov","orcid":"https://orcid.org/0000-0002-1078-0835","contributorId":5544,"corporation":false,"usgs":true,"family":"Sexson","given":"Matthew","email":"msexson@usgs.gov","middleInitial":"G.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":580292,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169237,"text":"70169237 - 2015 - Rising methane emissions from northern wetlands associated with sea ice decline","interactions":[],"lastModifiedDate":"2016-03-24T11:47:51","indexId":"70169237","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Rising methane emissions from northern wetlands associated with sea ice decline","docAbstract":"

The Arctic is rapidly transitioning toward a seasonal sea ice-free state, perhaps one of the most apparent examples of climate change in the world. This dramatic change has numerous consequences, including a large increase in air temperatures, which in turn may affect terrestrial methane emissions. Nonetheless, terrestrial and marine environments are seldom jointly analyzed. By comparing satellite observations of Arctic sea ice concentrations to methane emissions simulated by three process-based biogeochemical models, this study shows that rising wetland methane emissions are associated with sea ice retreat. Our analyses indicate that simulated high-latitude emissions for 2005–2010 were, on average, 1.7 Tg CH4 yr−1 higher compared to 1981–1990 due to a sea ice-induced, autumn-focused, warming. Since these results suggest a continued rise in methane emissions with future sea ice decline, observation programs need to include measurements during the autumn to further investigate the impact of this spatial connection on terrestrial methane emissions.

","language":"English","publisher":"Wiley","doi":"10.1002/2015GL065013","usgsCitation":"Parmentier, F.W., Zhang, W., Zhu, X., van Huissteden, J., Hayes, D.J., Zhuang, Q., Christensen, T.R., and McGuire, A.D., 2015, Rising methane emissions from northern wetlands associated with sea ice decline: Geophysical Research Letters, v. 42, no. 17, p. 7214-7222, https://doi.org/10.1002/2015GL065013.","productDescription":"9 p.","startPage":"7214","endPage":"7222","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063606","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl065013","text":"Publisher Index Page"},{"id":319362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"17","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-10","publicationStatus":"PW","scienceBaseUri":"56f50fd1e4b0f59b85e1eba4","contributors":{"authors":[{"text":"Parmentier, Frans-Jan W.","contributorId":60537,"corporation":false,"usgs":true,"family":"Parmentier","given":"Frans-Jan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":623638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Wenxin","contributorId":167815,"corporation":false,"usgs":false,"family":"Zhang","given":"Wenxin","email":"","affiliations":[],"preferred":false,"id":623639,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Xudong","contributorId":19684,"corporation":false,"usgs":true,"family":"Zhu","given":"Xudong","email":"","affiliations":[],"preferred":false,"id":623640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Huissteden, Jacobus","contributorId":167816,"corporation":false,"usgs":false,"family":"van Huissteden","given":"Jacobus","email":"","affiliations":[],"preferred":false,"id":623641,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":623642,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhuang, Qianlai","contributorId":101975,"corporation":false,"usgs":true,"family":"Zhuang","given":"Qianlai","affiliations":[],"preferred":false,"id":623643,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christensen, Torben R.","contributorId":11946,"corporation":false,"usgs":true,"family":"Christensen","given":"Torben","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":623644,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":623375,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70168977,"text":"70168977 - 2015 - Sediment yields from small, steep coastal watersheds of California","interactions":[],"lastModifiedDate":"2016-03-10T09:35:29","indexId":"70168977","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Sediment yields from small, steep coastal watersheds of California","docAbstract":"

Global inventories of sediment discharge to the ocean highlight the importance of small, steep watersheds (i.e., those having drainage areas less than 100,000 km2 and over 1000 m of relief) that collectively provide a dominant flux of sediment. The smallest of these coastal watersheds (e.g., those that have drainage areas less than 1000 km2) can represent a large portion of the drainage areas of active margin coasts, such as California’s coast, but remain almost universally unmonitored. Here we report on the suspended-sediment discharge of several small coastal watersheds (10-56 km2) of the Santa Ynez Mountains, California, that were found to have ephemeral discharge and suspended-sediment concentrations ranging between 1 and over 200,000 mgL-1. Sediment concentrations were weakly correlated with discharge (r2 = 0.10–0.25), and all types of hysteresis patterns were observed during high flows (clockwise, counterclockwise, no hysteresis, and complex). Sediment discharge varied strongly with time and was measurably elevated in one watershed following a wildfire. Although sediment yields varied by over 100-fold across the watersheds (e.g., 15 – 2100 tkm-2 yr -1during the relatively wet 2005 water year), the majority of sediment discharge (65-80%) occurred during only 1% of the time for all watersheds. Furthermore, sampling of dozens of high flow events provides evidence that sediment yields were generally related to peak discharge yields, although these relationships were not consistent across the watersheds. These results suggest that small watersheds of active margins can provide large fluxes of sediment to the coast, but that the rates and timing of this sediment discharge is more irregular in time – and thus more difficult to characterize – than the better monitored and studied watersheds that are 1000-100,000 km2.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2015.08.004","usgsCitation":"Warrick, J., Melack, J.M., and Goodridge, B.M., 2015, Sediment yields from small, steep coastal watersheds of California: Journal of Hydrology: Regional Studies, v. 4, no. Part B, p. 516-534, https://doi.org/10.1016/j.ejrh.2015.08.004.","productDescription":"19 p.","startPage":"516","endPage":"534","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052345","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2015.08.004","text":"Publisher Index Page"},{"id":318770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.69305419921874,\n 33.831638461142866\n ],\n [\n -120.69305419921874,\n 34.69194468425019\n ],\n [\n -118.50952148437499,\n 34.69194468425019\n ],\n [\n -118.50952148437499,\n 33.831638461142866\n ],\n [\n -120.69305419921874,\n 33.831638461142866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"Part B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56e2a8cce4b0f59b85d391b0","contributors":{"authors":[{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":146720,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan A.","email":"jwarrick@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":622424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melack, John M.","contributorId":167466,"corporation":false,"usgs":false,"family":"Melack","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":24713,"text":"Bren School of Environmental Science and Management, University of California, Santa Barbara, California, USA","active":true,"usgs":false}],"preferred":false,"id":622425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodridge, Blair M.","contributorId":167467,"corporation":false,"usgs":false,"family":"Goodridge","given":"Blair","email":"","middleInitial":"M.","affiliations":[{"id":24713,"text":"Bren School of Environmental Science and Management, University of California, Santa Barbara, California, USA","active":true,"usgs":false}],"preferred":false,"id":622426,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173404,"text":"70173404 - 2015 - A critical assessment of the ecological assumptions underpinning compensatory mitigation of salmon-derived nutrients","interactions":[],"lastModifiedDate":"2016-06-22T13:48:33","indexId":"70173404","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"A critical assessment of the ecological assumptions underpinning compensatory mitigation of salmon-derived nutrients","docAbstract":"

We critically evaluate some of the key ecological assumptions underpinning the use of nutrient replacement as a means of recovering salmon populations and a range of other organisms thought to be linked to productive salmon runs. These assumptions include: (1) nutrient mitigation mimics the ecological roles of salmon, (2) mitigation is needed to replace salmon-derived nutrients and stimulate primary and invertebrate production in streams, and (3) food resources in rearing habitats limit populations of salmon and resident fishes. First, we call into question assumption one because an array of evidence points to the multi-faceted role played by spawning salmon, including disturbance via redd-building, nutrient recycling by live fish, and consumption by terrestrial consumers. Second, we show that assumption two may require qualification based upon a more complete understanding of nutrient cycling and productivity in streams. Third, we evaluate the empirical evidence supporting food limitation of fish populations and conclude it has been only weakly tested. On the basis of this assessment, we urge caution in the application of nutrient mitigation as a management tool. Although applications of nutrients and other materials intended to mitigate for lost or diminished runs of Pacific salmon may trigger ecological responses within treated ecosystems, contributions of these activities toward actual mitigation may be limited.

","language":"English","publisher":"Springer","doi":"10.1007/s00267-015-0538-5","usgsCitation":"Collins, S.F., Marcarelli, A.M., Baxter, C.V., and Wipfli, M.S., 2015, A critical assessment of the ecological assumptions underpinning compensatory mitigation of salmon-derived nutrients: Environmental Management, v. 56, no. 3, p. 571-586, https://doi.org/10.1007/s00267-015-0538-5.","productDescription":"16 p.","startPage":"571","endPage":"586","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065573","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471823,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.idahoafs.org/documents/2012AnnualMeeting.pdf","text":"External Repository"},{"id":324229,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-13","publicationStatus":"PW","scienceBaseUri":"576bb6ade4b07657d1a2284d","contributors":{"authors":[{"text":"Collins, Scott F.","contributorId":172292,"corporation":false,"usgs":false,"family":"Collins","given":"Scott","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":640366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marcarelli, Amy M.","contributorId":81821,"corporation":false,"usgs":true,"family":"Marcarelli","given":"Amy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baxter, Colden V.","contributorId":172293,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":640368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637088,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173609,"text":"70173609 - 2015 - Linking resource selection and mortality modeling for population estimation of mountain lions in Montana","interactions":[],"lastModifiedDate":"2016-06-22T14:34:22","indexId":"70173609","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Linking resource selection and mortality modeling for population estimation of mountain lions in Montana","docAbstract":"

To be most effective, the scale of wildlife management practices should match the range of a particular species’ movements. For this reason, combined with our inability to rigorously or regularly census mountain lion populations, several authors have suggested that mountain lions be managed in a source-sink or metapopulation framework. We used a combination of resource selection functions, mortality estimation, and dispersal modeling to estimate cougar population levels in Montana statewide and potential population level effects of planned harvest levels. Between 1980 and 2012, 236 independent mountain lions were collared and monitored for research in Montana. From these data we used 18,695 GPS locations collected during winter from 85 animals to develop a resource selection function (RSF), and 11,726 VHF and GPS locations from 142 animals along with the locations of 6343 mountain lions harvested from 1988–2011 to validate the RSF model. Our RSF model validated well in all portions of the State, although it appeared to perform better in Montana Fish, Wildlife and Parks (MFWP) Regions 1, 2, 4 and 6, than in Regions 3, 5, and 7. Our mean RSF based population estimate for the total population (kittens, juveniles, and adults) of mountain lions in Montana in 2005 was 3926, with almost 25% of the entire population in MFWP Region 1. Estimates based on a high and low reference population estimates produce a possible range of 2784 to 5156 mountain lions statewide. Based on a range of possible survival rates we estimated the mountain lion population in Montana to be stable to slightly increasing between 2005 and 2010 with lambda ranging from 0.999 (SD = 0.05) to 1.02 (SD = 0.03). We believe these population growth rates to be a conservative estimate of true population growth. Our model suggests that proposed changes to female harvest quotas for 2013–2015 will result in an annual statewide population decline of 3% and shows that, due to reduced dispersal, changes to harvest in one management unit may affect population growth in neighboring units where smaller or even no changes were made. Uncertainty regarding dispersal levels and initial population density may have a significant effect on predictions at a management unit scale (i.e. 2000 km2), while at a regional scale (i.e. 50,000 km2) large differences in initial population density result in relatively small changes in population growth rate, and uncertainty about dispersal may not be as influential. Doubling the presumed initial density from a low estimation of 2.19 total animals per 100 km2 resulted in a difference in annual population growth rate of only 2.6% statewide when compared to high density of 4.04 total animals per 100 km2 (low initial population estimate λ = 0.99, while high initial population estimate λ = 1.03). We suggest modeling tools such as this may be useful in harvest planning at a regional and statewide level.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2015.05.013","usgsCitation":"Robinson, H.S., Ruth, T.K., Gude, J., Choate, D., DeSimone, R., Hebblewhite, M., Matchett, M.R., Mitchell, M.S., Murphy, K., and Williams, J., 2015, Linking resource selection and mortality modeling for population estimation of mountain lions in Montana: Ecological Modelling, v. 312, p. 11-25, https://doi.org/10.1016/j.ecolmodel.2015.05.013.","productDescription":"15 p.","startPage":"11","endPage":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057281","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"312","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576bb6b7e4b07657d1a228f1","contributors":{"authors":[{"text":"Robinson, Hugh S.","contributorId":139243,"corporation":false,"usgs":false,"family":"Robinson","given":"Hugh","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":640394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruth, Toni K.","contributorId":43657,"corporation":false,"usgs":true,"family":"Ruth","given":"Toni","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":640395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":640396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Choate, David","contributorId":172339,"corporation":false,"usgs":false,"family":"Choate","given":"David","affiliations":[],"preferred":false,"id":640397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeSimone, Rich","contributorId":99451,"corporation":false,"usgs":true,"family":"DeSimone","given":"Rich","email":"","affiliations":[],"preferred":false,"id":640398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hebblewhite, Mark","contributorId":69455,"corporation":false,"usgs":true,"family":"Hebblewhite","given":"Mark","affiliations":[],"preferred":false,"id":640399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matchett, Marc R.","contributorId":35581,"corporation":false,"usgs":true,"family":"Matchett","given":"Marc","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":640400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637398,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Murphy, Kerry","contributorId":172340,"corporation":false,"usgs":false,"family":"Murphy","given":"Kerry","affiliations":[],"preferred":false,"id":640401,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williams, Jim","contributorId":172341,"corporation":false,"usgs":false,"family":"Williams","given":"Jim","email":"","affiliations":[],"preferred":false,"id":640402,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70188145,"text":"70188145 - 2015 - Modelling multi-hazard hurricane damages on an urbanized coast with a Bayesian Network approach","interactions":[],"lastModifiedDate":"2017-06-01T12:52:37","indexId":"70188145","displayToPublicDate":"2015-09-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Modelling multi-hazard hurricane damages on an urbanized coast with a Bayesian Network approach","docAbstract":"

Hurricane flood impacts to residential buildings in coastal zones are caused by a number of hazards, such as inundation, overflow currents, erosion, and wave attack. However, traditional hurricane damage models typically make use of stage-damage functions, where the stage is related to flooding depth only. Moreover, these models are deterministic and do not consider the large amount of uncertainty associated with both the processes themselves and with the predictions. This uncertainty becomes increasingly important when multiple hazards (flooding, wave attack, erosion, etc.) are considered simultaneously. This paper focusses on establishing relationships between observed damage and multiple hazard indicators in order to make better probabilistic predictions. The concept consists of (1) determining Local Hazard Indicators (LHIs) from a hindcasted storm with use of a nearshore morphodynamic model, XBeach, and (2) coupling these LHIs and building characteristics to the observed damages. We chose a Bayesian Network approach in order to make this coupling and used the LHIs ‘Inundation depth’, ‘Flow velocity’, ‘Wave attack’, and ‘Scour depth’ to represent flooding, current, wave impacts, and erosion related hazards.

The coupled hazard model was tested against four thousand damage observations from a case site at the Rockaway Peninsula, NY, that was impacted by Hurricane Sandy in late October, 2012. The model was able to accurately distinguish ‘Minor damage’ from all other outcomes 95% of the time and could distinguish areas that were affected by the storm, but not severely damaged, 68% of the time. For the most heavily damaged buildings (‘Major Damage’ and ‘Destroyed’), projections of the expected damage underestimated the observed damage. The model demonstrated that including multiple hazards doubled the prediction skill, with Log-Likelihood Ratio test (a measure of improved accuracy and reduction in uncertainty) scores between 0.02 and 0.17 when only one hazard is considered and a score of 0.37 when multiple hazards are considered simultaneously. The LHIs with the most predictive skill were ‘Inundation depth’ and ‘Wave attack’. The Bayesian Network approach has several advantages over the market-standard stage-damage functions: the predictive capacity of multiple indicators can be combined; probabilistic predictions can be obtained, which include uncertainty; and quantitative as well as descriptive information can be used simultaneously.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2015.05.006","usgsCitation":"van Verseveld, H., Van Dongeren, A., Plant, N.G., Jager, W., and den Heijer, C., 2015, Modelling multi-hazard hurricane damages on an urbanized coast with a Bayesian Network approach: Coastal Engineering, v. 103, p. 1-14, https://doi.org/10.1016/j.coastaleng.2015.05.006.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-083654","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":342005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593127b0e4b0e9bd0ea9ef12","contributors":{"authors":[{"text":"van Verseveld, H.C.W.","contributorId":192572,"corporation":false,"usgs":false,"family":"van Verseveld","given":"H.C.W.","email":"","affiliations":[],"preferred":false,"id":696882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Dongeren, A. R.","contributorId":55572,"corporation":false,"usgs":true,"family":"Van Dongeren","given":"A. R.","affiliations":[],"preferred":false,"id":696883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":696881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jager, W.S.","contributorId":192574,"corporation":false,"usgs":false,"family":"Jager","given":"W.S.","email":"","affiliations":[],"preferred":false,"id":696884,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"den Heijer, C.","contributorId":192575,"corporation":false,"usgs":false,"family":"den Heijer","given":"C.","affiliations":[],"preferred":false,"id":696885,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}